Posts Tagged ‘Hypoxia-inducible factors’

Curbing Cancer Cell Growth & Metastasis-on-a-Chip’ Models Cancer’s Spread

Curator: Larry H. Bernstein, MD, FCAP


New Approach to Curbing Cancer Cell Growth

Using a new approach, scientists at The Scripps Research Institute (TSRI) and collaborating institutions have discovered a novel drug candidate that could be used to treat certain types of breast cancer, lung cancer and melanoma.

The new study focused on serine, one of the 20 amino acids (protein building blocks) found in nature. Many types of cancer require synthesis of serine to sustain rapid, constant and unregulated growth.

To find a drug candidate that interfered with this pathway, the team screened a large library of compounds from a variety of sources, searching for molecules that inhibited a specific enzyme known as 3-phosphoglycerate dehydrogenase (PHGDH), which is responsible for the first committed step in serine biosynthesis.

“In addition to discovering an inhibitor that targets cancer metabolism, we also now have a tool to help answer interesting questions about serine metabolism,” said Luke L. Lairson, assistant professor of chemistry at TSRI and principal investigator of cell biology at the California Institute for Biomedical Research (CALIBR).

Lairson was senior author of the study, published recently in the Proceedings of the National Academy of Sciences (PNAS), with Lewis Cantley of Weill Cornell Medical College and Costas Lyssiotis of the University of Michigan.

Addicted to Serine

Serine is necessary for nucleotide, protein and lipid biosynthesis in all cells. Cells use two main routes for acquiring serine: through import from the extracellular environment or through conversion of 3-phosphoglycerate (a glycolytic intermediate) by PHGDH.

“Since the late 1950s, it has been known that cancer cells use the process of aerobic glycolysis to generate metabolites needed for proliferative growth,” said Lairson.

This process can lead to an overproduction of serine. The genetic basis for this abundance had remained mysterious until recently, when it was demonstrated that some cancers acquire mutations that increased the expression of PHGDH; reducing PHGDH in these “serine-addicted” cancer cells also inhibited their growth.

The labs of Lewis C. Cantley at Weill Cornell Medical College (in work published in Nature Genetics) and David Sabatini at the Whitehead Institute (in work published in Nature) suggested PHGDH as a potential drug target for cancer types that overexpress the enzyme.

Lairson and colleagues hypothesized that a small molecule drug candidate that inhibited PHGDH could interfere with cancer metabolism and point the way to the development of an effective cancer therapeutic. Importantly, this drug candidate would be inactive against normal cells because they would be able to import enough serine to support ordinary growth.

As Easy as 1-2-800,000

Lairson, in collaboration with colleagues including Cantley, Lyssiotis, Edouard Mullarky of Weill Cornell and Harvard Medical School and Natasha Lucki of CALIBR, screened through a library of 800,000 small molecules using a high-throughput in vitro enzyme assay to detect inhibition of PHGDH. The group identified 408 candidates and further narrowed this list down based on cell-type specific anti-proliferative activity and by eliminating those inhibitors that broadly targeted other dehydrogenases.

With the successful identification of seven candidate inhibitors, the team sought to determine if these molecules could inhibit PHGDH in the complex cellular environment. To do so, the team used a mass spectrometry-based assay (test) to measure newly synthesized serine in a cell in the presence of the drug candidates.

One of the seven small molecules tested, named CBR-5884, was able to specifically inhibit serine synthesis by 30 percent, suggesting that the molecule specifically targeted PHGDH. The group went on to show that CBR-5884 was able to inhibit cell proliferation of breast cancer and melanoma cells lines that overexpress PHGDH.

As expected, CBR-5884 did not inhibit cancer cells that did not overexpress PHGDH, as they can import serine; however, when incubated in media lacking serine, the presence of CBR-5884 decreased growth in these cells.

The group anticipates much optimization work before this drug candidate can become an effective therapeutic. In pursuit of this goal, the researchers plan to take a medicinal chemistry approach to improve potency and metabolic stability.


