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Ubiquitin researchers win Nobel

Larry H. Bernstein, MD, FCAP, Curator

 

Ciechanover, Hershko, and Rose awarded for discovery of ubiquitin-mediated proteolysis

http://www.the-scientist.com/?articles.view/articleNo/23111/title/Ubiquitin-researchers-win-Nobel/

Nature Cell Biology 2, E171 (2000) http://dx.doi.org:/10.1038/35036412

The Royal Swedish Academy of Sciences has decided to award the Nobel Prize in Chemistry for 2004 “for the discovery of ubiquitin-mediated protein degradation” jointly to

Aaron Ciechanover
Technion – Israel Institute of Technology, Haifa, Israel,

Avram Hershko
Technion – Israel Institute of Technology, Haifa, Israel and

Irwin Rose
University of California, Irvine, USA

 

Proteins labelled for destruction

Proteins build up all living things: plants, animals and therefore us humans. In the past few decades biochemistry has come a long way towards explaining how the cell produces all its various proteins. But as to thebreaking down of proteins, not so many researchers were interested. Aaron Ciechanover, Avram Hershko and Irwin Rose went against the stream and at the beginning of the 1980s discovered one of the cell’s most important cyclical processes, regulated protein degradation. For this, they are being rewarded with this year’s Nobel Prize in Chemistry.

Aaron Ciechanover, Avram Hershko and Irwin Rose have brought us to realise that the cell functions as a highly-efficient checking station where proteins are built up and broken down at a furious rate. The degradation is not indiscriminate but takes place through a process that is controlled in detail so that the proteins to be broken down at any given moment are given a molecular label, a ‘kiss of death’, to be dramatic. The labelled proteins are then fed into the cells’ “waste disposers”, the so called proteasomes, where they are chopped into small pieces and destroyed.

 

Avram Hershko is an Israeli biochemist and winner of the 2004 Nobel Prize for Chemistry.

Hershko (born December 31, 1937) was born as Hersko Ferenc in Karcag, Hungary. In 1950, Hershko and his family emigrated from Hungary to Israel, where he adopted the name Avram. Hershko received his M.D. and Ph.D. from the Hadassah Medical School of the Hebrew University. In 1965-67, Hershko worked as a physician in the Israel Defense Forces.

In 1969-72, Hershko was a postdoctoral fellow with the late Dr. Gordon Tomkins at the University of California, San Francisco.

In 1987, Hershko was awarded the Weizmann Prize for Sciences, an honor given to top Israeli scientists. In 1994, he won the Israeli Prize for his contributions to Israeli society through biochemistry and medicine.

In 2004, Hershko was awarded the Nobel Prize in Chemistry “for the discovery of ubiquitin-mediated protein degradation.”

Ciechanover was born in Haifa, a year before the establishment of Israel. He is the son of Bluma (Lubashevsky), a teacher of English, and Yitzhak Ciechanover, an office worker.[1] His family were Jewish immigrants from Poland before World War II.

He earned a master’s degree in science in 1971 and graduated from Hadassah Medical School in Jerusalem in 1974. He received his doctorate in biochemistry in 1981 from the Technion – Israel Institute of Technology in Haifa before conducting postdoctoral research in the laboratory of Harvey Lodish at the Whitehead Instituteat MIT from 1981-1984. He is currently a Technion Distinguished Research Professor in the Ruth and Bruce Rappaport Faculty of Medicine and Research Institute at the Technion.

Ciechanover is a member of the Israel Academy of Sciences and Humanities, the Pontifical Academy of Sciences, and is a foreign associate of the United States National Academy of Sciences.

As one of Israel’s first Nobel Laureates in Science, he is honored in playing a central role in the history of Israel and in the history of the Technion – Israel Institute of Technology

 

  • Ciechanover, A., Hod, Y. and Hershko, A. (1978). A Heat-stable Polypeptide Component of an ATP-dependent Proteolytic System from Reticulocytes. Biochem. Biophys. Res. Commun. 81, 1100–1105.
  • Ciechanover, A., Heller, H., Elias, S., Haas, A.L. and Hershko, A. (1980). ATP-dependent Conjugation of Reticulocyte Proteins with the Polypeptide Required for Protein Degradation. Proc. Natl. Acad. Sci. USA 77, 1365–1368.
  • Hershko, A. and Ciechanover, A. (1982). Mechanisms of intracellular protein breakdown. Annu. Rev. Biochem. 51, 335–364.

Interview Transcript

Transcript from an interview with the 2004 Nobel Laureates in Chemistry Aaron Ciechanover, Avram Hershko and Irwin Rose, on 9 December 2004. Interviewer is Joanna Rose, science writer.

Aaron Ciechanover, Avram Hershko and Irwin Rose during the interview

Dr Ciechanover, Dr Hershko and Dr Rose, my congratulations to the Nobel Prize and welcome to this interview. I know that you two started as medical doctors but you are in science now, and you get the prize for scientific research. How come you left medicine?

Avram Hershko: Well, I started out as a medical student, I wanted to be a doctor. And during my medical studies I studied biochemistry. That was one of the subjects that every medical student studies, so I liked it very much. I liked, you know, the whole concept of biochemistry, of looking for chemical processes in cells, so we had, we could take off one year from the studies to spend in research in the lab. I also found a very good teacher, Jacob Mager, and I wanted to spend it with him, so I did. That’s how I got involved in biochemistry. Afterwards, I finished my medical studies but already, I, after that one year, I knew that I will go to biochemistry and not to practical medicine. That’s how I started. So, it’s, it’s, like all things in life, it starts by some kind of accident or so, that was the accident, I met a subject during my studies that I liked.

And a good teacher.

Avram Hershko: And a very good teacher.

Was it also a topic, an issue that you were interested in?

Avram Hershko: No, no, not yet, not yet. Mager was interested in many subjects so that was … Actually, I continued with him after my army service as a doctor, and during the course of a couple of years I evolved in four completely different subjects, protein, synthesis, purine metabolism, and a certain disease called glucose-6-phosphate dehydrogenase deficiency, because he was interested in many things, so that gave me a very good background, a very, very, you know, very good basic background.

What about you, Dr Ciechanover?

I fell in love with biochemistry …

Aaron Ciechanover: Surely you can repeat the story verbatim. The same very story, I started in the same medical school, and after four years I decided to try and taste, I fell in love with biochemistry, too.

Like ten years later.

Aaron Ciechanover: Exactly ten years later, and I also decided to taste it, and at that time at medical school they let students take one year off for medical studies, try some research, so I went into biochemistry, same very story, different mentor. And, a wonderful mentor, and I studied lipids.

Also.

Aaron Ciechanover: Not proteins at all, and then exactly, made a decision, that that’s it. But I had, because of obligations to serve in Israel in the military as a physician. I completed my medical studies, went to serve in the army, but meanwhile, in between, I was looking already for a future mentor, in biochemistry, and Avram was at the time abroad, in the University of California in San Francisco, and I got rave recommendation, that he is a great teacher and a great biochemist, and I wrote him, and he was ready to accept me, and there started this story. More or less.

So did you go to the States?

Aaron Ciechanover: No, no, he came here. He returned to /- – -/ fellow, he started a new department in Haifa, which was a new medical school, I joined him, not initially on this project, on a different one because I still had to serve in the army. It’s a little bit complicated date-wise, but basically it’s the same very story, mentorship, the same footstep, without knowing where I am going.

You will never know.

Aaron Ciechanover: I never know, but it’s basically, ten years later the same very footsteps.

Oh, that’s funny. What about you, Dr Rose? How did you get …

Irwin Rose: I have an anomalist’s story. It doesn’t, there is no precedent for this. We moved from the east coast to the town of Spokane, Washington, when I was about 13 years old, and I did not adapt very well to the, to the style of the place, and I spent most of my time in the public library. And I enjoyed the company of the Journal of Biological Chemistry, because it was the book shaped thing, in those days, you know, it was the small journal …

Avram Hershko: At the age of 13?

Irwin Rose: No, you know, like a couple of years, you know, I was very unpopular with the other students, and so I read the Journal of Biological … the small, the small Journal of Biological Chemistry, and I found an article I thought I understood. And I read it and I thought I understood it to the point where I could make some suggestions as to how it would be, the experiment might work, and then I was very satisfied with that, and then I … I didn’t spend much time in science at that point. Went into the navy, got out of the navy, tried to go to the University of California at Berkeley, but due to the failure to find the bulletin board announcing the laboratory time of organic chemistry, I couldn’t do my organic chemistry there.

So I said OK, I’ll be a biochemist …

So I went back to the State College of Washington and there I was influenced, I would say, by the embryology teacher, who was a very strong personality in terms of academic research, he tried to encourage his students. Then I went to the University of Chicago and there was a big shock to learn all the new kinds of things that they were teaching there, in organic chemistry and that sort of stuff, and very attractive concepts, and things began to come together in my mind as to how chemistry worked and how I might be able to exploit some of the early kinds of techniques that were being used in organic chemistry into biochemistry, which was something I was attracted to, due to my reading of the Journal of Biological Chemistry. So at that point I signed up, there was a big gymnasium, and people were signing people up for which major you were going to go into. So I said OK, I’ll be a biochemist.

So I entered into the department of biochemistry, never saw the chairman of biochemistry because he was the appointed ambassador to Britain for the United States. So I floated around in the department of biochemistry and learned some interesting things, and then I began to … I never wanted to work with a mentor, because I always wanted to have my own reputation and be free to do what I wanted to do. So I worked with the weakest people in the department. Don’t make that public. No, I don’t mention the names, but … so I did that sort of thing and that way I came to learn some more independence, and once in a while I did a good experiment, and so I had more confidence that I could do research, and so that’s how it got started.

Avram Hershko: Can I mention the story that you did your PhD or eight counts per minute or …

Irwin Rose: Oh yes, well, in those days people weren’t counting, people counted on planchettes. And you …

Avram Hershko: Puckered.

Irwin Rose: Well, it could be, depends on they were flat.

Avram Hershko: You dried them, didn’t you?

Irwin Rose: Yes, you dried them out, depending … yes, that’s right. You had to dry them out, it depends on what the compound was, but if it was trillium you had to get an infinitely thin layer so that you wouldn’t get self-absorption.

Avram Hershko: It’s common, self-absorption on a planchette.

Irwin Rose: Did you guys do that, too?

Aaron Ciechanover: Yeah, yeah, yeah.

Avram Hershko: We had a counter with only three /- – -/ so we moved it like that …

Irwin Rose: Oh yeah, yeah.

Avram Hershko: … it was a big excitement.

Irwin Rose: So I wasn’t that primitive. You were doing these things in Israel, an advanced state.

Aaron Ciechanover: You came to our country.

Irwin Rose: I did. I came to Israel. But anyway, yes, so we did those things. And even if you had eight counts above background, if there were eight, there were eight. That’s right. So you could do some experiments. That’s how it worked out.

So how did you meet together?

Avram Hershko: Well, that’s another story. I got interested in protein degradation during my post-doc fellowship in San Francisco, and when I came back to Israel I continued with that, and at that time it was a very obscure field, you know. People, there were all kinds of, not too many people were interested in it. Those that were interested were not very good. So I looked for somebody, and so my first time I think I came up and I looked for somebody to spend a sabbatical with. I couldn’t find anybody that attracted me. So then I met Ernie at a meeting in 1976, one year before, before my sabbatical was due. And do you remember, we met in the breakfast, so I said can I, just began to talk …

Irwin Rose: It’s alright, I forgot.

… it turned out that he was interested in protein degradation. And that was a secret …

Avram Hershko: … breakfast table, so I knew who he was, he was very well known for his work on enzyme mechanism. That I knew, but then I asked him what are you interested in, in other things? So it turned out that he was interested in protein degradation. And that was a secret, it was a secret because he never published anything on it, and I asked him how come you never published anything, and so he said there is nothing worth publishing on protein degradation. So that’s what he said.

Irwin Rose: Yeah, that was my opinion. Well, because I hadn’t done anything, you don’t say it right.

Avram Hershko: OK. Well, that’s how I remember it. And anyhow, I liked that attitude very much, and asked, I asked him can I spend my sabbatical with you? And he said yes, so that’s how it started, and then Aaron, the same year he started his PhD with me, and after my sabbatical the following, the summer after my sabbatical, Aaron joined us, and then he joined us for a couple of summers afterwards, so that’s how, that’s how the whole connection started.

But how come you pick up an obscure field in science, to work on?

Irwin Rose: Well, I’ll tell you, because when I first worked at Yale, the guy who had a lab next to me had made the original observation that there was a protein, there was an energy dependent on protein breakdown. Now, nobody believed him, but he had made some pretty strong observations that if you …

Avram Hershko: Here, we could mention names.

Irwin Rose: Yes, Melvin Simpson. He made these important observations.

Aaron Ciechanover: He hardly believed himself, because when you go into discussion on the paper, you kind of come to a convoluted argument whether it’s a direct requirement or indirect. We can do the conclusion that it’s indirect.

When was it?

Avram Hershko: 1953, so …

Irwin Rose: So I didn’t read the paper, but I had this man in the laboratory next to me and he said, he made this observation and I got very interested in it. And worked on it for, on sabbatical, and when I went to England and when I went to Israel I got mice from Mager, it turned out the same guy, but he wasn’t there at the time, and … but I never found an energy dependence on the protein breakdown. And it turns out later on that a fellow named Art Haas who had been a post doc with me, made the observation that if you’re not careful when you break cells, there’s a lysosomal enzyme that degrades the ubiquitin. So I never would have found it, you know. Somebody else had to make the observation that you could make a self-resistent that … that would show an ATP dependence on protein breakdown. It was not for me, but I did work on it earlier, and that’s the, that’s why I told you that I’d never made any important observations.

But you three work together. How does it work, to do things together?

Irwin Rose: I don’t do anything.

You do nothing? Who is the worker?

Avram Hershko: Well, that’s, first of all, that’s not true. I remember that you made some ubiquitin preparation …

Irwin Rose: I did.

Avram Hershko: Yes, and it fell on the floor, and then you collected it up from the floor … yeah, yeah. That first step is to boil the extra, because ubiquitin is heat stable, so you boiled it but then it fell on the floor, but you picked it up and it was good, yeah.

Irwin Rose: It was good, nothing could destroy it.

Irwin Rose: It was a licence only enzyme.

Aaron Ciechanover: The /- – -/ can take it, but not the floor.

Avram Hershko: But, yeah, but when I came to his lab we already had his first step, which was the fractionation, well, the reticulocyte cell-free system system was actually established in the laboratory of somebody else, Alfred Goldberg in Harvard, but they didn’t …

Aaron Ciechanover: /Inaudible./

Avram Hershko: No, no, but, yeah, but he made it first, he made it first.

Aaron Ciechanover: The first publication was from Harvard, no doubt.

Avram Hershko: But then he didn’t progress, but then he didn’t do what he should have done, which is fractionation. It’s hard to purify right away, but ATP dependent enzyme, he never found it. And what we did was fractionation and constitution, so we already had this first step of separating it into two, two fractions, fraction one and fraction two.

… we didn’t really understand that it’s binding …

So during these two years between the beginning of ’77 when I write to your lab and December of ’79, when we made the breakthrough in your lab, we purified the component from fraction one, we found it a heat stable protein, and then you had a part in that, you also boiled ubiquitin, and then in Haifa we found that it gets … when we labelled it with iodine and we found it gets bound to proteins and ATP dependent reaction, but we didn’t really understand that it’s binding, its co-herent binding the substate until that summer in 1971 in the laboratory of Rose where you invited me, together with Aaron who was then my graduate student in /- – -/ who was there. 1979, 1979. So that is when, when the discovery that ubiquitin …

Irwin Rose: Shall I tell the story about the ubiquitin?

Avram Hershko: Yes. I think I have finished. So then, that’s how I remember it, and how …

Irwin Rose: OK, well, here they had a heat stable factor that was required, and they made the observation that the ubiquitin went on to proteins. And so one of my post docs went to a post doc of another student, of another faculty member at the Fox Chase Cancer Centre, and said, there was a conversation, and do you know of any examples of a protein covalently linked to a protein? And this post doctoral fellow said yes, there is in the nucleus, a protein called ubiquitin that’s covalently linked to histone. And so they rushed to look at the amino acid composition of that so-called ubiquitin, and they compared it to the amino acid composition which you had published, I guess …

Aaron Ciechanover: No, not yet.

Irwin Rose: Not yet published.

Aaron Ciechanover: But in the end it was published back to back with JBC.

Irwin Rose: No, no, no. But how did they know the conversation …

Aaron Ciechanover: No, because they knew, the end story is that the Wilkinson paper came back to back with ours on the /- – -/.

Avram Hershko: OK. Let’s not go into the detail.

Irwin Rose: Well, for some reason or other, they found confidence…

Avram Hershko: They knew that I published that.

Irwin Rose: Really, and I was not a leak.

Avram Hershko: No, no, you were not.

Aaron Ciechanover: No, he was in the lab, he was free and did this. We didn’t hide anything.

Irwin Rose: OK, you’re getting the inside story here. Now, wait a second.

I have a statement from your colleague. “At first nobody cared about your work, and those that knew something about it, they didn’t believe it.” Was it so …?

Irwin Rose: Who said that?

Avram Hershko: That was, that was Fred Goldberg, yeah.

Aaron Ciechanover: Let’s not mention names.

Avram Hershko: Oh! No, we didn’t mention names.

That citation is right.

Aaron Ciechanover: I’ll tell you, I’ll tell you a funny story. I left the lab in ’81, basically after my PhD was completed I submitted it and I went to Harvard, I went to MIT to do a post doc fellow, and Harvard carried out weekly seminars. And in this weekly seminar, one of the founders in the field of proteolysis, one of the originally, not the founder, but it doesn’t matter. A famous scientist in the field presented the weekly seminar at Harvard. I knew of him because he was our competitor for many years, and I went to hear the seminar, so I crossed the river by the bus, I took the shuttle bus that goes /- – -/ and I was sitting in the very back bench. And this was probably about two weeks before you came to visit, it was the very beginning of my, do you remember when I met you, I came to the airport to pick you up.

Avram Hershko: Yeah, yeah.

Aaron Ciechanover: And then, near me, was sitting a very famous scientist that I only later realised that his name is Arthur Dee, a very famous scientist, and after this presentation of the professor, this was only ’81 when we had like eight or nine papers already in the literature with a huge amount of information there. And he was a protein researcher and he raised his hand, I remember very well, and the other guy, when we were both  /- – -/ he said, you know, I have a question to ask you. There is a fellow in Haifa by the name of Hershko, and another one with a very complicated Polish name that I cannot even pronounce, that published a series of papers on a small protein that is attached to other proteins and marks them for degradation, can you comment on it? And he basically dismissed it as an artefact.

… it adds to our benefit, because they left us alone for seven successive years …

And I don’t, I don’t criticise him, all I’m telling you it was symbolic for me enough for after eight papers in the literature, this was the spirit in the field from people who worked in the field, and there were very few. As a matter of fact, it adds to our benefit, because they left us alone for seven successive years, even after I left the lab to work out basically the entire system. The next scientist to join the field was a scientist at MIT, Alex Varshavsky, who joined in ’84, ’83, but published in ’84, and given I was there and collaborated, so for seven successive years they let us lay the entire stone down in the literature so I don’t criticise him, actually I appreciate him tremendously for letting us do it. You know, in retrospect.

But I wonder, how do you survive as a scientist when nobody believes you somehow? Nobody’s interested. You become kind of non-visible.

Irwin Rose: You’re making observations, and the observations get published, so the observations are true. Whether anybody will say that belongs to a big story like it turns out to be is not predictable, but so you don’t make claims like that. You say that this is very interesting and so on and so on and so on, and you keep following it up, and it doesn’t necessarily become the centre of attention yet, until you build a big enough story. I think that’s the way it works.

We all survive because funding for research was generous in those days, you know. It’s been less generous now, and we have a peer review system which is more critical and so I think you have to, you have to add successively to the picture you’re trying to portray. It’s not sufficient to just provide data. So I think that’s part of it. But I agree that it’s important to be left alone for a sufficient amount of time in order to be able to do it, and not feel that you’re in the middle of a big activity already, so you know, you need to do that sort of thing.

So do you think you would get support today for such work, which was kind of apart?

Avram Hershko: Well, I hope the fund /- – -/ look up your website and will hear these things. Because it’s … yeah, Joe Goldstein, you know, a Nobel Laureate and a good one, wrote a nice article about this year’s Lasker Award, in which he compared science to a sculpture by this British sculptor who had his stone, it was a huge stone of two and a half ton, on which another stone, and another stone, and another stone, and at the end is a little stone, so he said that in science there are big stones and small stones. The important science is the opposite. When you have a little stone, and on top of it you put a bigger stone and then a bigger stone. If you throw out a big stone at the beginning so there’s a lot of publicity sometimes nothing comes out of it, and the scientist, to find his little stone, on which the other stones can be built. So I recommend to read his article.

Now you find the small stones, Dr Rose, in your kitchen, as I understand it. You have a small laboratory there?

Irwin Rose: You want to talk about my kitchen?

Yeah. Your laboratory, I would say.

Irwin Rose: Well, when I retired from Fox Chase I took my spectrophotometer and a lot of my chemicals, based on a sort of suggestion of Dr … his recommendation. So I took all my chemicals and my spectrophotometer and my constant temperature bath and so forth with me to Irvine, and when the person whose laboratory I was sitting decided to retire, I had to do something with the spectrophotometer and so I found a place in my kitchen for it. And this was very convenient because it saved me a lot of time. I didn’t have to go to work every day and if I had a little experiment to do I could do it in my kitchen. So that was very good, although I’ve got a lot of chemicals that I have no use for and I’d like to take them back.

Aaron Ciechanover: Send them over, send them over.

Irwin Rose: I’ll send them over. I’ll get a box.

Avram Hershko: But I worry that you don’t have an ice machine. You need an ice machine.

Irwin Rose: No, I don’t have an ice machine. But I have a freezer and I can make ice cubes and I can break them up.

It’s kind of worrying, in science. So you can work when everything’s /- – -/ ?

Irwin Rose: Yeah, that’s right, exactly.

So are you the kind of scientists that work all day and all night long, kind of nerd scientists?

So that’s my recommendation, do not retire. Do not retire fellas. …

Irwin Rose: I think we all work all day and all night long. I do. I don’t have any hobbies, you know, I’m very embarrassed when people ask me what are my hobbies, I don’t have any hobbies. I mean, it’s just enough to keep up with the things I’m trying to solve. You know, I used to work on little puzzles and so on and so forth. Each puzzle requires attention and, so you get an idea. You get your ideas at different times. Sometimes your wife makes a statement and you say: aha, maybe you’re right. And so you go off to your kitchen, and do a little experiment, so you try to, that’s the way you make progress, if you continue these things. So that’s my recommendation, do not retire. Do not retire fellas.

Avram Hershko: I won’t.

Aaron Ciechanover: I’m never going to.

You worked together in the beginning, you were the graduate student of Dr Hershko, how was it to separate from each other?

Aaron Ciechanover: Well, it’s the nature of science, I think, because you know, you graduate, you go your post doctorate fellowship, and Avram was gracious enough to bring me back, but now is independent and that’s the entire idea, if you bring a young scientist back, you give him a bench, start up funds, and then you tell him now in five years, come back in five years, and show the committees that you worked for something. So actually, you know, it would be unnatural if we would have continued to work together. So, each of us is independent. Now we’re in the same institute and that’s the whole idea of children that grow up, students that become their own, scientists on their own, I think that’s the way.

Do you compete with each other?

Avram Hershko: No, there is enough to do in the ubiquitin field, we don’t feel that we had to compete. There are different aspects of the ubiquitin field. I am working on cell cycle and he works on …

Aaron Ciechanover: /- – -/. Completely different.

How is it to live in a small country with big problems and to get funds for science?

Avram Hershko: It is not easy, it is not easy. You have to know the daily tension which is of course distractive. The funds are small, some funds for science are small. Graduate students have to go to serve in the army and things like that, so it’s more difficult than elsewhere, but it’s possible, it’s possible.

And now everybody’s happy. About the Nobel Prize. So thank you very much for sharing your thoughts with us, and being with us.

 

See a Video of the Interview
26 min.

 

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MLA style: “Transcript from an interview with the 2004 Nobel Laureates in Chemistry Aaron Ciechanover, Avram Hershko and Irwin Rose, on 9 December 2004”. Nobelprize.org. Nobel Media AB 2014. Web. 5 Sep 2015. <http://www.nobelprize.org/nobel_prizes/chemistry/laureates/2004/ciechanover-hershko-rose-interview-transcript.html>

 

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Vincent Astor Professor Emeritus
2002 Albert Lasker Award for Special Achievement in Medical Science

Responsible for the various tasks required in turning genetic information into working proteins, ribonucleic acids are one of the most essential players in the life of a cell. First discovered in 1868, RNA today remains the subject of intense scientific scrutiny. Over the course of a career dedicated to understanding the intricate workings of gene transcription, Rockefeller University scientist James E. Darnell Jr. has revealed some of RNA’s most secretive and surprising mechanisms. For his half-century of illuminating research, Dr. Darnell received the 2002 Albert Lasker Award for Special Achievement in Medical Science.

In 1963, Dr. Darnell described a phenomenon he termed “RNA processing,” a step in the process of gene transcription, which had only recently been elucidated in bacterial systems. Working with mammalian cells — which differ from bacterial cells in that they contain a nucleus, where RNA is created — Dr. Darnell observed that very long strings of RNA disappear from the cell nucleus and that subsequently, shorter RNAs resembling the absent longer ones appear in the cytoplasm. Mammalian cells, he concluded, must distill their massive, immature nuclear RNA into shorter, mature forms that are individually coded for specific purposes by specific segments of the genome.

Dr. Darnell carried the principles of his finding — which he made in ribosomal RNA, part of the construction crew that builds cellular proteins — to other long nuclear RNA, including the longest one, which he named heterogeneous nuclear RNA (hnRNA). His hypothesis, that hnRNA is the precursor of the better known messenger RNA — which carries the genetic blueprint for protein building — soon bore fruit when he found a structural correlation between the two. Certain hnRNAs and nearly all messenger RNAs have a “tail” of adenine nucleotides at one end. Dr. Darnell followed this discovery with the observation that when an hnRNA string with an adenine tail disappears from the nucleus, a messenger RNA with the same tail then appears in the cytoplasm, suggesting a causal link between the two. When he found a second similarity — a cap at the end of the string opposite the adenine tail — he faced a conundrum. Scientific dogma had it that the order of nucleotides in any RNA mirrors that of DNA, whether the RNA is modeled from somewhere in the middle of the DNA or from one of the ends. The matching of a nuclear RNA to its cytoplasmic product by two end pieces glued together was surprising, but the concept was soon proven by colleagues at other institutions and called RNA splicing.

After a brief sojourn in Paris to work in François Jacob’s lab, Darnell worked at MIT, the Albert Einstein College of Medicine, and Rockefeller University on the relationship between mRNA and hnRNA. hnRNA was believed to be the precursor to mRNA, and despite making some key discoveries, Darnell admits that he could not free his imagination from the idea of colinearity and envision an hnRNA spliced to produce a smaller mRNA.

At this time, Darnell turned his attention to the question he had pondered since Paris: how were genes regulated in animal cells? This led to the discovery of the STAT and the Jak-STAT pathway of transcription control.

With the knowledge of RNA processing and splicing, Dr. Darnell next examined how cells begin the process of transcription and how they activate particular segments of DNA. Having moved to Rockefeller University in 1974, he found in the early 1980s that cells retain their specificity only in the context of their natural environment. Away from other liver cells, for example, a single liver cell stops producing liver-specific RNA, though it continues to make RNA for more generic cellular tasks. To pinpoint the signals responsible, which he believed must be coming from outside the cell, Dr. Darnell took a closer look at interferons (IFN), proteins that warn a cell when it’s time to raise its genetic defenses against harmful microbes.

Dr. Darnell’s laboratory studies how signals from the cell surface affect transcription of genes in the nucleus. Originally using interferon as a model cytokine, the Darnell group discovered that cell transcription was quickly changed by binding of cytokines to the cell surface. Introducing IFNβ into cell cultures, he watched as a particular type of mRNA accumulated in the cytoplasm, unaccompanied by any new protein synthesis. Analyzing the mRNA led him to the segment of DNA that had been activated, and the lack of new proteins told him that the cell contained its own, usually dormant, IFN-responsive transcription factor. By isolating a particular stretch of DNA from IFN-treated cells, he was able to call out of hiding the proteins that make up that factor, which, partly because they respond to signals very quickly, he called “STATs.” Dr. Darnell then traced the chemical relay that activates the STATs after IFN contact, called the Jak-Stat pathway.

The bound interferon led to the tyrosine phosphorylation of latent cytoplasmic proteins now called STATs (signal transducers and activators of transcription) that dimerize by reciprocal phosphotyrosine-SH2 interchange. They accumulate in the nucleus, bind DNA and drive transcription. This pathway has proved to be of wide importance, with seven STATs now known in mammals that take part in a wide variety of developmental and homeostatic events in all multicellular animals. Crystallographic analysis defined functional domains in the STATs, and current attention is focused on two areas: how the STATs complete their cycle of activation and inactivation, which requires regulated tyrosine dephosphorylation; and how persistent activation of STAT3 that occurs in a high proportion of many human cancers contributes to blocking apoptosis in cancer cells. Current efforts are devoted to inhibiting STAT3 with modified peptides that can enter cells.

 

Dr. Darnell received his M.D. in 1955 from the Washington University School of Medicine. His career has included poliovirus research with Harry Eagle at the National Institute of Allergy and Infectious Diseases, research with François Jacob at the Pasteur Institute in Paris and academic appointments at the Massachusetts Institute of Technology, the Albert Einstein College of Medicine and Columbia University. In 1974 Dr. Darnell joined Rockefeller as Vincent Astor Professor, and from 1990 to 1991 he was vice president for academic affairs.

A member of the National Academy of Sciences since 1973, he has received numerous awards, including the 2012 Albany Medical Center Prize in Medicine and Biomedical Research, the 2003 National Medal of Science, the 2002 Albert Lasker Award for Special Achievement in Medical Science, the 1997 Passano Award, the 1994 Paul Janssen Prize in Advanced Biotechnology and Medicine and the 1986 Gairdner Foundation International Award.

He is the coauthor with S.E. Luria of General Virology and the founding author with Harvey Lodish and David Baltimore of Molecular Cell Biology, now in its seventh edition. His book RNA, Life’s Indispensable Molecule was published in July 2011 by Cold Spring Harbor Laboratory Press. He is a member of the American Academy of Arts and Sciences and a foreign member of The Royal Society and The Royal Swedish Academy of Sciences.

 

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Metabolic Genomics and Pharmaceutics, Vol. 1 of BioMed Series D available on Amazon Kindle

Metabolic Genomics and Pharmaceutics, Vol. 1 of BioMed Series D available on Amazon Kindle

Reporter: Stephen S Williams, PhD

Article ID #180: Metabolic Genomics and Pharmaceutics, Vol. 1 of BioMed Series D available on Amazon Kindle. Published on 8/15/2015

WordCloud Image Produced by Adam Tubman

Leaders in Pharmaceutical Business Intelligence would like to announce the First volume of their BioMedical E-Book Series D:

Metabolic Genomics & Pharmaceutics, Vol. I

SACHS FLYER 2014 Metabolomics SeriesDindividualred-page2

which is now available on Amazon Kindle at

http://www.amazon.com/dp/B012BB0ZF0.

This e-Book is a comprehensive review of recent Original Research on  METABOLOMICS and related opportunities for Targeted Therapy written by Experts, Authors, Writers. This is the first volume of the Series D: e-Books on BioMedicine – Metabolomics, Immunology, Infectious Diseases.  It is written for comprehension at the third year medical student level, or as a reference for licensing board exams, but it is also written for the education of a first time baccalaureate degree reader in the biological sciences.  Hopefully, it can be read with great interest by the undergraduate student who is undecided in the choice of a career. The results of Original Research are gaining value added for the e-Reader by the Methodology of Curation. The e-Book’s articles have been published on the Open Access Online Scientific Journal, since April 2012.  All new articles on this subject, will continue to be incorporated, as published with periodical updates.

We invite e-Readers to write an Article Reviews on Amazon for this e-Book on Amazon.

All forthcoming BioMed e-Book Titles can be viewed at:

http://pharmaceuticalintelligence.com/biomed-e-books/

Leaders in Pharmaceutical Business Intelligence, launched in April 2012 an Open Access Online Scientific Journal is a scientific, medical and business multi expert authoring environment in several domains of  life sciences, pharmaceutical, healthcare & medicine industries. The venture operates as an online scientific intellectual exchange at their website http://pharmaceuticalintelligence.com and for curation and reporting on frontiers in biomedical, biological sciences, healthcare economics, pharmacology, pharmaceuticals & medicine. In addition the venture publishes a Medical E-book Series available on Amazon’s Kindle platform.

Analyzing and sharing the vast and rapidly expanding volume of scientific knowledge has never been so crucial to innovation in the medical field. WE are addressing need of overcoming this scientific information overload by:

  • delivering curation and summary interpretations of latest findings and innovations on an open-access, Web 2.0 platform with future goals of providing primarily concept-driven search in the near future
  • providing a social platform for scientists and clinicians to enter into discussion using social media
  • compiling recent discoveries and issues in yearly-updated Medical E-book Series on Amazon’s mobile Kindle platform

This curation offers better organization and visibility to the critical information useful for the next innovations in academic, clinical, and industrial research by providing these hybrid networks.

Table of Contents for Metabolic Genomics & Pharmaceutics, Vol. I

Chapter 1: Metabolic Pathways

Chapter 2: Lipid Metabolism

Chapter 3: Cell Signaling

Chapter 4: Protein Synthesis and Degradation

Chapter 5: Sub-cellular Structure

Chapter 6: Proteomics

Chapter 7: Metabolomics

Chapter 8:  Impairments in Pathological States: Endocrine Disorders; Stress

                   Hypermetabolism and Cancer

Chapter 9: Genomic Expression in Health and Disease 

 

Summary 

Epilogue

 

 

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Nonhematologic Cancer Stem Cells [11.2.3]

Writer and Curator: Larry H. Bernstein, MD, FCAP 

Nonhematologic Stem Cells

11.2.3.1 C8orf4 negatively regulates self-renewal of liver cancer stem cells via suppression of NOTCH2 signalling

Pingping Zhu, Yanying Wang, Ying Du, Lei He, Guanling Huang, et al.
Nature Communications May 2015; 6(7122). http://dx.doi.org:/10.1038/ncomms8122

Liver cancer stem cells (CSCs) harbor self-renewal and differentiation properties, accounting for chemotherapy resistance and recurrence. However, the molecular mechanisms to sustain liver CSCs remain largely unknown. In this study, based on analysis of several hepatocellular carcinoma (HCC) transcriptome datasets and our experimental data, we find that C8orf4 is weakly expressed in HCC tumors and liver CSCs. C8orf4 attenuates the self-renewal capacity of liver CSCs and tumor propagation. We show that NOTCH2 is activated in liver CSCs. C8orf4 is located in the cytoplasm of HCC tumor cells and associates with the NOTCH2 intracellular domain, which impedes the nuclear translocation of N2ICD. C8orf4 deletion causes the nuclear translocation of N2ICD that triggers the NOTCH2 signaling, which sustains the stemness of liver CSCs. Finally, NOTCH2 activation levels are consistent with clinical severity and prognosis of HCC patients. Altogether, C8orf4 negatively regulates the self-renewal of liver CSCs via suppression of NOTCH2 signaling.

Like stem cells, CSCs are characterized by self-renewal and differentiation simultaneously9. Not surprisingly, CSCs share core regulatory genes and developmental pathways with normal tissue stem cells. Accumulating evidence shows that NOTCH, Hedgehog and Wnt signaling pathways are implicated in the regulation of CSC self-renewal4. NOTCH signaling modulates many aspects of metazoan development and tissue stemness1011. NOTCH receptors contain four members (NOTCH1–4) in mammals, which are activated by engagement with various ligands. The aberrant NOTCH signaling was first reported to be involved in the tumorigenesis of human T-cell leukaemia1213. Recently, a number of studies have reported that the NOTCH signaling pathway is implicated in regulating self-renewal of breast stem cells and mammary CSCs1415. However, how the NOTCH signaling regulates the liver CSC self-renewal remains largely unknown.

C8orf4, also called thyroid cancer 1 (TC1), was originally cloned from a papillary thyroid carcinoma and its surrounding normal thyroid tissue16. C8orf4 is ubiquitously expressed across a wide range of vertebrates with the sequence conservation across species. A number of studies have reported that C8orf4 is highly expressed in several tumors and implicated in tumorigenesis171819. In addition, C8orf4 augments Wnt/β-catenin signaling in some cancer cells2021, suggesting it may be involved in the regulation of self-renewal of CSCs. However, the biological function of C8orf4 in the modulation of liver CSC self-renewal is still unknown. Here we show that C8orf4 is weakly expressed in HCC and liver CSCs. NOTCH2 signaling is highly activated in HCC tumors and liver CSCs. C8orf4 negatively regulates the self-renewal of liver CSCs via suppression of NOTCH2 signaling.

C8orf4 is weakly expressed in HCC tissues and liver CSCs

To search for driver genes in the oncogenesis of HCC, we performed genome-wide analyses using several online-available HCC transcriptome datasets by R language and Bioconductor approaches. After analysing gene expression profiles of HCC tumor and peri-tumor tissues, we identified >360 differentially expressed genes from both Park’s cohort (GSE36376; ref. 22) and Wang’s cohort (GSE14520; refs 2324). Of these changed genes, we focused on C8orf4, which was weakly expressed in HCC tumors derived from both Park’s cohort (GSE36376) and Wang’s cohort (GSE14520) (Fig. 1a). Lower expression of C8orf4 was further confirmed in HCC samples by quantitative reverse transcription–PCR (qRT–PCR) and immunoblotting (Fig. 1b,c). In this study, HCC patient samples we used included all subtypes of HCC. In addition, these observations were further validated by immunohistochemical (IHC) staining (Fig. 1d). These data indicate that C8orf4 is weakly expressed in HCC tumor tissues.

C8orf4 is weakly expressed in HCC tumours and liver CSCs

C8orf4 is weakly expressed in HCC tumours and liver CSCs

Figure 1. C8orf4 is weakly expressed in HCC tumours and liver CSCs

http://www.nature.com/ncomms/2015/150519/ncomms8122/images_article/ncomms8122-f1.jpg

(a)C8orf4 is weakly expressed in HCC patients. Using R language and Bioconductor methods, we analyzed C8orf4 expression in HCC tumor and peri-tumor tissues provided by Park’s cohort (GSE36376) and Wang’s cohort (GSE14520) datasets. (b,c) C8orf4 expression levels were verified in HCC patient samples by quantitative RT–PCR (qRT–PCR) (b) and immunoblotting (c). β-actin served as a loading control. 18S: 18S rRNA. (d) HCC samples were assayed by immunohistochemical staining. Scale bar—left: 50 μm; right: 20 μm. (eC8orf4 is weakly expressed in CD13+CD133+ cells sorted from Huh7 cells and primary HCC samples. C8orf4 messenger RNA (mRNA) was measured by qRT–PCR. Six HCC samples got similar results. (fC8orf4 is much more weakly expressed in oncospheres than non-sphere tumor cells. Non-sphere: Huh7 or HCC primary cells that failed to form spheres. (g) HCC sample tissues were co-stained with anti-C8orf4 and anti-CD13 or anti-CD133 antibodies, then counterstained with DAPI for confocal microscopy. White arrows indicate CD13+ or CD133+ cells. Scale bars: 20 μm. For a,b, data are shown as box and whisker plot. Boxes represent interquartile range (IQR); upper and lower edge corresponds to the 75th and 25th percentiles, respectively. Horizontal lines within boxes represent median levels of gene intensity. Whiskers below and above boxes extend to the 5th and 95th percentiles, respectively. For e and f, Student’s t-test was used for statistical analysis, *P<0.05;**P<0.01, data are shown as mean ± standard deviation. Data are representative of at least three independent experiments. P, peri-tumor; T, tumor.

 

Notably, C8orf4 was also weakly expressed in embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSCs) by analysis of its expression profiles derived from online datasets (GSE14897; ref. 25 and GSE25417; ref. 26) (Supplementary Fig. 1a,b). C8orf4 was also lowly expressed in normal liver stem cells (Supplementary Fig. 1c,d), suggesting that C8orf4 may be involved in the regulation of self-renewal of liver stem cells. Thus, we propose that C8orf4 might play a role in the maintenance of liver CSCs. Since CD13 and CD133 were widely used as liver CSC surface markers, we sorted CD13+CD133+ cells from Huh7 and Hep3B HCC cell lines as well as HCC samples, serving as liver CSCs. We observed that C8orf4 was weakly expressed in liver CSCs enriched from both HCC cell lines and patient samples (Fig. 1e). Six HCC samples were analyzed for these experiments. Similar results were obtained in CD13+CD133+ cells from Hep3B cells. Furthermore, we performed sphere formation experiments using Huh7 cells and HCC primary sample cells, and detected expression levels of C8orf4. We observed that C8orf4 was dramatically reduced in the oncospheres generated by both HCC cell lines and patient samples (Fig. 1f). In addition, we noticed that C8orf4 expression was negatively correlated with liver CSC markers such as CD13 and CD133 in HCC samples (Fig. 1g), suggesting lower expression of C8orf4 in liver CSCs. Moreover, C8orf4 was mainly located in the cytoplasm of tumour cells. Altogether, C8orf4 is weakly expressed in HCC tumor tissues and liver CSCs.

C8orf4 negatively regulates self-renewal of liver CSCs

We then wanted to look at whether C8orf4 plays a critical role in the self-renewal maintenance of liver CSCs. C8orf4 was knocked out in Huh7 cells through a CRISPR/Cas9 system (Fig. 2a). TwoC8orf4-knockout (KO) cell strains were established and C8orf4 was completely deleted in these two strains. C8orf4 deletion dramatically enhanced oncosphere formation (Fig. 2b). We co-stained SOX9, a widely used progenitor marker, and Ki67, a well-known proliferation marker, in C8orf4 KO sphere cells. We found that SOX9 was strongly stained in C8orf4 KO sphere cells (Supplementary Fig. 2a). In contrast, Ki67 staining was not significantly altered in C8orf4 KO sphere cells versus WT sphere cells. We also digested sphere cells and examined the SOX9 and Ki67 expression by flow cytometry. Similar results were achieved (Supplementary Fig. 2b). Importantly, through serial passage of CSC sphere cells, similar observations were obtained in the fourth generation oncosphere assay (Supplementary Fig. 2c,d). These data suggest that C8orf4 is involved in the regulation of liver CSC self-renewal.

(not shown)

Figure 2: C8orf4 knockout enhances self-renewal of liver CSCs.

http://www.nature.com/ncomms/2015/150519/ncomms8122/images_article/ncomms8122-f2.jpg

  • C8orf4-deficient Huh7 cells were established using a CRISPR/Cas9 system. T7 endonuclease I cleavage confirmed the efficiency of sgRNA (left panel, white arrowheads), and C8orf4-knockout efficiency was confirmed by western blot (right panel). Two knockout cell lines were used.  C8KO#1:C8orf4KO#1;  C8KO#2C8orf4KO#2. (bC8orf4-deficient cells enhanced sphere formation activity. Calculated ratios are shown in the right panel. (cC8orf4-deficient or WT Huh7 cells (1 × 106) were injected into BALB/c nude mice. Tumor sizes were observed every 5 days. (dC8orf4 deficiency enhances tumor-initiating capacity. Diluted cell numbers of Huh7 cells were implanted into BALB/c nude mice for tumor initiation. Percentages of tumor-formation mice were calculated (left panel), and frequency of tumor-initiating cells was calculated using extreme limiting dilution analysis (right panel). Error bars represent the 95% confidence intervals of the estimation. (e) Expression levels of CD13 andCD133 were analyzed in C8orf4-knockout Huh7 cells. (f) C8orf4 was silenced in HCC primary cells and C8orf4 depletion enhanced sphere formation activity. Calculated ratios are shown at the right panel. Three HCC specimens obtained similar results. (g) C8orf4-overexpressing Huh7 cells were established (left panel). C8orf4-overexpressing Huh7 cells and control Huh7 cells were cultured for sphere formation. (h,i) Xenograft tumor growth (h) and frequency of tumor-initiating cells (i) for C8orf4-overexpressing Huh7 cells were analyzed as c,d. (j) C8orf4 overexpression reduces expression of CD133 and CD13 in Huh7 cells. (k) C8orf4 was transfected in HCC primary cells and cultured for sphere formation. Three HCC patient samples obtained similar results. Scale bars: b,f,g,k, 500 μm. Student’s t-test was used for statistical analysis,    *P<0.05; **P<0.01; ***P<0.001, data are shown as mean ± standard deviation. Data represent at least three independent experiments. oeC8orf4, overexpression of C8orf4; oeVec, overexpression vector.

In addition, C8orf4-deficient Huh7 cells overtly increased xenograft tumour growth (Fig. 2c). We then performed sphere formation and digested oncospheres formed by C8orf4-deficient or WT cells into single-cell suspension, then subcutaneously implanted 1 × 104, 1 × 103, 1 × 102 and 10 cells into BALB/c nude mice. Tumour formation was examined for tumour-initiating capacity at the third month. C8orf4 deficiency remarkably enhanced tumour-initiating capacity and liver CSC ratios (Fig. 2d). In addition, C8orf4 deletion significantly enhanced expression levels of the liver CSC markers such as CD13 and CD133 (Fig. 2e). We also silenced C8orf4 in HCC primary cells using a lentivirus infection system and established C8orf4-silenced cells. Two pairs of short hairpin RNA (shRNA) sequences obtained similar knockdown efficiency. C8orf4 knockdown remarkably promoted sphere formation and xenograft tumour growth (Fig. 2f and Supplementary Fig. 2e). These data indicate that C8orf4 deletion potentiates the self-renewal of liver CSCs.
We next overexpressed C8orf4 in Huh7 cells and HCC primary cells using lentivirus infection. We observed that C8orf4 overexpression in Huh7 cells remarkably reduced sphere formation and xenograft tumour growth (Fig. 2g,h). In addition, C8orf4 overexpression remarkably reduced tumour-initiating capacity and expression of liver CSC markers (Fig. 2i,j). Similar results were observed by C8orf4 overexpression in HCC primary cells (Fig. 2k). We tested three HCC samples with similar results. Overall, C8orf4 negatively regulates the maintenance of liver CSC self-renewal and tumour propagation.

C8orf4 suppresses NOTCH2 signaling in liver CSCs

To further determine the underlying mechanism of C8orf4 in the regulation of liver CSCs, we analyzed three major self-renewal signaling pathways, including Wnt/β-catenin, Hedgehog and NOTCH pathways, in C8orf4-deleted Huh7 cells and HCC primary cells. We found that only NOTCH target genes were remarkably upregulated in C8orf4-deficient cells (Fig. 3a), whereasC8orf4 deficiency did not significantly affect the Wnt/β-catenin or the Hedgehog pathway. Given that the NOTCH family receptors have four members, we wanted to determine which NOTCH member was involved in the C8orf4-mediated suppression of liver CSC stemness. We noticed that only NOTCH2 was highly expressed in both Huh7 cells and HCC samples (Fig. 3b). In addition, this result was also confirmed by analysis of NOTCH expression levels derived from Wang’s cohort (GSE14520) and Petel’s cohort (E-TABM-36; ref. 27) (Fig. 3c). Moreover, we analysed expression profiles of C8orf4 and NOTCH target genes using Park’s cohort (GSE36376) and Wurmbach’s cohort (GSE6764; ref. 28). These cohort datasets provided several Notch signaling and its target genes. HEY1NRARP and HES6 genes were highly expressed in HCC tumour tissues (GSE6764; ref. 28), which were further confirmed in HCC samples by real-time PCR (Supplementary Fig. 3a,b). Furthermore, HEY1NRARP and HES6 genes have been reported to be relatively specific NOTCH target genes. We then examined these three genes as the NOTCH2 target genes throughout this study. We found that the C8orf4 expression level was negatively correlated with the expression levels of HEY1 and HES6, suggesting that C8orf4 inhibited NOTCH signaling in HCC patients (Fig. 3d). Finally these results were further confirmed in HCC samples by qRT-PCR (Fig. 3e). To further explore the activation status of NOTCH2 signaling in liver CSCs, we examined the expression levels of NOTCH downstream target genes in oncospheres and CD13+CD133+ cells derived from both Huh7 cells and HCC cells. We observed that NOTCH target genes were highly expressed in liver CSCs (Fig. 3f,g). These observations were verified by immunoblotting (Fig. 3h). In addition, the expression levels of NRARPHES6 and HEY1 were positively related to the expression levels of EpCAM and CD133 derived from Zhang’s cohort (GSE25097; ref. 29) and Wang’s cohort (GSE14520; Supplementary Fig. 3c,d). These data suggest that the NOTCH2 signaling plays a critical role in the maintenance of self-renewal of liver CSCs.

(not shown)

Figure 3: C8orf4 suppresses NOTCH2 signaling in liver CSCs.

http://www.nature.com/ncomms/2015/150519/ncomms8122/images_article/ncomms8122-f3.jpg

(aC8orf4 deficiency or depletion activates NOTCH signaling. The indicated major stemness signalling pathways were analysed in C8orf4-knockout Huh7 cells (left panel) and C8orf4-silenced primary cells of HCC samples (right panel). (b) Four receptor members of NOTCH family were examined in both Huh7 cells (left panel) and 29 pairs of HCC samples (right panel). (cNOTCH receptors were analyzed from Wang’s cohort (left panel) and Petel’s cohort (right panel) datasets. (dHEY1 and HES6 were highly expressed in C8orf4low samples by analysis of Park’s cohort (upper panel) and Wurmbach’s cohort (lower panel). (e) Expression levels of HEY1 and HES6 along with C8orf4 were analysed in HCC samples by qRT–PCR. (f,g) Expression levels of NRARPHEY1 and HES6 in spheres generated by Huh7 cells and HCC primary cells (f) and in CD13+CD133+ cells sorted from Huh7 cells and HCC primary cells (g). Non-sphere: Huh7 cells or HCC cells that failed to form spheres. (h) HEY1, HES6 and NRARP expression in sphere and non-sphere cells was detected by immunoblotting. β-actin was used as a loading control. For c,d, data are shown as box and whisker plot. Box: interquartile range (IQR); horizontal line within box: median; whiskers: 5–95 percentile. For a,b,f,g, Student’s t-test was used for statistical analysis, *P<0.05;**P<0.01; ***P<0.001, data are shown as mean ± standard deviation. Data are representative of at least three independent experiments.

C8orf4 interacts with NOTCH2 that is critical for liver CSCs

On ligand–receptor binding, the NOTCH receptor experiences a proteolytic cleavage by metalloprotease and γ-secretase, releasing a NOTCH extracellular domain (NECD) and a NOTCH intracellular domain (NICD), respectively30. Then the active NICD undergoes nuclear translocation and activates the expression of NOTCH downstream target genes31.Then we constructed the NOTCH2 extracellular domain (N2ECD) and intracellular domain (N2ICD) and examined the interaction with C8orf4 via a yeast two-hybrid approach. Interestingly, we found that C8orf4 interacted with N2ICD, but not N2ECD (Fig. 4a). The interaction was validated by co-immunoprecipitation (Fig. 4b). Through domain mapping, the ankyrin repeat domain of NOTCH2 was essential and sufficient for its association with C8orf4 (Fig. 4c). Taken together, C8orf4 interacts with the N2ICD domain of NOTCH2.

Figure 4: C8orf4 interacts with NOTCH2 that is required for the self-renewal maintenance of liver CSCs.

C8orf4 interacts with NOTCH2 that is required for the self-renewal maintenance of liver CSCs

C8orf4 interacts with NOTCH2 that is required for the self-renewal maintenance of liver CSCs

http://www.nature.com/ncomms/2015/150519/ncomms8122/images_article/ncomms8122-f4.jpg

(a) C8orf4 interacts with N2ICD. Yeast strain AH109 was co-transfected with Gal4 DNA-binding domain (BD) fused C8orf4 and Gal4-activating domain (AD) fused N2ICD. p53 and large T antigen were used as a positive control. (b) Recombinant Flag-N2ICD and GFP–C8orf4 were incubated for co-immunoprecipitation. (c) The ankyrin repeat AR domain is essential and sufficient for the interaction of C8orf4 with N2ICD. Various N2ICD truncation constructs were co-transfected with GFP–C8orf4 for domain mapping. NLS: nuclear location signal. (d) NOTCH2 was knocked down in Huh7 cells and detected by qRT–PCR and immunoblotting. (e) NOTCH2-silenced Huh7 cells were cultured for sphere formation assays. Two pairs of shRNAs against NOTCH2 obtained similar results. (f,g) Xenograft tumor growth (f) and frequency of tumor-initiating cells (g) for NOTCH2-silenced Huh7 cells were analyzed. (h) NOTCH2 was silenced in HCC primary cells and NOTCH2 depletion declined sphere formation activity. Three HCC specimens obtained similar results. (i) Sphere formation capacity was examined in differently treated HCC primary cells. (j) HCC primary cells were treated with indicated lentivirus and implanted into BALB/c nude mice for xenograft tumor growth assays. Scale bars: e,h,i, 500 μm, Student’s t-test was used for statistical analysis, *P<0.05; **P<0.01; ***P<0.001, data are shown as mean ± standard deviation. Data are representative of at least three independent experiments. IB, immunoblotting; IP, immunoprecipitation; NS, not significant.

To further verify the role of NOTCH2 in the maintenance of liver CSC self-renewal, we knocked down NOTCH2 in Huh7 cells and established stably depleted cell lines by two pairs of NOTCH2 shRNAs (Fig. 4d). NOTCH2 knockdown dramatically reduced sphere formation (Fig. 4e), as well as attenuated xenograft tumor growth and tumor-initiating capacity (Fig. 4f,g). Similar observations were achieved in NOTCH2-depleted HCC primary cells (Fig. 4h). In addition, we found that simultaneous knockdown of NOTCH2 and overexpression of C8orf4 failed to reduce sphere formation capacity compared with individual knockdown of NOTCH2 (Fig. 4i), suggesting that NOTCH2 and C8orf4 affected sphere formation through the same pathway. Meanwhile, C8orf4 knockdown failed to rescue the sphere formation ability of NOTCH2-depleted HCC primary cells (Fig. 4i). Similar observations were obtained in Huh7 cells (Supplementary Fig. 4). Finally, NOTCH2 depletion in C8orf4-silenced Huh7 cells or HCC primary cells also abrogated the C8orf4 depletion-mediated enhancement of xenograft tumor growth (Fig. 4j), suggesting that C8orf4 acted as upstream of NOTCH2 signaling. These data suggest that C8orf4 suppresses the liver CSC stemness through inhibiting the NOTCH2 signaling pathway.

C8orf4 blocks nuclear translocation of N2ICD

As shown in Fig. 1g, C8orf4 was mainly localized in the cytoplasm in tumor cells of HCC samples. To confirm these observations, we stained C8orf4 in several HCC cell lines and noticed that C8orf4 also resided in the cytoplasm of Huh7 cells and Hep3B cells (Fig. 5a and Supplementary Fig. 5a). These results were further validated by cellular fractionation (Fig. 5b). Importantly, C8orf4 KO led to nuclear translocation of N2ICD (Fig. 5c). In addition, we also examined the intracellular location of N2ICD in Huh7 spheres. We found that C8orf4 deletion caused complete nuclear translocation of N2ICD in oncosphere cells (Fig. 5d,e), while N2ICD was mainly located in the cytoplasm of WT oncosphere cells. However, we found that C8orf4 KO did not affect subcellular localization of β-catenin (Supplementary Fig. 5b,c). Through luciferase assays, C8orf4 transfection did not significantly influence promoter transcription activity of Wnt target genes such as TCF1, LEF and SOX4 (Supplementary Fig. 5d). These data indicate that C8orf4 resides in the cytoplasm of HCC cells and inhibits nuclear translocation of N2ICD.

C8orf4 deletion causes the nuclear translocation of N2ICD

C8orf4 deletion causes the nuclear translocation of N2ICD

Figure 5: C8orf4 deletion causes the nuclear translocation of N2ICD.

http://www.nature.com/ncomms/2015/150519/ncomms8122/images_article/ncomms8122-f5.jpg

(a) C8orf4 resides in the cytoplasm of Huh7 cells. Huh7 cells were permeabilized and stained with anti-C8orf4 antibody, then counterstained with PI for confocal microscopy. (b) Cellular fractionation was performed and detected by immunoblotting. (c,d) C8orf4 knockout causes the nuclear translocation of N2ICD. C8orf4-deficient Huh7 cells (c) and sphere cells (d) were permeabilized and stained with anti-C8orf4 and anti-N2ICD antibodies, then counterstained with DAPI followed by confocal microscopy. (e) Cellular fractionation was performed in C8orf4-deficient sphere and WT sphere cells followed by immunoblotting. (f) C8orf4-deficient Huh7 cells were implanted into BALB/c nude mice. Xenograft tumors were analyzed by immunohistochemical staining. Red arrowheads denote nuclear translocation of N2ICD. (g) C8orf4-overexpressing Huh7 cells were permeabilized for immunofluorescence staining. (h) Cellular fractionation was performed in C8orf4-overexpressing Huh7 cells for immunoblotting. (i,j) C8orf4 was overexpressed in N2ICD-overexpressing Huh7 cells followed by immunofluorescence staining (i) and immunoblotting (j). (k) NOTCH target genes were measured in cells treated as in i by real-time PCR. Scale bars: a,c,d,g,i, 10 μm; f, 40 μm. Student’s t-test was used for statistical analysis, **P<0.01;***P<0.001, data are shown as mean±s.d.. Data represent at least three independent experiments.

To further determine whether C8orf4 inhibits the NOTCH2 signaling in the propagation of xenograft tumors, we examined the distribution of N2ICD and NOTCH2 target gene activation inC8orf4-deficient xenograft tumor tissues. We found that C8orf4-deficient tumors displayed much more nuclear translocation of N2ICD compared with WT tumors (Fig. 5f). Expectedly, C8orf4-deficient tumors showed elevated expression levels of NOTCH2 target genes such as HEY1, HES6 and NRARP (Supplementary Fig. 5e). Furthermore, C8orf4 overexpression blocked the nuclear translocation of N2ICD (Fig. 5g,h). Consequently, C8orf4-overexpressing tumors showed much less N2ICD nuclear translocation and reduced expression levels of NOTCH2 target genes compared with control tumors (Supplementary Fig. 5f,g). Of note, C8orf4 overexpression in N2ICD-overexpressing Huh7 cells still blocked nuclear translocation of N2ICD (Fig. 5i,j). Consequently, C8orf4 overexpression abolished the activation of Notch2 signaling (Fig. 5k). These results suggest that C8orf4 deletion causes the nuclear translocation of N2ICD leading to activation of NOTCH2 signaling.

NOTCH2 signalling is required for the stemness of liver CSCs

To further verify the role of NRARP and HEY1 in the maintenance of liver CSC self-renewal, we knocked down these two genes in Huh7 cells and established stably depleted cell lines by two pairs of shRNAs. As expected, NRARP knockdown dramatically reduced sphere formation (Fig. 6a,b). NRARP knockdown also attenuated tumor-initiating capacity and liver CSC ratios (Fig. 6c). Similar results were achieved in NRARP-silenced HCC primary cells (Fig. 6d,e). Similarly, HEY1 silencing remarkably reduced sphere formation derived from Huh7 and HCC primary cells (Fig. 6f–i), as well as declined xenograft tumor growth and tumor-initiating capacity (Supplementary Fig. 6a,b). In sum, NOTCH2 signaling is required for the maintenance of liver CSC self-renewal.

(not shown)

Figure 6: Depletion of NRARP and HEY1 impairs stemness of liver CSCs.

http://www.nature.com/ncomms/2015/150519/ncomms8122/images_article/ncomms8122-f6.jpg

(a,b) NRARP-silenced Huh7 cells were established (a) and showed reduced sphere formation capacity (b). Two pairs of shRNAs against NRARP obtained similar results. (c) NRARP-silenced Huh7 cells decline tumour-initiating capacity (left panel) and reduce liver CSC frequency (right panel). Error bars represent the 95% confidence intervals of the estimation. (d,e) NRARP was knocked down in HCC primary cells (d) and sphere formation was detected (e). Three HCC samples were tested with similar results. (f,g) HEY1-silenced Huh7 cells were established (f) and sphere formation was assayed (g). Two pairs of shRNAs against HEY1 obtained similar results. (h,i) HEY1 was knocked down in HCC primary cells (h) and HEY1 depletion impaired sphere formation capacity (i). Three HCC samples were tested with similar results. Scale bars: b,e,g,i, 500 μm. For a,b,di, Student’s t-test was used for statistical analysis, *P<0.05; **P<0.01;  ***P<0.001, data are shown as mean ± standard deviation. Data are representative of at least three independent experiments.

NOTCH2 signaling is correlated with HCC severity

As shown above, the NOTCH2 signaling was highly activated in liver CSCs and involved in the regulation of liver CSC stemness. We further examined the relationship of NOTCH2 signaling with the progression of HCC. First, we analyzed NOTCH2 activation levels in HCC tumor tissues and peri-tumor tissues derived from Park’s cohort (GSE36376). We observed that HEY1HES6 and NRARP were highly expressed in the tumor tissues of HCC patients (Fig. 7a). Consistently, high expression levels of HEY1HES6 and NRARP in HCC tumors were validated by Zhang’s cohort (GSE25097) (Fig. 7b). Importantly, high expression of these three genes was confirmed in HCC samples through quantitative RT–PCR (Fig. 7c), as well as immunoblotting (Fig. 7d). To confirm a causative link between low C8orf4 expression level and nuclear N2ICD, we examined 93 HCC samples (31 peri-tumor, 37 early stage of HCC patients and 25 advanced stage of HCC patients) with immunohistochemistry staining. We observed that nuclear staining of N2ICD appeared in ~10% tumor cells in the majority of early HCC patients we tested (Fig. 7e,f). In advanced HCC patients, nuclear staining of N2ICD in tumor cells increased to ~30% in almost all the advanced HCC patients we examined. Consequently, HEY1 staining existed in ~10% tumor cells with scattered distribution and increased to 30% tumor cells in the advanced HCC patients (Fig. 7e). Consistently, low expression of C8orf4 was well correlated with activation of NOTCH2 signaling (Fig. 7e,f).

NOTCH2 activation levels are consistent with clinical severity and prognosis of HCC patients

NOTCH2 activation levels are consistent with clinical severity and prognosis of HCC patients

Figure 7: NOTCH2 activation levels are consistent with clinical severity and prognosis of HCC patients.

http://www.nature.com/ncomms/2015/150519/ncomms8122/images_article/ncomms8122-f7.jpg

(a,b) NOTCH target genes were highly expressed in HCC tumour tissues derived from Park’s cohort (a) and Zhang’s cohort (b). (c) High expression levels of NOTCH target genes in HCC tumor tissues were verified by qRT–PCR. (d) HEY1 expression in HCC tumor tissues was detected by western blot. (e) IHC staining for N2ICD, C8orf4 and HEY1. These images represent 93 HCC samples. Scale bars, 50 μm. (f) IHC images were calculated using Image-Pro Plus 6. (g) Expression levels of NOTCH target genes were elevated in HCC tumors and advanced HCC patients derived from Wang’s cohort. (hHEY1 expression level was positively correlated with prognosis prediction of HCC patients analyzed by Petel’s cohort and Wang’s cohort. HCC samples were divided into two groups according to HEY1 expression levels followed by Kaplan–Meier survival analysis. For ac, data are shown as box and whisker plot, Box: interquartile range (IQR); horizontal line within box: median; whiskers: 5–95 percentile. For f,g, Student’s t-test was used for statistical analysis, *P<0.05; **P<0.01; ***P<0.001; data are shown as mean ± standard deviation. Experiments were repeated at least three times. aHCC, advanced HCC; CL, cirrhosis liver; eHCC, early HCC; IL, inflammatory liver; NL, normal liver; NS, not significant.

Serial passages of colonies or sphere formation in vitro, as well as transplantation of tumor cells, are frequently used to assess the long-term self-renewal capacities of CSCs32. We used HCC primary cells for serial passage growth in vitro and tested the expression levels of C8orf4HEY1 and SOX9. We found that C8orf4 expression was gradually reduced over serial passages in oncosphere cells (Supplementary Fig. 7a). Consequently, the expression of NOTCH2 targets such as HEY1 and SOX9 was gradually increased in oncosphere cells during serial passages (Supplementary Fig. 7b). In addition, N2ICD nuclear translocation appeared in oncosphere cells with high expression of HEY1 plus low expression of C8orf4 (termed as C8orf4/N2ICDnuc/HEY1+cells) (Supplementary Fig. 7c). These data suggest that the C8orf4/N2ICDnuc/HEY1+ fraction cells represent a subset of liver CSCs.

Through analyzing Wang’s cohort (GSE54238), we noticed that the NOTCH2 activation levels were positively correlated with the development and progression of HCC (Fig. 7g). By contrast, the NOTCH2 pathway was not activated in inflammation liver, cirrhosis liver and normal liver (Fig. 7f). Consistently, similar observations were achieved by analysis of Zhang’s cohort (GSE25097) (Supplementary Fig. 7d). In addition, the NOTCH2 activation levels were consistent with clinicopathological stages of HCC patients derived from Wang’s cohort (GSE14520) (Supplementary Fig. 7e). Finally, HCC patients with higher expression of HEY1 displayed worse prognosis derived from Petel’s cohort (E-TABM-36) and Wang’s cohort (GSE14520) (Fig. 7h). These two cohorts (E-TABM-36 and GSE14520) have survival information of HCC patients. Taken together, the NOTCH2 activation levels in tumor tissues are consistent with clinical severity and prognosis of HCC patients.

Discussion

CSC have been identified in many solid tumors, including breast, lung, brain, liver, colon, prostate and bladder cancers4633. CSCs have similar characteristics associated with normal tissue stem cells, including self-renewal, differentiation and the ability to form new tumors. CSCs may be responsible for cancer relapse and metastasis due to their invasive and drug-resistant capacities34. Thus, targeting CSCs may become a promising therapeutic strategy to deadly malignancies3536. However, it remains largely unknown about hepatic CSC biology. In this study, we used CD13 and CD133 to enrich CD13+CD133+
subpopulation cells as liver CSCs. Based on analysis of several online-available HCC transcriptome datasets, we found that C8orf4 is weakly expressed in HCC tumors as well as in CD13+CD133+ liver CSCs. NOTCH2 signaling is required for the maintenance of liver CSC self-renewal. C8orf4 resides in the cytoplasm of tumor cells and interacts with N2ICD, blocking the nuclear translocation of N2ICD. Lower expression of C8orf4 causes nuclear translocation of N2ICD that activates NOTCH2 signaling in liver CSCs. NOTCH2 activation levels are consistent with clinical severity and prognosis of HCC patients. Therefore, C8orf4 negatively regulates self-renewal of liver CSCs via suppression of NOTCH2 signaling.

Elucidating signaling pathways that maintains self-renewal of liver CSCs is pivotal for the understanding of hepatic CSC biology and the development of novel therapies against HCC. Several signaling pathways, such as Wnt/β-catenin, transforming growth factor-beta, AKT and STAT3 pathways, have been defined to be implicated in the regulation of liver CSCs37. Not surprisingly, some liver CSC subsets and normal tissue stem cells may share core regulatory genes and common signaling pathways. The NOTCH signaling pathway plays an important role in development via cell-fate determination, proliferation and cell survival3839. The NOTCH family receptors contain four members in mammals (NOTCH1–4), which are activated by binding to their corresponding ligands. A large body of evidence provides that NOTCH signaling is implicated in carcinogenesis40. However, the role of NOTCH signaling in liver cancer is controversial. A previous study reported that NOTCH1 signaling suppresses tumor growth of HCC41. Recently, several reports showed that NOTCH signaling enhances liver tumor initiation424344. Importantly, a recent study showed that various NOTCH receptors have differential functions in the development of liver cancer45. Here we demonstrate that NOTCH2 signaling is activated in HCC tumor tissues and liver CSCs, which is required for the maintenance of liver CSC self-renewal.

C8orf4, also known as TC1, was originally cloned from a papillary thyroid cancer16, 46. The copy number variations of C8orf4 are associated with acute myeloid leukemia and other hematological malignancies19, 47. C8orf4 has been reported to be implicated in various cancers. C8orf4 was highly expressed in thyroid cancer, gastric cancer and breast cancer16, 20, 46. C8orf4 has been reported to enhance Wnt/β-catenin signaling in cancer cells that is associated with poor prognosis20, 21. However, C8orf4 is downregulated in colon cancer48. In this study, we show that C8orf4 is weakly expressed in HCC tumor tissues and liver CSCs. Our observations were confirmed by two HCC cohort datasets. Importantly, C8orf4 negatively regulates the NOTCH2 signaling to suppress the self-renewal of liver CSCs. Therefore, C8orf4 may exert distinct functions in the regulation of various malignancies.

NOTCH receptors consist of noncovalently bound extracellular and transmembrane domains. Once binding with membrane-bound Delta or Jagged ligands, the NOTCH receptors undergoes a proteolytic step by metalloprotease and γ-secretase, generating NECD and NICD fragments11, 31. The NICD, a soluble fragment, is released in the cytoplasm on proteolysis. Then the NICD translocates to the nucleus and binds to the transcription initiation complex, leading to activation of NOTCH-associated target genes49. However, it is largely unclear how the NICD is regulated during NOTCH signaling activation. Here we show that N2ICD binds to C8orf4 in the cytoplasm of liver non-CSC tumor cells, which impedes the nuclear translocation of N2ICD. By contrast, in liver CSCs, lower expression of C8orf4 causes the nuclear translocation of N2ICD, leading to activation of NOTCH signaling.

CSCs or tumour-initiating cells, behave like tissue stem cells in that they are capable of self-renewal and of giving rise to hierarchical organization of heterogeneous cancer cells4. Thus, CSCs harbour the stem cell properties of self-renewal and differentiation. Actually, the CSC model cannot account for tumorigenesis in all tumours. CSCs could undergo genetic evolution, and the non-CSCs might switch to CSC-like cells4. These results highlight the dynamic nature of CSCs, suggesting that the clonal evolution and CSC models can act in concert for tumorigenesis. Furthermore, low C8orf4 expression in tumor cells results in overall Notch2 activation, which then may have more of a progenitor signature and be more aggressive. These cells would likely have a growth advantage in non-adherent conditions and express many of the stemness markers. The dynamic nature of CSCs or persistent NOTCH2 activation may contribute to the high number of C8orf4/N2ICDnuc/HEY1+ cells in advanced HCC tumors and correlation in the patient cohort.

A recent study showed that NOTCH2 and its ligand Jag1 are highly expressed in human HCC tumors, suggesting activation of NOTCH2 signaling in HCC45. In addition, inhibiting NOTCH2 or Jag1 dramatically reduces tumor burden and growth. However, suppression of NOTCH3 has no effect on tumor growth. Dill et al.43 reported that Notch2 is an oncogene in HCC. Notch2-driven HCC are poorly differentiated with a high expression level of the progenitor marker Sox9, indicating a critical role of Notch2 signaling in liver CSCs. Here we found that NOTCH2 and its target genes such as NRARP, HEY1 and HES6 are highly expressed in HCC samples. In addition, depletion of NRARP and HEY1 impairs the stemness maintenance of liver CSCs and tumor propagation. Moreover, the expression levels of NRARP, HEY1 and HES6 in tumors are positively correlated with clinical severity and prognosis of HCC patients. Finally, the NOTCH2 activation status is positively related to the clinicopathological stages of HCC patients. Altogether, C8orf4 and NOTCH2 signaling can be detected for the diagnosis and prognosis prediction of HCC patients, as well as used as targets for eradicating liver CSCs for future therapy.

11.2.3.2 Quantifying the Landscape for Development and Cancer from a Core Cancer Stem Cell Circuit

The authors developed a landscape and path theoretical framework to investigate the global natures and dynamics for a core cancer stem cell gene network. The landscape exhibits four basins of attraction, representing cancer stem cell, stem cell, cancer and normal cell states. They also uncovered certain key genes and regulations responsible for determining the switching between different states. [Cancer Res]

Chunhe Li and Jin Wang
Cancer Res May 13, 2015; 75(10).
http://dx.doi.org:/10.1158/0008-5472.CAN-15-0079

Cancer presents a serious threat to human health. The understanding of the cell fate determination during development and tumor genesis remains challenging in current cancer biology. It was suggested that cancer stem cell (CSC) may arise from normal stem cells, or be transformed from normal differentiated cells. This gives hints on the connection between cancer and development. However, the molecular mechanisms of these cell type transitions and the CSC formation remain elusive. We quantified landscape, dominant paths and switching rates between cell types from a core gene regulatory network for cancer and development. Stem cell, CSC, cancer, and normal cell types emerge as basins of attraction on associated landscape. The dominant paths quantify the transition processes among CSC, stem cell, normal cell and cancer cell attractors. Transition actions of the dominant paths are shown to be closely related to switching rates between cell types, but not always to the barriers in between, due to the presence of the curl flux. During the process of P53 gene activation, landscape topography changes gradually from a CSC attractor to a normal cell attractor. This confirms the roles of P53 of preventing the formation of CSC, through suppressing self-renewal and inducing differentiation. By global sensitivity analysis according to landscape topography and action, we identified key regulations determining cell type switchings and suggested testable predictions. From landscape view, the emergence of the CSCs and the associated switching to other cell types are the results of underlying interactions among cancer and developmental marker genes. This indicates that the cancer and development are intimately connected. This landscape and flux theoretical framework provides a quantitative way to understand the underlying mechanisms of CSC formation and interplay between cancer and development. Major Findings: We developed a landscape and path theoretical framework to investigate the global natures and dynamics for a core cancer stem cell gene network. Landscape exhibits four basins of attraction, representing CSC, stem cell, cancer and normal cell states. We quantified the kinetic rate and paths between different attractor states. We uncovered certain key genes and regulations responsible for determining the switching between different states.

11.2.3.3 IMP3 Promotes Stem-Like Properties in Triple-Negative Breast Cancer by Regulating SLUG

Scientists observed that insulin-like growth factor-2 mRNA binding protein 3 (IMP3) expression is significantly higher in tumor initiating than in non-tumor initiating breast cancer cells and demonstrated that IMP3 contributes to self-renewal and tumor initiation, properties associated with cancer stem cells. [Oncogene]

S Samanta, H Sun, H L Goel, B Pursell, C Chang, A Khan, et al.
Oncogene
 , (18 May 2015) |
http://dx.doi.org:/10.1038/onc.2015.164

IMP3 (insulin-like growth factor-2 mRNA binding protein 3) is an oncofetal protein whose expression is prognostic for poor outcome in several cancers. Although IMP3 is expressed preferentially in triple-negative breast cancer (TNBC), its function is poorly understood. We observed that IMP3 expression is significantly higher in tumor initiating than in non-tumor initiating breast cancer cells and we demonstrate that IMP3 contributes to self-renewal and tumor initiation, properties associated with cancer stem cells (CSCs). The mechanism by which IMP3 contributes to this phenotype involves its ability to induce the stem cell factor SOX2. IMP3 does not interact with SOX2 mRNA significantly or regulate SOX2 expression directly. We discovered that IMP3 binds avidly to SNAI2 (SLUG) mRNA and regulates its expression by binding to the 5′ UTR. This finding is significant because SLUG has been implicated in breast CSCs and TNBC. Moreover, we show that SOX2 is a transcriptional target of SLUG. These data establish a novel mechanism of breast tumor initiation involving IMP3 and they provide a rationale for its association with aggressive disease and poor outcome.

11.2.3.4 Type II Transglutaminase Stimulates Epidermal Cancer Stem Cell Epithelial-Mesenchymal Transition

Researchers investigated the role of type II transglutaminase (TG2) in regulating epithelial mesenchymal transition (EMT) in epidermal cancer stem cells. They showed that TG2 knockdown or treatment with TG2 inhibitor, resulted in a reduced EMT marker expression, and reduced cell migration and invasion. [Oncotarget]

ML Fisher, G Adhikary, W Xu, C Kerr, JW Keillor, RL Ecker
Oncotarget May 08, 2015;

Type II transglutaminase (TG2) is a multifunctional protein that has recently been implicated as having a role in ECS cell survival. In the present study we investigate the role of TG2 in regulating epithelial mesenchymal transition (EMT) in ECS cells. Our studies show that TG2 knockdown or treatment with TG2 inhibitor, results in a reduced EMT marker expression, and reduced cell migration and invasion. TG2 has several activities, but the most prominent are its transamidase and GTP binding activity. Analysis of a series of TG2 mutants reveals that TG2 GTP binding activity, but not the transamidase activity, is required for expression of EMT markers (Twist, Snail, Slug, vimentin, fibronectin, N-cadherin and HIF-1α), and increased ECS cell invasion and migration. This coupled with reduced expression of E-cadherin. Additional studies indicate that NFϰB signaling, which has been implicated as mediating TG2 impact on EMT in breast cancer cells, is not involved in TG2 regulation of EMT in skin cancer. These studies suggest that TG2 is required for maintenance of ECS cell EMT, invasion and migration, and suggests that inhibiting TG2 GTP binding/G-protein related activity may reduce skin cancer tumor survival.

Epidermal squamous cell carcinoma (SCC) is among the most common cancers and the frequency is increasing at a rapid rate [1,2]. SCC is treated by surgical excision, but the rate of recurrence approaches 10% and the recurrent tumors are aggressive and difficult to treat [2]. We propose that human epidermal cancer stem (ECS) cells survive at the site of tumor excision, that these cells give rise to tumor regrowth, and that therapies targeted to kill ECS cells constitute a viable anti-cancer strategy. An important goal in this context is identifying and inhibiting activity of key proteins that are essential for ECS cell survival. Working towards this goal, we have developed systems for propagation of human ECS cells [3]. These cells display properties of cancer stem cells including self-renew and high level expression of stem cell marker proteins [3].

In the present study we demonstrate that ECS cells express proteins characteristic of cells undergoing EMT (epithelial-mesenchymal transition). EMT is a morphogenetic process whereby epithelial cells lose epithelial properties and assume mesenchymal characteristics [4]. The epithelial cells lose cell-cell contact and polarity, and assume a mesenchymal migratory phenotype. There are three types of EMT. This first is an embryonic process, during gastrulation, when the epithelial sheet gives rise to the mesoderm [5]. The second is a growth factor and cytokine-stimulated EMT that occurs at sites of tissue injury to facilitate wound repair [6]. The third is associated with epithelial cancer cell acquisition of a mesenchymal migratory/invasive phenotype. This process mimics normal EMT, but is not as well controlled and coordinated [478]. A number of transcription factors (ZEB1, ZEB2, snail, slug, and twist) that are expressed during EMT suppress expression of epithelial makers, including E-cadherin, desmoplakin and claudins [4]. Snail proteins also activate expression of vimentin, fibronectin and metalloproteinases [4]. Snail factors are not present in normal epithelial cells, but are present in the tumor cells and are prognostic factors for poor survival [4].

An important goal is identifying factors that provide overarching control of EMT in cancer stem cells. In this context, several recent papers implicate type II transglutaminase (TG2) as a regulator of EMT [912]. TG2, the best studied transglutaminase, was isolated in 1957 from guinea pig liver extract as an enzyme involved in the covalent crosslinks proteins via formation of isopeptide bonds [13]. However, subsequent studies reveal that TG2 also serves as a scaffolding protein, regulates cell adhesion, and modulates signal transduction as a GTP binding protein that participates in G protein signaling [14]. TG2 is markedly overexpressed in cancer cells, is involved in cancer development [1518], and has been implicated in maintaining and enhancing EMT in breast and ovarian cancer [10121920]. The G protein function may have an important role in these processes [102123].

In the present manuscript we study the role of TG2 in regulating EMT in human ECS cells. Our studies show that TG2 is highly enriched in ECS cells. We further show that these cells express EMT markers and that TG2 is required to maintain EMT protein expression. TG2 knockdown, or treatment with TG2 inhibitor, reduces EMT marker expression and ECS cell survival, invasion and migration. TG2 GTP binding activity is absolutely required for maintenance of EMT protein expression and EMT-related responses. However, in contrast to breast cancer [910], we show that TG2 regulation of EMT is not mediated via NFκB signaling.

TG2 is required for expression of EMT markers

EMT is a property of tumor stem cells that confers an ability to migrate and invade surrounding tissue [2426]. We first examined whether ECS cells express EMT markers. Non-stem cancer cells and ECS cells, derived from the SCC-13 cancer cell line, were analyzed for expression of EMT markers. Fig. 1A shows that a host of EMT transcriptional regulators, including Twist, Snail and Slug, are increased in ECS cells (spheroid) as compared to non-stem cancer cells (monolayer). This is associated with increased levels of vimentin, fibronectin and N-cadherin, which are mesenchymal proteins, and reduced expression of E-cadherin, an epithelial marker. HIF-1α, an additional marker frequently associated with EMT, is also elevated. We next examined whether TG2 is required to maintain EMT marker expression. SCC-13 cell-derived ECS cells were grown in the presence of control- or TG2-siRNA, to reduce TG2, and the impact on EMT marker level was measured. Fig. 1B shows that loss of TG2 is associated with reduced expression of Twist, Snail, vimentin and HIF-1α. To further assess the role of TG2, we utilized SCC13-Control-shRNA and SCC13-TG2-shRNA2 cell lines. These lines were produced by infection of SCC-13 cells with lentiviruses encoding control- or TG2-specific shRNA. Fig. 1C shows that SCC13-TG2-shRNA2 cells express markedly reduced levels of TG2 and that this is associated with reduced expression of EMT associated transcription factors and target proteins, and increased expression of E-cadherin. To confirm this, we grew SCC13-Control-shRNA and SCC13-TG2-shRNA2 cells as monolayer cultures for immunostain detection of EMT markers. As shown in Fig. 2A, TG2 levels are reduced in TG2-shRNA expressing cells, and this is associated with the anticipated changes in epithelial and mesenchymal marker expression.

Tumor cells that express EMT markers display enhanced migration and invasion ability [2426]. We therefore examined the impact of TG2 reduction on these responses. To measure invasion, control-shRNA and TG2-shRNA cells were monitored for ability to move through matrigel. Fig. 2B shows that loss of TG2 reduces movement through matrigel by 50%. We further show that this is associated with a reduction in cell migration using a monolayer culture wound closure assay. The control cells close the wound completely within 14 h, while TG2 knockdown reduces closure rate (Fig. 2C).

TG2 inhibitor reduces EMT marker expression and EMT functional responses

NC9 is a recently developed TG2-specific inhibitor [2728]. We therefore asked whether pharmacologic inhibition of TG2 suppresses EMT. SCC-13 cells were treated with 0 or 20 μM NC9. Fig. 3A shows that NC9 treatment reduces EMT transcription factor (Twist, Snail, Slug) and EMT marker (vimentin, fibronectin, N-cadherin, HIF-1α) levels. Consistent with these changes, the level of the epithelial marker, E-cadherin, is elevated. Fig. 3B and 3C show that pharmacologic inhibition of TG2 activity also reduces EMT biological response. Invasion (Fig. 3B) and cell migration (Fig. 3C) are also reduced.

Identification of TG2 functional domain required for EMT

We next performed studies to identify the functional domains and activities required for TG2 regulation of EMT. TG2 is a multifunctional enzyme that serves as a scaffolding protein, as a transamidase, as a kinase, and as a GTP binding protein [21]. The two best studied functions are the transamidase and GTP binding/G-protein related activities [21]. Transamidase activity is observed in the presence of elevated intracellular calcium, while GTP binding-related signaling is favored by low calcium conditions (reviewed in [21]). To identify the TG2 activity required for EMT, we measured the ability of wild-type and mutant TG2 to restore EMT in SCC13-TG2-shRNA2 cells, which have reduced TG2 expression (Fig. 4A). SCC13-TG2-shRNA2 cells display reduced expression of EMT markers including Twist, Snail, Slug, vimentin, fibronectin, N-cadherin and HIF-1α, and increased expression of the epithelial maker, E-cadherin, as compared to SCC13-Control-shRNA cells. Expression of wild-type TG2, or the TG2-C277S or TG2-W241A mutants, restores marker expression in SCC13-TG2-shRNA2 cells (Fig. 4A). TG2-C277S and TG2-W241A lack transamidase activity [10,2931]. In contrast, TG2-R580A, which lacks G-protein activity [2931], and TG2-Y516F, which retains only partial G-protein activity [30], do not efficiently restore marker expression. These findings suggest that the TG2 GTP binding function is required for EMT.

We next assayed the ability of the TG2 mutants to restore EMT functional responses-invasion and migration. Fig. 4B4C shows that wild-type TG2, TG2-C277S and TG2-W241A restore the ability of SCC13-TG2-shRNA2 cells to invade matrigel, but TG2-R580A and Y516F are less active. Fig. 4D shows a similar finding for cell migration, in that the TG2-R580A and Y517F mutant are only partially able to restore SCC13-TG2-shRNA2 cell migration. These findings suggest that TG2 GTP binding/G-protein related activity is required for EMT-related migration and invasion by skin cancer cells.

Role of TG2 in regulating EMT in A431 cells

The number of available epidermis-derived squamous cell carcinoma cell lines is limited, and so we compared our findings with A431 cells. A431 cells are squamous cell carcinoma cells established from human vulvar skin. A431 cells were grown as monolayer (non-stem cancer cells) and spheroids (ECS cells) and after 10 d the cells were harvested and assayed for expression of TG2 and EMT makers. Fig. 5A shows that TG2 levels are elevated in ECS cells and that this is associated with increased levels of mesenchymal markers, including Twist, Snail, Slug, vimentin, fibronectin, N-cadherin and HIF-1α. In contrast, E-cadherin levels are reduced. We next examined the impact of TG2 knockdown on EMT marker expression. Fig. 5B shows that mesenchymal markers are globally reduced and E-cadherin level is increased. As a biological endpoint of EMT, we examine the impact of TG2 knockdown on spheroid formation and found that TG2 loss leads to reduced spheroid formation (Fig. 5C). We next examined the impact of NC9 treatment on EMT and found a reduction in EMT markers expression associated with an increase in epithelial (E-cadherin) marker level (Fig. 5D). This loss of EMT marker expression is associated with reduced matrigel invasion (Fig. 5E), reduced spheroid formation (Fig. 5F) and reduced cell migration (Fig. 5G).

Role of NFκB

Previous studies in breast [183236], ovarian cancer [123738], and epidermoid carcinoma [11] indicate that NFκB signaling mediates TG2 impact on EMT. We therefore assessed the role of NFκB in skin cancer cells. As shown in Fig. 6A, the increase in TG2 level observed in ECS cells (spheroids) is associated with reduced NFκB level. In addition, NFκB level is increased in TG2 knockdown cells (Fig. 6B). Thus, increased NFκB is not associated with increased TG2. We next assessed the impact of NFκB knockdown on TG2 control of EMT marker expression. Fig. 6C shows that TG2 is required for increased expression of EMT markers (HIF-1α, snail, twist, N-cadherin, vimentin and fibronectin) and reduced expression of the E-cadherin epithelial marker; however, knockdown of NFκB expression does not interfere with TG2 regulation of these endpoints. We next examined the effect of TG2 knockdown on NFκB and IκBα localization. The fluorescence images in Fig. 6D suggest that TG2 knockdown with TG2-siRNA does not alter the intracellular localization of NFκB or IκBα. This is confirmed by subcellular fractionation assay (Fig. 6E) which compares NFκB level in SCC13-TG2-Control and SCC13-TG2-shRNA2 (TG2 knockdown) cells. We also monitored NFκB subcellular distribution following treatment with NC9, the TG2 inhibitor. Fig. 6F shows that cytoplasmic/nuclear distribution of NFκB is not altered by NC9. Finally, we monitored the impact of TG2 expression on NFκB binding to a canonical NFκB-response element. Increased NFκB binding to the response element is a direct measure of NFκB activity [10]. Fig. 6G shows that overall binding is reduced in nuclear (N) extract prepared from ECS cells (spheroids) as compared to non-stem cancer cells (monolayer), and that NFkB binding, as indicated by gel supershift assay, is also slightly reduced in ECS cell extracts. These findings indicate that NFkB binding is slightly reduced in ECS cells, which are TG2-enriched (Fig. 1A).

We next monitored the role of NFκB on biological endpoints of EMT. Fig. 7A and 7B show that TG2 knockdown reduces migration through matrigel, but NFκB knockdown has no impact. Likewise, TG2 knockdown reduces wound closure, but NFκB knockdown does not. These findings suggest that NFκB does not mediate the pro-EMT actions of TG2 in epidermal squamous cell carcinoma.

The metastatic cascade, from primary tumor to metastasis, is a complex process involving multiple pathways and signaling cascades [3941]. Cells that complete the metastatic cascade migrate away from the primary tumor through the blood to a distant site and there form a secondary tumor. Identifying the mechanisms that allow cells to survive this journey and form secondary tumors is an important goal. The processes involved in epithelial-mesenchymal transition (EMT) are important cancer therapy targets, as EMT is associated with enhanced cancer cell migration and stem cell self-renewal. EMT regulators, including Snail, Twist, Slug, are increased in expression in EMT and control expression of genes associated with the EMT phenotype [42].

TG2 is required for EMT

We have characterized a population of ECS cells derived from epidermal squamous cell carcinoma [3]. The present studies show that these cells, which display enhanced migration and invasion, possess elevated levels of TG2. Moreover, these cells are enriched in expression of transcription factors associated with EMT (Snail, Slug, and Twist, HIF-1α) as well as mesenchymal structural proteins including vimentin, fibronectin and N-cadherin. Consistent with a shift to mesenchymal phenotype, E-cadherin, an epithelial marker, is reduced in level. Additional studies show that TG2 knockdown results in a marked reduction in EMT marker expression and that this is associated with reduced ability of the cells to migrate to close a scratch wound and reduced movement in matrigel invasion assays. We also examined the impact of treatment with a TG2 inhibitor. NC9 is an irreversible active site inhibitor of TG2, that locks the enzyme in an open conformation [284345]. NC9 treatment of ECS cells results in decreased levels of Snail, Slug and Twist. These transcription factors suppress E-cadherin expression [46] and their decline in level is associated with increased levels of E-cadherin. NC9 inhibition of TG2 also reduces expression of vimentin, fibronectin and N-cadherin, and these changes are associated with reduced cell migration and reduced invasion through matrigel.

(Figures are not shown)

We also examined the role of TG2 in A431 squamous cell carcinoma cells derived from the vulva epithelium. TG2 is elevated in A431-derived ECS cells, as are EMT markers, and knockdown of TG2, with TG2-siRNA, reduces EMT marker expression and spheroid formation. Studies with NC9 indicate that NC9 inhibits A431 spheroid formation, EMT, migration and invasion. These studies indicate that TG2 is also required for EMT and migration and invasion in A431 cells. Based on these findings we conclude that TG2 is essential for EMT, migration and invasion, and is likely to contribute to metastasis in squamous cell carcinoma.

TG2 GTP binding activity is required for EMT

TG2 is a multifunctional enzyme that can act as a transamidase, GTP binding protein, protein disulfide isomerase, protein kinase, protein scaffold, and DNA hydrolase [21294447]. The two most studied functions are the transamidase and GTP binding functions [294447]. To identify the TG2 activity responsible for induction of EMT, we studied the ability of TG2 mutants to restore EMT in SCC13-TG2-shRNA2 cells, which express low levels of TG2 and do not express elevated levels of EMT markers or display EMT-related biological responses. These studies show that wild-type TG2 restores EMT marker expression and the ability of the cells to migrate on plastic and invade matrigel. TG2 mutants that retain GTP binding activity (TG2-C277S and TG2-W241A) also restore EMT. In contrast, TG2-R580A, which lacks GTP binding function, does not restore EMT. This evidence suggests that the GTP binding function is essential for TG2 induction of the EMT phenotype in ECS cells. Recent reports suggest that the TG2 is important for maintenance of stem cell survival in breast [91017] and ovarian [123848] cancer cells. Moreover, our findings are in agreement of those of Mehta and colleagues who reported that the TG2 GTP binding function, but not the crosslinking function, is required for TG2 induction of EMT in breast cancer cells [10].

TG2, NFκB signaling and EMT

To gain further insight into the mechanism of TG2 mediated EMT, we examined the role of NFκB. NFκB has been implicated as mediating EMT in breast, ovarian, and pancreatic cancer; however, NFκB may have a unique role in epidermal squamous cell carcinoma. In keratinocytes, NFκB has been implicated in keratinocyte dysplasia and hyperproliferation [49]. However, inhibition of NFκB function has also been shown to predispose murine epidermis to cancer [50]. Here we show that TG2 levels are elevated and NFκB levels are reduced in ECS cells as compared to non-stem cancer cells, and that TG2 knockdown is associated with increased NFκB level. In addition, TG2 knockdown, or inhibition of TG2 by treatment with NC9, does not altered the nuclear/cytoplasmic distribution of NFκB. We further show that elevated levels of TG2 in spheroid culture results in a slight reduction in NFκB binding to the NFκB response element, as measured by gel mobility supershift assay. These molecular assays strongly suggest that NFκB does not mediate the action of TG2 in epidermal cancer stem cells. Moreover, knockdown of NFκB-p65 in TG2 positive cells does not result in a reduction in Snail, Slug and Twist, or mesenchymal marker proteins expression, and concurrent knockdown of TG2 and NFκB does not reduce EMT marker protein levels beyond that of TG2 knockdown alone. These findings suggest that NFκB is not an intermediary in TG2-stimulated EMT in ECS cells. This is in contrast to the required role of NFκB in mediating TG2 induction of cell survival and EMT in breast cancer cells [183233] and ovarian cancer [123738] and epidermoid carcinoma [11].