How Cancer Stem Cells Thrive When Oxygen Is Scarce

(Image: Shutterstock)
image: Shutterstock

Working with human breast cancer cells and mice, scientists at The Johns Hopkins University say new experiments explain how certain cancer stem cells thrive in low oxygen conditions. Proliferation of such cells, which tend to resist chemotherapy and help tumors spread, are considered a major roadblock to successful cancer treatment.

The new research, suggesting that low-oxygen conditions spur growth through the same chain of biochemical events in both embryonic stem cells and breast cancer stem cells, could offer a path through that roadblock, the investigators say.

“There are still many questions left to answer but we now know that oxygen poor environments, like those often found in advanced human breast cancers serve as nurseries for the birth of cancer stem cells,” said Gregg Semenza, M.D., Ph.D., the C. Michael Armstrong Professor of Medicine and a member of the Johns Hopkins Kimmel Cancer Center. “That gives us a few more possible targets for drugs that diminish their threat in human cancer.”

A summary of the findings was published online March 21 in the Proceedings of the National Academy of Sciences.

“Aggressive cancers contain regions where the cancer cells are starved for oxygen and die off, yet patients with these tumors generally have the worst outcome. Our new findings tell us that low oxygen conditions actually encourage certain cancer stem cells to multiply through the same mechanism used by embryonic stem cells.”

All stem cells are immature cells known for their ability to multiply indefinitely and give rise to progenitor cells that mature into specific cell types that populate the body’s tissues during embryonic development. They also replenish tissues throughout the life of an organism. But stem cells found in tumors use those same attributes and twist them to maintain and enhance the survival of cancers.

Recent studies showed that low oxygen conditions increase levels of a family of proteins known as HIFs, or hypoxia-inducible factors, that turn on hundreds of genes, including one called NANOG that instructs cells to become stem cells.

Studies of embryonic stem cells revealed that NANOG protein levels can be lowered by a chemical process known as methylation, which involves putting a methyl group chemical tag on a protein’s messenger RNA (mRNA) precursor. Semenza said methylation leads to the destruction of NANOG’s mRNA so that no protein is made, which in turn causes the embryonic stem cells to abandon their stem cell state and mature into different cell types.

Zeroing in on NANOG, the scientists found that low oxygen conditions increased NANOG’s mRNA levels through the action of HIF proteins, which turned on the gene for ALKBH5, which decreased the methylation and subsequent destruction of NANOG’s mRNA. When they prevented the cells from making ALKBH5, NANOG levels and the number of cancer stem cells decreased. When the researchers manipulated the cell’s genetics to increase levels of ALKBH5 without exposing them to low oxygen, they found this also decreased methylation of NANOG mRNA and increased the numbers of breast cancer stem cells.

Finally, using live mice, the scientists injected 1,000 triple-negative breast cancer cells into their mammary fat pads, where the mouse version of breast cancer forms. Unaltered cells created tumors in all seven mice injected with such cells, but when cells missing ALKBH5 were used, they caused tumors in only 43 percent (six out of 14) of mice. “That confirmed for us that ALKBH5 helps preserve cancer stem cells and their tumor-forming abilities,” Semenza said.

How cancer stem cells thrive when oxygen is scarce

The new research, suggesting that low-oxygen conditions spur growth through the same chain of biochemical events in both embryonic stem cells and breast cancer stem cells, could offer a path through that roadblock, the investigators say.

“There are still many questions left to answer but we now know that oxygen poor environments, like those often found in advanced human breast cancers serve as nurseries for the birth of cancer stem cells,” says Gregg Semenza, M.D., Ph.D., the C. Michael Armstrong Professor of Medicine and a member of the Johns Hopkins Kimmel Cancer Center.

Chuanzhao Zhang, Debangshu Samanta, Haiquan Lu, John W. Bullen, Huimin Zhang, Ivan Chen, Xiaoshun He, Gregg L. Semenza.
Hypoxia induces the breast cancer stem cell phenotype by HIF-dependent and ALKBH5-mediated m6A-demethylation of NANOG mRNA.
Proceedings of the National Academy of Sciences, 2016; 201602883     DOI: 10.1073/pnas.1602883113


Pluripotency factors, such as NANOG, play a critical role in the maintenance and specification of cancer stem cells, which are required for primary tumor formation and metastasis. In this study, we report that exposure of breast cancer cells to hypoxia (i.e., reduced O2 availability), which is a critical feature of the tumor microenvironment, induces N6-methyladenosine (m6A) demethylation and stabilization of NANOG mRNA, thereby promoting the breast cancer stem cell (BCSC) phenotype. We show that inhibiting the expression of AlkB homolog 5 (ALKBH5), which demethylates m6A, or the hypoxia-inducible factors (HIFs) HIF-1α and HIF-2α, which activate ALKBH5 gene transcription in hypoxic breast cancer cells, is an effective strategy to decrease NANOG expression and target BCSCs in vivo.

N6-methyladenosine (m6A) modification of mRNA plays a role in regulating embryonic stem cell pluripotency. However, the physiological signals that determine the balance between methylation and demethylation have not been described, nor have studies addressed the role of m6A in cancer stem cells. We report that exposure of breast cancer cells to hypoxia stimulated hypoxia-inducible factor (HIF)-1α- and HIF-2α–dependent expression of AlkB homolog 5 (ALKBH5), an m6A demethylase, which demethylated NANOG mRNA, which encodes a pluripotency factor, at an m6A residue in the 3′-UTR. Increased NANOG mRNA and protein expression, and the breast cancer stem cell (BCSC) phenotype, were induced by hypoxia in an HIF- and ALKBH5-dependent manner. Insertion of the NANOG 3′-UTR into a luciferase reporter gene led to regulation of luciferase activity by O2, HIFs, and ALKBH5, which was lost upon mutation of the methylated residue. ALKBH5 overexpression decreased NANOG mRNA methylation, increased NANOG levels, and increased the percentage of BCSCs, phenocopying the effect of hypoxia. Knockdown of ALKBH5 expression in MDA-MB-231 human breast cancer cells significantly reduced their capacity for tumor initiation as a result of reduced numbers of BCSCs. Thus, HIF-dependent ALKBH5 expression mediates enrichment of BCSCs in the hypoxic tumor microenvironment.

Specific Proteins Found to Jump Start Spread of Cancer Cells

Metastatic breast cancer cells. [National Cancer Institute]

Scientists at the University of California, San Diego School of Medicine and Moores Cancer Center, with colleagues in Spain and Germany, have discovered how elevated levels of particular proteins in cancer cells trigger hyperactivity in other proteins, fueling the growth and spread of a variety of cancers. Their study (“Prognostic Impact of Modulators of G Proteins in Circulating Tumor Cells from Patients with Metastatic Colorectal Cancer”) is published in Scientific Reports.

Specifically, the international team, led by senior author Pradipta Ghosh, M.D., associate professor at the University of California San Diego School of Medicine, found that increased levels of expression of some members of a protein family called guanine nucleotide exchange factors (GEFs) triggered unsuspected hyperactivation of G proteins and subsequent progression or metastasis of cancer.

The discovery suggests GEFs offer a new and more precise indicator of disease state and prognosis. “We found that elevated expression of each GEF is associated with a shorter, progression-free survival in patients with metastatic colorectal cancer,” said Dr. Ghosh. “The GEFs fared better as prognostic markers than two well-known markers of cancer progression, and the clustering of all GEFs together improved the predictive accuracy of each individual family member.”

In recent years, circulating tumor cells (CTCs), which are shed from primary tumors into the bloodstream and act as seeds for new tumors taking root in other parts of the body, have become a prognostic and predictive biomarker. The presence of CTCs is used to monitor the efficacy of therapies and detect early signs of metastasis.

But counting CTCs in the bloodstream has limited utility, said Dr. Ghosh. “Enumeration alone does not capture the particular characteristics of CTCs that are actually tumorigenic and most likely to cause additional malignancies.”