11.2.3.5 CD24+ Ovarian Cancer Cells are Enriched for Cancer Initiating Cells and Dependent on JAK2 Signaling for Growth and Metastasis

Investigators showed that CD24+ and CD133+ cells have increased tumorsphere forming capacity. CD133+ cells demonstrated a trend for increased tumor initiation while CD24+ cells vs CD24– cells, had significantly greater tumor initiation and tumor growth capacity. [Mol Cancer Ther]

D Burgos-OjedaR Wu, K McLean, Yu-Chih Chen, M Talpaz, et al.
Molec Cancer Ther May 12, 2015; 14(5)
http://dx.doi.org:/10.1158/1535-7163.MCT-14-0607

Ovarian cancer is known to be composed of distinct populations of cancer cells, some of which demonstrate increased capacity for cancer initiation and/or metastasis. The study of human cancer cell populations is difficult due to long requirements for tumor growth, inter-patient variability and the need for tumor growth in immune-deficient mice. We therefore characterized the cancer initiation capacity of distinct cancer cell populations in a transgenic murine model of ovarian cancer. In this model, conditional deletion of Apc, Pten, and Trp53 in the ovarian surface epithelium (OSE) results in the generation of high grade metastatic ovarian carcinomas. Cell lines derived from these murine tumors express numerous putative stem cell markers including CD24, CD44, CD90, CD117, CD133 and ALDH. We show that CD24+ and CD133+ cells have increased tumor sphere forming capacity. CD133+ cells demonstrated a trend for increased tumor initiation while CD24+ cells vs CD24- cells, had significantly greater tumor initiation and tumor growth capacity. No preferential tumor initiating or growth capacity was observed for CD44+, CD90+, CD117+, or ALDH+ versus their negative counterparts. We have found that CD24+ cells, compared to CD24- cells, have increased phosphorylation of STAT3 and increased expression of STAT3 target Nanog and c-myc. JAK2 inhibition of STAT3 phosphorylation preferentially induced cytotoxicity in CD24+ cells. In vivo JAK2 inhibitor therapy dramatically reduced tumor metastases, and prolonged overall survival. These findings indicate that CD24+ cells play a role in tumor migration and metastasis and support JAK2 as a therapeutic target in ovarian cancer.

11.2.3.6 EpCAM-Antibody-Labeled Noncytotoxic Polymer Vesicles for Cancer Stem Cells-Targeted Delivery of Anticancer Drug and siRNA

Researchers designed and synthesized a novel anti-epithelial cell adhesion molecule (EpCAM)-monoclonal-antibody-labeled cancer stem cells (CSCs)-targeting, noncytotoxic and pH-sensitive block copolymer vesicle as a nano-carrier of anticancer drug and siRNA. [Biomacromolecules]

Jing Chen , Qiuming Liu , Jiangang Xiao , and Jianzhong Du
Biomacromolecules May 19, 2015. (just published)
http://dx.doi.org:/10.1021/acs.biomac.5b00551

Cancer stem cells (CSCs) have the capability to initiate tumor, to sustain tumor growth, to maintain the heterogeneity of tumor, and are closely linked to the failure of chemotherapy due to their self-renewal and multilineage differentiation capability with an innate resistance to cytotoxic agents. Herein, we designed and synthesized a novel anti-EpCAM (epithelial cell adhesion molecule)-monoclonal-antibody-labeled CSCs-targeting, noncytotoxic and pH-sensitive block copolymer vesicle as a nano-carrier of anticancer drug and siRNA (to overcome CSCs drug resistance by silencing the expression of oncogenes). This vesicle shows high delivery efficacy of both anticancer drug doxorubicin hydrochloride (DOX∙HCl) and siRNA to the CSCs because it is labeled by the monoclonal antibodies to the CSCs-surface-specific marker. Compared to non-CSCs-targeting vesicles, the DOX∙HCl or siRNA loaded CSCs-targeting vesicles exhibited much better CSCs killing and tumor growth inhibition capabilities with lower toxicity to normal cells (IC50,DOX decreased by 80%), demonstrating promising potential applications in nanomedicine.

11.2.3.7 Survival of Skin Cancer Stem Cells Requires the Ezh2 Polycomb Group Protein

Investigators showed that Ezh2 is required for epidermal cancer stem (ECS) cell survival, migration, invasion and tumor formation, and that this is associated with increased histone H3 trimethylation on lysine 27, a mark of Ezh2 action. They also showed that Ezh2 knockdown or treatment with Ezh2 inhibitors, GSK126 or EPZ-6438, reduced Ezh2 level and activity, leading to reduced ECS cell spheroid formation, migration, invasion and tumor growth. [Carcinogenesis]

G Adhikary, D Grun, S Balasubramanian, C Kerr, J Huang and RL Eckert
Carcinogenesis (2015)
http://dx.doi.org:/10.1093/carcin/bgv064

Polycomb group (PcG) proteins, including Ezh2, are important candidate stem cell maintenance proteins in epidermal squamous cell carcinoma. We previously showed that epidermal cancer stem cells (ECS cells) represent a minority of cells in tumors, are highly enriched in Ezh2 and drive aggressive tumor formation. We now show that Ezh2 is required for ECS cell survival, migration, invasion and tumor formation, and that this is associated with increased histone H3 trimethylation on lysine 27, a mark of Ezh2 action. We also show that Ezh2 knockdown or treatment with Ezh2 inhibitors, GSK126 or EPZ-6438, reduces Ezh2 level and activity, leading to reduced ECS cell spheroid formation, migration, invasion and tumor growth. These studies indicate that epidermal squamous cell carcinoma cells contain a subpopulation of cancer stem (tumor-initiating) cells that are enriched in Ezh2, that Ezh2 is required for optimal ECS cell survival and tumor formation, and that treatment with Ezh2 inhibitors may be a strategy for reducing epidermal cancer stem cell survival and suppressing tumor formation.

11.2.3.8 Inhibition of STAT3, FAK and Src mediated signaling reduces cancer stem cell load, tumorigenic potential and metastasis in breast cancer

R Thakur, R Trivedi, N Rastogi, M Singh & DP Mishra
Scientific Reports May 14, 2015; 5(10194)
http://dx.doi.org:/10.1038/srep10194

Cancer stem cells (CSCs) are responsible for aggressive tumor growth, metastasis and therapy resistance. In this study, we evaluated the effects of Shikonin (Shk) on breast cancer and found its anti-CSC potential. Shk treatment decreased the expression of various epithelial to mesenchymal transition (EMT) and CSC associated markers. Kinase profiling array and western blot analysis indicated that Shk inhibits STAT3, FAK and Src activation. Inhibition of these signaling proteins using standard inhibitors revealed that STAT3 inhibition affected CSCs properties more significantly than FAK or Src inhibition. We observed a significant decrease in cell migration upon FAK and Src inhibition and decrease in invasion upon inhibition of STAT3, FAK and Src. Combined inhibition of STAT3 with Src or FAK reduced the mammosphere formation, migration and invasion more significantly than the individual inhibitions. These observations indicated that the anti-breast cancer properties of Shk are due to its potential to inhibit multiple signaling proteins. Shk also reduced the activation and expression of STAT3, FAK and Src in vivo and reduced tumorigenicity, growth and metastasis of 4T1 cells. Collectively, this study underscores the translational relevance of using a single inhibitor (Shk) for compromising multiple tumor-associated signaling pathways to check cancer metastasis and stem cell load.

Breast cancer is the most common endocrine cancer and the second leading cause of cancer-related deaths in women. In spite of the diverse therapeutic regimens available for breast cancer treatment, development of chemo-resistance and disease relapse is constantly on the rise. The most common cause of disease relapse and chemo-resistance is attributed to the presence of stem cell like cells (or CSCs) in tumor tissues12. CSCs represent a small population within the tumor mass, capable of inducing independent tumors in vivo and are hard to eradicate2. Multiple signaling pathways including Receptor Tyrosine Kinase (RTKs), Wnt/β-catenin, TGF-β, STAT3, Integrin/FAK, Notch and Hedgehog signaling pathway helps in maintaining the stem cell programs in normal as well as in cancer cells3456. These pathways also support the epithelial-mesenchymal transition (EMT) and expression of various drug transporters in cancer cells. Cells undergoing EMT are known to acquire stem cell and chemo-resistant traits7. Thus, the induction of EMT programs, drug resistance and stem cell like properties are interlinked7. Commonly used anti-cancer drugs eradicate most of the tumor cells, but CSCs due to their robust survival mechanisms remain viable and lead to disease relapse8. Studies carried out on patient derived tumor samples and in vivo mouse models have demonstrated that the CSCs metastasize very efficiently than non-CSCs91011. Therefore, drugs capable of compromising CSCs proliferation and self-renewal are urgently required as the inhibition of CSC will induce the inhibition of tumor growth, chemo-resistance, metastasis and metastatic colonization in breast cancer.

Shikonin, a natural dietary component is a potent anti-cancer compound1213. Previous studies have shown that Shk inhibits the cancer cell growth, migration, invasion and tumorigenic potential12. Shk has good bioavailability, less toxicity and favorable pharmacokinetic and pharmacodynamic profiles in vivo12. In a recent report, it was shown that the prolonged exposure of Shk to cancer cells does not cause chemo-resistance13.Other studies have shown that it inhibits the expression of various key inflammatory cytokines and associated signaling pathways1214. It decreases the expression of TNFα, IL12, IL6, IL1β, IL2, IFNγ, inhibits ERK1/2 and JNK signaling and reduces the expression of NFκB and STAT3 transcription factors1415. It inhibits proteasome and also modulates the cancer cell metabolism by inhibiting tumor specific pyurvate kinase-M214,1516. Skh causes cell cycle arrest and induces necroptosis in various cancer types14. Shk also inhibits the expression of MMP9, integrin β1 and decreases invasive potential of cancer cells1417. Collectively, Shk modulates various signaling pathways and elicits anti-cancer responses in a variety of cancer types.

In breast cancer, Shk has been reported to induce the cell death and inhibit cell migration, but the mechanisms responsible for its effect are not well studied1819. Signaling pathways modulated by Shk in cancerous and non-cancerous models have previously been shown important for breast cancer growth, metastasis and tumorigenicity20. Therefore in the current study, we investigated the effect of Shk on various hallmark associated properties of breast cancer cells, including migration, invasion, clonogenicity, cancer stem cell load and in vivo tumor growth and metastasis.

Shk inhibits cancer hallmarks in breast cancer cell lines and primary cells

We first examined the effect of Shk on various cancer hallmark capabilities (proliferation, invasion, migration, colony and mammosphere forming potential) in breast cancer cells. MTT assay was used to find out effect of Shk on viability of breast cancer cells. Semi-confluent cultures were exposed to various concentrations of Shk for 24 h. Shk showed specific anti-breast cancer activity with IC50 values ranging from 1.38 μM to 8.3 μM in MDA-MB 231, MDA-MB 468, BT-20, MCF7, T47D, SK-BR-3 and 4T1 cells (Fig. 1A). Whereas the IC50 values in non-cancerous HEK-293 and human PBMCs were significantly higher indicating that it is relatively safe for normal cells (Fig. S1A). Shk was found to induce necroptotic cell death consistent with previous reports (Fig. S1B). Treatment of breast cancer cells for 24 h with 1.25 μM, 2.5 μM and 5.0 μM of Shk significantly reduced their colony forming potential (Fig. 1B). To check the effect of Shk on the heterogeneous cancer cell population, we tested it on patient derived primary breast cancer cells. Shk reduced the viability and colony forming potential of primary breast cancer cells in dose dependent manner (Fig. 1C,D). Further we checked its effects on migration and invasion of breast cancer cells. Shk (2.5 μM) significantly inhibited the migration of MDA-MB 231, MDA-MB 468, MCF7 and 4T1 cells (Fig. 1E). It also inhibited the cell invasion in dose dependent manner (Fig. 1F and S1CS1DS1E,S1F). We further examined its effect on mammosphere formation. MDA-MB 231, MDA-MB 468, MCF7 and 4T1 cell mammosphere cultures were grown in presence or absence of 1.25 μM, 2.5 μM and 5.0 μM Shk for 24 h. After 8 days of culture, a dose dependent decrease in the mammosphere forming potential of these cells was observed (Figs. 1G,H). Collectively, these results indicated that Shk effectively inhibits the various hallmarks associated with aggressive breast cancer.

(not shown)

Figure 1: Shk inhibits multiple cancer hallmarks

Shk reduces cancer stem cell load in breast cancer

As Shk exhibited strong anti-mammosphere forming potential; therefore it was further examined for its anti-cancer stem cell (CSC) properties. Cancer stem cell loads in breast cancer cells were assessed using Aldefluor assay which measures ALDH1 expression. MDA-MB 231 cells with the highest number of ALDH1+ cells were selected for further studies (Fig. S2A). We also checked the correlation between ALDH1 expression and mammosphere formation. Sorted ALDH1+ cells were subjected to mammosphere cultures. ALDH1+ cells formed highest number of mammospheres compared to ALDH1-/low and parent cell population, indicating that ALDH1+ cells are enriched in CSCs (Fig. S2B). Shk reduced the Aldefluor positive cells in MDA-MB 231 cells after 24 h of treatment (Fig. 2A,B). Next, we examined the effect of Shk on the expression of stem cell (Sox2, Oct3/4, Nanog, AldhA1 and c-Myc) and EMT (Snail, Slug, ZEB1, Twist, β-Catenin) markers, associated with the sustenance of breast CSCs. Shk (2.5 μM) treatment for 24 h reduced the expression of these markers (Fig. 2C and S2D). Shk also reduced protein expression of these markers in dose dependent manner (Fig. 2D,E and S2C).

(not shown)

Figure 2: Shk decreases stem cell load in breast cancer cells and enriched CD44+,CD24−/low breast cancer stem cells.

To further confirm anti-CSC properties of Shk, we checked the effect of shikonin on the load of CD44+ CD24− breast CSCs in MCF7 cells grown on matrigel. Shikonin reduced CD44+ CD24− cell load in dose dependent manner after 24 h of treatment (Fig S2E). We also tested its effects on the enriched CSC population. CD44+ CD24− cells were enriched from MCF7 cells using MagCellect CD24− CD44+ Breast CSC Isolation Kit (Fig. S2F). Enriched CSCs formed highest number of mammosphere in comparison to parent MCF7 cell population or negatively selected CD24+ cells (Fig. S2G). Enriched CSCs were treated with indicated doses of Shk (0.625 μM, 1.25 μM and 2.5 μM) for 24 h and were either analyzed for ALDH1 positivity or subjected to colony or mammosphere formation. 2.5 μM dose of Shk reduced ALDH1+ cells by 50% and inhibited colony and mammosphere formation (Fig. S2H2F2G and 2H). Shk also reduced the mRNA expression of CSC markers in CD44+ CD24− cells and patient derived primary cancer cells (Fig. 2I,J). These results collectively indicated that Shk inhibits CSC load and associated programs in breast cancer.

Shk is a potent inhibitor of STAT3 and poorly inhibits FAK and Src

To identify the molecular mechanism responsible for anti-cancer properties of Shk, we used a human phospho-kinase antibody array to study a subset of phosphorylation events in MDA-MB 231 cells after 6h of treatment with 2.5 μM Shk. Amongst the 46 phospho-antibodies spotted on the array, the relative extent of phosphorylation of three proteins decreased to about ≳ 2 fold (STAT3, 3.3 fold; FAK, 2.5 fold and Src, 1.8 fold) upon Shk treatment (Fig. 3A,B). These proteins (STAT3, FAK and Src) are known to regulate CSC proliferation and self renewal212223. Therefore, we focused on these proteins and the result of kinase-array was confirmed by western blotting. Shk effectively inhibits STAT3 at early time point (1 h) while activation of FAK and Src decreased on or after 3 h (Fig. 3C) confirming Shk as a potent inhibitor of STAT3. Shk also reduced the protein expression of STAT3, FAK and Src at 24 h (Fig. 3C).

(not shown)

Figure 3. Shk inhibits STAT3, FAK and Src signaling pathways.

We also observed that Shk does not inhibit JAK2 at initial time-points (Fig. 3C). This raised a possibility that Shk either regulates STAT3 independent of JAK2 or it binds directly to STAT3. To check the first probability, we activated STAT3 by treating the cells with IL6 (100 ng ml−1) for 1 h followed by treatment with Shk (2.5 μM) for 1 h. Both immunofluorescence and western-blotting results showed that Shk inhibited activated STAT3 without inhibiting JAK2 (Fig. S3AS3B) confirming that Shk inhibits JAK2 mediated activation of STAT3 possibly by binding directly to STAT3. For further confirmation, we performed an in silico molecular docking analysis to examine binding of Shk with the STAT3 SH2 domain. In a major conformational cluster, Shk occupied Lys-707, Lys-709 and Phe-710 binding sites in the STAT3 SH2 domain similar to the STAT3 standard inhibitor S3I-201 (Fig. S3C and S3D). The binding energy of Shk to STAT3 was −4.20 kcal mol−1. Collectively, these results showed that Shk potently inhibits STAT3 activation and also attenuates FAK and Src activation.

STAT3, Src and FAK are differentially expressed and activated in breast CSCs (BCSCs)

STAT3 and FAK are known to play an important role in proliferation and self-renewal of CSCs in various cancer types including breast cancer212224. Src also support CSC phenotype in some cancer types, but there are limited reports of its involvement in breast cancer25. Therefore, we checked the expression and activation of STAT3, FAK and Src in CSCs and non-CSCs. Here we used two methods to enrich the CSCs and non-CSCs. In the first method, the MDA-MB 231 cells were subjected to mammosphere formation for 96 h. After 96 h, mammosphere and non-mammosphere forming cells were clearly visible (Fig. 4A). These mammosphere and non-mammosphere forming cells were separated by using a 70 micron cell strainer. Mammospheres were subjected to two subculture cycles to enrich CSCs. With each passage, the viable single cells (non-mammosphere forming cells) and mammospheres were collected in RIPA lysis buffer and western blotting was done (Fig. 4B). We found that the activation and expression of the STAT3, FAK and Src is higher in enriched mammosphere cultures (Fig. 4C). In the second method, CD44+ CD24− cells were isolated from MCF7 cultures using MagCellect Breast CSC Isolation Kit. STAT3, FAK and Src activation and their mRNA and protein expression were assessed in enriched CSCs and were compared to parent MCF7 cell population. STAT3, FAK and Src all were differentially activated in CSCs (Fig. 4E). High mRNA as well as protein expressions of all the three genes was also observed in CSCs (Fig. 4D,E). Collectively, these results indicate that STAT3, FAK and Src are over expressed and activated in BCSCs.

Figure 4: STAT3, FAK and Src are differentially activated and expressed in breast cancer cells.

  • Representative picture indicating mammosphere and single suspended cells. (B) Schematic outline of mammosphere enrichment. (C) Protein expression and activation of STAT3, FAK and Src was determined in single suspended cells (non-mammosphere forming cells) and mammospheres by western blot. The full size blots corresponding to the cropped blot images are given in  S10. (D) Gene expression of STAT3, FAK and Src was determined in MCF7 parent population and CD44+ CD24−/low MCF7 cells using PCR. The full agarose gel images corresponding to the cropped images are given in Fig. S10. (E) Protein expression and activation of STAT3, FAK and Src was in CD44+ 24− cells and parent population.
STAT3, FAK and Src are differentially activated and expressed in breast cancer cells.

STAT3, FAK and Src are differentially activated and expressed in breast cancer cells.

http://www.nature.com/srep/2015/150514/srep10194/images_article/srep10194-f4.jpg

STAT3 is important for mammosphere formation and CSC programs in breast cancer

As our results indicated that the expression and activation of STAT3, FAK and Src is high in BCSCs and Shk is capable of inhibiting these signaling proteins; therefore to find out functional relevance of each protein and associated effects on their pharmacological inhibition by Shk, we used specific inhibitors against these three. Effect of these inhibitors was first tested on the mammosphere forming potential of MDA-MB 231, MDA-MB 468 and MCF7 cells. A drastic reduction in the mammosphere formation was observed upon STAT3 inhibition. FAK and Src inhibition also reduced the primary and secondary mammosphere formation but STAT3 inhibition showed most potent effect (Fig. 5A and S4). Further, we also checked the effect of these inhibitors on the expression of various CSC and EMT related markers in MDA-MB 231 cells. STAT3 inhibition decreased the expression of most of the CSC and EMT markers (Fig. 5B). These two findings indicated that STAT3 inhibition is more effective in reducing mammosphere forming potential and weakens major CSC programs and the anti-CSC potential of Shk is possibly due to its strong STAT3 inhibitory effect.
(not shown)

STAT3, FAK and Src activation status correlates with mammosphere forming potential in breast cancer

STAT3, FAK and Src activation status correlates with mammosphere forming potential in breast cancer

Figure 5: STAT3, FAK and Src activation status correlates with mammosphere forming potential in breast cancer.

http://www.nature.com/srep/2015/150514/srep10194/carousel/srep10194-f5.jpg

(A) Bar graph represents number of mammospheres formed from 2500 cells in presence and absence of indicated treatments. MDA-MB 231, MDA-MB 468 and MCF7 24 h mammosphere cultures were treated with Shk (2.5 μM), FAK inhibitor (FAK inhibitor 14; 2.5 μM), Src inhibitor (AZM 475271; 10 μM) and STAT3 inhibitor (WP1066; 10 μM). After 24 h, treatments were removed and cells were allowed to grow in fresh mammosphere culture media for 8 days. (B) Expression of various stem cell and EMT related transcription factors and markers were detected using western blotting in MDA-MB 231 cells with or without indicated treatments. The full size blots corresponding to the cropped blot images are given in Fig. S10. (C) MDA-MB 231, MDA-MB 468 and MCF7 cells were pre-treated with either IL6 (100 ng ml−1), Fibronectin (1 μg ml−1) or EGF (25 ng ml−1) for two population doublings and subjected to mammosphere formation. Bar graph represents average of three independent experiments. (D) MCF7 cells were pre-treated with either IL6 (100 ng ml−1), Fibronectin (1 μg ml−1) or EGF (25 ng ml−1) for two population doublings and subjected to mammosphere formation. After 24 h, cells were treated with DMSO (untreated) or Shk (treated) as indicated in the bar graph. Data are shown as the mean ±SD. (*) p < 0.05 and (**) p < 0.01.

To further check the involvement of these pathways in CSCs, we cultured MDA-MB 231, MDA-MB 468 and MCF7 cells in the presence of either IL6 (100ng ml−1), EGF (25 ng ml−1) or Fibronectin (1 μg ml−1) coated surface for two population doublings. Cells were then subjected to mammosphere formation. In IL6 pre-treated cultures, there was a sharp rise in mammosphere formation, indicating that the STAT3 activation shifts CSC and non-CSC dynamics towards CSCs (Fig. 5C). IL6 is previously known to induce the conversion of non-CSC to CSC via STAT3 activation26. In MCF7 cells, mammosphere forming potential after IL6 pre-treatment increased nearly by three fold. Therefore, we further checked the effectiveness of Shk on mammosphere forming potential in pre-treated MCF7 cells. It was found that Shk inhibits mammosphere formation most effectively in IL6 pre-treated cultures (Fig. 5D). However, in EGF and Fibronectin pre-treated cultures, Shk was relatively less effective. This was possibly due to its weak FAK and Src inhibitory potential. Collectively, these results illustrated that STAT3 activation is significantly correlated with the mammosphere forming potential of breast cancer cells and its inhibition by a standard inhibitor or Shk potently reduce the mammosphere formation.

Shk inhibit CSCs load by disrupting the STAT3-Oct3/4 axis

In breast cancer, STAT3 mediated expression of Oct3/4 is a major regulator of CSC self-renewal2627. As we observed that both Shk and STAT3 inhibitors decreased the Oct3/4 expression (Figs. 2C and 5B), we further checked the effect of STAT3 activation on ALDH1+ CSCs and Oct3/4 expression. On IL6 pre-treatment, number of ALDH1+ cells increased in all three (MDA-MB 231, MDA-MB 468 and MCF7) cancer cells (Fig. 6A). MCF7 cells showed highest increase. Therefore, to check the effect of STAT3 inhibition on CSC load, we incubated IL6 pre-treated MCF7 cells with Shk and STAT3 inhibitor for 24 h and analyzed for ALDH1 positivity. It was observed that both Shk and STAT3 inhibitor reduced the IL6 induced ALDH1 positivity from 10% to < 2% (Fig. 6B). These results suggested that Shk induced inhibition of STAT3 and decrease in BCSC load is interlinked. We further checked the effect of STAT3 activation status on Oct3/4 expression in MDA-MB 231, MDA-MB 468 and MCF7 cells. We observed that expression of Oct3/4 increases with the increase in STAT3 activation (Fig. 6C–E).

(not shown)

Figure 6: STAT3 activation status and its effect on cancer stem cell load

STAT3 transcriptional activity is important in maintaining CSC programs2829. Therefore, we also examined the effect of Shk on STAT3 promoter activity. STAT3 reporter assay was performed in presence of IL6 and Shk; it was found that Shk reduced the promoter activity of STAT3 in a dose dependent manner (Fig. S5). Collectively, these results showed that Shk mediated STAT3 inhibition are responsible for decrease in CSC load and Oct3/4 associated stem cell programs.

Shk inhibits mammosphere formation, migration and invasion through inhibition of STAT3, FAK and Src in breast cancer cells

As the earlier results (Fig. 1) showed that Shk inhibits cell migration and invasion in breast cancer cells, we further examined the effect of STAT3, FAK and Src inhibitors on cell migration and invasion in MDA-MB 231 cells. It was found that STAT3 inhibitor poorly inhibits cell migration while both Src and FAK inhibitors were effective in reducing cell migration (Fig. 7A). All the three inhibitors decreased the cell invasion and MMP9 expression significantly (Fig. 7B and S6). It was also observed that effect of all these inhibitors, except STAT3 inhibitor on mammosphere formation and FAK inhibitor on cell migration, were not comparable to that of Shk. Shk inhibited all these properties more effectively than individual inhibition of STAT3, FAK and Src. This made us to assume that the ability of Shk to inhibit multiple signaling molecules simultaneously is the reason behind its potent anti-cancer effect. To check this notion, we combined STAT3, FAK and Src inhibitors with each other and examined the effect of combinations on invasion, migration and mammosphere forming potential in MDA-MB 231 cells. We observed further decrease in cell migration and invasion on combining STAT3 and FAK, STAT3 and Src, or FAK and Src (Figs. 7A,B). Combination of FAK and Src was not very effective in inhibiting mammosphere formation in MDA-MB 231 cells and CD44+ CD24− MCF7 CSCs. However, their combination with STAT3 decreased the mammosphere forming potential equivalent to that of Shk (Fig. 7C,D). We also compared the mammosphere forming potential of Shk with Salinomycin (another anti-CSC agent) and found that at 2.5 μM dose of Shk was almost two times more potent than Salinomycin (Fig. S7). Collectively, these results indicated that Shk inhibits multiple signaling proteins (STAT3, FAK and Src) to compromise various aggressive breast cancer hallmarks.

Figure 7: Combination of FAK, Src and STAT3 inhibitors is more potent than individual inhibition against various cancer hallmarks.

combination-of-fak-src-and-stat3-inhibitors-is-more-potent-than-individual-inhibition-against-various-cancer-hallmarks

combination-of-fak-src-and-stat3-inhibitors-is-more-potent-than-individual-inhibition-against-various-cancer-hallmarks

http://www.nature.com/srep/2015/150514/srep10194/images_article/srep10194-f7.jpg

  • Cell migration and (B) cell invasion potential of MDA-MB 231 cells was assessed in the presence of Shk (2.5 μM), FAK inhibitor (FAK inhibitor 14; 2.5 μM), Src inhibitor (AZM 475271; 10 μM) and STAT3 inhibitor (WP1066; 10 μM). Various combinations of these inhibitors were also used STAT3+FAK inhibitor (WP1066; 10 μM + FAK inhibitor 14; 2.5 μM), STAT3 + Src Inhibitor (WP1066; 10 μM + AZM 475271; 10 μM) and FAK+Src Inhibitor (FAK inhibitor 14; 2.5 μM + AZM 475271; 10 μM). Cell migration and cell invasion was assessed through scratch cell migration assay and transwell invasion after 24 h of treatments. (C,D) Mammosphere forming potential of MDA-MB 231 cells and CD44+ CD24−/low enriched MCF7 cells was assessed in presence of similar combination of STAT3+FAK inhibitor (WP1066; 10 μM + FAK inhibitor 14; 2.5 μM), STAT3 + Src Inhibitor (WP1066; 10 μM+ AZM 475271; 10 μM) and FAK + Src Inhibitor (FAK inhibitor 14; 2.5 μM + AZM 475271; 10 μM). Cells were subjected to mammosphere cultures for 24 h and treated with the indicated inhibitors for next 24 h, followed by media change and growth of mammospheres were monitored for next 8 days. Data are shown as the mean ±SD. (**) p < 0.01.

Shk inhibits breast cancer growth, metastasis and decreases tumorigenicity

To explore whether Shk may have therapeutic potential for breast cancer treatment in vivo, we tested Shk against 4T1-induced breast cancer syngenic mouse model. 4T1 cells (mouse breast cancer cells) are capable of growing fast and metastasize efficiently in vivo30. Prior to the in vivo experiments, we checked the effect of Shk on ALDH1 positivity and on activation of STAT3, FAK and Src in 4T1 cells in vitro. Shk effectively decreased the ALDH1+ cells and inhibited STAT3, FAK and Src in 4T1 cells in vitro (Fig. S8A and S8B). For in vivo tumor generation, 1 × 106 cells were injected subcutaneously in the fourth nipple mammary fat pad of BALB/c mice. When the average size of tumors reached around 50 mm3, mice were divided into three groups, vehicle and two Shk treated groups each received either 2.5 mg Kg−1 or 5.0 mg Kg−1 Shk. Shk was administered via the intraperitoneal injection on every alternate day. It significantly suppressed the tumor growth in 4T1 induced syngenic mouse model (Fig. 8A). The average reduction in 4T1 tumor growth was 49.78% and 89.73% in 2.5 mg Kg−1 and 5.0 mg Kg−1 groups respectively compared with the vehicle treated group (Fig. 8A). No considerable change in body weight of the treated group animals was observed (Fig. S9A). We further examined the effect of Shk on the tumor initiating potential of breast cancer cells. 4T1 induced tumors were excised from the control and treatment groups on the second day after 4th dose of Shk was administered. Tumors were dissociated; cells were allowed to adhere and then re-injected into new animals for secondary tumor formation. Growth of secondary tumors was monitored till day 15 post-reinjection. Shk treated groups showed a marked decrease in secondary tumor formation (Fig. 8D). We also observed a drastic reduction in the number of metastatic nodules in the lungs of treatment group animals (Fig. 8F). The reduction in the metastatic load was not proportional to the decrease in tumor sizes; however within the treatment group, some animals with small tumors were carrying higher number of metastatic nodules. As FAK is an important mediator of cancer metastasis and metastatic colonization, we further examined the effects of Shk on metastatic colonization. For this, 1 × 105 4T1 cells were injected to BALB/c mice through tail vein. Animals were divided into three groups, as indicated above. Shk and vehicle were administered through intraperitoneal injections at alternate days starting from the 2nd day post tail vein injections till 33rd day. The average reduction in total number of metastatic nodules was 88.6% – 90.5% in Shk treated mice compared to vehicle control (Fig. 8F). An inset picture (Fig. 8A lower panel) represents lung morphology of vehicle control and treated groups. We further examined the activation and expression status of STAT3, FAK and Src between vehicle control and treated group tumors. There were low expression and activation of STAT3, FAK and Src in treated tumors as compared to the vehicle control (Fig. 8B,C). Similar trend was observed in ALDH1 expressions (Fig. 8B). Further, the mice tumor sections were subjected to immunohistochemistry, immunofluorescence and hematoxylin and eosin (H&E) staining to study histology and expression of key proteins being examined in this study. Fig. 8G shows representative images of H&E staining, proliferating cell nuclear antigen (PCNA), terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL), STAT3 and Oct3/4 immunostaining. PCNA expression was low while TUNEL positive cells were high in tumor tissues of Shk treated groups. STAT3 and Oct3/4 expression was low in Shk treated groups. These results collectively demonstrated that Shk modulates the expression and activation of STAT3, FAK and Src in vivo and is effective in suppressing tumorigenic potential and metastasis in syngenic mouse model.

Figure 8: Shk inhibits breast cancer growth, tumorigenicity and metastasis in vivo.

Shk inhibits breast cancer growth, tumorigenicity and metastasis in vivo

Shk inhibits breast cancer growth, tumorigenicity and metastasis in vivo

http://www.nature.com/srep/2015/150514/srep10194/images_article/srep10194-f8.jpg

  • Shk inhibited 4T1 tumor growth. Bar graph represents the average tumor volumes in vehicle control and Shk treated tumor bearing mice (n = 6). (*) p < 0.05 and (**) p < 0.01. Inset picture of upper panel represents tumor sizes and lower pane represents lung morphology in vehicle control and Shk treatment groups. (B) Western blot examination of indicated proteins for their expression and activation in vehicle control and treated tumor groups. The full size blots corresponding to the cropped blot images are given in Fig. S10. (C) Gene expression of stem cell and EMT markers in tumor tissues excised from the vehicle control and Shk treated groups (n = 3). (D) Number of secondary tumors formed after injecting indicated cell dilutions from Vehicle treated and Shk treated 4T1 tumors. (E) Number of lung nodules formed in mice injected with 4T1 mouse mammary tumor cells in the mammary fat pad and administered with 2.5 mg Kg−1 Shk or vehicle control on every alternate day for 3 weeks (n = 6). (F) Number of lung nodules in mice injected with 4T1 mouse mammary tumor cells through tail vein and administered with 2.5 mg Kg−1 Shk or vehicle control on every alternate day for 3 weeks. (n = 8) (G) Representative panel of the histological H&E staining, immunofluorescence staining for the STAT3, Oct3/4, cell proliferation marker PCNA and DNA damage indicator-TUNEL staining of tumor sections from vehicle and treatment groups.

Recent studies have shown that aggressiveness, therapy resistance and disease relapse in breast cancer is attributed to a small population of CSCs involved in continuous self-renewal and differentiation through signaling pathways similar to that of the normal stem cells31. Therapeutic targeting of CSCs therefore, has profound clinical implications for cancer treatment31. Recent studies indicated that therapies / agents targeting both differentiated cancer cells and CSCs may possibly have significant therapeutic advantages32. Therefore, it is imperative to look for novel therapeutic agents with lesser side effects urgently for effective targeting of CSCs. In search of novel, nontoxic anti-CSC agents, attention has been focused on natural agents in recent times33,34. In this study, we have used a natural napthoquinone compound, Shk with established antitumorigenic, favorable pharmacokinetic and toxicity profiles and report for the first time its potent anti-CSC properties. Shk significantly inhibits breast cancer cell proliferation in vitroex vivoand in vivo. It decreases the cell migration and invasion of breast cancer cells in vivo, as well as inhibits tumorigenicity, metastasis and metastatic colonization in a syngenic mouse model of breast cancer in vivo. These finding suggest a strong potential of Shk in breast cancer therapy.

We assessed the effect of Shk on the CSC load in breast cancer cells through various functional assays (tumorsphere in vitro and syngenic mouse model of breast cancer in vivo) and quantification of specific stem cell markers. In breast cancer, CD44+ CD24− cells and ALDH1+ cells are considered to be BCSCs2125. Shk significantly decreased the mammosphere formation (Fig. 1HS1G and 2H), ALDH1+ cell and CD44+ CD24− cell loads in vitro (Fig. 2BS2E and S2H). It also reduced the expression of CSC markers (Oct3/4, Sox2, Nanog, c-Myc and Aldh1) in vivo andin vitro (Fig. 2C,DS2C and S2D). These genes are known to regulate stem cell programs and in cancer, they are established promoters and regulators of CSC phenotype353637383940. Decrease in the expression of these genes on Shk treatment indicates its potential to suppress CSC programs. Tumor initiating potential (tumorigenicity) is the bona fide measure of CSCs. Reduction in the tumorigenic potential of cells isolated form Shk treated tumors indicates in vivoanti-CSC effects of Shk.

We further demonstrated that Shk is a potent inhibitor of STAT3 and it also inhibits FAK and Src (Fig. 3A–C). Its STAT3 inhibitory property was found to be responsible for its anti-CSC effects (Figs. 6B and 7B). STAT3 and FAK inhibitors are previously known to compromise CSC growth41,42. Here, we found that pharmacological inhibition of STAT3 was more effective in compromising CSC load than FAK and Src inhibitions (Fig. 5A). STAT3 activation through IL6 increases mammosphere formation more significantly than Src and FAK activation through EGF and Fibronectin (Fig. 5C). This indicates that IL6-STAT3 axis is a key regulator of BCSC dynamics.

11.2.3.9 Ovatodiolide Sensitizes Aggressive Breast Cancer Cells to Doxorubicin Anticancer Activity, Eliminates Their Cancer Stem Cell-Like Phenotype, and Reduces Doxorubicin-Associated Toxicity

Investigators evaluated the usability of ovatodiolide (Ova) in sensitizing triple negative breast cancer (TNBC) cells to doxorubicin (Doxo), cytotoxicity, so as to reduce Doxo effective dose and consequently its adverse effects. Ova-sensitized TNBC cells also lost their cancer stem cell-like phenotype evidenced by significant dissolution and necrosis of formed mammospheres, as well as their terminal differentiation. [Cancer Lett]

11.2.3.10 Glabridin Inhibits Cancer Stem Cell-Like Properties of Human Breast Cancer Cells: An Epigenetic Regulation of miR-148a/SMAd2 Signaling

The authors report that glabridin (GLA) attenuated the cancer stem cell (CSC)-like properties through microRNA-148a (miR-148a)/transforming growth factor beta-SMAD2 signal pathway in vitro and in vivo. In MDA-MB-231 and Hs-578T breast cancer cell lines, GLA enhanced the expression of miR-148a through DNA demethylation. [Mol Carcinog]

11.2.3.11 Ginsenoside Rh2 Inhibits Cancer Stem-Like Cells in Skin Squamous Cell Carcinoma

The effects of ginsenoside Rh2 (GRh2) on Lgr5-positive cancer stem cells (CSCs) were determined by flow cytometry and by tumor sphere formation. Scientists found that GRh2 dose-dependently reduced skin squamous cell carcinoma viability, possibly through reduced the number of Lgr5-positive CSCs. [Cell Physiol Biochem]

Liu S. Chen M. Li P. Wu Y. Chang C. Qiu Y. Cao L. Liu Z. Jia C.
Cell Physiol Biochem 2015;36:499-508
http://dx.doi.org:/10.1159/000430115

Background/Aims: Treatments targeting cancer stem cells (CSCs) are most effective cancer therapy, whereas determination of CSCs is challenging. We have recently reported that Lgr5-positive cells are cancer stem cells (CSCs) in human skin squamous cell carcinoma (SCC). Ginsenoside Rh2 (GRh2) has been shown to significantly inhibit growth of some types of cancers, whereas its effects on the SCC have not been examined. Methods: Here, we transduced human SCC cells with lentivirus carrying GFP reporter under Lgr5 promoter. The transduced SCC cells were treated with different doses of GRh2, and then analyzed cell viability by CCK-8 assay and MTT assay. The effects of GRh2 on Lgr5-positive CSCs were determined by fow cytometry and by tumor sphere formation. Autophagy-associated protein and β-catenin were measured by Western blot. Expression of short hairpin small interfering RNA (shRNA) for Atg7 and β-catenin were used to inhibit autophagy and β-catenin signaling pathway, respectively, as loss-of-function experiments. Results: We found that GRh2 dose-dependently reduced SCC viability, possibly through reduced the number of Lgr5-positive CSCs. GRh2 increased autophagy and reduced β-catenin signaling in SCC cells. Inhibition of autophagy abolished the effects of GRh2 on β-catenin and cell viability, while increasing β-catenin abolished the effects of GRh2 on autophagy and cell viability. Conclusion: Taken together, our data suggest that GRh2 inhibited SCC growth, possibly through reduced the number of Lgr5-positive CSCs. This may be conducted through an interaction Carcinoma account for more than 80% of all types of cancer worldwide, and squamous cell carcinoma (SCC) is the most frequent carcinoma. Skin SCC causes a lot of mortality yearly, which requires a better understanding of the molecular carcinogesis of skin SCC for developing efficient therapy [1,2]. Ginsenoside Rh2 (GRh2) is a characterized component in red ginseng, and has proven therapeutic effects on inflammation [3] and a number of cancers [4,5,6,7,8,9,10,11,12,13,14], whereas its effects on the skin SCC have not been examined.

Cancer stem cells (CSCs) are cancer cells with great similarity to normal stem cells, e.g., the ability to give rise to various cell types in a particular cancer [15,16]. CSCs are highly tumorigenic, compared to other non-CSCs. CSCs appear to persist in tumors as a distinct population and CSCs are believed to be responsible for cancer relapse and metastasis after primary tumor resection [15,16,17,18]. Recently, the appreciation of the critical roles of CSCs in cancer therapy have been continuously increasing, although the identification of CSCs in a particular cancer is still challenging.

To date, different cell surface proteins have been used to isolate CSCs from a variety of cancers by flow cytometry. Among these markers for identification of CSCs, the most popular ones are prominin-1 (CD133), side population (SP) and increased activity of aldehyde dehydrogenase (ALDH). CD133 is originally detected in hematopoietic stem cells, endothelial progenitor cells and neuronal and glial stem cells. Later on, CD133 has been shown to be expressed in the CSCs from some tumors [19,20,21,22,23], but with exceptions [24]. SP is a sub-population of cells that efflux chemotherapy drugs, which accounts for the resistance of cancer to chemotherapy. Hoechst (HO) has been experimentally used for isolation of SP cells, while the enrichment of CSCs by SP appears to be limited [25]. Increased activity of ALDH, a detoxifying enzyme responsible for the oxidation of intracellular aldehydes [26,27], has also been used to identify CSCs, using aldefluor assay [28,29]. However, ALDH has also been detected in other cell types, which creates doubts on the purity of CSCs using ALDH method [30,31]. Moreover, all these methods appear to be lack of cancer specificity.

The Wnt target gene Lgr5 has been recently identified as a stem cell marker of the intestinal epithelium, and of the hair follicle [32,33]. Recently, we reported that Lgr5 may be a potential CSC marker for skin SCC [34]. We detected extremely high Lgr5 levels in the resected skin SCC specimen from the patients. In vitro, Lgr5-positive SCC cells grew significantly faster than Lgr5-negative cells, and the fold increase in growth of Lgr5-positive vs Lgr5-negative cells is significantly higher than SP vs non-SP, or ALDH-high vs ALDH-low, or CD133-positive vs CD133-negative cells. Elimination of Lgr5-positive SCC cells completely inhibited cancer cell growth in vitro.

Here, we transduced human SCC cells with lentivirus carrying GFP reporter under Lgr5 promoter. The transduced SCC cells were treated with different doses of GRh2, and then analyzed cell viability by CCK-8 assay and MTT assay. The effects of GRh2 on Lgr5-positive CSCs were determined by flow cytometry and by tumor sphere formation. Autophagy-associated protein and β-catenin were measured by Western blot. Expression of short hairpin small interfering RNA (shRNA) for autophagy-related protein 7 (Atg7) and β-catenin were used to inhibit autophagy and β-catenin signaling pathway, respectively, as loss-of-function experiments. Atg7 was identified based on homology to Pichia pastoris GSA7 and Saccharomyces cerevisiae APG7. In the yeast, the protein appears to be required for fusion of peroxisomal and vacuolar membranes. The protein shows homology to the ATP-binding and catalytic sites of the E1 ubiquitin activating enzymes. Atg7 is a mediator of autophagosomal biogenesis, and is a putative regulator of autophagic function [35,36,37,38]. We found that GRh2 dose-dependently reduced SCC viability, possibly through reduced the number of Lgr5-positive CSCs. GRh2 increased autophagy and reduced β-catenin signaling in SCC cells. Inhibition of autophagy abolished the effects of GRh2 on β-catenin and cell viability, while increasing β-catenin abolished the effects of GRh2 on autophagy and cell viability.

Transduction of SCC cells with GFP under Lgr5 promoter

We have recently shown that Lgr5 is CSC marker for skin SCC [34]. In order to examine the role of GRh2 on SCC cells, as well as a possible effect on CSCs, we transduced human skin SCC cells A431 [34] with a lentivirus carrying GFP reporter under Lgr5 promoter (Fig. 1A). The Lgr5-positive cells were green fluorescent in culture (Fig. 1B), and could be analyzed or isolated by flow cytometry, based on GFP (Fig. 1C).

(not shown)

Fig. 1. Transduction of SCC cells with GFP under Lgr5 promoter. (A) The structure of lentivirus carrying GFP reporter under Lgr5 promoter. (B) The pLgr5-GFP-transduced A431 cells in culture. Lgr5-positive cells were green fluorescent. Nuclear staining was done by DAPI. (C) Representative flow chart for analyzing pLgr5-GFP-transduced A431 cells by flow cytometry based on GFP. Gated cells were Lgr5-positive cells. Scar bar is 20µm.

GRh2 dose-dependently inhibits SCC cell growth

Then, we examined the effect of GRh2 on the viability of SCC cells. We gave GRh2 at different doses (0.01mg/ml, 0.1mg/ml and 1mg/ml) to the cultured pLgr5-GFP-transduced A431 cells. We found that from 0.01mg/ml to 1mg/ml, GRh2 dose-dependently deceased the cell viability in either a CCK-8 assay (Fig. 2A), or a MTT assay (Fig. 2B). Next, we questioned whether GRh2 may have a specific effect on CSCs in SCC cells. Thus, we analyzed GFP+ cells, which represent Lgr5-positive CSCs in pLgr5-GFP-transduced A431 cells after GRh2 treatment. We found that GRh2 dose-dependently deceased the percentage of GFP+ cells, by representative flow charts (Fig. 2C), and by quantification (Fig. 2D). We also examined the capability of the GRh2-treated cells in the formation of tumor sphere. We found that GRh2 dose-dependently deceased the formation of tumor sphere-like structure, by quantification (Fig. 2E), and by representative images (Fig. 2F). Together, these data suggest that GRh2 dose-dependently inhibited SCC cell growth, possibly through inhibition of CSCs.

Fig. 2. GRh2 dose-dependently inhibits SCC cell growth. We gave GRh2 at different doses (0.01mg/ml, 0.1mg/ml and 1mg/ml) to the cultured pLgr5-GFP-transduced A431 cells. (A-B) GRh2 dose-dependently deceased the cell viability in either a CCK-8 assay (A), or a MTT assay (B). (C-D) GFP+ cells after GRh2 treatment were analyzed by flow cytometry, showing that GRh2 dose-dependently deceased the percentage of GFP+ cells, by representative flow charts (C), and by quantification (D). The capability of the GRh2-treated cells to form tumor sphere-like structures was examined, shown by quantification (E), and by representative images (F). *p

http://www.karger.com/Article/ShowPic/430115?image=000430115_f02.JPG

GRh2 treatment decreases β-catenin and increases autophagy in SCC cells

We analyzed the molecular mechanisms underlying the cancer inhibitory effects of GRh2 on SCC cells. We thus examined the growth-regulatory proteins in SCC. From a variety of proteins, we found that GRh2 treatment dose-dependently decreases β-catenin, and dose-dependently upregulated autophagy-related proteins Beclin, Atg7 and increased the ratio of LC3 II to LC3 I, by quantification (Fig. 3A), and by representative Western blots (Fig.3B). Since β-catenin signaling is a strong cell-growth stimulator and autophagy can usually lead to stop of cell-growth and cell death, we feel that the alteration in these pathways may be responsible for the GRh2-mediated suppression of SCC growth.

(not shown)

Figure 3. GRh2 treatment decreases β-catenin and increases autophagy in SCC cells.

http://www.karger.com/Article/ShowPic/430115?image=000430115_f03.JPG

Inhibition of autophagy abolishes the effects of GRh2 on β-catenin

In order to find out the relationship between β-catenin and autophagy in this model, we inhibited autophagy using a shRNA for Atg7, and examined its effect on the changes of β-catenin by GRh2. First, the inhibition of Atg7 in A431 cells by shAtg7 was confirmed by RT-qPCR (Fig. 4A), and by Western blot (Fig. 4B). Inhibition of Atg7 resulted in abolishment of the effects of GRh2 on other autophagy-associated proteins (Fig. 4B), and resulted in abolishment of the inhibitory effect of GRh2 on β-catenin (Fig. 4B). Moreover, the effects of GRh2 on cell viability were completely inhibited (Fig. 4C). Together, inhibition of autophagy abolishes the effects of GRh2 on β-catenin. Thus, the regulation of GRh2 on β-catenin needs autophagy-associated proteins.

Fig. 4. Inhibition of autophagy abolishes the effects of GRh2 on β-catenin.

A431 cells were transfected with shRNA for Atg7, or scrambled sequence (scr) as a control. (A) RT-qPCR for Atg7. (B) Quantification of β-catenin, Beclin, Atg7 and LC3 by Western blot. (C) Cell viability by CCK-8 assay. *p

http://www.karger.com/Article/ShowPic/430115?image=000430115_f04.JPG

Overexpression of β-catenin abolishes the effects of GRh2 on autophagy

Next, we inhibited the effects of GRh2 on β-catenin by overexpression of β-catenin in A431 cells. First, the overexpression of β-catenin in A431 cells was confirmed by RT-qPCR (Fig. 5A), and by Western blot (Fig. 5B). Overexpression of β-catenin resulted in abolishment of the effects of GRh2 on autophagy-associated proteins (Fig. 5B). Moreover, the effects of GRh2 on cell viability were completely inhibited (Fig. 5C). Together, inhibition of β-catenin signaling abolishes the effects of GRh2 on autophagy. Thus, the regulation of GRh2 on autophagy needs β-catenin signaling. This model is thus summarized in a schematic (Fig. 6), suggesting that GRh2 may target both β-catenin signaling and autophagy, which interacts with each other in the regulation of SCC cell viability and growth.

http://www.karger.com/Article/ShowPic/430115?image=000430115_f05.JPG

Fig. 5. Overexpression of β-catenin abolishes the effects of GRh2 on autophagy. A431 cells were transfected with β-catenin, or scrambled sequence (scr) as a control. (A) RT-qPCR for β-catenin. (B) Quantification of β-catenin, Beclin, Atg7 and LC3 by Western blot. (C) Cell viability by CCK-8 assay. *p

http://www.karger.com/Article/ShowPic/430115?image=000430115_f06.JPG

Fig. 6. Schematic of the model. GRh2 may target both β-catenin signaling and autophagy, which interacts with each other in the regulation of SCC cell viability and growth.

Understanding the cancer molecular biology of skin SCC and identification of an effective treatment are both critical for improving the current therapy [1]. Lgr5 has been recently identified as a novel stem cell marker of the intestinal epithelium and the hair follicle, in which Lgr5 is expressed in actively cycling cells [32,33]. Moreover, we recently showed that Lgr5-positive are CSCs in skin SCC [34]. Thus, specific targeting Lgr5-positive cells may be a promising therapy for skin SCC.

In the current study, we analyzed the effects of GRh2 on the viability of SCC. Importantly, we not only found that GRh2 dose-dependently decreases SCC cell viability, but also dose-dependently decreased the number of Lgr5-positive CSCs in SCC cells. These data suggest that the CSCs in SCC may be more susceptible for the GRh2 treatment, and the decreases in CSCs may result in the decreased viability in total SCC cells. This point was supported by following mechanism studies. Activated β-catenin signaling by WNT/GSK3β prevents degradation of β-catenin and induces its nuclear translocation [39]. Nuclear β-catenin thus activates c-myc, cyclinD1 and c-jun to promote cell proliferation, and activates Bcl-2 to inhibit apoptosis [39]. High β-catenin levels thus are a signature of CSCs. Therefore, it is not surprising that CSCs are more affected than other cells when GRh2 targets β-catenin signaling.

In addition, GRh2 appears to target autophagy. Although altered metabolism may be beneficial to the cancer cells, it can create an increased demand for nutrients to support cell growth and proliferation, which creates metabolic stress and subsequently induces autophagy, a catabolic process leading to degradation of cellular components through the lysosomal system [40]. Cancer cells use autophagy as a survival strategy to provide essential biomolecules that are required for cell viability under metabolic stress [40]. However, autophagy not only results in a staring in cell growth, but also may result in cell death [40]. Increases in autophagy may substantially decrease cancer cell growth. Thus, GRh2 has its inhibitory effect on skin SCC cells through a combined effect on cell proliferation (by decreasing β-catenin) and autophagy [40].

Interestingly, our data suggest an interaction between β-catenin and autophagy. This finding is consistent with previous reports showing that autophagy negatively modulates Wnt/β-catenin signaling by promoting Dvl instability [41,42], and with other studies showing that β-catenin regulates autophagy [38,43,44].

Of note, we have checked other SCC lines and essentially got same results. Together with our previous reports showing that Lgr5-positive cells are CSCs in skin SCC [34], these findings thus highlight a future engagement of Lgr5-directed GRh2 therapy, which could be performed in a sufficiently frequent manner, to substantially improve the current treatment for skin SCC.

Normal vs Cancer Thyroid Stem Cells: The Road to Transformation
The authors discuss new insights into thyroid stem cells as a potential source of cancer formation in light of the available information on the oncogenic role of genetic modifications that occur during thyroid cancer development. Understanding the fine mechanisms that regulate tumor transformation may provide new ground for clinical intervention in terms of prevention, diagnosis and therapy. [Oncogene] Abstract
Cancer Stem Cells: A Potential Target for Cancer Therapy
The identification of cancer stem cells (CSCs) and a better understanding of the complex characteristics of CSCs will provide invaluable diagnostic, therapeutic and prognostic targets for clinical application. The authors introduce the dysregulated properties of CSCs in cancers and discuss the possible challenges in targeting CSCs for cancer treatment. [Cell Mol Life Sci] Abstract
Targeting Cancer Stem Cells Using Immunologic Approaches
Wicha, M; Chang, A; Yingxin, X; Xiaolian, Z; Ning, N; Liu, Shuang, Q, L; Pan, Q
Stem Cells 2015-04-15 4.15 | Apr 22
Targeting Notch, Hedgehog, and Wnt Pathways in Cancer Stem Cells: Clinical Update
Ivy, P; Takebe, N
Nat Rev Clin Oncol 2015-04-07 4.14 | Apr 15
Hypoxia-Inducible Factors in Cancer Stem Cells and Inflammation
Liu, Y; Peng, G
Trends Pharmacol Sci 2015-04-06 4.14 | Apr 15
NANOG in Cancer Stem Cells and Tumor Development: An Update and Outstanding Questions
Tang, D; Chao, HP; Wang, J; Yang, Tao; Jeter, C
Stem Cells 2015-03-26 4.12 | Apr 1

Two Genes Control Breast Cancer Stem Cell Proliferation and Tumor Properties

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Protein-binding, Protein-Protein interactions & Therapeutic Implications

Writer and Curator: Larry H. Bernstein, MD, FCAP 

7.3  Protein-binding, Protein-Protein interactions & Therapeutic Implications

7.3.1 Action at a Distance. Allostery_Delabarre_allostery review

7.3.2 Chemical proteomics approaches to examine novel histone modifications

7.3.3 Misfolded Proteins – from Little Villains to Little Helpers… Against Cancer

7.3.4 Endoplasmic reticulum protein 29 (ERp29) in epithelial cancer

7.3.5 Putting together structures of epidermal growth factor receptors

7.3.6 Complex Relationship between Ligand Binding and Dimerization in the Epidermal Growth Factor Receptor

7.3.7 IGFBP-2.PTEN- A critical interaction for tumors and for general physiology

7.3.8 Emerging-roles-for-the-Ph-sensing-G-protein-coupled-receptor

7.3.9 Protein amino-terminal modifications and proteomic approaches for N-terminal profiling

7.3.10 Protein homeostasis networks in physiology and disease

7.3.11 Proteome sequencing goes deep

7.3.1 Action at a Distance. Allostery_Delabarre_allostery review

DeLaBarre B1Hurov J1Cianchetta G1Murray S1Dang L2.
Chem Biol. 2014 Sep 18; 21(9):1143-61
http://dx.doi.org:/10.1016/j.chembiol.2014.08.007

Cancer cells must carefully regulate their metabolism to maintain growth and division under varying nutrient and oxygen levels. Compelling data support the investigation of numerous enzymes as therapeutic targets to exploit metabolic vulnerabilities common to several cancer types. We discuss the rationale for developing such drugs and review three targets with central roles in metabolic pathways crucial for cancer cell growth: pyruvate kinase muscle isozyme splice variant 2 (PKM2) in glycolysis, glutaminase in glutaminolysis, and mutations in isocitrate dehydrogenase 1 and 2 isozymes (IDH1/2) in the tricarboxylic acid cycle. These targets exemplify the drugging approach to cancer metabolism, with allosteric modulation being the common theme. The first glutaminase and mutant IDH1/2 inhibitors have entered clinical testing, and early data are promising. Cancer metabolism provides a wealth of novel targets, and targeting allosteric sites promises to yield selective drugs with the potential to transform clinical outcomes across many cancer types.

Based on knowledge acquired to date, there is no doubt that cancer metabolism provides a wealth of novel therapeutic targets and multiple innovative ways in which to exploit metabolic vulnerabilities for therapeutic benefit. More comprehensive reviews cover the breadth of metabolic targets that are currently under investigation (Stine and Dang, 2013; Vander Heiden, 2011). The following sections of this review focus on PKM2, glutaminase, and mutated IDH1/2 as exemplary metabolism targets under investigation for development of cancer therapies.
Drugging Glycolysis: Targeting Pyruvate Kinase Muscle Isozyme Alternative Splice Variant 2 PK catalyzes the last step of glycolysis, converting phosphoenolpyruvate (PEP) to pyruvate, while producing one molecule of ATP. The reaction encompasses two chemical steps: the first involves a phosphoryl transfer from PEP to ADP, forming an enolate intermediate and ATP, and the second involves protonation of the enolate intermediate, forming pyruvate (Robinson and Rose, 1972). PKM2 is one of four PK isoforms in humans. PKM1 and PKM2 result from the alternative splicing of exons 9 and 10 of the PKM gene, which encode a stretch of amino acids that differ at 23 positions between PKM1 and PKM2. PKM1 is constitutively active in skeletal muscle and brain tissue, but is not allosterically regulated. PKM2 is expressed in fetal and proliferating tissues, has low basal activity compared with PKM1, and is allosterically regulated. R-type pyruvate kinase (PKR) and L-type pyruvate kinase (PKL) are transcribed via different promoters from the PKLR gene. PKR is expressed in erythrocytes and PKL in the liver. PKR, PKL, and PKM1 exist as stable tetramers,whereas PKM2 forms tetramers (high activity form), dimers (low activity form), and monomers (Mazurek, 2011).

Figure 1. Central Metabolic Pathways Utilized by Cancer Cells *denotes mutated isoenzyme.

Pyruvate Kinase Muscle Isozyme Alternative Splice Variant 2 in Cancer Cell Metabolism Cancer cells predominantly express PKM2, which can be downregulated by tyrosine kinase growth factor signaling pathways, allowing metabolic flexibility. Phosphotyrosine peptides have been shown to suppress PKM2 activity by binding tightly to PKM2, thereby catalyzing the release of fructose 1,6-bisphosphate (FBP), resulting in a switch to the low activity dimer state (Christofk et al., 2008b; Hitosugi et al., 2009). This downregulation is thought to support tumor growth and proliferation by allowing for the shunting of glycolytic intermediates toward other biosynthetic pathways (i.e., pentose phosphate and serine pathways). In keeping with this model, the activation of PKM2 in cancer cells using small molecule agonists resulted in serine auxotrophy (Kung et al., 2012). Consistent with the hypothesis that PKM2 is a critical metabolic switch, there is growing evidence that, depending on the cellular stress environment, PKM2activity canberegulated byposttranslational modification such as acetylation (Lv et al., 2011), phosphorylation (Hitosugi et al., 2009), cysteine oxidation (Anastasiou et al., 2011), and proline hydroxylation (Luo et al., 2011). The utility of PKM2 activators in the clinic has yet to be determined, but recent work with tumor xenografts with a PKM2 activator suggests that this may be a viable approach (Parnell et al., 2013). As PKM2 tetramers show greater than 50-fold higher activity than PKM2 monomers (Anastasiou et al., 2012), one consideration when designing drugs to activate PKM2 for therapeutic means would be the need for small-molecule ligands capable of driving the enzyme toward its optimally active tetrameric form, thus forcing cancer cells into a less flexible metabolic state.

Structure of Pyruvate Kinase Muscle Isozyme Alternative Splice Variant 2 The structure of the PKM2 tetramer is summarized in Figure 2A. PKM2 is allosterically activated in a ‘‘feedforward’’ manner by the upstream glycolytic metabolite, FBP, which induces a shift to the active tetrameric conformation (Christofk et al., 2008b; Dombrauckas et al., 2005). PKM2 can be independently allosterically activated by serine (Chaneton et al., 2012), which binds in a distinct pocket that can also accommodate the inhibitor phenylalanine (Protein Data Bank [PDB] ID: 4FXJ). The binding of phenylalanine results in a tetrameric form distinct from the active conformer (Morgan et al., 2013). It is not clear how the change from serine to phenylalanine elicits such a dramatic change in protein behavior, or whether there is any biological interaction between serine activation and phenylalanine inhibition of PKM2 in cancer cells. Of note, PKM1 and PKL/R are not activated by serine, despite the conservation of the serine binding site in all PK isoforms.
Figure 2. Three Different Metabolic Enzymes and Their Allosteric Inhibitors Protomers are depicted as cartoon ribbons in blue, green, yellow, and cyan. Synthetic allostery is depicted in stick format with red highlight. (A) Structure of tetrameric PKM2:AGI-980 (4:2 complex) from PDB 4G1N. AGI-980 is shown in stick rendering near the center of tetramer. Each PK monomer consists of four domains, usually designated A, B, C, and N (Dombrauckas et al., 2005). The tetramer is a dimer-of-dimers with approximate D2 symmetry. The dimer is formed between the A domains of each monomer, while the tetramer is formed via dimerization along the C subunit interfaces of each dimer. The active site of PKM2 lies within a cleft between the A and B domain, illustrated by a PEP analog (red spheres). The FBP binding pocket is located entirely within the C domain (pink spheres). The natural allosteric site of serine is also shown (black spheres). (B)Tetrameric GAC:BPTES (4:2 complex) from PDB 3UO9. Glutamate molecules are shown as spheres. (C) Dimeric IDH2R140Q:AGI-6780 (2:1 complex) from PDB 4JA8 (Wang et al., 2013). NADP molecules are shown as spheres.
Discovery of Allosteric Activators of Pyruvate Kinase Muscle Isozyme Alternative Splice Variant 2 A number of small molecules that potently activate PKM2 have been discovered by various groups (Table 1). Interestingly, all seven X-rayco-complexescurrentlyavailableshowcompoundsbound at a novel binding pocket distinct from the FBP and serine binding sites, which would otherwise allow cells to overcome negative regulation by phosphotyrosines (Kung et al., 2012). The compounds found in structures 3GQY, 3GR4 (Boxer et al., 2010), 3H6O (Jiang et al., 2010), 3ME3, and 3U2Z (Anastasiou et al., 2012) were identified by screening the NIH Small Molecule Repository, and can be classified into two distinct chemical series, both of which establish very similar interactions with PKM2 (Table 1). Analogues in these two classes selectively activated PKM2 allosterically with good selectivity against PKM1, PKL, and PKR (Anastasiou et al., 2012; Boxer et al., 2010; Jiang et al., 2010). The molecule found in the structure 4JPG (Guo et al., 2013) is similar to the two series described above, where the pyrimidone ring is found between the two Phe26 residues (Table 1). Interestingly, the activator found in the 4G1N structure (Kung et al., 2012) sits in the same pocket as the NIH compounds. However, the interactions are quite different, with the side chains of the two Phe26 that line the pocket assuming distinct conformations. This activator wraps around the two aromatic residues, which pushes it closer to the walls of the pocket, allowing for a richer series of interactions with PKM2 (Table 1). There are two additional series of PKM2 activators that have been reported for which no structural information is available (Table 1)(Parnell et al., 2013; Xu et al., 2014; Yacovan et al., 2012). Members of this series were shown to have an activation level comparable to that of FBP, with selectivity for PKM2 over PKL, PKR, and PKM1. PKM2 offers a very interesting example of an allosterically regulated enzyme. Different allosteric sites have so far been identified for three different types of activator (FBP, serine, and small-molecule ligands) and all activate PKM2 by stabilizing the tetrameric form. It is remarkable that molecules as small as serine can dramatically alter this protein’s conformational landscape and aggregation state and lead to an active enzyme. This unusual allosteric site revealed by the small-molecule ligands is of particular curiosity, largely because neither its function nor its native ligands are known. All of the drug-like activators described above bind at the dimer–dimer interface and seem to act by displacing water from the mainly apolar pocket, thus contributing to the stabilization of the tetramer. While these PKM2 activators show promising preclinical data, none have yet entered clinical development.

Table 1. Biochemical Properties of Small Molecule PKM2 Inhibitors Series PDB ID Ligand Reference Binding Characteristics

Substituted N,N’diarylsulfonamide 3GQY (Boxer et al., 2010)

  •  All completely buried within A-A’ interface, 35A ˚ from FBP pocket
  •  Binding pocket lined with residues equivalent to those of PKM2 molecules forming A-A’ interface
  •  All sandwiched between phenyl rings of the two Phe26 from different monomers
  •  All additionally interact with side chain of Phe26 through slightly distorted T-shaped p-p interactions (two such interactions for substituted N,N0diarylsulfonamides and one for thieno[3,2-b]pyrrole[3,2-] pyridazinones)
  1. 3GR4 (Boxer et al., 2010) 3ME3 (Anastasiou et al., 2012)
  2. Thieno[3,2-b]pyrrole [3,2-d]pyridazinone 3H6O (Jiang et al., 2010)
  3. 3U2Z (Anastasiou et al., 2012)
  4. 2-((1H-benzo[d]imidazol1-yl)methyl)-4H-pyrido [1,2-a]pyrimidin-4-ones
  5. 4JPG (Guo et al., 2013)
  • Pyrimidone ring found between the two Phe26 residues forming p-p interactions with the aromatic rings
  • Carbonyl interacts with a bridging water molecule
  • Benzimidazole reaches a region of the activator pocket that is not occupied in any of the published crystal structures
  • One of the imidazole nitrogens forms an H-bond with Lys311, which is normally part of a salt bridge to Asp354

Quinolone sulfonamides 4G1N (Kung et al., 2012)

  •  Quinoline moiety sits on a flat, mainly apolar surface defined by Phe26, Leu27 and Met30 from chain A and Phe26, Tyr390 and Leu394 from chain A’
  •  One of the two oxygen atoms of the sulfonamide accepts an H bond from the backbone oxygen of Tyr390, the other interacts with a water molecule
  •  The oxygen of the amide moiety forms an H-bond with side-chain nitrogen of Lys311
  •  Terminal aromatic ring sits in the other copy of the quinoline pocket d Aromatic rings of the side chains of the two Phe26 lining the pocket almost perpendicular (not parallel); activator wrapped around the two aromatic residues

3-(trifluoromethyl)-1Hpyrazole-5-carboxamide (Parnell et al., 2013; Xu et al., 2014)

  • Cocrystal structure of one compound bound to tetrameric PKM2 obtained but file not available for download from PDB: described as bound to the allosteric site at the dimer–dimer interface

5-((2,3-dihydrobenzo[b] [1,4]dioxin-6-yl)sulfonyl)-2methyl-1-(methylsulfonyl) indoline scaffold (Yacovan et al., 2012)

  • Cocrystal structure of one compound bound to PKM2 obtained but not available for download from the PDB: described as bound to dimer interface
  • Interactions very similar to those established by thieno [3,2-b]pyrrole[3,2-d]pyridazinone series above

Drugging Glutaminolysis: Targeting the Glutaminase C Variant Glutaminase catalyzes the conversion of glutamine to glutamate and ammonia. Glutamate can be oxidized to a-ketoglutarate (aKG), which then anaplerotically feeds into the TCA cycle as a means of providing proliferating cells with biosynthetic intermediates and ATP (Figure 1); glutamate is also used as a substrate for the generation of glutathione, which provides protection from redox stress (Hensley et al., 2013; Shanware et al., 2011). The ammonia produced during the reaction can be used in certain tissues like the kidney to provide pH homeostasis, and nitrogen derived from glutamine is utilized in nucleotide biosynthetic and glycosylation pathways.

Table 2. Characteristics of Small Molecule Glutaminase Inhibitors

BPTES N-(5–[1,3,4]thiadiazol-2yl)-2-phenylacetamide 6 (Shukla et al., 2012)

  • Similar potency but better water solubility vs. BPTES d Attenuated growth of P493 human lymphoma B cells in vitro d Diminished tumor growth in P493 tumor xenograft SCID mice with no apparent toxicity

CB-839 (Calithera) (Gross et al., 2014)

  • Orally bioavailable d Binds at allosteric sites of GLS1 KGA and GAC d Potent, selective, time-dependent reversible inhibition with slow recovery time
  • Anti-proliferative activity (double-digit nM potency) in cellular proliferation assays in wide range of tumors
  • Currently in Phase I trials of locally-advanced/metastatic refractory solid tumors (triple negative breast cancer, NSCLC, RCC, mesothelioma) and hematological cancers [Clinicaltrials.gov: NCT02071927, NCT02071862, NCT02071888]

Dibenzophenanthridines Compound 968 (Katt et al., 2012; Wang et al., 2010)

  • Modest potency in the low mM concentrations d Loses all inhibitory activity against glutaminase activated by preincubation with inorganic phosphate (phosphate does not affect BPTES potency)
  • Anti-proliferative activity in breast cancer cell line at 10 mmol/L concentration

There are three isoforms of IDH. IDH1 is located in both the peroxisome and the cytosol, whereas IDH2 and IDH3 are located in mitochondria. It is unclear what the relative contributions of the IDH2 and IDH3 isoforms are to overall mitochondrial TCA function. IDH1 and IDH2 are both obligatory homodimeric proteins and use NADP+ as a cofactor, whereas IDH3 uses NAD+ as a cofactor and is a heterotrimeric protein comprising alpha, beta, and gamma subunits. All three isozymes require either Mg2+ or Mn2+ asdivalent metal cofactors for catalysis.The dimeric structure of IDH2 is shown in Figure 2C.

Mutant Isocitrate Dehydrogenase in Cancer Cell Metabolism The role of IDH mutations in cancer metabolism was recognized following the observation of frequent and recurrent mutations of IDH1 and IDH2 in patients with glioma and AML, initially identified by genomic deep sequencing and subsequent comparative genetic analyses (Parsons et al., 2008; Yan et al., 2009). These mutations were originally characterized as loss of function (Mardis etal.,2009; Parsonsetal.,2008; Yanet al.,2009), suggesting that mutated IDH acts as a tumor suppressor due to the loss of catalytic conversion of isocitrate to aKG (Zhaoetal., 2009). However, with the exception of cases of haploinsufficiency, the heterozygous mutation pattern of IDH is more consistent with an oncogene role. Subsequently, IDH mutations were shown to possess the neomorphic activity to generate the oncometabolite, 2-hydroxyglutarate (2HG) (Dang et al., 2009; Gross et al., 2010; Ward et al., 2010). With a single codon substitution, the kinetic properties of the mutant IDH isozyme are significantly altered, resulting in an obligatory sequential ordered reaction in the reverse direction (Rendina et al., 2013). Indeed, the critical kinetic observation of mutant IDH was not only the loss of affinity for isocitrate, but also a dramatic increase in NADPH affinity by three orders of magnitude (Dang et al.,2009), suggesting a substantial change in protein dynamics imparted by the mutation. The only known homeostatic 2HG clearance mechanism is the relatively inefficient reconversion of 2HG back to aKG by D-2hydroxyglutarate dehydrogenase. Therefore, 2HG accumulates when over-produced by mutant IDH. 2HG itself has been shown to be sufficient to drive the malignant phenotype (Rakheja et al., 2013). Abnormally high 2HG levels impair aKG-dependent dioxygenases through competitive inhibition, including those that modify DNA and histones (i.e., Jumonji domain-containing histone demethylases and the ten-eleven translocation (TET) family of 50-methylcytosine hydroxylases) (Chowdhury et al., 2011; Figueroa et al., 2010), as well as EglN prolyl hydroxylase in regulating hypoxia-inducible factor (Losman et al., 2013). This results in altered epigenetic status that blocks cell differentiation. These findings, combined with the inhibitory effects of fumarate and succinate on the same families of aKG-dependent enzymes, highlight a critical and fascinatingnetwork that ties together central metabolic pathways and epigenetic control. Remarkably, mutations in TET2 are mutually exclusive with IDH mutations in AML, strongly suggesting that, in this context, the tumorigenic effects of 2HG are at least in part driven by inhibition of TET2. The precise targets of IDH mutations with associated 2HG production (and TET2 mutations) that promote tumorigenesis are currentlyunknown;however,itisclearthatIDH1/2andTET2mutations lead to a block in hematopoietic cell differentiation (Figueroa et al., 2010; Lu et al., 2012; Moran-Crusio et al., 2011; Wang et al., 2013). To date, no IDH3 mutation associated with cancer has been reported (Krell et al., 2011; Reitman and Yan, 2010), suggesting that the role of IDH1/2 has a greater impact on tumorigenesis. Targeting mutated isoforms of IDH1/2 therefore presents a logical approach to cancer therapy. A consideration in designing suchdrugsistheheterozygoussomaticnatureoftheIDH1/2mutation, which likely yields a mixture of homo- and heterodimers; statistically, heterodimers should be the major species in vivo. Mutant homodimers and wild-type-mutant heterodimers both efficiently catalyze the production of 2HG from aKG (Dang et al., 2009; Rendina et al., 2013). However, the heterodimer is potentially more oncogenic, as it is more efficient at producing 2HG than homodimeric mutants (Pietrak et al., 2011) due to an increased local concentration of substrate while conserving NADPH. The heterodimer as a molecular target therefore becomes an important consideration in this scenario.

Structure of Isocitrate Dehydrogenase Structurally, both IDH1 and IDH2 comprise three main domains: the large domain, the small domain, and the clasp region (Yang et al., 2010). A simplified description of protein motion is provided in Figure 3 (Rendina et al., 2013; Xu et al., 2004). The dynamic of motion may differ slightly between IDH1 and IDH2 mutants. IDH1 mutants appear to open wider than IDH2 mutants to the point of unwinding a helix termed ‘‘seg2’’ (Yang et al., 2010). In contrast, the open form of IDH2 does not involve the melting of any secondary structure, and as a consequence has a much narrower range of motion (Taylor et al., 2008; Wang et al., 2013). This differential in protein dynamics could possibly explain the differential responses of IDH1 and IDH2 to inhibitors. X-ray structures of IDH3 have not yet been reported, but it appears to be distinct from IDH1 and IDH2 in terms of primary sequence and predicted quaternary organization (Kim et al., 1995; Ramachandran and Colman, 1980). There are three arginine residues in the enzyme active site that are predicted to play a central role in electrostatic stabilization and proper geometric orientation of isocitrate via its acidic moieties as the substrate binds in the active site. With the exception of the novel G97D or G97N codon mutation (Ward et al., 2012), virtually all confirmed IDH mutations that generate high levels of 2HG occur in one of these arginines (i.e., IDH1-R132 and IDH2-R172/R140) (Losman and Kaelin, 2013) and have in common a substitution of one of the diffuse positive charges of the respective arginine’s guanidinium moiety.
Discovery of Inhibitors against Mutated Isocitrate Dehydrogenase Several inhibitors of mutant IDH isoforms that block 2HG production in vitro and in vivo have been recently described. The first potent and specific IDH1 inhibitors reported were the phenylglycine series, specifically AGI-5198 (Popovici-Muller et al., 2012; Rohle et al., 2013) and subsequently ML309 (Davis et al., 2014)(Table 3), which were shown to be rapid-equilibrium inhibitors specific for IDH1-R132-codon mutations. These compounds inhibited IDH1-R132H competitively with respect to aKG and uncompetitively with respect to NADPH, suggesting that they preferably bind to the enzyme-NADPH ternary complex. Notably, they do not appreciably cross-react against the IDH2-R140Q mutant isozyme, suggesting a unique binding mode in IDH1-R132 that does not favorably exist in IDH2R140. Because no X-ray co-complex has been reported for this series, the exact mode of binding cannot be ascertained at this time. Preclinical data indicated 2HG inhibition and antitumor effects in vitro and in vivo (Table 3). These phenylglycine compounds appear to be excellent chemical tools for tumor biology investigation, but optimization of their properties is likely required for further therapeutic development. Co-complexes of IDH1-R132H with two different 1-hydroxypyridin-2-one inhibitors have been reported (Zheng et al., 2013), but the quality of the crystal structure data supporting the mechanism of inhibition is poor. AG-120, a selective, potent inhibitor of mutated IDH1, is currently in clinical development for the treatment of cancers with IDH1 mutations (Table 3), but there is currently no published information on this inhibitor. Another inhibitor of mutated IDH1 has been reported recently (Table 3) (Deng et al., 2014). Co-complex X-ray studies revealed that Compound1 binds mutated IDH1 allosterically at the dimer interface resulting in an asymmetric open conformation. Distinctively, Compound 1 displaces the conserved catalytic Tyr139 and further disrupts the Mg2+ binding network, consistent with kinetic results of competitive inhibition with respect to Mg2+, but not with aKG substrate. Others have reported modeling of inhibitors into the active site of IDH1, but experimental evidence is lacking (Chaturvedi et al., 2013; Davis et al., 2014). The first reported potent and selective IDH2 inhibitor was the urea-sulfonamide series, AGI-6780 (Wang et al., 2013), a timedependent slow-tight binder to IDH2-R140Q exhibiting noncompetitive inhibition with respect to substrate and uncompetitive inhibition with respect to NADPH, and nanomolar potency for 2HG inhibition (Table 3). This compound showed good inhibitory selectivity for IDH2-R140Q, with no effect on the closely related IDH1 and IDH1-R132H isozymes. At doses that effectively blocked 2HG to basal levels, AGI-6780 induced differentiation of TF-1 erythroleukemia and primary human AML cells in vitro, suggesting potential to reverse leukemic phenotype in AML tumors harboring the IDH2 mutation. Unlike the case of IDH1 above, the published structure of AGI-6780 co-complexed with IDH2-R140Q allows for detailed analysis of its inhibitory mechanism (Wang et al., 2013). In the X-ray structure, a single molecule
of AGI-6780 binds at the interface of two protomers (Figure 2C). The allosteric inhibition appears to arise from the ability of AGI6780 to keep the IDH2-R140Q mutant enzyme in an open orientation, thereby preventing the NADPH cofactor and substrate aKG from coming close to the catalytic Mg2+ binding site (see Figure 3). The highly symmetric AGI-6780 binding pocket extends deep into the protein interface and is closed over by loops composed of residues 152–167, which also fold over the binding pocket, providing anexplanation for the time-dependent inhibition kinetics. AGI-6780 makes several direct H-bond interactions from its urea group and amide nitrogen to Gln316, but a significant amount of binding energy arises from van der Waals contacts between the protein and hydrophobic surfaces of AGI-6780. The in vivo potential for this compound is not known, since its pharmacokinetic properties were not reported. Nevertheless, this effective mode of inhibition serves as an important molecular model for the design of bioisosteric compounds. OtherIDH2inhibitorsareunderdevelopment,notablyAG-221, a first-in-class, orally available inhibitor (Table 3) which demonstrated a survival advantage in a preclinical study of a primary human IDH2 mutant AML xenograft mouse model (Yen et al., 2013). Early phase I clinical trial data for AG-221 show promise, with meaningful clinical responses in evaluable AML patients harboring IDH2 mutations (Stein et al., 2014). To date, there is no published example of a molecule that inhibits both IDH1 and IDH2 mutant isoforms with equipotency.

Table 3.Characteristics of Small Molecule Inhibitors of Mutant IDH

PhenylglycineAGI-5198 (Popovici-Mulleretal., 2012; Rohleetal.,2013)
N-cyclohexyl-2-(N-(3-fluorophenyl)-2(2-methyl-1H-imidazol-1-yl)acetamido)2-(o-tolyl)acetamide IDH1-R132H

  • Good potency against enzyme and in U87cell line overexpressing R132H mutation (IC50= 70nM)
  • Good oral exposure in rodents at high doses (>300mg/kg), which were likely at levels saturating hepatic clearance mechanisms
  • Plasma 2HG inhibition > 90% (BID dosing) in xenograft model of U87-R132H tumors
  • Promoted differentiation of glioma cells via induced demethylation of histone H3K9me3 and expression of genes associated with gliogenic differentiation at near-complete 2HG inhibition
  • inhibited plasma 2HG and delayed growth of IDH1-mutant but not wild-type glioma xenografts in mice

ML309 (Davis et al.,2014)
2-(2-(1H-benzo[d]imidazol-1-yl)-N-(3fluorophenyl)acetamido)-N-cyclopentyl2-o-tolylacetamide IDH1-R132H IDH1-R132C dIC50=68nM(R132H)

  • Inhibited 2HG production in glioblastoma cell line (IC50 = 250 nM) with minimal cytotoxicity
  • 1-hydroxypyridin2-one Compounds2and3 (Zhengetal.,2013)
    6-substituted1-hydroxypyridin-2-oneIDH1-R132H IDH1-R132C
  • K i= 190 and 280 nM (forR132H)
  • Inhibited production of 2HG in IDH1 mutated cells

Undisclosed
AG-120 (Agios)
Undisclosed
IDH1

  • Orally available, selective, potent inhibitor
  • PhaseI studies ongoing in advanced solid tumors (NCT02073994; NCT02074839)

Allostery as an Approach to Drugging Metabolic Enzymes Is Important in Cancer All enzymes discussed in this article are allosterically targeted by small molecule modulators. With the exception of the enzymes of lipid metabolism, it is striking that there are very few examples of the regulation of metabolic enzymes by drug-like molecules at the catalytic site. We believe that this observation will hold true for the wider set of metabolic enzymes. Metabolic pathways are typically regulated by upstream and downstream metabolites through feedforward and feedback mechanisms. This regulation occurs typically through binding at allosteric sites, which have distinctly different properties relative to active sites. Therefore regulation can come from effectors that may have very different properties to the substrate. This review describes the potential therapeutic impact of specific allosteric regulators of PKM2, glutaminase, and IDH. Additionally, preclinical studies of tool compounds demonstrated that allosteric regulators of other enzymes involved in cancer cell metabolism could provide more therapeutic opportunities (Table 4). Substrates and products of metabolic enzymes tend to be small and very polar, and often include crucial metal ions and their ligands, so it is likely that targeting their catalytic pockets will yield molecules with similar properties. From a drug-discovery point of view, targeting allosteric sites is appealing as hydrophilic substrate-binding sites are generally not hospitable to strong interactions with small molecule drugs, which gain potency to a large extent through hydrophobic interactions. In addition, as activity of most metabolic enzymes is regulated by multimerization, the formation of multimers provides opportunity for binding sites to form at protein–protein interfaces.

Table 4. Examples of Allostery in Cancer Cell Metabolism

TH           Tyrosine hydroxylase         Haloperidol                                           Activator             Catecholamine metabolism               (Casu and Gale, 1981)
PDK1      Pyruvate dehydrogenase
kinase isozyme1                  3,5-diphenylpent-2-enoicacids                         Activator             TCAcycle                                                (Stroba et al., 2009)
BCKDK  Branched chain keto acid
dehydrogenase kinase   (S)-a-chloro-phenylpropionicacid[(S)-CPP]     Inhibitor              Branch-chain amino acid                   (Tso et al., 2013)
ACACA   Acetyl-CoA carboxylase
alpha                                 5-tetradecyloxy-2-furoicacid (TOFA)                  Inhibitor              Fatty acid  synthesis                            (Wang et al.,2009)

FBP1     Fructose-1,6
bisphosphatase1               Benzoxazole benzene sulfonamide1                    Inhibitor              Glycolysis                                        (von Geldern et al., 2006)
ALADA minolevulinate
dehydratase                     wALAD in1 benzimidazoles                                     Inhibitor              Haem synthesis                                    (Lentz et al., 2014)
TYR       Tyrosinase         2,3-dithiopropanol                                                   Inhibitor              Melanin metabolism                    (Wood and Schallreuter, 1991)
DBHD  opamine beta
hydroxylase-2H-phthalazinehydrazone (hydralazine;HYD)
2-1H-pyridinonehydrazone (2-hydrazinopyridine;HP)
2-quinoline-carboxylicacid (QCA)
1H-imidazole-4-aceticacid (imidazole-4-aceticacid;IAA)                             Inhibitor         Neurotransmitter synthesis                    (Townes et al.,1990)
DCTD   dCMP
deaminase        5-iodo-2’-deoxyuridine5’-triphosphate                                 Inhibitor          Nucleotide metabolism                      (Prusoff and Chang, 1968)
TYMP  Thymidine
phosphorylase     5’-O-tritylinosine (KIN59)                                                    Inhibitor          Nucleotide metabolism                         (Casanova et al.,2006)
TYMS Thymidylate
synthase         1,3-propanediphosphonicacid (PDPA)                                     Inhibitor          Nucleotide   metabolism                        (Lovelace et al.,2007)

Figure 3. Simplified Description of IDH Protein Motion The large domain (residues 1–103 and 286–414) forms nearly all of the NADPH cofactor binding residues and roughly half of the substrate binding residues.The small domain(residues 104–136 and 186–285) contains the remaining substrate binding residues and the metal binding residues. The interface between the two protomers is formed by both the small domain and the clasp region (residues 137–185). The large domain moves away from the small domain to facilitate NADPH cofactor exchange and substrate binding. The large domain then closes up against the small domain, thereby completing the substrate binding pocket and bringing the cofactor, substrate, and metal into close contact with each other and with the key catalytic residues to facilitate hydride transfer between substrate and cofactor and enzyme-assisted carboxylation/decarboxylation. Subsequent opening of the large domain from the small domain would enable product release and cofactor exchange to complete the catalytic cycle (Rendina et al., 2013; Xu et al., 2004).

7.3.2 Chemical proteomics approaches to examine novel histone modifications

Xin LiXiang David Li
Current Opinion in Chemical Biology Feb 2015; 24:80–90
http://dx.doi.org/10.1016/j.cbpa.2014.10.015

Highlights

  • A variety of novel histone PTMs have been identified by MS-based methods.
  • Regulatory mechanisms and cellular functions of most novel histone PTMs remain unknown, due to lack of knowledge about their readers, erasers and writers.
  • Chemical proteomics approaches provide valuable tools to characterize novel histone PTMs.
  • The application of photoaffinity probes helps the profiling of histone PTMs’ readers, erasers and writers.

Histone posttranslational modifications (PTMs) play key roles in the regulation of many fundamental cellular processes, such as gene transcription, DNA damage repair and chromosome segregation. Significant progress has been made on the detection of a large variety of PTMs on histones. However, the identification of these PTMs’ regulating enzymes (i.e. ‘writers’ and ‘erasers’) and functional binding partners (i.e. ‘readers’) have been a relatively slow-paced process. As a result, cellular functions and regulatory mechanisms of many histone PTMs, particularly the newly identified ones, remain poorly understood. This review focuses on the recent progress in developing chemical proteomics approaches to profile readers, erasers and writers of histone PTMs. One of such efforts involves the development of the Cross-Linking-Assisted and SILAC-based Protein Identification (CLASPI) approach to examine PTM-mediated protein–protein interactions.

Table 1    Novel histone PTMs                      functions
1             Lysine formylation             Arising from oxidative damage of DNA modification sites overlap with lysine acetylation and methylation, potentially interfere with normal regulation of these PTMs

2      Lysine propionylation  p300,c CREB-binding protein,c Sirt1,c Sirt2,c Sirt3c
Structurally similar with lysine acetylation, regulated by same set of enzymes, H3K23pr may be regulatory for cell metabolism
3    Lysine butyrylation       p300,c CREB-binding protein,c Sirt1,c Sirt2,c Sirt3c
Structurally similar with lysine acetylation, regulated by same set of enzymes
4    Lysine malonylation    Sirt5c
Changing the positively charged lysine to negatively charged residue, likely to affect the chromatin structure
5   Lysine succinylation    Sirt5c
A  mutation to mimic crotonyl lysine that changes lysine to glutamic acid of histone H4K31, reduces cell viability
6  Lysine crotonylation   Sirt1,c Sirt2,c Sirt3
Enriched at active gene promoters potential enhancers in mammalian genomes, male germ cell differentiation
7 Lysine 2-hydroxyiso
butyrylation                     HDAC1-3c
Associated with gene transcription
8  Lysine 4-oxononoylation    Modified by 4-oxo-2-nonenal, generated under oxidative stress, prevents nucleosome assembly in vitro
9 Lysine 5-hydroxylation   JMJD6
suppress lysine acetylation and methylation
10 Glutamine methylation   Nop1  (yeast), fibrillarin (huma)
human histone H2AQ105
11 Serine and
threonine GlcNAcylation  O-GlcNAc transferase
H2BS112 GlcNAcylation promotes K120 monoubiquitination, H3S10 GlcNAcylation suppresses phosphorylation of site
12 Serine and threonine acetylation
13 Serine palmitoylation   Lpcat1
catalyzed H4S47 palmitoylation, Ca2+-dependent, regulates global RNA synthesis
14  Cysteine glutathionylation
H3.2 and H3.3
conserved cysteine, but not H3.1, destabilize the nucleosomal structure
15 Cysteine fatty-acylation
H3.2 C110
16 Tyrosine hydroxylation

Fig. 1. Schematic description of a MS-based method for the identification of novel histone PTMs.

http://ars.els-cdn.com/content/image/1-s2.0-S1367593114001562-gr1.sml

Fig. 2. Chemical proteomics approaches to profile readers and erasers of histone PTMs.
(a) Photo-cross-linking strategy to capture proteins recognizing histone PTMs.
(b) Chemical structure of photoaffinity peptide probes.
Modifications of interest were labeled in green; photo-cross-linkers were labeled in red; chemical handles (alkyne) were labeled in blue; the sequence of probe C and probes 1–5 were derived from the
histone H3 1–15 amino acids residues, the sequence of probe 6 was derived from the histone H4 1–19 amino acids residues.
(c) Schematic for the CLASPI strategy to profile proteins that bind certain histone mark in whole-cell proteomes

http://ars.els-cdn.com/content/image/1-s2.0-S1367593114001562-gr2.sml

Consistent with our findings, Tate and coworkers [57] recently reported the development of a photoaffinity probe based on a succinylated glutamate dehydrogenase (GDH) peptide for capturing Sirt5
as the corresponding desuccinylase. In addition to the application of photo-cross-linking strategy for examining the histone PTMs with known erasers, we recently used CLASPI with a photoaffinity
probe (probe 5, Figure 2b) to profile proteins that recognize a novel histone mark, crotonylation at histone H3K4 (H3K4cr, Table 1, Entry 6) [25], whose erasers were unknown. This study revealed,
for the first time, that Sirt3 can recognize the H3K4cr mark and efficiently catalyze the removal of histone crotonylation marks. More importantly, Sirt3 was found to regulate histone Kcr level in
cells and may potentially modulate gene transcription through its decrotonylase activity [58]. By converting bisubstrate inhibitors of HATs (histone peptides with certain lysine residues covalently
attached to Ac-CoA) to clickable photoaffinity probes (for example, probe 6, Figure 2b), they carried out the first systematic profiling of HATs in whole-cell proteomes [59].  We  anticipate  that  similar methods can be used to search for writers of novel histone PTMs such as Kmal, Ksucc, Kcr and Khib (Table 1) since the corresponding acyl-CoAs are presumed to be the acyl donors.

We have shown, in this review, the applications and recent advances of chemical tools, in combination with MS-based proteomics approaches, for the detection and characterization of histone
PTMs and their readers, erasers and writers.

This article belongs to a special issue

Omics Edited By Benjamin F Cravatt and Thomas Kodadek

Editorial overview: Omics: Methods to monitor and manipulate biological systems: recent advances in ‘omics’

Benjamin F Cravatt, Thomas Kodadek
Current Opinion in Chemical Biology Feb 2015; 24:v–vii
http://dx.doi.org/10.1016/j.cbpa.2014.12.023

7.3.3 Misfolded Proteins – from Little Villains to Little Helpers… Against Cancer

Ansgar Brüning1,* and Julia Jückstock
Front Oncol. 2015; 5: 47
http://dx.doi.org/10.3389.2Ffonc.2015.00047

The application of cytostatic drugs targeting the high proliferation rates of cancer cells is currently the most commonly used treatment option in cancer chemotherapy. However, severe side effects and resistance mechanisms may occur as a result of such treatment, possibly limiting the therapeutic efficacy of these agents. In recent years, several therapeutic strategies have been developed that aim at targeting not the genomic integrity and replication machinery of cancer cells but instead their protein homeostasis. During malignant transformation, the cancer cell proteome develops vast aberrations in the expression of mutated proteins, oncoproteins, drug- and apoptosis-resistance proteins, etc. A complex network of protein quality-control mechanisms, including chaperoning by heat shock proteins (HSPs), not only is essential for maintaining the extravagant proteomic lifestyle of cancer cells but also represents an ideal cancer-specific target to be tackled. Furthermore, the high rate of protein synthesis and turnover in certain types of cancer cells can be specifically directed by interfering with the proteasomal and autophagosomal protein recycling and degradation machinery, as evidenced by the clinical application of proteasome inhibitors. Since proteins with loss of their native conformation are prone to unspecific aggregations and have proved to be detrimental to normal cellular function, specific induction of misfolded proteins by HSP inhibitors, proteasome inhibitors, hyperthermia, or inducers of endoplasmic reticulum stress represents a new method of cancer cell killing exploitable for therapeutic purposes. This review describes drugs – approved, repurposed, or under investigation – that can be used to accumulate misfolded proteins in cancer cells, and particularly focuses on the molecular aspects that lead to the cytotoxicity of misfolded proteins in cancer cells.

Introduction:

How Do Proteins Fold and What Makes Misfolded Proteins Dangerous?

For an understanding of misfolded proteins, it is necessary to understand how cellular proteins attain and then further maintain their native conformation and how mature proteins and unfolded proteins are generated and converted into each other.

The principles and mechanisms of protein folding were one of the major research topics and achievements of biochemical research in the last century. For decades, Anfinsen’s model, which explained protein structure by thermodynamic principles applying to the polypeptide’s inherent amino acid sequence (1), was to be found in the introductory sections of all textbooks in protein biochemistry. According to Anfinsen’s thermodynamic hypothesis, the structure with the lowest conformational Gibbs free energy was finally taken by each single polypeptide due to a thermodynamic and stereochemical selection for side chain relations that form most stable and effective enzymes or structural proteins (1). Beyond this individual selection for the energetically most optimized conformation, evolution also selected for amino acid sequences that energetically allowed the smoothest and most “frustration-free” folding processes via a thermodynamic “folding funnel” (1–3).

Whereas Anfinsen’s model preferred the side chain elements as preferential organizing structures, recent hypotheses have inversely proposed the backbone hydrogen bonds as the driving force behind protein folding (4). According to the former theory, the finally folded protein was assumed to attain a single defined structure and shape (1, 4), and the unfolded conditions were described as being represented by a structureless statistical coil with nearly indefinite conformations – a so-called “featureless energy landscape” (4). The latter model assumes that a protein selects during its folding process from a limited repertoire of stable scaffolds of backbone hydrogen bond-satisfied α-helices and β-strands (4). This also implies that unfolded proteins are not structureless, shoelace-like linear amino acid alignments as often depicted in cartoons for graphical reasons, but actually, at least in part, retain discrete and stable scaffolds.

Once the protein has attained its final conformation, the problem of stabilizing this structure arises. Hydrophobic interactions that press non-polar side chains into the center of the protein are assumed to be a major force in protein stabilization (5, 6). At the protein surface, polar interactions, mainly by hydrogen bonds of polar side chains and backbone structure, are assumed to be of similar importance (6). Salt bridges and covalent disulfide bonds were identified as further forces supporting the stability of proteins (6). Accordingly, all conditions that interfere with these stabilizing forces, including extreme temperature, salt concentrations, and redox conditions, may lead to protein misfolding.

Another aspect that must be taken into account when studying protein folding relates to the very different conditions found in viable cells when compared to test tube conditions. Considering the life-cycle of a protein, each protein begins as a growing polypeptide chain protruding from the ribosomal exit tunnel and with several of its future interacting amino acid binding partners not even yet attached to the growing chain of the nascent polymer. In these ribosomal exit tunnels, first molecular interactions and helical structures are formed, and evidence exists to support the notion that the speed of translation is regulated by slow translating codon sequences just to optimize these first folding processes (7). After leaving the ribosomal tunnel, nascent polypeptides are also directly welcomed by chaperoning protein complexes, which facilitate and further guide the folding process of newly synthesized proteins (8). It is believed that a high percentage of nascent proteins are subject to immediate degradation due to early folding errors (9). Since many nascent proteins are synthesized in parallel at polysomes, the temporal and spatial proximity of unfolded peptides brings the additional risk of protein aggregation (10). Moreover, as mentioned above, even incomplete folding intermediates and partially folded states may form energetically but not physiologically active metastable structures (11, 12). An immediate, perinatal guidance and chaperoning of newborn proteins is therefore essential to creating functional, integrative proteins and to avoiding misfolded, function-less polypeptides with potentially cytotoxic features.

Since protein structure and function are coupled, misfolded proteins are, at first, loss-of-function proteins that might reduce cell viability, in particular when generated in larger quantities. A more dangerous feature of misfolded proteins, however, lies in their strong tendency toward abnormal protein–protein interactions or aggregations, which is reflected by the involvement of misfolded proteins and their aggregates in several amyloidotic diseases, including neurodegenerative syndromes such as Alzheimer’s disease and Parkinson’s disease (13, 14). The fact that several of these intracellular and extracellular protein aggregates contain β-sheet-like structures and form filamentous structures also supports the notion that misfolded proteins are not necessarily structureless protein coils or unspecific aggregates, at least when they are formed by homogenous proteins as in the case of several neurodegenerative diseases (13). Paradoxically, these larger aggregates appear to reflect a cell protective mechanism so as to sequester or segregate smaller, but highly reactive, nucleation cores of condensing protein aggregates (13).

Unspecific hydrophobic interactions, in particular, have been held responsible for protein aggregations that form when terminally folded proteins lose their native conformation and expose buried hydrophobic side chains on their surface (15, 16). These hydrophobic interactions are also believed to be the most problematic issues with newly synthesized polypeptides on single ribosomes or polysomes (12). Once exposed to the surface, the hydrophobic structures will quickly find possible interaction partners. The intracellular milieu can be regarded as a “crowded environment” (17), fully packed with proteins in close contact and near to their solubility limit (8, 12). Thus, misfolded proteins not only aggregate among each other but may also attach to normal native proteins and inhibit their function and activity. Since such misfolding effects and interactions can also include nuclear DNA replication and repair enzymes (18), misfolded proteins may not only exert proteotoxic but also genotoxic effects, thereby endangering the entire cellular “interactome” (19) by interfering both with the integrity of the proteome (proteostasis) and the genome. Therefore, a misfolded protein is not simply a loss-of-function protein but also a promiscuous little villain that might act like a free radical, exerting uncontrolled danger to the cell.

The way in which cells deal with misfolded proteins strongly depends on the nature, strength, length, and location of the damage induced by the various insults. Management of misfolded proteins can be achieved by heat shock protein (HSP)-mediated protein renaturation (repair); proteasomal, lysosomal, or autophagosomal degradation (recycling); intracellular disposal (aggregation); or – in its last consequence if overwhelmed – by programed cell death (despair). In the following paragraphs, the cellular management of misfolded proteins is described and therapeutic options to induce misfolded proteins in cancer cells are presented.

Hsp90 and Hsp90 Inhibitors

The best-known and evolutionarily most-conserved mechanism to protect against protein misfolding is the binding and refolding process mediated by so-called heat shock proteins (HSPs). HSPs recognize unfolded or misfolded proteins and facilitate their restructuring in either an ATP-dependent (large HSPs) or energy-independent manner (low weight HSPs). HSP of 90 kDa (hsp90) is a constitutively expressed HSP and is regarded as the most common and abundantly expressed HSP in eukaryotic cells (20, 21). Although commonly referred to as hsp90, it consists of a variety of isoforms that are encoding for cytosolic (hsp90α1, α2, β), mitochondrial (TRAP1), or endoplasmic reticulum (ER)-resident (GRP94) forms. Its primary function is less that of a stress response protein and more to bind to a certain group of client proteins unable to maintain a stable configuration without being assisted by hsp90 (20, 22, 23). Steroid hormone receptors (estrogen receptor, glucocorticoid receptor), cell cycle regulatory proteins (CDK4, cyclin D, polo-like kinase), and growth factor receptors and their downstream targets (epidermal growth factor receptor 1, HER2, AKT) are among the best-studied client proteins of hsp90 (20–22). Also, several cancer-specific mutations generating otherwise instable oncoproteins, such as mutant p53 or bcr-abl, rely on hsp90 chaperoning to keep them in a soluble form, thereby facilitating the extravagant but vulnerable “malignant lifestyle” of hsp90-addicted cancer cells (21, 24). Accordingly, hsp90 has been assumed to be a prominent target, in particular for hormone-responsive and growth factor receptor amplification-dependent cancer types.

The microbial antibiotics geldanamycin and radicicol are the prototypes of hsp90 inhibitors. Based on intolerable toxicity, these molecules had to be chemically modified for application in humans, and most of the ongoing clinical studies with hsp90 inhibitors are aimed at identifying semi-synthetic derivatives of these lead compounds with an acceptable risk profile. Unfortunately, most recent studies using geldanamycin derivatives have provided disappointing results because of toxicities and insufficient efficacy (22, 25–27). Studies with radicicol (resorcinol) derivatives, in particular with ganetespib, appear to be more promising because of fewer adverse effects (22, 25–27). Liver and ocular (retinal) toxicities have been described as main adverse effects of hsp90 inhibition, and appeared to be experienced less with ganetespib than with most of the first generation hsp90 inhibitors (28).

Since both geldanamycin and radicicol target the highly conserved and unique ATP-binding domain of hsp90, new synthetic inhibitors have also been generated by rational drug design (22, 25–27). However, none of the various natural or synthetic hsp90 inhibitors under investigation have yet provided convincing clinical data, and future studies will show whether hsp90 can eventually be added to the list of effective cancer targets.

Hsp70, Hsp40, Hsp27, and HSF1

Hsp90 is assisted by several other HSPs and non-chaperoning co-factors, finally forming a large protein complex that recruits and releases client proteins in an energy-dependent manner (21, 22, 29). Client proteins for hsp90 are first bound to hsp70, which transfers the prospective client to hsp90 through the mediating help of an hsp70–hsp90 organizing protein (HOP). Binding of potential hsp90 client proteins to hsp70 is facilitated by its co-chaperone hsp40 (23, 30). Exposed hydrophobic amino acids, the typical feature of misfolded proteins, have been described as the main recognition signal for hsp70 proteins (15, 16, 31). Hsp70 proteins are not only supporter proteins for hsp90 but also represent a large chaperone family capable of acting independently of hsp90 and that can be found in all cellular compartments, including cytosol and nucleus (hsp70, hsp72, hsc70), mitochondria (GRP75 = mortalin), and the ER (GRP78 = BiP). Hsp70 chaperones may act on misfolded or nascent proteins either as “holders” or “folders” (31), which means that they prevent protein aggregation either by sheltering these aggregation-prone protein intermediates or by allowing these proteins to fold/refold into their native form in an assisted mechanism within a protected environment (31). Hsc70 (HSPA8) is a constitutively expressed major hsp70 isoform that is an essential factor for normal protein homeostasis even in unstressed cells (16). Misfolded proteins can also be destined by hsp70 proteins for their ultimate degradation. Proteins that expose KFERQ amino acid motifs on their surface during their unfolding process are preferentially bound by hsc70 and can be directed to lysosomes in a process called chaperone-mediated autophagy (CMA) (32, 33). In another mechanism of targeted protein degradation, interaction of hsc70 with the E3 ubiquitin ligase CHIP (carboxyl terminus of Hsc70-interacting protein) leads to ubiquitination of misfolded proteins and thus their destination of the ubiquitin-proteasome protein degradation pathway (34, 35). Since hsc70 is essential for normal protein homeostasis and its knock-out is lethal in mice (16, 36), hsc70 inhibition might not be an optimal target for cancer-specific induction of misfolded proteins. This contrasts with the inducible forms of hsp70 such as hsp72 (HSPA1), which are upregulated in a cell stress-specific manner and are often found to be constitutively overexpressed in cancer tissues (16, 36). Transcriptional activation of these inducible HSPs is mediated by the heat shock factor 1 (HSF1), which also regulates expression of hsp40 and the small HSP hsp27 by sharing a common promoter consensus sequence (heat shock response element) for HSF1 binding (37). HSF1 was also found to be constitutively activated in cancer tissues, modulating several cell cycle- and apoptosis-related pathways via its target genes (38–40). HSF1 itself is kept inactive in the cytosol by binding to hsp90, and the recruitment of hsp90 to misfolded proteins is considered a main activation mechanism to release monomeric HSF1 for its subsequent trimerization, post-translational activation, and nuclear translocation (24, 41). Also, since hsp90 inhibition causes hsp70 induction by HSF1 activation as a compensatory feed-back mechanism (24), combined inhibition of hsp90 and hsp70, or of hsp90 and HSF1 might be a more effective therapeutic approach for cancer treatment than single HSP targeting alone.

Indeed, several small-molecule inhibitors and aptamers for hsp70, hsp40, and hsp27 have been designed (16, 42–44), but most of them remain in pre-clinical development, or are either not applicable in humans or associated with intolerable side effects (16, 42–44). Notably, the natural bioflavonoid quercetin was shown to inhibit phosphorylation and transcriptional activity of the heat shock transcription factor HSF1, thus reducing HSP expression at its most basal level (45–48). This HSP and HSF1 inhibition may also contribute to the observed cancer-preventing effects of a flavonoid-rich diet, which includes fruits and vegetables. However, due to their low bioavailability, the concentrations of flavonoids needed to induce direct cytotoxic effects in cancer cells for (chemo-)therapeutic reasons are obviously not achievable in humans, even when applied as nutritional supplements (49). More effective and clinically more easily applicable inhibitors of HSF1 are therefore urgently sought. Promising HSF1 targeting strategies are currently under development, although are apparently not yet suited for clinical applications (24, 50, 51).

SP Williams Comment:

There is a new hsp90- inhibitor, ganetespib, which is active against ovarian cancer in vitro and in vivo. Clinical trials are looking at this in cisplatin refractory cases. This was identified by a network analysis from a previous siRNA screen on ovarian cancer cells for pathways related to growth inhibition in an effort to find possible targets against CP resistance. The reference ishttp://www.researchgate.net/publication/253647952_Network_analysis_identifies_an_HSP90-central_hub_susceptible_in_ovarian_cancer

Protein Ubiquitination and Proteasomal Degradation

Ubiquitin is a 76 amino acid polypeptide that can covalently be attached via its carboxy-terminus to free (lysyl) amino groups of proteins. Ubiquitination of proteins generates a cellular recognition motif that is involved in various functions ranging from transcription factor and protein kinase activation to DNA repair and protein degradation – depending on the extent and exact location of this post-translational modification (52, 53). Monoubiquitination of peptides of more than 20 amino acids was found to be a minimal requirement for protein degradation, but the canonical fourfold (poly-)ubiquitination with three further lysine (K48) side chain-linked ubiquitins appears to be most apt for an effective and rapid substrate recognition by the proteasome (54). This canonical polyubiquitin structure, as well as several other mixed polyubiquitin structures, can be recognized by the external 19S subunits of the 26S proteasome complex (54, 55). Prior to degradation of ubiquitinated proteins by the proteasomal 20S core subunit, the attached ubiquitin chains are released by the external 19S subunits for recycling, although they can also be co-degraded by the proteasome (56). After first passing the 19S subunit, the proteasomal target proteins are then unfolded in an energy-dependent manner and introduced into the narrow enzymatic cavity of proteasome for degradation. The barrel-shaped 20S proteasomal core complex contains three different proteolytic activities in duplicate (β1: caspase-like-, β2: tryptic-, and β5: chymotryptic activity), which initiate an efficient cleavage of the proteasomal target proteins into smaller peptides (57).

It is important to note that specific ubiquitination and ensuing proteasomal degradation is not an exclusive degradation mechanism of misfolded proteins but is also used to regulate the expression level of several native cell cycle regulatory proteins [cyclins, proliferating cell nuclear antigen (PCNA), p53], signaling pathway molecules (β-catenin, IκB), and survival factors (mcl-1) during the course of normal protein homeostasis and cell cycle progression (53, 55, 57, 58). Moreover, proteasomes are involved in protein maturation, including the processing and maturation of the NF-κB transcription factor subunit p50 and the drug-resistant protein MDR1 (57). Therefore, targeting proteasomal activity has not only been of interest for the generation of misfolded, cytotoxic proteins but also for interfering with the expression of proteins involved in several hallmarks of cancer, including cell cycle progression, signal transduction, and apoptosis.

Proteasome Inhibitors

Bortezomib (PS-341, Velcade ™) has long been known as a paragon of a clinically applicable proteasome inhibitor. Bortezomib has been approved for the treatment of multiple myeloma and mantle cell lymphoma (55, 59, 60). The great expectations of transferring the success of bortezomib to non-hematological solid cancer types have unfortunately not yet been fulfilled. It has been suggested that the high antibody-producing capacity of myeloma cells and thus the need for an efficient proteasomal degradation system to cope with the recycling process of misfolded ER-generated antibodies [ER-associated degradation process (ERAD); see below] might contribute to the high sensitivity of myeloma cells to bortezomib (9, 60, 61). Originally, bortezomib was developed to inhibit the proteasomal degradation of the NF-κB inhibitor IκB, thus targeting the pro-inflammatory, but also cancer-promoting, effect of the NF-κB transcription factor (55, 60, 62). Recent insights indicate that the anti-tumoral effect of bortezomib is not only mediated by its NF-κB inhibitory activity but also by its ability to induce accumulation of misfolded proteins in the cytosol and the ER (60, 62–65). However, the use of bortezomib, even for highly sensitive multiple myeloma, is limited by its strong tendency to induce a proteasome inhibition-independent peripheral neuropathy by acting on neuronal mitochondria (61). Since neurodegenerative diseases are associated with protein misfolding and aggregation, the neuropathological effects of bortezomib might also be assumed to be mediated by the possible proteotoxic effects of bortezomib in neuronal cells. However, although proteasome inhibitor-induced neurodegeneration and inclusion body formation have been described in animal models, similarities between proteasome inhibitor-induced neurodegeneration and Parkinson’s disease-like histopathological features could not be established (66).

Table 1 Drugs described in this review and their mechanism of action (MOA), status of approval, and main adverse effects.

Aggresome Formation and Re-Solubilization: Role of HDAC6

As depicted above, proteasome and HSP inhibition will eventually lead to the accumulation of misfolded and polyubiquitinated proteins. Based on their inherent cohesive properties mediated by their exposed hydrophobic surfaces, both ubiquitinated and non-ubiquitinated misfolded proteins tend to adhere as small aggregates (Figure ​(Figure1).1). Individual ubiquitinated proteins and small ubiquitinated aggregates can be recognized by specific ubiquitin-binding proteins such as HDAC6 via its zinc finger ubiquitin-binding domain. HDAC6 is an unusual histone deacetylase located in the cytosol that regulates microtubule acetylation and is also able to bind ubiquitinated proteins. Based on HDAC6’s additional ability to bind to microtubule motor protein dynein, these aggregates are actively transported along the microtubular system into perinuclear aggregates around the microtubule organizing center (MTOC) (108384). Recognition of small, scattered ubiquitinated aggregates by HDAC6 has been described as being mediated by unanchored ubiquitin chains, which are generated by aggregate-attached ubiquitin ligase ataxin-3 (85). Whereas proteasomal target proteins are primarily tagged by K-48 (lysine-48) linked ubiquitins; K-63 linked ubiquitin chains appear to be a preferential modification for aggresomal targeting by HDAC6 and were assumed to mediate a redirection from proteasomal degradation to aggresome formation in the case of proteasomal inhibition or overload (86). Accordingly, aggresome formation is not an unspecific protein aggregation but a specific, ubiquitin-controlled sorting process. Furthermore, these aggresomes consist not only of misfolded and deposited proteins but have also been shown to contain a large amount of associated HSPs and ubiquitin-binding proteins, including HDAC6 [Figure ​[Figure1;1; (108384)]. Aggresomes contain, and are also surrounded by, large numbers of proteasomes (108384), which help to resolubilize these aggregates not only through their intrinsic proteasomal digestion but also by generating unanchored K63-branched polyubiquitin chains, which then stimulate HDAC6-mediated autophagy, another cellular disposal mechanism in involving HDAC6 (87). Notably, HDAC6 has also been shown to control further maturation of autophagic vesicles by stimulating autophagosome–lysosome fusion (Figure ​(Figure1)1) in a manner different from the normal autophagosome–lysosome fusion process (88).

Figure 1

Drugs that inhibit folding or disposal of misfolded proteins. Native mature proteins, nascent proteins, or misfolded proteins can be prevented from folding or refolding by small and large heat shock protein inhibitors, of which the hsp90 inhibitors based 

The HDAC6 multitalent also exerts its deacetylase activity on hsp90 and modifies hsp90 client binding by facilitating its chaperoning of steroid hormone receptors and HSF1 (8991). Recruitment of HDAC6 to ubiquitinated proteins leads to the dissociation of the repressive HDAC6/hsp90/HSF1 complex (91) and allows the release of transcriptionally active HSF1 to the nucleus. The engagement of HDAC6 at the aggresome–autophagy pathway hence also indirectly facilitates HSF1 activity. p97/VCP (valosin-containing protein), another binding partner of HDAC6 and itself a multi-interactive, ATP-dependent chaperone (9294), is assumed to be involved not only in the specific separation of hsp90 and HSF1 by its “segregase” activity but also in the binding and remodeling of polyubiquitinated proteins before their delivery to the proteasome (9395). Additionally, p97/VCP dissociates polyubiquitinated proteins bound to HDAC6 (91). Accumulation of polyubiquitinated proteins thus leads to HDAC6-dependent HSF1 activation and HSP induction, p97/VCP-dependent recruitment and “preparation” of polyubiquitinated proteins to proteasomes, and, in the case of pharmacological proteasome inhibition or physiological overload, to an HDAC6-dependent detoxification of polyubiquitinated proteins by the aggresome/autophagy pathway.

Pharmacological Inhibition of Aggresome Formation: HDAC6 Inhibitors

The central involvement of HDAC6 in aggresome formation and clearance makes HDAC6 one of the most interesting druggable targets for the induction of proteotoxicity in cancer cells. Also, HDAC6 has been found to be overexpressed in various cancer tissues, associated with advanced cancer stages and increased neoplastic transformation (96). Several pan-histone deacetylase inhibitors have been developed and tested in clinical studies for a variety of diseases, including different types of cancer (9798). Although hematological malignancies responded best to most of the already clinically tested pan-histone deacetylase inhibitors, the efficacy on solid cancer types was disappointingly poor and also associated with intolerable side effects (98). The unforeseeable pleiotropic epigenetic mechanism caused by non-specific (nuclear) histone deacetylase inhibitors may also limit their application for use in cancer treatment or HDAC6 inhibition, and has led to the search for selective HDAC6 inhibitors with no inhibitory effects on transcription modifying histone deacetylases. Through screening of small molecules under the rationale of selecting for tubulin deacetylase inhibitors with no cross-reactive histone deacetylase activity, the HDAC6 inhibitor tubacin was identified, and suggested for use in the treatment of neurodegenerative diseases or to reduce cancer cell migration and angiogenesis (99). Hideshima et al. then proved the hypothesis that the combined use of bortezomib with tubacin leads to an accumulation of non-disposed cytotoxic proteins and aggregates in cancer cells (100). Indeed, a synergistic effect of these two drugs against multiple myeloma cells could be observed with no detectable toxic effect on peripheral blood mononuclear cells (100). This and follow-up studies also revealed the efficacy of tubacin as a single agent against leukemia cells (100101) and a chemo-sensitizing effect on cytotoxic drugs in breast- and prostate-cancer cells (102).

Endoplasmic Reticulum Stress

Besides the cytosol, the ER is a major site for protein synthesis, in particular for those proteins destined for extracellular secretion, the cell membrane, or their retention within the endomembrane system. At the rough ER, nascent proteins are co-translationally transported across the ER membrane into the ER lumen (107), where they immediately encounter ER-resident chaperones, most prominently represented by hsp70 family member BiP/GRP78 and hsp90 family member GRP94 to help proper protein folding (15108). Most of these proteins also undergo post-translational modifications, including N- or O-linked glycosylation or protein disulfide bridge-building (109110), thereby adding further mechanisms of protein stabilization but also challenges for proper protein folding.

Similar to the situation in cytosolic protein biosynthesis, a large proportion of nascent proteins in the ER are assumed to misfold and to go “off-pathway” even under normal physiological conditions. Furthermore, the ER lumen, narrowly sandwiched between two phospholipid membranes, has been described as an even more densely crowded environment than the cytosol, additionally facilitating unspecific protein attachments and aggregations (15). Since, with the exception of bulk reticulophagy, the lumen of the ER contains no endogenous protein degradation system, and the anterograde transport of ER proteins to the Golgi, lysosomes, endosomes, or the extracellular environment requires properly folded proteins, a retrograde transport of ER proteins into the cytosol remains the only possible mechanism of preventing misfolded protein accumulation within the ER. In this ERAD, misfolded proteins are re-exported across the ER membrane by a specific multi protein complex, ubiquitinated by ER membrane-integrated ubiquitin ligases, and finally become degraded by cytosolic proteasomes (111112). Notably, association of the cytosolic p97/VCP protein, an important interacting partner with HDAC6, has also been described as being an essential factor for driving the luminal proteins through the ER membrane pore complex into the cytosol (92,112).

Accordingly, all agents and conditions that interfere with these folding, maturation, and retranslocation processes can lead to protein misfolding and aggregation within this sensitive organelle. Chemicals that act as glycosylation inhibitors (tunicamycin), calcium ionophore inhibitors (A23187, thapsigargin), heavy metal ions (cadmium, lead), reducing agents (dithiothreitol), as well as conditions like hypoxia or oxidative stress, all lead to a phenomenon called ER stress (113116). In the ER-stress response, a triad of ER membrane-resident signaling receptors and transducers, IRE1, ATF6, and PERK1, become activated and lead to the transcriptional activation of cytosolic and ER-resident chaperones to cope with the increasing number of misfolded proteins. Induction of autophagy (reticulophagy; ER-phagy) may also occur and supports the removal of damaged regions of the ER (117). Under very intensive or even unmanageable ER-stress conditions, a variety of pro-apoptotic pathways ensue, including CHOP induction, c-JUN-kinase activation, and caspase cleavage (118120), which eventually prevails over the cytoprotective arm of the ER-stress response and may lead to apoptosis. Targeting of protein folding within the ER is therefore a very promising strategy to induce apoptosis in cancer cells, in particular in those cancer cells characterized by an unphysiologically high protein secretion rate, such as, for example, multiple myeloma cells. Whereas the above-mentioned drugs such as tunicamycin or thapsigargin are valuable tools for cell biology studies, they display unacceptable toxicities in humans and are not suited for therapeutic applications. Interestingly, several already established drugs used for non-cancerous diseases have been described as inducing ER stress at pharmacologically relevant concentrations in humans as an off-target effect (113116). The non-steroidal anti-inflammatory COX-2 inhibitor celecoxib is an approved drug to treat various forms of arthritis and pain, but has also been described as exerting ER stress by functioning as a SERCA (sarco/ER Ca2+ ATPase) inhibitor (113116). However, although well tolerated in humans, the ER-stress-inducing ability of celecoxib seems to be weaker than that of direct SERCA inhibitors such as thapsigargin, and the usefulness of celecoxib against advanced cancer has been questioned (116). Various HIV protease inhibitors have been described as inducing ER stress in human tissue cells as a side effect (121123). In particular the HIV drugs lopinavir, saquinavir, and nelfinavir appear to be potent inducers of the ER-stress reaction, leading to a focused interest in these drugs for the induction of ER stress and apoptosis in cancer cells (116124128). In fact, with currently over 27 clinical studies in cancer patients2, nelfinavir, either used as a single agent or in combination therapy, is on the list of the most promising prospective candidates to induce selective proteotoxicity in cancer cells at pharmacologically relevant concentrations. Although the exact mechanism by which nelfinavir induces ER stress is not yet clear, it was shown that nelfinavir causes the upregulation of cytosolic and ER-resident HSPs, and induces apoptosis in cancer cells associated with caspase activation and induction of the pro-apoptotic transcription factor CHOP (125126). Nelfinavir was also shown to be combinable with bortezomib to enhance its activity on cancer cells (129). Since the retrograde transport of misfolded ER proteins is inhibited by the p97/VCP inhibitor eeyarestatin (130131), we recently tested the combination of eeyarestatin with nelfinavir but found no synergistic effect between these two agents in cervical cancer cells (132). In contrast, eeyarestatin markedly sensitized cervical cancer cells to bortezomib treatment (132), which was also observed in preceding studies in which eeyarestatin was used to augment the ER-stress-inducing ability of bortezomib in leukemia cells (131).

Induction of proteotoxicity through the accumulation of misfolded proteins has evolved as a new treatment modality in the fight against cancer. Clinically approved drugs such as bortezomib and carfilzomib provide evidence of the functionality of this approach. Newly developed agents like the HDAC6 inhibitor ACY-1215 or repurposed drugs like nelfinavir or disulfiram are currently being tested in clinical trials with cancer patients and will hopefully further broaden our arsenal of anti-cancer drugs. Notably, most proteotoxic agents that have been approved or are in clinical trials target the ubiquitin-proteasome-system (UPS) and are mainly effective in multiple myeloma cells, which rely on a functional ER/ERAD/UPS for excessive and proper antibody production. Similarly, it can be assumed that other cancer cell types with a marked secretory phenotype may also be affected by ER/ERAD/UPS inhibitors. In accordance with this notion, a recent dose-escalating Phase Ia study with nelfinavir as a single agent, that covered a large variety of solid cancer entities, revealed response rates primarily in patients with neuroendocrine tumors (140). In most other solid cancer types, however, the chemo-sensitizing or combination effects of proteotoxic drugs may prevail, and have become the focus of an increasing number of very promising clinical and pre-clinical studies.

7.3.4 Endoplasmic reticulum protein 29 (ERp29) in epithelial cancer

Friend or Foe: Endoplasmic reticulum protein 29 (ERp29) in epithelial cancer

Chen S1Zhang D2

FEBS Open Bio. 2015 Jan 30; 5:91-8
http://dx.doi.org:/10.1016/j.fob.2015.01.004

The endoplasmic reticulum (ER) protein 29 (ERp29) is a molecular chaperone that plays a critical role in protein secretion from the ER in eukaryotic cells. Recent studies have also shown that ERp29 plays a role in cancer. It has been demonstrated that ERp29 is inversely associated with primary tumor development and functions as a tumor suppressor by inducing cell growth arrest in breast cancer. However, ERp29 has also been reported to promote epithelial cell morphogenesis, cell survival against genotoxic stress and distant metastasis. In this review, we summarize the current understanding on the biological and pathological functions of ERp29 in cancer and discuss the pivotal aspects of ERp29 as “friend or foe” in epithelial cancer.

The endoplasmic reticulum (ER) is found in all eukaryotic cells and is complex membrane system constituting of an extensively interlinked network of membranous tubules, sacs and cisternae. It is the main subcellular organelle that transports different molecules to their subcellular destinations or to the cell surface [10,85].

The ER contains a number of molecular chaperones involved in protein synthesis and maturation. Of the ER chaperones, protein disulfide isomerase (PDI)-like proteins are characterized by the presence of a thioredoxin domain and function as oxido-reductases, isomerases and chaperones [33]. ERp29 lacks the active-site double-cysteine (CxxC) motif and does not belong to the redox-active PDIs [5,47]. ERp29 is recognized as a characterized resident of the cellular ER, and it is expressed ubiquitously and abundantly in mammalian tissues [50]. Protein structural analysis showed that ERp29 consists of N-terminal and C-terminal domains [5]: N-terminal domain involves dimerization whereas the C-terminal domain is essential for substrate binding and secretion [78]. The biological function of ERp29 in protein secretion has been well established in cells [8,63,67].

ERp29 is proposed to be involved in the unfolded protein response (UPR) as a factor facilitating transport of synthesized secretory proteins from the ER to Golgi [83]. The expression of ERp29 was demonstrated to be increased in cells exposed to radiation [108], sperm cells undergoing maturation [42,107], and in certain cell types both under the pharmacologically induced UPR and under the physiological conditions (e.g., lactation, differentiation of thyroid cells) [66,82]. Under ER stress, ERp29 translocates the precursor protein p90ATF6 from the ER to Golgi where it is cleaved to be a mature and active form p50ATF by protease (S1P and S2P) [48]. In most cases, ERp29 interacts with BiP/GRP78 to exert its function under ER stress [65].

ERp29 is considered to be a key player in both viral unfolding and secretion [63,67,77,78] Recent studies have also demonstrated that ERp29 is involved in intercellular communication by stabilizing the monomeric gap junction protein connexin43 [27] and trafficking of cystic fibrosis transmembrane conductance regulator to the plasma membrane in cystic fibrosis and non-cystic fibrosis epithelial cells [90]. It was recently reported that ERp29 directs epithelial Na(+) channel (ENaC) toward the Golgi, where it undergoes cleavage during its biogenesis and trafficking to the apical membrane [40]. ERp29 expression protects axotomized neurons from apoptosis and promotes neuronal regeneration [111]. These studies indicate a broad biological function of ERp29 in cells.

Recent studies demonstrated a tumor suppressive function of ERp29 in cancer. It was found that ERp29 expression inhibited tumor formation in mice [4,87] and the level of ERp29 in primary tumors is inversely associated with tumor development in breast, lung and gallbladder cancer [4,29].

However, its expression is also responsible for cancer cell survival against genotoxic stress induced by doxorubicin and radiation [34,76,109]. The most recent studies demonstrate other important roles of ERp29 in cancer cells such as the induction of mesenchymal–epithelial transition (MET) and epithelial morphogenesis [3,4]. MET is considered as an important process of transdifferentiation and restoration of epithelial phenotype during distant metastasis [23,52]. These findings implicate ERp29 in promoting the survival of cancer cells and also metastasis. Hence, the current review focuses on the novel functions of ERp29 and discusses its pathological importance as a “friend or foe” in epithelial cancer.

2. ERp29 regulates mesenchymal–epithelial transition

2.1. Epithelial–mesenchymal transition (EMT) and MET

The EMT is an essential process during embryogenesis [6] and tumor development [43,96]. The pathological conditions such as inflammation, organ fibrosis and cancer progression facilitate EMT [16]. The epithelial cells after undergoing EMT show typical features characterized as: (1) loss of adherens junctions (AJs) and tight junctions (TJs) and apical–basal polarity; (2) cytoskeletal reorganization and distribution; and (3) gain of aggressive phenotype of migration and invasion [98]. Therefore, EMT has been considered to be an important process in cancer progression and its pathological activation during tumor development induces primary tumor cells to metastasize [95]. However, recent studies showed that the EMT status was not unanimously correlated with poorer survival in cancer patients examined [92].

In addition to EMT in epithelial cells, mesenchymal-like cells have capability to regain a fully differentiated epithelial phenotype via the MET [6,35]. The key feature of MET is defined as a process of transdifferentiation of mesenchymal-like cells to polarized epithelial-like cells [23,52] and mediates the establishment of distant metastatic tumors at secondary sites [22]. Recent studies demonstrated that distant metastases in breast cancer expressed an equal or stronger E-cadherin signal than the respective primary tumors and the re-expression of E-cadherin was independent of the E-cadherin status of the primary tumors [58]. Similarly, it was found that E-cadherin is re-expressed in bone metastasis or distant metastatic tumors arising from E-cadherin-negative poorly differentiated primary breast carcinoma [81], or from E-cadherin-low primary tumors [25]. In prostate and bladder cancer cells, the nonmetastatic mesenchymal-like cells were interacted with metastatic epithelial-like cells to accelerate their metastatic colonization [20]. It is, therefore, suggested that the EMT/MET work co-operatively in driving metastasis.

2.2. Molecular regulation of EMT/MET

E-cadherin is considered to be a key molecule that provides the physical structure for both cell–cell attachment and recruitment of signaling complexes [75]. Loss of E-cadherin is a hallmark of EMT [53]. Therefore, characterizing transcriptional regulators of E-cadherin expression during EMT/MET has provided important insights into the molecular mechanisms underlying the loss of cell–cell adhesion and the acquisition of migratory properties during carcinoma progression [73].

Several known signaling pathways, such as those involving transforming growth factor-β (TGF-β), Notch, fibroblast growth factor and Wnt signaling pathways, have been shown to trigger epithelial dedifferentiation and EMT [28,97,110]. These signals repress transcription of epithelial genes, such as those encoding E-cadherin and cytokeratins, or activate transcription programs that facilitate fibroblast-like motility and invasion [73,97].

The involvement of microRNAs (miRNAs) in controlling EMT has been emphasized [11,12,18]. MiRNAs are small non-coding RNAs (∼23 nt) that silence gene expression by pairing to the 3′UTR of target mRNAs to cause their posttranscriptional repression [7]. MiRNAs can be characterized as “mesenchymal miRNA” and “epithelial miRNA” [68]. The “mesenchymal miRNA” plays an oncogenic role by promoting EMT in cancer cells. For instance, the well-known miR-21, miR-103/107 are EMT inducer by repressing Dicer and PTEN [44].

The miR-200 family has been shown to be major “epithelial miRNA” that regulate MET through silencing the EMT-transcriptional inducers ZEB1 and ZEB2 [13,17]. MiRNAs from this family are considered to be predisposing factors for cancer cell metastasis. For instance, the elevated levels of the epithelial miR-200 family in primary breast tumors associate with poorer outcomes and metastasis [57]. These findings support a potential role of “epithelial miRNAs” in MET to promote metastatic colonization [15].

2.3. ERp29 promotes MET in breast cancer

The role of ERp29 in regulating MET has been established in basal-like MDA-MB-231 breast cancer cells. It is known that myosin light chain (MLC) phosphorylation initiates to myosin-driven contraction, leading to reorganization of the actin cytoskeleton and formation of stress fibers [55,56]. ERp29 expression in this type of cells markedly reduced the level of phosphorylated MLC [3]. These results indicate that ERp29 regulates cortical actin formation through a mechanism involved in MLC phosphorylation (Fig. 1). In addition to the phenotypic change, ERp29 expression leads to: expression and membranous localization of epithelial cell marker E-cadherin; expression of epithelial differentiation marker cytokeratin 19; and loss of the mesenchymal cell marker vimentin and fibronectin [3] (Fig. 1). In contrast, knockdown of ERp29 in epithelial MCF-7 cells promotes acquisition of EMT traits including fibroblast-like phenotype, enhanced cell spreading, decreased expression of E-cadherin and increased expression of vimentin [3,4]. These findings further substantiate a role of ERp29 in modulating MET in breast cancer cells.

Fig. 1  ERp29 triggers mesenchymal–epithelial transition. Exogenous expression of ERp29 in mesenchymal MDA-MB-231 breast cancer cells inhibits stress fiber formation by suppressing MLC phosphorylation. In addition, the overexpressed ERp29 decreases the 

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2.4. ERp29 targets E-cadherin transcription repressors

The transcription repressors such as Snai1, Slug, ZEB1/2 and Twist have been considered to be the main regulators for E-cadherin expression [19,26,32]. Mechanistic studies revealed that ERp29 expression significantly down-regulated transcription of these repressors, leading to their reduced nuclear expression in MDA-MB-231 cells [3,4] (Fig. 2). Consistent with this, the extracellular signal-regulated kinase (ERK) pathway which is an important up-stream regulator of Slug and Ets1 was highly inhibited [4]. Apparently, ERp29 up-regulates the expressions of E-cadherin transcription repressors through repressing ERK pathway. Interestingly, ERp29 over-expression in basal-like BT549 cells resulted in incomplete MET and did not significantly affect the mRNA or protein expression of Snai1, ZEB2 and Twist, but increased the protein expression of Slug [3]. The differential regulation of these transcriptional repressors of E-cadherin by ERp29 in these two cell-types may occur in a cell-context-dependent manner.

Fig. 2  ERp29 decreases the expression of EMT inducers to promote MET. Exogenous expression of ERp29 in mesenchymal MDA-MB-231 breast cancer cells suppresses transcription and protein expression of E-cadherin transcription repressors (e.g., ZEB2, SNAI1 and Twist), ..

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2.5. ERp29 antagonizes Wnt/ β-catenin signaling

Wnt proteins are a family of highly conserved secreted cysteine-rich glycoproteins. The Wnt pathway is activated via a binding of a family member to a frizzled receptor (Fzd) and the LDL-Receptor-related protein co-receptor (LRP5/6). There are three different cascades that are activated by Wnt proteins: namely canonical/β-catenin-dependent pathway and two non-canonical/β-catenin-independent pathways that include Wnt/Ca2+ and planar cell polarity [84]. Of note, the Wnt/β-catenin pathway has been extensively studied, due to its important role in cancer initiation and progression [79]. The presence of Wnt promotes formation of a Wnt–Fzd–LRP complex, recruitment of the cytoplasmic protein Disheveled (Dvl) to Fzd and the LRP phosphorylation-dependent recruitment of Axin to the membrane, thereby leading to release of β-catenin from membrane and accumulation in cytoplasm and nuclei. Nuclear β-catenin replaces TLE/Groucho co-repressors and recruits co-activators to activate expression of Wnt target genes. The most important genes regulated are those related to proliferation, such as Cyclin D1 and c-Myc [46,94], which are over-expressed in most β-catenin-dependent tumors. When β-catenin is absent in nucleus, the transcription factors T-cell factor/lymphoid enhancer factors (TCF/LEF) recruits co-repressors of the TLE/Groucho family and function as transcriptional repressors.

β-catenin is highly expressed in the nucleus of mesenchymal MDA-MB-231 cells. ERp29 over-expression in this type of cells led to translocation of nuclear β-catenin to membrane where it forms complex with E-cadherin [3] (Fig. 3). This causes a disruption of β-catenin/TCF/LEF complex and abolishes its transcription activity. Indeed, ERp29 significantly decreased the expression of cyclin D1/D2 [36], one of the downstream targets of activated Wnt/β-catenin signaling [94], indicating an inhibitory effect of ERp29 on this pathway. Meanwhile, expression of ERp29 in this cell type increased the nuclear expression of TCF3, a transcription factor regulating cancer cell differentiation while inhibiting self-renewal of cancer stem cells [102,106]. Hence, ERp29 may play dual functions in mesenchymal MDA-MB-231 breast cancer cells by: (1) suppressing activated Wnt/β-catenin signaling via β-catenin translocation; and (2) promoting cell differentiation via activating TCF3 (Fig. 3). Because β-catenin serves as a signaling hub for the Wnt pathway, it is particularly important to focus on β-catenin as the target of choice in Wnt-driven cancers. Though the mechanism by which ERp29 expression promotes the disassociation of β-catenin/TCF/LEF complex in MDA-MB-231 cells remains elusive, activating ERp29 expression may exert an inhibitory effect on the poorly differentiated, Wnt-driven tumors.

Fig. 3  ERp29 over-expression “turns-off” activated Wnt/β-catenin signaling. In mesenchymal MDA-MB-231 cells, high expression of nuclear β-catenin activates its downstream signaling involved in cell cycles and cancer stem cell 

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3. ERp29 regulates epithelial cell integrity

3.1. Cell adherens and tight junctions

Adherens junctions (AJs) and tight junctions (TJs) are composed of transmembrane proteins that adhere to similar proteins in the adjacent cell [69]. The transmembrane region of the TJs is composed mainly of claudins, tetraspan proteins with two extracellular loops [1]. AJs are mediated by Ca2+-dependent homophilic interactions of cadherins [71] which interact with cytoplasmic catenins that link the cadherin/catenin complex to the actin cytoskeleton [74].

The cytoplasmic domain of claudins in TJs interacts with occludin and several zona occludens proteins (ZO1-3) to form the plaque that associates with the cytoskeleton [99]. The AJs form and maintain intercellular adhesion, whereas the TJs serve as a diffusion barrier for solutes and define the boundary between apical and basolateral membrane domains [21]. The AJs and TJs are required for integrity of the epithelial phenotype, as well as for epithelial cells to function as a tissue [75].

The TJs are closely linked to the proper polarization of cells for the establishment of epithelial architecture[86]. During cancer development, epithelial cells lose the capability to form TJs and correct apico–basal polarity [59]. This subsequently causes the loss of contact inhibition of cell growth [91]. In addition, reduction of ZO-1 and occludin were found to be correlated with poorly defined differentiation, higher metastatic frequency and lower survival rates [49,64]. Hence, TJs proteins have a tumor suppressive function in cancer formation and progression.

3.2. Apical–basal cell polarity

The apical–basal polarity of epithelial cells in an epithelium is characterized by the presence of two specialized plasma membrane domains: namely, the apical surface and basolateral surface [30]. In general, the epithelial cell polarity is determined by three core complexes. These protein complexes include: (1) the partitioning-defective (PAR) complex; (2) the Crumbs (CRB) complex; and (3) the Scribble complex[2,30,45,51]. PAR complex is composed of two scaffold proteins (PAR6 and PAR3) and an atypical protein kinase C (aPKC) and is localized to the apical junction domain for the assembly of TJs [31,39]. The Crumbs complex is formed by the transmembrane protein Crumbs and the cytoplasmic scaffolding proteins such as the homologue of Drosophila Stardust (Pals1) and Pals-associated tight junction protein (Patj) and localizes to the apical [38]. The Scribble complex is comprised of three proteins, Scribble, Disc large (Dlg) and Lethal giant larvae (Lgl) and is localized in the basolateral domain of epithelial cells [100].

Fig. 4  ERp29 regulates epithelial cell morphogenesis. Over-expression of ERp29 in breast cancer cells induces the transition from a mesenchymal-like to epithelial-like phenotype and the restoration of tight junctions and cell polarity. Up-regulation and membrane 

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The current data from breast cancer cells supports the idea that ERp29 can function as a tumor suppressive protein, in terms of suppression of cell growth and primary tumor formation and inhibition of signaling pathways that facilitate EMT. Nevertheless, the significant role of ERp29 in cell survival against drugs, induction of cell differentiation and potential promotion of MET-related metastasis may lead us to re-assess its function in cancer progression, particularly in distant metastasis. Hence, it is important to explore in detail the ERp29’s role in cancer as a “friend or foe” and to elucidate its clinical significance in breast cancer and other epithelial cancers. Targeting ERp29 and/or its downstream molecules might be an alternative molecular therapeutic approach for chemo/radio-resistant metastatic cancer treatment

7.3.5 Putting together structures of epidermal growth factor receptors

Bessman NJ, Freed DM, Lemmon MA
Curr Opin Struct Biol. 2014 Dec; 29:95-101
http://dx.doi.org:/10.1016/j.sbi.2014.10.002

Highlights

  • Several studies suggest flexible linkage between extracellular and intracellular regions. • Others imply more rigid connections, required for allosteric regulation of dimers. • Interactions with membrane lipids play important roles in EGFR regulation. • Cellular studies suggest half-of-the-sites negative cooperativity for human EGFR.

Numerous crystal structures have been reported for the isolated extracellular region and tyrosine kinase domain of the epidermal growth factor receptor (EGFR) and its relatives, in different states of activation and bound to a variety of inhibitors used in cancer therapy. The next challenge is to put these structures together accurately in functional models of the intact receptor in its membrane environment. The intact EGFR has been studied using electron microscopy, chemical biology methods, biochemically, and computationally. The distinct approaches yield different impressions about the structural modes of communication between extracellular and intracellular regions. They highlight possible differences between ligands, and also underline the need to understand how the receptor interacts with the membrane itself.

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Growth factor receptor tyrosine kinases (RTKs) such as the epidermal growth factor receptor (EGFR) have been the subjects of intense study for many years [1,2]. There are 58 RTKs in the deduced human
proteome, and all play key roles in regulating cellular processes such as proliferation, differentiation, cell survival and metabolism, cell migration, and cell cycle control [3].  Importantly, aberrant activation
of RTK signaling by mutation, gene amplification, gene translocation or other mechanisms has been causally linked to cancers, diabetes, inflammation, and other diseases. These observations have prompted
the development of many targeted therapies that inhibit RTKs such as EGFR [4], Kit, VEGFR, or their ligands — typically employing therapeutic antibodies [5] or small molecule tyrosine kinase inhibitors [6].
Following the initial discoveries for EGFR [7] and the platelet-derived growth factor receptor (PDGFR) [8] that ligand-stabilized dimers are essential for RTK signaling, structural studies over the past decade
or so have guided development of quite sophisticated mechanistic views[1]. Each RTK has a ligand-binding extracellular region (ECR) that is linked by a single transmembrane a-helix to an intracellular
tyrosine kinase domain (TKD). Structures of the isolated ECRs and TKDs from several RTKs point to surprising mechanistic diversity across the larger family [1]. Unliganded RTKs exist as an equilibrium
mixture of inactive monomers, inactive dimers and active dimers (Figure 1), except for the extreme case of the insulin receptor (IR), which is covalently dimerized [9]. Extracellular ligand can bind to monomers,
to inactive dimers, or to active dimers — in each case pushing the equilibria shown in Figure 1 towards the central ligand-bound active dimer. Thus, ligand binding can drive receptor dimerization (Figure 1,
upper), or can promote inactive-to-active conformational transitions in dimers (Figure 1, lower). Regardless of pathway, the intracellular TKD of the ligand-stabilized dimer becomes activated either through
trans-autophosphorylation or through induced allosteric changes [1,10]. Roles for other parts of the receptor in RTK activation, including the juxtamembrane (JM) and transmembrane (TM) segments, have
also become clearer. The key current challenge for the field is to assemble data from many studies of isolated RTK parts into coherent views of how the intact receptors are regulated in their native membranes.
We will focus here on recent efforts to do this for the EGFR (or ErbB receptor) family. The missing links in intact RTKs: flexible or rigid? A central goal in extrapolating to the intact RTKs from studies of
isolated soluble domains is to understand how the individual parts of the receptor communicate with one another. The methods that have been used to produce and study the isolated domains inevitably
yield the impression that inter-domain linkers are flexible and disordered. For example, extracellular juxtamembrane regions have typically only been observed as C-terminal extensions of  the soluble ECR.
Similarly, intracellular juxtamembrane regions have been encountered predominantly as N-terminal extensions of TKD constructs, or as short peptides. In each of these contexts, the JM regions are incomplete,
and may appear disordered and flexible simply because key structural restraints have been removed. Nonetheless, this possible artifact has strongly influenced thinking about linkages between the extracellular
and intracellular regions [11], and in turn about mechanisms of RTK signaling. Highly flexible linkages between extracellular and intracellular regions of RTKs are fully consistent with simpler ligand-induced
dimerization models for transmembrane signaling by RTKs. It is more difficult, however, to understand how subtle allosteric communication across the membrane could be achieved if the linkages are truly
flexible. For example, since flexible linkage implies structural independence of the extracellular and intracellular regions, it is difficult to envision how a transition from inactive to active dimer in Figure 1
could be controlled precisely by ligand without more rigid (or restricted) connections.

Recent experimental studies with intact — or nearly intact — EGFR differ in the impressions they provide about how flexibly or rigidly the extracellular and intracellular regions are linked. Springer’s laboratory used cysteine crosslinking and mutagenesis approaches to investigate this issue for EGFR expressed in Ba/F3 cells [12]. They were unable to identify any specific JM or TM region interfaces
that were required for EGFR signaling, leading them to argue that the linkage across the membrane is too flexible to transmit a specific orientation between the extracellular and intracellular regions.
Consistent with this, negative-stain electron microscopy studies of (nearly) full-length EGFR in dodecylmaltoside micelles showed that a given extracellular dimer can be linked to several different
arrangements of the intracellular kinase domain [13,14]. Similarly, dimers driven by inhibitor binding to the intracellular TKD could couple to multiple different ECR conformations [13]. Biochemical
studies are also consistent with such structural independence of the extracellular and intracellular  regions [15,16]. Contrasting with these observations, however, Schepartz and colleagues have
reported that different precise conformations within the EGFR intracellular region can be induced by distinct activating ligands [17]. They used a method called bipartite tetracysteine display that
reports on formation of a chemically detectable tetracysteine motif when two cysteine pairs come together at  the dimer  interface. EGF activation of the receptor led to formation of a  tetracysteine
motif that requires the intracellular JM helix  [18] shown in Figure 2a to form antiparallel coiled-coil dimers  (Figure 2b/c) as proposed by Kuriyan and colleagues [19,20]. Surprisingly, transforming
growth factor-a (TGFa),which also activates EGFR, did not bring these two cysteine pairs together in the same way — arguing that TGFa does not induce formation of the same intracellular antiparallel
coiled-coil. Instead, activation of EGFR with TGFa (but not EGF) stabilized an alternative tetracysteine motif, consistent with a different intracellular JM structure. Evidence for ‘inside-out’ signaling
in EGFR has also been reported, where alterations in the intracellular JM region directly influence allosteric EGF binding to the ECR of the intact receptor analyzed in CHO cells [21–23]. The contradictory
views of flexibility versus rigidity  in linkages between the domains leave the path to understanding the intact receptor unclear, although it seems  reasonable doubt that  the inactive dimers known to
form in the absence of ligand [24–26] could be regulated by extracellular ligand if all linkages are always highly flexible.
Does the membrane hold the key?
All of the studies that support direct conformational communication between the extracellular and intracellular regions of EGFR were performed in cells [17,21,22]. By contrast, most of those that
explicitly suggest otherwise were performed in detergent micelles [13,14,15] — where the potentially important influences of specific membrane lipids (or membrane geometry) are absent. Studies of intact  EGFR in liposomes with defined lipid compositions [27] have shown that the ganglioside GM3 inhibits ligand-independent activation (and dimerization) of the receptor, apparently through interactions with a  site in its extracellular JM region. McLaughlin and colleagues [28,29] also proposed a model in which interaction of the intracellular JM region (and TKD) with anionic phospholipids in the inner leaflet of  the plasma membrane (notably PtdIns(4,5)P2) exerts an inhibitory effect that must be overcome in order for EGFR to signal. Association of the JM and TM regions with specific membrane lipids is likely to  define specific structures in the linkages between the EGFR extracellular and intracellular regions that are more well-defined (and potentially rigid) than is typically appreciated. Recent studies have begun to  shed some structural light on how membrane interactions with the intracellular JM region of EGFR might influence the signaling mechanism. Endres et al. [20] found that simply tethering the complete  intracellular region of EGFR to the inner leaflet of the plasma membrane maintains the TKD in a largely monomeric state and inhibits its kinase activity. Parallel computational studies [30] suggest that this  results from the previously proposed [29] inhibitory interaction of the JM and TKD regions of EGFR with the negatively charged membrane surface. The data of Endres et al. [20] further indicated that TM-mediated dimerization reverses this inhibitory effect. Moreover, NMR studies of a 60-residue peptide containing the TM and part of  the JM region solubilized in lipid bicelles led them to conclude that specific  TM dimerization through an N terminal GxxxG motif stabilizes formation of an antiparallel coiled-coil between the two JM fragments in the dimer — the same JM coiled-coil shown in Figure 2b/c that was  investigated in the bipartite tetracysteine display studies of  intact EGF-bound EGFR described above [17,19]. Independent solid-state NMR studies of a similar TM-JM peptide from the EGFR relative
ErbB2 in vesicles containing acidic phospholipids [31] further suggested that an activating mutation in the TM domain leads to release of  the JM region from the anionic membrane surface. Collectively,
these data suggest that ligand-induced dimerization of the receptor (or reorientation of receptors within a dimer) may engage the TM domain in a specific dimer that promotes both the formation of activating
interactions in the JM region and the disruption of inhibitory interactions between the JM region (and possibly TKD) and the membrane surface.

Negative cooperativity 
A key characteristic of ligand binding at the cell surface to EGFR [36], IR [37], and other receptors [38] is negative cooperativity — which is lost when soluble forms of the ECR from human EGFR [39]
or IR [40] are studied in isolation. Several studies have shown that intracellular and/or transmembrane regions are required for this negative cooperativity to be manifest [21,22,40,41], implying that
these parts of the receptor contribute to breaking the symmetry of the dimer — as required for the two sites to have distinct binding properties [42]. Such propagation of dimer asymmetry across the
membrane would surely require defined structures in the regions that connect extracellular and intracellular regions, and is difficult to reconcile with highly flexible JM linkers.
In brief, binding of one ligand stabilizes a singly-liganded asymmetric dimer in which the unoccupied ligand-binding site is compromised [43]. The binding affinity of the second ligand is thus reduced,
constituting a half-of-the-sites mode of negative cooperativity [44]. Leahy’s group has provided important evidence consistent with a similar mechanism in the cases of human EGFR and ErbB4 [16].
By comparing human ErbB receptor ECR dimer crystal structures with different bound ligands, Leahy and colleagues went on to identify two types of dimer interface [16], a ‘flush’ interface that resembles
the asymmetric (singly-liganded) dimer seen for the Drosophila EGFR [43] and a ‘staggered’ interface seen in the ECRs from EGFR (with bound EGF [12]) and ErbB4 (with bound neuregulin1b[16]).
These observations suggest that the ‘flush’ interface drives the most  stable dimers, which are singly liganded (Figure 2b). Binding of the second ligand is weaker, and also forces the dimer interface
into the less stable ‘staggered’ conformation (Figure 2c). Taken together, these findings suggest both a structural basis for negative cooperativity and a possible structural distinction between singly-liganded
and doubly-liganded ErbB receptor dimers.

A model for EGFR activation
The model shown in Figure 2 summarizes key proposed steps in the activation of human EGFR. In the absence of ligand, the ECR exists in a tethered conformation with the domain II ‘dimerization
arm’ engaged in an intramolecular interaction with domain IV that occludes the dimer interface [49]. The TKDs and the N-terminal portions of each intracellular JM region are thought to be engaged
in autoinhibitory interactions with the membrane surface [20,28,29,30].

Figure 2. More detailed view of EGF-induced activation of EGFR, as described in the text.
In the absence of ligand (a), the ECR adopts a tethered conformation, with an autoinhibitory tether interaction between domains II and IV. The TKD and JM regions lie against the membrane, making what
are believed to be additional autoinhibitory interactions. Domains I and III of the ECR are colored red, and domains II and IV are green. The JM helix is shown as a short cylinder and labeled in magenta.
The N-lobes and C-lobes of the kinase are also labeled, and both helix aC (blue) and the short helix in the activation loop (green) that interacts with aC to inhibit the TKD [50] are shown. The C-tail is
also depicted as a curve bearing 5 tyrosines. As described in the text, binding of a single ligand (b) induces formation of a singly-liganded dimer with a ‘flush’ (presumed asymmetric) ECR dimer interface.
The JM region forms an anti-parallel helix, as labeled in magenta, and the TKDs form an asymmetric dimer in which the activator (grey) allosterically activates the receiver (shown with an amber N-lobe).
It is not clear how the extracellular and intracellular asymmetry is structurally related, if at all. Finally, a second ligand binds to yield a more symmetric dimer with the ‘staggered’ ECR interface (c) described
in the text.

Conclusions Our mechanistic understanding of EGFR and its relatives has advanced dramatically in recent years, and the past year or two has seen substantial progress in putting the results of studies
with isolated domains together into initial views of how the intact receptor works. New insights into the origin of allosteric regulation of EGFR have been gained through a combination of innovative
structural, biochemical, cellular, and computational studies. A self-consistent picture is beginning to emerge. Two key issues remain unclear, however, and represent the current frontiers in studies of EGFR.
The first — for which we describe progress in this review — centers on the influence of specific interactions of the receptor with membrane lipids, which seem likely to define the structural ‘connections’
between extracellular and intracellular regions of the receptor. The second centers on the role of the carboxy-terminal 230 amino acids, which is believed to play a regulatory role for which little detail has
so far been defined [55].
(10PRE4140108).
DMF
is
supported
by

7.3.6 Complex Relationship between Ligand Binding and Dimerization in the Epidermal Growth Factor Receptor

Bessman NJ1Bagchi A2Ferguson KM2Lemmon MA3.
Cell Rep. 2014 Nov 20; 9(4):1306-17.
http://dx.doi.org/10.1016/j.celrep.2014.10.010

Highlights

  • Preformed extracellular dimers of human EGFR are structurally heterogeneous • EGFR dimerization does not stabilize ligand binding
    • Extracellular mutations found in glioblastoma do not stabilize EGFR dimerization • Glioblastoma mutations in EGFR increase ligand-binding affinity

The epidermal growth factor receptor (EGFR) plays pivotal roles in development and is mutated or overexpressed in several cancers. Despite recent advances, the complex allosteric regulation of EGFR remains incompletely understood. Through efforts to understand why the negative cooperativity observed for intact EGFR is lost in studies of its isolated extracellular region (ECR), we uncovered unexpected relationships between ligand binding and receptor dimerization. The two processes appear to compete. Surprisingly, dimerization does not enhance ligand binding (although ligand binding promotes dimerization). We further show that simply forcing EGFR ECRs into preformed dimers without ligand yields ill-defined, heterogeneous structures. Finally, we demonstrate that extracellular EGFR-activating mutations in glioblastoma enhance ligand-binding affinity without directly promoting EGFR dimerization, suggesting that these oncogenic mutations alter the allosteric linkage between dimerization and ligand binding. Our findings have important implications for understanding how EGFR and its relatives are activated by specific ligands and pathological mutations.

http://www.cell.com/cms/attachment/2020816777/2040986303/fx1.jpg

X-ray crystal structures from 2002 and 2003 (Burgess et al., 2003) yielded the scheme for ligand-induced epidermal growth factor receptor (EGFR) dimerization shown in Figure 1. Binding of a single ligand to domains I and III within the same extracellular region (ECR) stabilizes an “extended” conformation and exposes a dimerization interface in domain II, promoting self-association with a KD in the micromolar range (Burgess et al., 2003, Dawson et al., 2005, Dawson et al., 2007). Although this model satisfyingly explains ligand-induced EGFR dimerization, it fails to capture the complex ligand-binding characteristics seen for cell-surface EGFR, with concave-up Scatchard plots indicating either negative cooperativity (De Meyts, 2008, Macdonald and Pike, 2008) or distinct affinity classes of EGF-binding site with high-affinity sites responsible for EGFR signaling (Defize et al., 1989). This cooperativity or heterogeneity is lost when the ECR from EGFR is studied in isolation, as also described for the insulin receptor (De Meyts, 2008).

Figure 1

Structural View of Ligand-Induced Dimerization of the hEGFR ECR

(A) Surface representation of tethered, unliganded, sEGFR from Protein Data Bank entry 1NQL (Ferguson et al., 2003). Ligand-binding domains I and III are green and cysteine-rich domains II and IV are cyan. The intramolecular domain II/IV tether is circled in red.

(B) Hypothetical model for an extended EGF-bound sEGFR monomer based on SAXS studies of an EGF-bound dimerization-defective sEGFR variant (Dawson et al., 2007) from PDB entry 3NJP (Lu et al., 2012). EGF is blue, and the red boundary represents the primary dimerization interface.

(C) 2:2 (EGF/sEGFR) dimer, from PDB entry 3NJP (Lu et al., 2012), colored as in (B). Dimerization arm contacts are circled in red.

http://www.cell.com/cms/attachment/2020816777/2040986313/gr1.sml

Here, we describe studies of an artificially dimerized ECR from hEGFR that yield useful insight into the heterogeneous nature of preformed ECR dimers and into the origins of negative cooperativity. Our data also argue that extracellular structures induced by ligand binding are not “optimized” for dimerization and conversely that dimerization does not optimize the ligand-binding sites. We also analyzed the effects of oncogenic mutations found in glioblastoma patients (Lee et al., 2006), revealing that they affect allosteric linkage between ligand binding and dimerization rather than simply promoting EGFR dimerization. These studies have important implications for understanding extracellular activating mutations found in EGFR/ErbB family receptors in glioblastoma and other cancers and also for understanding specificity of ligand-induced ErbB receptor heterodimerization

Predimerizing the EGFR ECR Has Modest Effects on EGF Binding

To access preformed dimers of the hEGFR ECR (sEGFR) experimentally, we C-terminally fused (to residue 621 of the mature protein) either a dimerizing Fc domain (creating sEGFR-Fc) or the dimeric leucine zipper from S. cerevisiae GCN4 (creating sEGFR-Zip). Size exclusion chromatography (SEC) and/or sedimentation equilibrium analytical ultracentrifugation (AUC) confirmed that the resulting purified sEGFR fusion proteins are dimeric (Figure S1). To measure KD values for ligand binding to sEGFR-Fc and sEGFR-Zip, we labeled EGF with Alexa-488 and monitored binding in fluorescence anisotropy (FA) assays. As shown in Figure 2A, EGF binds approximately 10-fold more tightly to the dimeric sEGFR-Fc or sEGFR-Zip proteins than to monomeric sEGFR (Table 1). The curves obtained for EGF binding to sEGFR-Fc and sEGFR-Zip showed no signs of negative cooperativity, with sEGFR-Zip actually requiring a Hill coefficient (nH) greater than 1 for a good fit (nH = 1 for both sEGFRWT and sEGFR-Fc). Thus, our initial studies argued that simply dimerizing human sEGFR fails to restore the negatively cooperative ligand binding seen for the intact receptor in cells.

One surprise from these data was that forced sEGFR dimerization has only a modest (≤10-fold) effect on EGF-binding affinity. Under the conditions of the FA experiments, isolated sEGFR (without zipper or Fc fusion) remains monomeric; the FA assay contains just 60 nM EGF, so the maximum concentration of EGF-bound sEGFR is also limited to 60 nM, which is over 20-fold lower than the KD for dimerization of the EGF/sEGFR complex (Dawson et al., 2005, Lemmon et al., 1997). This ≤10-fold difference in affinity for dimeric and monomeric sEGFR seems small in light of the strict dependence of sEGFR dimerization on ligand binding (Dawson et al., 2005,Lax et al., 1991, Lemmon et al., 1997). Unliganded sEGFR does not dimerize detectably even at millimolar concentrations, whereas liganded sEGFR dimerizes with KD ∼1 μM, suggesting that ligand enhances dimerization by at least 104– to 106-fold. Straightforward linkage of dimerization and binding equilibria should stabilize EGF binding to dimeric sEGFR similarly (by 5.5–8.0 kcal/mol). The modest difference in EGF-binding affinity for dimeric and monomeric sEGFR is also significantly smaller than the 40- to 100-fold difference typically reported between high-affinity and low-affinity EGF binding on the cell surface when data are fit to two affinity classes of binding site (Burgess et al., 2003, Magun et al., 1980).

Mutations that Prevent sEGFR Dimerization Do Not Significantly Reduce Ligand-Binding Affinity

The fact that predimerizing sEGFR only modestly increased ligand-binding affinity led us to question the extent to which domain II-mediated sEGFR dimerization is linked to ligand binding. It is typically assumed that the domain II conformation stabilized upon forming the sEGFR dimer in Figure 1C optimizes the domain I and III positions for EGF binding. To test this hypothesis, we introduced a well-characterized pair of domain II mutations into sEGFRs that block dimerization: one at the tip of the dimerization arm (Y251A) and one at its “docking site” on the adjacent molecule in a dimer (R285S). The resulting (Y251A/R285S) mutation abolishes sEGFR dimerization and EGFR signaling (Dawson et al., 2005, Ogiso et al., 2002). Importantly, we chose isothermal titration calorimetry (ITC) for these studies, where all interacting components are free in solution. Previous surface plasmon resonance (SPR) studies have indicated that dimerization-defective sEGFR variants bind immobilized EGF with reduced affinity (Dawson et al., 2005), and we were concerned that this reflects avidity artifacts, where dimeric sEGFR binds more avidly than monomeric sEGFR to sensor chip-immobilized EGF.

Surprisingly, our ITC studies showed that the Y251A/R285S mutation has no significant effect on ligand-binding affinity for sEGFR in solution (Table 1). These experiments employed sEGFR (with no Fc fusion) at 10 μM—ten times higher than KD for dimerization of ligand-saturated WT sEGFR (sEGFRWT) (KD ∼1 μM). Dimerization of sEGFRWT should therefore be complete under these conditions, whereas the Y251A/R285S-mutated variant (sEGFRY251A/R285S) does not dimerize at all (Dawson et al., 2005). The KD value for EGF binding to dimeric sEGFRWT was essentially the same (within 2-fold) as that for sEGFRY251A/R285S (Figures 2B and 2C; Table 1), arguing that the favorable Gibbs free energy (ΔG) of liganded sEGFR dimerization (−5.5 to −8 kcal/mol) does not contribute significantly (<0.4 kcal/mol) to enhanced ligand binding. …

Thermodynamics of EGF Binding to sEGFR-Fc

If there is no discernible positive linkage between sEGFR dimerization and EGF binding, why do sEGFR-Fc and sEGFR-Zip bind EGF ∼10-fold more strongly than wild-type sEGFR? To investigate this, we used ITC to compare EGF binding to sEGFR-Fc and sEGFR-Zip (Figures 3A and 3B ) with binding to isolated (nonfusion) sEGFRWT. As shown in Table 1, the positive (unfavorable) ΔH for EGF binding is further elevated in predimerized sEGFR compared with sEGFRWT, suggesting that enforced dimerization may actually impair ligand/receptor interactions such as hydrogen bonds and salt bridges. The increased ΔH is more than compensated for, however, by a favorable increase in TΔS. This favorable entropic effect may reflect an “ordering” imposed on unliganded sEGFR when it is predimerized, such that it exhibits fewer degrees of freedom compared with monomeric sEGFR. In particular, since EGF binding does induce sEGFR dimerization, it is clear that predimerization will reduce the entropic cost of bringing two sEGFR molecules into a dimer upon ligand binding, possibly underlying this effect.

Possible Heterogeneity of Binding Sites in sEGFR-Fc

Close inspection of EGF/sEGFR-Fc titrations such as that in Figure 3A suggested some heterogeneity of sites, as evidenced by the slope in the early part of the experiment. To investigate this possibility further, we repeated titrations over a range of temperatures. We reasoned that if there are two different types of EGF-binding sites in an sEGFR-Fc dimer, they might have different values for heat capacity change (ΔCp), with differences that might become more evident at higher (or lower) temperatures. Indeed, ΔCp values correlate with the nonpolar surface area buried upon binding (Livingstone et al., 1991), and we know that this differs for the two Spitz-binding sites in the asymmetric Drosophila EGFR dimer (Alvarado et al., 2010). As shown in Figure 3C, the heterogeneity was indeed clearer at higher temperatures for sEGFR-Fc—especially at 25°C and 30°C—suggesting the possible presence of distinct classes of binding sites in the sEGFR-Fc dimer. We were not able to fit the two KD values (or ΔH values) uniquely with any precision because the experiment has insufficient information for unique fitting to a model with four variables. Whereas binding to sEGFRWT could be fit confidently with a single-site binding model throughout the temperature range, enforced sEGFR dimerization (by Fc fusion) creates apparent heterogeneity in binding sites, which may reflect negative cooperativity of the sort seen with dEGFR. …

Ligand Binding Is Required for Well-Defined Dimerization of the EGFR ECR

To investigate the structural nature of the preformed sEGFR-Fc dimer, we used negative stain electron microscopy (EM). We hypothesized that enforced dimerization might cause the unliganded ECR to form the same type of loose domain II-mediated dimer seen in crystals of unliganded Drosophila sEGFR (Alvarado et al., 2009). When bound to ligand (Figure 4A), the Fc-fused ECR clearly formed the characteristic heart-shape dimer seen by crystallography and EM (Lu et al., 2010, Mi et al., 2011). Figure 4B presents a structural model of an Fc-fused liganded sEGFR dimer, and Figure 4C shows a calculated 12 Å resolution projection of this model. The class averages for sEGFR-Fc plus EGF (Figure 4A) closely resemble this model, yielding clear densities for all four receptor domains, arranged as expected for the EGF-induced domain II-mediated back-to-back extracellular dimer shown in Figure 1 (Garrett et al., 2002, Lu et al., 2010). In a subset of classes, the Fc domain also appeared well resolved, indicating that these particular arrangements of the Fc domain relative to the ECR represent highly populated states, with the Fc domains occupying similar positions to those of the kinase domain in detergent-solubilized intact receptors (Mi et al., 2011). …

Our results and those of Lu et al. (2012)) argue that preformed extracellular dimers of hEGFR do not contain a well-defined domain II-mediated interface. Rather, the ECRs in these dimers likely sample a broad range of positions (and possibly conformations). This conclusion argues against recent suggestions that stable unliganded extracellular dimers “disfavor activation in preformed dimers by assuming conformations inconsistent with” productive dimerization of the rest of the receptor (Arkhipov et al., 2013). The ligand-free inactive dimeric ECR species modeled by Arkhipov et al. (2013) in their computational studies of the intact receptor do not appear to be stable. The isolated ECR from EGFR has a very low propensity for self-association without ligand, with KD in the millimolar range (or higher). Moreover, sEGFR does not form a defined structure even when forced to dimerize by Fc fusion. It is therefore difficult to envision how it might assume any particular autoinhibitory dimeric conformation in preformed dimers. …

Extracellular Oncogenic Mutations Observed in Glioblastoma May Alter Linkage between Ligand Binding and sEGFR Dimerization

Missense mutations in the hEGFR ECR were discovered in several human glioblastoma multiforme samples or cell lines and occur in 10%–15% of glioblastoma cases (Brennan et al., 2013, Lee et al., 2006). Several elevate basal receptor phosphorylation and cause EGFR to transform NIH 3T3 cells in the absence of EGF (Lee et al., 2006). Thus, these are constitutively activating oncogenic mutations, although the mutated receptors can be activated further by ligand (Lee et al., 2006, Vivanco et al., 2012). Two of the most commonly mutated sites in glioblastoma, R84 and A265 (R108 and A289 in pro-EGFR), are in domains I and II of the ECR, respectively, and contribute directly in inactive sEGFR to intramolecular interactions between these domains that are thought to be autoinhibitory (Figure 5). Domains I and II become separated from one another in this region upon ligand binding to EGFR (Alvarado et al., 2009), as illustrated in the lower part of Figure 5. Interestingly, analogous mutations in the EGFR relative ErbB3 were also found in colon and gastric cancers (Jaiswal et al., 2013).

We hypothesized that domain I/II interface mutations might activate EGFR by disrupting autoinhibitory interactions between these two domains, possibly promoting a domain II conformation that drives dimerization even in the absence of ligand. In contrast, however, sedimentation equilibrium AUC showed that sEGFR variants harboring R84K, A265D, or A265V mutations all remained completely monomeric in the absence of ligand (Figure 6A) at a concentration of 10 μM, which is similar to that experienced at the cell surface (Lemmon et al., 1997). As with WT sEGFR, however, addition of ligand promoted dimerization of each mutated sEGFR variant, with KD values that were indistinguishable from those of WT. Thus, extracellular EGFR mutations seen in glioblastoma do not simply promote ligand-independent ECR dimerization, consistent with our finding that even dimerized sEGFR-Fc requires ligand binding in order to form the characteristic heart-shaped dimer. …

We suggest that domain I is normally restrained by domain I/II interactions so that its orientation with respect to the ligand is compromised. When the domain I/II interface is weakened with mutations, this effect is mitigated. If this results simply in increased ligand-binding affinity of the monomeric receptor, the biological consequence might be to sensitize cells to lower concentrations of EGF or TGF-α (or other agonists). However, cellular studies of EGFR with glioblastoma-derived mutations (Lee et al., 2006, Vivanco et al., 2012) clearly show ligand-independent activation, arguing that this is not the key mechanism. The domain I/II interface mutations may also reduce restraints on domain II so as to permit dimerization of a small proportion of intact receptor, driven by the documented interactions that promote self-association of the transmembrane, juxtamembrane, and intracellular regions of EGFR (Endres et al., 2013, Lemmon et al., 2014, Red Brewer et al., 2009).

Setting out to test the hypothesis that simply dimerizing the EGFR ECR is sufficient to recover the negative cooperativity lost when it is removed from the intact receptor, we were led to revisit several central assumptions about this receptor. Our findings suggest three main conclusions. First, we find that enforcing dimerization of the hEGFR ECR does not drive formation of a well-defined domain II-mediated dimer that resembles ligand-bound ECRs or the unliganded ECR from Drosophila EGFR. Our EM and SAXS data show that ligand binding is necessary for formation of well-defined heart-shaped domain II-mediated dimers. This result argues that the unliganded extracellular dimers modeled by Arkhipov et al. (2013)) are not stable and that it is improbable that stable conformations of preformed extracellular dimers disfavor receptor activation by assuming conformations that counter activating dimerization of the rest of the receptor. Recent work from the Springer laboratory employing kinase inhibitors to drive dimerization of hEGFR (Lu et al., 2012) also showed that EGF binding is required to form heart-shaped ECR dimers. These findings leave open the question of the nature of the ECR in preformed EGFR dimers but certainly argue that it is unlikely to resemble the crystallographic dimer seen for unligandedDrosophila EGFR (Alvarado et al., 2009) or that suggested by computational studies (Arkhipov et al., 2013).

This result argues that ligand binding is required to permit dimerization but that domain II-mediated dimerization may compromise, rather than enhance, ligand binding. Assuming flexibility in domain II, we suggest that this domain serves to link dimerization and ligand binding allosterically. Optimal ligand binding may stabilize one conformation of domain II in the scheme shown in Figure 1 that is then distorted upon dimerization of the ECR, in turn reducing the strength of interactions with the ligand. Such a mechanism would give the appearance of a lack of positive linkage between ligand binding and ECR dimerization, and a good test of this model would be to determine the high-resolution structure of a liganded sEGFR monomer (which we expect to differ from a half dimer). This model also suggests a mechanism for selective heterodimerization over homodimerization of certain ErbB receptors. If a ligand-bound EGFR monomer has a domain II conformation that heterodimerizes with ErbB2 in preference to forming EGFR homodimers, this could explain several important observations. It could explain reports that ErbB2 is a preferred heterodimerization partner of EGFR (Graus-Porta et al., 1997) and might also explain why EGF binds more tightly to EGFR in cells where it can form heterodimers with ErbB2 than in cells lacking ErbB2, where only EGFR homodimers can form (Li et al., 2012).

7.3.7 IGFBP-2/PTEN: A critical interaction for tumours and for general physiology?

IGFBP-2
The insulin-like growth factor family of proteins, together with insulin, form an evolutionarily conserved system that helps to coordinate the metabolic status and activity of organisms with their nutritional environment. When food is abundant, the IGF/insulin signalling pathway is switched on and cell proliferation and other activities are enhanced; while when food is limited, such activities are suppressed to conserve energy and resources [1,2]. The IGF axis consists of two ligands IGF-I and -II, a series of heterotetrameric tyrosine kinase receptors and six high affinity binding proteins IGFBP-1 to-6. These IGFBPs not only regulate the reservoir, availability and functions of IGFs but also have direct actions upon cell behaviour that are independent of IGF-binding [3]. The six IGFBPs are conserved in all placental mammals having evolved from serial duplication of genes that were present throughout vertebrate evolution [4]. Each of the six IGFBPs has evolved unique functions that presumably have conferred some evolutionary advantage and hence have been conserved across mammalian evolution. After IGFBP-3, IGFBP-2 is the second most abundant binding protein in the circulation throughout adult life in humans. While circulating IGFBP-3 levels peak during puberty and decrease thereafter, IGFBP-2 levels are highest in infancy and old age. Together with the other five IGFBPs, IGFBP-2 regulates IGF availability and actions and has pleiotropic effects on normal and neoplastic tissues [3]. One of the clear distinctive structural features of IGFBP-2 is that it contains an Arg-Gly-Asp (RGD) sequence that enables functional interactions with integrin receptors [4]. This structural element is only present in one of the other IGFBPs, IGFBP-1. Although the RGD sequence was only acquired in IGFBP-1 during mammalian evolution it was present within IGFBP-2 from early vertebrate evolution indicating that it has been a long retained functional characteristic of IGFBP-2 [4]. The integrin receptors are critical for the anchorage of cells to the extracellular matrix (ECM) within tissues and hence for maintaining tissue architecture [5,6]. In solid tissue an important safeguard is imposed by linking normal cell functions and proliferation to appropriate cues from the ECM that are mediated by signals from attachment receptors such as the integrin receptors. Anchoragedependent growth is a common feature of normal cells and loss of attachment results in a form of apoptosis called anoikis. The integrin receptors interact with growth factor receptors in an ancillary and permissive manner to ensure that the signals for growth and survival occur in the appropriate setting and not inappropriately in detached cells. It has also become clear that integrin receptors serve many other roles in regulating cell functions and integrating cues from the surrounding ECM [5,6]. Over the last few decades, as the role of IGFBPs as extracellular modulators of IGF-availability and actions has emerged, there has also been a gradual characterization of the intracellular counter-regulatory components that modulate the signals initiated by IGF-receptor activation. There has been considerable progress in charting the signalling cascades initiated from these receptors but it is evident that the reason needs to be mechanisms for inactivating the pathways in intervening periods in preparation for subsequent activation. Throughout the canonical kinase cascades, activated by receptor ligation, at each node there is a corresponding phosphatase that returns the pathway to the inactive state and modulates the signal. The extracellular regulators of these phosphatases have however received much less attention than the activating kinases. That the extracellular counter-regulators may act in synchrony and be linked to the intracellular counter-regulators has only recently started to be revealed. Transgenic over-expression of IGFBP-2 at supra-physiological levels in mice results in reduced somatic growth [7] and this growth deficit is more pronounced when these mice were crossed with mice with raised growth hormone/IGF-I [8] implying that the growth inhibitory effect was due to sequestration of IGF-I. As with most of the IGFBP-family [3], there are also however multiple lines of evidence that IGFBP-2 has cellular actions that are independent of its ability to bind IGFs. There is evidence that IGFBP-2 initiates intrinsic cellular signalling through specific binding of its RGD-motif to integrin receptors, particularly the α5β1 integrin.In addition IGFBP-2 appears to modulate IGF and epidermal growth factor signalling through interactions with α5β3 integrins [9]. A heparin binding domain also exists in IGFBP-2 and it has been shown to bind to glycosaminoglycans [10], heparin [11], and other proteoglycans such as the receptor protein tyrosine phosphatase-β (RPTPβ) [12,13]. In addition,IGFBP-2has been reported to be localized on the cell surface, in the cytoplasm and on the nuclear membrane[14]. Several groups have now reported nuclear localization of IGFBP-2 [15–17]. A functional nuclear localization sequence in the central domain of IGFBP-2 has been reported that appears to interact with importin-α [18]. In the nucleus IGFBP-2 has been reported to regulate the expression of vascular endothelial growth factor [19].
IGFBP-2 and metabolic regulation
Epidemiological studies of human populations have indicated that IGFBP-2 levels are reduced in obesity, metabolic syndrome and type 2 diabetes and are inversely correlated with insulin sensitivity [20]. That these associations were due to a metabolic role for IGFBP-2, rather thanitjustbeingamarkerofdisturbance,hasbeenconfirmedinanumber of animal models. Using a transgenic IGFBP-2 over-expressing mouse model, Wheatcroft and coworkers found that IGFBP-2 was able to protect mice from high-fat/high-energy induced obesity and insulin resistance, and also protected the mice from the age-related development of glucose intolerance and hypertension [21]. Over-expression of IGFBP-2 induced by Leptin in wild type or obese mice similarly resulted in reduced plasma glucose and insulin levels [22]. All these data indicate a metabolic role for IGFBP-2 in glucose homeostasis.
IGFBP-2 and cancer
As indicated above, the early reports had implied that IGFBP-2 was generally a negative regulator of IGF-activity; the systemic growth restriction observed in transgenic mice over-expressing IGFBP-2 was followed by observations that chemically induced colorectal cancers were inhibited in this model [23]. Despite this there has been an accumulation of evidence indicating that IGFBP-2 is positively associated with the malignant progression of a wide range of cancers, as has been reviewed previously [24]. Raised serum levels of IGFBP-2 have been reported and positive associations between tumor IGFBP-2 expression and malignancy or metastasis have been observed for a variety of cancers, including glioma [25], breast [26], prostate [27], lung [28], colon [29] and lymphoid tumor [30]. Subsequent work has generally been consistent with this association between IGFBP-2 and cancer progression. In view of the majority of evidence, indicating that IGFBP-2 interacting with IGFs generally inhibited cell growth, it was suggested thatIGF-independentactionswereprobablyresponsibleforpositiveassociations between IGFBP-2 and tumourgrowth and progression [24]. The explanation for the increased expression of IGFBP-2 that has beenreportedformanydifferentcancersappearstocomefromthefactorsthat have been shown to regulate IGFBP-2 expression.The tumor suppressor gene p53, which is the most mutated gene in many human cancers, has been reported to transcriptionally regulate IGFBP-2 [31].

There also appears to again be reciprocal feedback as p53 mRNA in the breast cancer cell line Hs578T increased significantly after treatment with human recombinant IGFBP-2, suggesting a close interaction between IGFBP-2 and p53 [14]. A number of hormonal regulators of IGFBP-2 expression have been described including hCG, FSH, TGF-β, IL1, estradiol, glucocorticoids, EGF, IGF-I, IGF-II and insulin [24]. The stimulation of IGFBP-2 expression by EGF, IGF-I, IGF-II and insulin has been shown to be via the PI3K/AKT/mTOR pathway in breast cancer cells [32] and in adipocytes [33]. This is one of the most well characterisedsignallingpathwaysactivatedbyinsulinandIGFs.Inaddition the critical counter-regulatory phosphatase that deactivates this pathway the phosphatase and tensin homologue PTEN has been shown to downregulate the expression of IGFBP-2 [34]. This suggests another autoregulatory loop in which activation of the PI3K/AKT/mTOR pathway by IGFs induces the expression of IGFBP-2 that then sequesters the IGFs and modulates the signal. As activating mutations in the PI3K pathway or loss of PTEN are very common across a variety of human cancers, this plus the effect of p53, probably accounts for the common dysregulation of IGFBP-2 observed across many cancers. Using prostate cancer cell lines it has also been shown that local IGFBP-2 expression is metabolically regulated; IGFBP-2 expression was increased in hyperglycemic conditions through acetylation of histones H3 and H4 associated with the IGFBP-2 promoter, furthermore this up-regulation of IGFBP-2 mediated hyperglycemia-induced chemo-resistance [35].

PI3K
The signaling kinase PI3K plays a fundamental role that has been maintained throughout most of evolution. The ability to control growth and development according to the availability of nutrients provides a survival advantage and therefore has been selectively retained throughout evolution. Evidence has accumulated to indicate that the PI3K pathway provides this control in all species from yeast to mammals.Various forms of the PI3K enzyme exist that are classified into three groups (classes I, II, and III). Only one of these forms is present in yeast and is equivalent to mammalian class III PI3K: this acts as a nutrient sensor and is directly activated by the availability of amino acids and then itself activates mTOR/S6K1 to regulate cell growth and development [36]. In mammals class 1API3K has evolved: this form is not directly activated by nutrients but consists of heterodimers comprising a catalytic p110 subunit and a regulatory p85 subunit that enables the enzyme to be controlled by receptor tyrosine kinases, classically the insulin and insulin-like growth factor receptors (IR and IGF-IR) [37]. This enables the regulation of PI3K by social nutritionally dependent signals rather than by nutrients directly. It is not by chance that the insulin/IGF/PI3K pathway plays a fundamental role in regulating both metabolism and growth as it clearly is an advantage to synchronize the set processes and this synchronized control has been maintained throughout evolution.

Phosphatase and tensin homolog (PTEN)
Of all the intracellular counter-regulators of the IGF-pathway the one that has received the most attention in relation to cancer is PTEN. PTEN is a lipid tyrosine phosphatase that negatively regulates the Akt/ PKB signaling pathway by specifically dephosphorylating phosphatidylinositol (3,4,5)-trisphosphate and thereby reduces AKT activation to reduce signals for cell metabolism, proliferation and survival [37]. PTEN is the second most often mutated tumor suppressor in human cancers, after p53[38]. Aberrant PTEN activity occurs due to mutation, homozygous deletion, loss of heterozygosity, or epigenetic silencing. Lost or reduced activity of PTEN has been observed in a great variety of cancers, including breast [39], prostate [40,41], colorectal [42], lung[43], glioblastoma [44], endometrial [45], etc. It has been demonstrated that deregulation of PTEN is involved in tumorigenesis, tumor progression and also the predisposition of many cancers [46]. AsPI3K/Akt signaling is critical for the metabolic effects of insulin. It is clear that PTEN will also play a role in modulating the metabolic actions of insulin. Consistent with this mice genetically modified to have haploinsufficiency of PTEN were observed to be hypersensitive to insulin [47]. Similarly humans with haplo-insufficiency due to mutations in PTEN were found to have enhanced insulin sensitivity [48]. Recently an increase in insulin sensitivity due to suppression of PTEN has been described in grizzly bears in preparation for hibernation, indicating that this is a mechanism for physiological adaptation [49]. Although the genetic defects resulting in PTEN loss in cancers and the intrinsic mechanisms for regulation of PTEN have been well characterised; there have been relatively few reports of external cell regulators. Of interest one of the few extrinsic regulators that has been described is IGF-II [50]. IGF-II is the most abundant growth factor present in most human tissues and activates the PI3K/AKT/mTOR pathway. Just as the induction of IGFBP-2 by activation of the PI3K pathway suggests an autoregulatory feedback loop extrinsic to the cell;the induction of PTEN by IGF-II via PI3K suggests an additional feedback loop that is intrinsic within the cell (Fig. 1). Activation of the pathway by IGF-II induces expression of PTEN that then attenuates the signal; conversely when the pathway is not activated then PTEN expression is reduced making the cell more responsive for when an activation signal is next received.One of the mechanisms that has emerged,to explain this feedback loop, indicates that the signaling output of the PI3K/PTEN pathway is balanced by asynchronous regulation of the activity of both PI3K and PTEN. The p85α regulatory subunit of PI3K that binds to and represses the activity of the p110 catalytic subunit also binds directly to PTEN at a regulatory site within PTEN where serine/threonine phosphorylation occurs to inactivatePTEN.The p85α subunit binds to unphosphorylated PTEN at this site and enhances its lipid phosphatase activity 3-fold [51]. The nature of this feedback loop has been further extended by reports that PTEN can suppress the expression of IGF-II [52,53]. As IGF-II induces PTEN, the ability of PTEN to subsequently reduce IGF-II expression may enable the cell to protect itself from over-stimulation. In contrast loss of PTEN may increase the expression of IGF-II resulting inactivation of the PI3K/AKT/mTOR pathway that is then unopposed.

PTEN/IGFBP-2 interactions
In view of the recognized importance of loss of PTEN for a variety of cancers there has been considerable interest in identifying biomarkers that could be used clinically to indicate loss of PTEN within tumors. An unbiased screen of human prostate cancer xenografts and human glioblastoma samples using microarray-based expression profiling found that the most significant gene was IGFBP-2 and it was confirmed in experimental models that IGFBP-2 was inversely regulated by PTEN [54]. This was consistent with all of the subsequent studies indicating that the expression of IGFBP-2 was regulated by the PI3K/AKT/mTOR pathway. An increase in tumor IGFBP-2 has also been associated with loss of PTEN in human breast cancer samples[55]. In the same year that a screen revealed IGFBP-2 as the best marker for loss of PTEN; the nature of the interaction between these two proteins was extended by the demonstration that at the cellular level IGFBP-2 can inversely regulate PTEN. With human breast cancer cells it was confirmed that IGF-II stimulated PTEN expression and that this was modulated by the binding of IGF-II to IGFBP-2, but when IGFBP-2 was not bound to IGF-II it was able to suppress PTEN via an interaction with cell surface integrin receptors (Fig. 1) [56]. Subsequent work with human prostate cancer cells indicated that the interaction of IGFBP-2 with integrin receptors could also result in PTEN inactivation via increasing its phosphorylation [57].

Fig.1. A proposed autoregulatory feedback loop of IGFBP-2/PTEN interaction. Binding of IGF-II to the IGF-IR activates the PI3K pathway. Induction of PI3K activates Akt and mTOR signaling and leads to cell proliferation and cell survival. The regulatory subunit of PI3K,p85, also binds and activates PTEN through dephosphorylation. This increased PTEN subsequently blocks IGFII production to avoid overstimulation. On the other hand, activated PI3K pathway induces IGFBP-2 expression, which when unbound to IGF-II, suppresses PTEN via an interaction with integrin receptors and/or the receptor protein tyrosine phosphatase β(RPTPβ). Thus the negative control of PTEN on PI3K signaling is counteracted. These feedback loops enable the extrinsic balance between IGF-II and IGFBP-2 to be tightly integrated to the intrinsic balance between PI3K and PTEN.

The ability of IGFBP-2 to regulate PTEN, originally observed in human cancer cell lines has subsequently been confirmed in a variety of normal cell types from different tissues. In IGFBP-2 knock-out mice a decrease in hematopoietic stem cell survival and cycling has been associated with an increase in PTEN and this appeared to be mediated by the heparin binding domain (HBD) within IGFBP-2 as the administration of a peptide analogue could restore the deficit [58]. Similarly a decrease in bone mass in the IGFBP-2 knock-out mice has been attributed to an increase in PTEN and again the use of a peptide analogue appeared to implicate the IGFBP-2HBD [59]. It was subsequently reported that the IGFBP-2HBD mediated an interaction with the RPTPβ resulting in dimerization and consequent inactivation of RPTPβ and that this reduction in phosphatase activity cooperated with IGF-I activation of the IGF-IR to enhance the phosphorylation and inactivation of PTEN [12]. Recently IGFBP-2 has been reported to also suppress PTEN in human skeletal muscle cells [60] and human visceral adipocytes [61] by interacting with integrin receptors. A similar association between IGFBP-2 and PTEN has been implicated as playing a role in murine skeletal muscle cell differentiation, although the functional regulation was not directly investigated in that study [62].

Summary
Evidence from a variety of different sources have indicated a close regulatory feedback loop between IGFBP-2 and PTEN. Work using a variety of different cell types from different tissues and different species has indicated that IGFBP-2 inversely regulates PTEN. There are reports that this is mediated via the IGFBP-2 RGD domain interacting with integrin receptors and by the IGFBP-2 HBD interacting with proteoglycans; the relative involvement of each of these domains and their functional interactions will require further work to elucidate. These studies however suggest a general mechanism that plays a role in a variety of normal physiological processes in addition to having important implications for the progression of many different cancers. The phosphatase PTEN has an important role in determining insulin sensitivity and the extent that IGFBP-2 exerts a metabolic role in regulating PTEN to determine insulin-sensitivity is yet to be examined. The extracellular balance between IGF-II and IGFBP-2 seems tightly linked with the intracellular balance between PI3K and PTEN (Fig. 1). When driving, in order to move forward there is a synchronous application of the accelerator and a removal of the brake. It appears that the cell also synchronizes activation of an essential regulatory pathway with the removal of the tightly linked inactivation pathway.