Numerous efforts are underway to improve the value and precision of CTC analysis. According to Dr. Ghosh the new findings are a step in that direction. First, GEFs activate trimeric G proteins, and second, G protein signaling is involved in CTCs. G proteins are ubiquitous and essential molecular switches involved in transmitting external signals from stimuli into cells’ interiors. They have been a subject of heightened scientific interest for many years.

Dr. Ghosh and colleagues found that elevated expression of nonreceptor GEFs activates Gαi proteins, fueling CTCs and ultimately impacting the disease course and survival of cancer patients.

“Our work shows the prognostic impact of elevated expression of individual and clustered GEFs on survival and the benefit of transcriptome analysis of G protein regulatory proteins in cancer biology,” said Dr. Ghosh. “The next step will be to carry this technology into the clinic where it can be applied directly to deciphering a patient’s state of cancer and how best to treat.”

Metastasis-on-a-Chip’ Models Cancer’s Spread

In the journal Biotechnology Bioengineering, the team reports on its “metastasis-on-a-chip” system believed to be one of the first laboratory models of cancer spreading from one 3D tissue to another.

The current version of the system models a colorectal tumor spreading from the colon to the liver, the most common site of metastasis. Skardal said future versions could include additional organs, such as the lung and bone marrow, which are also potential sites of metastasis. The team also plans to model other types of cancer, such as the deadly brain tumor glioblastoma

To create the system, researchers encapsulated human intestine and colorectal cancer cells inside a biocompatible gel-like material to make a mini-organ. A mini-liver composed of human liver cells was made in the same way. These organoids were placed in a “chip” system made up of a set of micro-channels and chambers etched into the chip’s surface to mimic a simplified version of the body’s circulatory system. The tumor cells were tagged with fluorescent molecules so their activity could be viewed under a microscope.

To test whether the system could model metastasis, the researchers first used highly aggressive cancer cells in the colon organoid. Under the microscope, they saw the tumor grow in the colon organoid until the cells broke free, entered the circulatory system and then invaded the liver tissue, where another tumor formed and grew. When a less aggressive form of colon cancer was used in the system, the tumor did not metastasize, but continued to grow in the colon.

To test the system’s potential for screening drugs, the team introduced Marimastat, a drug used to inhibit metastasis in human patients, into the system and found that it significantly prevented the migration of metastatic cells over a 10-day period. Likewise, the team also tested 5-fluorouracil, a common colorectal cancer drug, which reduced the metabolic activity of the tumor cells.

“We are currently exploring whether other established anti-cancer drugs have the same effects in the system as they do in patients,” said Skardal. “If this link can be validated and expanded, we believe the system can be used to screen drug candidates for patients as a tool in personalized medicine. If we can create the same model systems, only with tumor cells from an actual patient, then we believe we can use this platform to determine the best therapy for any individual patient.”

The scientists are currently working to refine their system. They plan to use 3D printing to create organoids more similar in function to natural organs. And they aim to make the process of metastasis more realistic. When cancer spreads in the human body, the tumor cells must break through blood vessels to enter the blood steam and reach other organs. The scientists plan to add a barrier of endothelial cells, the cells that line blood vessels, to the model.

This concept of modeling the body’s processes on a miniature level is made possible because of advances in micro-tissue engineering and micro-fluidics technologies. It is similar to advances in the electronics industry made possible by miniaturizing electronics on a chip.

Scientists Synthesize Anti-Cancer Agent

A schematic shows a trioxacarcin C molecule, whose structure was revealed for the first time through a new process developed by the Rice lab of synthetic organic chemist K.C. Nicolaou. Trioxacarcins are found in bacteria but synthetic versions are needed to study them for their potential as medications. Trioxacarcins have anti-cancer properties. Source: Nicolaou Group/Rice University
A schematic shows a trioxacarcin C molecule, whose structure was revealed for the first time through a new process developed by the Rice lab of synthetic organic chemist K.C. Nicolaou. Trioxacarcins are found in bacteria but synthetic versions are needed to study them for their potential as medications. Trioxacarcins have anti-cancer properties. Source: Nicolaou Group/Rice University

A team led by Rice University synthetic organic chemist K.C. Nicolaou has developed a new process for the synthesis of a series of potent anti-cancer agents originally found in bacteria.

The Nicolaou lab finds ways to replicate rare, naturally occurring compounds in larger amounts so they can be studied by biologists and clinicians as potential new medications. It also seeks to fine-tune the molecular structures of these compounds through analog design and synthesis to improve their disease-fighting properties and lessen their side effects.

Such is the case with their synthesis of trioxacarcins, reported this month in the Journal of the American Chemical Society.

“Not only does this synthesis render these valuable molecules readily available for biological investigation, but it also allows the previously unknown full structural elucidation of one of them,” Nicolaou said. “The newly developed synthetic technologies will allow us to construct variations for biological evaluation as part of a program to optimize their pharmacological profiles.”

At present, there are no drugs based on trioxacarcins, which damage DNA through a novel mechanism, Nicolaou said.

Trioxacarcins were discovered in the fermentation broth of the bacterial strain Streptomyces bottropensis. They disrupt the replication of cancer cells by binding and chemically modifying their genetic material.

“These molecules are endowed with powerful anti-tumor properties,” Nicolaou said. “They are not as potent as shishijimicin, which we also synthesized recently, but they are more powerful than taxol, the widely used anti-cancer drug. Our objective is to make it more powerful through fine-tuning its structure.”

He said his lab is working with a biotechnology partner to pair these cytotoxic compounds (called payloads) to cancer cell-targeting antibodies through chemical linkers. The process produces so-called antibody-drug conjugates as drugs to treat cancer patients. “It’s one of the latest frontiers in personalized targeting chemotherapies,” said Nicolaou, who earlier this year won the prestigious Wolf Prize in Chemistry.

Fluorescent Nanoparticle Tracks Cancer Treatment’s Effectiveness in Hours

Bevin Fletcher, Associate Editor

Using reporter nanoparticles loaded with either a chemotherapy or immunotherapy, researchers could distinguish between drug-sensitive and drug-resistant tumors in a pre-clinical model of prostate cancer. (Source: Brigham and Women's Hospital)

Using reporter nanoparticles loaded with either a chemotherapy or immunotherapy, researchers could distinguish between drug-sensitive and drug-resistant tumors in a pre-clinical model of prostate cancer. (Source: Brigham and Women’s Hospital)

Bioengineers at Brigham and Women’s Hospital have developed a new technique to help determine if chemotherapy is working in as few as eight hours after treatment. The new approach, which can also be used for monitoring the effectiveness of immunotherapy, has shown success in pre-clinical models.

The technology utilizes a nanoparticle, carrying anti-cancer drugs, that glows green when cancer cells begin dying. Researchers, using  the “reporter nanoparticles” that responds to a particular enzyme known as caspase, which is activated when cells die, were able to distinguish between a tumor that is drug-sensitive or drug-resistant much faster than conventional detection methods such as PET scans, CT and MRI.  The findings were published online March 28 in the Proceedings of the National Academy of Sciences.

“Using this approach, the cells light up the moment a cancer drug starts working,” co-corresponding author Shiladitya Sengupta, Ph.D., principal investigator in BWH’s Division of Bioengineering, said in a prepared statement.  “We can determine if a cancer therapy is effective within hours of treatment.  Our long-term goal is to find a way to monitor outcomes very early so that we don’t give a chemotherapy drug to patients who are not responding to it.”

Cancer killers send signal of success

Nanoparticles deliver drug, then give real-time feedback when tumor cells die   BY   SARAH SCHWARTZ

New lab-made nanoparticles deliver cancer drugs into tumors, then report their effects in real time by lighting up in response to proteins produced by dying cells. More light (right, green) indicates a tumor is responding to chemotherapy.

Tiny biochemical bundles carry chemotherapy drugs into tumors and light up when surrounding cancer cells start dying. Future iterations of these lab-made particles could allow doctors to monitor the effects of cancer treatment in real time, researchers report the week of March 28 in theProceedings of the National Academy of Sciences.