References
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7.3.8 Emerging roles for the pH-sensing G protein-coupled receptors in response to acidotic stress

Edward J Sanderlin, Calvin R Justus, Elizabeth A Krewson, Li V Yang
Cell Health & Cytoskel Mar 2015; 2015(7): 99—109
http://www.dovepress.com/emerging-roles-for-the-ph-sensing-g-protein-coupled-receptors-in-respo-peer-reviewed-article-CHC#

Protons (hydrogen ions) are the simplest form of ions universally produced by cellular metabolism including aerobic respiration and glycolysis. Export of protons out of cells by a number of acid transporters is essential to maintain a stable intracellular pH that is critical for normal cell function. Acid products in the tissue interstitium are removed by blood perfusion and excreted from the body through the respiratory and renal systems. However, the pH homeostasis in tissues is frequently disrupted in many pathophysiologic conditions such as in ischemic tissues and tumors where protons are overproduced and blood perfusion is compromised. Consequently, accumulation of protons causes acidosis in the affected tissue. Although acidosis has profound effects on cell function and disease progression, little is known about the molecular mechanisms by which cells sense and respond to acidotic stress. Recently a family of pH-sensing G protein-coupled receptors (GPCRs), including GPR4, GPR65 (TDAG8), and GPR68 (OGR1), has been identified and characterized. These GPCRs can be activated by extracellular acidic pH through the protonation of histidine residues of the receptors. Upon activation by acidosis the pH-sensing GPCRs can transduce several downstream G protein pathways such as the Gs, Gq/11, and G12/13 pathways to regulate cell behavior. Studies have revealed the biological roles of the pH-sensing GPCRs in the immune, cardiovascular, respiratory, renal, skeletal, endocrine, and nervous systems, as well as the involvement of these receptors in a variety of pathological conditions such as cancer, inflammation, pain, and cardiovascular disease. As GPCRs are important drug targets, small molecule modulators of the pH-sensing GPCRs are being developed and evaluated for potential therapeutic applications in disease treatment.

Cellular metabolism produces acid as a byproduct. Metabolism of each glucose molecule by glycolysis generates two pyruvate molecules. Under anaerobic conditions the metabolism of pyruvate results in the production of the glycolytic end product lactic acid, which has a pKa of 3.9. Lactic acid is deprotonated at the carboxyl group and results in one lactate ion and one proton at the physiological pH. Under aerobic conditions pyruvate is converted into acetyl-CoA and CO2 in the mitochondria. CO2in water forms a chemical equilibrium of carbonic acid and bicarbonate, an important physiological pH buffering system. The body must maintain suitable pH for proper physiological functions. Some regulatory mechanisms to control systemic pH are respiration, renal excretion, bone buffering, and metabolism.14 The respiratory system can buffer the blood by excreting carbonic acid as CO2 while the kidney responds to decreased circulatory pH by excreting protons and electrolytes to stabilize the physiological pH. Bone buffering helps maintain systemic pH by Ca2+ reabsorption and mineral dissolution. Collectively, it is clear that several biological systems require tight regulation to maintain pH for normal physiological functions. Cells utilize vast varieties of acid-base transporters for proper pH homeostasis within each biological context.58 Some such transporters are H+-ATPase, Na+/H+exchanger, Na+-dependent HCO3/C1 exchanger, Na+-independent anion exchanger, and monocarboxylate transporters. Cells can also maintain short-term pH homeostasis of the intracellular pH by rapid H+ consuming mechanisms. Some such mechanisms utilize metabolic conversions that move acids from the cytosol into organelles. Despite these cellular mechanisms that tightly maintain proper pH homeostasis, there are many diseases whereby pH homeostasis is disrupted. These pathological conditions are characterized by either local or systemic acidosis. Systemic acidosis can occur from respiratory, renal, and metabolic diseases and septic shock.14,9 Additionally, local acidosis is characterized in ischemic tissues, tumors, and chronically inflamed conditions such as in asthma and arthritis caused by deregulated metabolism and hypoxia.1015

Acidosis is a stress for the cell. The ability of the cell to sense and modulate activity for adaptation to the stressful environment is critical. There are several mechanisms whereby cells sense acidosis and modulate cellular functions to facilitate adaptation. Cells can detect extracellular pH changes by acid sensing ion channels (ASICs) and transient receptor potential (TRP) channels.16 Apart from ASIC and TRP channels, extracellular acidic pH was shown to stimulate inositol polyphosphate formation and calcium efflux.17,18 This suggested the presence of an unknown cell surface receptor that may be activated by a certain functional group, namely the imidazole of a histidine residue. The identity of the acid-activated receptor was later unmasked by Ludwig et al as a family of proton-sensing G protein-coupled receptors (GPCRs). This group identified human ovarian cancer GPCR 1 (OGR1) which upon activation will produce inositol phosphate and calcium efflux through the Gq pathway.19 These pH-sensing GPCR family members, including GPR4, GPR65 (TDAG8), and GPR68 (OGR1), will be discussed in this review (Figure 1). The proton-sensing GPCRs sense extracellular pH by protonation of several histidine residues on their extracellular domain. The activation of these proton-sensing GPCRs facilitates the downstream signaling through the Gq/11, Gs, and G12/13 pathways. Their expression varies in different cell types and play critical roles in sensing extracellular acidity and modulating cellular functions in several biological systems.

Figure 1 Biological roles and G protein coupling of the pH-sensing GPCRs.
Abbreviation: GPCRs, G protein-coupled receptors.

Role for the pH-sensing GPCRs in the immune system and inflammation

Acidic pH is a main characteristic of the inflammatory loci.14,20,21 The acidic microenvironment in inflamed tissue is predominately due to the increased metabolic demand from infiltrating immune cells, such as the neutrophil. These immune cells increase oxygen consumption and glucose uptake for glycolysis and oxidative phosphorylation. When oxygen availability is limited, cells often undergo anaerobic glycolysis. This process generates increasing amounts of lactic acid, thereby creating a local acidic microenvironment within the inflammatory loci.22 This presents a role for the pH-sensing GPCR GPR65 (TDAG8) in inflammation and immune cell function.23 TDAG8 was originally identified by cloning as an orphan GPCR which was observed to be upregulated during thymocyte apoptosis.24,25GPR65 (TDAG8) is predominately expressed in lymphoid tissues such as the spleen, lymph nodes, thymus, and leukocytes.2426 It was demonstrated that GPR65 inhibited pro-inflammatory cytokine secretion, which includes IL-6 and TNF-α, in mouse peritoneal macrophages upon activation by extracellular acidification. This cytokine inhibition was shown to occur through the Gs-cAMP-protein kinase A (PKA) signaling pathway.23,27 Treatment with dexamethasone, a potent glucocorticoid, increased GPR65 expression in peritoneal macrophages. Following dexamethasone treatment, there was an inhibition of TNF-α secretion in a manner dependent on increased expression of GPR65.28Another report provides an anti-inflammatory role for GPR65 in arthritis.29 Type II collagen-induced arthritis was increased in GPR65-null mice in comparison to wild-type mice. These studies taken together suggest GPR65 serves as a negative regulator in inflammation.30 However, one study provided a function for GPR65 as a positive modulator in inflammation.31 GPR65 was reported to increase eosinophil viability in the acidic microenvironment by reducing apoptosis through the cAMP pathway. As eosinophils are central in asthmatic inflammation and allergic airway disease, GPR65 may play a role in increasing asthmatic inflammation.31 On the other hand, GPR65 has shown little involvement in immune cell development. One report indicates that GPR65 knockout mice had normal immune development and function.26 Modulation of inflammation by GPR65 is complex and must be examined within each specific pathology.23

In addition to GPR65, GPR4 is also involved in the inflammatory response. Endothelial cells compose blood vessels that often penetrate acidic tissue microenvironments such as the inflammatory loci. Among the pH-sensing GPCR family, GPR4 has the highest expression in endothelial cells. Response to inflammation by vascular endothelial cells facilitates the induction of inflammatory cytokines that are involved in the recruitment of leukocytes for adherence and transmigration into inflamed tissues. Activation of GPR4 by acidosis in human umbilical vein endothelial cells, among other endothelial cell types, increased the expression of a broad range of pro-inflammatory genes including chemokines, cytokines, PTGS2, NF-κB pathway genes, and adhesion molecules.32 Moreover, human umbilical vein endothelial cells, when treated with acidic pH, increased GPR4-mediated endothelial adhesion to leukocytes.32,33 Altogether, GPR65 and GPR4 provide differential regulation of the inflammatory response through their acid sensing capabilities. GPR65 predominately demonstrates function in the inhibition of the inflammatory response whereas GPR4 activation exacerbates inflammation.

Role for the pH-sensing GPCRs in the cardiovascular system

Taken together, both GPR4 and GPR68 play roles in regulating the function of the cardiovascular system. GPR4 regulates blood vessel stability and endothelial cell function and GPR68 increases cardiomyogenic and pro-survival gene expression while also mediating aortic smooth muscle cell gene expression.

Role for the pH-sensing GPCRs in the renal system

GPR4 is expressed in the kidney cortex, isolated kidney collecting ducts, inner and outer medulla, and in cultured inner and outer medullary collecting duct cells.59 In mice deficient for GPR4, renal acid excretion and the ability to respond to metabolic acidosis was reduced.59 In response to acidosis, inner and outer medullary collecting duct cells produced cAMP, a second messenger for the Gs G-protein pathway, through the GPR4 receptor.59 In renal HEK293 epithelial cells GPR4 overexpression was found to increase the activity of PKA.60 In addition, the protein expression of H+-K+-ATPase α-subunit (HKα2) was increased following GPR4 overexpression dependent on increased PKA activity.60

GPR68 has also been reported to alter proton export of HEK293 cells by stimulating the Na+/H+exchanger and H+-ATPase.58 The activation of GPR68 by acidosis was found to stimulate this effect through a cluster of extracellular histidine residues and the Gq/PKC signaling pathway.58 In GPR68-null mice the expression of the pH-sensitive kinase Pyk2 in the kidney proximal tubules was upregulated which might compensate for GPR68 deficiency.58 Taken together, GPR4 and GPR68 may both be necessary for successful systemic pH buffering by controlling renal acid excretion.

Role for the pH-sensing GPCRs in the respiratory system

Aoki et al demonstrated that GPR68-deficient mice were resistant to asthma along with inhibiting Th2 cytokine and immunoglobulin E production.68 This study concludes that GPR68 in dendritic cells is crucial for the onset of asthmatic responses.68 Moreover, GPR65 has been implicated as having a role in respiratory disorders as it is highly expressed in eosinophils, hallmark cells for asthmatic inflammation.69 Kottyan et al showed that GPR65 increased the viability of eosinophils within an acidic environment through the cAMP pathway in murine asthma models.31 In summary, GPR68 and GPR65 play important roles in the respiratory system and asthma. GPR68 regulates gene expression in airway epithelial, smooth muscle and immune cells while GPR65 enhances the survival of airway eosinophils in response to acidosis.

Role for the pH-sensing GPCRs in the skeletal system

GPR65 has also been reported as a pH sensor in bone. GPR65 is expressed in osteoclasts and its activity may inhibit Ca2+ resorption.81 Disruption of GPR65 gene exacerbated osteoclastic bone resorption in ovariectomized mice.81 The relative bone density of GPR65-null mice was less than control mice.81 In cultured osteoclast cells from mice deficient for GPR65, the normal inhibition of osteoclast formation in response to acidosis was abrogated.81 Taken together, this data suggest that the activation of GPR65 may enhance bone density, thus the GPR65 signaling may be important for disease processes such as osteoporosis and other bone density disorders.

Role for the pH-sensing GPCRs in the endocrine system

GPR68 has also been found to modify insulin production and secretion. In GPR68 knockout mice insulin secretion in response to glucose administration was reduced when compared to wild-type mice although blood glucose was not significantly altered.84 GPR68 deficiency in this respect may reduce insulin secretion but at the same time increase insulin sensitivity. In addition, stimulation of GPR68 in islet cells by acidosis increased the secretion of insulin through the Gq/11 G-protein signaling.84

Role for the pH-sensing GPCRs in the nervous system and nociception

Acidosis causes pain by exciting nociceptors located in sensory neurons. Several types of ion channels and receptors, such as ASICs, TRPV1, and proton-sensing GPCRs, have been identified as nociceptors in response to acidosis. ASICs and TRPV act as proton-gated membrane-bound channels, which are activated by acidic pH and mediate multimodal sensory perception including nociception.8688  GPR65 activation sensitized the response of TRPV1 to capsaicin. The results suggest high accumulation of protons post inflammation may not only stimulate nociceptive ion channels such as TRPV1 to trigger pain, but also activate proton-sensing GPCRs to regulate heightened sensitivity to pain.89 Furthermore, Hang et al demonstrated GPR65 activation elicited cancer-related bone pain through the PKA and phosphorylated CREB (pCREB) signaling pathway in the rat model.90 Collectively, GPR4, GPR65, and GPR68 are all expressed in the dorsal root ganglia; GPR65 is a functional receptor involved in nociception and the nervous system by sensitizing inflammatory pain and the evocation of cancer-related bone pain.

Role for the pH-sensing GPCRs in tumor biology

The tumor microenvironment is highly heterogeneous. Hypoxia, acidosis, inflammation, defective vasculature, poor blood perfusion, and deregulated cancer cell metabolism are hallmarks of the tumor microenvironment.9193 The acidity in the tumor microenvironment is owing to the altered cancer cell metabolism termed the “Warburg Effect”. This metabolic phenotype allows the cancer cells to preferentially utilize glycolysis over oxidative phosphorylation as a primary means of energy production.94 This process occurs even in normoxic tissue environments where sufficient oxygen is available. Due to this phenomenon, the Warburg Effect is often termed “aerobic glycolysis”. This unique metabolic phenotype produces vast quantities of lactic acid, which serve as a proton source for acidification. Upon disassociation of lactic acid to one lactate molecule and one proton, the monocarboxylate transporter and proton transporters export lactate and protons into the extracellular tumor microenvironment.95 The proton-sensing GPCRs are activated by acidic pH and facilitate tumor cell modulation in response to extracellular acidification. GPR4, GPR65, and GPR68 play roles in tumor cell apoptosis, proliferation, metastasis, angiogenesis, and immune cell function.19,27,32,33,44,45,96,97

GPR4 has had conflicting reports in terms of tumor suppressing or promoting activities. One study demonstrated that GPR4 could act as a tumor metastasis suppressor, when overexpressed and activated by acidic pH in B16F10 melanoma cells, by impeding migration and invasion of tumor cells.45 GPR4 overexpression also significantly inhibited the lung metastasis of B16F10 melanoma cells in mice.45 Another study utilizing the B16F10 melanoma cell line which overexpressed GPR4 showed an increase in mitochondrial surface area and a significant reduction in membrane protrusions by quantification of 3D morphology.98 These data point to a decrease in cancer cell migration when GPR4 is overexpressed and provides another example of GPR4 as exhibiting tumor metastasis suppressor function.98 However, in another report GPR4 malignantly transformed immortalized NIH3T3 fibroblasts.99 This presents GPR4 with tumor-promoting capabilities. The conflicting reports seem to indicate the functional ability of GPR4 to act as a tumor promoter and a tumor suppressor depending on the context of certain cell types and biological systems.

Reports with GPR65 involvement in cancer cells provide evidence in favor for cancer cell survival; however, opposing evidences suggest GPR65 functions as a tumor suppressor. In the same report suggesting GPR4 is oncogenic due to GPR4 transforming immortalized NIH3T3 fibroblasts, GPR65 overexpression was able to transform the mouse NMuMG mammary epithelial cell line.99 Another group demonstrated in NCI-H460 human non-small cell lung cancer cells that GPR65 promotes cancer cell survival in an acidic microenvironment.100 Conversely, a recent study showed that GPR65 inhibited c-Myc oncogene expression in human lymphoma cells.101 Furthermore, GPR65 messenger ribonucleic acid expression was reduced by more than 50% in a variety of human lymphoma samples when compared to normal lymphoid tissues, therefore implying GPR65 has a tumor suppressor function in lymphoma.101 GPR65 has also been shown to increase glucocorticoid-induced apoptosis in murine lymphoma cells.102 These reports highlight cell type dependency and biological context for GPR65 activity as a tumor suppressor or promoter.

GPR68 also has roles in tumor biology as a potential tumor suppressor or a tumor promoter. Reports have shown that GPR68 can inhibit cancer metastasis, reduce cancer cell proliferation, and inhibit migration. One study showed that when GPR68 was overexpressed in prostate cancer cells, metastasis to the lungs, diaphragm, and spleen was inhibited.97 When GPR68 was overexpressed in ovarian cancer (HEY) cells, cellular proliferation and migration were significantly reduced, and cell adhesion to the extracellular matrix was increased.96 Another study reported GPR68 expression was critical for the tumor cell induced immunosuppression in myeloid-derived cells. This study proposed that GPR68 promotes M2 macrophage development and inhibits T-cell infiltration, and thereby facilitates tumor development.103 In summary, the biological roles of GPR4, GPR65, and GPR68 in tumor biology are complex and both tumor-suppressing and tumor-promoting functions have been reported, primarily dependent on cell type and biological milieu.

Development of small molecule modulators of the pH-sensing GPCRs

GPCRs are critical receptors for the regulation of many physiological operations. It is of little surprise that GPCRs have become a central focus of pharmaceutical development. In fact, 30%–50% of therapeutics focuses on modulating GPCR activity.104,105 In view of the diverse roles of the pH-sensing GPCRs in the context of multiple biological systems, targeting these receptors with small molecules and other modulators could serve as potential therapeutics for diseases associated with deregulated pH homeostasis. There have been recent developments in the characterization of GPR4 antagonists along with agonists for GPR65 and GPR68.29,32,50,106 The GPR4 antagonist demonstrated effectiveness in vitro to reduce the GPR4-mediated inflammatory response to acidosis in endothelial cells.32 The GPR65 agonist, BTB09089, showed in vitro effects in GPR65 activation of immune cells to inhibit inflammatory response; however, the activity of BTB09089 was not strong enough for the use in animal models in vivo.29 The GPR68 agonist, lsx, exhibited pro-neurogenic activity and induced hippocampal neurogenesis in young mice.107 It was also demonstrated that lsx suppressed the proliferation of malignant astrocytes.108 To date, however, much advancement needs to be done in development of efficacious agonists and antagonists of the pH-sensing GPCRs coupled with a capacity to target specific tissue dysfunction in the midst of systemic drug administration to optimize therapeutic effects and minimize potential adverse effects.

Concluding remarks

Cells encounter acidotic stress in many pathophysiologic conditions such as inflammation, cancer, and ischemia. Intricate molecular mechanisms, including a large array of acid/base transporters and acid sensors, have evolved for cells to sense and respond to acidotic stress. Emerging evidence has demonstrated that a family of the pH-sensing GPCRs can be activated by extracellular acidotic stress and regulate the function of multiple physiological systems (Table 1). The pH-sensing GPCRs also play important roles in various pathological disorders. Agonists, antagonists and other modulators of the pH-sensing GPCRs are being actively developed and evaluated as potential novel treatment for acidosis-related diseases.

Table 1 The main biological functions of the pH-sensing GPCRs

7.3.9 Protein amino-terminal modifications and proteomic approaches for N-terminal profiling

Lai ZW1, Petrera A2, Schilling O3.
Curr Opin Chem Biol. 2015 Feb; 24:71-9
http://dx.doi.org:/10.1016/j.cbpa.2014.10.026

Amino-/N-terminal processing is a crucial post-translational modification affecting almost all proteins. In addition to altering the chemical properties of the N-terminus, these modifications affect protein activation, conversion, and degradation, which subsequently lead to diversified biological functions. The study of N-terminal modifications is of increasing interest; especially since modifications such as proteolytic truncation or pyroglutamate formation have been linked to disease processes. During the past decade, mass spectrometry has played an important role in facilitating the investigation of N-terminal modifications. Continuous progress is being made in the development and application of robust methods for the dedicated analysis of native and modified protein N-termini in a proteome-wide manner. Here we highlight recent progress in our understanding of protein N-terminal biology as well as outlining present enrichment strategies for mass spectrometry-based studies of protein N-termini.

Highlights

    • N-terminal acetylation, pyroglutamate formation, N-degrons and proteolysis are reviewed.• N-terminomics provide comprehensive profiling of modification at protein N-termini in a proteome-wide manner.• We outline a number of established methodologies for the enrichment of protein N-termini through positive and negative selection strategies.• Peptidomics-based approach is beneficial for the study of post-translational processing of protein N-termini.

 Introduction The life of every protein begins at the amino-terminus, also known as the N-terminus. During the initiation of mRNA translation into proteins or polypeptides, newly synthesized amino
acid chains form the N-termini and are the first to exit the ribosomes into the cytosol or the endoplasmic reticulum. The N-termini of these proteins or protein precursors often contain a signaling peptide
sequence proximal to the N-terminus, which may function as a ‘zip-code’ to direct the delivery of a protein to a cellular compartment as well as orchestrating protein maturation via different post-translational
modifications (PTMs) such as acetylation or proteolysis. These modifications often determine protein activity or stability; thus being crucial for the tight regulation of cellular homeostasis (Figure 1).
Mass spectrometry (MS) based analyses of protein N-termini, termed N-terminomics, is a promising tool to tackle these problems. In the past decade, we have witnessed significant progress in the
area of mass spectrometric investigation of post-translational modifications such as phosphorylation or glycosylation [1].  Similarly, MS-based studies of protein N-termini are gaining momentum.
Recent progress in positional proteomics using advanced MS platforms combined with a number of effective enrichment strategies has reinforced significant interest in N-terminomics.
Here we outline some of the most current highlights on proteomics-based studies on N-terminal modifications, including N-acetylation, pyroglutamate formation, proteolysis, and N-terminal degrons
(Figure 2). We also present a number of recent N-terminomic methodologies for the study of protein N-termini.

Acetylation of protein N-termini represents an abundant post-translational modification in eukaryotes, affecting nearly all cytoplasmic proteins. This  modification is catalyzed by the N-terminal
acetyltransferase (Nat) enzyme complex, which transfers an acetyl group to the N-termini of newly synthesized proteins during translation (Figure 2). Initial findings highlighted that N-terminal
acetylation protects proteins from degradation [2–4]. Recent studies however yield a more diverse picture. N-terminal acetylation may also play a role in protein delivery and localization [5–7],
protein complex formation and generation of specific degradation signals in cellular proteins via the N-degron pathway [9,10]. Loss of N-terminal acetylation through inactive acetyltransferases leads to
smaller aggregates of prion proteins [11]. In addition, N-terminal acetyltransferases have been described to also function as N-terminal proprionyltransferases [12].  Genetic mutation in the Naa10 gene,
encoding the NatA catalytic subunit, is known to cause N-terminal acetyltransferase deficient phenotypes. This genetic mutation has also been linked to X-linked disorder of infancy, causing lethality in
male infants[13]. The multifunctional roles of N-acetyltransferases as well as the importance of  N-terminal acetylation have been previously reviewed in [14]. Few MS-based studies have emerged that
specifically investigate acetylated N-termini in a proteome wide manner. The structural and functional integrity of actomyosin fibers depends on active NatB. A novel methodology determines the
extent of N-terminal acetylation in vivo through chemical, stable-isotope coded acetylation of proteins before their mass spectrometric analysis [16].

Pyroglutamate conversion of N-terminal glutamate and glutamine Many proteins and biologically active peptides exhibit an N-terminal pyroglutamic acid (pGlu) residue. This post
translational modification originates from the conversion of N-terminal glutamate and glutamine into pyroglutamic acid by glutaminyl cyclase or isoglutaminyl cyclase (Figure 2). N-terminal
pGlu influences structural stability as well as biological activity of peptides and proteins [17]. pGlu protects proteins from degradation by aminopeptidases [18] as well as regulating the
biological activity of peptide hormones, neuropeptides or chemokines [19]. Examples include thyrotropin releasing hormone (TRH), gonadotropin-releasing hormone, and the human
chemokines MCP-1 and 2. The presence of N-terminal pGlu in some amyloidogenic peptides, such as amyloid-b peptides, increases their hydrophobicity, resulting in an accelerated
aggregation [20]. Modulating the extent of N-terminal pGlu formation through pharmaceutical inhibition of glutaminyl cyclase is considered a promising strategy, for example, to
increase the degradation of inflammatory and neurotoxic peptides. Inhibition of glutaminyl cyclase has alleviated liver inflammation by destabilizing the chemokine MCP1 (CCL2) [21].
Proteolytic degradation of this promigratory chemokine by inhibiting glutaminyl cyclase was also proposed as an attractive novel strategy in preventing thyroid cancer metastasis [22].
Given the functional relevance of N-terminal pGlu in pathological conditions, an MS-based approach to profile this modification may be particularly useful.

N-terminal degrons N-terminal residues have a strong impact on protein stability and half-life. Firstly described in 1986 by Varshavsky and colleagues [25], the N-end rule pathway
has been identified in a broad range of species, from mammals to bacteria, and from yeast to plants [26]. This control of protein degradation in eukaryotes and bacteria is governed
by the formation and recognition of specific sequences at protein N-termini, called N-degrons. The main determinant of an N-degron is an N-terminal destabilizing residue. In eukaryotes,
two N-end rule pathways are being distinguished: the Ac/N-end rule pathway targets proteins through their N-terminally acetylated residues while the Arg/N-rule pathway targets
unacetylated N-terminal residues and involves N-terminal arginylation [26]. Proteolytic processing leading to new protein N-termini is increasingly recognized to play an important
role in the formation of N-degrons. In eukaryotes, N-degron mediated protein degradation occurs through the  ubiquitin–proteasome system. N degrons are recognized by E3
ubiquitin ligases called N-recognins, which induce protein ubiquitylation. Recent studies showed that the N-end rule pathway can be regulated by various mechanisms [26].
Hemin, the ferric (Fe3+) counterpart of heme, and short peptides can bind to components of the N-end rule pathway and impede their functionality [26]. Although the N-end rule
pathway has been molecularly dissected in great detail, numbers of identified physiological substrates undergoing N-end rule degradation have remained limited. A recent study
has expanded the range of substrates targeted by the Arg/N-end rule. Kim and colleagues have shown that N terminal Met followed by a hydrophobic residue functions as an N-degron
[27]. N-terminal Met followed by a small residue is typically removed by aminopeptidases in a cotranslational manner (Figure 2). However, approximately 15% of the genes in mammals
or yeast encode for an N-terminal Met followed by a larger hydrophobic residue. This specific N-degron is targeted by the Ac/N-end rule pathway when the N-terminal Met is acetylated.
The Arg/N-end rule acts instead on the non-acetylated N-terminal Met. As previously mentioned, novel N-degrons can be generated by preceding proteolysis. Piatkov and colleagues
investigated this concept for proteolytic cleavage products that occur during apoptosis [28]. They find that numerous proapoptotic fragments are short lived substrates of Arg/N-end
rule pathway, attributing to this pathway an anti-apoptotic role. Notably, the corresponding N-degron sequences are evolutionary conserved.

Figure 1 Protein N-termini are susceptible to various post-translational modification.
For a more comprehensive overview of all possible N terminal modification, see [60].

Figure 2 Examples of N-terminal mofications: acetylation, pyroglutamate conversion, proteolysis and N-degron processing via deamidation and amino acid conjugation.

Proteolytic processing of N-termini Proteolysis has long been regarded a degradation process. It is now increasingly recognized as an important posttranslational modification
with an array of proteases mediating cellular signaling via the precise processing of bioactive proteins and peptides. The study of cleavage events using N-terminomics is particularly
useful for the identification of proteolytic substrates. Proteolytic cleavage of proteins and polypeptides results in the generation of cleavage fragments with new N-termini and
C-termini. Numerous recent proteomic studies highlighted differential regulation of proteases in different disease settings. MALDI-TOF in combination with enzymatic assays
established reduced levels of dipeptidyl-peptidase (DPP)4 in the serum of patients suffering from metastatic prostate cancer [31]. Another proteomic based study,  using isotope
coded affinity tag (ICAT) labeling showed bacterial leucine aminopeptidase from Plasmodium chabaudi to be significantly upregulated in periodontal disease [32]. Mass spectrometry
was also used for the functional characterization of proteases.

7.3.10 Protein homeostasis networks in physiology and disease

Although most text books of biochemistry describe the process of protein folding to a three dimensional native state as an intrinsic property of the primary sequence, it is becoming increasingly clear that this process can go wrong in an almost infinite number of ways. In fact, many different diseases are caused by the misfolding and aggregation of certain proteins without genetic mutations in the primary sequence. An integrative view of the mechanisms that maintain protein folding homeostasis is emerging, which could be thought as a balanced and dynamic network of interconnected processes tightly regulated by a series of quality control mechanisms. This protein homeostasis network involves families of folding catalysts, co-factors under specific environmental and metabolic conditions. Maintaining protein homeostasis is particularly challenging in specialized secretory cells where the high demand for protein synthesis generates a constant source of stress that could lead to proteotoxicity.

Protein folding is assisted and monitored by diverse interconnected processes that follow a sequential pattern over time. The calnexin/calreticulin cycle ensures the proper folding of glycosylated proteins through the secretory pathway, which establishes the final pattern of disulfide bond formation through interactions with the disulfide isomerase ERp57. Coupled to this cycle is the ER-associated degradation (ERAD) pathway, which translocates terminally misfolded proteins to the cytosol for degradation by proteasomes. In addition, macroautophagy is becoming a relevant mechanism for the clearance of damaged proteins and abnormal protein aggregates through lysosomal hydrolysis, a process also referred to as ERAD-II. The folding status at the ER is constantly monitored by the Unfolded Protein Response (UPR), a specialized signaling pathway initiated by the activation of three types of stress sensors. The process underlying the surveillance of protein folding stress by the UPR is not fully understood, but it may require coupling to key folding mediators such as BiP or the direct recognition of the misfolded peptides by stress sensors. The UPR regulates genes and processs related to almost every folding step in the secretory pathway to reduce the load of misfolded proteins, including protein translation into the ER, translocation, folding, quality control, ERAD, the redox status, and many other related functions. Protein folding stress is observed in many disease conditions such as cancer, diabetes, and neurodegeneration. For example, abnormal protein aggregation and the accumulation of protein inclusions is associated with Parkinson’s and Alzheimer’s Disease, and amyotrophic lateral sclerosis. In those diseases and many others, neuronal dysfunction and disease progression correlates with the presence of a strong ER stress response; however, the direct in vivo role of the UPR in the disease process has been experimentally defined in only a few cases. Therapeutic strategies are currently being developed to increase protein folding and clearance of misfolded proteins, with the goal of alleviating ER stress.

In this issue of Current Opinion in Cell Biology we present a series of focused reviews from recognized experts in the field, that provide an overview of mechanisms underlying protein folding and quality control, and how balance of protein homeostasis is maintained in physiology and deregulated in diseases. Daniela Roth and William Balch integrate the concept of protein homeostasis networks into an interesting model termed FoldFx, showing how the interconnection between different pathways in the context of the cellular proteome determines the energetic barrier required to generate a functional folded peptide. The authors have previously proposed the term Proteostasis to refer to the set of interacting activities that maintain the health of the proteome and the organism (protein homeostasis). The ER is a central subcellular compartment for protein synthesis and quality control in the secretory pathway. Yukio Kimata and Kenji Kohno give an overview of the signaling pathways that control adaptation to ER stress and maintenance of protein folding homeostasis. The authors summarize the models proposed so far for the activation of UPR stress sensors, and discuss how this directly or indirectly relates to the accumulation of unfolded proteins in the ER lumen. Chronic or irreversible ER stress triggers cell death by apoptosis. Gordon Shore, Feroz Papa, and Scott Oakes summarize the complex signaling pathways initiating apoptosis by ER stress, where cross talk between the ER and the mitochondria play a central role. The authors focus on addressing the role of the BCL-2 protein family on the activation of intrinsic mitochondrial apoptosis pathways, highlighting different cytosolic and transcriptional events that determine the transition between adaptive responses to apoptosis programmed by the UPR to eliminate irreversibly injured cells.

Although diverse families of chaperones, foldases and co-factors are expressed at the ER, only a few protein folding networks have been well defined. However, molecular explanations for specific substrate recognition and quality control mechanisms are poorly defined. Here we present a series of reviews covering different aspects of protein maturation. Amy Lee summarizes what is known about the biology of the key ER folding chaperone BiP/Grp78, and its emerging role in diverse pathological conditions including cancer. In two reviews, David B. Williams and Linda M. Hendershot describe the best characterized mechanism of protein quality control at the ER, the calnexin cycle. In addition, they give an overview of the function of a family of ER foldases, the protein disulfide isomerases (PDIs), in folding, quality control and degradation of abnormally folded proteins. PDIs are also becoming key factors in establishing the redox tone of the ER. Riccardo Bernasconi and Maurizio Molinari overview the ERAD process and how this pathway affects the efficiency of the protein folding process at the ER and its relation to pathological conditions.

Lysosomal-mediated degradation is becoming a fundamental process for the control of the haft-life of proteins and the degradation of misfolded, aggregate prone proteins. Ana Maria Cuervo reviews the relevance of Chaperone-mediated autophagy in the selective degradation of soluble cytosolic proteins in lysosomes, and also points out a key role for Chaperone-mediated autophagy in the cellular defense against proteotoxicity. David Rubinsztein and Guido Kroemer present two reviews highlighting the emerging relevance of macroautophagy in maintaining the homeostasis of the nervous system. They also discuss the actual impact of macroautophagy in the clearance of protein aggregates related to neurodegenerative diseases, including Parkinson’s disease, amyotrophic lateral sclerosis, Huntington’s disease among others. In addition, recent evidence suggesting an actual impairment of macroautophagy as a causative factor in aging-related disorders is also discussed.

Alterations in protein homeostasis underlie the etiology of many diseases affecting the nervous system, in addition to cancer and diabetes. Fumiko Urano summarizes the impact of ER stress in β cell dysfunction and death during the progression of type 1 and type 2 diabetes, as well as in genetic forms of diabetes such as Wolfram syndrome. The occurrence of basal ER stress is observed in specialized secretory cells and organs, including plasma B cells. Roberto Sitia covers several aspects of how proteotoxic stresses physiologically contribute to regulate the biogenesis, function and lifespan of B cells, and speculates about the possible impact of ER stress in the treatment of multiple myeloma. Claudio Soto describes the specific role of calcineurin, a key phosphatase in the brain, in the occurrence of synaptic dysfunction and neuronal death in prion-related disorders. We also present provide a review summarizing the emerging role of ER stress and the UPR in most neurodegenerative diseases related to protein misfolding. We also discuss the particular mechanisms currently proposed to be involved in the generation of protein folding stress at the ER in these pathologies, and speculate about possible therapeutic interventions to treat neurodegenerative diseases.

Strategies to increase the efficiency of quality control mechanisms, to reduce protein aggregation and to enhance folding are suggested to be beneficial in the setting of diseases associated with the disruption of protein homeostasis. Finally, Jeffery Kelly overviews recent chemical and biological therapeutic strategies to restore protein homeostasis, which could be achieved by enhancing the biological capacity of the proteostasis network or through small molecule to stabilize misfolding-prone proteins. In summary, this volume ofCurrent Opinion in Cell Biology compiles the most recent advances in understanding the impact of protein folding stress in physiology and disease, and integrates a variety of complex mechanisms that evolved to maintain protein homeostasis in a dynamic way in the context of a changing environment. The biomedical applications of developing strategies to cope with protein folding stress have profound implications for the treatment of the most prevalent diseases in the human population.

7.3.11 Proteome sequencing goes deep
Advances in mass spectrometry (MS) have transformed the scope and impact of protein characterization efforts. Identifying hundreds of proteins from rather simple biological matrices, such as yeast, was a daunting task just a few decades ago. Now, expression of more than half of the estimated ∼20,000 human protein coding genes can be confirmed in record time and from minute sample quantities. Access to proteomic information at such unprecedented depths has been fueled by strides in every stage of the shotgun proteomics workflow-from sample processing to data analysis-and promises to revolutionize our understanding of the causes and consequences of proteome variation.
Highlights
    • Recent MS advances have transformed the depth of coverage of the human proteome.• Expression of half the estimated human protein coding genes can be verified by MS.• MS sample preparation, instrumentation, and data analysis techniques are highlighted.

http://ars.els-cdn.com/content/image/1-s2.0-S1367593114001586-gr1.sml

Mammalian proteomes  are complex [3]. The human proteome contains ~20,300 protein-coding genes; however, non-synonymous single nucleotide polymorphisms (nsSNPs), alternative
splicing events, and post-translational modifications (PTMs) all occur and exponentially increase the number of distinct proteoforms [4–6]. Detection of 5000 proteins in a proteomic
experiment was a considerable achievement just a few years ago [7–9]. More recently, two groups identified over 10,000 protein groups in a single experiment. Through extensive protein
and peptide fractionation (72 fractions) and digestion with multiple enzymes, Nagaraj et al. identified 10,255 protein groups from HeLa cells over 288 hours of instrument analysis [10].
A comparison with paired RNA-Seq data revealed nearly complete overlap between the detected proteins and the expressed transcripts. In that same year, a similar strategy enabled
the identification of 10,006 proteins from the U2OS cell line [11]. Kim and co-workers analyzed 30 human tissues and primary cells over 2000 LC–MS/MS experiments, resulting
in the detection of 293,000 peptides with unique amino acid sequences and evidence for 17,294 gene products [16]. Wilhelm et al. amassed a total of 16,857 LC–MS/MS experiments
from human cell lines, tissues, and body fluids. These experiments produced 946,000 unique peptides, which map to 18,097 protein coding genes [17]. Together, these two studies
provide direct evidence for protein translation of over 90% of  human genes (Figure 2). New developments in mass spectrometer technology have increased the rate at which proteomes
can be analyzed. We describe developments in sample preparation, MS instrumentation, and bioinformatics that have been key to obtaining comprehensive proteomic coverage.
Further, we consider how access to such proteomic detail will impact genomic  research.

Aurelian Udristioiu

Aurelian

Aurelian Udristioiu

Lab Director at Emergency County Hospital Targu Jiu

Mg²+ is critical for maintaining the positional integrity of closely clustered phosphate groups. These clusters appear in numerous and distinct parts of the cell nucleus and cytoplasm. The Mg²+ ion maintains the integrity of nucleic acids, ribosomes and proteins. In addition, this ion acts as an oligo-element with role in energy catalysis. Biological cell membranes and cell walls exhibit poly-anionic charges on the surface. This finding has important implications for the transport of ions, particularly because different membranes preferentially bind different ions. Both Mg²+ and Ca²+ regularly stabilize membranes by cross-linking the carboxylated and phosphorylated head groups of lipids.

Notable document –

Theor Biol Med Model. 2010 Jun 9;7:19.
Native aggregation as a cause of origin of temporary cellular structures needed for all forms of cellular activity, signaling and transformations.
Matveev VV1.
Cell physiologist at Institute of Cytology, Russian Academy of Sciences

According to the hypothesis explored in this paper, native aggregation is genetically controlled (programmed) reversible aggregation that occurs when interacting proteins form new temporary structures through highly specific interactions. It is assumed that Anfinsen’s dogma may be extended to protein aggregation: composition and amino acid sequence determine not only the secondary and tertiary structure of single protein, but also the structure of protein aggregates (associates). Cell function is considered as a transition between two states (two states model), the resting state and state of activity (this applies to the cell as a whole and to its individual structures). In the resting state, the key proteins are found in the following inactive forms: natively unfolded and globular. When the cell is activated, secondary structures appear in natively unfolded proteins (including unfolded regions in other proteins), and globular proteins begin to melt and their secondary structures become available for interaction with the secondary structures of other proteins. These temporary secondary structures provide a means for highly specific interactions between proteins. As a result, native aggregation creates temporary structures necessary for cell activity.”One of the principal objects of theoretical research in any department of knowledge is to find the point of view from which the subject appears in its greatest simplicity.”Josiah Willard Gibbs (1839-1903).

http://www.ncbi.nlm.nih.gov/pmc/articles/instance/2901313/bin/1742-4682-7-19-1.gif

http://www.ncbi.nlm.nih.gov/pmc/articles/instance/2901313/bin/1742-4682-7-19-2.gif

To date, numerous mechanisms, signal pathways, and different factors have been found in the cell. Researchers are naturally eager to find commonalities in the mechanisms of cellular regulation. I would like to propose a substantial approach to problems of cell physiology – the structural ground that produces signals and underlies the diversity of cellular mechanisms.

The methodological basis for the proposed hypothesis results from studies by the scientific schools of Dmitrii Nasonov [1] and Gilbert Ling [26], which have gained new appreciation over the last 20-30 years owing to advances in protein physics [7] in the study of properties of globular proteins, their unfolding and folding, as well as the discovery of novel states of the protein molecule: the natively unfolded and the molten globule. The key statement for the rationale of the present paper is that the specificity of interactions of polypeptide chains with each other (at the intra- and inter-molecular levels) can be provided only by their secondary structures, primarily α-helices and β-sheets.

Nasonov’s school discovered and studied a fundamental phenomenon — the nonspecific reaction of the cell to external actions [1], while works by Ling [5] and his followers allow the mechanisms of this phenomenon to be understood.

The above-mentioned cell reaction has been called nonspecific because diverse physical and chemical factors produce the same complex of structural changes in the cell: an increase in the turbidity and macroscopic viscosity of the cytoplasm and in the adsorption of hydrophobic substances by cytoplasmic proteins. It is of primary importance that the same changes also occur in the cell during its transition into the active state: muscle contraction, action potential, enhancement of secretory activity (for details, see [8]). Hence, from the point of view of structural changes, there is no fundamental difference between the result of action on the cell of hydrostatic pressure and, for instance, muscle contraction. In both cases, proteins are aggregated.

Nasonov called the cause of these changes the stages of cell protein denaturation, as the changes of properties of isolated proteins during denaturation are very similar to the changes in the cytoplasm during the nonspecific reaction. As a result, the denaturational theory of cell excitation and damage was created [1]. The structural changes of protein denaturation were unclear in Nasonov’s time. Nowadays, it is assumed that the denaturation is the destruction of the tertiary and secondary structure of a protein. Below I give two definitions, for the denaturation of natively folded (globular) proteins and for natively unfolded proteins.

A key notion in physiology is the resting state of the cell. This is implicit in the concept of the threshold character of the action of stimuli on the cell, which has played a historical role in the development of physiological science. It is the threshold that is the boundary between two states — rest and activity. But in effect, all our knowledge about cells concerns active cells, not cells in the resting state. It is in the active cell that variable changes occur that can be recorded. Nothing happens in the resting cell, so there is nothing to be recorded in it. Nevertheless, it is obvious that the resting state is the initial cell state, the starting point for all changes occurring in the cell.

What characterizes the structural aspect of the cell in the state of rest? It is only in Ling’s work [5] that I have found a clear answer to this question. The answer can be interpreted as follows: if all resting cell proteins were arranged in one line, it would turn out that most of the peptide bonds in this superpolypeptide would be accessible to solvent (water), while only a few would be included in secondary structures. When the cell is activated, the ratio between the unfolded and folded areas is changed sharply to the opposite: the proportion of peptide bonds accessible to solvent decreases markedly, whereas the proportion included in secondary structures rises significantly. These two extreme states of cell proteins, suggested by Ling, provide a basis for further consideration.

If Ling’s approach is combined with Nasonov’s theory, we obtain several interesting consequences. First of all, it is clear that proteins with maximally unfolded structures form the structural basis of resting cells because they are inactive, i.e., do not interact with other proteins or other macromolecules. The situation changes when an action on the cell exceeds the threshold: completely or partially unfolded key proteins begin to fold when new secondary protein structures are formed. Owing to these new secondary structures, the proteins become capable of reacting, i.e., intramolecular aggregation (folding of individual polypeptides into globules) and intermolecular aggregation (interaction of some proteins with others) begin. A distinguishing feature of these aggregational processes is their absolutely specific character, which is ensured by the amino acid composition, shape, and size of the secondary structures. The structures appearing have physiological meaning, so such aggregation is native and the secondary structures causing it are centers of native aggregation. Another source of secondary structures necessary for native aggregation is the molten globule.

The ability of cells to return to the initial state, the state of rest, means that native aggregation is completely reversible, and the structures appearing in the course of native aggregation are temporary and are disassembled as soon as they cease to be necessary. Native aggregation can involve both the whole cell and individual organelles, compartments, and structures, and activation of proteins is of a threshold rather than a spontaneous character.

The meaning of the proposed hypothesis of native aggregation is that the primary cause of any functional changes in cell is the appearance, as a result of native aggregation, of temporary structures, continually appearing and disintegrating during the life of the cell. Since native aggregation is initiated by external stimuli or regulatory processes and the structures appearing have a temporary character, these structures can be called signal structures.

Signal structures can have different properties: (i) they can be centers of binding of ions, molecules (solutes), and proteins; (ii) they can have enzymatic activity; (iii) they can form channels and intercellular contacts; (iv) they can serve as matrices organizing the interactions of molecules in synthetic and transport processes; (iv) they can serve as receptors for signal molecules; (v) they can serve as the basis for constructing even more complex supramolecular structures. These structures “flash” in the cell space like signal lights, perform their role, and disappear, to appear in another place and at another time. The meaning of the existence of the structural “flashes” is that during transition into the active state the cell needs new resources, functions, mechanisms, regulators, and signals. As soon as the cell changes to the resting state, the need for these structures disappears, and they are disassembled. Extreme examples of native aggregation are muscle contraction, condensation of chromosomes, the appearance of the division spindle, and interactions of ligands with receptors.

Thus, the present paper will consider the meaning and significance of native aggregation as the universal structural basis of the active cell. The basis of pathological states is the inability of the cell to return to the resting state and errors in the formation of signal structures. The presentation of native aggregation is based on three pillars: (i) reversible protein aggregation is a structural basis of cell activity (Nasonov’s School); (ii) the operation of the living cell or its individual structures can be regarded as a repetitive sequence of transitions between two states (active and resting), a key role in which belongs to natively unfolded proteins (Ling’s approach); (iii) the specificity of interactions of separate parts of a single polypeptide chain with each other (folding) or the interaction of separate polypeptide chains among themselves (self-assembly, aggregation) can be provided only by protein secondary structures.

The goal of this paper is the enunciation of principles, rather than a review of facts corresponding to these principles.

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Novel Approaches to Cancer Therapy

Writer sand Curator: Larry H. Bernstein, MD, FCAP

11.1       Novel Approaches to Cancer Therapy

11.1.1 Electrically-driven modulation of surface-grafted RGD peptides for .. cell adhesion

11.1.2 The metabolic state of cancer stem cells—a target for cancer therapy

11.1.3 Regulation of tissue morphogenesis by endothelial cell-derived signals

11.1.4 Novel approach to bis(indolyl)methanes. De novo synthesis of 1-hydroxyimino-methyl derivatives with anti-cancer properties

11.1.5 Synthesis and Biological Evaluation of New 1,3-Thiazolidine-4-one Derivatives of 2-(4-Isobutylphenyl)propionic Acid molecules

11.1.6 Targeting pyruvate kinase M2 contributes to radiosensitivity of NSCLC cells

11.1.7 The tyrosine kinase inhibitor nilotinib has antineoplastic activity in prostate cancer cells but up-regulates the ERK survival signal—Implications for targeted therapies

11.1.8 PAF and EZH2 Induce Wnt.β-Catenin Signaling Hyperactivation

11.1.9 PAF Makes It EZ(H2) for β-Catenin Transactivation

11.1.10 PI3K.AKT.mTOR pathway as a therapeutic target in ovarian cancer

11.1.11 Endogenous, hyperactive Rac3 controls proliferation of breast cancer cells by a p21-activated kinase-dependent pathway

11.1.12 Curcumin-could-reduce-the-monomer-of-ttr-with-tyr114cys-mutation via autophagy in cell model of familial amyloid polyneuropathy.

11.1.1 Electrically-driven modulation of surface-grafted RGD peptides for .. cell adhesion

Lashkor M1Rawson FJStephenson-Brown APreece JAMendes PM.
Chem Commun (Camb). 2014 Dec 21; 50(98):15589-92
http://dx.doi.org/10.1039%2Fc4cc06649a

Reported herein is a switchable surface that relies on electrically-induced conformational changes within surface-grafted arginine–glycine–aspartate (RGD) oligopeptides as the means of modulating cell adhesion

Stimuli-responsive surfaces that are capable of modulating their biological properties in response to an external stimuli, including temperature,1,2 light,3 magnetic field4 and electrical potential,59 are of growing interest for a variety of biological and medical applications.10,11 Switchable surfaces that can be controlled on-demand are playing an increasingly important part in the development of highly sensitive biosensors,1215novel drug delivery systems1618 and functional microfluidic, bioanalysis, and bioseparation systems.1922Additionally, dynamic, synthetic surfaces that can control the presentation of regulatory signals to a cell are expected to have a significant impact in the field of tissue engineering and regenerative medicine, and to provide unprecedented opportunities in fundamental studies of cell biology.23,24 The availability of sophisticated and functional switchable surfaces is expected to emulate more complex in vivo like extracellular environments, and provide a powerful means to probe and control the dynamic interactions between the cell and its external environments.

The majority of studies on stimuli-responsive surfaces reported to date either rely2529 on controlling non-specific interactions (i.e., hydrophobic/hydrophilic and electrostatic) of the biomolecules with the active surface, or have focused3032 on demonstrating modulation of specific biomolecular interactions using relatively simple biological systems (e.g. biotin–streptavidin) and conditions (i.e. water or buffer solutions). For example, Zareie et al. 30 fabricated a mixed self-assembled monolayer (SAM) on gold comprising oligo(ethylene glycol) (OEG) thiol molecules and shorter disulfides carrying biotin end-groups that regulated the interaction between biotin and streptavidin in water. The OEG thiols were able to switch in response to a change in temperature below and above their lower critical solution temperature (LCST = 37 °C). At 23 °C the structure of the OEG molecules was fully extended hindering the shorter biotin disulfide components. On the contrary, at 45 °C the OEG backbone collapsed, thus allowing the specific interaction between the biotin molecule on the surface and the protein streptavidin in solution. In our previous work,79 electrically controlled switching has been applied to regulate the conformational changes of modified positively charged oligolysine peptides tethered to a gold surface, such that biotin moieties incorporated into the oligolysines could be reversibly exposed or concealed on demand, as a function of surface potential. Switchable SAMs used to control biomolecular interactions via an electrical stimulus are particularly appealing because of their fast response times, ease of creating multiple individually addressable switchable regions on the same surface, as well as low-drive voltage and electric fields, which are compatible with biological systems.33 Our previous reported electrically switchable surface was able to control directly the biomolecular interactions between biotin and neutravidin in phosphate buffer saline (PBS) solution.

However, switchable surfaces have been scarcely used, thus far, to control biomolecular interactions on more complex systems such as those involving modulation of cell responsiveness.3437 Jonkheijm and co-workers35 have reported a cucurbit[8]uril-based SAM system to electrochemically control the release of cells. Charged end groups on SAM surfaces have been exploited to electrically control the early stages of bacterial cell adhesion37 and form patterned surfaces with two independent dynamic functions for inducing cell migration.36 In spite of these efforts, given cellular complexity and diversity, such studies are very limited in number, as are the opportunities to further understand and control the complex interplay of events and interactions occurring within living cells.

Herein, we report on a stimuli-responsive surface that relies on electrically-induced conformational changes within surface-grafted arginine–glycine–aspartate (RGD) oligopeptides as the means of modulating cell adhesion. RGD, which is present in most of the adhesive ECM proteins (e.g. fibronectin, vitronectin, laminin and collagen), is specific for integrin-mediated cell adhesion.38 The RGD modified electrode is used here to dynamically regulate the adhesion of immune macrophage cells. The stimuli-responsive surface is fabricated on a gold surface and comprises a mixed SAM consisting of two components (Fig. 1): (i) an oligopeptide containing a terminal cysteine for attachment to the gold surface, three lysine residues as the main switching unit, and a glycine–arginine–glycine–aspartate–serine (GRGDS) as the recognition motif for cell adhesion –C3K-GRGDS, and (ii) an ethylene glycol-terminated thiol (C11TEG) to space out the oligopeptides. Since the charged backbone of the oligopeptide can be potentially harnessed79 to induce its folding on the surface upon an application of an electrical potential, we reasoned that such conformational changes can be employed to selectively expose under open circuit (OC) conditions (bio-active state) or conceal under negative potential (bio-inactive state) the RGD to the cell and dynamically regulate cell adhesion.

 rdg-oligopeptide-sam-utilised-for-controlling-specific-cellular-interactions-c4cc06649a


rdg-oligopeptide-sam-utilised-for-controlling-specific-cellular-interactions-c4cc06649a

RDG oligopeptide SAM utilised for controlling specific cellular interactions

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4230383/bin/c4cc06649a-f1.jpg

Fig. 1 Schematic of the dynamic RDG oligopeptide SAM utilised for controlling specific cellular interactions. The electrically switchable SAM exposes the RGD peptide and supports cell adhesion under open circuit (OC) conditions (no applied potential), while …

Mixed SAMs of C3K-GRGDS : C11TEG were formed from a solution ratio of 1 : 40 and characterised by X-ray photoelectron spectroscopy (XPS) (Fig. S2, ESI). XPS analysis confirmed the formation of the C3K-GRGDS:C11TEG mixed monolayer and displayed signals from S, N, C and O. The chemical state of the sulphur atom was probed using the XPS spectra of the S 2p emission (Fig. S2, ESI). The S 2p spectrum (Fig. S2a, ESI) consists of two doublet peaks, with one doublet peak at 162.0 eV (S 2p3/2) and 163.2 eV (S 2p1/2), indicating that the sulphur is chemisorbed on the gold surface.39 A second small doublet peak can be observed at 163.8 eV and 165.0 eV, which can be attributed to the S–H bond, indicating a small presence of unbound sulphur. No sulphur peaks above 166 eV were observed, indicating that no oxidised sulphur is present at the surface. The N 1s spectrum (Fig. S2b, ESI) can be de-convoluted into two peaks, which support the presence of the peptide on the surface. The first peak centred at 400.5 eV is attributed to amino (NH2) and amide (CONH) moieties. The second peak centred at 402.8 eV is ascribed to protonated amino groups.40 Note that no nitrogen peak was observed for pure C11TEG SAMs. The C 1s spectrum (Fig. S2c, ESI) can be de-convoluted into three peaks, which are attributed to five different binding environments. The peak at 285.0 eV is attributed to C–C bonds,41 while the peak at 286.7 eV corresponds to C 1s of the three binding environments of C–S, C–N and C–O.41 The third and smaller peak (288.6 eV) is assigned to the C 1s photoelectron of the carbonyl moiety, C O.41 The O 1s spectrum (Fig. S2d, ESI) is de-convoluted into two different peaks, corresponding to two different binding environments, arising from the C–O (533.3 eV) and C O (532.0 eV) bonds.41 From integrating the area of the S 2 p and N 1s peaks and taking into consideration that the C3K-GRGDS oligopeptide consists of 15 N atoms and 1 S atom and C11TEG has no N and 1 S atom only, it was possible to infer that the ratio of C3K-GRGDS:C11TEG on the surface is 1 : 10 ± 2. The presence of C11TEG was utilised not only to ensure sufficient spatial freedom for molecular reorientation of the surface bound oligopeptide, but also to stop non-specific binding to the surface.

The C3K-GRGDS:C11TEG mixed SAMs were shown to support adhesion of immune macrophage cells as determined by cell counting42,43 (Fig. 2). When RAW 264.7 mouse macrophages were cultured on theC3K-GRGDS:C11TEG mixed SAM in supplemented Dulbecco’s Modified Eagle Medium (DMEM), the number of cells adhered to the surface increased with incubation time, reaching 1792 ± 157 cells per mm2after 24 hours. This is in contrast with the weak cell adhesion observed in two control surfaces, pureC11TEG SAMs and clean gold, in which the number of cells that adhere was 60% and 50% lower, respectively, after 24 hours (Fig. 2).

microscopic-images-and-density-of-adhered-cells-on-c3k-grgds-c11teg-mixed-sam-pure-c11teg-sam-and-bare-gold-surfaces

microscopic-images-and-density-of-adhered-cells-on-c3k-grgds-c11teg-mixed-sam-pure-c11teg-sam-and-bare-gold-surfaces

Microscopic images and density of adhered cells on C3K-GRGDS:C11TEG mixed SAM, pure C11TEG SAM and bare gold surfaces

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4230383/bin/c4cc06649a-f2.jpg

Fig. 2 Microscopic images and density of adhered cells on C3K-GRGDS:C11TEG mixed SAM, pure C11TEG SAM and bare gold surfaces that were normalized against the density of cells adherent onto the C3K-GRGDS:C11TEG mixed SAM. The surfaces were cultured in RAW 264.7 mouse macrophage cells under OC conditions for 24 hours.

In order to demonstrate that the C3K-GRGDS:C11TEG mixed SAMs can support or resist cell adhesion on demand, the macrophage cells were cultured on the C3K-GRGDS:C11TEG mixed SAM in DMEM medium under OC conditions and applied negative potential (–0.4 V) for a period of 1 h. Note that DMEM contains a mixture of inorganic salts, amino acids, glucose and vitamins. On application of the applied potential of –0.4 V the number of adherent cells was 70% less compared to the C3K-GRGDS:C11TEGmixed SAMs under OC conditions, Fig. 3. Similar switching efficiencies have been observed in another oligopeptide system using different DMEM solutions.44 These findings suggest that the negative potential induces the conformational changes in the C3K moiety of C3K-GRGDS in the SAM which in turn leads to the RGD moiety being concealed and hence reducing the binding of the cells.

density-of-adhered-cells-on-c3k-grgds-c11teg-c11teg-c6eg-grgds-c11teg-mixed-sams-c4cc06649a-f3

density-of-adhered-cells-on-c3k-grgds-c11teg-c11teg-c6eg-grgds-c11teg-mixed-sams-c4cc06649a-f3

Density of adhered cells on C3K-GRGDS:C11TEG, C11TEG, C6EG-GRGDS:C11TEG mixed SAMs

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4230383/bin/c4cc06649a-f3.jpg

Fig. 3 Density of adhered cells on C3K-GRGDS:C11TEG, C11TEG, C6EG-GRGDS:C11TEG mixed SAMs that were normalized against the density of cells adherent onto the C3K-GRGDS:C11TEG mixed SAM. The surfaces were cultured in RAW 264.7 for 1 h under OC conditions or while applying –0.4 V.

Previous studies have shown that small conformational and orientational changes in proteins and peptides modulate the availability and potency of the active sites for cell surface receptors.4547 Thus, in a similar manner, small changes in the conformation/orientation of the RGD peptide on the surface induced by application of an electrical potential are able to affect the binding activity of the peptide. Recently, we have conducted detailed theoretical8 and experimental9 studies aimed at understanding the switching mechanism of oligopeptide-based switchable surfaces, that similarly as in the case of the C3K-GRGDS:C11TEG mixed SAMs, use lysine residues to act as the switching unit. These previous studies unraveled that the surface-appended oligolysines undergo conformational changes between fully extended, partially extended and collapsed conformer structures in response to an applied positive potential, open circuit conditions and negative electrical potential, respectively. Thus, these previous findings allow us to propose that when a negative potential is applied to the GRGDS:C11TEG mixed SAM surface, the oligopeptide chain adopts a collapsed conformation on the surface and the RGD binding motif is partially embedded on the C11TEGmatrix, thus showing no bioactivity (“OFF” state).

In order to verify that the changes in adhesion upon application of a negative surface potential occur due to changes in the conformational orientation of the RGD instead of cell repulsion or cell damage due to the presence of an electrical potential, control mixed SAMs were also prepared using C11TEG and a peptide where the 3 lysine residues as the switching unit were replaced by 6 non-switchable ethylene glycol units –C6EG-GRGDS (Fig. S1, ESI). Fig. 3 demonstrates that cells adhered in similar numbers to the C11TEGand C6EG-GRGDS:C11TEG mixed SAMs under OC conditions and an applied negative potential. These results provide strong evidence that control over cell adhesion using the C3K-GRGDS:C11TEG mixed SAM is due to a conformational behaviour of the lysine-containing oligopeptide that can either expose or conceal the RGD moiety.

Cell viability was checked following application of –0.4 V for 1 h by performing a trypan blue assay. Cells that were dead were stained blue due to a break down in membrane integrity. Incubation of the cells under a negative potential had negligible effect on cell viability, which was greater than 98%. Cyclic voltammetric studies (outlined in detail in the Fig. S3, ESI) were also performed to demonstrate that no significant faradaic process occur over the potential range studied, and thus ions are not participating in redox reactions and consequently redox chemistry is not being significantly affected by application of the potential used. In agreement with other studies,35,36,48 we conclude that the electrical modulation of the surface neither affected cell viability nor induced any redox process in the medium that could have had an effect on cells.

We then addressed the question of whether the C3K-GRGDS:C11TEG surfaces could be switched between different cell adhesive states (cell-resistant and cell-adhesive states). To begin with, we investigated the switching from a cell-adhesive state to a cell-resistant state, and the possibility to detach the cells from the substrate upon the application of a negative potential. Cells were incubated in the C3K-GRGDS:C11TEGmixed SAMs for 1 h under OC conditions, thereby exposing the RGD moiety and allowing for cell attachment. This step was followed by the application of a potential of –0.4 V for 1 h in order to detach the cells from the surface, by concealing the RGD moieties. Cell counts showed no significant differences between the pre and post application of the –0.4 V, suggesting that the electrostatic force generated by the applied negative electrical potential might not be sufficient to disrupt the RGD–integrin interaction. These results were to a certain extent expected since adherent cells are able to withstand strong detachment forces due to the adhesion being mediated by multiple RGD–integrin bonds in parallel.49

In contrast, a reversal of the switching sequence demonstrated that our surfaces can be dynamically switched from a non-adhesive to cell-adhesive state. Cells were incubated in the C3K-GRGDS:C11TEG mixed SAMs for 1 h while holding the potential at –0.4 V for 1 h making the RGD peptide inaccessible for recognition by the corresponding integrin. As above, the number of adherent cells when a negative potential of –0.4 V was applied was 70% of the number that adhered to the C3K-GRGDS:C11TEG mixed SAMs under OC conditions, Fig. 4. The potential was then shifted to open circuit conditions for 1 h on those exposed to a potential of –0.4 V, which resulted in a significant increase in the number of cells as a result of the exposure of the RGD moiety to the cells (Fig. 4). These values were similar to those obtained for the samples that were only incubated for 1 hour under OC conditions (Fig. 4), indicating that the surfaces were highly effective at switching from a non-adhesive to cell-adhesive state.

microscopic-images-and-density-of-adhered-cells-on-c3k-grgds-c11teg-mixed-sams-c4cc06649a-f4

microscopic-images-and-density-of-adhered-cells-on-c3k-grgds-c11teg-mixed-sams-c4cc06649a-f4

Microscopic images and density of adhered cells on C3K-GRGDS:C11TEG mixed SAMs

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4230383/bin/c4cc06649a-f4.jpg

Fig. 4  Microscopic images and density of adhered cells on C3K-GRGDS:C11TEG mixed SAMs that were incubated with cells for 1 h while applying –0.4 V and subsequently in OC conditions for 1 h. The density was normalized against the density of cells adherent onto C3K-GRGDS:C11TEG mixed SAMs that were incubated with cells in OC conditions for 1 h.

In summary, an electrically switchable surface has been devised and fabricated that is capable of efficiently exposing and concealing the RGD cell adhesion motif and dynamically regulate the adhesion of immune macrophage cells. This study will no doubt be useful in developing more realistic dynamic extracellular matrix models and is certainly applicable in a wide variety of biological and medical applications. For instance, macrophage cell adhesion to surfaces plays a key role in mediating immune response to foreign materials.50 Thus, development of such dynamic in vitro model systems that can control macrophage cell adhesion on demand are likely to provide new opportunities to understand adhesion signaling in macrophages51 and develop effective approaches for prolonging the life-span of implantable medical devices and other biomaterials.52

11.1.2 The metabolic state of cancer stem cells—a target for cancer therapy

Vlashi E1Pajonk F2.
Free Radic Biol Med. 2015 Feb; 79:264-8
http://dx.doi.org:/10.1016/j.freeradbiomed.2014.10.732

Highlights

  • Bulk tumor cell populations rely on aerobic glycolysis.
  • Cancer stem cells are in a specific metabolic state.
  • Cancer stem cells in breast cancer, glioblastoma, and leukemia rely on oxidative phosphorylation of glucose.

In the 1920s Otto Warburg first described high glucose uptake, aerobic glycolysis, and high lactate production in tumors. Since then high glucose uptake has been utilized in the development of PET imaging for cancer. However, despite a deepened understanding of the molecular underpinnings of glucose metabolism in cancer, this fundamental difference between normal and malignant tissue has yet to be employed in targeted cancer therapy in the clinic. In this review, we highlight attempts in the recent literature to target cancer cell metabolism and elaborate on the challenges and controversies of these strategies in general and in the context of tumor cell heterogeneity in cancer.

 

 

11.1.3 Regulation of tissue morphogenesis by endothelial cell-derived signals

Saravana K. RamasamyAnjali P. KusumbeRalf H. Adams
Trends Cell Biol  Mar 2015; 25(3):148–157
http://dx.doi.org/10.1016/j.tcb.2014.11.007

Highlights

  • Endothelial cells lining blood vessels induce organ formation and other morphogenetic processes in the embryo.
  • Blood vessels are also an important source of paracrine (angiocrine) signals acting on other cell types in organ regeneration.
  • Vascular niches and endothelial cell-derived signals generate microenvironments for stem and progenitor cells.

Endothelial cells (ECs) form an extensive network of blood vessels that has numerous essential functions in the vertebrate body. In addition to their well-established role as a versatile transport network, blood vessels can induce organ formation or direct growth and differentiation processes by providing signals in a paracrine (angiocrine) fashion. Tissue repair also requires the local restoration of vasculature. ECs are emerging as important signaling centers that coordinate regeneration and help to prevent deregulated, disease-promoting processes. Vascular cells are also part of stem cell niches and have key roles in hematopoiesis, bone formation, and neurogenesis. Here, we review these newly identified roles of ECs in the regulation of organ morphogenesis, maintenance, and regeneration.

http://ars.els-cdn.com/content/image/1-s2.0-S0962892414002104-gr1.sml

Figure 1. Role of endothelial cells (ECs) during organogenesis

http://ars.els-cdn.com/content/image/1-s2.0-S0962892414002104-gr2.sml

Figure 2. Endothelial cells (ECs) in lung regeneration

http://ars.els-cdn.com/content/image/1-s2.0-S0962892414002104-gr3.sml

Figure 3. Liver endothelium in regeneration and fibrosis.

Vascular cells have key roles in morphogenesis and regeneration

Vascular cells have key roles in morphogenesis and regeneration

http://ars.els-cdn.com/content/image/1-s2.0-S0962892414002104-gr4.sml

Figure 4. Functional roles of the bone vasculature

http://ars.els-cdn.com/content/image/1-s2.0-S0962892414002104-gr5.sml

Figure 5. Vascular niche for neurogenesis.

Concluding remarks

The examples provided in this review highlight the important roles of ECs in tissue development, patterning, homeostasis, and regeneration. The endothelium often takes a central position in these processes and there are many reasons why ECs are ideally positioned as the source of important instructive, angiocrine signals. The vascular transport network extends into every organ system and needs to be embedded in those tissues in a certain spacing or pattern, which places ECs in central and, therefore, strategic positions for the regulation of morphogenesis and organ homeostasis.

Given that ECs and other cell types frequently form functional units, such as kidney glomeruli, liver lobules, or lung alveoli, the assembly, differentiation, and function of the different cellular components needs to be tightly coordinated. In addition, because circulating blood cells extensively rely on the vascular conduit system and frequently interact with the endothelium, it is perhaps not surprising that ECs contribute to niche microenvironments. During tissue repair, proliferative cell expansion processes are sometimes temporally separated from cell differentiation and tissue patterning events. The latter has to involve the restoration of a fully functional vascular network so that ECs appear ideally suited as the source of molecular signals that can trigger or suppress processes in the surrounding tissue.

 

11.1.4 Novel approach to bis(indolyl)methanes. De novo synthesis of 1-hydroxyimino-methyl derivatives with anti-cancer properties

Grasso C, et al.
Eur J Medicinal Chem 01/2015; 93:9-15.
http://dx.doi.org:/10.1016/j.ejmech.2015.01.050

A versatile and broad range approach to previously unknown bis(indolyl)methane oximes based on two consecutive hetero Diels-Alder cycloaddition reactions of electrophilic conjugated nitrosoalkenes with indoles is disclosed. The cytotoxic properties and selectivity of some adducts against several human cancer cell lines pointing to a promising role in the development of anti-tumoural drugs, in particular for leukemia and lymphoma.

Novel approach to bis(indolyl)methanes: De novo synthesis of 1-hydroxyiminomethyl derivatives with anti-cancer properties. Available from:
https://www.researchgate.net/publication/271525370

_Novel_approach_to_bis-28indolyl-29methanes_De_novo_synthesis_of_1-hydroxyiminomethyl_ derivatives_with_anti-cancer_properties [accessed Apr 11, 2015].

The one-pot synthetic strategy to bis(indolyl)methanes is outlined in Scheme 3. The starting a,a 0-dihalogenooximes 3 were efficiently prepared from the respective ketones by known procedures [58,61]. These compounds, in the presence of base, were converted, in situ, into the corresponding transient and reactive nitrosoalkenes 4, which were intercepted bya first molecule of the appropriate indole 5 originating the intermediate indole oximes 6. The initially formed tetrahydroxazines undergo ring-opening to the corresponding oximes, under the driving force of the energy gain on rearomatisation. Subsequent dehydro-halogenation of 6 produces nitrosoalkenes 7 which reacted with a second molecule of indole, producing the target bis(indolyl)methanes 8. The results obtained are summarised in Table 1.

The reaction yields may be considered generally good, taking into account that the synthetic process involves a sequence of reactions. On the other hand, no other products could be obtained, which indicates that the reactions were regioselective. The results have shown also that both alkyl and aryl oximes can be used in the synthesis of bis(indolyl)methanes. Starting from aryl oximes 3aef the expected (E) oximes 9 were obtained as single or major products (Entries 1e11) whereas alkyl oxime 3g reacted with indole to give the (Z)-oxime 10g as the major product (Entries 12e13). The stereochemistry assignment of oximes 9 and 10 was confirmed by analysis of the NOESY spectra of 9d, 9g, 10d and 10g. In the spectra of 10d and 10g, connectivity was observed between the hydroxyl proton and the phenyl protons and the methyl protons, respectively, whereas in the case of 9d and 9g no connectivity was observed. Moreover, oximes 9 and 10 are also characterized by 1H NMR spectra with different features. The chemical shift of the methylenic proton appears at higher value for (E)-oximes 9 (9b: δ  6.81 ppm; 9d: δ  = 6.82 ppm; 9g: δ = 6.39 ppm) than for the corresponding (Z) oximes 10 (10b: δ = 5.74 ppm; 10d: δ = 5.77 ppm; 10g: δ = 5.41 ppm).

The synthesis of two isomeric oximes from the reaction of arylnitrosoethylenes with pyrrole and dipyrromethanes has been previously observed [62]. The process was rationalized considering the conjugate addition of the heterocycle to the nitrosoalkene, at the s-cis or s-trans conformation, followed by rearomatization of the pyrrole unit leading to (E)- and (Z)-oxime, respectively. Thus, the synthesis of the BIM oximes via 1,4-conjugate addition of indole to the nitrosoelkene cannot be ruled out.

The use of water as solvent in Diels- Alder reactions has been shown to be advantageous, not only in environmental terms but also inducing critical improvements in reaction times, yields and selectivity [51,63]. We observed that carrying out the synthesis of bis(indolyl)methanes in water using dichloromethane as co-solvent is a valuable alternative to the use of dichloromethane as the only solvent. Generally the yields were better or comparable to those obtained in dichloromethane and reaction time significantly shorter (the reaction time was reduced from 36 h to 3 h). Clearly the efficiency of the reaction, using H2O/CH2Cl2 system, amongst the nitrosoalkenes bearing halogenated aryl substituents increases in the order F > Cl > Br > H the order of electron withdrawing ability and consequently the order of the expected effectiveness for an inverse electron demand Diels-Alder reaction (entries 2, 5, 7 and 9). However, the isolated yields from the reaction carried out in CH2Cl2 do not reflect the expected reactivity, which can be explained considering differences in the efficiency of the purification process.

The cytotoxicity of compounds 9a, 9e and 9d was evaluated in different tumorl cell lines, namely HepG2 (hepatocellular carcinoma), MDA-MB-468 (human breast carcinoma), RAW 264.7 (murine leukemic monocyte macrophages), THP1 (human acute monocytic leukaemia), U937 (human leukaemic monocytic lymphoma) and EL4 cells (murine T-lymphoma). The compounds’ selectivity towards tumoural cells was assessed determining their cytotoxicity with respect to two non-tumoural derived cell lines S17 (murine bone marrow) and N9 cells (murine microglial). Results of the half maximal concentrations (IC50) are shown in Table 2 together with the toxicity of etoposide, a known antitumoural drug. Compound 9e was considerably less cytotoxic on tumor cell lines than the other two compounds, with IC50 values ranging from 35.7 (HepG2) to 124 mM (THP1) and was not selective. Compounds 9a and 9d, however, were considerably cytotoxic to all cells tested, with IC50 values ranging from 1.62 (THP1) to 23.9 mM (RAW) and from 10.7 (MDA) to 34.1 mM (U937), respectively. Compound 9a was particularly active against non-adherent cell lines with IC50 values ranging from 1.62 in THP1 to 1.65 mM in EL4.

Some conclusions regarding structure activity relationships can be redrawn based on the biological evaluation of these bis(indolyl)methanes. There is a dramatic difference in anticancer activitybetweenN-unsubstituted bis(indolyl)methanes 9a and the Nmethyl substituted derivative 9e, the latter characterized by high IC50 values. On the other hand, the significantly lower IC50 values observed for 9a for non-adherent cell lines in comparisonwith the ones obtained for 9d demonstrates that the presence of the bromo substituent leads to higher cytotoxic activity.

The observed high cytotoxicity of compound 9a against THP1, EL4 and U937 cell lines led us to extend the study to BIMs 9c, 9g and 10g (Table 3). Compound 9c, bearing a 4-fluorophenyl substituent, showed moderate anti-cancer activity which reinforces the observation that the 4-bromophenyl group is crucial to ensure low IC50 values. On the other hand, alkyl oximes 9g and 10g were even less cytotoxic against THP1, EL4 and U937 cell lines. None of these compounds were selective towards the tumor cell lines (selectivity index calculated for non-tumour cell line S17). In addition to having displayed higher toxicity towards the nontumor cell lines than all the studied compounds, compound 9a demonstrated the highest selectivity indexes: 9.86-14.2. Further studies using 9a as scaffold in the development of anti-tumoural drugs for leukaemia and lymphoma is worth pursuing since it presents lower IC50 and higher selectivity than etoposide.

Conclusions

The reliable preparation of a variety of unknown BIMs bearing different oxime substituents at the methylene bridge was presented. This strategy, supported on the robust and proved methodology of Diels-Alder cyclo addition reactions of electrophilic nitrosoalkenes with electron rich indoles, may pave the way for the synthesis of a vast library of new compounds.

Table 1 Preparation of bis(indolyl)methane oxime

Scheme 1. Selected biological active bis(indolyl)methanes.

Scheme 2. Common methods for BIMs’ preparation [27e44].

Scheme 3. Synthetic strategy towards BIM oximes.

Synthesis of a new bis(indolyl)methane that inhibits growth and induces apoptosis in human prostate cancer cells

Marrelli M., et al.
Natural product research 08/2013; 27(21).
http://dx.doi.org:/10.1080/14786419.2013.824440

The synthesis and the antiproliferative activity against the human breast MCF-7, SkBr3 and the prostate LNCaP cancer cell lines of a series of bis(indolyl)methane derivatives are reported. The synthesis of new compounds was first accomplished by the reaction of different indoles with trimethoxyacetophenone in the presence of catalytic amounts of hydrochloric acid. A second procedure involving the use of oxalic acid dihydrate [(CO2H)2·2H2O] and N-cetyl-N,N,N-trimethylammonium bromide in water was carried out and led to better yields. Compound 5b significantly reduced LNCaP prostate cancer cell viability in a dose-dependent manner, with an IC50 of 0.64 ± 0.09 μM. To determine whether the growth inhibition was associated with the induction of apoptosis, treated cells were stained using DAPI. LNCaP cells treated with 1 μM of 5b showed the morphological changes characteristic of apoptosis after 24 h of incubation.

11.1.5 Synthesis and Biological Evaluation of New 1,3-Thiazolidine-4-one Derivatives of 2-(4-Isobutylphenyl)propionic Acid molecules

Vasincu IM1Apotrosoaei M2Panzariu AT3Buron F4Routier S5Profire L6
Molecules. 2014 Sep 18; 19(9):15005-25
http://dx.doi.org/10.3390/molecules190915005

New thiazolidine-4-one derivatives of 2-(4-isobutylphenyl)propionic acid (ibuprofen) have been synthesized as potential anti-inflammatory drugs. The structure of the new compounds was proved using spectral methods (FR-IR, 1H-NMR, 13C-NMR, MS). The in vitro antioxidant potential of the synthesized compounds was evaluated according to the total antioxidant activity, the DPPH and ABTS radical scavenging assays. Reactive oxygen species (ROS) and free radicals are considered to be involved in many pathological events like diabetes mellitus, neurodegenerative diseases, cancer, infections and more recently, in inflammation. It is known that overproduction of free radicals may initiate and amplify the inflammatory process via upregulation of genes involved in the production of proinflammatory cytokines and adhesion molecules. The chemical modulation of acyl hydrazones of ibuprofen 3a–l through cyclization to the corresponding thiazolidine-4-ones 4a–n led to increased antioxidant potential, as all thiazolidine-4-ones were more active than their parent acyl hydrazones and also ibuprofen. The most active compounds are the thiazolidine-4-ones 4e, m, which showed the highest DPPH radical scavenging ability, their activity being comparable with vitamin E.

In order to improve the anti-inflammatory effect and safety profile of representative NSAIDs, one research strategy is derivatization of the carboxylic acid group with various heterocyclic systems (oxazole, izoxazole, pyrazole, oxadiazole, thiazole, thiadiazole, triazole, etc.) [9,10]. In the past two decades there has been considerable interest in the role of reactive oxygen species (ROS) in inflammation [11]. ROS mediate the oxidative degradation of cellular components and alteration of protease/antiprotease balance with damage to the corresponding tissue. In the early stages of the inflammatory process, ROS exert their actions through activation of nuclear factors, such as NFkB or AP-1, that induce the synthesis of cytokines. In later stages, endothelial cells are activated due to the synergy between free radicals and cytokines, promoting the synthesis of inflammatory mediators and adhesion of molecules. In the last step free radicals react with different cellular components (trypsin, collagen, LDL, DNA, lipids) inducing the death of cells [12,13].

The thiazolidine-4-one moiety is a heterocycle that has received more attention in the last years due its important biological properties [14]. Many effects have been found, including anti-inflammatory and analgesic [15], antitubercular [16], antimicrobial and antifungal [17], antiviral, especially as anti-HIV agents [18], anticancer, antioxidants [19], anticonvulsants [20] and antidiabetic activity [21]. In the present study, some new derivatives of ibuprofen that contain thiazolidine-4-one scaffolds were synthesized in order to obtain compounds with double effect—antioxidant and anti-inflammatory properties. The structures of the compounds were assigned based on their spectral data (FT-IR, 1H-NMR, 13C-NMR, MS) and the compounds were screened for their in vitro antioxidant potential.

The 1,3-thiazolidine-4-one derivatives 4am were synthesized in several steps using the method summarized in Scheme 1 and Table 1. First 2-(4-isobutylphenyl)propionic acid (ibuprofen, 1) was reacted with thionyl chloride, followed by treatment with dry ethanol to get 2-(4-isobutylphenyl)propionic acid ethyl ester, which was turned in 2-(4-isobutylphenyl)propionic acid hydrazide (2) by reaction with 66% hydrazine hydrate [22]. The condensation of compound 2 with various aromatic aldehydes allowed the preparation of the corresponding hydrazone derivatives 3al in satisfactory yields. Finally, the hydrazone derivatives of ibuprofen upon reaction with mercaptoacetic acid led to the thiazolidine-4-one derivatives 4al in moderate to good yields. By reduction of compound 4g in presence of tin chloride and few drops of acetic acid in ethanol, the thiazolidine-4-one 4m was obtained in 90% yield. Acetylation of 4m with acetyl chloride gave thiazolidine-4-one 4n in moderate yield.

In the acyl hydrazone series most of the the tested compounds showed a radical scavenging ability comparable with ibuprofen (Table 4). The most active compounds were 3e and 3f which are about three times and two times more active than their parent compound, respectively. The scavenging ability of the acyl hydrazones was improved by cyclization to the corresponding thiazolidine-4-one derivatives, these compounds all being more active than ibuprofen, except for compound 4j which contains a CF3 group in the metaposition of phenyl ring (Table 5). The most active compounds were 4e and 4m which contain NO2 and NH2 groups in ortho and paraposition of the phenyl ring, respectively. For these compounds the radical scavenging ability (%) was 94.42 ± 0.43 and 94.88 ± 0.57, which means that the compounds are about 23 times more active than ibuprofen (4.15 ± 0.22). The activity of these compounds is comparable with that of vitamin E used as positive control. Important radical scavenging ability was also shown by compound 4b(81.31 ± 0.55), which contains a Cl group in the para position of the phenyl ring, the compound being 20 times more active than ibuprofen.

The acyl hydrazone derivatives showed an antioxidant activity comparable with ibuprofen. The most active compound in this series was 3h, with radical scavenging activity of 13.31 ± 0.81, which means that this compound is three times more active than ibuprofen (4.42 ± 0.18). In the thiazolidine-4-one series the most active compounds were 4b4e and 4k, which contain Cl(4), NO2(2) and CN(4), respectively, as substituents on the phenyl ring. These compounds, which showed a scavenging ability of around 50%, are 12 times more active than ibuprofen. In comparison with the corresponding acyl hydrazones 3b3e and 3k the thiazolidine-4-ones were 10 times (4b), seven times (4e) and 13 times (3k) more active. The improved antiradical activity of acyl hydrazones by cyclization to form thiazolidine-4-ones was also observed for compounds 3d3f and 3g. The most favorable influence was observed for acyl hydrazone 4g, which contains a NO2 in the para position of the phenyl ring. The corresponding thiazolidine-4-one (4g, 37.14 ± 1.10) is 22 times more active than 3g (1.67 ± 0.35). These data strongly support the favorable influence of the thiazolidine-4-one ring on the antioxidant potential of these compounds. The tested compounds were less active than vitamin E.

In this study new heterocyclic compounds that combine the thiazolidine-4-one structure with the arylpropionic acid one have been synthesized. The structure of the new compounds was proved using spectral methods (IR, 1H-NMR, 13C-NMR, MS). The compounds were evaluated for their antioxidant effects using in vitro assays: total antioxidant activity, DPPH and ABTS radical scavenging ability. All thiazolidin-4-one derivatives 4an showed improved antioxidant effects in comparison with the corresponding acyl hydrazones 3al and ibuprofen, the parent compound. The encouraging preliminary results illustrate the antioxidant potential of the synthesized compounds and motivate our next research focused on their anti-inflammatory effects in chronic and acute inflammation models.

11.1.6 Targeting pyruvate kinase M2 contributes to radiosensitivity of NSCLC cells

Meng MB1Wang HH2Guo WH3Wu ZQ2Zeng XL2Zaorsky NG4, et al.
Cancer Lett. 2015 Jan 28; 356(2 Pt B):985-93
http://dx.doi.org:/10.1016/j.canlet.2014.11.016

Aerobic glycolysis, a metabolic hallmark of cancer, is associated with radioresistance in non-small cell lung cancer (NSCLC). Pyruvate kinase M2 isoform (PKM2), a key regulator of glycolysis, is expressed exclusively in cancers. However, the impact of PKM2 silencing on the radiosensitivity of NSCLC has not been explored. Here, we show a plasmid of shRNA-PKM2 for expressing a short hairpin RNA targeting PKM2 (pshRNA-PKM2) and demonstrate that treatment with pshRNA-PKM2 effectively inhibits PKM2 expression in NSCLC cell lines and xenografts. Silencing of PKM2 expression enhanced ionizing radiation (IR)-induced apoptosis and autophagy in vitro and in vivo, accompanied by inhibiting AKT and PDK1 phosphorylation, but enhanced ERK and GSK3β phosphorylation. These results demonstrated that knockdown of PKM2 expression enhances the radiosensitivity of NSCLC cell lines and xenografts as well as may aid in the design of new therapies for the treatment of NSCLC.

Knockdown of PKM2 expression increases the sensitivity of NSCLC cells to radiotherapy in vitro

To examine PKM2 expressions levels in the normal lung epithelial cell and the NSCLC cell lines, we evaluated the expression levels of PKM2 in normal lung bronchial epithelial cell BEAS-2B and five NSCLC cell lines including A549, H460, H1299, H292, and H520 by Western blotting assays, and our results demonstrated that PKM2 expression was elevated in almost five NSCLC cell lines examined compared to autologous normal lung bronchial epithelial cell, although the expression levels fluctuated slightly depending on the different cell lines (Fig.1A). To test the role of PKM2 in the sensitivity of NSCLC to radiotherapy, we generated plasmids of pshRNA-PKM2 and control pshRNA-Con by inserting the DNA fragment for a pshRNA specifically targeting the PKM2 or control into the pGenesil2 vector. After demonstrating the authenticity, A549 and H460 cells were transfected with the plasmid for 48h and the levels of PKM2 expression were tested by Western blot assays. Obviously, transfection with control plasmid did not significantly modulate PKM2 expression; while transfection with pshRNA-PKM2 reduced the levels of PKM2 expression (Fig.1B and Appendix: Supplementary Fig.S1A). Quantitative analysis revealed that transfection with pshRNA-PKM2 significantly reduced PKM2 expressions as compared with that in the mock-treated and control pshRNA-Con plasmid-transfected cells, respectively (p<0.05, Fig.1C). Mock-treated and pshRNA-PKM2-trasnfected A549 and H460 cells were subjected to IR (4Gy), and 12 and 24h after IR, these cells, together with un-irradiated mock-treated, pshRNA-Con-transfected, and pshRNA-PKM2-trasnfected cells, were tested for cell viability by trypan blue staining. Knockdown of PKM2 reduced the percentage of A549 viable cells by 12.6–20% and IR treatment decreased the frequency of viable cells by 17.1–28.2%. However, the percentages of viable cells in the PKM2-silencing and irradiated cells were reduced by 27.7–48.7%, which were significantly lower than that in other groups (Fig.1D, p<0.05). Furthermore, it was consistent with the above results of A549 cells that knockdown of PKM2 significantly reduced the percentage of H460 viable cells (Appendix: Supplementary Fig.S1B). In addition, to further validate PKM2 silencing on their radiosensitivity,unirradiated control, mock-treated, and pshRNA-PKM2 transfected A549 cells were subjected to IR (0, 2, 4, 6, and 8Gy), and two weeks after IR, these cells were tested for the capacity for colony formation. The results showed that the numbers of colonies formed by pshRNA-PKM2 cells were significantly decreased compared with that of mock-treated and control cells; however, there was no significant change in mock-treated cells compared with control cells. These results suggested that pshRNA-PKM2 cells were more sensitive to IR than mock-treated and control cells (Fig.1E and F). Given that IR usually causes DNA double-strand breaks [28], we characterized the frequency of γ-H2AX nuclear foci positive cells by immunofluorescent assays. While IR treatment dramatically increased the frequency of γ-H2AX+ cells, the same dose of IR further significantly increased the percentages of γ-H2AX+ cells when combined with PKM2 silencing at 12 and 24h after IR, and there was a significant difference in γ-H2AX+ cells between these two groups at 12 and 24 h after IR (Fig. 1G and H, p < 0.05).

Fig. 1. The PKM2 expression levels in the normal lung epithelial cell and the NSCLC cell lines and knockdown of PKM2 expression enhance the radiosensitivity of A549 cells in vitro. The expression levels of PKM2 in normal lung bronchial epithelial cell BEAS-2B and five NSCLC cell lines including A549, H460, H1299, H292, and H520 were determined by Western blotting assay (A). A549 cells were transfected with pshRNA-PKM2 or pshRNA-Con plasmid for 48h, and the levels of PKM2 expression were determined by Western blot assays using a PKM2-specific antibody and β-actin as an internal control (B and C). Data are representative images or expressed as mean±SD of the relative levels of PKM2 to control β-actin in individual groups of cells from three separate experiments. # p

Knockdown of PKM2 enhances IR-induced apoptosis in NSCLC cells

Next, we tested the impact of PKM2-silencing on IR-induced cell death types. One day after IR, the apoptotic cells in the irradiatedmock-treated,pshRNA-PKM2-trasnfected cells, and one group of cells that had been pre-treated with 30μM Z-VAD for 1h prior to IR, together with mock-treated, unirradiated pshRNA-Contransfected, and pshRNA-PKM2-trasnfected groups of cells were characterized by TUNEL assays and/or FACS analysis (Fig.2A and C). In comparison with that in mock-treated and control plasmid transfected cells, the frequency of apoptotic cells in the PKM2 silencing or IR-treated cells increased moderately, while the percentages of apoptotic cells in the cells receiving combined treatment with IR and PKM2-silencing were significantly greater. However, the frequency of apoptotic cells in the Z-VAD-pretreated cells was partially reduced. Apparently, knockdown of PKM2 and IR induced apoptosis in NSCLC cells in vitro (Fig. 2B and D, and Appendix: Supplementary Fig.S1C).

Fig. 2. Knockdown of PKM2 expression enhances IR-induced apoptosis in A549 cells. A549 cells were transfected with, or without, pshRNA-Con or pshRNA-PKM2 for 48h and treated with, or without, Z-VAD for 1h. Subsequently, the cells were subjected to IR, and 24h later, the frequency of apoptotic cells was determined by TUNEL assays and FACS. (A and C) TUNEL and FACS analyses of apoptotic cells. (B and D) Quantitative analysis of the percentage of apoptotic cells. Data are representative images or expressed as mean%±SD of individual groups of cells from three independent experiments. * p

Knockdown of PKM2 enhances IR-induced autophagy in NSCLC cells

The cell autophagy is characterized by the formation of numerous autophagic vacuoles, autophagosome, in the cytoplasm and elevated levels of the microtubule-associated protein 1 light chain 3 (LC3)-II [29]. To test the impact of PKM2 silencing on IR-induced autophagy, the presence of autophagosome in mock-treated, pshRNACon-transfected, pshRNA-PKM2-transfected, IR-treated alone, IR + pshRNA-PKM2-transfected, and 1 mM 3-MA-pretreated IR + pshRNA-PKM2-transfected cells was characterized by electronic microphotography (EM). Intriguingly and importantly, numerous autophagosomes were detected in the IR + pshRNAPKM2-transfected cells, and only a few were detected in the sensitivity of the NSCLC cells to radiotherapy in vitro. It was noted that pshRNA-Con had almost no effect on A549 cells, therefore, some subsequently experiments did not set this group.

Fig. 3. Knockdown of PKM2 and IR induce A549 cell autophagy. A549 cells were transfected with, or without, pshRNA-Con or pshRNA-PKM2 for 48h and treated with, or without, 3-MA for 1h. Subsequently, the cells were subjected to IR, and 2h later, the presence of autophagic vacuoles and autolysosomes in A549 cells was determined by EM and the relative levels of LC3-I, LC3-II, AKT, ERK1/2, and control β-actin expression and AKT, ERK1/2, GSK3β, PDK1 phosphorylation were determined by Western blot assays using specific antibodies. Data are representative images and expressed as mean values of the relative levels of target protein to control in individual groups of cells from three separate experiments. The relative levels of target protein to control in mock-treated cells were designated as 1. (A) EM analysis of autophagic vacuoles and autophagosomes. Black arrows point to autophagic vacuoles and autophagosomes in the cytoplasma of A549 cells. (B) Western blot analysis of LC3-I and LC3-II expression. The values indicate the ratios of the relative levels of LC3-II to LC3-I in individual groups. (C) Western blotting analysis of individual signal events. The values indicate the relative levels of target protein to control β-actin in individual groups of cell

Fig. 4. The impact of 3-MA or/and V-ZAD on cell viability, colony formation, apoptosis and autophagy in A549 cells. A549 cells were transfected with, or without, pshRNACon or pshRNA-PKM2 for 48h and pre-treated with, or without, 3-MA or V-ZAD for 1h, respectively. Subsequently, the cells were subjected to IR. Twenty-four hours later and two weeks, the viability, apoptosis, and colony formation were determined. Two hours after treatment, autophagy and the relative levels of LC3-I and LC3-II expression in different groups of cells were determined. Data are representative images and expressed as mean%±SD of individual groups of cells from three separate experiments. (A) The percentages of viable cells. (B) The capacity of cell colony formation. (C) Quantitative analysis of apoptotic cells. (D) Western blot analysis of LC3-I and LC3-II expression. The values indicate the ratios of LC3-II to LC3-I in individual groups of cells. * p

Fig. 5. Treatment with pshRNA-PKM2 enhances the IR-inhibited growth of implanted tumors in mice. The nude mice were inoculated with A549 cells and when the tumor grew at 50mm3 in one dimension, the mice were randomized and treated with vehicle (PS), plasmid of pshRNA-Con or pshRNA-PKM2 alone or IR (4Gy×7f) alone or in combination with pshRNA-PKM2 and IR, respectively. The body weights and tumor growths of individual mice were monitored longitudinally. At the end of the in vivo experiment, the tumor tissues were dissected out and the frequency of apoptotic cells, the presence of autophagosomes and the expression of PKM2 were determined by TUNEL, EM and immunohistochemistry, respectively. Data are representative images or expressed as mean±SD of individual groups of mice (n=6 per group). (A) The body weights of mice. (B and C) The tumor growth curve of implanted tumors and the log-transformed tumor growth curve of implanted tumors in mice. (D) Quantitative analysis of the frequency of apoptotic cells.(E) EM analysis of autophagy. (F)The expression of PKM2.(G) Quantitative analysis of PKM2 expression.The cells with brown cytoplasma were considered as positive anti-PKM2 staining and the percentage of PKM2-positive cells was obtained by dividing the numbers of the PKM2-positive cells by the total number of cancer cells in the same field.

11.1.7 The tyrosine kinase inhibitor nilotinib has antineoplastic activity in prostate cancer cells but up-regulates the ERK survival signal—Implications for targeted therapies

Schneider M1Korzeniewski N2Merkle K2Schüler J, et al.
Urol Oncol. 2015 Feb; 33(2):72.e1-7
http://dx.doi.org:/10.1016/j.urolonc.2014.06.001

Background: Novel therapeutic options beyond hormone ablation and chemotherapy are urgently needed for patients with advanced prostate cancer. Tyrosine kinase inhibitors (TKIs) are an attractive option as advanced prostate cancers show a highly altered phosphotyrosine proteome. However, despite favorable initial clinical results, the combination of the TKI dasatinib with docetaxel did not result in improved patient survival for reasons that are not known in detail. Methods: The National Cancer Institute-Approved Oncology Drug Set II was used in a phenotypic drug screen to identify novel compounds with antineoplastic activity in prostate cancer cells. Validation experiments were carried out in vitro and in vivo. Results: We identified the TKI nilotinib as a novel compound with antineoplastic activity in hormone-refractory prostate cancer cells. However, further analyses revealed that treatment with nilotinib was associated with a significant up-regulation of the phospho-extracellular-signal-regulated kinases (ERK) survival signal. ERK blockade alone led to a significant antitumoral effect and enhanced the cytotoxicity of nilotinib when used in combination. Conclusions: Our findings underscore that TKIs, such as nilotinib, have antitumoral activity in prostate cancer cells but that survival signals, such as ERK up-regulation, may mitigate their effectiveness. ERK blockade alone or in combination with TKIs may represent a promising therapeutic strategy in advanced prostate cancer.

Identification of nilotinib as a novel antineoplastic compound in prostate cancer cells

Using the NCI-Approved Oncology Drug Panel II for a phenotypic drug screen of normal prostate epithelial cells and prostate cancer cell lines (Fig. 1) [7], we identified the TKI nilotinib as a positive hit in hormone-refractory DU-145 prostate cancer cells.

Fig. 1. Discovery of nilotinib as a novel antineoplastic agent in prostate cancer cells using a phenotypic drug screen. Overview of the drug screen procedure (see text for details).

Results were confirmed using annexin V staining, which showed a significant induction of apoptosis beginning at 24 hours (Fig. 2A). The IC50 of nilotinib against DU-145 cells was determined at 10 μM using an MTT cell viability assay (Fig. 2B). Immunoblot experiments confirmed an induction of apoptosis using PARP cleavage in DU-145 cells and in hormonerefractory PC-3 prostate cancer cells at this drug concentration (Fig. 2C). An onset of apoptosis at 24 hours was likewise confirmed using PARP cleavage at a nilotinib concentration of 10 μM(Fig. 2D). PWR-1E prostate epithelial cells and hormone-sensitive prostate LNCaP prostate cancer cells were not found to undergo enhanced apoptosis when treated with nilotinib (not shown).

Fig. 2. Antitumoral effects of nilotinib in prostate cancer cells: (A) flow cytometric analysis of DU-145 prostate cancer cells for annexin V to detect apoptotic cells after treatment with 10 μM of nilotinib for the indicated intervals; (B) cell viability (MTT) assay to determine the IC50 of nilotinib in DU-145 cells (24-h treatment); (C and D) immunoblot analysis of DU-145 and PC-3 prostate cancer cells for PARP cleavage (arrow) at nilotinib concentrations and time intervals as indicated. GAPDH is shown for protein loading; and (E) colony growth assay of DU-145 cells after drug treatment and washout as shown. Cells grown in 60-mm dishes were stained with crystal violet to visualize viable cells at the time points indicated. (Color version of figure is available online.

To further confirm the effect of nilotinib on prostate cancer cell growth, we performed a colony growth assay in which DU-145 cells were treated with nilotinib for 72 hours followed by a washout of the drug and continued culture for additional 9 days (Fig. 2E). We found that nilotinib induced significant cytotoxicity after 72 hours and that a minor regrowth of cancer cells did not occur until 6 to 9 days after the washout, which is comparable to other TKIs [8]. Next, we sought to identify the targets of nilotinib in DU-145 prostate cancer cells. Overall, 5 well-established targets, including ABL1, KIT, PDGFRA, DDR1, and NQO2, were analyzed for their role in the drug response. We found that protein expression of 3 of these targets (ABL1, KIT, and PDGFRA) was not detectable in DU-145 cells and that small interfering RNA–mediated knockdown of the remaining 2 targets, DDR1 and NQO2, did not result in apoptosis (not shown). Collectively, these results show a significant antitumoral activity of nilotinib in prostate cancer cells. However, this effect was associated with a relatively high IC50 and was independent of known nilotinib targets.

Nilotinib up-regulates the ERK survival signal in prostate cancer cells

To further investigate why relatively high concentrations of nilotinib were required to induce cytotoxicity, we analyzed 40,6-diamidino-2-phenylindole–stained DU-145 cells treated with 10 μM of nilotinib for 24 hours using fluorescence microscopy (Fig. 3A).

Fig. 3. Nilotinib up-regulates the ERK survival signal in prostate cancer cells. (A) Fluorescence microscopic analysis of DAPI-stained DU-145 cells. (B and C) Immunoblot analyses of DU-145 cells (B) or DU-145 cells in comparison with LNCaP and PC-3 cells (C) treated with nilotinib for the expression of phospho-ERK1/2 T202/Y204 and total ERK. Immunoblot for GAPDH is shown as a loading control. (D) Immunohistochemical staining of xenografted DU-145 cells after 21 days of treatment with 75 mg/kg/d of nilotinib for phospho-ERK1/2 T202/Y204 expression. It can be noted that tumors explanted from vehicle-treated mice showed mostly positivity at the tumor periphery, whereas tumors explanted from nilotinib-treated mice showed a more evenly distributed phospho-ERK immunostaining (left panels). Quantification of phospho-ERK–positive DU-145 xenografts explanted after 21 days of treatment. Mean and standard errors of positive cells per high-power field (HPF; [1]40) from at least 3 tumors are given (right panel). (E) Immunoblot analysis of DU-145 cells treated with U0126 alone or in combination with nilotinib shows abrogation of phospho-ERK1/2 T202/Y204 expression by U0126. (F) Quantification of viable cells compared with that of controls using the MTT assay after treatment with U0126 (10 μM) or nilotinib (10 μM) or both and after either pretreatment (24 h) or simultaneous treatment (72 h). DAPI ¼ 40,6-diamidino-2-phenylindole. (Color version of figure is available online.)

We found that, despite the presence of apoptotic cells, there was also a population of actively dividing tumor cells in the presence of nilotinib as well as a population of viable but multinucleated cells (Fig. 3A). We interpreted these results as evidence that a subset of tumor cells has the ability to resist TKI treatment. To reconcile these results, we analyzed the activation of ERK1/2, which is known to function as a prosurvival signal in TKI-treated tumor cells [9,10]. We detected a robust overexpression of phospho-ERK1/2 T202/Y204 in nilotinib-treated DU-145 cells (Fig. 3B). An up-regulation of phospho-ERK1/2 T202/Y204 was also detectable in nilotinib-treated LNCaP cells, albeit at a lower level, and was not found in PC-3 cells (Fig. 3C). To further corroborate the evidence of phospho-ERK upregulation in vivo, we analyzed explanted DU-145 xenografts from a representative experiment in which nilotinib was used at a 75-mg/kg/d concentration. This initial dosage was based on published animal experiments [11] but yielded no or incomplete tumor control in our experiment (data not shown).

In vivo antitumoral activity of nilotinib and ERK blockade

Our results raised 2 important questions First, can a higher dose of nilotinib induce improved tumor control, and second, is a combination of nilotinib with the MEK inhibitor U0126 to block ERK activity superior to nilotinib alone?

Fig. 4. In vivo antitumoral activity of nilotinib and ERK blockade in prostate cancer cells: (A) tumor growth curves of DU-145 xenografts in NMRI-nude mice and (B) analysis of tumor volumes on day 21. Asterisks indicate statistical significance (**P r 0.01 and ***P r 0.001). (Color version of figure is available online.)

11.1.8 PAF and EZH2 Induce Wnt.β-Catenin Signaling Hyperactivation

Jung HY1Jun SLee MKim HCWang XJi HMcCrea PDPark JI
Mol Cell. 2013 Oct 24; 52(2):193-205
http://dx.doi.org/10.1016%2Fj.molcel.2013.08.028

Fine-control of Wnt signaling is essential for various cellular and developmental decision making processes. However, deregulation of Wnt signaling leads to pathological consequences including cancer. Here, we identify a novel function of PAF, a component of translesion DNA synthesis, in modulating Wnt signaling. PAF is specifically overexpressed in colon cancer cells and intestinal stem cells, and required for colon cancer cell proliferation. In Xenopus laevis, ventrovegetal expression of PAF hyperactivates Wnt signaling, developing secondary axis with β-catenin target gene upregulation. Upon Wnt signaling activation, PAF is dissociated from PCNA, and directly binds to β-catenin. Then, PAF recruits EZH2 to β-catenin transcriptional complex, and specifically enhances Wnt target gene transactivation, independently of EZH2’s methyltransferase activity. In mouse, conditional expression of PAF induces intestinal neoplasia via Wnt signaling hyperactivation. Our studies reveal an unexpected role of PAF in regulating Wnt signaling, and propose a novel regulatory mechanism of Wnt signaling during tumorigenesis. Fine-control of Wnt signaling is essential for various cellular and developmental decision making processes. However, deregulation of Wnt signaling leads to pathological consequences including cancer. Here, we identify a novel function of PAF, a component of translesion DNA synthesis, in modulating Wnt signaling. PAF is specifically overexpressed in colon cancer cells and intestinal stem cells, and required for colon cancer cell proliferation. In Xenopus laevis, ventrovegetal expression of PAF hyperactivates Wnt signaling, developing secondary axis with β-catenin target gene upregulation. Upon Wnt signaling activation, PAF is dissociated from PCNA, and directly binds to β-catenin. Then, PAF recruits EZH2 to β-catenin transcriptional complex, and specifically enhances Wnt target gene transactivation, independently of EZH2’s methyltransferase activity. In mouse, conditional expression of PAF induces intestinal neoplasia via Wnt signaling hyperactivation. Our studies reveal an unexpected role of PAF in regulating Wnt signaling, and propose a novel regulatory mechanism of Wnt signaling during tumorigenesis.

Keywords: Wnt, β-catenin, PAF, KIAA0101, EZH2

Strict regulation of stem cell proliferation and differentiation is required for mammalian tissue homeostasis, and its repair in the setting of tissue damage. These processes are precisely orchestrated by various developmental signaling pathways, with dysregulation contributing to disease and genetic disorders, including cancer (Beachy et al., 2004). Cancer is initiated by the inactivation of tumor suppressor genes and activation of oncogenes. For instance, colon cancer cells harbor genetic mutations in Wnt/β-catenin pathway constituents such as adenomatous polyposis coli (APC), Axin, and β-catenin (Polakis, 2007). In mouse models, inactivation of APC or activation of β-catenin results in the development of intestinal hyperplasia and adenocarcinoma (Moser et al., 1990), indicating that hyperactivation of Wnt signaling promotes intestinal tumorigenesis.

In canonical Wnt signaling, Wnt ligand induces stabilization of β-catenin protein via inhibition of the protein destruction complex (glycogen synthase kinase 3, APC, casein kinase I, and Axin). Then, activated β-catenin is translocated into the nucleus and binds to its nuclear interacting partners, TCF/LEF. Finally, β-catenin-TCF/LEF transactivates the expression of its target genes (Clevers and Nusse, 2012).

Although various Wnt/β-catenin modulators have been identified (Wnt homepage; wnt.stanford.edu), the pathological relevance of these modulators to tumorigenesis remains elusive. Also, many reports have suggested that mutation-driven Wnt signaling activation can be enhanced further (Goentoro and Kirschner, 2009He et al., 2005Suzuki et al., 2004Vermeulen et al., 2010), which implies the presence of an additional layer of Wnt-signaling regulation in cancer beyond genetic mutations in APC or β-catenin. Here, we unraveled a novel function of the DNA repair gene, PAF (PCNA-associated factor) /KIAA0101). PAF was shown to be involved in translesion DNA synthesis (TLS), an error-prone DNA repair process that permits DNA replication machinery to replicate DNA lesions with specialized translesion DNA polymerase (Emanuele et al., 2011Povlsen et al., 2012Sale et al., 2012). Our comprehensive approaches uncover that cancer-specifically expressed PAF hyperactivates Wnt/β-catenin signaling and induces intestinal tumorigenesis.

Mitogenic role of PAF via Wnt signaling

To identify colon cancer-specific Wnt signaling regulators, we analyzed multiple sets of human colon cancer tissue samples using the publicly available database (www.oncomine.org), and selected genes that are highly expressed in colon cancer cells (fold change > 2; P < 0.0001; top 10% ranked). Among several genes, we investigated the biological role of PAF, based on its significant overexpression in human colon adenocarcinoma with correlated expression of Axin2, a well-established specific target gene of β-catenin (Jho et al., 2002Lustig et al., 2002)(Figure 1A). To validate our in silico analysis, we performed immunostaining of colon cancer tissue microarray, and confirmed that PAF was highly expressed in colon cancer cells, whereas its expression was barely detectable in normal intestine (Figure 1B). Consistently, PAF was strongly expressed and mainly localized in the nucleus of colon cancer cell lines (Figure 1C). Additionally, we found that PAF was not expressed in non-transformed cells such as NIH3T3, mouse embryonic fibroblasts, and mammary epithelial cells (data not shown). Next, to assess the relevance of PAF upregulation in colon cancer cell proliferation, we depleted endogenous PAF using short hairpin RNAs (shRNAs) in these cell lines. Intriguingly, PAF knockdown (sh-PAF) inhibited colon cancer cell proliferation (Figures 1D and 1E). Given that PAF was shown to interact with PCNA via PIP box (Yu et al., 2001), we also examined whether PAF-PCNA interaction is required for mitogenic effects of PAF. In reconstitution experiments, sh-PAF-induced cell growth inhibition was rescued by ectopic expression of both shRNA non-targetable wild-type PAF (nt-PAF) and PIP mutant PAF (mutPIP-PAF) (Figure 1F), indicating that the PAF-PCNA interaction is not necessary for PAF-mediated colon cancer cell proliferation. Interestingly, PAF knockdown downregulated cell proliferation–related genes (Cyclin D1 and c-Myc) (Figure 1G). Given that Cyclin D1 and c-Myc are β-catenin direct target genes (He et al., 1998Tetsu and McCormick, 1999), PAF likely participates in regulating Wnt/β-catenin signaling. Interestingly, PAF depletion-induced downregulation of Cyclin D1 andc-Myc was only observed in SW620 colon cancer cells, but not in Panc-1 and MDA-MB-231 cells (Figure 1G), indicating the specific effects of PAF on Cyclin D1 and c-Myc expression in colon cancer cells. We also assessed the effects of PAF knockdown on Axin2. Indeed, PAF knockdown suppressed Axin2transcription in colon cancer cells (Figure 1H). Moreover, as nt-PAF did, β-catenin ectopic expression reverted sh-PAF–induced cell growth arrest (Figure 1I), implying that PAF might be functionally associated with Wnt/β-catenin. We also examined whether other mitogenic signaling pathways mediate PAF’s mitogenic role. Of note, except HT29, other colon cancer cell lines (SW620, HCT116, HCC2998, and HCT15) harbor oncogenic mutations in K-Ras gene. Nonetheless, PAF depletion induced the suppression of cell growth on all five colon cancer cells (Figure 1D), indicating that PAF’s mitogenic function is independent of Ras/MAPK signaling activation. Additionally, overexpression of wild-type Akt or constitutively active form of Akt (myristoylated form of Akt [Myr-Akt]) did not rescue sh-PAF-induced inhibition of cell proliferation (Figure 1I). Moreover, β-catenin activation did not revert cell proliferation suppression resulted from MAPK or PI3K inhibition (Figure 1J), indicating that β-catenin-mediated mitogenic function is independent of MAPK and PI3K signaling pathways. These results suggest that PAF contributes to colon cancer cell proliferation, possibly via Wnt/β-catenin signaling.

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Figure 1 Mitogenic role of PAF in colon cancer cells

PAF positively modulates Wnt signaling

Given that many cancers develop as a result of deregulation of developmental signalings (Beachy et al., 2004), analyzing PAF expression during development may provide insights into the mechanisms of PAF-mediated signaling regulation. Whole mount immunostaining of mouse embryos, showed that PAF was specifically enriched in the apical ectodermal ridge (AER) of the limb bud, midbrain, hindbrain, and somites (Figure 2A and data not shown). During limb development, AER induction is specifically coordinated by active Wnt signaling (Figure 2B)(Kengaku et al., 1998). Using, Axin2-LacZ, a β-catenin reporter (Lustig et al., 2002), mouse embryos, we confirmed the specific activation of Wnt signaling in AER (Figure 2C). Intriguingly, Wnt signaling activity as exhibited in the AER, overlapped with the pattern of PAF expression (Figures 2A and 2C). Given that (1) Wnt signaling is deregulated in most colon cancer, (2) PAF is highly overexpressed in colon cancer cells, (3) PAF is required for colon cancer cell proliferation (Figure 1D), and (4) PAF is enriched in AER where Wnt signaling is active (Figure 2A), we hypothesized that PAF modulates the Wnt signaling pathway. To test this, we first examined the impact of PAF on β-catenin transcriptional activity using TOPFLASH reporter assays. In HeLa cells, PAF knockdown decreased β-catenin reporter activation by 6-bromoindirubin-3′-oxime, a GSK3 inhibitor (Figure 2D). Similarly, Wnt3A-induced transcriptional activation of Axin2 was also inhibited by PAF depletion (Figure 2E). These data suggest that PAF might be required for Wnt target gene expression.

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Figure 2 Activation of Wnt signaling by PAF

To gain better insight of PAF’s role in Wnt signaling regulation, we utilized Xenopus laevis embryos for axis duplication assays (Funayama et al., 1995), as previously performed (Park et al., 2009). Because of Wnt signaling’s pivotal role in vertebrate anterior-posterior axis development, the effects of Xenopus PAF (xPAF) on Wnt signaling can be monitored and quantified on the basis of secondary axis formation following injection of in vitro transcribed mRNAs. xβ-catenin mRNA, titrated to a subphenotypic level when expressed in isolation, was co-injected with xPAF mRNA into ventrovegetal blastomeres. Unlike the controls (β-catenin and β-galactosidase mRNA), the experimental group (β-catenin and xPAF mRNA) displayed axis-duplications (Figures 2F-H). Of note, the ventrovegetal injection of xPAF mRNA alone failed to induce secondary axes (data not shown), showing that PAF hyperactivates Wnt/β-catenin signaling only in the presence of active β-catenin. Consistent with the results of axis duplication assays, qRT-PCR assays showed that xPAF expression upregulated expression of Siamois and Xnr3, β-catenin targets in frogs (Figure 2I). Furthermore, we examined the specificity of PAF on Wnt/β-catenin signaling activity, using various luciferase assays. Ectopic expression of PAF hyperactivates Wnt3A or LiCl, a GSK3 inhibitor, -induced activation of β-catenin target gene reporter activity (MegaTOPFLASH, Siamoisc-Myc, and Cyclin D1). Of note, BMP/Smad pathway also plays an essential role in the developing limb AER (Ahn et al., 2001). However, PAF knockdown or overexpression did not affect BMP/Smad or FoxO signalings, respectively, (Figure 2J) indicating the specificity of PAF in regulating Wnt signaling. These results suggest that PAF positively modulates Wnt/β-catenin signaling in vitro and in vivo.

PAF-EZH2-β-catenin transcriptional complex formation

Next, we investigated the molecular mechanism underlying PAF hyperactivation of Wnt signaling. Given that stabilization of β-catenin protein is a key process in transducing Wnt signaling, we asked whether PAF affects β-catenin protein level. However, we found that the level of β-catenin protein was not altered by PAF knockdown or overexpression (Figures 2E and ​and3A),3A), leading us to test whether PAF controls the β-catenin/TCF transcriptional complex activity. Owing to the nuclear specific localization of PAF in colon cancer cells (Figure 1C), we tested whether PAF interacts with β-catenin transcriptional complex. Using a glutathione S-transferase (GST) pull-down assay, we found that PAF bound to β-catenin and TCF proteins (Figure 3B). Also, endogenous PAF interacted with β-catenin and TCF3 in SW620 cells that display constitutive hyperactivation of Wnt signaling by APC mutation (Figure 3C). Moreover, binding domain mapping assays showed that the Armadillo repeat domain of β-catenin was essential for its interaction with PAF (Figure 3D). Although PAF is a cell cycle-regulated anaphase-promoting complex substrate (Emanuele et al., 2011), PAF-β-catenin interaction was not affected (Figure S1). These data suggest that PAF directly binds to β-catenin transcriptional complex and this interaction is independent of cell cycle. Next, due to interaction of PAF with β-catenin and TCF, we tested whether PAF is also associated with Wnt/β-catenin target genes. First, we analyzed the subnuclear localization of PAF by chromatin fractionation. We found that PAF was only detected in the chromatin fraction of HCT116 cells (Figure 3E). Additionally, chromatin immunoprecipitation (ChIP) assays showed that both ectopically expressed and endogenous PAF occupied the TCF-binding element (TBE)-containing proximal promoter of the β-catenin targets (c-Myc and Cyclin D1) in HCT116 cells (Figures 3F and 3G). These data show that PAF is specifically associated with the promoters of Wnt/β-catenin target genes.

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Figure 3 PAF-EZH2-β-catenin transcriptional complex at target gene promoters

In intestine, Wnt/β-catenin signaling constitutively activates intestinal stem cells (ISCs) to give rise to progenitor cells, which replenishes intestinal epithelium (Figure 3H). Given the involvement of PAF on Wnt/β-catenin signaling regulation (Figure 2), we analyzed the spatial expression of PAF in intestinal epithelium. Immunostaining showed that PAF was specifically expressed in B lymphoma Mo-MLV insertion region 1 homolog (Bmi1) positive intestinal stem cells (ISCs)(Figures 3I and 3J). Bmi1 and its associated components in Polycomb-repressive complex 1 (PRC1) and 2 (PRC2) are shown to epigenetically regulate gene expression (Sparmann and van Lohuizen, 2006). Due to (1) specific association of PAF with TBEs of β-catenin target promoters (Figures 3F and 3G) and (2) co-localization with Bmi1 positive ISCs (Figure 3J), we asked whether PAF is associated with components of PRC1 and PRC2, using co-immunoprecipitation (co-IP) assays. Intriguingly, PAF interacted with both Bmi1 and enhancer of zeste homolog 2 (EZH2) in SW620 cells (Figure 3K), which led us to test whether either Bmi1 or EZH2 is functionally associated with PAF-mediated Wnt signaling hyperactivation. To do this, we assessed the effects of Bmi1 and EZH2 on β-catenin transcriptional activity, using β-catenin reporter assays. We observed that ectopic expression of EZH2 upregulated β-catenin transcriptional activity, but Bmi1 overexpression did not (data not shown), implying that EZH2 might be associated with Wnt signaling activation. Binding domain mapping analysis showed that EZH2 bound to PAF via the middle region of EZH2 including the CXC cysteine-rich domain (Figure 3L). In conjunction with the Bmi1-containing PRC1, EZH2-containing PRC2 catalyzes histone H3 lysine 27 trimethylation (H3K27me3) via histone methyltransferase domain. Despite the crucial role of EZH2 in H3K27me3-meidated gene regulation, we found that other core components of PRC2, EED, and Suz12 were not associated with PAF (Figure 3K). Moreover, although EZH2 overexpression in cancer induces PRC4 formation in association with the NAD+-dependent histone deacetylase Sirt1 (Kuzmichev et al., 2005), the PAF-EZH2 complex did not contain Sirt1 (Figure 3K). These data indicate that PAF-EZH2 complex is distinct from the conventional PRCs in cancer cells. Also, we questioned whether PCNA is required for PAF’s interaction with either PAF or β-catenin. Interestingly, β-catenin-PAF and EZH2-PAF complexes existed only in PCNA-free fractions (Figure 3M, compare lanes 1 and 2), which is consistent with PCNA-independent mitogenic role of PAF in colon cancer cell proliferation (Figure 1I). Due to exclusive interaction of PAF with either PCNA or β-catenin, we asked whether Wnt signaling activation affects either PAF-β-catenin or PAF-PCNA interaction. Co-IP assays showed that, in HeLa cells, PAF-β-catenin interaction was only detected upon LiCl treatment, while PAF-EZH2 interaction remained constant. Moreover, PAF-PCNA association was decreased by LiCl or Wnt3A treatment (Figures 3N and 3O, compare lanes 3 and 4). These data suggest that Wnt signaling activation is required for PAF-β-catenin interaction. Due to absence of endogenous Wnt signaling activity in HeLa cells, we also assessed the effects of active Wnt/β-catenin signaling on PAF-PCNA binding in colon cancer cell lines that exhibit hyperactivation of Wnt signaling by genetic mutations in APC or β-catenin alleles. Surprisingly, PAF-PCNA interaction was barely detectable in colon cancer cell lines, whereas 293T and HeLa cells displayed strong PAF-PCNA association (Figure 3P), implying that active β-catenin may sequester PAF from PCNA. In binding domain mapping analysis, we also found that N-terminal and PIP regions are required for β-catenin interaction (Figure S2), suggesting that β-catenin competes with PCNA for PAF interaction. These results suggest that, upon Wnt signaling activation, PAF is conditionally associated with β-catenin transcriptional complex.

PAF activates β-catenin target genes by recruiting EZH2 to promoters

Previous studies showed that EZH2 interacts with β-catenin (Li et al., 2009Shi et al., 2007). Also, we found that PAF is physically associated with EZH2, independently of PRC2 complex (Figure 3). These evidences prompted us to ask whether EZH2 mediates PAF-induced Wnt signaling hyperactivation. Given PAF-EZH2-β-catenin complex formation, we tested whether EZH2 is also associated with the promoters of β-catenin target genes. Intriguingly, PAF, EZH2, and β-catenin steadily co-occupied the promoters of c-Myc,Cyclin D1, and Axin2 in HCT116 cells carrying β-catenin mutation, whereas PCNA, EED, and Suz12 did not (Figure 4A), which recapitulates PRC2 complex-independent association of EZH2 with PAF (see Figures 3K and 3N). Next, we asked whether PAF, EZH2, and β-catenin are recruited to β-catenin target gene promoter upon Wnt signaling activation, as PAF-β-catenin interaction was dependent of Wnt signaling activation (Figure 3N). In HeLa cells, we found that PAF, EZH2, and β-catenin conditionally bound to TBEs in the c-Myc and Axin2 promoters, only upon LiCl treatment (Figure 4B), indicating that Wnt signaling activation is a prerequisite for PAF-β-catenin-EZH2’s promoter association. To further confirm the specificity of PAF-EZH2-β-catenin’s recruitment to β-catenin target promoters, we performed ChIP promoter scanning of 10 kb of the c-Myc promoter, and found that PAF, EZH2, and β-catenin specifically co-occupied the proximal promoter containing TBEs of the c-Myc gene (at -1037 and -459 bp) (He et al., 1998) in HCT116 cells (Figure 4C). Also, the analysis of EZH2 ChIP-sequencing data from mouse embryonic stem cells showed that EZH2 was specifically enriched in the proximal promoters of β-catenin targets (Lef1Lgr5c-Myc, and Axin2) (Figure 4D).

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Figure 4 PAF promotes EZH2-β-catenin interaction

Next, we asked whether EZH2 promoter recruitment is necessary for activation of β-catenin target gene transcription. Previously, depletion of EZH2 was shown to inhibit c-Myc expression in DLD-1 colon cancer cells (Fussbroich et al., 2011). Consistently, EZH2 knockdown downregulated β-catenin target genes, Axin2and Cyclin D1 in HCT116 cells (Figure 4E), and decreased LiCl-induced β-catenin reporter activation (Figure 4F), suggesting that EZH2 is required for PAF-mediated Wnt target gene hyperactivation. These results are also supported by previous finding that EZH2 enhances β-catenin transcriptional activity by connecting β-catenin with the Med1/RNA polymerase II (Pol II) complex (Shi et al., 2007). Indeed, Med1/TRAAP220 and Pol II conditionally binds to c-Myc and Axin2 promoters in LiCl-treated HeLa cells (Figure 4G). Given that PRC2-indepednent interaction between EZH2 and PAF (Figures 3K and 3N), we asked whether EZH2’s histone methyltransferase activity is dispensable in β-catenin regulation. We utilized an EZH2 point mutant (F681I) that disrupts the contact between the EZH2 hydrophobic pocket and histone lysine residue H3K27 (Joshi et al., 2008). Ectopic expression of either EZH2 or EZH2-F681I enhanced β-catenin reporter activity (Figure 4H). Also, PAF knockdown did not change the H3K27 methylation status (H3K27me3) of proximal promoters of c-MycAxin2Cyclin D1, and DCC in HCT116 cells (Figure 4I). These results indicate a methyltransferase-independent role of EZH2 in transactivating β-catenin targets.

Due to PAF’s (1) small size (111 amino acids, one α-helix), (2) lack of a specific catalytic domain, and (3) binding to both β-catenin and EZH2, PAF may facilitate the interaction between EZH2 and β-catenin through recruiting EZH2 to the promoter. We tested this using ChIP assays for EZH2 in the setting of PAF depletion. Indeed, PAF-depleted HCT116 cells displayed decreased EZH2-association at the c-Myc promoter (Figure 4J), suggesting that PAF assists or is needed to recruit EZH2 to β-catenin transcriptional complex. Also, β-catenin knockdown decreased recruitment of PAF and EZH2 to promoters (Figure 4K), showing that PAF and EZH2 occupy target promoters via β-catenin. We then asked whether PAF promotes β-catenin-EZH2 binding. In vitro binding assays showed that the addition of GST-PAF protein increased EZH2-β-catenin association (Figure 4L). Moreover, ectopic expression of PAF promoted the EZH2-β-catenin interaction in HeLa cells treated with LiCl (Figure 4M). Additionally, we tested whether Wnt signaling-induced post-translational modification of either β-catenin or PAF is required for EZH2 interaction. However, in GST pull-down assays, we found that bacterially expressed either GST-β-catenin or –PAF bound to EZH2 (Figure S3). Due to the lack of post-translational modification in GST protein expression system, these data indicate that post-translation modification of either β-catenin or PAF is not necessary for EZH2 interaction. Together, these results suggest that PAF acts as a molecular adaptor to facilitate EZH2-β-catenin complex, and subsequently enhances the transcriptional activity of the β-catenin transcriptional complex at Wnt target promoters (Figure 4N).

Intestinal tumorigenesis following PAF conditional expression

Having determined that PAF is overexpressed in colon cancer cells and hyperactivates Wnt/β-catenin signaling, we aimed to determine whether mimicking PAF overexpression drives intestinal tumorigenesis, using genetically engineered mouse models. To conditionally express PAF, we generated doxycycline (doxy)-inducible PAF transgenic mice (TetO-PAF-IRES-emGFP [iPAF]). For intestine-specific expression of PAF, we used iPAF:Villin-Cre:Rosa26-LSL-rtTA mouse strains. Villin-Cre is specifically expressed in intestinal epithelial cells (IECs), including ISCs and progenitor cells. Cre removes a floxed stop cassette (loxP-STOP-loxP [LSL]) from the Rosa26 allele and induces rtTA expression. Upon doxy treatment, rtTA drives the transcriptional activation of the tetracycline-responsive element promoter, resulting in conditional transactivation of PAF selectively in IECs. We also utilized the Rosa26-rtTA strain for ubiquitous expression of PAF (Figure 5A and Figure S4). First, we examined the effects of PAF induction on IEC proliferation using a crypt organoid culture system (Figure S5A). Intriguingly, PAF conditional expression (2 weeks) induced expansion of the crypt organoids (Figures 5B and 5C), which recapitulates the mitogenic function of PAF (Figure 1). In mouse, IEC-specific PAF expression (iPAF:Villin-Cre:Rosa26-LSL-rtTA; 2 months) developed adenoma in both small intestine and colon (Figure 5D). Also, microscopic analysis using hematoxylin and eosin (H&E) staining showed aberrant IEC growth and crypt foci formation (Figures 5E and 5F), with disorganized epithelial cell arrangements (Figure S5B). Consistently, PAF-induced IEC hyperproliferation was manifested by increased Ki67 expression, a mitotic marker (Figure 5G). Importantly, these lesions exhibited the upregulation of CD44, a β-catenin target gene, whereas CD44 was expressed strictly in the crypts of normal intestine (Figure 5H). Next, we examined whether PAF directly hyperactivates Wnt/β-catenin in vivo using BAT-gal, a β-catenin reporter transgenic mouse carrying multiple TBEs followed by a LacZ reporter. To quantify the early effects of PAF on β-catenin activity, we treated mice with doxy for 1 week, and found that short-term induction of PAF increased β-catenin transcriptional activity as represented by enhanced X-gal staining (Figure 5I). Moreover, conditional PAF expression upregulated the β-catenin target genes, Axin2Lgr5CD44Cyclin D1, and c-Myc in crypt organoids (Figure 5J). Additionally, mice ubiquitously expressing PAF exhibited intestinal hypertrophy (Figure S5C), which is similar to that induced by R-Spondin1, a secreted Wnt agonist (Kim et al., 2005). These data strongly suggest that PAF expression is sufficient to initiate intestinal tumorigenesis via Wnt signaling hyperactivation.

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Figure 5 Induction of intestinal neoplasia by PAF expression

Herein we reveal the unexpected role of PAF in modulating Wnt/β-catenin signaling. PAF enhances the transcription of Wnt targets by recruiting EZH2 to the β-catenin transcriptional complex. This is similar to the mechanism by which Lgl/BCL9 binds to β-catenin and thereby recruits the PHD-finger protein Pygopus, to bridge the β-catenin/TCF complex to Med12 and Med13 (Carrera et al., 2008). Importantly, due to specific overexpression of PAF in cancer cells, our studies identified an additional layer of the regulatory mechanism of β-catenin target gene transactivation.

In cancer cells, the upregulation of EZH2 contributes to tumorigenesis through the epigenetic repression of various genes including tumor suppressor genes, Wnt antagonists, and DNA repair genes (Chang et al., 2011Cheng et al., 2011Kondo et al., 2008). Our results propose a noncanonical function of EZH2 in activating β-catenin target genes in conjunction with PAF. Consistently, recent study also suggests methyltransferase activity-independent function of EZH2 in gene activation (Xu et al., 2012). Moreover, this non-canonical role of EZH2 is supported by several lines of evidence: (a) EZH2 transactivates β-catenin target genes (Li et al., 2009Shi et al., 2007) (Figures 4E and 4F); (b) EZH2 overexpression in murine mammary epithelium induces ductal hyperplasia (Li et al., 2009), which phenocopies that in a ∆Nβ-catenin (constitutively active form of β-catenin) mouse model (Imbert et al., 2001); (c) EZH2 occupies β-catenin target promoters (Figures 4A-D); and (d) EZH2’s methyltransferase activity is dispensable for β-catenin target activation (Figures 4H and 4I). Moreover, similar to PAF expression in the AER (Figure 2A), EZH2 is also specifically expressed there to maintain of Hox cluster gene transcription (Wyngaarden et al., 2011). Thus, it is plausible that EZH2 and PAF cooperatively control Hox gene activation in the developing limb. Interestingly, despite the presence of a physical and functional connection between Bmi1 and EZH2 in H3K27me3-mediated gene repression, EZH2 is expressed only in crypt IECs including ISCs (Figure S6), whereas Bmi1 is expressed in ISCs at position 4 (Figure 3J), implying a Bmi1-independent role for EZH2 in gene regulation. These results demonstrate the novel function of EZH2 in β-catenin target gene activation, independent of the histone methyltransferase activity of EZH2.

Previously, we found that TERT, a catalytic subunit of telomerase, positively modulates Wnt signaling (Park et al., 2009), elucidating a non-telomeric function of telomerase in development and cancer. Here our results propose that one component of DNA damage bypass process also functions in regulating Wnt signaling, dependent of context. In cancer, PAF overexpression may play a dual role in inducing (a) cell hyperproliferation (via Wnt signaling hyperactivation) and (b) the accumulation of mutations arising from DNA lesion bypass (by PAF-mediated TLS) (Povlsen et al., 2012). Importantly, PAF is only expressed in cancer cells, but not in normal epithelial cells. Thus, upon DNA damage, instead of cell growth arrest to permit high-fidelity DNA repair, the PAF overexpression in cancer cells is likely to induce DNA lesion bypass by facilitating TLS. However, in the setting of Wnt signaling deregulation, nuclear β-catenin sequesters PAF from PCNA and utilize PAF as a co-factor of transcriptional complex, which induces Wnt signaling hyperactivation and possibly lead to increased mutagenesis.

We observed that PAF marked the stemness of ISCs and mouse embryonic stem cells (Figure S7), implicating its roles in stem cell regulation under physiological conditions. In a previous study, a PAFgermline knockout mouse model displayed defects in hematopoietic stem cell self-renewal (Amrani et al., 2011), suggesting a crucial role of PAF in stem cell maintenance and activation. In the intestine, β-catenin activation in Lgr5-positive or Bmi1-positive cells is sufficient to develop intestinal adenoma (Barker et al., 2009Sangiorgi and Capecchi, 2008), suggesting an essential role of tissue stem cells in tumor initiation. Considering PAF expression in Bmi1-positive ISCs, PAF upregulation in ISCs likely hyperactivates the Wnt/β-catenin signaling and contributes to intestinal tumor initiation.

Despite the critical role of Wnt signaling in early vertebrate, development PAF germline knockout mice are viable (Amrani et al., 2011). It is noteworthy that, whereas deletion of any core component in the Wnt signaling pathway causes embryonic lethality, mice with germline knockout of Wnt signaling modulators, including Nkd1/2Pygo1/2, and BCL9/9-2, exhibit no lethal phenotypes (Deka et al., 2010Schwab et al., 2007Zhang et al., 2007). This may result from the robustness of Wnt signaling during embryogenesis because of functional compensation not only via the presence of multiple Wnt signaling regulators per se but also via other types of signaling crosstalk. Therefore, as described previously in pRb studies (Sage et al., 2003), acute deletion of PAF in a conditional knockout mouse model may disrupt the developmental balance or tissue homeostasis, and then reveal the full spectrum of the physiological and pathological roles of PAF in tumorigenesis. Taken together, our findings reveal unexpected function of PAF and EZH2 in modulating Wnt signaling, and highlight the impacts of PAF-induced Wnt signaling deregulation on tumorigenesis.

11.1.9 PAF Makes It EZ(H2) for β-Catenin Transactivation

Xinjun Zhang1 and Xi He1
Mol Cell. 2013 Oct 24; 52(2)
http://dx.doi.org:/10.1016/j.molcel.2013.10.008.

In this issue of Molecular Cell, Park and colleagues (Jung et al., 2013) show that PAF (PCNA-associatedfactor) binds to and hyperactivates transcriptional function of β-catenin in colon cancer cells by recruiting EZH2 to the coactivator complex. PAF-β-catenin and PAF-PCNA interactions are competitive, raising the question of whether β-catenin might regulate PCNA-dependent DNA replication and repair.

Wnt signaling through stabilization of transcription co-activator β-catenin plays critical roles in animal development and tissue homeostasis, and its deregulation is involved in myriad human diseases including cancer (Clevers and Nusse, 2012). Notably, most colorectal cancers (CRCs) have elevated β-catenin signaling caused by mutations of Wnt pathway components such as the tumor suppressor APC (Adenomatosis polyposis coli) and β-catenin itself (Clevers and Nusse, 2012). Much effort has focused on studying β-catenin-dependent transactivation in CRCs, including the current study by Park and colleagues that identifies PAF as an unexpected β-catenin co-activator (Jung et al., 2013).

PAF, for PCNA (proliferating cell nuclear antigen)-associated factor (also known as KIAA0101 or p15PAF), is an interacting partner of PCNA (Yu et al., 2001). PCNA has a key role in DNA replication and repair by assembling various DNA polymerase and repair complexes at the replication fork (Mailand et al., 2013). Dynamic regulation of PAF abundance and/or interaction with PCNA appears to be important for engaging DNA damage repair and bypass pathways (Emanuele et al., 2011Povlsen et al., 2012). PAF is overexpressed in many types of cancers and required for cell proliferation (e.g., Yu et al., 2001).

In the current study (Jung et al., 2013), Jung et al. show that PAF is overexpressed in CRCs in a manner that parallels expression of Axin2, an established Wnt/β-catenin target gene. PAF knockdown inhibits CRC proliferation, and this effect is independent of PAF-PCNA interaction and can be rescued by a PAF mutant that does not binds to PCNA or by β-catenin overexpression. PAF knockdown downregulates the expression of Wnt/β-catenin target genes Cyclin D1c-Myc, and Axin2 in a CRC line, leading the authors to hypothesize that PAF participates in Wnt/β-catenin signaling. Indeed PAF knockdown reduces, and its overexpression augments, Wnt/β-catenin responsive TOPFLASH reporter and target gene expression induced by Wnt3a or by pharmacological agents that stabilize β-catenin. In Xenopus embryos, PAF synergizes with β-catenin to induce Wnt target gene expression and axis duplication (a hallmark of Wnt/β-catenin activation). In mouse embryos, PAF is highly expressed in regions known for Wnt/β-catenin signaling such as the apical ectodermal ridge of the limb bud. Therefore PAF appears to be a positive regulator of Wnt/β-catenin signaling in CRCs and vertebrate embryos.

PAF does not affect β-catenin protein levels and is localized in the nucleus. Protein binding assays show that PAF interacts, directly or indirectly, with β-catenin (via the Armadillo-repeat domain) and its DNA-bound partner TCF (T Cell factor). Indeed PAF is associated with promoters of Wnt/β-catenin target genes in chromatin in CRC cells. Interestingly in the mouse intestine, the PAF protein is enriched in Bmi (B lymphoma Mo-MLV insertion region 1 homolog)-positive stem cells (at the “+4” position) (Sangiorgi and Capecchi, 2008). Bmi1 is a component of Polycomb Repressive Complex 1 (PRC1), which, together with the PRC2 complex that modifies Histone H3, has critical functions in transcriptional epigenetic silencing. Previous studies have suggested that a core PRC2 component, EZH2 (enhancer of zeste homolog 2), is a partner and paradoxically a co-activator of β-catenin, acting in a manner that is independent of EZH2’s methyltransferase activity (Li et al., 2009Shi et al., 2007). Jung et al. found that PAF indeed interacts with both Bmi1 and EZH2, but not other PRC2 components, and EZH2 overexpression augments β-catenin transcriptional activity. PAF, EZH2, and β-catenin are found to co-occupy promoters of several Wnt/β-catenin target genes in CRC and mouse ES cells, and PAF depletion decreases EZH2 association with the c-Myc promoter, and β-catenin depletion decreases the association of both PAF and EZH2 with the promoter. Thus the β-catenin-PAF-EZH2 complex appears to constitute a chain of co-activators (Figure 1), and indeed PAF, which binds to both β-catenin and EZH2, enhances β-catenin-EZH2 co-immunoprecipitation. Together with an earlier study (Shi et al., 2007), these results suggest a model that PAF brings EZH2 and the associated RNA polymerase II Mediator complex to β-catenin target genes for transactivation in CRCs (Figure 1). Consistent with this model, transgenic overexpression of PAF in the mouse intestine induces β-catenin-dependent target and reporter gene expression, intestinal overgrowth, and adenoma formation in vivo and crypt organoid expansion in vitro, resembling Wnt/β-catenin signaling activation in the gastrointestinal tract.

ceb2-catenin-transactivation-nihms532034f1

ceb2-catenin-transactivation-nihms532034f1

β-catenin transactivation

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3848709/bin/nihms532034f1.jpg

Figure 1 β-catenin transactivation mediated by PAF and EZH2 in the G1 phase and a speculative role of β-catenin in modulating PAF-PCNA-dependent DNA replication and repair/bypass pathways in the S phase.

PAF and EZH2 represent newer additions to β-catenin’s plethora of co-activators (Mosimann et al., 2009), which offer multiple routes to engage the basal transcription apparatus. These co-activators may have partially redundant and/or context-dependent functions for numerous Wnt/β-catenin-dependent gene programs. Mouse mutants that lack an individual β-catenin co-activator are often viable (MacDonald et al., 2009Mosimann et al., 2009). Paf−/− mice are viable but exhibit defects in hematopoietic stem cell properties (Amrani et al., 2011). PAF is also expressed in self-renewing mouse ES cells but the expression is downregulated upon ES cell differentiation (Jung et al., 2013). Whether PAF has a general role in self-renewal of embryonic and adult stem cells through its role in β-catenin signaling or DNA replication and repair pathways remains to be investigated.

PAF-β-catenin interaction is observed under Wnt stimulation, likely as a consequence of β-catenin accumulation (Jung et al., 2013). In some cell types PAF is ubiquitinated and degraded by the anaphase promoting complex and thus exhibits the lowest level in the G1 phase of the cell cycle (Emanuele et al., 2011). In these cells PAF may have a limited role as a co-activator for β-catenin-dependent transcription, which primarily occurs in G1. But in CRC and other cancers where PAF is overexpressed, PAF may have a prominent role as a β-catenin co-activator.

PAF-PCNA interaction is well documented (e.g., Yu et al., 2001). Surprisingly however, in CRCs with high levels of β-catenin, PAF-PCNA interaction is barely detectable (Jung et al., 2013). Conversely, in cells where the basal level of Wnt/β-catenin signaling is low, PAF-PCNA interaction is detected but is diminished by Wnt3a or pharmacological agents that stabilize β-catenin (Jung et al., 2013). PAF seems to interact with β-catenin and PCNA via an overlapping domain (although this remains to be better defined), offering a possible explanation why PAF-β-catenin and PAF-PCNA complexes appear to be mutually exclusive (Jung et al., 2013). This may simply reflect the fact that PAF-β-catenin (for RNA transcription) and PAF-PCNA (for DNA replication/repair) complexes act in G1 and S, respectively (Figure 1). However, when β-catenin levels are high in Wnt-stimulated cells or in CRCs, one may speculate that β-catenin accumulation could inhibit PAF-PCNA complex formation in the S phase, thereby enabling Wnt/β-catenin signaling to modulate PAF-PCNA-dependent DNA replication and repair/bypass pathways (Figure 1). This would constitute an unsuspected role for Wnt/β-catenin signaling in genomic stability beyond its established transcriptional function and could have implications to tumorigenesis.

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11.1.10 PI3K.AKT.mTOR pathway as a therapeutic target in ovarian cancer

Li H1Zeng JShen K.
Arch Gynecol Obstet. 2014 Dec; 290(6):1067-78
http://dx.doi.org:/10.1007/s00404-014-3377-3

Background: Ovarian cancer is one of the major causes of death in women worldwide. Despite improvements in conventional treatment approaches, such as surgery and chemotherapy, a majority of patients with advanced ovarian cancer experience relapse and eventually succumb to the disease; the outcome of patients remains poor. Hence, new therapeutic strategies are urgently required. The phosphatidylinositol 3-kinase (PI3K)/AKT/mammalian target of rapamycin (mTOR) is activated in approximately 70 % of ovarian cancers, resulting in hyperactive signaling cascades that relate to cellular growth, proliferation, survival, metabolism, and angiogenesis. Consistent with this, a number of clinical studies are focusing on PI3K pathway as an attractive target in the treatment of ovarian cancer. In this review, we present an overview of PI3K pathway as well as its pathological aberrations reported in ovarian cancer. We also discuss inhibitors of PI3K pathway that are currently under clinical investigations and the challenges these inhibitors face in future clinical utility.Methods: PubMed was searched for articles of relevance to ovarian cancer and the PI3K pathway. In addition, the ClinicalTrials.gov was also scanned for data on novel therapeutic inhibitors targeting the PI3K pathway. Results: Genetic aberrations at different levels of PI3K pathway are frequently observed in ovarian cancer, resulting in hyperactivation of this pathway. The alterations of this pathway make the PI3K pathway an attractive therapeutic target in ovarian cancer. Currently, several inhibitors of PI3K pathway, such as PI3K/AKT inhibitors, rapamycin analogs for mTOR inhibition, and dual PI3K/mTOR inhibitors are in clinical testing in patients with ovarian cancer. Conclusions: PI3K pathway inhibitors have shown great promise in the treatment of ovarian cancer. However, further researches on selection patients that respond to PI3K inhibitors and exploration of effective combinatorial therapies are required to improve the management of ovarian cancer.

Fig.1. Inputs from receptor tyrosine kinases (RTKs) and G protein-coupled receptors (GPCR) to class I PI3K.

Fig. 2. Schematic representation of the PI3K/AKT/mTOR signaling pathway.

Fig.3. PI3K/AKT/mTOR inhibitors.

AKT inhibitors

AKT inhibitors can be grouped into three classes including lipid based phosphatidylinositol (PI) analogs, ATP-competitive inhibitors, and allosteric inhibitors. Perifosine, which is the most clinically studied AKT inhibitor, is a lipid-based PIanalog that targets the pleckstrin homology domain of AKT, preventing its translocation to the cell membrane. Amongthe three classes of AKT inhibitors, allosteric AKT inhibitors display highly specific selectivity for AKT isoforms. Considering the genetic background of ovarian cancer, allosteric AKT inhibitors such as MK2206 that can target both AKT1 and AKT2 might be the best agents for treating ovarian cancer.In clinical trials, AKT inhibitors have shown similar toxicities to those caused by PI3K inhibitors, such as hyperglycemia, rashes, stomatitis, and gastrointestinal side effects [25].

mTOR inhibitors

Rapamycin and its analogs Rapamycin (sirolimus), a potent inhibitor of mTORC1, was first isolated in 1975 from the bacterium Streptomyces hygroscopicus. Rapamycin inhibits mTORC1 by first binding to the intracellular protein FK506 binding protein 12 (FKBP12). The resultant rapamycin–FKBP12 complex then binds to the FKBP12–rapamycin-binding domain (FRB) of mTORC1 and inhibits the serine/threonine kinase activity of mTORC1 via an allosteric mechanism. In contrast to mTORC1, the rapamycin–FKBP12 complex cannot interact with the FRB domain of mTORC2, and thus,mTORC2 is generally resistant to rapamycin treatment [12]. As rapamycin displays very poor water solubility, which limits its clinical use, several soluble ester analogs of rapamycin (rapalogs) have been developed [12]. Currently, these analogs include temsirolimus, everolimus, and ridaforolimus. Temsirolimus and everolimus are formulated for intravenous and oral administration, respectively. Ridaforolimus was initially developed as an intravenous formulation, but an oral formulation was subsequently produced [12,28]. Clinically, rapalogs are generally well tolerated, with the most common side effects including stomatitis, rashes, fatigue, hyperglycemia, hyperlipidemia, hypercholesterolemia, and myelosuppression [3,12,25].

ATP-competitive inhibitors

Different from rapalogs, ATP-competitive inhibitors do not require co-factors such as FKBP12 to bind to mTOR. By competingwith ATP for theATP-binding sites of mTOR, this class of mTOR inhibitors can inhibit the kinase activity of both mTORC1 and mTORC2. Although there is a concern that the simultaneous inhibition of mTORC1 and mTORC2 might result in greater toxicities in normal tissues, ATP-competitive mTOR inhibitors have been shown to display stronger anti-proliferative activity than rapalogs across a broad range of cancers includingovarian cancer [12,15].

Metformin

Metformin,the most commonly prescribed oral anti-diabetic agent, has been shown to reduce the incidence of malignancies in patients with diabetes. The activation of 5′ adenosine monophosphateactivated protein kinase (AMPK) by metformin plays an important role in mediating the drug’s effects. AMPK activation results in the phosphorylation and activation of TSC2, which exerts inhibitory effects on mTORC1. Metformin-induced AMPK activation also reduces AKT activity by inhibiting insulin receptor substrate 1 (IRS-1). Ultimately, AMPK activation results in the inhibition of the PI3K/AKT/mTOR signaling pathway, making metformin an effective treatment for cancer [28].

mTORC1 inhibitors              mTORC1                      Dual PI3K/mTOR inhibitors

PI3K inhibitors                     Class I PI3K                   mTORC2

AKT inhibitors                        AKT                              mTORC ½  inhibitors

PI3K inhibitors

Pan-class I PI3K inhibitors Pan-class IPI3K inhibitors can inhibit the kinase activity ofall 4 isoforms of classI PI3K.The main advantage of pan-class IPI3K inhibitors is that most cancer cells express multiple PI3K isoforms with redundant oncogenic signaling functions. Early clinical trials have suggested that the most common toxicitiesof pan-class IPI3K inhibitors are hyperglycemia, skin toxicities, stomatitis, and gastrointestinal side effects. Of these, hyperglycemia is likely to be a mechanism-based toxicity given the well described role of PI3K in insulin receptor signaling [3,25].

Isoform-selective PI3K inhibitors

This class of agents target the specific PI3K p110 isoforms involved in particular types of cancer. The p110α isoform (which is encoded by the PIK3CA gene) is a frequent genetic driver (PIK3CA mutations) of ovarian cancer, whereas p110β activity is known to be essential in cancer cells lacking PTEN. As for the p110δ isoform, it plays a fundamental role in the survival of normal B cells and is implicated in malignancies affecting this lineage. Thus, the main theoretical advantage of these inhibitors is that they have the potential to completely block the relevant target whilst causing limited toxicities compared with pan-PI3K inhibitors. Consistent withthese findings, preclinical studies have detected significant activities of PI3Kα inhibitor in tumors exhibiting PIK3CA mutations, PI3Kβ inhibitors in tumors with PTEN loss, and PI3Kδ inhibitors in hematologic malignancies. In addition, PI3Kδ inhibitors have already shown very promising activity in patients with chronic lymphocytic leukemia [26].

Dual PI3K/mTOR inhibitors

Structural similarities between the ATP-binding domain of p110 and the catalytic domain of mTOR have led to the development of a class of agents that inhibit both class I PI3K and mTORC1/2. Theoretically, dual mTOR/PI3K inhibitors should lead to more complete suppression of the PI3K/AKT/mTOR pathway than targeting either component independently.In agreement with this, in preclinical studies of ovarian cancer dual PI3K/mTOR inhibitors were found to exhibit greater in vitro and in vivo anti-tumor activity than mTOR inhibitors alone [27]. The safety profile of these inhibitors is similar to that of pan-PI3K inhibitors, with common adverse events including nausea, diarrhea, fatigue, and vomiting [3,25]. 

 

11.1.11 Endogenous, hyperactive Rac3 controls proliferation of breast cancer cells by a p21-activated kinase-dependent pathway

Mira JP1Benard VGroffen JSanders LCKnaus UG.
Proc Natl Acad Sci U S A. 2000 Jan 4; 97(1):185-9.

Uncontrolled cell proliferation is a major feature of cancer. Experimental cellular models have implicated some members of the Rho GTPase family in this process. However, direct evidence for active Rho GTPases in tumors or cancer cell lines has never been provided. In this paper, we show that endogenous, hyperactive Rac3 is present in highly proliferative human breast cancer-derived cell lines and tumor tissues. Rac3 activity results from both its distinct subcellular localization at the membrane and altered regulatory factors affecting the guanine nucleotide state of Rac3. Associated with active Rac3 was deregulated, persistent kinase activity of two isoforms of the Rac effector p21-activated kinase (Pak) and of c-Jun N-terminal kinase (JNK). Introducing dominant-negative Rac3 and Pak1 fragments into a breast cancer cell line revealed that active Rac3 drives Pak and JNK kinase activities by two separate pathways. Only the Rac3-Pak pathway was critical for DNA synthesis, independently of JNK. These findings identify Rac3 as a consistently active Rho GTPase in human cancer cells and suggest an important role for Rac3 and Pak in tumor growth.

Uncontrolled cell proliferation is a major feature of cancer. Experimental cellular models have implicated some members of the Rho GTPase family in this process. However, direct evidence for active Rho GTPases in tumors or cancer cell lines has never been provided. In this paper, we show that endogenous, hyperactive Rac3 is present in highly proliferative human breast cancer-derived cell lines and tumor tissues. Rac3 activity results from both its distinct subcellular localization at the membrane and altered regulatory factors affecting the guanine nucleotide state of Rac3. Associated with active Rac3 was deregulated, persistent kinase activity of two isoforms of the Rac effector p21-activated kinase (Pak) and of c-Jun N-terminal kinase (JNK). Introducing dominant-negative Rac3 and Pak1 fragments into a breast cancer cell line revealed that active Rac3 drives Pak and JNK kinase activities by two separate pathways. Only the Rac3–Pak pathway was critical for DNA synthesis, independently of JNK. These findings identify Rac3 as a consistently active Rho GTPase in human cancer cells and suggest an important role for Rac3 and Pak in tumor growth.

Rac proteins are members of the Rho GTPase family and act as molecular switches in regulating a variety of biological response pathways, including cell motility, gene transcription, cell transformation, and cell-cycle progression (1). The Rac family includes Rac1, the myeloid-lineage-specific Rac2, and the recently cloned Rac3 proteins (2). Rac3 differs from Rac1 and Rac2 in two domains, the insert region and the C terminus, which influence transformation (34), interaction with guanine nucleotide exchange factors (GEFs) (56), and subcellular localization (78). Small GTPases, including Rac, cycle between an inactive GDP-bound state and an active GTP-bound state. Two classes of regulatory factors, GTPase-activating proteins (GAPs) and GEFs, determine by their opposing effects the ratio of GDP versus GTP, which is bound to the GTPase (1). GAP proteins increase the intrinsic rate of GTP hydrolysis, rendering the GTPase inactive, whereas GEFs enhance the exchange of bound GDP for GTP, thereby activating the protein. Active Rac regulates distinct downstream signaling pathways by interacting with specific effector proteins, including a family of serine-threonine protein kinases termed Paks (p21-activated kinases) (911).

Apart from its well documented role in cytoskeletal rearrangements in growth factor-stimulated cells (12), Rac1 is required for Ras-induced malignant transformation and is involved in transcription and growth control (11314). Recently, the importance of the Rac effector Pak in cell transformation has been highlighted by inhibiting RasV12- and Rac1V12-induced transformation of Rat-1 fibroblasts with a catalytically inactive form of Pak (1516). The involvement of Rac1 in driving cell-cycle progression through the G1 phase and stimulating DNA synthesis has been shown by introducing dominant-active and -negative Rac1 mutants into fibroblasts (1718). However, the signaling pathways used by Rac to control mitogenesis and proliferation still remain poorly understood. Overexpression of constitutively active Rac-effector-domain mutants in fibroblasts indicated that although Rac1 mediated cyclin D1 transcription by Pak in NIH 3T3 cells (19), Pak was not involved in the DNA synthesis of Swiss 3T3 cells (20). Accumulating evidence, however, suggests higher complexity where Pak-binding proteins, such as the GEF Pix, contribute to the Rac–Pak interaction in vivo and influence subsequent cellular functions (2123).

All biological functions listed above have been attributed to Rac1 in experimental cell systems using overexpression or microinjection of mutant forms. Endogenously active Rho GTPases, including Rac, have not yet been observed. In this paper, we describe a consistently active Rac3 GTPase leading to hyperactivity of its effector protein kinase, Pak, in human breast cancer-derived epithelial cell lines. Analysis of growth properties and DNA synthesis revealed that both proteins are required to convey the highly proliferative phenotype displayed by these cells.

Highly Proliferating Cancer Cells Contain Hyperactive Rac3.

Comparison of growth rates among several breast cancer cell lines showed that three lines (MDA-MB 435, T47D, and MCF 7) grew faster under normal and low-serum conditions (Fig. ​(Fig.1).1). Interestingly, in contrast to MDA-MD 231 and Hs578T cells, these three highly proliferative cell lines do not possess mutated Ras (2829). To assess whether Rho GTPases drive this cellular phenotype, we determined whether these cell lines contained active GTP-bound Rac or Cdc42. We used a recently described assay, the PBD-pulldown assay (24), which is based on the specific binding of the GTP-bound forms of Rac and Cdc42 to the PBD of Pak (10). Neither active Rac1 (Fig. ​(Fig.22A) nor active Cdc42 (data not shown) could be detected in any of the cell lysates obtained from serum-starved cells. However, both proteins were detected if the PBD-pulldown assay was performed with in vitro guanosine 5′-[γ-thio]triphosphate (GTP[γS])-loaded cell lysates, confirming that Rac1 and Cdc42 were present in their inactive GDP-bound forms in these cells (Fig. ​(Fig.22A for Rac1). Next we wanted to determine whether active Rac3 was present in breast cancer cell lines. Because Rac3 effectors have not yet been characterized, we demonstrated by overlay binding and kinase assays that Rac3 bound to and activated Pak as efficiently as Rac1 (data not shown). We verified that the PBD-pulldown assay specifically detected the active GTP-bound form of Rac3 (GTP[γS]-loaded Rac3wt or Rac3V12, Fig. ​Fig.22B) and not the inactive form. To probe for Rac3 protein in breast cell lysates, a Rac3-specific antibody was used. GST-PBD-pulldown experiments from cell lysates revealed the presence of hyperactive Rac3 in highly proliferative cell lines (MDA-MB 435, T47D, and MCF 7), but not in normal breast cell lines or in less proliferative breast cancer cells (Fig. ​(Fig.22C). Additionally, as indicated by the virtual absence of Rac3 in the supernatant of the PBD pulldown, all the Rac3 protein present in these cell lines was active (Fig. ​(Fig.22C). To demonstrate that consistent Rac3 activation is not limited to cell lines, we performed an initial screening of human metastatic breast cancer tissues and found active Rac3 in one of three samples, underlining the potential clinical relevance of the cellular findings (Fig. ​(Fig.22D).

Differential growth rates of human breast cell lines.  pq0104939001

Differential growth rates of human breast cell lines. pq0104939001

Differential growth rates of human breast cell lines.
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC26637/bin/pq0104939001.jpg

Figure 1 Differential growth rates of human breast cell lines. Human breast cell lines, including HMEC 184 (○), MDA-MB 231 (▵), Hs578T (□), MDA-MB 435 (●), T47D (▴), and MCF 7 (♦), were grown in 10% serum (A) or 0.5% serum (B) conditions. The cells were split in duplicate over 6-well plates at 5 × 105 cells per well and counted daily with a hemocytometer for 4 days. Data shown in A and B are representative of three independent experiments.

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC26637/bin/pq0104939002.jpg

Figure 2 Active Rac3 is present in highly proliferative cell lines and in human breast cancer tissue. (A and C) Cell lysates from serum-starved breast cancer cell lines without (A and C) or after (+) GTP[γS] loading (A) were incubated with 10 μg of GST-PBD. Active Rac proteins (PBD pulldown) were detected by immunoblot with anti-Rac1 (A) or anti-Rac3 antibodies (C). Blotting of PBD supernatants revealed the GDP-bound form of Rac3 in lysates. Equal amounts of Rac3 protein were detected by immunoblot (IB) in all cell lines. (B) A PBD-pulldown assay of extracts from HeLa cells expressing Myc-Rac3wt or -Rac3 mutants, followed by an anti-Myc immunoblot, detected only active Rac3 (GTP[γS] loading or Rac3V12). (D) PBD pulldown of lysates obtained from three different human metastatic breast cancer tissues, followed by anti-Rac1 and anti-Rac3 immunoblots, revealed active Rac3 in tissue 1. (E) PBD pulldown of lysates derived from MDA-MB 435 and MDA-MB 231 cells expressing LacZ control or Myc-Rac3wt without or after in vitro GTP[γS] loading. Consistent activation of Myc-Rac3wt occurred only in MDA-MB 435 cells. (F) Subcellular localization of Rac1 and Rac3. Cytosol (c) and membranes (m) were obtained after nitrogen cavitation and fractionation of breast cancer cell lines and immunoblotted with anti-Rac1 and anti-Rac3 antibodies. All blots are representative of at least three experiments.

Subcellular Localization and GTPase-Regulatory Factors Influence Rac3 Activity.

Constitutive activation of Ras proteins in cancer cells is often caused by activating point mutations at the switch I or II regions (29). cDNA cloning and complete sequence analysis of full-length Rac3 did not reveal any mutations in the breast cell lines studied and did not explain the observed Rac3 activation. GTPase-regulatory proteins such as GEFs and GAPs, which are usually regulated by upstream stimuli, control cycling between the active and inactive forms of Rac. To confirm the presence of an altered regulatory mechanism involved in Rac3 activation, we used the PBD-pulldown assay to analyze the activation state of Myc-tagged Rac3wt transfected into either MDA-MB 231, a cell line harboring only GDP-Rac3, or MDA-MB 435, a cell line that contains endogenous, active GTP-Rac3. Fig. ​Fig.22E shows that activated Myc-Rac3 was detected only in the MDA-MB 435 cell line, confirming that the regulation of the GDP/GTP state of Rac3 was altered in these cells. We then investigated several upstream stimuli that have been shown to affect GTPase-regulatory proteins (283032). We excluded the possibility of an autocrine growth-stimulatory loop by culturing MDA-MB 231 cells with the conditioned medium from MDA-MB 435, which did not affect the Rac3 activation state (data not shown). Treatment of cell cultures with phosphatidylinositol 3-kinase or tyrosine kinase inhibitors, including wortmannin, LY294002, and genistein, did not decrease Rac3 activation (data not shown). At this point, we speculated that an oncogenic, Rac3-specific GEF is present in certain breast cancer cells. GEFs possess a pleckstrin homology domain that is essential for membrane localization and for their oncogenic properties (533). Analysis of the subcellular localization of the Rac family members revealed that Rac3 is located in the membranes of breast epithelial cell lines, independently of its activation state (Fig. ​(Fig.22F). In contrast, endogenous Rac1 in its inactive GDP-bound state was essentially cytosolic (Fig. ​(Fig.22F). Thus, the distinct localization of Rac3 and Rac1 may contribute to their different activation states in certain breast cancer cell lines. It is conceivable that the highly proliferative cell lines (Fig. ​(Fig.1)1) express a constitutively active, membrane-bound Rho GEF that activates adjacent Rac3 protein. This hypothesis was further supported by using an hydroxymethylglutaryl-CoA reductase inhibitor, lovastatin, that interferes with isoprenoid synthesis and thereby with posttranslational processing of GTPases. Unprocessed Rac3 from lovastatin-treated MDA-MB 435 cells was predominantly cytosolic and inactive (GDP-Rac3) (data not shown). The requirement of membrane localization for consistent Rac3 activity was further supported by using a Rac3S189 mutant. Replacing cysteine-189 of the CAAX box with serine abolishes isoprenoid incorporation, rendering the GTPase cytosolic. This Rac3 mutant remained in its inactive GDP-bound state when transfected into MDA-MB 435 cells (data not shown).

Several Rho GTPase-regulating GEFs have been identified (5), including the Rac1-specific GEF Tiam-1, which has been linked to tumors such as invasive T-lymphomas (34). Although Tiam-1 is expressed in virtually all tissues, no evidence of oncogenic truncations or alternative splicing of Tiam-1 transcripts has been found (35). A variation of Tiam-1 transcript levels in certain cancer cell lines might lead to overexpression and possibly activation of Tiam-1 protein. However, the activation state of Rac3 protein in the cell lines used in this study does not seem to correlate with Tiam-1 expression levels as reported by Habets et al. (35). Hyperactivity of Rac3 in cancer cells could also result from an absent or dysfunctional Rac3-specific GAP protein. By accelerating the intrinsic GTP hydrolysis rate, GAPs render the GTPase inactive and act as tumor suppressors. Deletion or mutations in the RasGAP gene NF1 and the RhoGAP homologs bcr and DLC-1 have been reported in cancer cells (3637).

Active Rac3 Drives Epithelial Cell Proliferation.

To study whether active Rac3 could account for the high proliferation rate of certain breast cancer cells, we expressed a constitutively active Rac3 mutant (Rac3V12) in normal mammary epithelial cells (HMEC 184) that contain only GDP-Rac3 (Fig. ​(Fig.22C). Rac3V12 expression significantly increased the incorporation of BrdUrd into nascent DNA (Fig. ​(Fig.3),3), emphasizing that transfection of active Rac3 drives epithelial cell proliferation.

Rac3V12 induces DNA synthesis in human mammary epithelial cells pq0104939003

Rac3V12 induces DNA synthesis in human mammary epithelial cells pq0104939003

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC26637/bin/pq0104939003.jpg

Rac3V12 induces DNA synthesis in human mammary epithelial cells

Figure 3 Rac3V12 induces DNA synthesis in human mammary epithelial cells. HMEC 184 cells, infected with recombinant LacZ or Rac3V12 Semliki Forest virus, were allowed to express protein for 14 h in serum-free medium containing 10 μM BrdUrd. Cells were fixed and stained with anti-Myc antibody for Myc-Rac3V12 expression level (Upper) or with FITC-conjugated anti-BrdUrd antibody for BrdUrd incorporation (Lower). The presence of bright fluorescent nuclei indicates BrdUrd-positive cells. The percentage was calculated after counting 400 cells in each of three independent experiments.

Hyperactive Pak and c-Jun Kinases in Cancer Cells.

The signaling cascade utilized by Rac proteins to control cell proliferation still remains to be identified (19), but might involve Paks. We analyzed Pak activity in cell lysates derived from serum-starved breast cancer cell lines by using in-gel kinase assays and by usingin vitro kinase assays after immunoprecipitation with Pak-specific antibodies. Pak activity was increased 4- to 6-fold in the three cell lines containing active Rac3 (Fig. ​(Fig.44A). This increased kinase activity was mainly associated with the Pak2 isoform, which can phosphorylate and positively regulate Raf-1 activity, another key component in cell proliferation (3840).

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC26637/bin/pq0104939004.jpg

Figure 4 Rac3 activates Pak and JNK by two different pathways. (A) Breast cancer cell lysates from serum-starved cells were analyzed for Pak and JNK activities. Pak activities in cell lysates were analyzed by in-gel kinase assays. JNK activity was determined by 

Intracellular Rac-regulated signaling pathways impinge on distinct mitogen-activated protein kinase cascades. Constitutively active Rac has been shown to positively regulate the activity of the stress-activated kinases JNK and p38 (1). Moreover, ERK activity can be indirectly stimulated by Rac or mediated by crosstalk between the distinct mitogen-activated protein kinase cascades (141). Determination of distinct mitogen-activated protein and stress-activated protein kinase activities in the breast cell lines studied here showed that consistent Rac3 and Pak kinase activities were associated with enhanced JNK activity (Fig. ​(Fig.44A). In contrast, no correlation existed between p38 or ERK kinase activities and active Rac3 or Pak (data not shown).

Rac3 Triggers Pak and JNK Activities by Separate Pathways.

To determine whether the highly proliferative phenotype of breast cancer cells depends directly on a consistently active Rac3-Pak-JNK cascade, we used virus-mediated protein expression in MDA-MB 435 cells to examine the ability of Rac3 and Paks to control JNK activation and cellular proliferation. The importance of Pak as an effector protein in Rac-mediated activation of JNK is still controversial and seems to be cell-type-dependent (42). Expression of the PBD domain, which controls the activity of both Rac and Pak (21), completely inhibited Pak and JNK stimulation (Fig. ​(Fig.44B). The mutation of leucine to phenylalanine at position 107 of the PBD domain suppresses the autoinhibitory function of the PBD (21). Thus, PBD F107 will act only to sequester active Rac3 and blocks its ability to bind and activate endogenous effectors. Expression of either dominant-negative Rac3N17 or PBD F107 almost completely blocked Pak and JNK activities, demonstrating that Rac3 is upstream of these proteins (Fig. ​(Fig.44B). Moreover, Pak kinase activity can be inhibited independently of Rac3 by overexpressing the kinase autoinhibitory domain, PID, which does not interact with Rac (2143). Transfection of PID into MDA-MB 435 cells dramatically inhibited Pak activity as expected, but did not decrease JNK activation (Fig. ​(Fig.44B). Our results indicate that in MDA-MB 435 cells, consistent stimulation of JNK by Rac3 is independent of PAK activity and that Rac3 initiates two different pathways involving Pak and JNK, respectively.

Rac3 and Pak Are Both Required for Breast Cancer Cell Proliferation.

We subsequently determined which of these two Rac3 pathways promoted the increased cell proliferation in breast cancer cell lines with hyperactive Rac3. We studied the consequence of expressing inhibitory Rac mutants or Pak fragments on DNA synthesis. LacZ-expressing MDA-MB 435 cells still proliferated in low-serum conditions and 35% incorporated BrdUrd (Fig. ​(Fig.5).5). This percentage increased to 50% when Rac3wt, which will be partially activated in these cells (Fig. ​(Fig.22E), is expressed (Fig. ​(Fig.55 Bottom Right). In contrast, expression of inhibitory proteins, including Rac3N17 or the PBD that suppressed Pak and JNK activation (Fig. ​(Fig.44B), almost completely blocked S-phase entry, as indicated by the absence of BrdUrd incorporation (Fig. ​(Fig.5).5). Expression of the PID that inhibited Pak kinase activity without affecting JNK stimulation (Fig. ​(Fig.44B) also arrested proliferation in MDA-MB 435 cells (Fig. ​(Fig.5).5). These experiments emphasize the crucial role of active Rac3 for DNA synthesis in breast cancer cell lines and demonstrate that Pak kinase activity is necessary for Rac3-induced proliferation.

Rac3 mediates proliferation in MDA-MB 435 cells  pq0104939005

Rac3 mediates proliferation in MDA-MB 435 cells pq0104939005

Rac3 mediates proliferation in MDA-MB 435 cells

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC26637/bin/pq0104939005.jpg

Figure 5 Rac3 mediates proliferation in MDA-MB 435 cells by a Pak-dependent pathway. MDA-MB 435 cells growing in 0.5% FBS were infected with Semliki Forest virus encoding for LacZ, Rac3N17, Pak1-PBD, Pak1-PBD F107, Pak1-PID, or Rac3wt. After 12 to14 h of protein expression in serum-free medium, 20 μM BrdUrd was added for 20 min before the cells were fixed and stained with anti-Myc antibody and phalloidin for expression (Top) or with FITC-conjugated anti-BrdUrd antibody for BrdUrd incorporation (Lower five micrographs). The presence of bright fluorescent nuclei indicates BrdUrd-positive cells. The percentage was calculated after counting 400 cells in each of four independent experiments.

Our results establish the persistent activation of a small Rho GTPase, Rac3, and the effector kinase Pak in human breast cancer cells. In contrast to Rac1, endogenous Rac3 is localized at the plasma membrane in both guanine nucleotide states. It seems likely that a Rac3 regulatory protein is altered or deleted in highly proliferating cancer cells, and that its specificity toward Rac3 results from the adjacent location of both proteins at the membrane and/or from discrete Rac3 domains, which convey a specific interaction. The cytoskeletal phenotypes of serum-starved breast cancer cells, such as ruffles or lamellipodia typical of Rac1 protein activation, did not seem to correlate with the GDP versus GTP state of endogenous Rac3. This may suggest that Rac family members are specialized in certain cellular functions, as already reported for Rac2 in leukocyte phagocytosis (44) and now demonstrated by us for Rac3 in cancer cell proliferation. Our studies establish further that endogenous, active Rac3 is essential for breast cancer cell proliferation via a Pak-dependent pathway. Paks have been shown to directly phosphorylate Raf kinase, which binds to retinoblastoma protein and regulates its function (45), and to interact with cyclin-dependent kinases to up-regulate cyclin D1 expression (46). Initial screening of various human cancer-derived cell lines revealed the presence of hyperactive Rac3 and Pak kinase in other types of highly proliferating tumors (data not shown). Further investigations, primarily in animal models and clinical settings, will be necessary to assess whether loss of Rac3 and Pak regulation correlates with certain breast tumor stages and is accompanied by specific alterations in cell-cycle regulators. Approaches to inhibit Rac3 or Pak activity would then open a new avenue for cancer therapeutics.

11.1.12 Curcumin-could-reduce-the-monomer-of-ttr-with-tyr114cys-mutation via autophagy in cell model of familial amyloid polyneuropathy.

Li H1Zhang Y1Cao L1Xiong R1Zhang B1Wu L1Zhao Z1Chen SD2
Drug Des Devel Ther. 2014 Oct 31; 8:2121-8
http://dx.doi.org:/10.2147/DDDT.S70866.

Transthyretin (TTR) familial amyloid polyneuropathy (FAP) is an autosomal dominant inherited neurodegenerative disorder caused by various mutations in the transthyretin gene. We aimed to identify the mechanisms underlying TTR FAP with Tyr114Cys (Y114C) mutation. Our study showed that TTR Y114C mutation led to an increase in monomeric TTR and impaired autophagy. Treatment with curcumin resulted in a significant decrease of monomeric TTR by recovering autophagy. Our research suggests that impairment of autophagy might be involved in the pathogenesis of TTR FAP with Y114C mutation, and curcumin might be a potential therapeutic approach for TTR FAP.

Transthyretin (TTR) familial amyloid polyneuropathy (FAP) is an autosomal dominant inherited disease, characterized clinically by progressive sensory, motor, and autonomic impairment, which typically lead to death around a decade after diagnosis.1 Since the first identification of TTR with Val30Met mutation (TTR V30M), the most common gene mutation in FAP patients, more than 100 TTR mutations have been found to cause FAP.2 However, the detailed pathogenesis underlying TTR FAP remains undefined. Previous studies of the TTR V30M mutant have shown that misfolding and self-aggregation of TTR are implicated in the pathogenesis of TTR FAP involving abnormal endoplasmic reticulum (ER) stress.3

Corresponding to the various TTR gene mutations and a wide range of geographical distributions, FAP presents diverse characteristics in genotype-phenotype in different regions. We have recently published the first report of a TTR Tyr114Cys (TTR Y114C) mutation in a Chinese family with TTR FAP.4 Compared with TTR V30M, the TTR Y114C mutation showed different clinical manifestations, and was also observed in a Japanese family.5,6 This suggests that the pathogenesis of the TTR Y114C and TTR V30M mutations might be different. Studies focused on monomer generation and tetramer depolymerization have been performed.1,2 However, the mechanisms underlying the clearing of the abnormally increased monomer are unknown.

Autophagy is the major lysosomal pathway via which cells degrade intracytoplasmic protein. It is widely accepted that autophagy plays a key role in the process of amyloid deposition in certain neurodegenerative diseases, including alpha-synuclein, beta peptides, tau oligomers, and misfolded prion protein.7 Therefore, autophagy may be involved in degradation of the TTR monomer in TTR FAP.

Curcumin and its analogs have demonstrated a protective effect in many diseases involving antimicrobial, antitubercular,8 and anticancer mechanisms,9 and they can also modulate innate immunity.10 Of note, curcumin has been shown to promote autophagy.11 Therefore, we hypothesized that autophagy might be involved in the pathogenetic mechanism of the TTR Y114C mutation in TTR FAP and curcumin might have potential therapeutic role in this disease. In this study, we aimed to identify the role of autophagy in the pathogenetic mechanism of TTR FAP and to assess the therapeutic effect of curcumin in the disease.

TTR Y114C mutation led to increased monomeric TTR and impaired autophagy in vitro

To investigate the alteration of monomeric TTR with different mutations, we generated HEK293T cell lines with wild-type TTR, TTR Y114C, and stable overexpression of TTR V30M. Wild-type TTR represented the normal control and TTR V30M represented the positive control. Western blotting analysis of the TTR level in the cells when cultured for 24 hours showed that the monomer of TTR Y114C and TTR V30M was increased by approximately 2.3 times and 2.78 times, respectively, compared with wild-type TTR (Figure 1A and B). Mutation of TTR Y114C was related to the increase in monomeric TTR, as well as the mutation of TTR V30M.

Changes in autophagy and endoplasmic reticulum stress related to wild-type TTR, TTR V30M, and TTR Y114C dddt-8-2121Fig1

Changes in autophagy and endoplasmic reticulum stress related to wild-type TTR, TTR V30M, and TTR Y114C dddt-8-2121Fig1

Changes in autophagy and endoplasmic reticulum stress related to wild-type TTR, TTR V30M, and TTR Y114C

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4222630/bin/dddt-8-2121Fig1.jpg

Figure 1 Changes in autophagy and endoplasmic reticulum stress related to wild-type TTR, TTR V30M, and TTR Y114C.

Next we investigated the activation of several markers associated with ER stress, including ER-resident chaperone BiP and p-eIF2α. Our results showed the levels of BiP and p-eIF2α is higher in TTR V30M than those in wild-type TTR. In contrast, BiP and p-eIF2α levels in TTR Y114C were similar to those in wild-type TTR (Figure 1A and C), indicating ER stress might not be the main pathogenetic mechanism for the TTR Y114C mutation. We then investigated whether autophagy plays a role in the mechanism of TTR Y114C mutation. LC3-II is well known to be a robust marker of autophagosomes, and immunofluorescent staining of LC3-II can be used to assay for autophagosome formation. A high ratio of LC3-II to LC3-I would indicate induction of autophagy. Our results revealed that the ratio of LC3-II/I was markedly decreased for TTR Y114C, but less suppressed for TTR V30M (Figure 1A and D). Likewise, a significant decrease in LC3-II immunoreactivity was detected in TTR Y114C (Figure 1E). The results of Western blotting and immunofluorescence indicated that autophagy in TTR Y114C was significantly downregulated. Therefore, impaired autophagy might be responsible for the pathogenesis of TTR Y114C mutation.

Curcumin decreased monomeric TTR by promoting autophagy

The effects of curcumin were investigated in TTR Y114C and wild-type TTR stable overexpressed HEK293T cells. Curcumin did not show toxic effects in the stable overexpressed cell lines at curcumin concentrations below 10 µM (Figure 2A and B). We chose 5 µM as the experimental concentration, because it is the minimal effective concentration of curcumin in these cell lines. Further, we wanted to determine whether curcumin could decrease monomeric TTR by promoting autophagy at the minimal effective concentration. Therefore, we used curcumin (2.5 µM and 5 µM) as a protective agent to assess whether it could decrease monomeric TTR with mutation by promoting autophagy. Quantification of LC3-II and LC3-I indicated markedly higher activation of LC3 in TTR Y114C treated with curcumin 5 µM for 24 hours (Figure 2D). In contrast, treatment with curcumin at different concentrations could not activate LC3 in wild-type TTR (Figure 2C, E). We next examined the ratio of monomers to tetramers in TTR Y114C, which was significantly decreased after 24 hours of treatment with 5 µM curcumin compared with no treatment with curcumin (Figure 2D and F). However, for wild-type TTR, the ratio of monomers to tetramers was unchanged after treatment with curcumin (Figure 2C and E). These results indicate that treatment with curcumin 5 µM for 24 hours was able to decrease the monomer in the TTR Y114C mutation by promoting autophagy.

Curcumin decreased monomeric TTR by promoting autophagy dddt-8-2121Fig2

Curcumin decreased monomeric TTR by promoting autophagy dddt-8-2121Fig2

Curcumin decreased monomeric TTR by promoting autophagy

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4222630/bin/dddt-8-2121Fig2.jpg

Figure 2 Curcumin decreased monomeric TTR by promoting autophagy.

Protective effect of curcumin on TTR Y114C could be partially blocked by 3-MA

To further validate whether the decrease in monomer by curcumin in our experiments was mediated by autophagy, 3-MA, an inhibitor of autophagosome formation, was implied to negatively regulate autophagy. 3-MA (1 mM) was added to the cell culture medium 2 hours before curcumin and incubated for 24 hours. Analysis of LC3, tetrameric TTR, and monomeric TTR from TTR Y114C revealed that 3-MA partly reversed the LC3 II activation induced by curcumin and increased the monomer of TTR Y114C (Figure 3). These results confirm that curcumin induced the decrease in the TTR Y114C monomer by promoting the autophagy pathway.

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4222630/bin/dddt-8-2121Fig3.jpg

Figure 3 Protective effect of curcumin on TTR Y114C could be partially blocked by 3-MA.

Discussion

TTR FAP is a severe autosomal dominant inherited disease, for which the treatment options are limited. Liver transplantation performed early in the course of the disease is the only therapeutic strategy known to stabilize this neuropathy.1,13 More recently, tafamidis meglumine, a potent inhibitor of misfolding and deposition of mutated TTR, has completed an 18-month, placebo-controlled Phase II/III clinical trial for the treatment of FAP.14 However, in June 2012, the US Food and Drug Administration Peripheral and Central Nervous System Drugs Advisory Committee rejected this drug, stating a lack of convincing data supporting its efficacy.15 Hence, it is important to identify the pathogenetic mechanism of FAP to find an alternative effective treatment strategy.

Accumulating studies focused on the TTR mutation gene and protein have provided insights into the pathogenesis of TTR FAP, including decreased stability of TTR tetramers, conformational change in the crystal structure of variant TTR, altered kinetics of denaturation, and disturbing endoplasmic ER quality control system.1,1618 Previous studies have demonstrated that increased levels of ER stress are correlated with extracellular TTR deposition. Two ER stress markers, BiP and p-eIF2α, have been observed to be present and upregulated in the salivary gland tissue of FAP patients.3 However, the precise molecular mechanisms underlying TTR FAP and its phenotypic heterogeneity are not yet fully understood.

Our current study investigated whether the two mutations, TTR Y114C and TTR V30M, share the same pathogenesis and evaluated the effect of pathogenic mutations on the clearance of the monomer. Our results show that the ratio of LC3-II/I was markedly decreased, while BiP and p-eIF2α levels remained constant in TTR Y114C when compared with wild-type TTR and TTR 30M. The results of our research indicate the impaired autophagy contributed to the TTR Y114C mutation, but not ER stress. This observation indicates that abnormal accumulation of TTR caused by a different mutation might be cleared by different pathways, and more studies are necessary to confirm whether this difference applies to other TTR mutations.

Curcumin is known to have neuroprotective properties through a variety of mechanisms.811 Our research indicates that curcumin decreased the monomeric TTR by promoting autophagy, and without toxic effects. Moreover, this protective effect of curcumin on TTR Y114C could be partially blocked by 3-MA. Pullakhandam et al showed that curcumin binds to wild-type TTR and prevents urea-induced perturbations in the tertiary structure of TTR in vitro.19 Recently, Ferreira et al reported that dietary curcumin modulated TTR amyloidogenicity.20 Therefore, curcumin might be an effective therapy for FAP involving multiple molecular pathways.

Overall, our findings show that abnormal accumulation of TTR caused by different mutations might be cleared in different ways, and curcumin might be an effective therapy for FAP by promoting autophagy. Further studies are necessary to determine whether this phenomenon exists in other TTR mutations.

Stephen Williams, PhD

For PI3K and related inhibitors of PI3K/AKT/mTOR i would refer you to two people who should be in the discussion of this signaling pathway and PI3K/AKT inhibitors used for chemotherapy. The first is Dr. Mien-Chie Hung and the second is Dr. Gordon Mills. They both had been at MD Anderson and developed some of the first inhibitors as well as the earliest discoveries of overactivity of PI3K/AKT in ovarian cancer.
Next the field had never progressed any inhibitors past Stage II as there has been some serious toxicities seen in preclinical phases (most long term tox studies are done after patients are enrolled in phase I).

I would refer to three papers

Discovery of GSK2126458, a Highly Potent Inhibitor of PI3K and the Mammalian Target of Rapamycin http://pubs.acs.org/doi/abs/10.1021/ml900028r

A new mutational AKTivation in the PI3K pathwayhttp://www.researchgate.net/publication/6146395_A_new_mutational_AKTivation_in_the_PI3K_pathway

These will show how inhibitors of certain isoforms of PI3K (namely delta) had to be developed to circumvent some of the severe toxicity seen with the earliest inhibitors (wortmanin and LY294002.

Also
Take your PIK: phosphatidylinositol 3-kinase inhibitors race through the clinic and toward cancer therapy http://mct.aacrjournals.org/content/8/1/1.full

Targeting the phosphoinositide 3-kinase (PI3K) pathway in cancerhttp://www.ncbi.nlm.nih.gov/pmc/articles/PMC3142564/

Development of PI3K Inhibitors in Breast Cancer http://www.onclive.com/publications/contemporary-oncology/2014/November-2014/Development-of-PI3K-Inhibitors-in-Breast-Cancer by Aggerwal nice review

Phosphatidylinositol 3-kinase (PI3K) inhibitors as cancer therapeuticshttp://www.ncbi.nlm.nih.gov/pmc/articles/PMC3843585/ will explain about some of the toxicities and describes the one PI3K that has made it to phase II

Most of them have failed and I believe now are being thought as an adjuvant not front line therapy

Aurelian Udristioiu

Aurelian

Aurelian Udristioiu

Lab Director at Emergency County Hospital Targu Jiu

In experimental models, disrupting the MDM2–p53
interaction restored p53 function and sensitized tumors to
chemotherapy or radiotherapy. (Kojima et al., 2005). This
strategy could be particularly beneficial in treating
cancers that do not harbor TP53 mutations. For example
in hematologic malignancies, such as multiple myeloma,
chronic lymphocytic leukemia (CLL), acute lymphoblastic
leukemia (ALL), acute myeloid leukemia (AML), and
Hodgkin’s disease, the induction of p53 – using a small
MDM2-inhibitor molecule, nutlin-3 – can induce the
apoptosis of malignant cells. Nutlins are a group of cisimidazoline
analogs, first identified by Vassilev et al.
(2004), which have a high binding potency and selectivity
for MDM2. Crystallization data have shown that nutlin-3
mimics the three residues of the helical region of the
trans-activation domain of p53 (Phe19, Trp23 and
Leu26), which are conserved across species and critical
for binding to MDM2 (Wade et al., 2010). Nutlin-3
displaces p53 by competing for MDM2 binding. It has
also been found that nutlin-3 potently induces apoptosis
in cell lines derived from hematologic malignancies,
including AML, myeloma, ALL, and B-cell CLL (Secchiero
et al., 2010).

Stephen J Williams, PhD

Now as far as PKM2 you would want to look at a company called Synta Pharmaceuticals and their inhibitor Elesclomal. elesclomol binds copper ions causing a change in conformation that enables its uptake through membranes and into cells. Elesclomol binds copper in an oxidative, positively charged state called Cu(II). Once inside mitochondria, the elesclomol-Cu(II) complex interacts with the energy production mechanism of the cell, or the electron transport chain. This interaction reduces the copper from Cu(II) to Cu(I), resulting in a cascade of reduction-oxidation, or redox, reactions, that causes a rapid increase of oxidative stress, disruption of mitochondrial energy production, and ultimately, triggering of the mitochondrial apoptosis pathway.

The important part is that it seemed, to prefer tumors which had lower LDH activity, meaning that these tumor cells actually did have a more active electron transport chain than tumors with high LDH (Warburg) and therefore in clinical trials the tumors with lower LDH activity responded more favorably.

http://www.drugs.com/clinical_trials/synta-pharmaceuticals-announces-updated-elesclomol-symmetry-data-presented-melanoma-xiii-8223.html for press release and study results

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Upregulate Tumor Suppressor Pathways

Writer and Curator: Larry H Bernstein, MD, FCAP

 

7.5  Upregulate Tumor Suppressor Pathways

7.5.1 NR4A nuclear receptors are orphans but not lonesome

7.5.2 The interplay of NR4A receptors and the oncogene–tumor suppressor networks in cancer

7.5.3 NLRX1 acts as tumor suppressor by regulating TNF-α induced apoptosis

7.5.4 The Mre11 Complex Suppresses Oncogene-Driven Breast Tumorigenesis and Metastasis

7.5.5 Expression of Stromal Cell-derived Factor 1 and CXCR4 Ligand Receptor System in Pancreatic Cancer

7.5.6 DLC1- a significant GAP in the cancer genome

7.5.7 DLC1 is a chromosome 8p tumor suppressor whose loss promotes hepatocellular carcinoma.

7.5.8 Smad7 regulates compensatory hepatocyte proliferation in damaged mouse liver and positively relates to better clinical outcome in human hepatocellular carcinoma

 

 

7.5.1 NR4A nuclear receptors are orphans but not lonesome

Kurakula K, Koenis DS, van Tiel CM, de Vries CJ.
Biochim Biophys Acta. 2014 Nov; 1843(11):2543-2555
http://dx.doi.org/10.1016/j.bbamcr.2014.06.010

Highlights

  • Nuclear receptors Nur77, Nurr1 and NOR-1 are ‘orphan’ receptors of the NR4A subfamily.
  • The NR4A receptors have no ligands.
  • The known protein–protein interactions of all three NR4A receptors are summarized.
  • Interacting proteins are transcription factors, coregulators or protein kinases.
  • Protein–protein interactions modulate NR4A receptor activity and function.