“This is the first system that allows you to read out whether your drug is working or not,” says study coauthor Shiladitya Sengupta, a bioengineer at Brigham and Women’s Hospital in Boston.

Each roughly 100-nanometer-wide particle consists of a drug and a fluorescent dye linked to a coiled molecular chain. Before the particles enter cells, the dye is tethered to a “quencher” molecule that prevents it from lighting up. When injected into the bloodstream of a mouse with cancer, the nanoparticles accumulate in tumor cells and release the drug, which activates a protein that tears a cancer cell apart. This cell-splitting protein not only kills the tumor cell, but also severs the link between the dye and the quencher, allowing the nanoparticles to glow under infrared light.

Reporter nanoparticle that monitors its anticancer efficacy in real time

Ashish Kulkarnia,b,1,Poornima Raoa,b,Siva Natarajana,b,Aaron Goldman, et al.

The ability to identify responders and nonresponders very early during chemotherapy by direct visualization of the activity of the anticancer treatment and to switch, if necessary, to a regimen that is effective can have a significant effect on the outcome as well as quality of life. Current approaches to quantify response rely on imaging techniques that fail to detect very early responses. In the case of immunotherapy, the early anatomical readout is often discordant with the biological response. This study describes a self-reporting nanomedicine that not only delivers chemotherapy or immunotherapy to the tumor but also reports back on its efficacy in real time, thereby identifying responders and nonresponders early on

The ability to monitor the efficacy of an anticancer treatment in real time can have a critical effect on the outcome. Currently, clinical readouts of efficacy rely on indirect or anatomic measurements, which occur over prolonged time scales postchemotherapy or postimmunotherapy and may not be concordant with the actual effect. Here we describe the biology-inspired engineering of a simple 2-in-1 reporter nanoparticle that not only delivers a cytotoxic or an immunotherapy payload to the tumor but also reports back on the efficacy in real time. The reporter nanoparticles are engineered from a novel two-staged stimuli-responsive polymeric material with an optimal ratio of an enzyme-cleavable drug or immunotherapy (effector elements) and a drug function-activatable reporter element. The spatiotemporally constrained delivery of the effector and the reporter elements in a single nanoparticle produces maximum signal enhancement due to the availability of the reporter element in the same cell as the drug, thereby effectively capturing the temporal apoptosis process. Using chemotherapy-sensitive and chemotherapy-resistant tumors in vivo, we show that the reporter nanoparticles can provide a real-time noninvasive readout of tumor response to chemotherapy. The reporter nanoparticle can also monitor the efficacy of immune checkpoint inhibition in melanoma. The self-reporting capability, for the first time to our knowledge, captures an anticancer nanoparticle in action in vivo.


Cancer Treatment’s New Direction  
Genetic testing helps oncologists target tumors and tailor treatments

Evan Johnson had battled a cold for weeks, endured occasional nosebleeds and felt so fatigued he struggled to finish his workouts at the gym. But it was the unexplained bruises and chest pain that ultimately sent the then 23-year-old senior at the University of North Dakota to the Mayo Clinic. There a genetic test revealed a particularly aggressive form of acute myeloid leukemia. That was two years ago.

The harrowing roller-coaster that followed for Mr. Johnson and his family highlights new directions oncologists are taking with genetic testing to find and attack cancer. Tumors can evolve to resist treatments, and doctors are beginning to turn such setbacks into possible advantages by identifying new targets to attack as the tumors change.

His course involved a failed stem cell transplant, a half-dozen different drug regimens, four relapses and life-threatening side effects related to his treatment.

Nine months in, his leukemia had evolved to develop a surprising new mutation. The change meant the cancer escaped one treatment, but the new anomaly provided doctors with a fresh target, one susceptible to drugs approved for other cancers. Doctors adjusted Mr. Johnson’s treatment accordingly, knocked out the disease and paved the way for a second, more successful stem cell transplant. He has now been free of leukemia for a year.