 

The NR4A subfamily of nuclear receptors consists of three mammalian members: Nur77, Nurr1, and NOR-1. The NR4A receptors are involved in essential physiological processes such as adaptive and innate immune cell differentiation, metabolism and brain function. They act as transcription factors that directly modulate gene expression, but can also form trans-repressive complexes with other transcription factors. In contrast to steroid hormone nuclear receptors such as the estrogen receptor or the glucocorticoid receptor, no ligands have been described for the NR4A receptors. This lack of known ligands might be explained by the structure of the ligand-binding domain of NR4A receptors, which shows an active conformation and a ligand-binding pocket that is filled with bulky amino acid side-chains. Other mechanisms, such as transcriptional control, post-translational modifications and protein–protein interactions therefore seem to be more important in regulating the activity of the NR4A receptors. For Nur77, over 80 interacting proteins (the interactome) have been identified so far, and roughly half of these interactions has been studied in more detail. Although the NR4As show some overlap in interacting proteins, less information is available on the interactome of Nurr1 and NOR-1. Therefore, the present review will describe the current knowledge on the interactomes of all three NR4A nuclear receptors with emphasis on Nur77.
Nur77 in the regulation of endocrine signals and steroid hormone synthesis

Nur77 is expressed in endocrine tissues and in organs that are crucial for steroid hormone synthesis such as the adrenal glands, the pituitary gland and the testes. The first functional NurRE was identified in the promoter of the pro-opiomelanocortin (POMC) gene of pituitary derived AtT-20 cells [2]. Nur77 can bind this NurRE either as a homodimer or as a heterodimer with either one of the other two NR4A receptors Nurr1 and NOR-1. Interestingly, it was shown that these heterodimers enhance POMC gene transcription more potently than homodimers of Nur77 do, suggesting that there is interdependency between the NR4A receptors in activating their target genes [3]. The NurRE sequence in the POMC promoter also partially overlaps with a STAT1-3 response element. Philips et al. showed that Nur77 and STAT1-3 bind simultaneously to this so called NurRE-STAT composite site and synergistically enhance transcription of the POMC gene. However, Nur77 and STAT1-3 do not interact directly, which suggests that oneor more facilitatingfactors are involved in NurRE-STAT driven transcription. Mynard et al. showed that this third factor is cAMP response element binding protein (CREB), which binds both STAT1-3 and Nur77 and indirectly enhances transcription of the POMC gene by facilitating the synergistic activation of the NurRE-STAT composite site by STAT1-3 and Nur77 [4]. Nur77also plays animportant role in the steroidogenic acute regulatory protein (StAR)-mediated testosterone production by Leydig cells. StAR is required for the transport of cholesterol through the mitochondrial membrane to initiate steroid hormone synthesis. Nur77 binds to an NBRE in the StAR promoter, which is in close proximity to an AP-1 response element. In response to cAMP stimulation c-Jun and Nur77 synergistically increase StAR gene expression [5], presumably through a direct interaction between c-Jun and the LBD of Nur77 [6]. On the other hand, c-Jun has also been shown to suppress expression of the hydroxylase P450 c17 gene by blocking the DNA-binding activity o fNur77 in response to stimulation of Leydig cells with reactive oxygen species [7].The effect of c-Jun on the transcriptional activity of Nur77 therefore seems to depend on other factors as well. One of these factors could be the atypical nuclear receptor DAX1 (NR0B1), which lacks a DBD and associates with multiple coregulatory proteins. DAX1 binds Nur77 directly and represses its ability to enhance transcription of the previously mentioned P450 c17 gene.

Fig.1.Schematic representation of the domain structure of nuclear receptors. Nuclear receptors are composed of an N-terminal domain (N-term), a central DNA-binding domain (DBD) and a ligand-binding domain (LBD). The amino acid similarity between the individual domains of Nur77 with Nurr1 and NOR-1 is given in percentages below the domains.

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The interactome of NOR-1

NOR-1 is less well studied than Nur77 and Nurr1 and most of the data on interacting proteins of NOR-1 are presented in studies that are mainly focused on its homologues. As a consequence, NOR-1 protein– protein interactions are described with limited detail, for example the HATp300/CBPacetylatesNOR-1similarlyasNur77,however,theeffect on NOR-1 activity has not been described [79]. Likewise, NOR-1 interacts with the co-regulator TIF1β resulting in enhanced NOR-1 activity, but the domain involved in the interaction is unknown [48]. Similar to Nur77, PKC and RSK1/2 were shown to induce NOR-1 mitochondrial translocation [73,79] and DNA-PK binds the DBD of NOR-1. Even though Nurr1 and Nur77 are both essential for optimal DSB repair the function of NOR-1 in this process remains to be studied [68]. Both FHL2 and the peptidyl-prolyl isomerase Pin1 bind the N-terminal domain and DBD of NOR-1, resulting in reduced or enhanced transcriptional activity of NOR-1, respectively [59,64]. Muscat and co-workers performed detailed studies to identify coregulatorsofNOR-1andwerethefirsttorevealtheabsenceofaconventional ligand-binding pocket in the LBD of NOR-1, through molecular modeling and hydrophobicity analysis of the LBD [104]. Based on these analyses, the relative importance of the N-terminal domain of NOR-1 in regulation of the transcriptional activity of NOR-1 became apparent and direct interaction of a number of crucial co-regulators to this domain was shown;SRC-2 (GRIP-1), SRC-1, SRC-3, p300, DRIP250/ TRAP220 and PCAF [104]. The interaction between the N-terminal domain of NOR-1 and TRAP220 is independent of PKA- and PKC phosphorylation sites in TRAP220. Most interestingly, the purine derivative 6-mercaptopurine, which enhances the activity of NR4As without directly binding these nuclear receptors promotes the interaction between NOR-1 and TRAP220 [105]. Both Nur77 and NOR-1 are involved in T-cell receptor mediated apoptosis of developing T cells [106]. During activation of T cells the expressionofNOR-1isinducedandproteinkinaseC(PKC)becomesactive.NOR-1is aPKCsubstratethat isphosphorylatedand subsequently translocatesfromthenucleustothemitochondriawhereitbindsBcl-2. Most interestingly, as already indicated above the interaction between NOR-1/Nur77 and Bcl-2 causes a conformational change in Bcl-2 allowing its BH3 domain to be exposed, resulting in the conversion of Bcl-2 from an anti-apoptotic into a pro-apoptotic protein. For Nur77 it is exactly known which amino acids are involved to provoke the functional switchin Bcl-2, whichis not thecasefor NOR-1 [57,79]. Initially, the homeobox domain containing protein Six3 was identified in a yeast-two-hybrid study as a protein that interacts uniquely withtheDBDandLBDofNOR-1withoutbindingorinhibitingtheactivity of Nur77 or Nurr1. Of interest, NOR-1 and Six3 show overlap in expression in the rat fetal forebrain on embryonic day 18 [107]. In a later study this specificity of Six3 forNOR-1 was not found, rather interaction with all three NR4As was observed [108]. NOR-1 is part of the EWS/NOR-1 fusion protein that is expressed in human extraskeletal myxoid chondrosarcoma tumors. Six3 enhances the activity of NOR-1 (and Nur77 and Nurr1), whereas the activity of EWS/NOR-1 is inhibited and the interaction only requires the DBD of NOR-1. The opposing data in these two studies may be explained by the use of different cell types for the activity assays, as well as the use of Gal4-fusion proteins in the latter study. PARP-1 specifically and effectively interacts with theDBD of NOR-1 independent of the enzymatic activity of PARP-1 [69]. Nurr1 interacts with lower affinity, whereas EWS/NOR-1 and Nur77 do not bind PARP-1, unless the N-terminal domain of Nur77 is deleted. The latter experiment nicely illustrates that the N-terminal domains of Nur77 and EWS/NOR-1 disturb PARP-1 interaction with the DBD. This may be the underlying mechanism of differential function of NOR-1 and the EWS/NOR-1 fusion protein. In line with the binding characteristics, PARP-1 only inhibits the activity of NOR-1 effectively, again independently of the ribose polymerase activity of PARP-1.

Table 5 NOR-1 interacting proteins.

Fig.2. Nur77 and its interacting proteins. Schematic overview of the protein–protein interactions with Nur77 for which the domains of interaction have been elucidated. Details are described in the text and in Tables 1–3, which also contain the full names of the indicated proteins. N-term, N-terminal domain; DBD, DNA-binding domain; LBD, ligand-binding domain.

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Fig.3. Nur77 and kinases modulating its activity and localization. A, Overview of the amino-acid sequence of Nur77 with known phosphorylation sites and associated kinases indicated (T= threonine,S= serine). B,Schematic illustration of effects of different kinases on Nur77 transcriptional activity and subcellular localization. See Table3 for definitions of the abbreviations of the kinases shown.

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Discussion and concluding remarks
This review summarizes the currently available knowledge on the protein–protein interactions of the NR4A nuclear receptor family and their downstream effects. When looking at the information gathered in this review three main observations can be made. First, there are a large number of protein–protein interactions that regulate the activity of Nur77 and there is a large variation in the effects of these interactions on the ‘target’ protein, be it Nur77 or the interacting protein itself. These effects include modulation of transcriptional activity, protein stability, post-translational modification and cellular localization: all processes that are tightly regulated by ligand binding in other nuclear receptors. In light of the many interactions it undergoes with other proteins, Nur77 could also be considered to be a molecular ‘chameleon’: a protein that selectively adopts the responsiveness of other proteins by directly interacting with them. Secondly, the protein–protein interactions with Nur77 described in this review have been studied in a wide range of cell types, such as immune cells (T-cells, thymocytes, monocytes and macrophages); somatic cells(neurons,smooth muscle cells,endothelial
cells and hepatocytes) and cancer cells from diverse origins.We reason that a stimulus- and cell type-specific expression pattern of interacting proteins may be decisive in determining both the interactions of NR4 As with other proteins and their activity in general.The well-studied interaction between Nur77 and RXRα, which has unique outcomes depending on both the cell type studied and the stimulus used, is one such interaction that is modulated by stimulus- or cell type- specific auxiliary proteins. Lastly, there is a large amount of overlap in interacting proteins between the three NR4A nuclear receptors. All three domains of the NR4As are involved in interactions with other proteins (Tables 1–5, Fig. 2), and we think that the unstructured N-terminal domains are of special interest as they have the lowest overall amino acid similarity (Fig. 1). Based on this dissimilarity, it could be hypothesized that the N-terminal domain of each NR4A receptor interacts with a unique set of proteins that specifically regulates each of their activities, if it were not for the fact that this review has shown that the interacting partners of the NR4As strongly overlap. However, a closer look at the N-terminal domains of Nur77, Nurr1 and NOR-1 reveals small stretches of relatively high similarity within the amino acid sequences (Fig. 4). The possible importance of these small stretches of high similarity is most readily apparent when looking at phosphorylation sites of the NR4As.

Fig. 4. Amino-acid sequence similarity between the N-terminal domains of the NR4A receptors. The amino-acid sequence of the N-terminal domains of Nur77, Nurr1 and NOR-1 was aligned and the extent of sequence similarity is indicated with colors; e.g. blue indicates the regions where the sequence of the three NR4As is identical. In the Nur77 sequence, the CHEK2 target Thr88, the JNK1 target Ser95, the ERK2 target Thr143, the CK2 target Ser152, and the DNA-PK target Ser164 are indicated with arrows. In the Nurr1 sequence, the ERK2 targets Ser126 and Thr132, and the ERK5 targets Thr168 and Ser177 are indicated with arrows.

 

 

7.5.2 The interplay of NR4A receptors and the oncogene–tumor suppressor networks in cancer

Beard JA, Tenga A, Chen T
Cell Signal. 2015 Feb; 27(2):257-66
http://dx.doi.org/10.1016/j.cellsig.2014.11.009

Highlights

  • The expression and function of NR4As are dysregulated in multiple cancer types.
  • NR4As are positively regulated by oncogenic signaling pathways.
  • NR4As are capable of inhibiting tumor suppressor signaling.
  • The connectedness of NR4As with these pathways mediate their functions in cancer.
  • NR4A agonists and antagonists offer therapeutic strategies for cancer treatment.

Abstract

Nuclear receptor (NR) subfamily 4 group A (NR4A) is a family of three highly homologous orphan nuclear receptors that have multiple physiological and pathological roles, including some in cancer. These NRs are reportedly dysregulated in multiple cancer types, with many studies demonstrating pro-oncogenic roles for NR4A1 (Nur77) and NR4A2 (Nurr1). Additionally, NR4A1 and NR4A3 (Nor-1) are described as tumor suppressors in leukemia. The dysregulation and functions of the NR4A members are due to many factors, including transcriptional regulation, protein-protein interactions, and post-translational modifications. These various levels of intracellular regulation result from the signaling cross-talk of the NR4A members with various signaling pathways, many of which are relevant to cancer and likely explain the family members’ functions in oncogenesis and tumor suppression. In this review, we discuss the multiple functions of the NR4A receptors in cancer and summarize a growing body of scientific literature that describes the interconnectedness of the NR4A receptors with various oncogene and tumor suppressor pathways.

NR4As are positively regulated by oncogenic signaling pathways

NR4A subfamily of nuclear receptors

NR4A subfamily of nuclear receptors

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intracellular regulation result from the signaling cross-talk of the NR4A members

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7.5.3 NLRX1 acts as tumor suppressor by regulating TNF-α induced apoptosis

Singh K, Poteryakhina A, Zheltukhin A, …Chumakov PM, Singh R.
Biochim Biophys Acta. 2015 May; 1853(5):1073-86
http://dx.doi.org/10.1016/j.bbamcr.2015.01.016

Highlights

  • NLRX1 sensitizes cancer cells to TNF induced cell death by regulating Caspase-8.
  • NLRX1 localizes to mitochondria (mt) and regulates TNF induced mt-ROS generation.
  • Mitochondrial association of Caspase-8 with NLRX1 may regulate mt-ETC function.
  • NLRX1 expression in cancer cells suppresses tumorigenicity in nude mice.

Chronic inflammation in tumor microenvironment plays an important role at different stages of tumor development. The specific mechanisms of the association and its role in providing a survival advantage to the tumor cells are not well understood. Mitochondria are emerging as a central platform for the assembly of signaling complexes regulating inflammatory pathways, including the activation of type-I IFN and NF-κB. These complexes in turn may affect metabolic functions of mitochondria and promote tumorigenesis. NLRX1, a mitochondrial NOD-like receptor protein, regulate inflammatory pathways, however its role in regulation of cross talk of cell death and metabolism and its implication in tumorigenesis is not well understood. Here we demonstrate that NLRX1 sensitizes cells to TNF-α induced cell death by activating Caspase-8. In the presence of TNF-α, NLRX1 and active subunits of Caspase-8 are preferentially localized to mitochondria and regulate the mitochondrial ROS generation. NLRX1 regulates mitochondrial Complex I and Complex III activities to maintain ATP levels in the presence of TNF-α. The expression of NLRX1 compromises clonogenicity, anchorage-independent growth, migration of cancer cells in vitro and suppresses tumorigenicity in vivo in nude mice. We conclude that NLRX1 acts as a potential tumor suppressor by regulating the TNF-α induced cell death and metabolism.

 

7.5.4 The Mre11 Complex Suppresses Oncogene-Driven Breast Tumorigenesis and Metastasis

Gupta GPVanness KBarlas AManova-Todorova KOWen YHPetrini JH
Mol Cell. 2013 Nov 7;52(3):353-65
http://dx.doi.org/10.1016%2Fj.molcel.2013.09.001

The DNA damage response (DDR) is activated by oncogenic stress, but the mechanisms by which this occurs, and the particular DDR functions that constitute barriers to tumorigenesis, remain unclear. We established a mouse model of sporadic onco-gene-driven breast tumorigenesis in a series of mutant mouse strains with specific DDR deficiencies to reveal a role for the Mre11 complex in the response to oncogene activation. We demonstrate that an Mre11-mediated DDR restrains mammary hyperplasia by effecting an oncogene-induced G2 arrest. Impairment of Mre11 complex functions promotes the progression of mammary hyperplasias into invasive and metastatic breast cancers, which are often associated with secondary inactivation of the Ink4a-Arf (CDKN2a) locus. These findings provide insight into the mechanism of DDR engagement by activated oncogenes and highlight genetic interactions between the DDR and Ink4a-Arf pathways in suppression of oncogene-driven tumorigenesis and metastasis.

The DNA damage response (DDR) network comprises DNA repair, DNA damage signaling, apoptosis, and cell-cycle checkpoint functions (Ciccia and Elledge, 2010). Two lines of evidence support the view that the DDR is a barrier to tumorigenesis. Mutations affecting components of the DDR are frequently associated with predisposition to cancer (Ciccia and Elledge, 2010). Also, indices of DDR activation are evident in preneoplastic lesions or in cultured cells harboring activated oncogenes (Bart-kova et al., 2005Gorgoulis et al., 2005). Despite supportive genetic data from in vitro and tumor inoculation studies (Bartkova et al., 2006;Di Micco et al., 2006), causal demonstration that the oncogene-induced DDR suppresses tumorigenesis within a tissue context remains limited (Gorrini et al., 2007Squatrito et al., 2010Takacova et al., 2012). In certain contexts, the role for ataxia telangiectasia mutated (ATM) in suppressing onco-gene-driven tumorigenesis was relatively minor, although these mouse models were limited by the fact that ATM−/− mice are prone to early spontaneous lymphomagenesis (Efeyan et al., 2009).

The mechanism for DDR activation in response to oncogene expression remains incompletely understood, but the prevailing view posits that oncogene activation leads to replication stress in the form of stalled, and subsequently collapsed, DNA replication forks (Halazonetis et al., 2008). Analysis of the ATRSeckel mouse has indicated that ATR may be required for cell viability upon oncogene activation, suggesting that DNA replication stress may indeed underlie these effects of oncogene activation (López-Contreras et al., 2012;Murga et al., 2011Schoppy et al., 2012). However, since ATR promotes viability, rather than elimination of the oncogene-expressing cells, this outcome is not consistent with a barrier function for that component of the DDR. The purpose of this study was to delineate the particular aspects of the DDR network that constitute barriers to oncogenesis using a mouse model of sporadic, oncogene-driven breast cancer.

The Mre11 complex is a sensor of DNA double-strand breaks (Stracker and Petrini, 2011). Hypomorphic mutations in this complex, modeled in the mouse after alleles inherited in ataxiatelangiectasia-like disorder (A-TLD) and Nijmegen breakage syndrome (NBS), have facilitated the elucidation of the Mre11 complex’s role in the ATM-dependent DDR. Here, we utilize these and other mutant mouse strains, individually and in combination, to define the tumor-suppressive functions of the DDR in mammary epithelium.

A Mouse Model of Sporadic, Oncogene-Induced Mammary Neoplasia

Expression of activated NeuT (Bargmann and Weinberg, 1988), the rodent ortholog of the ERBB2/HER2oncogene, in the mammary epithelium of adult mice via the RCAS/MMTVTVA system (Du et al., 2006) results in early DDR activation, and oligoclonal tumors with an average latency of 5 months (Reddy et al., 2010). To delineate the aspects of the DDR primarily relevant for tumor suppression in the face of oncogene activation, we interbred MMTV-TVA mice with a variety of mutant mouse strains with established DDR deficiencies. Age-matched cohorts of female animals (12–18 weeks old) were injected with either RCAS-HA-NeuT or control virus via mammary intraductal injection. The genotypes analyzed wereMre11ATLD1/ATLD1Nbs1ΔBBChk2−/−Nbs1ΔCChk2−/−p53515C/515Cp53−/−, and 53BP1−/−, each of which exhibits defects in DNA-damage-induced cell-cycle checkpoint activation, apoptosis, and/or DNA repair (Figures S1A and S1B available online; Liu et al., 2004Shibata et al., 2010Stracker et al., 20072008Stracker and Petrini, 2011Theunissen et al., 2003Williams et al., 2002). These mouse strains did not exhibit any histopathological deficits in mammary gland development (data not shown), circumventing the potential problem of differences in mammary tissue among the various genetic backgrounds confounding the analyses.

We performed digital quantification of glandular structures relative to total cellular content in the oncogene-expressing mammary glands and normalized this value to the glandular content observed in the matched control mammary glands (Figure 1C). These variations in mammary ductal enlargement, luminal filling, cellular turnover, and glandular density across the different genotypes are summarized in Figure 1D.

NeuT expression in Chk2−/− and Nbs1ΔCChk2−/− mammary epithelium produced hyperplasias that were only modestly dissimilar from WT (Figures 1B–1D; data not shown), suggesting that apoptosis and the intra-S phase checkpoint—diminished in both mutants (Stracker et al., 2008)—do not mediate the early response to oncogene activation. Consistent with that interpretation, p53515C/515C mutants, in which p53-dependent apoptosis is lost (Liu et al., 2004), also exhibited relatively modest hyper-plasia, although some morphological changes were noted (Figures 1B–1D). In contrast, p53−/− mammary glands resembled p53515C/515C morphologically, but exhibited more extensive NeuT-induced hyperplasia (Figures 1B–1D), consistent with additional deficiencies of the null mutant—including, but not limited to, induction of the G1/S checkpoint and senescence pathways.

In contrast to the aforementioned genotypes, oncogene-induced hyperplasia was markedly distinct in Mre11ATLD1/ATLD1 and Nbs1ΔBB mammary glands relative to WT mammary glands (Figures 1B–1D). The Mre11 complex mutant genotypes exhibited florid hyperplasia in response to oncogene expression that frequently filled the lumen of the enlarged mammary ducts. Quantification of hyperplasia across the entire mammary gland revealed that Mre11ATLD1/ATLD1 was associated with the most significant degree of oncogene-induced proliferative change (Figure 1C).

We examined oncogene-dependent activation of the DDR in WT and Mre11ATLD1/ATLD1 mammary hyperplasias. Consistent with prior reports (Reddy et al., 2010), we observed the formation of γH2AX foci and accumulation of 53BP1 nuclear staining in WT hyperplasias after the introduction of NeuT (Figures 2A and 2B). We observed a highly significant, >2-fold reduction in both NeuT-induced γH2AX foci formation and 53BP1 accumulation within Mre11ATLD1/ATLD1 lesions relative to WT (p < 0.0001; Figures 2A and 2B). In contrast to the effects of Mre11 complex hypomorphism, oncogene-dependent DDR activation was unperturbed in p53−/− mammary glands (Figure 2A; data not shown). These data demonstrate that the Mre11 complex is required for DDR activation upon NeuT expression.

The oncogene-driven, Mre11 complex-dependent DDR exhibited dissimilarities from that induced by ionizing radiation (IR). First, oncogene expression in the WT mammary gland resulted in finely punctate 53BP1 staining and did not induce the large foci that develop after irradiation of the mammary gland (Figure S4). In addition, phosphorylation of the ATM target KAP1 at Ser824 was not observed in the oncogene-expressing mammary gland, but was readily detected in IR-treated mammary tissue (Figure 2C). Similarly, we observed significantly less p53 stabilization in mammary epithelial cells after oncogene expression in comparison to irradiated tissue (Figure S4). Hence, the Mre11 complex-mediated response to oncogene activation appears to be qualitatively distinct from the response to clastogen-induced DNA damage.

We examined apoptosis and growth arrest—functional outcomes of DDR activation—in hyperplastic lesions. While NeuT expression was associated with increased proliferation and apoptosis rates relative to control mammary glands, we did not observe a statistically significant difference in TUNEL or Ki67 positivity between WT and Mre11ATLD1/ATLD1 oncogene-induced hyperplasias (Figures 3A and 3B). We observed a 4-fold increase in pHH3-S10 staining in WT versus Mre11ATLD1/ATLD1 hyperplasias (p < 0.001; Figure 3C), which was unexpected given the significantly increased cellularity of Mre11ATLD1/ATLD1 hyperplasias. The pHH3-S10 staining pattern that we observed was punctate, and pHH3-S10-positive nuclei did not exhibit morphological features of mitosis (Figure 3C, inset), suggesting that the pHH3-S10 signal represented pericentromeric staining characteristic of late G2 cells rather than mitotic cells.

Centriole duplication was evident in 84% of pHH3-S10-positive cells, compared to only 16% of pHH3-S10-negative cells (p < 0.0001; Figure 4B), indicating a cell-cycle state that is beyond the G1/S transition. These observations collectively suggest that NeuT expression in mammary epithelium activates a Mre11 complex-dependent G2 arrest or accumulation. Notably, this G2 arrest is distinct from the canonical IR-induced G2/M checkpoint, which is also Mre11 dependent (Theunissen et al., 2003). In that context, pHH3-S10 is not induced, suggesting that the heterochromatin-associated accumulation of this marker is oncogene specific.

The variable and prolonged latency of tumor onset in Mre11ATLD1/ATLD1 animals suggests that additional genetic alterations may be required for NeuT-mediated transformation of mammary epithelial cells. We examined p19Arf expression—a well-established oncogene-induced tumor-suppressive pathway (Sherr, 2001)—in the 3-week-old NeuT-expressing mammary hyperplasias from WT and Mre11ATLD1/ATLD1animals. We observed >10-fold induction of p19Arf after oncogene expression in Mre11ATLD1/ATLD1relative to control-injected mammary glands (Figure 6A). The extent of p19Arf induction in NeuT-expressingWT mammary glands was <50% of that observed in Mre11ATLD1/ATLD1 (p < 0.007, Figure 6A). Notably, there was no difference in HA-NeuT expression levels between the WT and Mre11ATLD1/ATLD1 mice that could account for the elevated levels of p19Arf (Figure S6A). As expected, p53 levels were modestly elevated in Mre11ATLD1/ATLD1 hyperplasias relative to WT (Figure S6B).

Collectively, the findings presented here indicate that the Mre11 complex constitutes an inducible barrier to oncogene-driven neoplasia. In response to oncogene activation, the Mre11 complex mediates a G2 arrest that appears to be qualitatively distinct from that revealed in previous analyses of Mre11 complex-dependent DDR functions (Figure 7EStracker et al., 2004). The arrest is associated with heterochromatin changes, including the appearance of macroH2A and histone H3 (Ser10) phosphorylation. Histone H3 phosphorylation at pericentric heterochromatin begins early in G2 phase and expands as cells enter mitosis (Crosio et al., 2002). That fact, along with the finding that H3 phosphorylation arises in cells that have undergone centriole duplication, indicates that cells in oncogene-expressing hyperplasias accumulate in G2. We cannot exclude the possibility that other NeuT-expressing cells also arrest in G1 without the observed heterochromatic changes. In Mre11ATLD1/ATLD1 mammary epithelium, the NeuT-induced arrest is lost, and macroH2A and histone H3 phosphorylation are not detected in hyperplastic tissue, demonstrating that the G2 accumulation depends on the Mre11 complex.

The Mre11 complex-dependent G2 arrest does not appear permanent, as WT cells are capable at low frequency of progressing to tumors. When the arrest is attenuated, as in Mre11ATLD1/ATLD1, we observe more extensive oncogene-induced mammary hyperplasia, and a significantly greater likelihood of progression to invasive breast cancer. Although previous studies show that the Mre11 complex suppresses genome instability, and thus the risk of spontaneous DNA-damage-associated tumorigenesis (Stracker et al., 2008Theunissen et al., 2003), this study demonstrates that the Mre11 complex also suppresses oncogene-driven neoplasia and tumorigenesis.

An important question concerns the underlying basis of the response to oncogene activation. Given the importance of the Mre11 complex in sensing DNA double-strand breaks and initiating an ATM-dependent DDR, a parsimonious interpretation is that oncogene activation results in DNA damage. Indeed, there are compelling genetic data supporting the induction of DNA replication stress upon oncogene activation (Bartkova et al., 2006Campaner and Amati, 2012Di Micco et al., 2006Dominguez-Sola et al., 2007;López-Contreras and Fernandez-Capetillo, 2010). DNA replication stress is a common precursor of frank DNA damage when forks collapse (Allen et al., 2011), which would readily account for the induction of DNA damage upon oncogene induction.

Potential crosstalk between the oncogene-induced DDR and the Arf tumor suppressor pathways has recently been described (Evangelou et al., 2013Monasor et al., 2013Velimezi et al., 2013). Our data provide direct evidence for a genetic interaction between these pathways during oncogene-driven tumorigenesis. We demonstrate that when Mre11 complex function is impaired, oncogene expression induces Arf expression, and Ink4a-Arf inactivation is commonly observed in the mammary tumors that ensue. The mechanism for how Mre11 hypomorphism promotes oncogene-induced Arf expression remains unclear.  We observe that 40% of the NeuT-induced mammary tumors that developed in Mre11ATLD1/ATLD1 mice had genetic inactivation of the Ink4a-Arf locus, and the remaining tumors exhibited reduced p19Arf expression, suggesting alternative modes of pathway suppression. These findings provide compelling genetic evidence for the cooperative roles of the Mre11 complex and Ink4a-Arf pathways in the suppression of oncogene-driven tumorigenesis and metastasis.

The behavior of the emergent tumors in Mre11ATLD1/ATLD1mice suggests a link between increased chromosomal instability and an elevated rate of metastatic dissemination from the primary tumor. The observation that all of the Ink4a-Arf mutated mammary tumors were lung metastatic also raises the possibility that Arf loss promotes metastatic progression in the context of Mre11 complex impairment.

Our genetic data suggest that functional hypomorphism of this pathway may be a driver of breast tumorigenesis, genomic instability, and metastasis. Given the profound DDR defects associated with Mre11 complex hypomorphism (Stracker and Petrini, 2011), this subset of human breast cancer may exhibit exquisite DNA damage sensitivities that could be therapeutically exploited to improve clinical outcomes.

 

 

7.5.5 Expression of Stromal Cell-derived Factor 1 and CXCR4 Ligand Receptor System in Pancreatic Cancer

Koshiba T, Hosotani R, Miyamoto Y, Ida J, …, Fujii N, Imamura M
Clin Cancer Res Sep; 6(9):3530-5
NR4A subfamily of nuclear receptors
http://clincancerres.aacrjournals.org/content/6/9/3530.long

To examine the expression of the stromal cell-derived factor 1 (SDF-1)/CXCR4 receptor ligand system in pancreatic cancer cells and endothelial cells, we performed immunohistochemical analysis for 52 pancreatic cancer tissue samples with anti-CXCR4 antibody and reverse transcription-PCR analysis for CXCR4 and SDF-1 in five pancreatic cancer cell lines (AsPC-1, BxPC-3, CFPAC-1, HPAC, and PANC-1), an endothelial cell line (HUVEC), and eight pancreatic cancer tissues. We then performed cell migration assay on AsPC-1 cells, HUVECs, and CFPAC-1 cells in the presence of SDF-1 or MRC-9 fibroblast cells. Immunoreactive CXCR4 was found mainly in pancreatic cancer cells and endothelial cells of relatively large vessels around a tumorous lesion. The immunopositive ratio in the pancreatic cancer was 71.2%. There was no statistically significant correlation with clinicopathological features. SDF-1 mRNA expressions were detected in all pancreatic cancer tissues but not in pancreatic cancer cell lines and HUVECs; meanwhile, CXCR4 mRNA was detected in all pancreatic cancer tissues, cancer cell lines, and HUVECs. The results indicate that the paracrine mechanism is involved in the SDF-1/CXCR4 receptor ligand system in pancreatic cancer. In vitro studies demonstrated that SDF-1 significantly increased the migration ability of AsPC-1 and HUVECs, and these effects were inhibited by CXCR4 antagonist T22, and that the coculture system with MRC-9 also increased the migration ability of CFPAC-1 cells, and this effect was significantly inhibited by T22. Our results suggested that the SDF-1/CXCR4 receptor ligand system may have a possible role in the pancreatic cancer progression through tumor cell migration and angiogenesis.

Chemokines belong to the small molecule chemoattractive cytokine family and are grouped into CXC chemokines and CC chemokines, on the basis of the characteristic presence of four conserved cysteine residues (123) . Chemokines mediate the chemical effect on target cells through G-protein-coupled receptors, which are characterized structurally by seven transmembrane spanning domains and are involved in the attraction and activation of mononuclear and polymorphonuclear leukocytes. The effects of CXC chemokines on cancer cells have been investigated in the case of IL3 -8. Several studies have demonstrated the presence of IL-8 and its receptor in tumor tissues, which were involved in vascular endothelial cell proliferation and tumor neovascularization ,(4567) . It was also reported that IL-8 inhibited non-small cell lung cancer proliferation via the autocrine and paracrine pathway (8) . IL-8 produced by malignant melanoma was found to induce cell proliferation via the autocrine pathway in vitro (9) . These studies indicate that IL-8 is involved in the regulation of tumor progression through tumor angiogenesis and/or direct cancer cell growth.

SDF-1 was initially cloned by Tashiro et al. (10) and later identified as a growth factor for B cell progenitors, a chemotactic factor for T cells and monocytes, and in B-cell lymphopoiesis and bone marrow myelopoiesis (111213) . SDF-1 is a member of the CXC subfamily of chemokines, and its chemotactic effect is mediated by the chemokine receptor CXCR4 (12 , 14) . Most of the chemokine receptors interact with pleural ligands, and vice versa, but the SDF-1/CXCR4 receptor ligand system has been shown to involve a one-on-one interaction (15 , 16) . Furthermore, CXCR4 has been shown to function as a coreceptor for T lymphocytotrophic HIV-1 isolates (17) . Recent studies have demonstrated that endothelial cells express CXCR4 and are strongly chemoattracted by SDF-1 (1819,20) . Tachibana et al. (15) reported that in the embryo of CXCR4 or SDF-1 knockout mice larger branches of the superior mesenteric artery were missing and that the resultant abnormal circulatory system led to gastrointestinal hemorrhage and intestinal obstruction. These findings suggest that SDF-1 and CXCR4 are involved in organ vascularization, as well as in the immune and hematopoietic system.

To clarify the role of the SDF-1/CXCR4 receptor ligand system in pancreatic cancer, we have investigated the expression of CXCR4 and SDF-1 with the aid of immunohistochemical analysis and RT-PCR in pancreatic cancer tissue and experimental chemotactic activity of SDF-1 in pancreatic cancer cells and vascular endothelial cells in vitro.

The distribution of CXCR4 protein expression in pancreatic cancer tissue was examined by means of immunohistochemical analysis of pancreatic cancer tissue samples obtained at surgical operation. Fig. 1<$REFLINK> shows representative immunostainings of cancerous and noncancerous regions in pancreatic cancer tissues. Staining of the CXCR4 protein was identified in the cytoplasm and/or cell membrane of cancer cells, but was not detected in the normal acinar cells and ductal cells of noncancerous region in pancreatic cancer tissue. Negative or weak staining for the CXCR4 protein was observed in a majority of the infiltrating inflammatory cells in the specimens. The immunopositive ratio of cancer cells in the pancreatic cancer tissue specimens was 71.2% (37 of 52). Table 1<$REFLINK>summarizes the relationship between CXCR4 expression and clinicopathological features of 52 pancreatic cancers. There was no significant correlation between the expression of CXCR4 protein and the clinicopathological variables examined (i.e., tumor extension, lymph node metastasis, liver metastasis, and Union International Contre Cancer stage). CXCR4 immunoreactivities were observed in endothelial cells of relatively large vessels around the tumorous lesions, but were scarcely found in the endothelial cells of microvessels inside tumorous lesions (Fig. 2, A and B)<$REFLINK> .

We performed RT-PCR using specific primers, as described in“ Materials and Methods,” to confirm CXCR4 and SDF-1 mRNA expression in pancreatic cancer cells, endothelial cells (HUVECs), and pancreatic cancer tissues. CXCR4 mRNA expressions were clearly detected in five pancreatic cancer cell lines, HUVECs, and eight pancreatic cancer tissue samples (Fig. 3a)<$REFLINK> . On the other hand, SDF-1 mRNA expression was not detected in five pancreatic cancer cell lines and HUVECs, but was identified in eight pancreatic cancer tissue samples (Fig. 3b)<$REFLINK> .

Transwell migration assays were performed to examine the effects of SDF-1 on motility of pancreatic cancer cells (AsPC-1) and endothelial cells (HUVEC). At a concentration of 100 ng/ml, SDF-1 induced chemotaxis of AsPC-1 cells, which was approximately double that of the control. One micromolar of T22 (CXCR4 antagonist) and 10 μg/ml of IVR7 (neutralizing CXCR4 antibody) completely blocked the chemotaxis of AsPC-1 induced by 100 ng/ml SDF-1 (Fig. 4a)<$REFLINK> . At a concentration of 100 g/ml SDF-1 induced an approximately quadruple chemotaxis of HUVECs. One micromolar of T22 caused a 33% reduction of the chemotaxis of HUVECs in the presence of containing 100 ng/ml SDF-1 (Fig. 4b)<$REFLINK> .

SDF-1 belongs to the CXC chemokine family and is a ligand for CXCR4. The role of the SDF-1/CXCR4 receptor ligand system has been investigated mainly in the field of immunology, especially in the mechanism of infection of T lymphocytotrophic HIV-1 and for the prevention of HIV-1 infection. Investigators have also paid attention to the role of the SDF-1/CXCR4 receptor ligand system in cancer tissues.

In this study, we first used immunohistochemical methods to examine CXCR4 expression in pancreatic cancer tissues. Immunoreactive CXCR4 was found in the cytoplasm and/or cell membrane of pancreatic cancer cells. Although CXCR4 staining in pancreatic cancer tissue was heterogeneous and showed differences between specimens, it was found mainly in cancer cells: the immunopositive ratio for the pancreatic cancer tissue specimens was 71.2% (37 of 52). There was a tendency for the immunopositive ratio of CXCR4 in tumors with lymph node metastasis or liver metastasis to be higher than in tumors without these features, but no statistically significant correlation with clinicopathological features were found. There is a diversity of views on the role of the SDF-1/CXCR4 receptor ligand system in malignant tissues. In the current study, SDF-1 mRNA expressions were detected in all pancreatic cancer tissues (eight of eight) but were not detected in pancreatic cancer cell lines (zero of five), whereas CXCR4 mRNA was detected in both pancreatic cancer tissues (eight of eight) and cancer cell lines (five of five). The results indicate that the paracrine mechanism may be involved in the SDF-1/CXCR4 receptor ligand system in pancreatic cancer.

Our results suggest that the SDF-1/CXCR4 receptor ligand system may have a possible role in the pancreatic cancer progression through tumor cell migration and angiogenesis. Because T22 suppressed the migration of both pancreatic cancer cells and endothelial cells in vitro, additional in vivo studies are warranted to examine whether T22 suppresses the tumor spread and tumor angiogenesis to clarify the role of the SDF-1/CXCR4 receptor ligand system in pancreatic cancer.

 

7.5.6 DLC1- a significant GAP in the cancer genome

Aurelia Lahoz and Alan Hall
Genes Dev. 2008 Jul 1; 22(13): 1724–1730
http://dx.doi.org/10.1101.2Fgad.1691408

Rho GTPases are believed to make important contributions to the development and progression of human cancer, but direct evidence in the form of somatic mutations analogous to those affecting Ras has been lacking. A recent study in Genes & Development by Xue and colleagues (1439–1444) now provides in vivo evidence that DLC1, a negative regulator of Rho, is a tumor suppressor gene deleted almost as frequently as p53 in common cancers such as breast, colon, and lung.

Cancer is a complex set of diseases arising from combinations of genetic and epigenetic events, including base mutations, chromosomal rearrangements, DNA methylation, and chromatin modification. Genetic changes were first seen cytologically and revealed gross chromosomal abnormalities, such as translocations, deletions, amplifications (of entire chromosomes or parts of chromosomes), and inversions. Subsequently, DNA sequencing of candidate genes and then whole genomes has uncovered large numbers of more subtle genetic alterations. The recent and continuing successes of sequencing and other nonfunctional based genomic approaches have raised new problems in how to determine which changes have significance for tumor development. This is not a trivial problem and will require combinations of cell-based assays, in vivo animal models, and ultimately clinical intervention.

The identification of the Ras oncogene was the first major triumph of the early application of molecular biology to the cancer problem (Malumbres and Barbacid 2003). Although originally identified as a viral oncogene in a rodent sarcoma-inducing retrovirus, it was the seminal work of the Weinberg and Cooper laboratories in 1981 (Krontiris and Cooper 1981Shih et al. 1981), using DNA transfection assays of human tumor DNA into immortalized mouse fibroblasts, that led to the identification of Ras as a true human oncogene. Several groups went on to show that any one of the three Ras genes (HRASKRAS, and NRAS) could be converted into a human oncogene by a single base mutation leading to a single amino acid substitution in the encoded Ras protein. Ras mutations are found in ∼30% of most, though not all, cancer types and it remains the most frequently mutated dominant oncogene so far identified (Bos 1989). We now know much about the consequences of those amino acid substitutions and the cellular and physiological importance of Ras in controlling proliferation and differentiation. Ras is an example of a regulatory GTPase that cycles between active (GTP-bound) and inactive (GDP-bound) conformations to control biochemical pathways and processes. These molecular switches are activated by guanine nucleotide exchange factors (GEFs), which catalyze exchange of GDP for GTP, and are inactivated by GTPase-activating proteins (GAPs), which promote the otherwise slow, intrinsic GTPase activity of the proteins (Fig. 1). The amino acid substitutions identified in Ras in human cancers are found at codons 12, 61, and to a lesser extent 13, and the common consequence of these changes is to prevent GAP-mediated stimulation of GTP hydrolysis leading to permanent activation of the switch (Trahey and McCormick 1987). Inspection of Figure 1 suggests possible alternative ways in which this molecular switch could be inappropriately activated. For example, activating mutations in one of the nine RasGEF genes or inactivation of one of the eight RasGAP genes could lead to hyperactivation of the switch. To date, no such mutations have been reported in GEF genes in human cancers, but one of the GAPs, neurofibromin, is encoded by the NF1 tumor suppressor gene. Patients with neurofibromatosis type I inherit only one functional NF1 gene and are then predisposed to cancer through complete loss of NF1. In addition, mutational activation of components of downstream signaling pathways (Fig. 1) could bypass the need for Ras and this is clearly the case with somatic mutations in BRAF (which encodes a Ras effector), found most frequently in malignant melanomas (>50%), but also in thyroid, colorectal, and ovarian cancer (Davies et al. 2002Wellbrock et al. 2004).

The Ras GTP.GDP cycle

The Ras GTP.GDP cycle

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2732422/bin/1724fig1.jpg

Figure 1. The Ras GTP/GDP cycle. Ras GTPases are molecular switches and the GDP/GTP cycle is controlled by GEFs and GAPs. The output of the switch is through the interaction of Ras.GTP with effector proteins.

Rho GTPases can trigger numerous downstream signaling pathways by interacting with distinct effectors—to date, ∼20 such target proteins have been reported that specifically interact with Rho (Etienne-Manneville and Hall 2002). One of the best-characterized is Rho kinase (ROCK), which regulates myosin II and actin filament contractility, through its ability to phosphorylate and inactivate myosin light chain phosphatase (Fukata et al. 2001). Rho kinase is involved in many aspects of normal cell biology, such as cell cycle, morphogenesis, and migration, and in addition has been shown to participate in the proliferation, invasion, and metastasis of cancer cells (Etienne-Manneville and Hall 2002Sahai and Marshall 2002Narumiya and Yasuda 2006). In the final part of their study, Xue et al. (2008) show that two small molecule Rho kinase inhibitors, Y-27632 and to a lesser extent Fasudil, inhibit in vitro colony formation of p53−/− liver progenitor cells expressing c-Myc and DCL1 shRNA. It should be noted, however, that both Y-27632 and Fasudil inhibit PRK/PKN and citron kinase, two other kinases activated by Rho, so the result is not entirely conclusive (Ishizaki et al. 2000).

Embryonic fibroblasts can be obtained from DLC1−/− mice and these display alterations in the organization of actin filaments and focal adhesion (Durkin et al. 2005). Confusingly, however, these knockout cells have fewer stress fibers and focal adhesions—the opposite of what would have been predicted for the loss of a GAP that regulates Rho. In fact the cytoskeletal and adhesion complex changes seen in DLC−/− fibroblasts appear to be more in keeping with Rac activation. Unfortunately the authors did not examine the levels of either Rho.GTP or Rac.GTP in these cells, which might have provided some insight into this unexpected result. In the absence of tissue-specific mouse knockouts, we must look to work in Drosophila on RhoGAP88C, the fly ortholog of DCL1, to provide some in vivo physiological data. Mutations in RhoGAP88C were first identified as crossveinless-c and result in defects in tissue morphogenesis during development (Denholm et al. 2005). Closer examination suggests that this GAP regulates tubulogenesis and convergent extension, two processes driven by reorganization of the actin cytoskeleton. An additional and provocative observation to emerge from this study is that RhoGAP88C acts through Rho in some tissues, but it acts through Rac and not Rho in others. The in vitro biochemical activity of this GAP has not been determined and so it is possible that it shows a different specificity from its mammalian counterpart. Otherwise, tissue-specific modification of its catalytic activity would need to be invoked, rendering the in vitro assays essentially useless for predicting specificity. Two subsequent studies have concluded that RhoGAP88C is localized basolaterally in epithelial cells and serves to restrict Rho activity to the apical surface and thereby generate morphogenetic tissue remodeling through polarized activation of myosin II (Brodu and Casanova 2006Simoes et al. 2006).

Taken together, a picture emerges of spatially localized DLC1 acting to control Rho activity so as to promote changes in the actin cytoskeleton during cell morphogenesis. The disruption of this pathway might be expected to lead to tissue disorganization during differentiation programs, which could promote inappropriate cell proliferation (Fig. 2).

DLC1 is a tumor suppressor.

DLC1 is a tumor suppressor.

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2732422/bin/1724fig2.jpg

Figure 2.  DLC1 is a tumor suppressor. Loss of DLC1 leads to deregulated and/or delocalized activation of Rho. This may disrupt tissue morphogenesis leading to inappropriate proliferation. (PM) Plasma membrane.

Directed therapeutic intervention depends on a deep understanding of the relevant signaling pathways through which DLC1 loss is manifest. It is a sobering thought that the signaling pathways downstream from Ras responsible for human cancer are still debated some 25 years after its discovery as a human oncogene and it would be optimistic to believe that identifying Rho pathways will be any easier. Inhibiting the GTPase itself, whether Ras or Rho, is challenging. One of the most promising potential targets for Ras inactivation has been farnesyltransferase (FT), the enzyme required for carboxy-terminal, post-translational modification by a farnesyl lipid (Wright and Philips 2006). FT inhibitors are currently in clinical trials, though the data reported so far are not encouraging. Inhibiting Rho using a similar strategy seems less attractive, since it uses a geranylgeranyltransferase to add a geranylgeranyl group; a much more widespread modification than farnesyl addition. Two other processing enzymes that act on both Ras and Rho, a carboxyl-protease and an isoprenylcysteine carboxyl methyltransferase, are being considered as Ras targets, but in tissue culture at least these seem not to be essential for Rho function (Michaelson et al. 2005). Another possibility that is distinctive to DLC1 might be to attack the epigenetic mechanisms that appear to be commonly used to silence this gene in human cancers. Inhibitors of DNA methyltransferase and histone deacetylase (HDAC) have already been shown to induce the restoration of DLC1 expression in cancer cells, making Zebularine, a new and highly effective DNA demethylating agent, as well as HDAC inhibitors attractive therapeutic approaches (Guan et al. 2006Neureiter et al. 2007Seng et al. 2007Xu et al. 2007). Finally, if it turns out that Rho kinase mediates the key signaling pathway downstream from DLC1 loss, then there is already a huge effort underway to develop small molecule inhibitors of this protein. Rho kinase has been implicated in various forms of cardiovascular disease—such as pulmonary hypertension, myocardial hypertrophy, and atherosclerosis—and in fact one compound, Fasudil, is already being used clinically in Japan for cerebral ischemia (Rikitake and Liao 2005Tawara and Shimokawa 2007). With over a dozen pharmaceutical companies reportedly working on this problem, and if the work from Xue et al. (2008) implicating Rho kinase downstream from DLC1 turns out to be correct, those companies may end up with a blockbuster!

 

7.5.7 DLC1 is a chromosome 8p tumor suppressor whose loss promotes hepatocellular carcinoma.

Xue W, Krasnitz A, Lucito R, Sordella R, … , Zender L, Lowe SW.
Genes Dev. 2008 Jun 1;22(11):1439-44
http://dx.doi.org/10.1101.2Fgad.1672608

Deletions on chromosome 8p are common in human tumors, suggesting that one or more tumor suppressor genes reside in this region. Deleted in Liver Cancer 1 (DLC1) encodes a Rho-GTPase activating protein and is a candidate 8p tumor suppressor. We show that DLC1 knockdown cooperates with Myc to promote hepatocellular carcinoma in mice, and that reintroduction of wild-type DLC1 into hepatoma cells with low DLC1 levels suppresses tumor growth in situ. Cells with reduced DLC1 protein contain increased GTP-bound RhoA, and enforced expression a constitutively activated RhoA allele mimics DLC1 loss in promoting hepatocellular carcinogenesis. Conversely, down-regulation of RhoA selectively inhibits tumor growth of hepatoma cells with disabled DLC1. Our data validate DLC1 as a potent tumor suppressor gene and suggest that its loss creates a dependence on the RhoA pathway that may be targeted therapeutically.

Tumor suppressor genes act in signaling networks that protect against tumor initiation and progression, and can be inactivated by deletions, point mutations, or promoter hypermethylation. Although tumor suppressors are rarely considered direct drug targets, they can negatively regulate pro-oncogenic signaling proteins that are amenable to small molecule inhibition. For instance, NF1 inhibits the Ras signaling pathway, which is deregulated in many cancers and has been pursued for its therapeutic potential (Downward 2003). Similarly, PTEN inhibits the PI3–kinase pathway, and inhibitors of PI3K pathway components such as PI3K, AKT, and mTORs have entered clinic trials (Luo et al. 2003).

Recurrent chromosomal deletions found in sporadic cancers often contain tumor suppressor genes. For example, PTEN loss on chromosome 10q23 frequently occurs in various cancers and promotes tumorigenesis by deregulating the PI3 kinase pathway (Maser et al. 2007). Similarly, heterozygous deletions on chromosome 8p22 in many hepatocellular carcinomas (HCC) (Jou et al. 2004) and other cancer types, including carcinomas of the breast, prostate, colon, and lung (Matsuyama et al. 2001Durkin et al. 2007). Several genes, including DLC1MTUS1FGL1 and TUSC3, have been identified as candidate tumor suppressors in this region (Yan et al. 2004). Deleted in Liver Cancer 1 (DLC1) is a particularly attractive candidate owing to its genomic deletion, promoter methylation, and underexpressed mRNA in cancer (Yuan et al. 19982003aNg et al. 2000Wong et al. 2003Guan et al. 2006Seng et al. 2007Ying et al. 2007;Zhang et al. 2007Pike et al. 2008; for review, see Durkin et al. 2007).

Despite its potential importance, functional data implicating DLC1 loss in tumorigenesis are lacking. DLC1encodes a RhoGAP protein that catalyzes the conversion of active GTP-bound RhoGTPase (Rho) to the inactive GDP-bound form and thus suppresses Rho activity (Yuan et al. 1998). DLC1 has potent GAP activity for RhoA and limited activity for CDC42 (Wong et al. 2003Healy et al. 2008). When overexpressed, DLC1 inhibits the growth of tumor cells and xenografts (Yuan et al. 2003b2004Zhou et al. 2004Wong et al. 2005Kim et al. 2007), but whether this requires its Rho-GAP activity or other functions remains unresolved (Qian et al. 2007Liao et al. 2007). Most functional studies to date have relied on DLC1 overexpression and, as yet, none have documented that loss of DLC1 promotes transformation in vitro or tumorigenesis in vivo. Indeed, homozygous dlc1 knockout mice die around embryonic day 10.5 (E10.5), and there is no overt phenotype in dlc1 heterozygous mice (Durkin et al. 2005).

Our laboratory recently developed a “mosaic” mouse model whereby liver carcinomas can be rapidly produced with different genetic alterations by manipulation of cultured embryonic liver progenitor cells (hepatoblasts) followed by transplantation into the livers of recipient mice (Zender et al. 20052006). We previously used this model to identify new oncogenes in HCC, which could be characterized in an appropriate biological and genetic context (Zender et al. 2006). Furthermore, using this system, we showed that shRNAs capable of suppressing gene function by RNAi could recapitulate the consequences of tumor suppressor gene loss on liver carcinogenesis (Zender et al. 2005Xue et al. 2007). Here we combine this mosaic model and RNAi to validate DLC1 as a potent tumor suppressor gene and study its action in vivo.

Studies using low-resolution genome scanning methods have identified chromosome 8p deletions as common lesions in liver carcinoma and other tumor types. To confirm and extend these observations, we examined a series of data sets of copy number alterations in HCC obtained using representational oligonucleotide microarray analysis (ROMA), a variation of array-based CGH that enables genome scanning at high resolution (Lucito et al. 2003). In a panel of 86 liver cancers, heterozygous deletions encompassing theDLC1 were observed in 59 tumors (Fig. 1A,B; data not shown). Consistent with previous reports, these deletions were large (>5 Mb), encompassing >20 annotated genes but invariably included the DLC1 locus. Indeed, heterozygous deletions of DLC1 occurred more frequently than those observed for the well-established tumor suppressors such as INK4a/ARFPTEN, and TP53 (Fig. 1C). Furthermore, DLC1deletions were nearly as common as those for TP53 in other major tumor types such as lung, colon, and breast (Fig. 1C). Again, most 8p deletions were large, although in breast cancer DLC1 resided at a local deletion epicenter reminiscent of that surrounding the INK4a/ARF locus on chromosome 9p21 (Fig. 1D,E). Although we did not examine the status of the remaining allele in this tumor cohort, studies suggest that it can be silenced by promoter methylation (Yuan et al. 2003a; for review, see Durkin et al. 2007). Together, these data suggest that DLC1 loss plays an important role in human cancer but, in the absence of functional validation, are not conclusive.

Genetically modified liver progenitors were seeded into the livers of syngeneic recipients to assess their ability to form tumors in situ. In contrast to the modest impact of DLC1 loss in vitro, DLC1 shRNAs significantly accelerated tumor onset in vivo (P value < 0.0001 for shDLC1-1 and P < 0.0005 for shDLC1-2) (Fig. 2D,E). In fact, at 57 d post-transplantation, GFP-positive tumor nodules were observed in the livers of most animals receiving cells harboring DLC1 shRNAs, whereas the control animals showed no macroscopically detectable tumor burden (Fig. 2E). Furthermore, the pathology of tumors derived from DLC1 knockdown resembled aggressive human HCC and displayed a high proliferative index as assessed by Ki67 immunohistochemistry (Fig. 2F). Tumors also expressed the HCC markers α-fetoprotein (AFP) and albumin (Supplemental Fig. S3B). These data demonstrate that loss of DLC1 can efficiently promote the development of HCC.

We also ectopically expressed the murine dlc1 gene in mouse hepatoma cells and tested their ability to form tumors orthotopically. To this end, we cloned a Myc-tagged murine dlc1 cDNA and confirmed its ability to produce a protein of the correct molecular weight (Fig. 3A). A mouse hepatoma cell line harboring a luciferase reporter and expressing oncogenic Ras and undetectable DLC1 (see Fig. 1F, lane 8) was infected with the DLC1-expressing retrovirus or an empty vector. Consistent with the literature (Ng et al. 2000), reintroduction of DLC1 produced a modest effect on proliferation in colony formation assays (Supplemental Fig. S4A,B).

Although RhoA has been identified as a DLC1 effector, overexpression studies suggest that other DLC1 functions can contribute to its anti-proliferative activities (Liao et al. 2007Qian et al. 2007). To determine whether RhoA is required for maintaining tumorigenesis stimulated by DLC1 loss, we tested whether suppression of RhoA in DLC1-suppressed hepatoma lines would impact their expansion as subcutaneous tumors in immunocompromised mice. shRNAs capable of down-regulating RhoA to varying degrees (Fig. 5A) decreased the in vivo growth of two independent murine hepatoma lines with undetectable DLC1 (Fig. 5B, cell lines 1,2; Supplemental Fig. S6A,B). Of note, none of the shRNAs completely suppressed RhoA expression, and their ability to limit tumor expansion was proportional to their knockdown efficiency (Supplemental Fig. S6A). The impact of these shRNAs was less pronounced in hepatoma cell lines with higher DLC1 levels (Fig. 5B, cell lines 3,4; Supplemental Fig. S6C,D). Although complete inhibition of RhoA activity might be generally cytostatic (see Piekny et al. 2005), these data suggest that RhoA is required for maintaining the growth of tumors with attenuated DLC1 activity.

In this study, we combined in vivo RNAi and a mosaic mouse model of HCC to study the impact of DLC1 loss on liver carcinogenesis in mice, which to date has not been possible owing to the embryonic lethality of DLC1 knockout animals. We show that DLC1 loss, when combined with other oncogenic lesions, promotes HCC in vivo and that RhoA activation is both necessary and sufficient for its effects. In our survey of copy number alterations in human tumors, 8p22 deletions encompassing DLC1 occurred in >60% of heptocellular carcinomas as well as a large portion of human lung, breast, and colon carcinomas (see also Durkin et al. 2007). Similarly, RhoA is up-regulated in HCC and many other tumor types (Sahai and Marshall 2002;Fukui et al. 2006). Although other tumor suppressor genes may also reside in the 8p region, our results demonstrate that DLC1 is functionally important and highlight the potential importance of the RhoA signaling network in epithelial cancers.

Molecularly targeted therapies have been devised for inhibiting several oncogenic pathways, including those affected by BCR-ABL, activated Ras and PI3kinase (Downward 2003Luo et al. 2003). Although tumor suppressors are generally not amenable to direct therapeutic targeting, their mutation may confer a cellular dependency on downstream oncogenic proteins that can be inhibited with small molecule drugs. In this regard, the impact of DLC1 loss may parallel that produced by loss of PTEN, which deregulates the PI3K pathway and can sensitize cells to pharmacological inhibitors of downstream effectors such as mTOR (Maser et al. 2007). Our data indicate that RhoA is required for maintaining at least some tumors driven by DLC1 loss, and that cells with disabled DLC1 are particularly sensitive to inhibitors that target at least one RhoA effector. Clearly, more studies will be required to confirm and extend these observations; nevertheless, the high frequency of DLC1 loss in human cancer implies that pharmacologic intervention of the signaling pathways modulated by DLC1 may have broad therapeutic utility.

 

7.5.8 Smad7 regulates compensatory hepatocyte proliferation in damaged mouse liver and positively relates to better clinical outcome in human hepatocellular carcinoma

Feng T, Dzieran J, Gu X, Marhenke S, Vogel A, …, Dooley S, Meindl-Beinker NM.
Clin Sci (Lond). 2015 Jun 1; 128(11):761-74
http://dx.doi.org:/10.1042/CS20140606

Transforming growth factor β (TGF-β) is cytostatic towards damage-induced compensatory hepatocyte proliferation. This function is frequently lost during hepatocarcinogenesis, thereby switching the TGF-β role from tumour suppressor to tumour promoter. In the present study, we investigate Smad7 overexpression as a pathophysiological mechanism for cytostatic TGF-β inhibition in liver damage and hepatocellular carcinoma (HCC). Transgenic hepatocyte-specific Smad7 overexpression in damaged liver of fumarylacetoacetate hydrolase (FAH)-deficient mice increased compensatory proliferation of hepatocytes. Similarly, modulation of Smad7 expression changed the sensitivity of Huh7, FLC-4, HLE and HLF HCC cell lines for cytostatic TGF-β effects. In our cohort of 140 HCC patients, Smad7 transcripts were elevated in 41.4% of HCC samples as compared with adjacent tissue, with significant positive correlation to tumour size, whereas low Smad7 expression levels were significantly associated with worse clinical outcome. Univariate and multivariate analyses indicate Smad7 levels as an independent predictor for overall (P<0.001) and disease-free survival (P=0.0123). Delineating a mechanism for Smad7 transcriptional regulation in HCC, we identified cold-shock Y-box protein-1 (YB-1), a multifunctional transcription factor. YB-1 RNAi reduced TGF-β-induced and endogenous Smad7 expression in Huh7 and FLC-4 cells respectively. YB-1 and Smad7 mRNA expression levels correlated positively (P<0.0001). Furthermore, nuclear co-localization of Smad7 and YB-1 proteins was present in cancer cells of those patients. In summary, the present study provides a YB-1/Smad7-mediated mechanism that interferes with anti-proliferative/tumour-suppressive TGF-β actions in a subgroup of HCC cells that may facilitate aspects of tumour progression.

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Growth Factors, Suppressors and Receptors in Tumorigenesis

Writer and Curator: Larry H Bernstein, MD, FCAP

7.1 Growth Factors, Suppressors and Receptors in Tumorigenesis

7.1.1 Friend or Foe: Endoplasmic reticulum protein 29 (ERp29) in epithelial cancer

7.1.2 Putting together structures of epidermal growth factor receptors

7.1.3 Complex Relationship between Ligand Binding and Dimerization in the Epidermal Growth Factor Receptor

7.1.4 IGFBP-2.PTEN- A critical interaction for tumors and for general physiology

7.1.5 Emerging-roles-for-the-Ph-sensing-G-protein-coupled-receptor

7.1.6 Protein amino-terminal modifications and proteomic approaches for N-terminal profiling

7.1.7 Protein homeostasis networks in physiology and disease

7.1.8 Proteome sequencing goes deep

7.1.1 Friend or Foe: Endoplasmic reticulum protein 29 (ERp29) in epithelial cancer

Chen S1Zhang D2
FEBS Open Bio. 2015 Jan 30; 5:91-8
http://dx.doi.org:/10.1016/j.fob.2015.01.004

The endoplasmic reticulum (ER) protein 29 (ERp29) is a molecular chaperone that plays a critical role in protein secretion from the ER in eukaryotic cells. Recent studies have also shown that ERp29 plays a role in cancer. It has been demonstrated that ERp29 is inversely associated with primary tumor development and functions as a tumor suppressor by inducing cell growth arrest in breast cancer. However, ERp29 has also been reported to promote epithelial cell morphogenesis, cell survival against genotoxic stress and distant metastasis. In this review, we summarize the current understanding on the biological and pathological functions of ERp29 in cancer and discuss the pivotal aspects of ERp29 as “friend or foe” in epithelial cancer.

The endoplasmic reticulum (ER) is found in all eukaryotic cells and is complex membrane system constituting of an extensively interlinked network of membranous tubules, sacs and cisternae. It is the main subcellular organelle that transports different molecules to their subcellular destinations or to the cell surface [10,85].

The ER contains a number of molecular chaperones involved in protein synthesis and maturation. Of the ER chaperones, protein disulfide isomerase (PDI)-like proteins are characterized by the presence of a thioredoxin domain and function as oxido-reductases, isomerases and chaperones [33]. ERp29 lacks the active-site double-cysteine (CxxC) motif and does not belong to the redox-active PDIs [5,47]. ERp29 is recognized as a characterized resident of the cellular ER, and it is expressed ubiquitously and abundantly in mammalian tissues [50]. Protein structural analysis showed that ERp29 consists of N-terminal and C-terminal domains [5]: N-terminal domain involves dimerization whereas the C-terminal domain is essential for substrate binding and secretion [78]. The biological function of ERp29 in protein secretion has been well established in cells [8,63,67].

ERp9 is proposed to be involved in the unfolded protein response (UPR) as a factor facilitating transport of synthesized secretory proteins from the ER to Golgi [83]. The expression of ERp29 was demonstrated to be increased in cells exposed to radiation [108], sperm cells undergoing maturation [42,107], and in certain cell types both under the pharmacologically induced UPR and under the physiological conditions (e.g., lactation, differentiation of thyroid cells) [66,82]. Under ER stress, ERp29 translocates the precursor protein p90ATF6 from the ER to Golgi where it is cleaved to be a mature and active form p50ATF by protease (S1P and S2P) [48]. In most cases, ERp29 interacts with BiP/GRP78 to exert its function under ER stress [65].

ERp29 is considered to be a key player in both viral unfolding and secretion [63,67,77,78] Recent studies have also demonstrated that ERp29 is involved in intercellular communication by stabilizing the monomeric gap junction protein connexin43 [27] and trafficking of cystic fibrosis transmembrane conductance regulator to the plasma membrane in cystic fibrosis and non-cystic fibrosis epithelial cells [90]. It was recently reported that ERp29 directs epithelial Na(+) channel (ENaC) toward the Golgi, where it undergoes cleavage during its biogenesis and trafficking to the apical membrane [40]. ERp29 expression protects axotomized neurons from apoptosis and promotes neuronal regeneration [111]. These studies indicate a broad biological function of ERp29 in cells.

Recent studies demonstrated a tumor suppressive function of ERp29 in cancer. It was found that ERp29 expression inhibited tumor formation in mice [4,87] and the level of ERp29 in primary tumors is inversely associated with tumor development in breast, lung and gallbladder cancer [4,29].

However, its expression is also responsible for cancer cell survival against genotoxic stress induced by doxorubicin and radiation [34,76,109]. The most recent studies demonstrate other important roles of ERp29 in cancer cells such as the induction of mesenchymal–epithelial transition (MET) and epithelial morphogenesis [3,4]. MET is considered as an important process of transdifferentiation and restoration of epithelial phenotype during distant metastasis [23,52]. These findings implicate ERp29 in promoting the survival of cancer cells and also metastasis. Hence, the current review focuses on the novel functions of ERp29 and discusses its pathological importance as a “friend or foe” in epithelial cancer.

ERp29 regulates mesenchymal–epithelial transition

Epithelial–mesenchymal transition (EMT) and MET

The EMT is an essential process during embryogenesis [6] and tumor development [43,96]. The pathological conditions such as inflammation, organ fibrosis and cancer progression facilitate EMT [16]. The epithelial cells after undergoing EMT show typical features characterized as: (1) loss of adherens junctions (AJs) and tight junctions (TJs) and apical–basal polarity; (2) cytoskeletal reorganization and distribution; and (3) gain of aggressive phenotype of migration and invasion [98]. Therefore, EMT has been considered to be an important process in cancer progression and its pathological activation during tumor development induces primary tumor cells to metastasize [95]. However, recent studies showed that the EMT status was not unanimously correlated with poorer survival in cancer patients examined [92].

In addition to EMT in epithelial cells, mesenchymal-like cells have capability to regain a fully differentiated epithelial phenotype via the MET [6,35]. The key feature of MET is defined as a process of transdifferentiation of mesenchymal-like cells to polarized epithelial-like cells [23,52] and mediates the establishment of distant metastatic tumors at secondary sites [22]. Recent studies demonstrated that distant metastases in breast cancer expressed an equal or stronger E-cadherin signal than the respective primary tumors and the re-expression of E-cadherin was independent of the E-cadherin status of the primary tumors [58]. Similarly, it was found that E-cadherin is re-expressed in bone metastasis or distant metastatic tumors arising from E-cadherin-negative poorly differentiated primary breast carcinoma [81], or from E-cadherin-low primary tumors [25]. In prostate and bladder cancer cells, the nonmetastatic mesenchymal-like cells were interacted with metastatic epithelial-like cells to accelerate their metastatic colonization [20]. It is, therefore, suggested that the EMT/MET work co-operatively in driving metastasis.

Molecular regulation of EMT/MET

E-cadherin is considered to be a key molecule that provides the physical structure for both cell–cell attachment and recruitment of signaling complexes [75]. Loss of E-cadherin is a hallmark of EMT [53]. Therefore, characterizing transcriptional regulators of E-cadherin expression during EMT/MET has provided important insights into the molecular mechanisms underlying the loss of cell–cell adhesion and the acquisition of migratory properties during carcinoma progression [73].

Several known signaling pathways, such as those involving transforming growth factor-β (TGF-β), Notch, fibroblast growth factor and Wnt signaling pathways, have been shown to trigger epithelial dedifferentiation and EMT [28,97,110]. These signals repress transcription of epithelial genes, such as those encoding E-cadherin and cytokeratins, or activate transcription programs that facilitate fibroblast-like motility and invasion [73,97].

The involvement of microRNAs (miRNAs) in controlling EMT has been emphasized [11,12,18]. MiRNAs are small non-coding RNAs (∼23 nt) that silence gene expression by pairing to the 3′UTR of target mRNAs to cause their posttranscriptional repression [7]. MiRNAs can be characterized as “mesenchymal miRNA” and “epithelial miRNA” [68]. The “mesenchymal miRNA” plays an oncogenic role by promoting EMT in cancer cells. For instance, the well-known miR-21, miR-103/107 are EMT inducer by repressing Dicer and PTEN [44].

The miR-200 family has been shown to be major “epithelial miRNA” that regulate MET through silencing the EMT-transcriptional inducers ZEB1 and ZEB2 [13,17]. MiRNAs from this family are considered to be predisposing factors for cancer cell metastasis. For instance, the elevated levels of the epithelial miR-200 family in primary breast tumors associate with poorer outcomes and metastasis [57]. These findings support a potential role of “epithelial miRNAs” in MET to promote metastatic colonization [15].

ERp29 promotes MET in breast cancer

The role of ERp29 in regulating MET has been established in basal-like MDA-MB-231 breast cancer cells. It is known that myosin light chain (MLC) phosphorylation initiates to myosin-driven contraction, leading to reorganization of the actin cytoskeleton and formation of stress fibers [55,56]. ERp29 expression in this type of cells markedly reduced the level of phosphorylated MLC [3]. These results indicate that ERp29 regulates cortical actin formation through a mechanism involved in MLC phosphorylation (Fig. 1). In addition to the phenotypic change, ERp29 expression leads to: expression and membranous localization of epithelial cell marker E-cadherin; expression of epithelial differentiation marker cytokeratin 19; and loss of the mesenchymal cell marker vimentin and fibronectin [3] (Fig. 1). In contrast, knockdown of ERp29 in epithelial MCF-7 cells promotes acquisition of EMT traits including fibroblast-like phenotype, enhanced cell spreading, decreased expression of E-cadherin and increased expression of vimentin [3,4]. These findings further substantiate a role of ERp29 in modulating MET in breast cancer cells.

Fig. 1  ERp29 triggers mesenchymal–epithelial transition. Exogenous expression of ERp29 in mesenchymal MDA-MB-231 breast cancer cells inhibits stress fiber formation by suppressing MLC phosphorylation. In addition, the overexpressed ERp29 decreases the 

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ERp29 targets E-cadherin transcription repressors

The transcription repressors such as Snai1, Slug, ZEB1/2 and Twist have been considered to be the main regulators for E-cadherin expression [19,26,32]. Mechanistic studies revealed that ERp29 expression significantly down-regulated transcription of these repressors, leading to their reduced nuclear expression in MDA-MB-231 cells [3,4] (Fig. 2). Consistent with this, the extracellular signal-regulated kinase (ERK) pathway which is an important up-stream regulator of Slug and Ets1 was highly inhibited [4]. Apparently, ERp29 up-regulates the expressions of E-cadherin transcription repressors through repressing ERK pathway. Interestingly, ERp29 over-expression in basal-like BT549 cells resulted in incomplete MET and did not significantly affect the mRNA or protein expression of Snai1, ZEB2 and Twist, but increased the protein expression of Slug [3]. The differential regulation of these transcriptional repressors of E-cadherin by ERp29 in these two cell-types may occur in a cell-context-dependent manner.

Fig. 2  ERp29 decreases the expression of EMT inducers to promote MET. Exogenous expression of ERp29 in mesenchymal MDA-MB-231 breast cancer cells suppresses transcription and protein expression of E-cadherin transcription repressors (e.g., ZEB2, SNAI1 and Twist), ..

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ERp29 antagonizes Wnt/ β-catenin signaling

Wnt proteins are a family of highly conserved secreted cysteine-rich glycoproteins. The Wnt pathway is activated via a binding of a family member to a frizzled receptor (Fzd) and the LDL-Receptor-related protein co-receptor (LRP5/6). There are three different cascades that are activated by Wnt proteins: namely canonical/β-catenin-dependent pathway and two non-canonical/β-catenin-independent pathways that include Wnt/Ca2+ and planar cell polarity [84]. Of note, the Wnt/β-catenin pathway has been extensively studied, due to its important role in cancer initiation and progression [79]. The presence of Wnt promotes formation of a Wnt–Fzd–LRP complex, recruitment of the cytoplasmic protein Disheveled (Dvl) to Fzd and the LRP phosphorylation-dependent recruitment of Axin to the membrane, thereby leading to release of β-catenin from membrane and accumulation in cytoplasm and nuclei. Nuclear β-catenin replaces TLE/Groucho co-repressors and recruits co-activators to activate expression of Wnt target genes. The most important genes regulated are those related to proliferation, such as Cyclin D1 and c-Myc [46,94], which are over-expressed in most β-catenin-dependent tumors. When β-catenin is absent in nucleus, the transcription factors T-cell factor/lymphoid enhancer factors (TCF/LEF) recruits co-repressors of the TLE/Groucho family and function as transcriptional repressors.

β-catenin is highly expressed in the nucleus of mesenchymal MDA-MB-231 cells. ERp29 over-expression in this type of cells led to translocation of nuclear β-catenin to membrane where it forms complex with E-cadherin [3] (Fig. 3). This causes a disruption of β-catenin/TCF/LEF complex and abolishes its transcription activity. Indeed, ERp29 significantly decreased the expression of cyclin D1/D2 [36], one of the downstream targets of activated Wnt/β-catenin signaling [94], indicating an inhibitory effect of ERp29 on this pathway. Meanwhile, expression of ERp29 in this cell type increased the nuclear expression of TCF3, a transcription factor regulating cancer cell differentiation while inhibiting self-renewal of cancer stem cells [102,106]. Hence, ERp29 may play dual functions in mesenchymal MDA-MB-231 breast cancer cells by: (1) suppressing activated Wnt/β-catenin signaling via β-catenin translocation; and (2) promoting cell differentiation via activating TCF3 (Fig. 3). Because β-catenin serves as a signaling hub for the Wnt pathway, it is particularly important to focus on β-catenin as the target of choice in Wnt-driven cancers. Though the mechanism by which ERp29 expression promotes the disassociation of β-catenin/TCF/LEF complex in MDA-MB-231 cells remains elusive, activating ERp29 expression may exert an inhibitory effect on the poorly differentiated, Wnt-driven tumors.

Fig. 3  ERp29 over-expression “turns-off” activated Wnt/β-catenin signaling. In mesenchymal MDA-MB-231 cells, high expression of nuclear β-catenin activates its downstream signaling involved in cell cycles and cancer stem cell 

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ERp29 regulates epithelial cell integrity

Cell adherens and tight junctions

Adherens junctions (AJs) and tight junctions (TJs) are composed of transmembrane proteins that adhere to similar proteins in the adjacent cell [69]. The transmembrane region of the TJs is composed mainly of claudins, tetraspan proteins with two extracellular loops [1]. AJs are mediated by Ca2+-dependent homophilic interactions of cadherins [71] which interact with cytoplasmic catenins that link the cadherin/catenin complex to the actin cytoskeleton [74].

The cytoplasmic domain of claudins in TJs interacts with occludin and several zona occludens proteins (ZO1-3) to form the plaque that associates with the cytoskeleton [99]. The AJs form and maintain intercellular adhesion, whereas the TJs serve as a diffusion barrier for solutes and define the boundary between apical and basolateral membrane domains [21]. The AJs and TJs are required for integrity of the epithelial phenotype, as well as for epithelial cells to function as a tissue [75].

The TJs are closely linked to the proper polarization of cells for the establishment of epithelial architecture[86]. During cancer development, epithelial cells lose the capability to form TJs and correct apico–basal polarity [59]. This subsequently causes the loss of contact inhibition of cell growth [91]. In addition, reduction of ZO-1 and occludin were found to be correlated with poorly defined differentiation, higher metastatic frequency and lower survival rates [49,64]. Hence, TJs proteins have a tumor suppressive function in cancer formation and progression.

Apical–basal cell polarity

The apical–basal polarity of epithelial cells in an epithelium is characterized by the presence of two specialized plasma membrane domains: namely, the apical surface and basolateral surface [30]. In general, the epithelial cell polarity is determined by three core complexes. These protein complexes include: (1) the partitioning-defective (PAR) complex; (2) the Crumbs (CRB) complex; and (3) the Scribble complex[2,30,45,51]. PAR complex is composed of two scaffold proteins (PAR6 and PAR3) and an atypical protein kinase C (aPKC) and is localized to the apical junction domain for the assembly of TJs [31,39]. The Crumbs complex is formed by the transmembrane protein Crumbs and the cytoplasmic scaffolding proteins such as the homologue of Drosophila Stardust (Pals1) and Pals-associated tight junction protein (Patj) and localizes to the apical [38]. The Scribble complex is comprised of three proteins, Scribble, Disc large (Dlg) and Lethal giant larvae (Lgl) and is localized in the basolateral domain of epithelial cells [100].

Fig. 4  ERp29 regulates epithelial cell morphogenesis. Over-expression of ERp29 in breast cancer cells induces the transition from a mesenchymal-like to epithelial-like phenotype and the restoration of tight junctions and cell polarity. Up-regulation and membrane 

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The current data from breast cancer cells supports the idea that ERp29 can function as a tumor suppressive protein, in terms of suppression of cell growth and primary tumor formation and inhibition of signaling pathways that facilitate EMT. Nevertheless, the significant role of ERp29 in cell survival against drugs, induction of cell differentiation and potential promotion of MET-related metastasis may lead us to re-assess its function in cancer progression, particularly in distant metastasis. Hence, it is important to explore in detail the ERp29’s role in cancer as a “friend or foe” and to elucidate its clinical significance in breast cancer and other epithelial cancers. Targeting ERp29 and/or its downstream molecules might be an alternative molecular therapeutic approach for chemo/radio-resistant metastatic cancer treatment

7.1.2 Putting together structures of epidermal growth factor receptors

Bessman NJ1Freed DM2Lemmon MA3
Curr Opin Struct Biol. 2014 Dec; 29:95-101
http://dx.doi.org:/10.1016/j.sbi.2014.10.002

Highlights

  • Several studies suggest flexible linkage between extracellular and intracellular regions.
  • Others imply more rigid connections, required for allosteric regulation of dimers.
  • Interactions with membrane lipids play important roles in EGFR regulation.
  • Cellular studies suggest half-of-the-sites negative cooperativity for human EGFR.

Numerous crystal structures have been reported for the isolated extracellular region and tyrosine kinase domain of the epidermal growth factor receptor (EGFR) and its relatives, in different states of activation and bound to a variety of inhibitors used in cancer therapy. The next challenge is to put these structures together accurately in functional models of the intact receptor in its membrane environment. The intact EGFR has been studied using electron microscopy, chemical biology methods, biochemically, and computationally. The distinct approaches yield different impressions about the structural modes of communication between extracellular and intracellular regions. They highlight possible differences between ligands, and also underline the need to understand how the receptor interacts with the membrane itself.

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7.1.3 Complex Relationship between Ligand Binding and Dimerization in the Epidermal Growth Factor Receptor

Bessman NJ1Bagchi A2Ferguson KM2Lemmon MA3.
Cell Rep. 2014 Nov 20; 9(4):1306-17.
http://dx.doi.org/10.1016/j.celrep.2014.10.010

Highlights

  • Preformed extracellular dimers of human EGFR are structurally heterogeneous
  • EGFR dimerization does not stabilize ligand binding
  • Extracellular mutations found in glioblastoma do not stabilize EGFR dimerization
  • Glioblastoma mutations in EGFR increase ligand-binding affinity

Summary

The epidermal growth factor receptor (EGFR) plays pivotal roles in development and is mutated or overexpressed in several cancers. Despite recent advances, the complex allosteric regulation of EGFR remains incompletely understood. Through efforts to understand why the negative cooperativity observed for intact EGFR is lost in studies of its isolated extracellular region (ECR), we uncovered unexpected relationships between ligand binding and receptor dimerization. The two processes appear to compete. Surprisingly, dimerization does not enhance ligand binding (although ligand binding promotes dimerization). We further show that simply forcing EGFR ECRs into preformed dimers without ligand yields ill-defined, heterogeneous structures. Finally, we demonstrate that extracellular EGFR-activating mutations in glioblastoma enhance ligand-binding affinity without directly promoting EGFR dimerization, suggesting that these oncogenic mutations alter the allosteric linkage between dimerization and ligand binding. Our findings have important implications for understanding how EGFR and its relatives are activated by specific ligands and pathological mutations.

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X-ray crystal structures from 2002 and 2003 (Burgess et al., 2003) yielded the scheme for ligand-induced epidermal growth factor receptor (EGFR) dimerization shown in Figure 1. Binding of a single ligand to domains I and III within the same extracellular region (ECR) stabilizes an “extended” conformation and exposes a dimerization interface in domain II, promoting self-association with a KD in the micromolar range (Burgess et al., 2003, Dawson et al., 2005, Dawson et al., 2007). Although this model satisfyingly explains ligand-induced EGFR dimerization, it fails to capture the complex ligand-binding characteristics seen for cell-surface EGFR, with concave-up Scatchard plots indicating either negative cooperativity (De Meyts, 2008, Macdonald and Pike, 2008) or distinct affinity classes of EGF-binding site with high-affinity sites responsible for EGFR signaling (Defize et al., 1989). This cooperativity or heterogeneity is lost when the ECR from EGFR is studied in isolation, as also described for the insulin receptor (De Meyts, 2008).

ligand-induced-dimerization-of-the-hegfr-ecr

ligand-induced-dimerization-of-the-hegfr-ecr

Figure 1

Structural View of Ligand-Induced Dimerization of the hEGFR ECR

(A) Surface representation of tethered, unliganded, sEGFR from Protein Data Bank entry 1NQL (Ferguson et al., 2003). Ligand-binding domains I and III are green and cysteine-rich domains II and IV are cyan. The intramolecular domain II/IV tether is circled in red.

(B) Hypothetical model for an extended EGF-bound sEGFR monomer based on SAXS studies of an EGF-bound dimerization-defective sEGFR variant (Dawson et al., 2007) from PDB entry 3NJP (Lu et al., 2012). EGF is blue, and the red boundary represents the primary dimerization interface.

(C) 2:2 (EGF/sEGFR) dimer, from PDB entry 3NJP (Lu et al., 2012), colored as in (B). Dimerization arm contacts are circled in red.

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Here, we describe studies of an artificially dimerized ECR from hEGFR that yield useful insight into the heterogeneous nature of preformed ECR dimers and into the origins of negative cooperativity. Our data also argue that extracellular structures induced by ligand binding are not “optimized” for dimerization and conversely that dimerization does not optimize the ligand-binding sites. We also analyzed the effects of oncogenic mutations found in glioblastoma patients (Lee et al., 2006), revealing that they affect allosteric linkage between ligand binding and dimerization rather than simply promoting EGFR dimerization. These studies have important implications for understanding extracellular activating mutations found in EGFR/ErbB family receptors in glioblastoma and other cancers and also for understanding specificity of ligand-induced ErbB receptor heterodimerization

Predimerizing the EGFR ECR Has Modest Effects on EGF Binding

To access preformed dimers of the hEGFR ECR (sEGFR) experimentally, we C-terminally fused (to residue 621 of the mature protein) either a dimerizing Fc domain (creating sEGFR-Fc) or the dimeric leucine zipper from S. cerevisiae GCN4 (creating sEGFR-Zip). Size exclusion chromatography (SEC) and/or sedimentation equilibrium analytical ultracentrifugation (AUC) confirmed that the resulting purified sEGFR fusion proteins are dimeric (Figure S1). To measure KD values for ligand binding to sEGFR-Fc and sEGFR-Zip, we labeled EGF with Alexa-488 and monitored binding in fluorescence anisotropy (FA) assays. As shown in Figure 2A, EGF binds approximately 10-fold more tightly to the dimeric sEGFR-Fc or sEGFR-Zip proteins than to monomeric sEGFR (Table 1). The curves obtained for EGF binding to sEGFR-Fc and sEGFR-Zip showed no signs of negative cooperativity, with sEGFR-Zip actually requiring a Hill coefficient (nH) greater than 1 for a good fit (nH = 1 for both sEGFRWT and sEGFR-Fc). Thus, our initial studies argued that simply dimerizing human sEGFR fails to restore the negatively cooperative ligand binding seen for the intact receptor in cells.

One surprise from these data was that forced sEGFR dimerization has only a modest (≤10-fold) effect on EGF-binding affinity. Under the conditions of the FA experiments, isolated sEGFR (without zipper or Fc fusion) remains monomeric; the FA assay contains just 60 nM EGF, so the maximum concentration of EGF-bound sEGFR is also limited to 60 nM, which is over 20-fold lower than the KD for dimerization of the EGF/sEGFR complex (Dawson et al., 2005, Lemmon et al., 1997). This ≤10-fold difference in affinity for dimeric and monomeric sEGFR seems small in light of the strict dependence of sEGFR dimerization on ligand binding (Dawson et al., 2005,Lax et al., 1991, Lemmon et al., 1997). Unliganded sEGFR does not dimerize detectably even at millimolar concentrations, whereas liganded sEGFR dimerizes with KD ∼1 μM, suggesting that ligand enhances dimerization by at least 104– to 106-fold. Straightforward linkage of dimerization and binding equilibria should stabilize EGF binding to dimeric sEGFR similarly (by 5.5–8.0 kcal/mol). The modest difference in EGF-binding affinity for dimeric and monomeric sEGFR is also significantly smaller than the 40- to 100-fold difference typically reported between high-affinity and low-affinity EGF binding on the cell surface when data are fit to two affinity classes of binding site (Burgess et al., 2003, Magun et al., 1980).

Mutations that Prevent sEGFR Dimerization Do Not Significantly Reduce Ligand-Binding Affinity

The fact that predimerizing sEGFR only modestly increased ligand-binding affinity led us to question the extent to which domain II-mediated sEGFR dimerization is linked to ligand binding. It is typically assumed that the domain II conformation stabilized upon forming the sEGFR dimer in Figure 1C optimizes the domain I and III positions for EGF binding. To test this hypothesis, we introduced a well-characterized pair of domain II mutations into sEGFRs that block dimerization: one at the tip of the dimerization arm (Y251A) and one at its “docking site” on the adjacent molecule in a dimer (R285S). The resulting (Y251A/R285S) mutation abolishes sEGFR dimerization and EGFR signaling (Dawson et al., 2005, Ogiso et al., 2002). Importantly, we chose isothermal titration calorimetry (ITC) for these studies, where all interacting components are free in solution. Previous surface plasmon resonance (SPR) studies have indicated that dimerization-defective sEGFR variants bind immobilized EGF with reduced affinity (Dawson et al., 2005), and we were concerned that this reflects avidity artifacts, where dimeric sEGFR binds more avidly than monomeric sEGFR to sensor chip-immobilized EGF.

Surprisingly, our ITC studies showed that the Y251A/R285S mutation has no significant effect on ligand-binding affinity for sEGFR in solution (Table 1). These experiments employed sEGFR (with no Fc fusion) at 10 μM—ten times higher than KD for dimerization of ligand-saturated WT sEGFR (sEGFRWT) (KD ∼1 μM). Dimerization of sEGFRWT should therefore be complete under these conditions, whereas the Y251A/R285S-mutated variant (sEGFRY251A/R285S) does not dimerize at all (Dawson et al., 2005). The KD value for EGF binding to dimeric sEGFRWT was essentially the same (within 2-fold) as that for sEGFRY251A/R285S (Figures 2B and 2C; Table 1), arguing that the favorable Gibbs free energy (ΔG) of liganded sEGFR dimerization (−5.5 to −8 kcal/mol) does not contribute significantly (<0.4 kcal/mol) to enhanced ligand binding. …

Thermodynamics of EGF Binding to sEGFR-Fc

If there is no discernible positive linkage between sEGFR dimerization and EGF binding, why do sEGFR-Fc and sEGFR-Zip bind EGF ∼10-fold more strongly than wild-type sEGFR? To investigate this, we used ITC to compare EGF binding to sEGFR-Fc and sEGFR-Zip (Figures 3A and 3B ) with binding to isolated (nonfusion) sEGFRWT. As shown in Table 1, the positive (unfavorable) ΔH for EGF binding is further elevated in predimerized sEGFR compared with sEGFRWT, suggesting that enforced dimerization may actually impair ligand/receptor interactions such as hydrogen bonds and salt bridges. The increased ΔH is more than compensated for, however, by a favorable increase in TΔS. This favorable entropic effect may reflect an “ordering” imposed on unliganded sEGFR when it is predimerized, such that it exhibits fewer degrees of freedom compared with monomeric sEGFR. In particular, since EGF binding does induce sEGFR dimerization, it is clear that predimerization will reduce the entropic cost of bringing two sEGFR molecules into a dimer upon ligand binding, possibly underlying this effect.

Possible Heterogeneity of Binding Sites in sEGFR-Fc

Close inspection of EGF/sEGFR-Fc titrations such as that in Figure 3A suggested some heterogeneity of sites, as evidenced by the slope in the early part of the experiment. To investigate this possibility further, we repeated titrations over a range of temperatures. We reasoned that if there are two different types of EGF-binding sites in an sEGFR-Fc dimer, they might have different values for heat capacity change (ΔCp), with differences that might become more evident at higher (or lower) temperatures. Indeed, ΔCp values correlate with the nonpolar surface area buried upon binding (Livingstone et al., 1991), and we know that this differs for the two Spitz-binding sites in the asymmetric Drosophila EGFR dimer (Alvarado et al., 2010). As shown in Figure 3C, the heterogeneity was indeed clearer at higher temperatures for sEGFR-Fc—especially at 25°C and 30°C—suggesting the possible presence of distinct classes of binding sites in the sEGFR-Fc dimer. We were not able to fit the two KD values (or ΔH values) uniquely with any precision because the experiment has insufficient information for unique fitting to a model with four variables. Whereas binding to sEGFRWT could be fit confidently with a single-site binding model throughout the temperature range, enforced sEGFR dimerization (by Fc fusion) creates apparent heterogeneity in binding sites, which may reflect negative cooperativity of the sort seen with dEGFR. …

Ligand Binding Is Required for Well-Defined Dimerization of the EGFR ECR

To investigate the structural nature of the preformed sEGFR-Fc dimer, we used negative stain electron microscopy (EM). We hypothesized that enforced dimerization might cause the unliganded ECR to form the same type of loose domain II-mediated dimer seen in crystals of unliganded Drosophila sEGFR (Alvarado et al., 2009). When bound to ligand (Figure 4A), the Fc-fused ECR clearly formed the characteristic heart-shape dimer seen by crystallography and EM (Lu et al., 2010, Mi et al., 2011). Figure 4B presents a structural model of an Fc-fused liganded sEGFR dimer, and Figure 4C shows a calculated 12 Å resolution projection of this model. The class averages for sEGFR-Fc plus EGF (Figure 4A) closely resemble this model, yielding clear densities for all four receptor domains, arranged as expected for the EGF-induced domain II-mediated back-to-back extracellular dimer shown in Figure 1 (Garrett et al., 2002, Lu et al., 2010). In a subset of classes, the Fc domain also appeared well resolved, indicating that these particular arrangements of the Fc domain relative to the ECR represent highly populated states, with the Fc domains occupying similar positions to those of the kinase domain in detergent-solubilized intact receptors (Mi et al., 2011). …

Our results and those of Lu et al. (2012)) argue that preformed extracellular dimers of hEGFR do not contain a well-defined domain II-mediated interface. Rather, the ECRs in these dimers likely sample a broad range of positions (and possibly conformations). This conclusion argues against recent suggestions that stable unliganded extracellular dimers “disfavor activation in preformed dimers by assuming conformations inconsistent with” productive dimerization of the rest of the receptor (Arkhipov et al., 2013). The ligand-free inactive dimeric ECR species modeled by Arkhipov et al. (2013) in their computational studies of the intact receptor do not appear to be stable. The isolated ECR from EGFR has a very low propensity for self-association without ligand, with KD in the millimolar range (or higher). Moreover, sEGFR does not form a defined structure even when forced to dimerize by Fc fusion. It is therefore difficult to envision how it might assume any particular autoinhibitory dimeric conformation in preformed dimers. …

Extracellular Oncogenic Mutations Observed in Glioblastoma May Alter Linkage between Ligand Binding and sEGFR Dimerization

Missense mutations in the hEGFR ECR were discovered in several human glioblastoma multiforme samples or cell lines and occur in 10%–15% of glioblastoma cases (Brennan et al., 2013, Lee et al., 2006). Several elevate basal receptor phosphorylation and cause EGFR to transform NIH 3T3 cells in the absence of EGF (Lee et al., 2006). Thus, these are constitutively activating oncogenic mutations, although the mutated receptors can be activated further by ligand (Lee et al., 2006, Vivanco et al., 2012). Two of the most commonly mutated sites in glioblastoma, R84 and A265 (R108 and A289 in pro-EGFR), are in domains I and II of the ECR, respectively, and contribute directly in inactive sEGFR to intramolecular interactions between these domains that are thought to be autoinhibitory (Figure 5). Domains I and II become separated from one another in this region upon ligand binding to EGFR (Alvarado et al., 2009), as illustrated in the lower part of Figure 5. Interestingly, analogous mutations in the EGFR relative ErbB3 were also found in colon and gastric cancers (Jaiswal et al., 2013).

We hypothesized that domain I/II interface mutations might activate EGFR by disrupting autoinhibitory interactions between these two domains, possibly promoting a domain II conformation that drives dimerization even in the absence of ligand. In contrast, however, sedimentation equilibrium AUC showed that sEGFR variants harboring R84K, A265D, or A265V mutations all remained completely monomeric in the absence of ligand (Figure 6A) at a concentration of 10 μM, which is similar to that experienced at the cell surface (Lemmon et al., 1997). As with WT sEGFR, however, addition of ligand promoted dimerization of each mutated sEGFR variant, with KD values that were indistinguishable from those of WT. Thus, extracellular EGFR mutations seen in glioblastoma do not simply promote ligand-independent ECR dimerization, consistent with our finding that even dimerized sEGFR-Fc requires ligand binding in order to form the characteristic heart-shaped dimer. …

We suggest that domain I is normally restrained by domain I/II interactions so that its orientation with respect to the ligand is compromised. When the domain I/II interface is weakened with mutations, this effect is mitigated. If this results simply in increased ligand-binding affinity of the monomeric receptor, the biological consequence might be to sensitize cells to lower concentrations of EGF or TGF-α (or other agonists). However, cellular studies of EGFR with glioblastoma-derived mutations (Lee et al., 2006, Vivanco et al., 2012) clearly show ligand-independent activation, arguing that this is not the key mechanism. The domain I/II interface mutations may also reduce restraints on domain II so as to permit dimerization of a small proportion of intact receptor, driven by the documented interactions that promote self-association of the transmembrane, juxtamembrane, and intracellular regions of EGFR (Endres et al., 2013, Lemmon et al., 2014, Red Brewer et al., 2009).

Setting out to test the hypothesis that simply dimerizing the EGFR ECR is sufficient to recover the negative cooperativity lost when it is removed from the intact receptor, we were led to revisit several central assumptions about this receptor. Our findings suggest three main conclusions. First, we find that enforcing dimerization of the hEGFR ECR does not drive formation of a well-defined domain II-mediated dimer that resembles ligand-bound ECRs or the unliganded ECR from Drosophila EGFR. Our EM and SAXS data show that ligand binding is necessary for formation of well-defined heart-shaped domain II-mediated dimers. This result argues that the unliganded extracellular dimers modeled by Arkhipov et al. (2013)) are not stable and that it is improbable that stable conformations of preformed extracellular dimers disfavor receptor activation by assuming conformations that counter activating dimerization of the rest of the receptor. Recent work from the Springer laboratory employing kinase inhibitors to drive dimerization of hEGFR (Lu et al., 2012) also showed that EGF binding is required to form heart-shaped ECR dimers. These findings leave open the question of the nature of the ECR in preformed EGFR dimers but certainly argue that it is unlikely to resemble the crystallographic dimer seen for unligandedDrosophila EGFR (Alvarado et al., 2009) or that suggested by computational studies (Arkhipov et al., 2013).

This result argues that ligand binding is required to permit dimerization but that domain II-mediated dimerization may compromise, rather than enhance, ligand binding. Assuming flexibility in domain II, we suggest that this domain serves to link dimerization and ligand binding allosterically. Optimal ligand binding may stabilize one conformation of domain II in the scheme shown in Figure 1 that is then distorted upon dimerization of the ECR, in turn reducing the strength of interactions with the ligand. Such a mechanism would give the appearance of a lack of positive linkage between ligand binding and ECR dimerization, and a good test of this model would be to determine the high-resolution structure of a liganded sEGFR monomer (which we expect to differ from a half dimer). This model also suggests a mechanism for selective heterodimerization over homodimerization of certain ErbB receptors. If a ligand-bound EGFR monomer has a domain II conformation that heterodimerizes with ErbB2 in preference to forming EGFR homodimers, this could explain several important observations. It could explain reports that ErbB2 is a preferred heterodimerization partner of EGFR (Graus-Porta et al., 1997) and might also explain why EGF binds more tightly to EGFR in cells where it can form heterodimers with ErbB2 than in cells lacking ErbB2, where only EGFR homodimers can form (Li et al., 2012).

7.1.4 IGFBP-2.PTEN- A critical interaction for tumors and for general physiology

Li ZengClaire M. PerksJeff M.P. Holly
Growth Hormone & IGF Research online 7 February 2015
http://dx.doi.org/10.1016/j.ghir.2015.01.003

Highlights

  • IGFBP-2 is the second most abundant of the IGFBPs in the circulation.
  • IGFBP2 levels are increased in a variety of tumors and associated with progression and poor prognosis.
  • PTEN is a phosphatase that returns the PI3K/AKT/mTOR pathway to its inactivated state.
  • PTEN is the second most commonly mutated gene in a variety of common cancers.
  • Recent evidence indicates that IGFBP-2 regulates PTEN in a variety of normal and malignant cell types.
  • This review summarizes the evidence that these extracellular and intracellular modulators of the IGF-system are linked.

Abstract

IGFBP-2 is an important modulator of IGF availability and activity. It is the second most abundant of the IGFBPs in the circulation and its levels are increased in a variety of tumors and associated with progression and poor prognosis. PTEN is a phosphatase that returns the PI3K/AKT/mTOR pathway to its inactivated state and is therefore a critical modulator of one of the main intracellular signaling pathways activated by the IGFs. Recent evidence has indicated that IGFBP-2 regulates PTEN in a variety of normal and malignant cell types. This review summarizes the recent evidence that these extracellular and intracellular modulators are linked to provide a synchronous system for cell regulation with coordinated control of both the ‘accelerator’ and the ‘brake’.

IGFBP-2.PTEN

IGFBP-2.PTEN

http://ars.els-cdn.com/content/image/1-s2.0-S1096637415000167-gr1.sml

7.1.5 Emerging-roles-for-the-Ph-sensing-G-protein-coupled-receptor

Sanderlin EJ, Justus CR, Krewson EA, Yang LV
CHC March 2015 Volume 2015:7 Pages 99—109

http://www.dovepress.com/emerging-roles-for-the-ph-sensing-g-protein-coupled-receptors-in-respo-peer-reviewed-fulltext-article-CHC#

Protons (hydrogen ions) are the simplest form of ions universally produced by cellular metabolism including aerobic respiration and glycolysis. Export of protons out of cells by a number of acid transporters is essential to maintain a stable intracellular pH that is critical for normal cell function. Acid products in the tissue interstitium are removed by blood perfusion and excreted from the body through the respiratory and renal systems. However, the pH homeostasis in tissues is frequently disrupted in many pathophysiologic conditions such as in ischemic tissues and tumors where protons are overproduced and blood perfusion is compromised. Consequently, accumulation of protons causes acidosis in the affected tissue. Although acidosis has profound effects on cell function and disease progression, little is known about the molecular mechanisms by which cells sense and respond to acidotic stress. Recently a family of pH-sensing G protein-coupled receptors (GPCRs), including GPR4, GPR65 (TDAG8), and GPR68 (OGR1), has been identified and characterized. These GPCRs can be activated by extracellular acidic pH through the protonation of histidine residues of the receptors. Upon activation by acidosis the pH-sensing GPCRs can transduce several downstream G protein pathways such as the Gs, Gq/11, and G12/13 pathways to regulate cell behavior. Studies have revealed the biological roles of the pH-sensing GPCRs in the immune, cardiovascular, respiratory, renal, skeletal, endocrine, and nervous systems, as well as the involvement of these receptors in a variety of pathological conditions such as cancer, inflammation, pain, and cardiovascular disease. As GPCRs are important drug targets, small molecule modulators of the pH-sensing GPCRs are being developed and evaluated for potential therapeutic applications in disease treatment.

Cellular metabolism produces acid as a byproduct. Metabolism of each glucose molecule by glycolysis generates two pyruvate molecules. Under anaerobic conditions the metabolism of pyruvate results in the production of the glycolytic end product lactic acid, which has a pKa of 3.9. Lactic acid is deprotonated at the carboxyl group and results in one lactate ion and one proton at the physiological pH. Under aerobic conditions pyruvate is converted into acetyl-CoA and CO2 in the mitochondria. CO2in water forms a chemical equilibrium of carbonic acid and bicarbonate, an important physiological pH buffering system. The body must maintain suitable pH for proper physiological functions. Some regulatory mechanisms to control systemic pH are respiration, renal excretion, bone buffering, and metabolism.14 The respiratory system can buffer the blood by excreting carbonic acid as CO2 while the kidney responds to decreased circulatory pH by excreting protons and electrolytes to stabilize the physiological pH. Bone buffering helps maintain systemic pH by Ca2+ reabsorption and mineral dissolution. Collectively, it is clear that several biological systems require tight regulation to maintain pH for normal physiological functions. Cells utilize vast varieties of acid-base transporters for proper pH homeostasis within each biological context.58 Some such transporters are H+-ATPase, Na+/H+exchanger, Na+-dependent HCO3/C1 exchanger, Na+-independent anion exchanger, and monocarboxylate transporters. Cells can also maintain short-term pH homeostasis of the intracellular pH by rapid H+ consuming mechanisms. Some such mechanisms utilize metabolic conversions that move acids from the cytosol into organelles. Despite these cellular mechanisms that tightly maintain proper pH homeostasis, there are many diseases whereby pH homeostasis is disrupted. These pathological conditions are characterized by either local or systemic acidosis. Systemic acidosis can occur from respiratory, renal, and metabolic diseases and septic shock.14,9 Additionally, local acidosis is characterized in ischemic tissues, tumors, and chronically inflamed conditions such as in asthma and arthritis caused by deregulated metabolism and hypoxia.1015

Acidosis is a stress for the cell. The ability of the cell to sense and modulate activity for adaptation to the stressful environment is critical. There are several mechanisms whereby cells sense acidosis and modulate cellular functions to facilitate adaptation. Cells can detect extracellular pH changes by acid sensing ion channels (ASICs) and transient receptor potential (TRP) channels.16 Apart from ASIC and TRP channels, extracellular acidic pH was shown to stimulate inositol polyphosphate formation and calcium efflux.17,18 This suggested the presence of an unknown cell surface receptor that may be activated by a certain functional group, namely the imidazole of a histidine residue. The identity of the acid-activated receptor was later unmasked by Ludwig et al as a family of proton-sensing G protein-coupled receptors (GPCRs). This group identified human ovarian cancer GPCR 1 (OGR1) which upon activation will produce inositol phosphate and calcium efflux through the Gq pathway.19 These pH-sensing GPCR family members, including GPR4, GPR65 (TDAG8), and GPR68 (OGR1), will be discussed in this review (Figure 1). The proton-sensing GPCRs sense extracellular pH by protonation of several histidine residues on their extracellular domain. The activation of these proton-sensing GPCRs facilitates the downstream signaling through the Gq/11, Gs, and G12/13 pathways. Their expression varies in different cell types and play critical roles in sensing extracellular acidity and modulating cellular functions in several biological systems.

Figure 1 Biological roles and G protein coupling of the pH-sensing GPCRs

Biological roles and G protein coupling of the pH-sensing GPCRs

Biological roles and G protein coupling of the pH-sensing GPCRs

http://www.dovepress.com/cr_data/article_fulltext/s60000/60508/img/fig1small.jpg

Cells encounter acidotic stress in many pathophysiologic conditions such as inflammation, cancer, and ischemia. Intricate molecular mechanisms, including a large array of acid/base transporters and acid sensors, have evolved for cells to sense and respond to acidotic stress. Emerging evidence has demonstrated that a family of the pH-sensing GPCRs can be activated by extracellular acidotic stress and regulate the function of multiple physiological systems (Table 1). The pH-sensing GPCRs also play important roles in various pathological disorders. Agonists, antagonists and other modulators of the pH-sensing GPCRs are being actively developed and evaluated as potential novel treatment for acidosis-related diseases.

Table 1 The main biological functions of the pH-sensing GPCRs
Table1 The main biological functions of the pH-sensing GPCRs

Table1 The main biological functions of the pH-sensing GPCRs

http://www.dovepress.com/cr_data/article_fulltext/s60000/60508/img/Table1small.jpg

7.1.6 Protein amino-terminal modifications and proteomic approaches for N-terminal profiling

Lai ZW1Petrera A2Schilling O3.
Curr Opin Chem Biol. 2015 Feb; 24:71-9
http://dx.doi.org/10.1016/j.cbpa.2014.10.026

Highlights

  • N-terminal acetylation, pyroglutamate formation, N-degrons and proteolysis are reviewed.
  • N-terminomics provide comprehensive profiling of modification at protein N-termini in a proteome-wide manner.
  • We outline a number of established methodologies for the enrichment of protein N-termini through positive and negative selection strategies.
  • Peptidomics-based approach is beneficial for the study of post-translational processing of protein N-termini.

Amino-/N-terminal processing is a crucial post-translational modification affecting almost all proteins. In addition to altering the chemical properties of the N-terminus, these modifications affect protein activation, conversion, and degradation, which subsequently lead to diversified biological functions. The study of N-terminal modifications is of increasing interest; especially since modifications such as proteolytic truncation or pyroglutamate formation have been linked to disease processes. During the past decade, mass spectrometry has played an important role in facilitating the investigation of N-terminal modifications. Continuous progress is being made in the development and application of robust methods for the dedicated analysis of native and modified protein N-termini in a proteome-wide manner. Here we highlight recent progress in our understanding of protein N-terminal biology as well as outlining present enrichment strategies for mass spectrometry-based studies of protein N-termini

7.1.7 Protein homeostasis networks in physiology and disease

Claudio Hetz1,2,3,* and Laurie H. Glimcher3,4,*
Curr Opin Cell Biol. 2011 Apr; 23(2): 123–125.
http://dx.doi.org/10.1016%2Fj.ceb.2011.01.004

Although most text books of biochemistry describe the process of protein folding to a three dimensional native state as an intrinsic property of the primary sequence, it is becoming increasingly clear that this process can go wrong in an almost infinite number of ways. In fact, many different diseases are caused by the misfolding and aggregation of certain proteins without genetic mutations in the primary sequence. An integrative view of the mechanisms that maintain protein folding homeostasis is emerging, which could be thought as a balanced and dynamic network of interconnected processes tightly regulated by a series of quality control mechanisms. This protein homeostasis network involves families of folding catalysts, co-factors under specific environmental and metabolic conditions. Maintaining protein homeostasis is particularly challenging in specialized secretory cells where the high demand for protein synthesis generates a constant source of stress that could lead to proteotoxicity.

Protein folding is assisted and monitored by diverse interconnected processes that follow a sequential pattern over time. The calnexin/calreticulin cycle ensures the proper folding of glycosylated proteins through the secretory pathway, which establishes the final pattern of disulfide bond formation through interactions with the disulfide isomerase ERp57. Coupled to this cycle is the ER-associated degradation (ERAD) pathway, which translocates terminally misfolded proteins to the cytosol for degradation by proteasomes. In addition, macroautophagy is becoming a relevant mechanism for the clearance of damaged proteins and abnormal protein aggregates through lysosomal hydrolysis, a process also referred to as ERAD-II. The folding status at the ER is constantly monitored by the Unfolded Protein Response (UPR), a specialized signaling pathway initiated by the activation of three types of stress sensors. The process underlying the surveillance of protein folding stress by the UPR is not fully understood, but it may require coupling to key folding mediators such as BiP or the direct recognition of the misfolded peptides by stress sensors. The UPR regulates genes and processs related to almost every folding step in the secretory pathway to reduce the load of misfolded proteins, including protein translation into the ER, translocation, folding, quality control, ERAD, the redox status, and many other related functions. Protein folding stress is observed in many disease conditions such as cancer, diabetes, and neurodegeneration. For example, abnormal protein aggregation and the accumulation of protein inclusions is associated with Parkinson’s and Alzheimer’s Disease, and amyotrophic lateral sclerosis. In those diseases and many others, neuronal dysfunction and disease progression correlates with the presence of a strong ER stress response; however, the direct in vivo role of the UPR in the disease process has been experimentally defined in only a few cases. Therapeutic strategies are currently being developed to increase protein folding and clearance of misfolded proteins, with the goal of alleviating ER stress.

In this issue of Current Opinion in Cell Biology we present a series of focused reviews from recognized experts in the field, that provide an overview of mechanisms underlying protein folding and quality control, and how balance of protein homeostasis is maintained in physiology and deregulated in diseases. Daniela Roth and William Balch integrate the concept of protein homeostasis networks into an interesting model termed FoldFx, showing how the interconnection between different pathways in the context of the cellular proteome determines the energetic barrier required to generate a functional folded peptide. The authors have previously proposed the term Proteostasis to refer to the set of interacting activities that maintain the health of the proteome and the organism (protein homeostasis). The ER is a central subcellular compartment for protein synthesis and quality control in the secretory pathway. Yukio Kimata and Kenji Kohno give an overview of the signaling pathways that control adaptation to ER stress and maintenance of protein folding homeostasis. The authors summarize the models proposed so far for the activation of UPR stress sensors, and discuss how this directly or indirectly relates to the accumulation of unfolded proteins in the ER lumen. Chronic or irreversible ER stress triggers cell death by apoptosis. Gordon Shore, Feroz Papa, and Scott Oakes summarize the complex signaling pathways initiating apoptosis by ER stress, where cross talk between the ER and the mitochondria play a central role. The authors focus on addressing the role of the BCL-2 protein family on the activation of intrinsic mitochondrial apoptosis pathways, highlighting different cytosolic and transcriptional events that determine the transition between adaptive responses to apoptosis programmed by the UPR to eliminate irreversibly injured cells.

Although diverse families of chaperones, foldases and co-factors are expressed at the ER, only a few protein folding networks have been well defined. However, molecular explanations for specific substrate recognition and quality control mechanisms are poorly defined. Here we present a series of reviews covering different aspects of protein maturation. Amy Lee summarizes what is known about the biology of the key ER folding chaperone BiP/Grp78, and its emerging role in diverse pathological conditions including cancer. In two reviews, David B. Williams and Linda M. Hendershot describe the best characterized mechanism of protein quality control at the ER, the calnexin cycle. In addition, they give an overview of the function of a family of ER foldases, the protein disulfide isomerases (PDIs), in folding, quality control and degradation of abnormally folded proteins. PDIs are also becoming key factors in establishing the redox tone of the ER. Riccardo Bernasconi and Maurizio Molinari overview the ERAD process and how this pathway affects the efficiency of the protein folding process at the ER and its relation to pathological conditions.

Lysosomal-mediated degradation is becoming a fundamental process for the control of the haft-life of proteins and the degradation of misfolded, aggregate prone proteins. Ana Maria Cuervo reviews the relevance of Chaperone-mediated autophagy in the selective degradation of soluble cytosolic proteins in lysosomes, and also points out a key role for Chaperone-mediated autophagy in the cellular defense against proteotoxicity. David Rubinsztein and Guido Kroemer present two reviews highlighting the emerging relevance of macroautophagy in maintaining the homeostasis of the nervous system. They also discuss the actual impact of macroautophagy in the clearance of protein aggregates related to neurodegenerative diseases, including Parkinson’s disease, amyotrophic lateral sclerosis, Huntington’s disease among others. In addition, recent evidence suggesting an actual impairment of macroautophagy as a causative factor in aging-related disorders is also discussed.

Strategies to increase the efficiency of quality control mechanisms, to reduce protein aggregation and to enhance folding are suggested to be beneficial in the setting of diseases associated with the disruption of protein homeostasis.  Jeffery Kelly reviews recent chemical and biological therapeutic strategies to restore protein homeostasis, which could be achieved by enhancing the biological capacity of the proteostasis network or through small molecule to stabilize misfolding-prone proteins. In summary, this volume of Current Opinion in Cell Biology compiles the most recent advances in understanding the impact of protein folding stress in physiology and disease, and integrates a variety of complex mechanisms that evolved to maintain protein homeostasis in a dynamic way in the context of a changing environment. The biomedical applications of developing strategies to cope with protein folding stress have profound implications for the treatment of the most prevalent diseases in the human population.

7.1.8 Proteome sequencing goes deep

Richards AL1Merrill AE2Coon JJ3.
Curr Opin Chem Biol. 2015 Feb; 24:11-7
http://dx.doi.org/10.1016/j.cbpa.2014.10.017

Highlights

  • Recent MS advances have transformed the depth of coverage of the human proteome.
  • Expression of half the estimated human protein coding genes can be verified by MS.
  • MS sample preparation, instrumentation, and data analysis techniques are highlighted.

Advances in mass spectrometry (MS) have transformed the scope and impact of protein characterization efforts. Identifying hundreds of proteins from rather simple biological matrices, such as yeast, was a daunting task just a few decades ago. Now, expression of more than half of the estimated ∼20 000 human protein coding genes can be confirmed in record time and from minute sample quantities. Access to proteomic information at such unprecedented depths has been fueled by strides in every stage of the shotgun proteomics workflow — from sample processing to data analysis — and promises to revolutionize our understanding of the causes and consequences of proteome variation.

  1. Advances in proteomic sample preparation
  2. Advances in peptide separation and MS instrumentation
  3. Advances in computational proteomics
  4. Conclusions and outlook

Mg²+ is critical for maintaining the positional integrity of closely clustered phosphate groups. These clusters appear in numerous and distinct parts of the cell nucleus and cytoplasm. The Mg²+ ion maintains the integrity of nucleic acids, ribosomes and proteins. In addition, this ion acts as an oligo-element with role in energy catalysis. [6] Biological cell membranes and cell walls exhibit poly-anionic charges on the surface. This finding has important implications for the transport of ions, particularly because different membranes preferentially bind different ions. Both Mg²+ and Ca²+ regularly stabilize membranes by cross-linking the carboxylated and phosphorylated head groups of lipids.

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Mitochondrial Isocitrate Dehydrogenase and Variants

Writer and Curator: Larry H. Bernstein, MD, FCAP 

2.1.4      Mitochondrial Isocitrate Dehydrogenase (IDH) and variants

2.1.4.1 Accumulation of 2-hydroxyglutarate is not a biomarker for malignant progression of IDH-mutated low grade gliomas

Juratli TA, Peitzsch M, Geiger K, Schackert G, Eisenhofer G, Krex D.
Neuro Oncol. 2013 Jun;15(6):682-90
http://dx.doi.org:/10.1093/neuonc/not006

Low-grade gliomas (LGG) occur in the cerebral hemispheres and represent 10%–15% of all astrocytic brain tumors.1 Despite long-term survival in many patients, 50%–75% of patients with LGG eventually die of either progression of a low-grade tumor or transformation to a malignant glioma.2 The time to progression can vary from a few months to several years,35 and the median survival among patients with LGG ranges from 5 to 10 years.6,7 Among several risk factors, only age, histology, tumor location, and Karnofsky performance index have generally been accepted as prognostic factors for patients with LGG.8,9 As a prognostic molecular marker, only 1p19q codeletion was identified as such in pure oligodendrogliomas. However, this association was not seen in either astrocytomas or oligoastrocytomas.10

Somatic mutations in human cytosolic isocitrate dehydrogenases 1 (IDH1) were first described in 2008 in ∼12% of glioblastomas11 and later in acute myeloid leukemia, in which the reported mutations were missense and specific for a single R132 residue.11,12 Some gliomas lacking cytosolic IDH1 mutations were later observed to have mutations in IDH2, the mitochondrial homolog of IDH1.12 IDH mutations are the most commonly mutated genes in many types of gliomas, with incidences of up to 75% in grade II and grade III gliomas.13,14 Further frequent mutations in patients with LGG were recently identified, including inactivating alterations in alpha thalassemia/mental retardation syndrome X-linked (ATRX), inactivating mutations in 2 suppressor genes, homolog of Drosophila capicua (CIC) and far-upstream binding protein 1 (FUBP1), in about 70% of grade II gliomas and 57% of sGBM.1517 The association between ATRX mutations with IDHmutations and the association between CIC/FUBP1 mutations and IDH mutations and 1p/19q loss are especially common among the grade II-III gliomas and remarkably homogeneous in terms of genetic alterations and clinical characteristics.16

It was thought that IDH mutations might be a prognostic factor in LGG, predicting a prolonged survival from the beginning of the disease.1823 However, this assumption, as shown in our and other earlier studies, had to be corrected because survival among patients who have LGG with IDH mutations is only improved after transformation to secondary high-grade gliomas.18,19,24 Furthermore, it had already been demonstrated that an IDH mutation is not a biomarker for further malignant transformation in LGG.18 IDH1 and IDH2 catalyze the oxidative decarboxylation of isocitrate to α-ketoglutarate (α-KG) and reduce NADP to NADPH.25 The mutations inactivate the standard enzymatic activity of IDH112 and confer novel activity on IDH1 for conversion of α-KG and NADPH to 2-hydroxyglutarate (2HG) and NADP+, supporting the evidence thatIDH1 and 2 are proto-oncogenes. This gain of function causes an accumulation of 2HG in glioma and acute myeloid leukemia samples.26,27 The 2HG levels in cancers with IDH mutations are found to be consistently elevated by 10–100-fold, compared with levels in samples lacking mutations of IDH1 or IDH2.26,28Nevertheless, how exactly the production or accumulation of 2HG by mutant IDH might drive cancer development is not well understood.

In the present study, we postulate that intratumoral 2HG could be a useful biomarker that predicts the malignant transformation of WHO grade II LGG. We therefore screened for IDH mutations in patients with LGG and measured the accumulation of 2HG in 2 populations of patients, patients with LGG with and without malignant transformation, with use of liquid chromatography–tandem mass spectrometry (LC-MS/MS). Furthermore, we compared the concentrations of 2HG in LGG and their consecutive secondary glioblastomas (sGBM) to evaluate changes in metabolite levels during the malignant progression.

Objectives: To determine whether accumulation of 2-hydroxyglutarate in IDH-mutated low-grade gliomas (LGG; WHO grade II) correlates with their malignant transformation and to evaluate changes in metabolite levels during malignant progression. Methods: Samples from 54 patients were screened for IDH mutations: 17 patients with LGG without malignant transformation, 18 patients with both LGG and their consecutive secondary glioblastomas (sGBM; n = 36), 2 additional patients with sGBM, 10 patients with primary glioblastomas (pGBM), and 7 patients without gliomas. The cellular tricarboxylic acid cycle metabolites, citrate, isocitrate, 2-hydroxyglutarate, α-ketoglutarate, fumarate, and succinate were profiled by liquid chromatography-tandem mass spectrometry. Ratios of 2-hydroxyglutarate/isocitrate were used to evaluate differences in 2-hydroxyglutarate accumulation in tumors from LGG and sGBM groups, compared with pGBM and nonglioma groups. Results: IDH1 mutations were detected in 27 (77.1%) of 37 patients with LGG. In addition, in patients with LGG with malignant progression (n = 18), 17 patients were IDH1 mutated with a stable mutation status during their malignant progression. None of the patients with pGBM or nonglioma tumors had an IDH mutation. Increased 2-hydroxyglutarate/isocitrate ratios were seen in patients with IDH1-mutated LGG and sGBM, in comparison with those with IDH1-nonmutated LGG, pGBM, and nonglioma groups. However, no differences in intratumoral 2-hydroxyglutarate/isocitrate ratios were found between patients with LGG with and without malignant transformation. Furthermore, in patients with paired samples of LGG and their consecutive sGBM, the 2-hydroxyglutarate/isocitrate ratios did not differ between both tumor stages. Conclusion: Although intratumoral 2-hydroxyglutarate accumulation provides a marker for the presence of IDH mutations, the metabolite is not a useful biomarker for identifying malignant transformation or evaluating malignant progression.

LC-MS/MS Analysis of Tricarboxylic Acid Cycle (TCA) Metabolites

Instrumentation included an AB Sciex QTRAP 5500 triple quadruple mass spectrometer coupled to a high-performance liquid chromatography (HPLC) system from Shimadzu containing a binary pump system, an autosampler, and a column oven. Targeted analyses of citrate, isocitrate, α-ketoglutarate (α-KG), succinate, fumarate (Sigma-Aldrich), and 2-hydroxyglutarate (2HG; SiChem GmbH) were performed in multiple reaction monitoring (MRM) scan mode with use of negative electrospray ionization (-ESI). Expected mass/charge ratios (m/z), assumed as [M-H+], were m/z 190.9, m/z 191.0, m/z 145.0, m/z 116.9, m/z 114.8, and m/z 147.0 for citrate, isocitrate, α-KG, succinate, fumarate, and 2HG, respectively. For quantification, ratios of analytes and respective stable isotope-labeled internal standards (IS) (Table 2) were used. For quantification of isocitrate and 2HG, stable isotope-labeled succinate was used as IS because of unavailability of labeled analogs. MRM transitions are summarized in Table 2.

IDH1 Mutation and Outcome

An IDH1 mutation was detected in 27 of 35 patients with LGG (77.1%), in 10 of 17 patients in LGG1 (59%), and in 17 of 18 patients in LGG2 (95%). In all cases, IDH1 mutations were found on R132. IDH2mutations were not detected in any of the patients. The IDH1 mutation status was stable during progression from LGG to sGBM in all patients in LGG2. None of the patients with pGBM or nonglioma had an IDH mutation. Patients with LGG with an IDH1 mutation had a median PFS of 3.3 years, which was comparable to that among patients with wild-type LGG (2.8 years; P > .05). Furthermore, the OS among patients with LGG with an IDH1 mutation was not statistically different at 13.0 years compared with that among patients with LGG without an IDH1 mutation, who had an OS of 9.3 years (P = .66).

LC-MS/MS Profiling of TCA Metabolites

TCA metabolites, citrate, isocitrate, α-ketoglutarate, succinate, fumarate, and 2-hydroxyglutarate were measured in glioma samples with and without an IDH1 mutation, in samples identified as primary GBM, and in nonglioma brain tumor specimens (Fig. 1). No differences in citrate, isocitrate, α-KG, succinate, and fumarate concentrations were found when comparing all of the latter groups. Concentrations of 2HG, a side product in IDH1-mutated gliomas, were 20–34-fold higher in IDH1-mutated gliomas (0.64–0.81 µmol/g), compared with non–IDH1-mutated LGG1 (P ≤ .001). No differences were observed between IDH1-mutated gliomas and IDH1-nonmutated LGG2 and sGBM, caused by strongly elevated 2HG levels in either 1 or 2 samples in these groups, respectively. Furthermore, in IDH1-mutated gliomas, 2HG concentrations were a mean of 20 times higher than in pGBM and nongliomas (P ≤ .001) (Fig. 1). No differences were observed between the single groups of IDH1-mutated gliomas LGG1, LGG2, and sGBM in relation to 2HG concentration.

Fig. 1.  Dot-box and whisker plots show concentration ranges for TCA metabolites measured in IDH1-nonmutated (IDH1wt) and IDH1-mutated (IDH1mut) LGG and sGBM and in pGBM and nonglioma tumor specimens

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3661092/bin/not00601.gif

To detect possible differences among the IDH1-mutated LGG1, LGG2, and sGBM, the α-KG/isocitrate and 2HG/isocitrate ratios were used in additional tests. Therefore, the direct precursor-product relation would correct for all differences possibly expected during pre-analytical processing. To prove this, analyte ratios ofIDH1-mutated and nonmutated gliomas were compared. IDH1-mutated gliomas showed a 2HG/isocitrate ratio that was 13 times higher (P ≤ .001) (Fig. 2A), which corresponds to a lower accumulation of 2HG inIDH1-nonmutated gliomas. α-KG/isocitrate ratios were determined to be approximately 10-fold higher inIDH1-mutated gliomas than in IDH1-nonmutated gliomas (P = .005) (Fig. 2B), which also implies lower accumulation of α-KG in IDH1-nonmutated gliomas.

2-hydroxyglutarate-to-isocitrate-ratios

2-hydroxyglutarate-to-isocitrate-ratios

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3661092/bin/not00602.jpg

Fig. 2.  2-Hydroxyglutarate to isocitrate ratios (A) and α-ketoglutarate to isocitrate ratios (B) for IDH1-nonmutated (IDH1wt) and IDH1-mutated (IDH1mut) gliomas (LGG and sGBM); boxes span the 25th and 75th percentiles with median, and whiskers represent the 10th and 90th percentiles with points as outliers. Abbreviations: LGG, low-grade gliomas; sGBM, secondary glioblastomas.

2HG/isocitrate and α-KG/isocitrate ratios, respectively, were calculated in all 8 specimen groups (Fig. 3). In addition to the differences in 2HG/isocitrate ratios of IDH1-mutated and nonmutated gliomas (Fig. 2A), the ratios in IDH1-mutated gliomas were 4–9 times higher, compared with those in pGBM (P ≤ .001), and 3–6 times higher, compared with those in non-glioma tumor specimens, which was not statistically significant (Fig. 3A). In detail, ratios of 2HG and isocitrate were established to be 13, 9.4, and 22 times higher in IDH1-mutated LGG1, LGG2, and their consecutive sGBM, respectively, than in IDH1-nonmutated LGG1 (Fig. 3A). No significant differences were observed between IDH1-mutated gliomas and IDH1-nonmutated LGG2 and sGBM. The comparison of 2HG/isocitrate ratios between IDH1-nonmutated gliomas and IDH1-mutated LGG2 and sGBM showed no statistically significant differences. However, a trend toward higher ratios inIDH1-mutated LGG1/2 was seen. Furthermore, no differences could be determined by comparing 2HG/isocitrate ratios measured in the groups of IDH1-mutated LGG1 and LGG2. Although 2HG/isocitrate ratios in IDH1-mutated secondary glioblastomas are 1.7 and 2.3 times higher than in the LGG1 and LGG2 groups, respectively, no statistically significant differences were observed.   Fig. 3.

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The absence of a straight trend to higher 2HG/isocitrate ratios during malignant progression is shown by paired analysis of IDH1-mutated LGG2 and their consecutive sGBM (Fig. 3C). Similar findings were observed using the α-KG/isocitrate ratios. Although significant differences were found, with ratios approximately 10 times higher in IDH1-mutated glioblastomas than in IDH1-nonmutated glioblastomas (Fig. 2B), it was not possible to differentiate among the 3 IDH1-mutated glioblastoma groups LGG1, LGG2, and their consecutive sGBM with use of this analyte ratio (Fig. 3B and D).

On the basis of a comprehensive analysis of cellular TCA metabolites from several cohorts of patients with glioma and nonglioma, our study provides evidence that the level of 2HG accumulation is not suitable as an early biomarker for distinguishing patients with LGG in relation to their course of malignancy. To our knowledge, this is the first report of a paired analysis of 2HG levels in LGG and their consecutive sGBM showing stable 2HG accumulation during malignant progression. This fact assumes that malignant transformation of IDH-mutated LGG appears to be independent of their intracellular 2HG accumulation. Considering these results, we could not stratify patients with LGG into subgroups with distinct survival.

2.1.4.2 An Inhibitor of Mutant IDH1 Delays Growth and Promotes Differentiation of Glioma Cells

Rohle D1, Popovici-Muller J, Palaskas N, Turcan S, Grommes C, et al.
Science. 2013 May 3; 340(6132):626-30
http://dx.doi.org:/10.1126/science.1236062

The recent discovery of mutations in metabolic enzymes has rekindled interest in harnessing the altered metabolism of cancer cells for cancer therapy. One potential drug target is isocitrate dehydrogenase 1 (IDH1), which is mutated in multiple human cancers. Here, we examine the role of mutant IDH1 in fully transformed cells with endogenous IDH1 mutations. A selective R132H-IDH1 inhibitor (AGI-5198) identified through a high-throughput screen blocked, in a dose-dependent manner, the ability of the mutant enzyme (mIDH1) to produce R-2-hydroxyglutarate (R-2HG). Under conditions of near-complete R-2HG inhibition, the mIDH1 inhibitor induced demethylation of histone H3K9me3 and expression of genes associated with gliogenic differentiation. Blockade of mIDH1 impaired the growth of IDH1-mutant–but not IDH1-wild-type–glioma cells without appreciable changes in genome-wide DNA methylation. These data suggest that mIDH1 may promote glioma growth through mechanisms beyond its well-characterized epigenetic effects.

Somatic mutations in the metabolic enzyme isocitrate dehydrogenase (IDH) have recently been identified in multiple human cancers, including glioma (12), sarcoma (34), acute myeloid leukemia (56), and others. All mutations map to arginine residues in the catalytic pockets of IDH1 (R132) or IDH2 (R140 and R172) and confer on the enzymes a new activity: catalysis of alpha-ketoglutarate (2-OG) to the (R)-enantiomer of 2-hydroxyglutarate (R-2HG) (78). R-2HG is structurally similar to 2-OG and, due to its accumulation to millimolar concentrations in IDH1-mutant tumors, competitively inhibits 2-OG–dependent dioxygenases (9).

The mechanism by which mutant IDH1 contributes to the pathogenesis of human glioma remains incompletely understood. Mutations in IDH1 are found in 50 to 80% of human low-grade (WHO grade II) glioma, a disease that progresses to fatal WHO grade III (anaplastic glioma) and WHO grade IV (glioblastoma) tumors over the course of 3 to 15 years. IDH1 mutations appear to precede the occurrence of other mutations (10) and are associated with a distinctive gene-expression profile (“proneural” signature), DNA hypermethylation [CpG island methylator phenotype (CIMP)], and certain clinicopathological features (1113). When ectopically expressed in immortalized human astrocytes, R132H-IDH1 promotes the growth of these cells in soft agar (14) and induces epigenetic alterations found in IDH1-mutant human gliomas (15,16). However, no tumor formation was observed when R132H-IDH1 was expressed from the endogenousIDH1 locus in several cell types of the murine central nervous system (17).

To explore the role of mutant IDH1 in tumor maintenance, we used a compound that was identified in a high-throughput screen for compounds that inhibit the IDH1-R132H mutant homodimer (fig. S1 and supplementary materials) (18). This compound, subsequently referred to as AGI-5198 (Fig. 1A), potently inhibited mutant IDH1 [R132H-IDH1; half-maximal inhibitory concentration (IC50), 0.07 µM) but not wild-type IDH1 (IC50 > 100 µM) or any of the examined IDH2 isoforms (IC50 > 100 µM) (Fig. 1B). We observed no induction of nonspecific cell death at the highest examined concentration of AGI-5198 (20 µM).

Fig. 1 An R132H-IDH1 inhibitor blocks R-2HG production and soft-agar growth of IDH1-mutant glioma cells

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an-r132h-idh1-inhibitor-blocks-r-2hg-production-and-soft-agar-growth-of-idh1-mutant-glioma-cells

an-r132h-idh1-inhibitor-blocks-r-2hg-production-and-soft-agar-growth-of-idh1-mutant-glioma-cells

(A) Chemical structure of AGI-5198. (B) IC50 of AGI-5198 against different isoforms of IDH1 and IDH2, measured in vitro. (C) Sanger sequencing chromatogram (top) and comparative genomic hybridization profile array (bottom) of TS603 glioma cells. (D) AGI-5198 inhibits R-2HG production in R132H-IDH1 mutant TS603 glioma cells. Cells were treated for 2 days with AGI-5198, and R-2HG was measured in cell pellets. R-2HG concentrations are indicated above each bar (in mM). Error bars, mean ± SEM of triplicates. (E and F) AGI-5198 impairs soft-agar colony formation of (E) IDH1-mutant TS603 glioma cells [*P < 0.05, one-way analysis of variance (ANOVA)] but not (F) IDH1–wild-type glioma cell lines (TS676 and TS516). Error bars, mean ± SEM of triplicates.

We next explored the activity of AGI-5198 in TS603 glioma cells with an endogenous heterozygous R132H-IDH1 mutation, the most common IDH mutation in glioma (2). TS603 cells were derived from a patient with anaplastic oligodendroglioma (WHO grade III) and harbor another pathognomomic lesion for this glioma subtype, namely co-deletion of the short arm of chromosome 1 (1p) and the long arm of chromosome 19 (19q) (19) (Fig. 1C). Measurements of R-2HG concentrations in pellets of TS603 glioma cells demonstrated dose-dependent inhibition of the mutant IDH1 enzyme by AGI-5198 (Fig. 1D). When added to TS603 glioma cells growing in soft agar, AGI-5198 inhibited colony formation by 40 to 60% (Fig. 1E). AGI-5198 did not impair colony formation of two patient-derived glioma lines that express only the wild-type IDH1allele (TS676 and TS516) (Fig. 1F), further supporting the selectivity of AGI-5198.

After exploratory pharmacokinetic studies in mice (fig. S2), we examined the effects of orally administered AGI-5198 on the growth of human glioma xenografts. When given daily to mice with established R132H-IDH1 glioma xenografts, AGI-5198 [450 mg per kg of weight (mg/kg) per os] caused 50 to 60% growth inhibition (Fig. 2A). Treatment was tolerated well with no signs of toxicity during 3 weeks of daily treatment (fig. S3). Tumors from AGI-5198– treated mice showed reduced staining with an antibody against the Ki-67 protein, a marker used for quantification of tumor cell proliferation in human brain tumors. In contrast, staining with an antibody against cleaved caspase-3 showed no differences between tumors from vehicle and AGI-5198–treated mice (fig. S4), suggesting that the growth-inhibitory effects of AGI-5198 were primarily due to impaired tumor cell proliferation rather than induction of apoptotic cell death. AGI-5198 did not affect the growth of IDH1 wild-type glioma xenografts (Fig. 2B).

Fig. 2 AGI-5198 impairs growth of IDH1-mutant glioma xenografts in mice

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AGI-5198 impairs growth of IDH1-mutant glioma xenografts in mice

AGI-5198 impairs growth of IDH1-mutant glioma xenografts in mice

Given the likely prominent role of R-2HG in the pathogenesis of IDH-mutant human cancers, we investigated whether intratumoral depletion of this metabolite would have similar growth inhibitory effects onR132H-IDH1-mutant glioma cells as AGI-5198. We engineered TS603 sublines in which IDH1–short hairpin RNA (shRNA) targeting sequences were expressed from a doxycycline-inducible cassette. Doxycycline had no effect on IDH1 protein levels in cells expressing the vector control but depleted IDH1 protein levels by 60 to 80% in cells infected with IDH1-shRNA targeting sequences (Fig. 2C). We next injected these cells into the flanks of mice with severe combined immunodeficiency and, after establishment of subcutaneous tumors, randomized the mice to receive either regular chow or doxycycline-containing chow. As predicted from our experiments with AGI-5198, doxycycline impaired the growth of TS603 glioma cells expressing inducible IDH1-shRNAs in soft agar (fig. S5) and in vivo (Fig. 2D) but had no effect on the growth of tumors expressing the vector control (fig. S6). Immunohistochemistry (IHC) with a mutant-specific R132H-IDH1 antibody confirmed depletion of the mutant IDH1 protein in IDH1-shRNA tumors treated with doxycycline. This was associated with an 80 to 90% reduction in intratumoral R-2HG levels, similar to the levels observed in TS603 glioma xenografts treated with AGI-5198 (fig. S7). Knockdown of the IDH1 protein in R132C-IDH1-mutant HT1080 sarcoma cells similarly impaired the growth of these cells in vitro and in vivo (fig. S8).

Fig. 3 AGI-5198 promotes astroglial differentiation in R132H-IDH1  mutant cells
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3985613/bin/nihms504357f3.jpg

The gene-expression data suggested that treatment of IDH1-mutant glioma xenografts with AGI-5198 promotes a gene-expression program akin to gliogenic (i.e., astrocytic and oligodendrocytic) differentiation. To examine this question further, we treated TS603 glioma cells ex vivo with AGI-5198 and performed immunofluorescence for glial fibrillary acidic protein (GFAP) and nestin (NES) as markers for astrocytes and undifferentiated neuroprogenitor cells, respectively. .. We investigated whether blockade of mutant IDH1 could restore this ability, and this was indeed the case (Fig. 3D). These results indicate that mIDH1 plays an active role in restricting cellular differentiation potential, and this defect is acutely reversible by blockade of the mutant enzyme.

In the developing central nervous system, gliogenic differentiation is regulated through changes in DNA and histone methylation (24). Mutant IDH1 can affect both epigenetic processes through R-2HG mediated suppression of TET (ten-eleven translocation) methyl cytosine hydroxylases and Jumonji-C domain histone demethylases (JHDMs). We therefore sought to define the epigenetic changes that were associated with the acute growth-inhibitory effects of AGI-5198 in vivo. .. Treatment of mice with AGI-5198 resulted in dose-dependent reduction of intratumoral R-2HG with partial R-2HG reduction at the 150 mg/kg dose (0.85 ± 0.22 mM) and near-complete reduction at the 450 mg/kg dose (0.13 ± 0.03 mM) (Fig. 4A).

Fig. 4 Dose-dependent inhibition of histone methylation in IDH1-mutant gliomas after short term treatment with AGI-5198

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We next examined whether acute pharmacological blockade of the mutant IDH1 enzyme reversed the CIMP, which is strongly associated with IDH1-mutant human gliomas (12). ..  On a genome-wide scale, we observed no statistically significant change in the distribution of β values between AGI-5198– and vehicle-treated tumors (Fig. 4B) (supplementary materials).
We next examined the kinetics of histone demethylation after inhibition of the mutant IDH1 enzyme. The histone demethylases JMJD2A and JMJD2C, which remove bi- and trimethyl marks from H3K9, are significantly more sensitive to inhibition by the R-2HG oncometabolite than other 2-OG–dependent oxygenases (891425). Restoring their enzymatic activity in IDH1-mutant cancer cells would thus be expected to require near-complete inhibition of R-2HG production. Consistent with this prediction, tumors from the 450 mg/kg AGI-5198 cohort showed a marked decrease in H3K9me3 staining, but there was no decrease in H3K9me3 staining in tumors from the 150 mg/kg AGI-5198 cohort (Fig. 4C) (fig. S11). Of note, AGI-5198 did not decrease H3K9 trimethylation in IDH1–wild-type glioma xenografts (fig. S12A) or in normal astrocytes (fig. S12B), demonstrating that the effect of AGI-5198 on histone methylation was not only dose-dependent but also IDH1-mutant selective.

Because the inability to erase repressive H3K9 methylation can be sufficient to impair cellular differentiation of nontransformed cells (16), we examined the TS603 xenograft tumors for changes in the RNA expression of astrocytic (GFAP, AQP4, and ATP1A2) and oligodendrocytic (CNP and NG2) differentiation markers by real-time polymerase chain reaction (RT-PCR). Compared with vehicletreated tumors, we observed an increase in the expression of astroglial differentiation genes only in tumors treated with 450 mg/kg AGI-5198 (Fig. 4D).

In summary, we describe a tool compound (AGI-5198) that impairs the growth of R132H-IDH1-mutant, but not IDH1 wild-type, glioma cells. This data demonstrates an important role of mutant IDH1 in tumor maintenance, in addition to its ability to promote transformation in certain cellular contexts (1426). Effector pathways of mutant IDH remain incompletely understood and may differ between tumor types, reflecting clinical differences between these disorders. Although much attention has been directed toward TET-family methyl cytosine hydroxylases and Jumonji-C domain histone demethylases, the family of 2-OG–dependent dioxygenases includes more than 50 members with diverse functions in collagen maturation, hypoxic sensing, lipid biosynthesis/metabolism, and regulation of gene expression (27).

2.1.4.3 Detection of oncogenic IDH1 mutations using MRS

OC Andronesi, O Rapalino, E Gerstner, A Chi, TT Batchelor, et al.
J Clin Invest. 2013;123(9):3659–3663
http://dx.doi.org:/10.1172/JCI67229

The investigation of metabolic pathways disturbed in isocitrate dehydrogenase (IDH) mutant tumors revealed that the hallmark metabolic alteration is the production of D-2-hydroxyglutarate (D-2HG). The biological impact of D-2HG strongly suggests that high levels of this metabolite may play a central role in propagating downstream the effects of mutant IDH, leading to malignant transformation of cells. Hence, D-2HG may be an ideal biomarker for both diagnosing and monitoring treatment response targeting IDH mutations. Magnetic resonance spectroscopy (MRS) is well suited to the task of noninvasive D-2HG detection, and there has been much interest in developing such methods. Here, we review recent efforts to translate methodology using MRS to reliably measure in vivo D-2HG into clinical research.

Recurrent heterozygous somatic mutations of the isocitrate dehydrogenase 1 and 2 (IDH1 and IDH2) genes were recently found by genome-wide sequencing to be highly frequent (50%–80%) in human grade II–IV gliomas (12). IDH mutations are also often observed in several other cancers, including acute myeloid leukemia (3), central/periosteal chondrosarcoma and enchondroma (4), and intrahepatic cholangiocarcinoma (5). The identification of frequent IDH mutations in multiple cancers suggests that this pathway is involved in oncogenesis. Indeed, increasing evidence demonstrates that IDH mutations alter downstream epigenetic and genetic cellular signal transduction pathways in tumors (67). In gliomas, IDH1 mutations appear to define a distinct clinical subset of tumors, as these patients have a 2- to 4-fold longer median survival compared with patients with wild-type IDH1 gliomas (8). IDH1 mutations are especially common in secondary glioblastoma (GBM) arising from lower-grade gliomas, arguing that these mutations are early driver events in this disease (9). Despite aggressive therapy with surgery, radiation, and cytotoxic chemotherapy, average survival of patients with GBM is less than 2 years, and less than 10% of patients survive 5 years or more (10).

The discovery of cancer-related IDH1 mutations has raised hopes that this pathway can be targeted for therapeutic benefit (1112). Methods that can rapidly and noninvasively identify patients for clinical trials and determine the pharmacodynamic effect of candidate agents in patients enrolled in trials are particularly important to guide and accelerate the translation of these treatments from bench to bedside. Magnetic resonance spectroscopy (MRS) can play an important role in clinical and translational research because IDH mutated tumor cells have such a distinct molecular phenotype (13,14).

The family of IDH enzymes includes three isoforms: IDH1, which localizes in peroxisomes and cytoplasm, and IDH2 and IDH3, which localize in mitochondria as part of the tricarboxylic acid cycle (11). All three wild-type enzymes catalyze the oxidative decarboxylation of isocitrate to α-ketoglutarate (αKG), using the cofactor NADP+ (IDH1 and IDH2) or NAD+(IDH3) as the electron acceptor. To date, only mutations of IDH1 and IDH2 have been identified in human cancers (11), and only one allele is mutated. In gliomas, about 90% of IDH mutations involve a substitution in IDH1 in which arginine 132 (R132) from the catalytic site is replaced by a histidine (IDH1 R132H), known as the canonical IDH1 mutation (8). A number of noncanonical mutations such as IDH1 R132C, IDH1 R132S, IDH1 R132L, and IDH1 R132G are less frequently present. Arginine R172 in IDH2 is the corresponding residue to R132 in IDH1, and the most common mutation is IDH2 R172K. In addition to IDH2 R172K, IDH2 R140Q has also been observed in acute myeloid leukemia. Although most IDH1 mutations occur at R132, a small number of mutations producing D-2-hydroxyglutarate (D-2HG) occur at R100, G97, and Y139 (15). However, only a single residue is mutated in either IDH1 or IDH2 in a given tumor.

IDH mutations result in a very high accumulation of the oncometabolite D-2HG in the range of 5- to 35-mM levels, which is 2–3 orders of magnitude higher than D-2HG levels in tumors with wild-type IDH or in healthy tissue (13). All IDH1 G97, R100, R132, and Y139 and IDH2 R140 and R172 mutations confer a neomorphic activity to the IDH1/2 enzymes, switching their activity toward the reduction of αKG to D-2HG, using NADPH as a cofactor (15). The gain of function conferred by these mutations is possible because in each tumor cell a copy of the wild-type allele exists to supply the αKG substrate and NADPH cofactor for the mutated allele.

A cause and effect relationship between IDH mutation and tumorigenesis is probable, and D-2HG appears to play a pivotal role as the relay agent. Evidence is mounting that high levels of D-2HG alter the biology of tumor cells toward malignancy by influencing the activity of enzymes critical for regulating the metabolic (14) and epigenetic state of cells (671618). D-2HG may act as an oncometabolite via competitive inhibition of αKG-dependent dioxygenases (16). This includes inhibition of histone demethylases and 5-methlycytosine hydroxylases (e.g., TET2), leading to genome-wide alterations in histone and DNA hypermethylation as well as inhibition of hydroxylases, resulting in upregulation of HIF-1 (19). The effects of D-2HG have been shown to be reversible in leukemic transformation (18), which gives further evidence that treatments that lower D-2HG could be a valid therapeutic approach for IDH-mutant tumors. In addition to increased D-2HG, widespread metabolic disturbances of the cellular metabolome have been measured in cells with IDH mutations, including changes in amino acid concentration (increased levels of glycine, serine, threonine, among others, and decreased levels of aspartate and glutamate), N-acetylated amino acids (N-acetylaspartate, N-acetylserine, N-acetylthreonine), glutathione derivatives, choline metabolites, and TCA cycle intermediates (fumarate, malate) (14). These metabolic changes might be exploited for therapy. For example, IDH mutations cause a depletion of NADPH, which lowers the reductive capabilities of tumor cells (20) and perhaps makes them more susceptible to treatments that create free radicals (e.g., radiation) (21).

In vivo MRS of D-2HG in IDH mutant tumors

D-2HG may be an optimal biomarker for tumors with IDH mutations, as it ideally fulfills several important requirements: (a) there is virtually no normal D-2HG background — in cells without IDH mutations, D-2HG is produced as an error product of normal metabolism and is only present at trace levels; (b) 99% of tumors with IDH mutations have increased levels of D-2HG by several orders of magnitude; (c) the only other known cause of elevated 2HG is hydroxyglutaric aciduria (in this case, high L-2HG caused by a mutation in 2HG dehydrogenase), which is a rare inborn error of metabolism that presents with a different clinical phenotype and marked developmental anomalies in early childhood. Hence, tumors displaying increased levels of D-2HG are unlikely to represent false-positive cases for IDH mutations. Furthermore, this raises the possibility that D-2HG levels could also be used to quantify and predict the efficacy of drugs targeting mutant IDH1 for antitumor therapy (1115). In fact, it is hard to find a similar example of another tumor biomarker metabolite that is so well supported by the underlying biology.

The high levels of D-2HG observed in IDH1-mutant gliomas are amenable to detection by in vivo MRS. Given that the detection threshold of in vivo MRS is around 1 mM (1 μmol/g, wet tissue), D-2HG should be measurable only in situations in which it accumulates due to IDH1 mutations. Conversely, D-2HG is not expected to be detectable in tumors in which IDH1 is not mutated or in healthy tissues. In addition, ex vivo MRS measurements of intact biopsies (22) or extracts reach higher sensitivity 0.1–0.01 mM (0.1–0.01 μmol/g) and can be used as a cheaper and faster alternative to mass spectrometry.

Recently, reliable detection of D-2HG using in vivo 1H MRS was demonstrated in glioma patients (2930). Andronesi et al. reported the unambiguous detection of D-2HG in mutant IDH1 glioma in vivo using 2D correlation spectroscopy (COSY) and J-difference spectroscopy (29). In 2D COSY the overlapping signals are resolved along a second orthogonal chemical shift dimension (3132), and in the case of D-2HG, the cross-peaks resulting from the scalar coupling of Hα-Hβ protons show up in a region that is free of the contribution of other metabolites in both healthy and wild-type tumors. While 2D COSY retains all the metabolites in the spectrum, J-difference spectroscopy (2533) takes the opposite approach instead by focusing on the metabolite of interest, such as D-2HG, and selectively applying a narrow-band radiofrequency pulse to selectively refocus the Hα-Hβ scalar coupling evolution, then removing the contribution of overlapping metabolites. In this case a 1D difference spectrum with the Hα signal of D-2HG is detected at 4.02 ppm. Both methods have strengths and weaknesses: 2D COSY has the highest resolving power to disentangle overlapping metabolites, but has less sensitivity and quantification is more complex; J-difference spectroscopy has increased sensitivity, and quantification is straightforward, but it is susceptible to subtraction errors.

In Table 1, a comparison is made among the published methods for D-2HG detection. Results selected from the literature are shown in Figure 1. Besides the approaches discussed thus far, other methods are available in the in vivo MRS armamentarium that could be perhaps explored for reliable detection of 2D-HG, such as multiple-quantum filtering sequences (3435) and a variety of 2D spectroscopic methods (3639).

Table 1 Summary of in vivo 1H MRS methods used in the literature for detection of D-2HG in patients with mutant IDH glioma

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Figure 1 In vivo D-2HG measurements: (A) J-difference spectroscopy with MEGA-LASER sequence in a patient with GBM with mutant IDH1. Adapted with permission from Science Translational Medicine (29). (B) Spectral editing with PRESS sequence of TE 97 ms (TE1: 32 ms, TE2: 65 ms) in a patient with mutant IDH1 oligodendroglioma. Adapted with permission from Nature Medicine (30). (C) Spectra acquired with PRESS sequence of TE 30 ms in a patient with mutant IDH1 anaplastic astrocytoma. Adapted with permission from Journal of Neuro-Oncology (24). Cho, choline; Cre, creatine; Gln, glutamine; Glu, glutamate; Lac, lactate; MM, macromolecules; NAA, N-acetyl- aspartate.

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Ex vivo MRS of D-2HG in tumors with IDH mutations

The panoply of methods and ability of ex vivo MRS (50) to detect D-2HG in patient samples is far superior to in vivo MRS because the above list of limitations and artifacts is not of concern.

Metabolic profiling of intact tumor biopsies as small as 1 mg can be performed with high-resolution magic angle spinning (HRMAS) (5153). HRMAS preserves the integrity of the samples that can be further analyzed with immunohistochemistry, genomics, or other metabolic profiling tools such as mass spectrometry. Detection of D-2HG in mutant IDH1 glioma was confirmed by ex vivo HRMAS experiments (295455). In addition to D-2HG, ex vivo HRMAS studies can detect quantitative and qualitative changes for a large number of metabolites in IDH mutated tumors (5455).

The example of IDH1 mutations is a perfect illustration of the rapid pace of progress brought to the medical sciences by the power and advances of modern technology: genome-wide sequencing, metabolomics, and imaging.

In vivo MRS has the unique ability to noninvasively probe IDH mutations by measuring the endogenously produced oncometabolite D-2HG. As an imaging-based technique, it has the benefit of posing minimal risk to the patients, can be performed repeatedly as many times as necessary, and can probe tumor heterogeneity without disturbing the internal milieu. To date, in vivo MRS is the only imaging method that is specific to IDH mutations — existing PET or SPECT radiotracers are not specific (5657), IDH-targeted agents for in vivo molecular imaging do not yet exist, and the prohibitive cost of radiotracers will likely limit their clinical development.
2.1.4.4 Hypoxia promotes IDH-dependent carboxylation of α-KG to citrate to support cell growth and viability

DR Wise, PS Ward, JES Shay, JR Cross, Joshua J Grube, et al.
PNAS | Dec 6, 2011; 108(49):19611–19616
http://www.pnas.org/cgi/doi/10.1073/pnas.1117773108

Citrate is a critical metabolite required to support both mitochondrial bioenergetics and cytosolic macromolecular synthesis. When cells proliferate under normoxic conditions, glucose provides the acetyl-CoA that condenses with oxaloacetate to support citrate production. Tricarboxylic acid (TCA) cycle anaplerosis is maintained primarily by glutamine. Here we report that some hypoxic cells are able to maintain cell proliferation despite a profound reduction in glucose-dependent citrate production. In these hypoxic cells, glutamine becomes a major source of citrate. Glutamine-derived α-ketoglutarate is reductively carboxylated by the NADPH-linked mitochondrial isocitrate dehydrogenase (IDH2) to form isocitrate, which can then be isomerized to citrate. The increased IDH2-dependent carboxylation of glutamine-derived α-ketoglutarate in hypoxia is associated with a concomitantincreased synthesisof2-hydroxyglutarate (2HG) in cells with wild-type IDH1 and IDH2. When either starved of glutamine or rendered IDH2-deficient by RNAi, hypoxic cells areunable toproliferate.The reductive carboxylation ofglutamine is part of the metabolic reprogramming associated with hypoxia-inducible factor 1 (HIF1), as constitutive activation of HIF1 recapitulates the preferential reductive metabolism of glutamine derived α-ketoglutarate even in normoxic conditions. These data support a role for glutamine carboxylation in maintaining citrate synthesis and cell growth under hypoxic conditions.

Citrate plays a critical role at the center of cancer cell metabolism. It provides the cell with a source of carbon for fatty acid and cholesterol synthesis (1). The breakdown of citrate by ATP-citrate lyase is a primary source of acetyl-CoA for protein acetylation (2). Metabolism of cytosolic citrate by aconitase and IDH1 can also provide the cell with a source of NADPH for redox regulation and anabolic synthesis. Mammalian cells depend on the catabolism of glucose and glutamine to fuel proliferation (3). In cancer cells cultured at atmospheric oxygen tension (21% O2), glucose and glutamine have both been shown to contribute to the cellular citrate pool, with glutamine providing the major source of the four-carbon molecule oxaloacetate and glucose providing the major source of the two-carbon molecule acetyl-CoA (4, 5). The condensation of oxaloacetate and acetyl-CoA via citrate synthase generates the 6 carbon citrate molecule. However, both the conversion of glucose-derived pyruvate to acetyl-CoA by pyruvate dehydrogenase (PDH) and the conversion of glutamine to oxaloacetate through the TCA cycle depend on NAD+, which can be compromised under hypoxic conditions. This raises the question of how cells that can proliferate in hypoxia continue to synthesize the citrate required for macromolecular synthesis.

This question is particularly important given that many cancers and stem/progenitor cells can continue proliferating in the setting of limited oxygen availability (6, 7). Louis Pasteur first highlighted the impact of hypoxia on nutrient metabolism based on his observation that hypoxic yeast cells preferred to convert glucose into lactic acid rather than burning it in an oxidative fashion. The molecular basis forthis shift in mammalian cells has been linked to the activity of the transcription factor HIF1 (8–10). Stabilization of the labile HIF1α subunit occurs in hypoxia. It can also occur in normoxia through several mechanisms including loss of the von Hippel-Lindau tumor suppressor (VHL), a common occurrence in renal carcinoma(11). Although hypoxia and/or HIF1α stabilization is a common feature of multiple cancers, to date the source of citrate in the setting of hypoxia or HIF activation has not been determined. Here, we study the sources of hypoxic citrate synthesis in a glioblastoma cell line that proliferates in profound hypoxia (0.5% O2). Glucose uptake and conversion to lactic acid increased in hypoxia. However, glucose conversion into citrate dramatically declined. Glutamine consumption remained constant in hypoxia, and hypoxic cells were addicted to the use of glutamine in hypoxia as a source of α-ketoglutarate. Glutamine provided the major carbon source for citrate synthesis during hypoxia. However, the TCA cycle-dependent conversion of glutamine into citric acid was significantly suppressed. In contrast, there was a relative increase in glutamine-dependent citrate production in hypoxia that resulted from carboxylation of α-ketoglutarate. This reductive synthesis required the presence of mitochondrial isocitrate dehydrogenase 2 (IDH2). In confirmation of the reverse flux through IDH2, the increased reductive metabolism of glutamine-derived α-ketoglutarate in hypoxia was associated with increased synthesis of 2HG. Finally, constitutive HIF1α-expressing cells also demonstrated significant reductive carboxylation-dependent synthesis of citrate in normoxia and a relative defect in the oxidative conversion of glutamine into citrate. Collectively, the data demonstrate that mitochondrial glutaminemetabolismcanbereroutedthroughIDH2-dependent citrate synthesis in support of hypoxic cell growth.

Some Cancer Cells Can Proliferate at 0.5% O2 Despite a Sharp Decline in Glucose-Dependent Citrate Synthesis. At 21% O2, cancer cells have been shown to synthesize citrate by condensing glucose-derived acetyl-CoA with glutamine-derived oxaloacetate through the activity of the canonical TCA cycle enzyme citrate synthase (4). In contrast, less is known regarding the synthesis of citrate by cells that can continue proliferating in hypoxia. The glioblastoma cellline SF188 is able to proliferate at 0.5% O2 (Fig.1A),a level of hypoxia that is sufficient to stabilize HIF1α (Fig. 1B) and predicted to limit respiration (12, 13). Consistent with previous observations in hypoxic cells, we found that SF188 cells demonstrated increased lactate production when incubated in hypoxia
(Fig. 1C), and the ratio of lactate produced to glucose consumed increased demonstrating an increase in the rate of anaerobic glycolysis. When glucose-derived carbon in the form of pyruvate is converted to lactate, it is diverted away from subsequent metabolism that can contribute to citrate production. However, we observed that SF188 cells incubated in hypoxia maintain their intracellular citrate to ∼75% of the level maintained under normoxia (Fig. 1D). This prompted an investigation of how proliferating cells maintain citrate production under hypoxia. Increased glucose uptake and glycolytic metabolism are critical elements of the metabolic response to hypoxia. To evaluate the contributions made by glucose to the citrate pool under normoxia or hypoxia, SF188 cells incubated in normoxia or hypoxia were cultured in medium containing 10 mM [U-13C] glucose. Following a 4-h labeling period, cellular metabolites were extracted and analyzed for isotopic enrichment.

Fig. 1. SF188 glioblastoma cells proliferate at 0.5% O2 despite a profound reduction in glucose-dependent citrate synthesis. (A) SF188 cells were plated in complete medium equilibrated with 21% O2 (Normoxia) or 0.5% O2 (Hypoxia), total viable cells were counted 24 h and 48 h later (Day 1 and Day 2), and population doublings were calculated. Data are the mean ± SEM of four independent experiments. (B) Western blot demonstrates stabilized HIF1α protein in cells cultured in hypoxia compared with normoxia. (C) Cells were grown in normoxia or hypoxia for 24 h, after which culture medium was collected. Medium glucose and lactate levels were measured and compared with the levels in fresh medium. (D) Cells were cultured for 24 h as in C. Intracellular metabolism was then quenched with 80% MeOH prechilled to −80 °C that was spiked with a 13C-labeled citrate as an internal standard. Metabolites were then extracted, and intracellular citrate levels were analyzed with GC-MS and normalized to cell number. Data for C and D are the mean ± SEM of three independent experiments. (E) Model depicting the pathway for cit+2 production from [U-13C] glucose. Glucose uniformly 13Clabeled will generate pyruvate+3. Pyruvate+3 can be oxidatively decarboxylated by PDH to produce acetyl-CoA+2, which can condense with unlabeled oxaloacetate to produce cit+2. (F) Cells were cultured for 24 h as in C and D, followed by an additional 4 h of culture in glucose-deficient medium supplemented with 10 mM [U-13C]glucose. Intracellular metabolites were then extracted, and 13C-enrichment in cellular citrate was analyzed by GCMS and normalized to the total citrate pool size. Data are the mean ± SD of three independent cultures from a representative of two independent experiments. *P < 0.05, ***P < 0.001

Fig. 2. Glutamine carbon is required for hypoxic cell viability and contributes to increased citrate production through reductive carboxylation relative to oxidative metabolism in hypoxia. (A) SF188 cells were cultured for 24 h in complete medium equilibrated with either 21% O2 (Normoxia) or 0.5% O2 (Hypoxia). Culture medium was then removed from cells and analyzed for glutamine levels which were compared with the glutamine levels in fresh medium. Data are the mean ± SEM of three independent experiments. (B) The requirement for glutamine to maintain hypoxic cell viability can be satisfied by α-ketoglutarate. Cells were cultured in complete medium equilibrated with 0.5% O2 for 24 h, followed by an additional 48 h at 0.5% O2 in either complete medium (+Gln), glutamine-deficient medium (−Gln), or glutamine-deficient medium supplemented with 7 mM dimethyl α-ketoglutarate (−Gln +αKG). All medium was preconditioned in 0.5% O2. Cell viability was determined by trypan blue dye exclusion. Data are the mean and range from two independent experiments. (C) Model depicting the pathways for cit+4 and cit+5 production from [U-13C]glutamine (glutamine+5). Glutamine+5 is catabolized to α-ketoglutarate+5, which can then contribute to citrate production by two divergent pathways. Oxidative metabolism produces oxaloacetate+4, which can condense with unlabeled acetyl-CoA to produce cit+4. Alternatively, reductive carboxylation produces isocitrate+5, which can isomerize to cit+5. (D) Glutamine contributes to citrate production through increased reductive carboxylation relative to oxidative metabolism in hypoxic proliferating cancer cells. Cells were cultured for 24 h as in A, followed by 4 h of culture in glutamine-deficient medium supplemented with 4 mM [U-13C]glutamine. 13C enrichment in cellular citrate was quantitated with GC-MS. Data are the mean ± SD of three independent cultures from a representative of three independent experiments. **P < 0.01.

Fig. 3. Cancer cells maintain production of other metabolites in addition to citrate through reductive carboxylation in hypoxia. (A) SF188 cells were cultured in complete medium equilibrated with either 21% O2 (Normoxia) or 0.5% O2 (Hypoxia) for 24 h. Intracellular metabolism was then quenched with 80% MeOH prechilled to −80 °C that was spiked with a 13C-labeled citrate as an internal standard. Metabolites were extracted, and intracellular aspartate (asp), malate (mal), and fumarate (fum) levels were analyzed with GC-MS. Data are the mean± SEM of three independent experiments. (B) Model for the generation of aspartate, malate, and fumarate isotopomers from [U-13C] glutamine (glutamine+5). Glutamine+5 is catabolized to α-ketoglutarate+5. Oxidative metabolism of α-ketoglutarate+5 produces fumarate+4, malate+4, and oxaloacetate (OAA)+4 (OAA+ 4 is in equilibrium with aspartate+4 via transamination). Alternatively, α-ketoglutarate+5 can be reductively carboxylated to generate isocitrate+5 and citrate+5. Cleavage of citrate+5 in the cytosol by ATP-citrate lyase (ACL) will produce oxaloacetate+3 (in equilibrium with aspartate+3). Oxaloacetate+3 can be metabolized to malate+3 and fumarate+3. (C) SF188 cells were cultured for 24 h as in A, and then cultured for an additional 4 h in glutamine-deficient medium supplemented with 4 mM [U-13C] glutamine. 13C enrichment in cellular aspartate, malate, and fumarate was determined by GC-MS and normalized to the relevant metabolite total pool size. Data shown are the mean ± SD of three independent cultures from a representative of three independent experiments. **P < 0.01, ***P < 0.001.

Glutamine Carbon Metabolism Is Required for Viability in Hypoxia. In addition to glucose, we have previously reported that glutamine can contribute to citrate production during cell growth under normoxic conditions (4). Surprisingly, under hypoxic conditions, we observed that SF188 cells retained their high rate of glutamine consumption (Fig. 2A). Moreover, hypoxic cells cultured in glutamine-deficient medium displayed a significant loss of viability (Fig. 2B). In normoxia, the requirement for glutamine to maintain viability of SF188 cells can be satisfied by α-ketoglutarate, the downstream metabolite of glutamine that is devoid of nitrogenous groups (14). α-ketoglutarate cannot fulfill glutamine’s roles as a nitrogen source for nonessential amino acid synthesis or as an amide donor for nucleotide or hexosamine synthesis, but can be metabolized through the oxidative TCA cycle to regenerate oxaloacetate, and subsequently condense with glucose-derived acetyl-CoA to produce citrate. To test whether the restoration of carbon from glutamine metabolism in the form of α-ketoglutarate could rescue the viability defect of glutamine-starved SF188 cells even under hypoxia, SF188 cells incubated in hypoxia were cultured in glutamine-deficient medium supplemented with a cell-penetrant form of α-ketoglutarate (dimethyl α-ketoglutarate). The addition of dimethyl α-ketoglutarate rescued the defect in cell viability observed upon glutamine withdrawal (Fig. 2B). These data demonstrate that, even under hypoxic conditions, when the ability of glutamine to replenish oxaloacetate through oxidative TCA cycle metabolism is diminished, SF188 cells retain their requirement for glutamine as the carbon backbone for α-ketoglutarate. This result raised the possibility that glutamine could be the carbon source for citrate production through an alternative, nonoxidative, pathway in hypoxia.

Cells Proliferating in Hypoxia Preferentially Produce Citrate Through Reductive Carboxylation Rather than Oxidative Metabolism. To distinguish the pathways by which glutamine carbon contributes to citrate production in normoxia and hypoxia, SF188 cells were incubated in normoxia or hypoxia and cultured in medium containing 4 mM [U-13C] glutamine. After 4 h of labeling, intracellular metabolites were extracted and analyzed by GC-MS. In normoxia,the cit+4 pool constituted the majority of the enriched citrate in the cell. Cit+4 arises from the oxidative metabolism of glutamine-derived α-ketoglutarate+5 to oxaloacetate+4 and its subsequent condensation with unenriched, glucose-derived acetyl-CoA (Fig.2C and D). Cit+5 constituted a significantly smaller pool than cit+4 in normoxia. Conversely, in hypoxia, cit+5 constituted the majority of the enriched citrate in the cell. Cit+5 arises from the reductive carboxylation of glutamine-derived α-ketoglutarate+5 to isocitrate+5, followed by the isomerization of isocitrate+5 to cit+5 by aconitase. The contribution of cit+4 to the total citrate pool was significantly lower in hypoxia than normoxia, and the accumulation of other enriched citrate species in hypoxia remained low. These data support the role of glutamine as a carbon source for citrate production in normoxia and hypoxia.

Cells Proliferating in Hypoxia Maintain Levels of Additional Metabolites Through Reductive Carboxylation. Previous work has documented that, in normoxic conditions, SF188 cells use glutamine as the primary anaplerotic substrate, maintaining the pool sizes of TCA cycle intermediates through oxidative metabolism (4). Surprisingly, we found that, when incubated in hypoxia, SF188 cells largely maintained their levels of aspartate (in equilibrium with oxaloacetate), malate, and fumarate (Fig. 3A). To distinguish how glutamine carbon contributes to these metabolites in normoxia and hypoxia, SF188 cells incubated in normoxia or hypoxia were cultured in medium containing 4 mM [U-13C] glutamine. After a 4-h labeling period, metabolites were extracted and the intracellular pools of aspartate, malate, and fumarate were analyzed by GC-MS. In normoxia, the majority of the enriched intracellular asparatate, malate, and fumarate were the +4 species, which arise through oxidative metabolism of glutamine-derived α-ketoglutarate (Fig. 3 B and C). The +3 species, which can be derived from the citrate generated by the reductive carboxylation of glutamine derived α-ketoglutarate, constituted a significantly lower percentage of the total aspartate, malate, and fumarate pools. By contrast, in hypoxia, the +3 species constituted a larger percentage of the total aspartate, malate, and fumarate pools than they did in normoxia. These data demonstrate that, in addition to citrate, hypoxic cells preferentially synthesize oxaloacetate, malate, and fumarate through the pathway of reductive carboxylation rather than the oxidative TCA cycle.

IDH2 Is Critical in Hypoxia for Reductive Metabolism of Glutamine and for Cell Proliferation.We hypothesized that the relative increase in reductive carboxylation we observed in hypoxia could arise from the suppression of α-ketoglutarate oxidation through the TCA cycle. Consistent with this, we found that α-ketoglutarate levels increased in SF188 cells following 24 h in hypoxia (Fig. 4A). Surprisingly, we also found that levels of the closely related metabolite 2-hydroxyglutarate (2HG) increased in hypoxia, concomitant with the increase in α-ketoglutarate under these conditions. 2HG can arise from the noncarboxylating reduction of α-ketoglutarate (Fig. 4B). Recent work has found that specific cancer-associated mutations in the active sites of either IDH1 or IDH2 lead to a 10- to 100-fold enhancement in this activity facilitating 2HG production (15–17), but SF188 cells lack IDH1/2 mutations. However, 2HG levels are also substantially elevated in the inborn error of metabolism 2HG aciduria, and the majority of patients with this disease lack IDH1/2 mutations. As 2HG has been demonstrated to arise in these patients from mitochondrial α-ketoglutarate (18), we hypothesized that both the increased reductive carboxylation of glutamine-derived α-ketoglutarate to citrate and the increased 2HG accumulation we observed in hypoxia could arise from increased reductive metabolism by wild-type IDH2 in the mitochondria.

Fig. 4. Reductive carboxylation of glutamine-derived α-ketoglutarate to citrate in hypoxic cancer cells is dependent on mitochondrial IDH2. (A) α-ketoglutarate and 2HG increase in hypoxia. SF188 cells were cultured in complete medium equilibrated with either 21% O2 (Normoxia) or 0.5% O2 (Hypoxia) for 24 h. Intracellular metabolites were then extracted, cell extracts spiked with a 13C-labeled citrate as an internal standard, and intracellular α-ketoglutarate and 2HG levels were analyzed with GC-MS. Data shown are the mean ± SEM of three independent experiments. (B) Model for reductive metabolism from glutamine-derived α-ketoglutarate. Glutamine+5 is catabolized to α-ketoglutarate+5. Carboxylation of α-ketoglutarate+5 followed by reduction of the carboxylated intermediate (reductive carboxylation) will produce isocitrate+5, which can then isomerize to cit+5. In contrast, reductive activity on α-ketoglutarate+5 that is uncoupled from carboxylation will produce 2HG+5. (C) IDH2 is required for reductive metabolism of glutamine-derived α-ketoglutarate in hypoxia. SF188 cells transfected with a siRNA against IDH2 (siIDH2) or nontargeting negative control (siCTRL) were cultured for 2 d in complete medium equilibrated with 0.5% O2.(Upper) Cells were then cultured at 0.5% O2 for an additional 4 h in glutamine-deficient medium supplemented with 4 mM [U-13C]glutamine. 13C enrichment in intracellular citrate and 2HG was determined and normalized to the relevant metabolite total pool size. (Lower) Cells transfected and cultured in parallel at 0.5% O2 were counted by hemocytometer (excluding nonviable cells with trypan blue staining) or harvested for protein to assess IDH2 expression by Western blot. Data shown for GC-MS and cell counts are the mean ± SD of three independent cultures from a representative experiment. **P < 0.01, ***P < 0.001.

Reprogramming of Metabolism by HIF1 in the Absence of Hypoxia Is Sufficient to Induce Increased Citrate Synthesis by Reductive Carboxylation Relative to Oxidative Metabolism. The relative increase in the reductive metabolism of glutamine-derived α-ketoglutarate at 0.5% O2 may be explained by the decreased ability to carry out oxidative NAD+-dependent reactions as respiration is inhibited (12, 13). However, a shift to preferential reductive glutamine metabolism could also result from the active reprogramming of cellular metabolism by HIF1 (8–10), which inhibits the generation of mitochondrial acetyl-CoA necessary for the synthesis of citrate by oxidative glucose and glutamine metabolism (Fig. 5A). To better understand the role of HIF1 in reductive glutamine metabolism, we used VHL-deficient RCC4 cells, which display constitutive expression of HIF1α under normoxia (Fig. 5B).

Fig. 5. Reprogramming of metabolism by HIF1 in the absence of hypoxia is sufficient to induce reductive carboxylation of glutamine-derived α-ketoglutarate. (A) Model depicting how HIF1 signaling’s inhibition of pyruvate dehydrogenase (PDH) activity and promotion of lactate dehydrogenase-A (LDH-A) activity can block the generation of mitochondrial acetyl-CoA from glucose-derived pyruvate, thereby favoring citrate synthesis from reductive carboxylation of glutamine-derived α-ketoglutarate. (B) Western blot demonstrating HIF1α protein in RCC4 VHL−/− cells in normoxia with a nontargeting shRNA (shCTRL), and the decrease in HIF1α protein in RCC4 VHL−/− cells stably expressing HIF1α shRNA (shHIF1α). (C) HIF1-induced reprogramming of glutamine metabolism. Cells from B at 21% O2 were cultured for 4 h in glutamine-deficient medium supplemented with 4 mM [U-13C]glutamine. Intracellular metabolites were then extracted, and 13C enrichment in cellular citrate was determined by GC-MS. Data shown are the mean ± SD of three independent cultures from a representative of three independent experiments. ***P < 0.001.

Compared with glucose metabolism, much less is known regarding how glutamine metabolism is altered under hypoxia. It has also remained unclear how hypoxic cells can maintain the citrate production necessary for macromolecular biosynthesis. In this report, we demonstrate that in contrast to cells at 21% O2, where citrate is predominantly synthesized through oxidative metabolism of both glucose and glutamine, reductive carboxylation of glutamine carbon becomes the major pathway of citrate synthesis in cells that can effectively proliferate at 0.5% O2. Moreover, we show that in these hypoxic cells, reductive carboxylation of glutamine-derived α-ketoglutarate is dependent on mitochondrial IDH2. Although others have previously suggested the existence of reductive carboxylation in cancer cells (19, 20), these studies failed to demonstrate the intracellular localization or specific IDH isoform responsible for the reductive carboxylation flux. Recently, we identified IDH2 as an isoform that contributes to reductive carboxylation in cancer cells incubated at 21% O2 (16), but remaining unclear were the physiological importance and regulation of this pathway relative to oxidative metabolism, as well as the conditions where this reductive pathway might be advantageous for proliferating cells. Here we report that IDH2-mediated reductive carboxylation of glutamine-derived α-ketoglutarate to citrate is an important feature of cells proliferating in hypoxia. Moreover, the reliance on reductive glutamine metabolism can be recapitulated in normoxia by constitutive HIF1 activation in cells with loss of VHL. The mitochondrial NADPH/NADP+ ratio required to fuel the reductive reaction through IDH2 can arise from the increased NADH/NAD+ ratio existing in the mitochondria under hypoxic conditions (21, 22), with the transfer of electrons from NADH to NADP+ to generate NADPH occurring through the activity of the mitochondrial transhydrogenase (23).

In further support of the increased mitochondrial reductive glutamine metabolism that we observe in hypoxia, we report here that incubation in hypoxia can lead to elevated 2HG levels in cells lacking IDH1/2 mutations. 2HG production from glutamine-derived α-ketoglutarate significantly decreased with knockdown of IDH2, supporting the conclusion that 2HG is produced in hypoxia by enhanced reverse flux of α-ketoglutarate through IDH2in a truncated, noncarboxylating reductive reaction. However,other mechanisms may also contribute to 2HG elevation in hypoxia. These include diminished oxidative activity and/or enhanced reductive activity of the 2HG dehydrogenase, a mitochondrial enzyme that normally functions to oxidize 2HG back to α-ketoglutarate (25). The level of 2HG elevation we observe in hypoxic cells is associated with a concomitant increase in α-ketoglutarate, and is modest relative to that observed in cancers with IDH1/2 gain-of-function mutations. Nonetheless, 2HG elevation resulting from hypoxia in cells with wild-type IDH1/2 may hold promise as a cellular or serum biomarker for tissues undergoing chronic hypoxia and/or excessive glutamine metabolism.

2.1.4.5 IDH mutation impairs histone demethylation and results in a block to cell differentiation.

C Lu, PS Ward, GS Kapoor, D Rohle, S Turcan, et al.
Nature 483, 474–478 (22 Mar 2012)
http://dx.doi.org:/10.1038/nature10860

Recurrent mutations in isocitrate dehydrogenase 1 (IDH1) and IDH2 have been identified in gliomas, acute myeloid leukaemias (AML) and chondrosarcomas, and share a novel enzymatic property of producing 2-hydroxyglutarate (2HG) from α-ketoglutarate1, 2, 3, 4, 5, 6. Here we report that 2HG-producing IDH mutants can prevent the histone demethylation that is required for lineage-specific progenitor cells to differentiate into terminally differentiated cells. In tumour samples from glioma patients, IDH mutations were associated with a distinct gene expression profile enriched for genes expressed in neural progenitor cells, and this was associated with increased histone methylation. To test whether the ability of IDH mutants to promote histone methylation contributes to a block in cell differentiation in non-transformed cells, we tested the effect of neomorphic IDH mutants on adipocyte differentiation in vitro. Introduction of either mutant IDH or cell-permeable 2HG was associated with repression of the inducible expression of lineage-specific differentiation genes and a block to differentiation. This correlated with a significant increase in repressive histone methylation marks without observable changes in promoter DNA methylation. Gliomas were found to have elevated levels of similar histone repressive marks. Stable transfection of a 2HG-producing mutant IDH into immortalized astrocytes resulted in progressive accumulation of histone methylation. Of the marks examined, increased H3K9 methylation reproducibly preceded a rise in DNA methylation as cells were passaged in culture. Furthermore, we found that the 2HG-inhibitable H3K9 demethylase KDM4C was induced during adipocyte differentiation, and that RNA-interference suppression of KDM4C was sufficient to block differentiation. Together these data demonstrate that 2HG can inhibit histone demethylation and that inhibition of histone demethylation can be sufficient to block the differentiation of non-transformed cells.

Figure 1: IDH mutations are associated with dysregulation of glial differentiation and global histone methylation.

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Figure 2: Differentiation arrest induced by mutant IDH or 2HG is associated with increased global and promoter-specific H3K9 and H3K27 methylation.

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Figure 3: IDH mutation induces histone methylation increase in CNS-derived cells and can alter cell lineage gene expression.

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2.1.4.6 Isocitrate dehydrogenase mutations in leukemia

McKenney AS, Levine RL.
J Clin Invest. 2013 Sep; 123(9):3672-7
http://dx.doi.org:/1172/JCI67266

Recent genome-wide discovery studies have identified a spectrum of mutations in different malignancies and have led to the elucidation of novel pathways that contribute to oncogenic transformation. The discovery of mutations in the genes encoding isocitrate dehydrogenase (IDH) has uncovered a critical role for altered metabolism in oncogenesis, and the neomorphic, oncogenic function of IDH mutations affects several epigenetic and gene regulatory pathways. Here we discuss the relevance of IDH mutations to leukemia pathogenesis, therapy, and outcome and how mutations in IDH1 and IDH2 affect the leukemia epigenome, hematopoietic differentiation, and clinical outcome.

Mutations in isocitrate dehydrogenase (IDH) have been identified in a spectrum of human malignancies. Mutations in IDH1 were first identified in an exome resequencing analysis of patients with colorectal cancer (1). Shortly thereafter, recurrent IDH1 and IDH2 mutations were found in patients with glioma, most commonly in patients who present with lower-grade gliomas (2). IDH1 mutations were subsequently discovered in patients with acute myeloid leukemia (AML) through whole genome sequencing (3), which was followed by the identification of somatic IDH2 mutations in patients with AML (46). Further studies revealed that IDH mutations induce a neomorphic function to produce the oncometabolite 2-hydroxyglutarate (2HG) (78), which can inhibit many cellular processes (910). In particular, the ability of 2HG to alter the epigenetic landscape makes IDH a prototypical target for prognostic studies and drug targeting in leukemias.

IDH proteins catalyze the oxidative decarboxylation of isocitrate to α-ketoglutarate (αKG, also known as 2-oxoglutarate). IDH3 primarily functions as the allosterically regulated, rate-limiting enzymatic step in the TCA cycle, while the other two isoforms, which are mutated in cancer, utilize this catalytic process in additional contexts including metabolism and glucose sensing (IDH1) and regulation of oxidative respiration (IDH2) (1112). Loss-of-function mutations in other TCA cycle components have previously been identified in other types of cancer, specifically in mutations in fumarate hydratase (FH) and succinate dehydrogenase (SDH). As such, many hypothesized that IDH1/2 mutations would result in loss of metabolic activity, and indeed, enzymatic studies confirmed that the mutant protein’s ability to perform its native function is markedly attenuated, as measured by reduced production of αKG or NADPH (1314).

However, the genetic data relating to these mutations were more consistent with gain-of-function mutation: all of the observed alterations are somatic, heterozygous mutations that occur at highly conserved positions, which appear to be functionally equivalent between different isoforms. This discrepancy was resolved when metabolic profiling showed that the IDH1 mutant protein catalyzes a neomorphic reaction that converts αKG to 2HG. 2HG can be detected at high levels in gliomas harboring these mutations (4), and the accumulation of 2HG was further found to be common to oncogenic IDH mutations (8). This finding indicated that 2HG may serve as a potential functional biomarker of IDH mutation, and later, metabolomics analysis of 2HG content in patient samples led to the identification of IDH2 mutations in leukemias (6). IDH mutant proteins have been proposed to form a heterodimer with the remaining wild-type IDH isoform (7814), which is consistent with genetic data showing retention of the wild-type allele in IDH-mutant cancers.

The discovery of the neomorphic function of IDH opened the doors for true investigation into the implications of these mutations and the resultant intracellular accumulation of 2HG. 2HG is thought to competitively inhibit the activity of a broad spectrum of αKG-dependent enzymes with known and postulated roles in oncogenic transformation. Some targets, such as the prolyl 4-hydroxylases, have unclear implications in leukemia pathogenesis. However, the recent demonstration that alterations in epigenetic factors occur in the majority of acute leukemias led to investigations of the effects of 2HG on the jumonji C domain histone-modifying enzymes and the newly characterized tet methylcytosine dioxygenase (TET) family of methylcytosine hydroxylases. Importantly, expression of IDH or exposure to chemically modified, cell-permeable 2HG affects hematopoietic differentiation, likely due to changes in epigenetic regulation that induce reversible alterations in differentiation states (15).

TET1 was initially discovered as a binding partner of mixed-lineage leukemia (MLL) in patients with MLL-translocated AML (1617). However, the function of the TET gene family and its role in leukemogenesis remained unknown until TET1 was shown to catalyze αKG-dependent addition of a hydroxyl group to methylated cytosines (18), which precedes DNA demethylation and results in altered epigenetic control (10,1824). TET enzymes have further been shown to catalyze conversion of 5-methylcytosine (5mC) to 5-formylcytosine (5fC) or 5-carboxylcytosine (5cC) (2526). These data suggest that loss of TET2 enzymatic function can lead to aberrant cytosine methylation and epigenetic silencing in malignant settings. TET2mutations were initially found in array-comparative genomic hybridization and genome-wide SNP arrays, which identified microdeletions containing this gene in a patient with myeloproliferative neoplasm (MPN) and myelodysplastic syndrome (MDS) (27). This discovery was followed by the identification of somatic missense, nonsense, and frameshift TET2 mutations in patients with MDS, MPN, AML, and other myeloid malignancies (2730). Most TET2 alleles result in nonsense/frameshift mutations, which result in loss of TET2 catalytic function (31), consistent with a tumor suppressor function in myeloid malignancies.

When 2HG was hypothesized to affect specific enzymatic processes in oncogenesis, AML patients were observed to harbor IDH1/2 and TET mutations in a mutually exclusive manner (9). Of note, exploration into the functional relationship between these mutant IDH proteins and the function of TET2 ultimately suggested a role for 2HG in inhibiting TET enzymatic function. IDH- or TET2-mutant patient samples are characterized by increased global hypermethylation of DNA and transcriptional silencing of genes with hypermethylated promoters. Expression of these IDH-mutant alleles in experimental models was further observed to result in increased methylation, reduced hydroxymethylation, and impaired TET2 function (9). Finally, in biochemical assays, 2HG was shown to directly inhibit TET2 as well as other αKG-dependent enzymes (10). These data demonstrate that a key feature of IDH1/2 mutations in hematopoietic cells is to impair TET2 function and disrupt DNA methylation (​Figure1).

Figure 1 Normal IDH functions to convert isocitrate to αKG in the Krebs cycle.

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mutations have been observed with IDH1_2 mutations leukemias

mutations have been observed with IDH1_2 mutations leukemias

Many mutations have been observed in conjunction with IDH1/2 mutations in different types of leukemia.

In de novo adult AML, these mutations should be observed in the context of other prognostic indicators such as CEBPA, NPM1, and DNMT3A mutation. In AML that progresses from MPN, IDH1/2 mutations can be examined separately from the mutations responsible for MPN (such as JAK2 or MPL mutations) using paired pre- and post-transformation samples. Evidence supports a role for IDH1/2 hotspot mutations in leukemic transformation.

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Conditional loss of Tet2 expression in mice results in a chronic myelomonocytic leukemia (CMML) phenotype and in increased hematopoietic self-renewal in vivo (32). Of note, in vitro systems have shown that TET2 silencing and expression of IDH1/2 mutant alleles leads to impaired hematopoietic differentiation and expansion of stem/progenitor cells (9). More recently, IDH1 (R132H) conditional knockin mice with hematopoietic-specific recombination were analyzed and found to have myeloid expansion, although they did not develop overt AML. This suggests that IDH mutations by themselves cannot promote overt transformation, and that additional genetic, epigenetic, and/or microenvironmental factors are needed to cooperate with mutant IDH alleles to promote hematologic malignancies. The hematopoietic defects included increased numbers of hematopoietic stem cells and myeloid progenitor cells, and a DNA methylation signature that was similar to observed patterns in primary AML patients with IDH1 mutations (33). While many models of IDH-mutant leukemia have shown potential, future models that incorporate the complexity seen in human patients are needed, as discussed below. More recently, the effects of IDH1/2 mutations on hematopoietic cell lines were replicated using exogenously applied 2HG, which was rendered permeable to the cell membrane by esterification. The Kaelin group used this system to dissect the role of 2HG in the αKG-dependent pathways that may be affected in IDH mutation, and to show that the effects are reversible (34). Tools such as these will help advance our understanding of the biology of IDH mutations and, by extension, the potential therapies that may affect mutant IDH and the downstream pathways. Indeed, given the recent description of mutant-selective IDH1/2 inhibitors (3437), the development of genetically accurate models of IDH mutant–mediated leukemogenesis will be critical to evaluate the effects of targeted therapies in mice with AML and subsequently in the clinical context.

2.1.4.7 The Common Feature of Leukemia-Associated IDH1 and IDH2 Mutations – a Neomorphic Enzyme Activity Converting α-Ketoglutarate to 2-Hydroxyglutarate

PS Ward, J Patel, DR Wise, O Abdel-Wahab, BD Bennett, HA Coller, et al.
Cancer Cell 2010 Mar 16; 17(3):225–234
http://dx.doi.org/10.1016/j.ccr.2010.01.020

Highlights

  • All IDH mutations reported in cancer share a common neomorphic enzymatic activity
  • Both wild-type IDH1 and IDH2 are required for cell proliferation
  • IDH2 R140Q mutations occur in 9% of AML cases
  • Overall, IDH2 mutations appear more common than IDH1 mutations in AML

 

Summary

The somatic mutations in cytosolic isocitrate dehydrogenase 1 (IDH1) observed in gliomas can lead to the production of 2-hydroxyglutarate (2HG). Here, we report that tumor 2HG is elevated in a high percentage of patients with cytogenetically normal acute myeloid leukemia (AML). Surprisingly, less than half of cases with elevated 2HG possessed IDH1 mutations. The remaining cases with elevated 2HG had mutations in IDH2, the mitochondrial homolog of IDH1. These data demonstrate that a shared feature of all cancer-associated IDH mutations is production of the oncometabolite 2HG. Furthermore, AML patients with IDH mutations display a significantly reduced number of other well characterized AML-associated mutations and/or associated chromosomal abnormalities, potentially implicating IDH mutation in a distinct mechanism of AML pathogenesis.

Significance

Most cancer-associated enzyme mutations result in either catalytic inactivation or constitutive activation. Here we report that the common feature of IDH1 and IDH2 mutations observed in AML and glioma is the acquisition of an enzymatic activity not shared by either wild-type enzyme. The product of this neomorphic enzyme activity can be readily detected in tumor samples, and we show that tumor metabolite analysis can identify patients with tumor-associated IDH mutations. Using this method, we discovered a 2HG-producing IDH2 mutation, IDH2 R140Q, that was present in 9% of serial AML samples. Overall, IDH1 and IDH2 mutations were observed in over 23% of AML patients.

Mutations in human cytosolic isocitrate dehydrogenase I (IDH1) occur somatically in > 70% of grade II-III gliomas and secondary glioblastomas, and in 8.5% of acute myeloid leukemias (AML) (Mardis et al., 2009 and Yan et al., 2009). Mutations have also been reported in cancers of the colon and prostate (Kang et al., 2009 and Sjoblom et al., 2006). To date, all reported IDH1 mutations result in an amino acid substitution at a single arginine residue in the enzyme’s active site, R132. A subset of intermediate grade gliomas lacking mutations in IDH1 has been found to harbor mutations in IDH2, the mitochondrial homolog of IDH1. The IDH2 mutations that have been identified in gliomas occur at the analogous residue to IDH1 R132, IDH2 R172. Both IDH1 R132 and IDH2 R172 mutants lack the wild-type enzyme’s ability to convert isocitrate to α-ketoglutarate (Yan et al., 2009). To date, all reported IDH1 or IDH2 mutations are heterozygous, with the cancer cells retaining one wild-type copy of the relevant IDH1 or IDH2 allele. No patient has been reported with both an IDH1 and IDH2 mutation. These data argue against the IDH mutations resulting in a simple loss of function.

Normally both cytosolic IDH1 and mitochondrial IDH2 exist as homodimers within their respective cellular compartments, and the mutant proteins retain the ability to bind to their respective wild-type partner. Therefore, it has been proposed that mutant IDH1 can act as a dominant negative against wild-type IDH1 function, resulting in a decrease in cytosolic α-ketoglutarate levels and leading to an indirect activation of the HIF-1α pathway (Zhao et al., 2009). However, recent work has provided an alternative explanation. The R132H IDH1 mutation observed in gliomas was found to display a gain of function for the NADPH-dependent reduction of α-ketoglutarate to R(–)-2-hydroxyglutarate (2HG) ( Dang et al., 2009). This in vitro activity was confirmed when 2HG was found to be elevated in IDH1-mutated gliomas. Whether this neomorphic activity is a common feature shared by IDH2 mutations was not determined.

IDH1 R132 mutations identical to those reported to produce 2HG in gliomas were recently reported in AML (Mardis et al., 2009). These IDH1 R132 mutations were observed in 8.5% of AML patients studied, and a significantly higher percentage of mutation was observed in the subset of patients whose tumors lacked cytogenetic abnormalities. IDH2 R172 mutations were not observed in this study. However, during efforts to confirm and extend these findings, we found an IDH2 R172K mutation in an AML sample obtained from a 77-year-old woman. This finding confirmed that both IDH1 and IDH2 mutations can occur in AML and prompted us to more comprehensively investigate the role of IDH2 in AML.

The present study was undertaken to see if IDH2 mutations might share the same neomorphic activity as recently reported for glioma-associated IDH1 R132 mutations. We also determined whether tumor-associated 2HG elevation could prospectively identify AML patients with mutations in IDH. To investigate the lack of reduction to homozygosity for either IDH1 or IDH2 mutations in tumor samples, the ability of wild-type IDH1 and/or IDH2 to contribute to cell proliferation was examined.

IDH2 Is Mutated in AML

A recent study employing a whole-genome sequencing strategy in an AML patient resulted in the identification of somatic IDH1 mutations in AML (Mardis et al., 2009). Based on the report that IDH2 mutations were also observed in the other major tumor type in which IDH1 mutations were implicated (Yan et al., 2009), we sequenced the IDH2 gene in a set of de-identified AML DNA samples. Several cases with IDH2 R172 mutations were identified. In the initial case, the IDH2 mutation found, R172K, was the same mutation reported in glioma samples. It has been recently reported that cancer-associated IDH1 R132 mutants display a loss-of-function for the use of isocitrate as substrate, with a concomitant gain-of-function for the reduction of α-ketoglutarate to 2HG (Dang et al., 2009). This prompted us to determine if the recurrent R172K mutation in IDH2 observed in both gliomas and leukemias might also display the same neomorphic activity. In IDH1, the role of R132 in determining IDH1 enzymatic activity is consistent with the stabilizing charge interaction of its guanidinium moiety with the β-carboxyl group of isocitrate (Figure 1A). This β-carboxyl is critical for IDH’s ability to catalyze the interconversion of isocitrate and α-ketoglutarate, with the overall reaction occurring in two steps through a β-carboxyl-containing intermediate (Ehrlich and Colman, 1976). Proceeding in the oxidative direction, this β-carboxyl remains on the substrate throughout the IDH reaction until the final decarboxylating step which produces α-ketoglutarate.

IDH1 R132 and IDH2 R172 Are Analogous Residues

IDH1 R132 and IDH2 R172 Are Analogous Residues

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Figure 1. IDH1 R132 and IDH2 R172 Are Analogous Residues that Both Interact with the β-Carboxyl of Isocitrate

(A) Active site of crystallized human IDH1 with isocitrate.

(B) Active site of human IDH2 with isocitrate, modeled based on the highly homologous and crystallized pig IDH2 structure. For (A) and (B), carbon 6 of isocitrate containing the β-carboxyl is highlighted in cyan, with remaining isocitrate carbons shown in yellow. Carbon atoms of amino acids (green), amines (blue), and oxygens (red) are also shown. Hydrogen atoms are omitted from the figure for clarity. Dashed lines depict interactions < 3.1 Å, corresponding to hydrogen and ionic bonds. Residues coming from the other monomer of the IDH dimer are denoted with a prime (′) symbol.

To understand how R172 mutations in IDH2 might relate to the R132 mutations in IDH1 characterized for gliomas, we modeled human IDH2 based on the pig IDH2 structure containing bound isocitrate (Ceccarelli et al., 2002). Human and pig IDH2 protein share over 97% identity and all active site residues are identical. The active site of human IDH2 was structurally aligned with human IDH1 (Figure 1). Similar to IDH1, in the active site of IDH2 the isocitrate substrate is stabilized by multiple charge interactions throughout the binding pocket. Moreover, like R132 in IDH1, the analogous R172 in IDH2 is predicted to interact strongly with the β-carboxyl of isocitrate. This raised the possibility that cancer-associated IDH2 mutations at R172 might affect enzymatic interconversion of isocitrate and α-ketoglutarate similarly to IDH1 mutations at R132.

Mutation of IDH2 R172K Enhances α-Ketoglutarate-Dependent NADPH Consumption

To test whether cancer-associated IDH2 R172K mutations shared the gain of function in α-ketoglutarate reduction observed for IDH1 R132 mutations (Dang et al., 2009), we overexpressed wild-type or R172K mutant IDH2 in cells with endogenous wild-type IDH2 expression, and then assessed isocitrate-dependent NADPH production and α-ketoglutarate-dependent NADPH consumption in cell lysates. As reported previously (Yan et al., 2009), extracts from cells expressing the R172K mutant IDH2 did not display isocitrate-dependent NADPH production above the levels observed in extracts from vector-transfected cells. In contrast, extracts from cells expressing a comparable amount of wild-type IDH2 markedly increased isocitrate-dependent NADPH production (Figure 2A). However, when these same extracts were tested for NADPH consumption in the presence of α-ketoglutarate, R172K mutant IDH2 expression was found to correlate with a significant enhancement to α-ketoglutarate-dependent NADPH consumption. Vector-transfected cell lysates did not demonstrate this activity (Figure 2B). Although not nearly to the same degree as with the mutant enzyme, wild-type IDH2 overexpression also reproducibly enhanced α-ketoglutarate-dependent NADPH consumption under these conditions.

Expression of R172K Mutant IDH2 Results in Enhanced α-Ketoglutarate-Dependent Consumption of NADPH

Expression of R172K Mutant IDH2 Results in Enhanced α-Ketoglutarate-Dependent Consumption of NADPH

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Figure 2. Expression of R172K Mutant IDH2 Results in Enhanced α-Ketoglutarate-Dependent Consumption of NADPH

(A) 293T cells transfected with wild-type or R172K mutant IDH2, or empty vector, were lysed and subsequently assayed for their ability to generate NADPH from NADP+ in the presence of 0.1 mM isocitrate.

(B) The same cell lysates described in (A) were assayed for their consumption of NADPH in the presence of 0.5 mM α-ketoglutarate. Data for (A) and (B) are each representative of three independent experiments. Data are presented as the mean and standard error of the mean (SEM) from three independent measurements at the indicated time points.

(C) Expression of wild-type and R172K mutant IDH2 was confirmed by western blotting of the lysates assayed in (A) and (B). Reprobing of the same blot with IDH1 antibody as a control is also shown.

Mutation of IDH2 R172K Results in Elevated 2HG Levels

R172K mutant IDH2 lacks the guanidinium moiety in residue 172 that normally stabilizes β-carboxyl addition in the interconversion of α-ketoglutarate and isocitrate. Yet R172K mutant IDH2 exhibited enhanced α-ketoglutarate-dependent NADPH consumption in cell lysates (Figure 2B). A similar enhancement of α-ketoglutarate-dependent NADPH consumption has been reported for R132 mutations in IDH1, resulting in conversion of α-ketoglutarate to 2HG (Dang et al., 2009). To determine whether cells expressing IDH2 R172K shared this property, we expressed IDH2 wild-type or IDH2 R172K in cells. The accumulation of organic acids, including 2HG, both within cells and in culture medium of the transfectants was then assessed by gas-chromatography mass spectrometry (GC-MS) after MTBSTFA derivatization of the organic acid pool. We observed a metabolite peak eluting at 32.5 min on GC-MS that was of minimal intensity in the culture medium of IDH2-wild-type-expressing cells, but that in the medium of IDH2-R172K-expressing cells had a markedly higher intensity approximating that of the glutamate signal (Figures 3A and 3B). Mass spectra of this metabolite peak fit that predicted for MTBSTFA-derivatized 2HG, and the peak’s identity as 2HG was additionally confirmed by matching its mass spectra with that obtained by derivatization of commercial 2HG standards (Figure 3C). Similar results were obtained when the intracellular organic acid pool was analyzed. IDH2 R172K expressing cells were found to have an approximately 100-fold increase in the intracellular levels of 2HG compared with the levels detected in vector-transfected and IDH2-wild-type-overexpressing cells (Figure 3D). Consistent with previous work, IDH1-R132H-expressing cells analyzed in the same experiment had comparable accumulation of 2HG in both cells and in culture medium. 2HG accumulation was not observed in cells overexpressing IDH1 wild-type (data not shown).

Figure 3. Expression of R172K Mutant IDH2 Elevates 2HG Levels within Cells and in Culture Medium

(A and B) 293T cells transfected with IDH2 wild-type (A) or IDH2 R172K (B) were provided fresh culture medium the day after transfection. Twenty-four hours later, the medium was collected, from which organic acids were extracted, purified, and derivatized with MTBSTFA. Shown are representative gas chromatographs for the derivatized organic acids eluting between 30 to 34 min, including aspartate (Asp) and glutamate (Glu). The arrows indicate the expected elution time of 32.5 min for MTBSTFA-derivatized 2HG, based on similar derivatization of a commercial R(-)-2HG standard. Metabolite abundance refers to GC-MS signal intensity.

(C) Mass spectrum of the metabolite peak eluting at 32.5 min in (B), confirming its identity as MTBSTFA-derivatized 2HG. The structure of this derivative is shown in the inset, with the tert-butyl dimethylsilyl groups added during derivatization highlighted in green. m/e indicates the mass (in atomic mass units) to charge ratio for fragments generated by electron impact ionization.

(D) Cells were transfected as in (A) and (B), and after 48 hr intracellular metabolites were extracted, purified, MTBSTFA-derivatized, and analyzed by GC-MS. Shown is the quantitation of 2HG signal intensity relative to glutamate for a representative experiment. See also Figure S1.

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Mutant IDH2 Produces the (R) Enantiomer of 2HG

Cancer-associated mutants of IDH1 produce the (R) enantiomer of 2HG ( Dang et al., 2009). To determine the chirality of the 2HG produced by mutant IDH2 and to compare it with that produced by R132H mutant IDH1, we used a two-step derivatization method to distinguish the stereoisomers of 2HG by GC-MS: an esterification step with R-(−)-2-butanolic HCl, followed by acetylation of the 2-hydroxyl with acetic anhydride ( Kamerling et al., 1981). Test of this method on commercial S(+)-2HG and R(−)-2HG standards demonstrated clear separation of the (S) and (R) enantiomers, and mass spectra of the metabolite peaks confirmed their identity as the O-acetylated di-(−)-2-butyl esters of 2HG (see Figures S1A and S1B available online). By this method, we confirmed the chirality of the 2HG found in cells expressing either R132H mutant IDH1 or R172K mutant IDH2 corresponded exclusively to the (R) enantiomer ( Figures S1C and S1D).

Leukemic Cells Bearing Heterozygous R172K IDH2 Mutations Accumulate 2HG

IDH2 Is Critical for Proliferating Cells and Contributes to the Conversion of α-Ketoglutarate into Citrate in the Mitochondria

A peculiar feature of the IDH-mutated cancers described to date is their lack of reduction to homozygosity. All tumors with IDH mutations retain one IDH wild-type allele. To address this issue we examined whether wild-type IDH1 and/or IDH2 might play a role in either cell survival or proliferation. Consistent with this possibility, we found that siRNA knockdown of either IDH1 or IDH2 can significantly reduce the proliferative capacity of a cancer cell line expressing both wild-type IDH1 and IDH2 ( Figure 4A).

Both IDH1 and IDH2 Are Critical for Cell Proliferation

Both IDH1 and IDH2 Are Critical for Cell Proliferation

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Figure 4. Both IDH1 and IDH2 Are Critical for Cell Proliferation

(A) SF188 cells were treated with either of two unique siRNA oligonucleotides against IDH1 (siIDH1-A and siIDH1-B), either of two unique siRNA oligonucleotides against IDH2 (siIDH2-A and siIDH2-B), or control siRNA (siCTRL), and total viable cells were counted 5 days later. Data are the mean ± SEM of four independent experiments. In each case, both pairs of siIDH nucleotides gave comparable results. A representative western blot from one of the experiments, probed with antibody specific for either IDH1 or IDH2 as indicated, is shown on the right-hand side.

(B) Model depicting the pathways for citrate +4 (blue) and citrate +5 (red) formation in proliferating cells from [13C-U]-L-glutamine (glutamine +5).

(C) Cells were treated with two unique siRNA oligonucleotides against IDH2 or control siRNA, labeled with [13C-U]-L-glutamine, and then assessed for isotopic enrichment in citrate by LC-MS. Citrate +5 and Citrate +4 refer to citrate with five or four 13C-enriched atoms, respectively. Reduced expression of IDH2 from the two unique oligonucleotides was confirmed by western blot. Blotting with actin antibody is shown as a loading control.

(D) Cells were treated with two unique siRNA oligonucleotides against IDH3 (siIDH3-A and siIDH3-B) or control siRNA, and then labeled and assessed for isotopic citrate enrichment by GC-MS. Shown are representative data from three independent experiments. Reduced expression of IDH3 from the two unique oligonucleotides was confirmed by western blot. In (C) and (D), data are presented as mean and standard deviation of three replicates per experimental group.

The genetic analysis of these tumor samples revealed two neomorphic IDH mutations that produce 2HG. Among the IDH1 mutations, tumors with IDH1 R132C or IDH1 R132G accumulated 2HG. This result is not unexpected, as a number of mutations of R132 to other residues have also been shown to accumulate 2HG in glioma samples (Dang et al., 2009).

The other neomorphic allele was unexpected. All five of the IDH2 mutations producing 2HG in this sample set contained the same mutation, R140Q. As shown in Figure 1, both R140 in IDH2 and R100 in IDH1 are predicted to interact with the β-carboxyl of isocitrate. Additional modeling revealed that despite the reduced ability to bind isocitrate, the R140Q mutant IDH2 is predicted to maintain its ability to bind and orient α-ketoglutarate in the active site (Figure 6). This potentially explains the ability of cells with this neomorph to accumulate 2HG in vivo. As shown in Figure 5, samples containing IDH2 R140Q mutations were found to have accumulated 2HG to levels 10-fold to 100-fold greater than the highest levels detected in IDH wild-type samples.

Figure 5. Primary Human AML Samples with IDH1 or IDH2 Mutations Display Marked Elevations of 2HG

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Structural Modeling of R140Q Mutant IDH2

Structural Modeling of R140Q Mutant IDH2

Figure 6.  Structural Modeling of R140Q Mutant IDH2

(A) Active site of human wild-type IDH2 with isocitrate replaced by α-ketoglutarate (α-KG). R140 is well positioned to interact with the β-carboxyl group that is added as a branch off carbon 3 when α-ketoglutarate is reductively carboxylated to isocitrate.

(B) Active site of R140Q mutant IDH2 complexed with α-ketoglutarate, demonstrating the loss of proximity to the substrate in the R140Q mutant. This eliminates the charge interaction from residue 140 that stabilizes the addition of the β-carboxyl required to convert α-ketoglutarate to isocitrate.

IDH2 Mutations Are More Common Than IDH1 Mutations in AML

  • Neomorphic Enzymatic Activity to Produce 2HG Is the Shared Feature of IDH1 and IDH2 Mutations
  • 2HG as a Screening and Diagnostic Marker
  • Maintaining At Least One IDH1 and IDH2 Wild-Type Allele May Be Essential for Transformed Cells
  • 2HG as an Oncometabolite

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Warburg Effect and Mitochondrial Regulation -2.1.3

Writer and Curator: Larry H Bernstein, MD, FCAP 

2.1.3 Warburg Effect and Mitochondrial Regulation

Warburg Effect and Mitochondrial Regulation- 2.1.3

Word Cloud by Daniel Menzin

2.1.3.1 Regulation of Substrate Utilization by the Mitochondrial Pyruvate Carrier

NM Vacanti, AS Divakaruni, CR Green, SJ Parker, RR Henry, TP Ciaraldi, et a..
Molec Cell 6 Nov 2014; 56(3):425–435
http://dx.doi.org/10.1016/j.molcel.2014.09.024

Highlights

  • Oxidation of fatty acids and amino acids is increased upon MPC inhibition
    •Respiration, proliferation, and biosynthesis are maintained when MPC is inhibited
    •Glutaminolytic flux supports lipogenesis in the absence of MPC
    •MPC inhibition is distinct from hypoxia or complex I inhibition

Summary

Pyruvate lies at a central biochemical node connecting carbohydrate, amino acid, and fatty acid metabolism, and the regulation of pyruvate flux into mitochondria represents a critical step in intermediary metabolism impacting numerous diseases. To characterize changes in mitochondrial substrate utilization in the context of compromised mitochondrial pyruvate transport, we applied 13C metabolic flux analysis (MFA) to cells after transcriptional or pharmacological inhibition of the mitochondrial pyruvate carrier (MPC). Despite profound suppression of both glucose and pyruvate oxidation, cell growth, oxygen consumption, and tricarboxylic acid (TCA) metabolism were surprisingly maintained. Oxidative TCA flux was achieved through enhanced reliance on glutaminolysis through malic enzyme and pyruvate dehydrogenase (PDH) as well as fatty acid and branched-chain amino acid oxidation. Thus, in contrast to inhibition of complex I or PDH, suppression of pyruvate transport induces a form of metabolic flexibility associated with the use of lipids and amino acids as catabolic and anabolic fuels.

oxidation-of-fatty-acids-and-amino-acid

oxidation-of-fatty-acids-and-amino-acids

Graphical Abstract – Oxidation of fatty acids and amino acids is increased upon MPC inhibition

Figure 2. MPC Regulates Mitochondrial Substrate Utilization (A) Citrate mass isotopomer distribution (MID) resulting from culture with [U-13C6]glucose (UGlc). (B) Percentage of 13C-labeled metabolites from UGlc. (C) Percentage of fully labeled lactate, pyruvate, and alanine from UGlc. (D) Serine MID resulting from culture with UGlc. (E) Percentage of fully labeled metabolites derived from [U-13C5]glutamine (UGln). (F) Schematic of UGln labeling of carbon atoms in TCA cycle intermediates arising via glutaminoloysis and reductive carboxylation. Mitochondrion schematic inspired by Lewis et al. (2014). (G and H) Citrate (G) and alanine (H) MIDs resulting from culture with UGln. (I) Maximal oxygen consumption rates with or without 3 mM BPTES in medium supplemented with 1 mM pyruvate. (J) Percentage of newly synthesized palmitate as determined by ISA. (K) Contribution of UGln and UGlc to lipogenic AcCoA as determined by ISA. (L) Contribution of glutamine to lipogenic AcCoA via glutaminolysis (ISA using a [3-13C] glutamine [3Gln]) and reductive carboxylation (ISA using a [5-13C]glutamine [5Gln]) under normoxia and hypoxia. (M) Citrate MID resulting from culture with 3Gln. (N) Contribution of UGln and exogenous [3-13C] pyruvate (3Pyr) to lipogenic AcCoA. 2KD+Pyr refers to Mpc2KD cells cultured with 10 mM extracellular pyruvate. Error bars represent SD (A–E, G, H, and M), SEM(I), or 95% confidence intervals(J–L, and N).*p<0.05,**p<0.01,and ***p<0.001 by ANOVA with Dunnett’s post hoc test (A–E and G–I) or * indicates significance by non-overlapping 95% confidence intervals (J–L and N).

Figure 3. Mpc Knockdown Increases Fatty Acid Oxidation. (A) Schematic of changes in flux through metabolic pathways in Mpc2KD relative to control cells. (B) Citrate MID resulting from culture with [U-13C16] palmitate conjugated to BSA (UPalm). (C) Percentage of 13C enrichment resulting from culture with UPalm. (D) ATP-linked and maximal oxygen consumption rate, with or without 20m Metomoxir, with or without 3 mM BPTES. Culture medium supplemented with 0.5 mM carnitine. Error bars represent SD (B and C) or SEM (D). *p < 0.05, **p < 0.01, and ***p < 0.001 by two-tailed, equal variance, Student’s t test(B–D), or by ANOVA with Dunnett’s post hoc test (D).

Figure 4. Metabolic Reprogramming Resulting from Pharmacological Mpc Inhibition Is Distinct from Hypoxia or Complex I Inhibition

2.1.3.2 Oxidation of Alpha-Ketoglutarate Is Required for Reductive Carboxylation in Cancer Cells with Mitochondrial Defects

AR Mullen, Z Hu, X Shi, L Jiang, …, WM Linehan, NS Chandel, RJ DeBerardinis
Cell Reports 12 Jun 2014; 7(5):1679–1690
http://dx.doi.org/10.1016/j.celrep.2014.04.037

Highlights

  • Cells with mitochondrial defects use bidirectional metabolism of the TCA cycle
    •Glutamine supplies the succinate pool through oxidative and reductive metabolism
    •Oxidative TCA cycle metabolism is required for reductive citrate formation
    •Oxidative metabolism produces reducing equivalents for reductive carboxylation

Summary

Mammalian cells generate citrate by decarboxylating pyruvate in the mitochondria to supply the tricarboxylic acid (TCA) cycle. In contrast, hypoxia and other impairments of mitochondrial function induce an alternative pathway that produces citrate by reductively carboxylating α-ketoglutarate (AKG) via NADPH-dependent isocitrate dehydrogenase (IDH). It is unknown how cells generate reducing equivalents necessary to supply reductive carboxylation in the setting of mitochondrial impairment. Here, we identified shared metabolic features in cells using reductive carboxylation. Paradoxically, reductive carboxylation was accompanied by concomitant AKG oxidation in the TCA cycle. Inhibiting AKG oxidation decreased reducing equivalent availability and suppressed reductive carboxylation. Interrupting transfer of reducing equivalents from NADH to NADPH by nicotinamide nucleotide transhydrogenase increased NADH abundance and decreased NADPH abundance while suppressing reductive carboxylation. The data demonstrate that reductive carboxylation requires bidirectional AKG metabolism along oxidative and reductive pathways, with the oxidative pathway producing reducing equivalents used to operate IDH in reverse.

Proliferating cells support their growth by converting abundant extracellular nutrients like glucose and glutamine into precursors for macromolecular biosynthesis. A continuous supply of metabolic intermediates from the tricarboxylic acid (TCA) cycle is essential for cell growth, because many of these intermediates feed biosynthetic pathways to produce lipids, proteins and nucleic acids (Deberardinis et al., 2008). This underscores the dual roles of the TCA cycle for cell growth: it generates reducing equivalents for oxidative phosphorylation by the electron transport chain (ETC), while also serving as a hub for precursor production. During rapid growth, the TCA cycle is characterized by large influxes of carbon at positions other than acetyl-CoA, enabling the cycle to remain full even as intermediates are withdrawn for biosynthesis. Cultured cancer cells usually display persistence of TCA cycle activity despite robust aerobic glycolysis, and often require mitochondrial catabolism of glutamine to the TCA cycle intermediate AKG to maintain rapid rates of proliferation (Icard et al., 2012Hiller and Metallo, 2013).

Some cancer cells contain severe, fixed defects in oxidative metabolism caused by mutations in the TCA cycle or the ETC. These include mutations in fumarate hydratase (FH) in renal cell carcinoma and components of the succinate dehydrogenase (SDH) complex in pheochromocytoma, paraganglioma, and gastrointestinal stromal tumors (Tomlinson et al., 2002Astuti et al., 2001Baysal et al., 2000Killian et al., 2013Niemann and Muller, 2000). All of these mutations alter oxidative metabolism of glutamine in the TCA cycle. Recently, analysis of cells containing mutations in FH, ETC Complexes I or III, or exposed to the ETC inhibitors metformin and rotenone or the ATP synthase inhibitor oligomycin revealed that turnover of TCA cycle intermediates was maintained in all cases (Mullen et al., 2012). However, the cycle operated in an unusual fashion characterized by conversion of glutamine-derived AKG to isocitrate through a reductive carboxylation reaction catalyzed by NADP+/NADPH-dependent isoforms of isocitrate dehydrogenase (IDH). As a result, a large fraction of the citrate pool carried five glutamine-derived carbons. Citrate could be cleaved to produce acetyl-CoA to supply fatty acid biosynthesis, and oxaloacetate (OAA) to supply pools of other TCA cycle intermediates. Thus, reductive carboxylation enables biosynthesis by enabling cells with impaired mitochondrial metabolism to maintain pools of biosynthetic precursors that would normally be supplied by oxidative metabolism. Reductive carboxylation is also induced by hypoxia and by pseudo-hypoxic states caused by mutations in the von Hippel-Lindau (VHL) tumor suppressor gene (Metallo et al., 2012Wise et al., 2011).

Interest in reductive carboxylation stems in part from the possibility that inhibiting the pathway might induce selective growth suppression in tumor cells subjected to hypoxia or containing mutations that prevent them from engaging in maximal oxidative metabolism. Hence, several recent studies have sought to understand the mechanisms by which this pathway operates. In vitro studies of IDH1 indicate that a high ratio of NADPH/NADP+ and low citrate concentration activate the reductive carboxylation reaction (Leonardi et al., 2012). This is supported by data demonstrating that reductive carboxylation in VHL-deficient renal carcinoma cells is associated with a low concentration of citrate and a reduced ratio of citrate:AKG, suggesting that mass action can be a driving force to determine IDH directionality (Gameiro et al., 2013b). Moreover, interrupting the supply of mitochondrial NADPH by silencing the nicotinamide nucleotide transhydrogenase (NNT) suppresses reductive carboxylation (Gameiro et al., 2013a). This mitochondrial transmembrane protein catalyzes the transfer of a hydride ion from NADH to NADP+ to generate NAD+ and NADPH. Together, these observations suggest that reductive carboxylation is modulated in part through the mitochondrial redox state and the balance of substrate/products.

Here we used metabolomics and stable isotope tracing to better understand overall metabolic states associated with reductive carboxylation in cells with defective mitochondrial metabolism, and to identify sources of mitochondrial reducing equivalents necessary to induce the reaction. We identified high levels of succinate in some cells using reductive carboxylation, and determined that most of this succinate was formed through persistent oxidative metabolism of AKG. Silencing this oxidative flux by depleting the mitochondrial enzyme AKG dehydrogenase substantially altered the cellular redox state and suppressed reductive carboxylation. The data demonstrate that bidirectional/branched AKG metabolism occurs during reductive carboxylation in cells with mitochondrial defects, with oxidative metabolism producing reducing equivalents to supply reductive metabolism.

Shared metabolomic features among cell lines with cytb or FH mutations

To identify conserved metabolic features associated with reductive carboxylation in cells harboring defective mitochondrial metabolism, we analyzed metabolite abundance in isogenic pairs of cell lines in which one member displayed substantial reductive carboxylation and the other did not. We used a pair of previously described cybrids derived from 143B osteosarcoma cells, in which one cell line contained wild-type mitochondrial DNA (143Bwt) and the other contained a mutation in the cytb gene (143Bcytb), severely reducing complex III function (Rana et al., 2000Weinberg et al., 2010). The 143Bwt cells primarily use oxidative metabolism to supply the citrate pool while the 143Bcytb cells use reductive carboxylation (Mullen et al., 2012). The other pair, derived from FH-deficient UOK262 renal carcinoma cells, contained either an empty vector control (UOK262EV) or a stably re-expressed wild-type FH allele (UOK262FH). Metabolites were extracted from all four cell lines and analyzed by triple-quadrupole mass spectrometry. We first performed a quantitative analysis to determine the abundance of AKG and citrate in the four cell lines. Both 143Bcytb and UOK262EV cells had less citrate, more AKG, and lower citrate:AKG ratios than their oxidative partners (Fig. S1A-C), consistent with findings from VHL-deficient renal carcinoma cells (Gameiro et al., 2013b).

Next, to identify other perturbations, we profiled the relative abundance of more than 90 metabolites from glycolysis, the pentose phosphate pathway, one-carbon/nucleotide metabolism, the TCA cycle, amino acid degradation, and other pathways (Tables S1 and S2). Each metabolite was normalized to protein content, and relative abundance was determined between cell lines from each pair. Hierarchical clustering (Fig 1A) and principal component analysis (Fig 1B) revealed far greater metabolomic similarities between the members of each pair than between the two cell lines using reductive carboxylation. Only three metabolites displayed highly significant (p<0.005) differences in abundance between the two members of both pairs, and in all three cases the direction of the difference (i.e. higher or lower) was shared in the two cell lines using reductive carboxylation. Proline, a nonessential amino acid derived from glutamine in an NADPH-dependent biosynthetic pathway, was depleted in 143Bcytb and UOK262EV cells (Fig. 1C). 2-hydroxyglutarate (2HG), the reduced form of AKG, was elevated in 143Bcytb and UOK262EV cells (Fig. 1D), and further analysis revealed that while both the L- and D-enantiomers of this metabolite were increased, L-2HG was quantitatively the predominant enantiomer (Fig. S1D). It is likely that 2HG accumulation was related to the reduced redox ratio associated with cytb and FH mutations. Although the sources of 2HG are still under investigation, promiscuous activity of the TCA cycle enzyme malate dehydrogenase produces L-2HG in an NADH-dependent manner (Rzem et al., 2007). Both enantiomers are oxidized to AKG by dehydrogenases (L-2HG dehydrogenase and D-2HG dehydrogenase). It is therefore likely that elevated 2-HG is a consequence of a reduced NAD+/NADH ratio. Consistent with this model, inborn errors of the ETC result in 2-HG accumulation (Reinecke et al., 2011). Exposure to hypoxia (<1% O2) has also been demonstrated to reduce the cellular NAD+/NADH ratio (Santidrian et al., 2013) and to favor modest 2HG accumulation in cultured cells (Wise et al., 2011), although these levels were below those noted in gliomas expressing 2HG-producing mutant alleles of isocitrate dehydrogenase-1 or -2 (Dang et al., 2009).

Figure 1 Metabolomic features of cells using reductive carboxylation

 

Finally, the TCA cycle intermediate succinate was markedly elevated in both cell lines (Fig. 1E). We tested additional factors previously reported to stimulate reductive AKG metabolism, including a genetic defect in ETC Complex I, exposure to hypoxia, and chemical inhibitors of the ETC (Mullen et al., 2012Wise et al., 2011Metallo et al., 2012). These factors had a variable effect on succinate, with impairments of Complex III or IV strongly inducing succinate accumulation, while impairments of Complex I either had little effect or suppressed succinate (Fig. 1F).

Oxidative glutamine metabolism is the primary route of succinate formation

UOK262EV cells lack FH activity and accumulate large amounts of fumarate (Frezza et al., 2011); elevated succinate was therefore not surprising in these cells, because succinate precedes fumarate by one reaction in the TCA cycle. On the other hand, TCA cycle perturbation in 143Bcytb cells results from primary ETC dysfunction, and reductive carboxylation is postulated to be a consequence of accumulated AKG (Anastasiou and Cantley, 2012Fendt et al., 2013). Accumulation of AKG is not predicted to result in elevated succinate. We previously reported that 143Bcytb cells produce succinate through simultaneous oxidative and reductive glutamine metabolism (Mullen et al., 2012). To determine the relative contributions of these two pathways, we cultured 143Bwt and 143Bcytb with [U-13C]glutamine and monitored time-dependent 13C incorporation in succinate and other TCA cycle intermediates. Oxidative metabolism of glutamine generates succinate, fumarate and malate containing four glutamine-derived 13C nuclei on the first turn of the cycle (m+4), while reductive metabolism results in the incorporation of three 13C nuclei in these intermediates (Fig. S2). As expected, oxidative glutamine metabolism was the predominant source of succinate, fumarate and malate in 143Bwt cells (Fig. 2A-C). In 143Bcytb, fumarate and malate were produced primarily through reductive metabolism (Fig. 2E-F). Conversely, succinate was formed primarily through oxidative glutamine metabolism, with a minor contribution from the reductive carboxylation pathway (Fig. 2D). Notably, this oxidatively-derived succinate was detected prior to that formed through reductive carboxylation. This indicated that 143Bcytb cells retain the ability to oxidize AKG despite the observation that most of the citrate pool bears the labeling pattern of reductive carboxylation. Together, the labeling data in 143Bcytb cells revealed bidirectional metabolism of carbon from glutamine to produce various TCA cycle intermediates.

Figure 2  Oxidative glutamine metabolism is the primary route of succinate formation in cells using reductive carboxylation to generate citrate

Pyruvate carboxylation contributes to the TCA cycle in cells using reductive carboxylation

Because of the persistence of oxidative metabolism, we determined the extent to which other routes of metabolism besides reductive carboxylation contributed to the TCA cycle. We previously reported that silencing the glutamine-catabolizing enzyme glutaminase (GLS) depletes pools of fumarate, malate and OAA, eliciting a compensatory increase in pyruvate carboxylase (PC) to supply the TCA cycle (Cheng et al., 2011). In cells with defective oxidative phophorylation, production of OAA by PC may be preferable to glutamine oxidation because it diminishes the need to recycle reduced electron carriers generated by the TCA cycle. Citrate synthase (CS) can then condense PC-derived OAA with acetyl-CoA to form citrate. To examine the contribution of PC to the TCA cycle, cells were cultured with [3,4-13C]glucose. In this labeling scheme, glucose-derived pyruvate is labeled in carbon 1 (Fig. S3). This label is retained in OAA if pyruvate is carboxylated, but removed as CO2 during conversion of pyruvate to acetyl-CoA by pyruvate dehydrogenase (PDH).

Figure 3 Pyruvate carboxylase contributes to citrate formation in cells using reductive carboxylation

Oxidative metabolism of AKG is required for reductive carboxylation

Oxidative synthesis of succinate from AKG requires two reactions: the oxidative decarboxylation of AKG to succinyl-CoA by AKG dehydrogenase, and the conversion of succinyl-CoA to succinate by succinyl-CoA synthetase. In tumors with mutations in the succinate dehydrogenase (SDH) complex, large accumulations of succinate are associated with epigenetic modifications of DNA and histones to promote malignancy (Kaelin and McKnight, 2013Killian et al., 2013). We therefore tested whether succinate accumulation per se was required to induce reductive carboxylation in 143Bcytb cells. We used RNA interference directed against the gene encoding the alpha subunit (SUCLG1) of succinyl-CoA synthetase, the last step in the pathway of oxidative succinate formation from glutamine (Fig. 4A). Silencing this enzyme greatly reduced succinate levels (Fig. 4B), but had no effect on the labeling pattern of citrate from [U-13C]glutamine (Fig. 4C). Thus, succinate accumulation is not required for reductive carboxylation.

Figure 5 AKG dehydrogenase is required for reductive carboxylation

Figure 6 AKG dehydrogenase and NNT contribute to NAD+/NADH ratio

Finally, we tested whether these enzymes also controlled the NADP+/NADPH ratio in 143Bcytb cells. Silencing either OGDH or NNT increased the NADP+/NADPH ratio (Fig. 6F,G), whereas silencing IDH2reduced it (Fig. 6H). Together, these data are consistent with a model in which persistent metabolism of AKG by AKG dehydrogenase produces NADH that supports reductive carboxylation by serving as substrate for NNT-dependent NADPH formation, and that IDH2 is a major consumer of NADPH during reductive carboxylation (Fig. 6I).

Reductive carboxylation of AKG initiates a non-conventional form of metabolism that produces TCA cycle intermediates when oxidative metabolism is impaired by mutations, drugs or hypoxia. Because NADPH-dependent isoforms of IDH are reversible, supplying supra-physiological pools of substrates on either side of the reaction drives function of the enzyme as a reductive carboxylase or an oxidative decarboxylase. Thus, in some circumstances reductive carboxylation may operate in response to a mass effect imposed by drastic changes in the abundance of AKG and isocitrate/citrate. However, reductive carboxylation cannot occur without a source of reducing equivalents to produce NADPH. The current work demonstrates that AKG dehydrogenase, an NADH-generating enzyme complex, is required to maintain a low NAD+/NADH ratio for reductive carboxylation of AKG. Thus, reductive carboxylation not only coexists with oxidative metabolism of AKG, but depends on it. Furthermore, silencing NNT, a consumer of NADH, also perturbs the redox ratio and suppresses reductive formation of citrate. These observations suggest that the segment of the oxidative TCA cycle culminating in succinate is necessary to transmit reducing equivalents to NNT for the reductive pathway (Fig 6I).

Succinate accumulation was observed in cells with cytb or FH mutations. However, this accumulation was dispensable for reductive carboxylation, because silencing SUCLG1 expression had no bearing on the pathway as long as AKG dehydrogenase was active. Furthermore, succinate accumulation was not a universal finding of cells using reductive carboxylation. Rather, high succinate levels were observed in cells with distal defects in the ETC (complex III: antimycin, cytb mutation; complex IV: hypoxia) but not defects in complex I (rotenone, metformin, NDUFA1 mutation). These differences reflect the known suppression of SDH activity when downstream components of the ETC are impaired, and the various mechanisms by which succinate may be formed through either oxidative or reductive metabolism. Succinate has long been known as an evolutionarily conserved anaerobic end product of amino acid metabolism during prolonged hypoxia, including in diving mammals (Hochachka and Storey, 1975, Hochachka et al., 1975). The terminal step in this pathway is the conversion of fumarate to succinate using the NADH-dependent “fumarate reductase” system, essentially a reversal of succinate dehydrogenase/ETC complex II (Weinberg et al., 2000, Tomitsuka et al., 2010). However, this process requires reducing equivalents to be passed from NADH to complex I, then to Coenzyme Q, and eventually to complex II to drive the reduction of fumarate to succinate. Hence, producing succinate through reductive glutamine metabolism would require functional complex I. Interestingly, the fumarate reductase system has generally been considered as a mechanism to maintain a proton gradient under conditions of defective ETC activity. Our data suggest that the system is part of a more extensive reorganization of the TCA cycle that also enables reductive citrate formation.

In summary, we demonstrated that branched AKG metabolism is required to sustain levels of reductive carboxylation observed in cells with mitochondrial defects. The organization of this branched pathway suggests that it serves as a relay system to maintain the redox requirements for reductive carboxylation, with the oxidative arm producing reducing equivalents at the level of AKG dehydrogenase and NNT linking this activity to the production of NADPH to be used in the reductive carboxylation reaction. Hence, impairment of the oxidative arm prevents maximal engagement of reductive carboxylation. As both NNT and AKG dehydrogenase are mitochondrial enzymes, the work emphasizes the flexibility of metabolic systems in the mitochondria to fulfill requirements for redox balance and precursor production even when the canonical oxidative function of the mitochondria is impaired.

2.1.3.3 Rewiring Mitochondrial Pyruvate Metabolism. Switching Off the Light in Cancer Cells

Peter W. Szlosarek, Suk Jun Lee, Patrick J. Pollard
Molec Cell 6 Nov 2014; 56(3): 343–344
http://dx.doi.org/10.1016/j.molcel.2014.10.018

Figure 1. MPC Expression and Metabolic Targeting of Mitochondrial Pyruvate High MPC expression (green) is associated with more favorable tumor prognosis, increased pyruvate oxidation, and reduced lactate and ROS, whereas low expression or mutated MPC is linked to poor tumor prognosis and increased anaplerotic generation of OAA. Dual targeting of MPC and GDH with small molecule inhibitors may ameliorate tumorigenesis in certain cancer types.

The study by Yang et al., (2014) provides evidence for the metabolic flexibility to maintain TCA cycle function. Using isotopic labeling, the authors demonstrated that inhibition of MPCs by a specific compound (UK5099) induced glutamine-dependent acetyl-CoA formation via glutamate dehydrogenase (GDH). Consequently, and in contrast to single agent treatment, simultaneous administration of MPC and GDH inhibitors drastically abrogated the growth of cancer cells (Figure 1). These studies have also enabled a fresh perspective on metabolism in the clinic and emphasized a need for high-quality translational studies to assess the role of mitochondrial pyruvate transport in vivo. Thus, integrating the biomarker of low MPC expression with dual inhibition of

MPC and GDH as a synthetic lethal strategy (Yang et al., 2014) is testable and may offer a novel therapeutic window for patients (DeBerardinis and Thompson, 2012). Indeed, combinatorial targeting of cancer metabolism may prevent early drug resistance and lead to enhanced tumor control, as shown recently for antifolate agents combined with arginine deprivation with modulation of intracellular glutamine (Szlosarek, 2014). Moreover, it will be important to assess both intertumoral and intratumoral metabolic heterogeneity going forward, as tumor cells are highly adaptable with respect to the precursors used to fuel the TCA cycle in the presence of reduced pyruvate transport. The observation by Vacanti et al. (2014) that the flux of BCAAs increased following inhibition of MPC activity may also underlie the increase in BCAAs detected in the plasma of patients several years before a clinical diagnosis of pancreatic cancer (Mayers et al., 2014). Since measuring pyruvate transport via the MPC is technically challenging, the use of 18-FDG positron emission tomography and more recently magnetic spectroscopy with hyperpolarized 13C-labeled pyruvate will need to be incorporated into these future studies (Brindle et al., 2011).

References

Bricker, D.K., Taylor, E.B., Schell, J.C., Orsak, T., Boutron, A., Chen, Y.C., Cox, J.E., Cardon, C.M., Van Vranken, J.G., Dephoure, N., et al. (2012). Science 337, 96–100.

Brindle, K.M., Bohndiek, S.E., Gallagher, F.A., and Kettunen, M.I. (2011). Magn. Reson. Med. 66, 505–519.

DeBerardinis, R.J., and Thompson, C.B. (2012). Cell 148, 1132–1144.

Herzig, S., Raemy, E., Montessuit, S., Veuthey, J.L., Zamboni, N., Westermann, B., Kunji, E.R., and Martinou, J.C. (2012). Science 337, 93–96.

Mayers, J.R., Wu, C., Clish, C.B., Kraft, P., Torrence, M.E., Fiske, B.P., Yuan, C., Bao, Y., Townsend, M.K., Tworoger, S.S., et al. (2014). Nat. Med. 20, 1193–1198.

Metallo, C.M., and Vander Heiden, M.G. (2013). Mol. Cell 49, 388–398.

Schell, J.C., Olson, K.A., Jiang, L., Hawkins, A.J., Van Vranken, J.G., et al. (2014). Mol. Cell 56, this issue, 400–413.

Szlosarek, P.W. (2014). Proc. Natl. Acad. Sci. USA 111, 14015–14016.

Vacanti, N.M., Divakaruni, A.S., Green, C.R., Parker, S.J., Henry, R.R., et al. (2014). Mol. Cell 56, this issue, 425–435.

Yang, C., Ko, B., Hensley, C.T., Jiang, L., Wasti, A.T., et al. (2014). Mol. Cell 56, this issue, 414–424.

2.1.3.4 Betaine is a positive regulator of mitochondrial respiration

Lee I
Biochem Biophys Res Commun. 2015 Jan 9; 456(2):621-5.
http://dx.doi.org:/10.1016/j.bbrc.2014.12.005

Highlights

  • Betaine enhances cytochrome c oxidase activity and mitochondrial respiration.
    • Betaine increases mitochondrial membrane potential and cellular energy levels.
    • Betaine’s anti-tumorigenic effect might be due to a reversal of the Warburg effect.

Betaine protects cells from environmental stress and serves as a methyl donor in several biochemical pathways. It reduces cardiovascular disease risk and protects liver cells from alcoholic liver damage and nonalcoholic steatohepatitis. Its pretreatment can rescue cells exposed to toxins such as rotenone, chloroform, and LiCl. Furthermore, it has been suggested that betaine can suppress cancer cell growth in vivo and in vitro. Mitochondrial electron transport chain (ETC) complexes generate the mitochondrial membrane potential, which is essential to produce cellular energy, ATP. Reduced mitochondrial respiration and energy status have been found in many human pathological conditions including aging, cancer, and neurodegenerative disease. In this study we investigated whether betaine directly targets mitochondria. We show that betaine treatment leads to an upregulation of mitochondrial respiration and cytochrome c oxidase activity in H2.35 cells, the proposed rate limiting enzyme of ETC in vivo. Following treatment, the mitochondrial membrane potential was increased and cellular energy levels were elevated. We propose that the anti-proliferative effects of betaine on cancer cells might be due to enhanced mitochondrial function contributing to a reversal of the Warburg effect.

2.1.3.5 Mitochondrial dysfunction in human non-small-cell lung cancer cells to TRAIL-induced apoptosis by reactive oxygen species and Bcl-XL/p53-mediated amplification mechanisms

Y-L Shi, S Feng, W Chen, Z-C Hua, J-J Bian and W Yin
Cell Death and Disease (2014) 5, e1579
http://dx.doi.org:/10.1038/cddis.2014.547

Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) is a promising agent for anticancer therapy; however, non-small-cell lung carcinoma (NSCLC) cells are relatively TRAIL resistant. Identification of small molecules that can restore NSCLC susceptibility to TRAIL-induced apoptosis is meaningful. We found here that rotenone, as a mitochondrial respiration inhibitor, preferentially increased NSCLC cells sensitivity to TRAIL-mediated apoptosis at subtoxic concentrations, the mechanisms by which were accounted by the upregulation of death receptors and the downregulation of c-FLIP (cellular FLICE-like inhibitory protein). Further analysis revealed that death receptors expression by rotenone was regulated by p53, whereas c-FLIP downregulation was blocked by Bcl-XL overexpression. Rotenone triggered the mitochondria-derived reactive oxygen species (ROS) generation, which subsequently led to Bcl-XL downregulation and PUMA upregulation. As PUMA expression was regulated by p53, the PUMA, Bcl-XL and p53 in rotenone-treated cells form a positive feedback amplification loop to increase the apoptosis sensitivity. Mitochondria-derived ROS, however, promote the formation of this amplification loop. Collectively, we concluded that ROS generation, Bcl-XL and p53-mediated amplification mechanisms had an important role in the sensitization of NSCLC cells to TRAIL-mediated apoptosis by rotenone. The combined TRAIL and rotenone treatment may be appreciated as a useful approach for the therapy of NSCLC that warrants further investigation.

Abbreviations: c-FLIP, cellular FLICE-like inhibitory protein; DHE, dihydroethidium; DISC, death-inducing signaling complex; DPI, diphenylene iodonium; DR4/DR5, death receptor 4/5; EB, ethidium bromide; FADD, Fas-associated protein with death domain; MnSOD, manganese superoxide; NAC, N-acetylcysteine; NSCLC, non-small-cell lung carcinoma; PBMC, peripheral blood mononuclear cells; ROS, reactive oxygen species; TRAIL, tumor necrosis factor-related apoptosis-inducing ligand; UPR, unfolded protein response.

Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) has emerged as a promising cancer therapeutic because it can selectively induce apoptosis in tumor cells in vitro, and most importantly, in vivo with little adverse effect on normal cells.1 However, a number of cancer cells are resistant to TRAIL, especially highly malignant tumors such as lung cancer.23 Lung cancer, especially the non-small-cell lung carcinoma (NSCLC) constitutes a heavy threat to human life. Presently, the morbidity and mortality of NSCLC has markedly increased in the past decade,4 which highlights the need for more effective treatment strategies.

TRAIL has been shown to interact with five receptors, including the death receptors 4 and 5 (DR4 and DR5), the decoy receptors DcR1 and DcR2, and osteoprotegerin.5 Ligation of TRAIL to DR4 or DR5 allows for the recruitment of Fas-associated protein with death domain (FADD), which leads to the formation of death-inducing signaling complex (DISC) and the subsequent activation of caspase-8/10.6 The effector caspase-3 is activated by caspase-8, which cleaves numerous regulatory and structural proteins resulting in cell apoptosis. Caspase-8 can also cleave the Bcl-2 inhibitory BH3-domain protein (Bid), which engages the intrinsic apoptotic pathway by binding to Bcl-2-associated X protein (Bax) and Bcl-2 homologous antagonist killer (BAK). The oligomerization between Bcl-2 and Bax promotes the release of cytochrome c from mitochondria to cytosol, and facilitates the formation of apoptosome and caspase-9 activation.7 Like caspase-8, caspase-9 can also activate caspase-3 and initiate cell apoptosis. Besides apoptosis-inducing molecules, several apoptosis-inhibitory proteins also exist and have function even when apoptosis program is initiated. For example, cellular FLICE-like inhibitory protein (c-FLIP) is able to suppress DISC formation and apoptosis induction by sequestering FADD.891011

Until now, the recognized causes of TRAIL resistance include differential expression of death receptors, constitutively active AKT and NF-κB,1213overexpression of c-FLIP and IAPs, mutations in Bax and BAK gene.2 Hence, resistance can be overcome by the use of sensitizing agents that modify the deregulated death receptor expression and/or apoptosis signaling pathways in cancer cells.5 Many sensitizing agents have been developed in a variety of tumor cell models.2 Although the clinical effectiveness of these agents needs further investigation, treatment of TRAIL-resistant tumor cells with sensitizing agents, especially the compounds with low molecular weight, as well as prolonged plasma half-life represents a promising trend for cancer therapy.

Mitochondria emerge as intriguing targets for cancer therapy. Metabolic changes affecting mitochondria function inside cancer cells endow these cells with distinctive properties and survival advantage worthy of drug targeting, mitochondria-targeting drugs offer substantial promise as clinical treatment with minimal side effects.141516 Rotenone is a potent inhibitor of NADH oxidoreductase in complex I, which demonstrates anti-neoplastic activity on a variety of cancer cells.1718192021 However, the neurotoxicity of rotenone limits its potential application in cancer therapy. To avoid it, rotenone was effectively used in combination with other chemotherapeutic drugs to kill cancerous cells.22

In our previous investigation, we found that rotenone was able to suppress membrane Na+,K+-ATPase activity and enhance ouabain-induced cancer cell death.23 Given these facts, we wonder whether rotenone may also be used as a sensitizing agent that can restore the susceptibility of NSCLC cells toward TRAIL-induced apoptosis, and increase the antitumor efficacy of TRAIL on NSCLC. To test this hypothesis, we initiated this study.

Rotenone sensitizes NSCLC cell lines to TRAIL-induced apoptosis

Four NSCLC cell lines including A549, H522, H157 and Calu-1 were used in this study. As shown in Figure 1a, the apoptosis induced by TRAIL alone at 50 or 100 ng/ml on A549, H522, H157 and Calu-1 cells was non-prevalent, indicating that these NSCLC cell lines are relatively TRAIL resistant. Interestingly, when these cells were treated with TRAIL combined with rotenone, significant increase in cell apoptosis was observed. To examine whether rotenone was also able to sensitize normal cells to TRAIL-mediated apoptosis, peripheral blood mononuclear cell (PBMC) isolated from human blood were used. As a result, rotenone failed to sensitize human PBMC to TRAIL-induced apoptosis, indicating that the sensitizing effect of rotenone is tumor cell specific. Of note, the apoptosis-enhancing effect of rotenone occurred independent of its cytotoxicity, because the minimal dosage required for rotenone to cause toxic effect on NSCLC cell lines was 10 μM, however, rotenone augmented TRAIL-mediated apoptosis when it was used as little as 10 nM.

Figure 1.

Full figure and legend (310K)

http://www.nature.com/cddis/journal/v5/n12/fig_tab/cddis2014547f1.html#figure-title
To further confirm the effect of rotenone, cells were stained with Hoechst and observed under fluorescent microscope (Figure 1b). Consistently, the combined treatment of rotenone with TRAIL caused significant nuclear fragmentation in A549, H522, H157 and Calu-1 cells. Rotenone or TRAIL treatment alone, however, had no significant effect.

Caspases activation is a hallmark of cell apoptosis. In this study, the enzymatic activities of caspases including caspase-3, -8 and -9 were measured by flow cytometry by using FITC-conjugated caspases substrate (Figure 1c). As a result, rotenone used at 1 μM or TRAIL used at 100 ng/ml alone did not cause caspase-3, -8 and -9 activation. The combined treatment, however, significantly increased the enzymatic activities of them. Moreover, A549 or H522 cell apoptosis by TRAIL combined with rotenone was almost completely suppressed in the presence of z-VAD.fmk, a pan-caspase inhibitor (Figure 1d). All of these data indicate that both intrinsic and extrinsic pathways are involved in the sensitizing effect of rotenone on TRAIL-mediated apoptosis in NSCLC.

Upregulation of death receptors expression is required for rotenone-mediated sensitization to TRAIL-induced apoptosis

Sensitization to TRAIL-induced apoptosis has been explained in some studies by upregulation of death receptors,24 whereas other results show that sensitization can occur without increased TRAIL receptor expression.25 As such, we examined TRAIL receptors expression on NSCLC cells after treatment with rotenone. Rotenone increased DR4 and DR5 mRNA levels in A549 cells in a time or concentration-dependent manner (Figures 2a and b), also increased DR4 and DR5 protein expression levels (Supplementary Figure S1). Notably, rotenone failed to increase DR5 mRNA levels in H157 and Calu-1 cells (Supplementary Figure S2). To observe whether the increased DR4 and DR5 mRNA levels finally correlated with the functional molecules, we examined the surface expression levels of DR4 and DR5 by flow cytometry. The results, as shown in Figure 2c demonstrated that the cell surface expression levels of DR4 and DR5 were greatly upregulated by rotenone in either A549 cells or H522 cells.

Figure 2.

Full figure and legend (173K)

http://www.nature.com/cddis/journal/v5/n12/fig_tab/cddis2014547f2.html#figure-title

To analyze whether the upregulation of DR4 and DR5 is a ‘side-effect’, or contrarily, necessary for rotenone-mediated sensitization to TRAIL-induced apoptosis, we blocked upregulation of the death receptors by small interfering RNAs (siRNAs) against DR4 and DR5 (Supplementary Figure S3). The results showed that blocking DR4 and DR5 expression alone significantly reduced the rate of cell apoptosis in A549 cells (Figure 2d). However, the highest inhibition of apoptosis was observed when upregulation of both receptors was blocked in parallel, thus showing an additive effect of blocking DR4 and DR5 at the same time. Similar results were also obtained in H522 cells

To analyze whether the upregulation of DR4 and DR5 is a ‘side-effect’, or contrarily, necessary for rotenone-mediated sensitization to TRAIL-induced apoptosis, we blocked upregulation of the death receptors by small interfering RNAs (siRNAs) against DR4 and DR5 (Supplementary Figure S3). The results showed that blocking DR4 and DR5 expression alone significantly reduced the rate of cell apoptosis in A549 cells (Figure 2d). However, the highest inhibition of apoptosis was observed when upregulation of both receptors was blocked in parallel, thus showing an additive effect of blocking DR4 and DR5 at the same time. Similar results were also obtained in H522 cells.

Rotenone-induced p53 activation regulates death receptors upregulation

TRAIL receptors DR4 and DR5 are regulated at multiple levels. At transcriptional level, studies suggest that several transcriptional factors including NF-κB, p53 and AP-1 are involved in DR4 or DR5 gene transcription.2 The NF-κB or AP-1 transcriptional activity was further modulated by ERK1/2, JNK and p38 MAP kinase activity. Unexpectedly, we found here that none of these MAP kinases inhibitors were able to suppress the apoptosis mediated by TRAIL plus rotenone (Figure 3a). To find out other possible mechanisms, we observed that rotenone was able to stimulate p53 phosphorylation as well as p53 protein expression in A549 and H522 cells (Figure 3b). As a p53-inducible gene, p21 mRNA expression was also upregulated by rotenone treatment in a time-dependent manner (Figure 3c). To characterize the effect of p53, A549 cells were transfected with p53 siRNA. The results, as shown in Figure 3d-1 demonstrated that rotenone-mediated surface expression levels of DR4 and DR5 in A549 cells were largely attenuated by siRNA-mediated p53 expression silencing. Control siRNA, however, failed to reveal such effect. Similar results were also obtained in H522 cells (Figure 3d-2). Silencing of p53 expression in A549 cells also partially suppressed the apoptosis induced by TRAIL plus rotenone (Figure 3e).

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Rotenone suppresses c-FLIP expression and increases the sensitivity of A549 cells to TRAIL-induced apoptosis

The c-FLIP protein has been commonly appreciated as an anti-apoptotic molecule in death receptor-mediated cell apoptosis. In this study, rotenone treatment led to dose-dependent downregulation of c-FLIP expression, including c-FLIPL and c-FLIPs in A549 cells (Figure 4a-1), H522 cells (Figure 4a-2), H441 and Calu-1 cells (Supplementary Figure S4). To test whether c-FLIP is essential for the apoptosis enhancement, A549 cells were transfected with c-FLIPL-overexpressing plasmids. As shown in Figure 4b-1, the apoptosis of A549 cells after the combined treatment was significantly reduced when c-FLIPL was overexpressed. Similar results were also obtained in H522 cells (Figure 4b-2).

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Bcl-XL is involved in the apoptosis enhancement by rotenone

Notably, c-FLIP downregulation by rotenone in NSCLC cells was irrelevant to p53 signaling (data not shown). To identify other mechanism involved, we found that anti-apoptotic molecule Bcl-XL was also found to be downregulated by rotenone in a dose-dependent manner (Figure 5a). Notably, both Bcl-XL and c-FLIPL mRNA levels remained unchanged in cells after rotenone treatment (Supplementary Figure S5). Bcl-2 is homolog to Bcl-XL. But surprisingly, Bcl-2 expression was almost undetectable in A549 cells. To examine whether Bcl-XL is involved, A549 cells were transfected with Bcl-XL-overexpressing plasmid. As compared with mock transfectant, cell apoptosis induced by TRAIL plus rotenone was markedly suppressed under the condition of Bcl-XL overexpression (Figure 5b). To characterize the mechanisms, surface expression levels of DR4 and DR5 were examined. As shown in Figure 5c, the increased surface expression of DR4 and DR5 in A549 cells, or in H522 cells were greatly reduced after Bcl-XLoverexpression (Figure 5c). In addition, Bcl-XL overexpression also significantly prevented the downregulation of c-FLIPL and c-FLIPs expression in A549 cells by rotenone treatment (Figure 5d).

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Rotenone suppresses the interaction between BCL-XL/p53 and increases PUMA transcription

Lines of evidence suggest that Bcl-XL has a strong binding affinity with p53, and can suppress p53-mediated tumor cell apoptosis.26 In this study, FLAG-tagged Bcl-XL and HA-tagged p53 were co-transfected into cells; immunoprecipitation experiment was performed by using FLAG antibody to immunoprecipitate HA-tagged p53. As a result, we found that at the same amount of p53 protein input, rotenone treatment caused a concentration-dependent suppression of the protein interaction between Bcl-XL and p53 (Figure 6a). Rotenone also significantly suppressed the interaction between endogenous Bcl-XL and p53 when polyclonal antibody against p53 was used to immunoprecipitate cellular Bcl-XL (Figure 6b). Recent study highlighted the importance of PUMA in BCL-XL/p53 interaction and cell apoptosis.27 We found here that rotenone significantly increased PUMA gene transcription (Figure 6c) and protein expression (Figure 6d) in NSCLC cells, but not in transformed 293T cell. Meanwhile, this effect was attenuated by silencing of p53 expression (Figure 6e).

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Mitochondria-derived ROS are responsible for the apoptosis-enhancing effect of rotenone

As an inhibitor of mitochondrial respiration, rotenone was found to induce reactive oxygen species (ROS) generation in a variety of transformed or non-transformed cells.2022 Consistently, by using 2′,7′-dichlorofluorescin diacetate (DCFH) for the measurement of intracellular H2O2 and dihydroethidium (DHE) for O2.−, we found that rotenone significantly triggered the .generation of H2O2(Figure 7a) and O2.− (Figure 7b) in A549 and H522 cells. To identify the origin of ROS production, we first incubated cells with diphenylene iodonium (DPI), a potent inhibitor of plasma membrane NADP/NADPH oxidase. The results showed that DPI failed to suppress rotenone-induced ROS generation (Figure 7c). Then, we generated A549 cells deficient in mitochondria DNA by culturing cells in medium supplemented with ethidium bromide (EB). These mtDNA-deficient cells were subject to rotenone treatment, and the result showed that rotenone-induced ROS production were largely attenuated in A549 ρ° cells, but not wild-type A549 cells, suggesting ROS are mainly produced from mitochondria (Figure 7d). Notably, the sensitizing effect of rotenone on TRAIL-induced apoptosis in A549 cells was largely dependent on ROS, because the antioxidant N-acetylcysteine (NAC) treatment greatly suppressed the cell apoptosis, as shown in annexin V/PI double staining experiment (Figure 7e), cell cycle analysis (Figure 7f) and caspase-3 cleavage activity assay (Figure 7g). Finally, in A549 cells stably transfected with manganese superoxide (MnSOD) and catalase, apoptosis induced by TRAIL and rotenone was partially reversed (Figure 7h). All of these data suggest that mitochondria-derived ROS, including H2O2 and O2.−, are responsible for the apoptosis-enhancing effect of rotenone.

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Rotenone promotes BCl-XL degradation and PUMA transcription in ROS-dependent manner

To understand why ROS are responsible for the apoptosis-enhancing effect of rotenone, we found that rotenone-induced suppression of BCL-XL expression can be largely reversed by NAC treatment (Figure 8a). To examine whether this effect of rotenone occurs at posttranslational level, we used cycloheximide (CHX) to halt protein synthesis, and found that the rapid degradation of Bcl-XL by rotenone was largely attenuated in A549 ρ0 cells (Figure 8b). Similarly, rotenone-induced PUMA upregulation was also significantly abrogated in A549 ρ0 cells (Figure 8c). Finally, A549 cells were inoculated into nude mice to produce xenografts tumor model. In this model, the therapeutic effect of TRAIL combined with rotenone was evaluated. Notably, in order to circumvent the potential neurotoxic adverse effect of rotenone, mice were challenged with rotenone at a low concentration of 0.5 mg/kg. The results, as shown in Figure 8d revealed that while TRAIL or rotenone alone remained unaffected on A549 tumor growth, the combined therapy significantly slowed down the tumor growth. Interestingly, the tumor-suppressive effect of TRAIL plus rotenone was significantly attenuated by NAC (P<0.01). After experiment, tumors were removed and the caspase-3 activity in tumor cells was analyzed by flow cytometry. Consistently, the caspase-3 cleavage activities were significantly activated in A549 cells from animals challenged with TRAIL plus rotenone, meanwhile, this effect was attenuated by NAC (Figure 8e). The similar effect of rotenone also occurred in NCI-H441 xenografts tumor model (Supplementary Figure S6).

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Restoration of cancer cells susceptibility to TRAIL-induced apoptosis is becoming a very useful strategy for cancer therapy. In this study, we provided evidence that rotenone increased the apoptosis sensitivity of NSCLC cells toward TRAIL by mechanisms involving ROS generation, p53 upregulation, Bcl-XL and c-FLIP downregulation, and death receptors upregulation. Among them, mitochondria-derived ROS had a predominant role. Although rotenone is toxic to neuron, increasing evidence also demonstrated that it was beneficial for improving inflammation, reducing reperfusion injury, decreasing virus infection or triggering cancer cell death. We identified here another important characteristic of rotenone as a tumor sensitizer in TRAIL-based cancer therapy, which widens the application potential of rotenone in disease therapy.

As Warburg proposed the cancer ‘respiration injury’ theory, increasing evidence suggest that cancer cells may have mitochondrial dysfunction, which causes cancer cells, compared with the normal cells, are under increased generation of ROS.33 The increased ROS in cancer cells have a variety of biological effects. We found here that rotenone preferentially increased the apoptosis sensitivity of cancer cells toward TRAIL, further confirming the concept that although tumor cells have a high level of intracellular ROS, they are more sensitive than normal cells to agents that can cause further accumulation of ROS.

Cancer cells stay in a stressful tumor microenvironment including hypoxia, low nutrient availability and immune infiltrates. These conditions, however, activate a range of stress response pathways to promote tumor survival and aggressiveness. In order to circumvent TRAIL-mediated apoptotic clearance, the expression levels of DR4 and DR5 in many types of cancer cells are nullified, but interestingly, they can be reactivated when cancer cells are challenged with small chemical molecules. Furthermore, those small molecules often take advantage of the stress signaling required for cancer cells survival to increase cancer cells sensitivity toward TRAIL. For example, the unfolded protein response (UPR) has an important role in cancer cells survival, SHetA2, as a small molecule, can induce UPR in NSCLC cell lines and augment TRAIL-induced apoptosis by upregulating DR5 expression in CHOP-dependent manner. Here, we found rotenone manipulated the oxidative stress signaling of NSCLC cells to increase their susceptibility to TRAIL. These facts suggest that cellular stress signaling not only offers opportunity for cancer cells to survive, but also renders cancer cells eligible for attack by small molecules. A possible explanation is that depending on the intensity of stress, cellular stress signaling can switch its role from prosurvival to death enhancement. As described in this study, although ROS generation in cancer cells is beneficial for survival, rotenone treatment further increased ROS production to a high level that surpasses the cell ability to eliminate them; as a result, ROS convert its role from survival to death.

2.1.3.6 PPARs and ERRs. molecular mediators of mitochondrial metabolism

Weiwei Fan, Ronald Evans
Current Opinion in Cell Biology Apr 2015; 33:49–54
http://dx.doi.org/10.1016/j.ceb.2014.11.002

Since the revitalization of ‘the Warburg effect’, there has been great interest in mitochondrial oxidative metabolism, not only from the cancer perspective but also from the general biomedical science field. As the center of oxidative metabolism, mitochondria and their metabolic activity are tightly controlled to meet cellular energy requirements under different physiological conditions. One such mechanism is through the inducible transcriptional co-regulators PGC1α and NCOR1, which respond to various internal or external stimuli to modulate mitochondrial function. However, the activity of such co-regulators depends on their interaction with transcriptional factors that directly bind to and control downstream target genes. The nuclear receptors PPARs and ERRs have been shown to be key transcriptional factors in regulating mitochondrial oxidative metabolism and executing the inducible effects of PGC1α and NCOR1. In this review, we summarize recent gain-of-function and loss-of-function studies of PPARs and ERRs in metabolic tissues and discuss their unique roles in regulating different aspects of mitochondrial oxidative metabolism.

Energy is vital to all living organisms. In humans and other mammals, the vast majority of energy is produced by oxidative metabolism in mitochondria [1]. As a cellular organelle, mitochondria are under tight control of the nucleus. Although the majority of mitochondrial proteins are encoded by nuclear DNA (nDNA) and their expression regulated by the nucleus, mitochondria retain their own genome, mitochondrial DNA (mtDNA), encoding 13 polypeptides of the electron transport chain (ETC) in mammals. However, all proteins required for mtDNA replication, transcription, and translation, as well as factors regulating such activities, are encoded by the nucleus [2].

The cellular demand for energy varies in different cells under different physiological conditions. Accordingly, the quantity and activity of mitochondria are differentially controlled by a transcriptional regulatory network in both the basal and induced states. A number of components of this network have been identified, including members of the nuclear receptor superfamily, the peroxisome proliferator-activated receptors (PPARs) and the estrogen-related receptors (ERRs) [34 and 5].

The Yin-Yang co-regulators

A well-known inducer of mitochondrial oxidative metabolism is the peroxisome proliferator-activated receptor γ coactivator 1α (PGC1α) [6], a nuclear cofactor which is abundantly expressed in high energy demand tissues such as heart, skeletal muscle, and brown adipose tissue (BAT) [7]. Induction by cold-exposure, fasting, and exercise allows PGC1α to regulate mitochondrial oxidative metabolism by activating genes involved in the tricarboxylic acid cycle (TCA cycle), beta-oxidation, oxidative phosphorylation (OXPHOS), as well as mitochondrial biogenesis [6 and 8] (Figure 1).

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Figure 1.  PPARs and ERRs are major executors of PGC1α-induced regulation of oxidative metabolism. Physiological stress such as exercise induces both the expression and activity of PGC1α, which stimulates energy production by activating downstream genes involved in fatty acid and glucose metabolism, TCA cycle, β-oxidation, OXPHOS, and mitochondrial biogenesis. The transcriptional activity of PGC1α relies on its interactions with transcriptional factors such as PPARs (for controlling fatty acid metabolism) and ERRs (for regulating mitochondrial OXPHOS).

The effect of PGC1α on mitochondrial regulation is antagonized by transcriptional corepressors such as the nuclear receptor corepressor 1 (NCOR1) [9 and 10]. In contrast to PGC1α, the expression of NCOR1 is suppressed in conditions where PGC1α is induced such as during fasting, high-fat-diet challenge, and exercise [9 and 11]. Moreover, the knockout of NCOR1 phenotypically mimics PGC1α overexpression in regulating mitochondrial oxidative metabolism [9]. Therefore, coactivators and corepressors collectively regulate mitochondrial metabolism in a Yin-Yang fashion.

However, both PGC1α and NCOR1 lack DNA binding activity and rather act via their interaction with transcription factors that direct the regulatory program. Therefore the transcriptional factors that partner with PGC1α and NCOR1 mediate the molecular signaling cascades and execute their inducible effects on mitochondrial regulation.

PPARs: master executors controlling fatty acid oxidation

Both PGC1α and NCOR1 are co-factors for the peroxisome proliferator-activated receptors (PPARα, γ, and δ) [71112 and 13]. It is now clear that all three PPARs play essential roles in lipid and fatty acid metabolism by directly binding to and modulating genes involved in fat metabolism [1314151617,18 and 19]. While PPARγ is known as a master regulator for adipocyte differentiation and does not seem to be involved with oxidative metabolism [14 and 20], both PPARα and PPARδ are essential regulators of fatty acid oxidation (FAO) [3131519 and 21] (Figure 1).

PPARα was first cloned as the molecular target of fibrates, a class of cholesterol-lowering compounds that increase hepatic FAO [22]. The importance of PPARα in regulating FAO is indicated in its expression pattern which is restricted to tissues with high capacity of FAO such as heart, liver, BAT, and oxidative muscle [23]. On the other hand, PPARδ is ubiquitously expressed with higher levels in the digestive tract, heart, and BAT [24]. In the past 15 years, extensive studies using gain-of-function and loss-of-function models have clearly demonstrated PPARα and PPARδ as the major drivers of FAO in a wide variety of tissues.

ERRS: master executors controlling mitochondrial OXPHOS

ERRs are essential regulators of mitochondrial energy metabolism [4]. ERRα is ubiquitously expressed but particularly abundant in tissues with high energy demands such as brain, heart, muscle, and BAT. ERRβ and ERRγ have similar expression patterns, both are selectively expressed in highly oxidative tissues including brain, heart, and oxidative muscle [45]. Instead of endogenous ligands, the transcriptional activity of ERRs is primarily regulated by co-factors such as PGC1α and NCOR1 [4 and 46] (Figure 1).

Of the three ERRs, ERRβ is the least studied and its role in regulating mitochondrial function is unclear [4 and 47]. In contrast, when PGC1α is induced, ERRα is the master regulator of the mitochondrial biogenic gene network. As ERRα binds to its own promoter, PGC1α can also induce an autoregulatory loop to enhance overall ERRα activity [48]. Without ERRα, the ability of PGC1α to induce the expression of mitochondrial genes is severely impaired. However, the basal-state levels of mitochondrial target genes are not affected by ERRα deletion, suggesting induced mitochondrial biogenesis is a transient process and that other transcriptional factors such as ERRγ may be important maintaining baseline mitochondrial OXPHOS [41•42 and 43]. Consistent with this idea, ERRγ (which is active even when PGC1α is not induced) shares many target genes with ERRα [49 and 50].

Conclusion and perspectives

Taken together, recent studies have clearly demonstrated the essential roles of PPARs and ERRs in regulating mitochondrial oxidative metabolism and executing the inducible effects of PGC1α (Figure 1). Both PPARα and PPARδ are key regulators for FA oxidation. While the function of PPARα seems more restricted in FA uptake, beta-oxidation, and ketogenesis, PPARδ plays a broader role in controlling oxidative metabolism and fuel preference, with its target genes involved in FA oxidation, mitochondrial OXPHOS, and glucose utilization. However, it is still not clear how much redundancy exists between PPARα and PPARδ, a question which may require the generation of a double knockout model. In addition, more effort is needed to fully understand how PPARα and PPARδ control their target genes in response to environmental changes.

Likewise, ERRα and ERRγ have been shown to be key regulators of mitochondrial OXPHOS. Knockout studies of ERRα suggest it to be the principal executor of PGC1α induced up-regulation of mitochondrial genes, though its role in exercise-dependent changes in skeletal muscle needs further investigation. Transgenic models have demonstrated ERRγ’s powerful induction of mitochondrial biogenesis and its ability to act in a PGC1α-independent manner. However, it remains to be elucidated whether ERRγ is sufficient for basal-state mitochondrial function in general, and whether ERRα can compensate for its function.

2.1.3.7 Metabolic control via the mitochondrial protein import machinery

Opalińska M, Meisinger C.
Curr Opin Cell Biol. 2015 Apr; 33:42-48
http://dx.doi.org:/10.1016/j.ceb.2014.11.001

Mitochondria have to import most of their proteins in order to fulfill a multitude of metabolic functions. Sophisticated import machineries mediate targeting and translocation of preproteins from the cytosol and subsequent sorting into their suborganellar destination. The mode of action of these machineries has been considered for long time as a static and constitutively active process. However, recent studies revealed that the mitochondrial protein import machinery is subject to intense regulatory mechanisms that include direct control of protein flux by metabolites and metabolic signaling cascades.
2.1.3.8 The Protein Import Machinery of Mitochondria—A Regulatory Hub

AB Harbauer, RP Zahedi, A Sickmann, N Pfanner, C Meisinger
Cell Metab 4 Mar 2014; 19(3):357–372

Mitochondria are essential cell. They are best known for their role as cellular powerhouses, which convert the energy derived from food into an electrochemical proton gradient across the inner membrane. The proton gradient drives the mitochondrial ATP synthase, thus providing large amounts of ATP for the cell. In addition, mitochondria fulfill central functions in the metabolism of amino acids and lipids and the biosynthesis of iron-sulfur clusters and heme. Mitochondria form a dynamic network that is continuously remodeled by fusion and fission. They are involved in the maintenance of cellular ion homeostasis, play a crucial role in apoptosis, and have been implicated in the pathogenesis of numerous diseases, in particular neurodegenerative disorders.

Mitochondria consist of two membranes, outer membrane and inner membrane, and two aqueous compartments, intermembrane space and matrix (Figure 1). Proteomic studies revealed that mitochondria contain more than 1,000 different proteins (Prokisch et al., 2004Reinders et al., 2006Pagliarini et al., 2008 and Schmidt et al., 2010). Based on the endosymbiotic origin from a prokaryotic ancestor, mitochondria contain a complete genetic system and protein synthesis apparatus in the matrix; however, only ∼1% of mitochondrial proteins are encoded by the mitochondrial genome (13 proteins in humans and 8 proteins in yeast). Nuclear genes code for ∼99% of mitochondrial proteins. The proteins are synthesized as precursors on cytosolic ribosomes and are translocated into mitochondria by a multicomponent import machinery. The protein import machinery is essential for the viability of eukaryotic cells. Numerous studies on the targeting signals and import components have been reported (reviewed in Dolezal et al., 2006,Neupert and Herrmann, 2007Endo and Yamano, 2010 and Schmidt et al., 2010), yet for many years little has been known on the regulation of the import machinery. This led to the general assumption that the protein import machinery is constitutively active and not subject to detailed regulation.

Figure 1. Protein Import Pathways of Mitochondria.  Most mitochondrial proteins are synthesized as precursors in the cytosol and are imported by the translocase of the outer mitochondrial membrane (TOM complex). (A) Presequence-carrying (cleavable) preproteins are transferred from TOM to the presequence translocase of the inner membrane (TIM23 complex), which is driven by the membrane potential (Δψ). The proteins either are inserted into the inner membrane (IM) or are translocated into the matrix with the help of the presequence translocase-associated motor (PAM). The presequences are typically cleaved off by the mitochondrial processing peptidase (MPP). (B) The noncleavable precursors of hydrophobic metabolite carriers are bound to molecular chaperones in the cytosol and transferred to the receptor Tom70. After translocation through the TOM channel, the precursors bind to small TIM chaperones in the intermembrane space and are membrane inserted by the Δψ-dependent carrier translocase of the inner membrane (TIM22 complex).
(C) Cysteine-rich proteins destined for the intermembrane space (IMS) are translocated through the TOM channel in a reduced conformation and imported by the mitochondrial IMS import and assembly (MIA) machinery. Mia40 functions as precursor receptor and oxidoreductase in the IMS, promoting the insertion of disulfide bonds into the imported proteins. The sulfhydryl oxidase Erv1 reoxidizes Mia40 for further rounds of oxidative protein import and folding. (D) The precursors of outer membrane β-barrel proteins are imported by the TOM complex and small TIM chaperones and are inserted into the outer membrane by the sorting and assembly machinery (SAM complex). (E) Outer membrane (OM) proteins with α-helical transmembrane segments are inserted into the membrane by import pathways that have only been partially characterized. Shown is an import pathway via the mitochondrial import (MIM) complex

Studies in recent years, however, indicated that different steps of mitochondrial protein import are regulated, suggesting a remarkable diversity of potential mechanisms. After an overview on the mitochondrial protein import machinery, we will discuss the regulatory processes at different stages of protein translocation into mitochondria. We propose that the mitochondrial protein import machinery plays a crucial role as regulatory hub under physiological and pathophysiological conditions. Whereas the basic mechanisms of mitochondrial protein import have been conserved from lower to higher eukaryotes (yeast to humans), regulatory processes may differ between different organisms and cell types. So far, many studies on the regulation of mitochondrial protein import have only been performed in a limited set of organisms. Here we discuss regulatory principles, yet it is important to emphasize that future studies will have to address which regulatory processes have been conserved in evolution and which processes are organism specific.

Protein Import Pathways into Mitochondria

The classical route of protein import into mitochondria is the presequence pathway (Neupert and Herrmann, 2007 and Chacinska et al., 2009). This pathway is used by more than half of all mitochondrial proteins (Vögtle et al., 2009). The proteins are synthesized as precursors with cleavable amino-terminal extensions, termed presequences. The presequences form positively charged amphipathic α helices and are recognized by receptors of the translocase of the outer mitochondrial membrane (TOM complex) (Figure 1A) (Mayer et al., 1995Brix et al., 1997van Wilpe et al., 1999Abe et al., 2000Meisinger et al., 2001 and Saitoh et al., 2007). Upon translocation through the TOM channel, the cleavable preproteins are transferred to the presequence translocase of the inner membrane (TIM23 complex). The membrane potential across the inner membrane (Δψ, negative on the matrix side) exerts an electrophoretic effect on the positively charged presequences (Martin et al., 1991). The presequence translocase-associated motor (PAM) with the ATP-dependent heat-shock protein 70 (mtHsp70) drives preprotein translocation into the matrix (Chacinska et al., 2005 and Mapa et al., 2010). Here the presequences are typically cleaved off by the mitochondrial processing peptidase (MPP). Some cleavable preproteins contain a hydrophobic segment behind the presequence, leading to arrest of translocation in the TIM23 complex and lateral release of the protein into the inner membrane (Glick et al., 1992Chacinska et al., 2005 and Meier et al., 2005). In an alternative sorting route, some cleavable preproteins destined for the inner membrane are fully or partially translocated into the matrix, followed by insertion into the inner membrane by the OXA export machinery, which has been conserved from bacteria to mitochondria (“conservative sorting”) (He and Fox, 1997Hell et al., 1998Meier et al., 2005 and Bohnert et al., 2010).  …

Regulatory Processes Acting at Cytosolic Precursors of Mitochondrial Proteins

Two properties of cytosolic precursor proteins are crucial for import into mitochondria. (1) The targeting signals of the precursors have to be accessible to organellar receptors. Modification of a targeting signal by posttranslational modification or masking of a signal by binding partners can promote or inhibit import into an organelle. (2) The protein import channels of mitochondria are so narrow that folded preproteins cannot be imported. Thus preproteins should be in a loosely folded state or have to be unfolded during the import process. Stable folding of preprotein domains in the cytosol impairs protein import.  …

Import Regulation by Binding of Metabolites or Partner Proteins to Preproteins

Binding of a metabolite to a precursor protein can represent a direct means of import regulation (Figure 2A, condition 1). A characteristic example is the import of 5-aminolevulinate synthase, a mitochondrial matrix protein that catalyzes the first step of heme biosynthesis (Hamza and Dailey, 2012). The precursor contains heme binding motifs in its amino-terminal region, including the presequence (Dailey et al., 2005). Binding of heme to the precursor inhibits its import into mitochondria, likely by impairing recognition of the precursor protein by TOM receptors (Lathrop and Timko, 1993González-Domínguez et al., 2001,Munakata et al., 2004 and Dailey et al., 2005). Thus the biosynthetic pathway is regulated by a feedback inhibition of mitochondrial import of a crucial enzyme, providing an efficient and precursor-specific means of import regulation dependent on the metabolic situation.

Figure 2. Regulation of Cytosolic Precursors of Mitochondrial Proteins

(A) The import of a subset of mitochondrial precursor proteins can be positively or negatively regulated by precursor-specific reactions in the cytosol. (1) Binding of ligands/metabolites can inhibit mitochondrial import. (2) Binding of precursors to partner proteins can stimulate or inhibit import into mitochondria. (3) Phosphorylation of precursors in the vicinity of targeting signals can modulate dual targeting to the endoplasmic reticulum (ER) and mitochondria. (4) Precursor folding can mask the targeting signal. (B) Cytosolic and mitochondrial fumarases are derived from the same presequence-carrying preprotein. The precursor is partially imported by the TOM and TIM23 complexes of the mitochondrial membranes and the presequence is removed by the mitochondrial processing peptidase (MPP). Folding of the preprotein promotes retrograde translocation of more than half of the molecules into the cytosol, whereas the other molecules are completely imported into mitochondria.

Regulation of Mitochondrial Protein Entry Gate by Cytosolic Kinases

Figure 3. Regulation of TOM Complex by Cytosolic Kinases

(A) All subunits of the translocase of the outer mitochondrial membrane (TOM complex) are phosphorylated by cytosolic kinases (phosphorylated amino acid residues are indicated by stars with P). Casein kinase 1 (CK1) stimulates the assembly of Tom22 into the TOM complex. Casein kinase 2 (CK2) stimulates the biogenesis of Tom22 as well as the mitochondrial import protein 1 (Mim1). Protein kinase A (PKA) inhibits the biogenesis of Tom22 and Tom40, and inhibits the activity of Tom70 (see B). Cyclin-dependent kinases (CDK) are possibly involved in regulation of TOM. (B) Metabolic shift-induced regulation of the receptor Tom70 by PKA. Carrier precursors bind to cytosolic chaperones (Hsp70 and/or Hsp90). Tom70 has two binding pockets, one for the precursor and one for the accompanying chaperone (shown on the left). When glucose is added to yeast cells (fermentable conditions), the levels of intracellular cAMP are increased and PKA is activated (shown on the right). PKA phosphorylates a serine of Tom70 in vicinity of the chaperone binding pocket, thus impairing chaperone binding to Tom70 and carrier import into mitochondria.

Casein Kinase 2 Stimulates TOM Biogenesis and Protein Import

Metabolic Switch from Respiratory to Fermentable Conditions Involves Protein Kinase A-Mediated Inhibition of TOM

Network of Stimulatory and Inhibitory Kinases Acts on TOM Receptors, Channel, and Assembly Factors

Protein Import Activity as Sensor of Mitochondrial Stress and Dysfunction

Figure 4. Mitochondrial Quality Control and Stress Response

(A) Import and quality control of cleavable preproteins. The TIM23 complex cooperates with several machineries: the TOM complex, a supercomplex consisting of the respiratory chain complexes III and IV, and the presequence translocase-associated motor (PAM) with the central chaperone mtHsp70. Several proteases/peptidases involved in processing, quality control, and/or degradation of imported proteins are shown, including mitochondrial processing peptidase (MPP), intermediate cleaving peptidase (XPNPEP3/Icp55), mitochondrial intermediate peptidase (MIP/Oct1), mitochondrial rhomboid protease (PARL/Pcp1), and LON/Pim1 protease. (B) The transcription factor ATFS-1 contains dual targeting information, a mitochondrial targeting signal at the amino terminus, and a nuclear localization signal (NLS). In normal cells, ATFS-1 is efficiently imported into mitochondria and degraded by the Lon protease in the matrix. When under stress conditions the protein import activity of mitochondria is reduced (due to lower Δψ, impaired mtHsp70 activity, or peptides exported by the peptide transporter HAF-1), some ATFS-1 molecules accumulate in the cytosol and can be imported into the nucleus, leading to induction of an unfolded protein response (UPRmt).

Regulation of PINK1/Parkin-Induced Mitophagy by the Activity of the Mitochondrial Protein Import Machinery

Figure 5.  Mitochondrial Dynamics and Disease

(A) In healthy cells, the kinase PINK1 is partially imported into mitochondria in a membrane potential (Δψ)-dependent manner and processed by the inner membrane rhomboid protease PARL, which cleaves within the transmembrane segment and generates a destabilizing N terminus, followed by retro-translocation of cleaved PINK1 into the cytosol and degradation by the ubiquitin-proteasome system (different views have been reported if PINK1 is first processed by MPP or not; Greene et al., 2012, Kato et al., 2013 and Yamano and Youle, 2013). Dissipation of Δψ in damaged mitochondria leads to an accumulation of unprocessed PINK1 at the TOM complex and the recruitment of the ubiquitin ligase Parkin to mitochondria. Mitofusin 2 is phosphorylated by PINK1 and likely functions as receptor for Parkin. Parkin mediates ubiquitination of mitochondrial outer membrane proteins (including mitofusins), leading to a degradation of damaged mitochondria by mitophagy. Mutations of PINK1 or Parkin have been observed in monogenic cases of Parkinson’s disease. (B) The inner membrane fusion protein OPA1/Mgm1 is present in long and short isoforms. A balanced formation of the isoforms is a prerequisite for the proper function of OPA1/Mgm1. The precursor of OPA1/Mgm1 is imported by the TOM and TIM23 complexes. A hydrophobic segment of the precursor arrests translocation in the inner membrane, and the amino-terminal targeting signal is cleaved by MPP, generating the long isoforms. In yeast mitochondria, the import motor PAM drives the Mgm1 precursor further toward the matrix such that a second hydrophobic segment is cleaved by the inner membrane rhomboid protease Pcp1, generating the short isoform (s-Mgm1). In mammals, the m-AAA protease is likely responsible for the balanced formation of long (L) and short (S) isoforms of OPA1. A further protease, OMA1, can convert long isoforms into short isoforms in particular under stress conditions, leading to an impairment of mitochondrial fusion and thus to fragmentation of mitochondria.

….

Mitochondrial research is of increasing importance for the molecular understanding of numerous diseases, in particular of neurodegenerative disorders. The well-established connection between the pathogenesis of Parkinson’s disease and mitochondrial protein import has been discussed above. Several observations point to a possible connection of mitochondrial protein import with the pathogenesis of Alzheimer’s disease, though a direct role of mitochondria has not been demonstrated so far. The amyloid-β peptide (Aβ), which is generated from the amyloid precursor protein (APP), was found to be imported into mitochondria by the TOM complex, to impair respiratory activity, and to enhance ROS generation and fragmentation of mitochondria (Hansson Petersen et al., 2008, Ittner and Götz, 2011 and Itoh et al., 2013). An accumulation of APP in the TOM and TIM23 import channels has also been reported (Devi et al., 2006). The molecular mechanisms of how mitochondrial activity and dynamics may be altered by Aβ (and possibly APP) and how mitochondrial alterations may impact on the pathogenesis of Alzheimer’s disease await further analysis.

It is tempting to speculate that regulatory changes in mitochondrial protein import may be involved in tumor development. Cancer cells can shift their metabolism from respiration toward glycolysis (Warburg effect) (Warburg, 1956, Frezza and Gottlieb, 2009, Diaz-Ruiz et al., 2011 and Nunnari and Suomalainen, 2012). A glucose-induced downregulation of import of metabolite carriers into mitochondria may represent one of the possible mechanisms during metabolic shift to glycolysis. Such a mechanism has been shown for the carrier receptor Tom70 in yeast mitochondria (Schmidt et al., 2011). A detailed analysis of regulation of mitochondrial preprotein translocases in healthy mammalian cells as well as in cancer cells will represent an important task for the future.

Conclusion

In summary, the concept of the “mitochondrial protein import machinery as regulatory hub” will promote a rapidly developing field of interdisciplinary research, ranging from studies on molecular mechanisms to the analysis of mitochondrial diseases. In addition to identifying distinct regulatory mechanisms, a major challenge will be to define the interactions between different machineries and regulatory processes, including signaling networks, preprotein translocases, bioenergetic complexes, and machineries regulating mitochondrial membrane dynamics and contact sites, in order to understand the integrative system controlling mitochondrial biogenesis and fitness.

2.1.3.9 Exosome Transfer from Stromal to Breast Cancer Cells Regulates Therapy Resistance Pathways

MC Boelens, Tony J. Wu, Barzin Y. Nabet, et al.
Cell 23 Oct 2014; 159(3): 499–513
http://www.sciencedirect.com/science/article/pii/S0092867414012392

Highlights

  • Exosome transfer from stromal to breast cancer cells instigates antiviral signaling
    • RNA in exosomes activates antiviral STAT1 pathway through RIG-I
    • STAT1 cooperates with NOTCH3 to expand therapy-resistant cells
    • Antiviral/NOTCH3 pathways predict NOTCH activity and resistance in primary tumors

Summary

Stromal communication with cancer cells can influence treatment response. We show that stromal and breast cancer (BrCa) cells utilize paracrine and juxtacrine signaling to drive chemotherapy and radiation resistance. Upon heterotypic interaction, exosomes are transferred from stromal to BrCa cells. RNA within exosomes, which are largely noncoding transcripts and transposable elements, stimulates the pattern recognition receptor RIG-I to activate STAT1-dependent antiviral signaling. In parallel, stromal cells also activate NOTCH3 on BrCa cells. The paracrine antiviral and juxtacrine NOTCH3 pathways converge as STAT1 facilitates transcriptional responses to NOTCH3 and expands therapy-resistant tumor-initiating cells. Primary human and/or mouse BrCa analysis support the role of antiviral/NOTCH3 pathways in NOTCH signaling and stroma-mediated resistance, which is abrogated by combination therapy with gamma secretase inhibitors. Thus, stromal cells orchestrate an intricate crosstalk with BrCa cells by utilizing exosomes to instigate antiviral signaling. This expands BrCa subpopulations adept at resisting therapy and reinitiating tumor growth.

stromal-communication-with-cancer-cells

stromal-communication-with-cancer-cells

Graphical Abstract

2.1.3.10 Emerging concepts in bioenergetics and cancer research

Obre E, Rossignol R
Int J Biochem Cell Biol. 2015 Feb; 59:167-81
http://dx.doi.org:/10.1016/j.biocel.2014.12.008

The field of energy metabolism dramatically progressed in the last decade, owing to a large number of cancer studies, as well as fundamental investigations on related transcriptional networks and cellular interactions with the microenvironment. The concept of metabolic flexibility was clarified in studies showing the ability of cancer cells to remodel the biochemical pathways of energy transduction and linked anabolism in response to glucose, glutamine or oxygen deprivation. A clearer understanding of the large-scale bioenergetic impact of C-MYC, MYCN, KRAS and P53 was obtained, along with its modification during the course of tumor development. The metabolic dialog between different types of cancer cells, but also with the stroma, also complexified the understanding of bioenergetics and raised the concepts of metabolic symbiosis and reverse Warburg effect. Signaling studies revealed the role of respiratory chain-derived reactive oxygen species for metabolic remodeling and metastasis development. The discovery of oxidative tumors in human and mice models related to chemoresistance also changed the prevalent view of dysfunctional mitochondria in cancer cells. Likewise, the influence of energy metabolism-derived oncometabolites emerged as a new means of tumor genetic regulation. The knowledge obtained on the multi-site regulation of energy metabolism in tumors was translated to cancer preclinical studies, supported by genetic proof of concept studies targeting LDHA, HK2, PGAM1, or ACLY. Here, we review those different facets of metabolic remodeling in cancer, from its diversity in physiology and pathology, to the search of the genetic determinants, the microenvironmental regulators and pharmacological modulators.

2.1.3.11 Protecting the mitochondrial powerhouse

M Scheibye-Knudsen, EF Fang, DL Croteau, DM Wilson III, VA Bohr
Trends in Cell Biol, Mar 2015; 25(3):158–170

Highlights

  • Mitochondrial maintenance is essential for cellular and organismal function.
    • Maintenance includes reactive oxygen species (ROS) regulation, DNA repair, fusion–fission, and mitophagy.
    • Loss of function of these pathways leads to disease.

Mitochondria are the oxygen-consuming power plants of cells. They provide a critical milieu for the synthesis of many essential molecules and allow for highly efficient energy production through oxidative phosphorylation. The use of oxygen is, however, a double-edged sword that on the one hand supplies ATP for cellular survival, and on the other leads to the formation of damaging reactive oxygen species (ROS). Different quality control pathways maintain mitochondria function including mitochondrial DNA (mtDNA) replication and repair, fusion–fission dynamics, free radical scavenging, and mitophagy. Further, failure of these pathways may lead to human disease. We review these pathways and propose a strategy towards a treatment for these often untreatable disorders.

Discussion

Radoslav Bozov –

Larry, pyruvate is a direct substrate for synthesizing pyrimidine rings, as well as C-13 NMR study proven source of methyl groups on SAM! Think about what cancer cells care for – dis-regulated growth through ‘escaped’ mutability of proteins, ‘twisting’ pathways of ordered metabolism space-time wise! mtDNA is a back up, evolutionary primitive, however, primary system for pulling strings onto cell cycle events. Oxygen (never observed single molecule) pulls up electron negative light from emerging super rich energy carbon systems. Therefore, ATP is more acting like a neutralizer – resonator of space-energy systems interoperability! You cannot look at a compartment / space independently , as dimension always add 1 towards 3+1.

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