Now patients with advanced cancer who are treated at major centers can expect to have their tumors sequenced, in hopes of finding a match in a growing medicine chest of drugs that precisely target mutations that drive cancer’s growth. When they work, such matches can have a dramatic effect on tumors. But these “precision medicines” aren’t cures. They are often foiled when tumors evolve, pushing doctors to take the next step to identify new mutations in hopes of attacking them with an effective treatment.

Dr. Kasi and his Mayo colleagues—Naseema Gangat, a hematologist, and Shahrukh Hashmi, a transplant specialist—are among the authors of an account of Mr. Johnson’s case published in January in the journal Leukemia Research Reports.

Before qualifying for a transplant, a patient’s blasts need to be under 5%.

To get under 5%, he started on a standard chemotherapy regimen and almost immediately, things went south. His blast cells plummeted, but “the chemo just wiped out my immune system,”

Then as mysteriously as it began, a serious mycotic throat infection stopped. But Mr. Johnson couldn’t tolerate the chemo, and his blast cells were on the rise. A two-drug combination that included the liver cancer drug Nexavar, which targets the FLT3 mutation, knocked back the blast cells. But the stem cell transplant in May, which came from one of his brothers, failed to take, and he relapsed after 67 days, around late July.

He was put into a clinical trial of an experimental AML drug being developed by Astellas Pharma of Japan. He started to regain weight. In November 2014, doctors spotted the initial signs in blood tests that Mr. Johnson’s cancer was evolving to acquire a new mutation. By late January, he relapsed again , but there was a Philadelphia chromosome mutation,  a well-known genetic alteration associated with chronic myeloid leukemia. It also is a target of the blockbuster cancer drug Gleevec and several other medicines.

Clonal evolution of AML on novel FMS-like tyrosine kinase-3 (FLT3) inhibitor therapy with evolving actionable targets

Naseema GangatMark R. LitzowMrinal M. PatnaikShahrukh K. HashmiNaseema Gangat

•   The article reports on a case of AML that underwent clonal evolution.
•   We report on novel acquisition of the Philadelphia t(9;22) translocation in AML.
•   Next generation sequencing maybe helpful in these refractory/relapse cases.
•   Novel FLT3-inhibitor targeted therapies are another option in patients with AML.
•   Personalizing cancer treatment based on evolving targets is a viable option.

For acute myeloid leukemia (AML), identification of activating mutations in the FMS-like tyrosine kinase-3 (FLT3) has led to the development of several FLT3-inhibitors. Here we present clinical and next generation sequencing data at the time of progression of a patient on a novel FLT3-inhibitor clinical trial (ASP2215) to show that employing therapeutic interventions with these novel targeted therapies can lead to consequences secondary to selective pressure and clonal evolution of cancer. We describe novel findings alongside data on treatment directed towards actionable aberrations acquired during the process. (Clinical Trial: NCT02014558; registered at: 〈〉)

The development of kinase inhibitors for the treatment of leukemia has revolutionized the care of these patients. Since the introduction of imatinib for the treatment of chronic myeloid leukemia, multiple other tyrosine kinase inhibitors (TKIs) have become available[1]. Additionally, for acute myeloid leukemia (AML), identification of activating mutations in the FMS-like tyrosine kinase-3 (FLT3) has led to the development of several FLT3-inhibitors [2], [3], [4] and [5]. The article herein reports a unique case of AML that underwent clonal evolution while on a novel FLT3-inhibitor clinical trial.

Our work herein presents clinical and next generation sequencing data at the time of progression to illustrate these important concepts stemming from Darwinian evolution [6]. We describe novel findings alongside data on treatment directed towards actionable aberrations acquired during the process.

Our work focuses on a 23-year-old male who presented with 3 months history of fatigue and easy bruising, a white blood count of 22.0×109/L with 51% circulating blasts, hemoglobin 7.6 g/dL, and a platelet count of 43×109/L. A bone marrow biopsy confirmed a diagnosis of AML. Initial cytogenetic studies identified trisomy 8 in all the twenty metaphases examined. Mutational analysis revealed an internal tandem duplication of the FLT3 gene (FLT3-ITD).

He received standard induction chemotherapy (7+3) with cytarabine (ARA-C; 100 mg/m2for 7 days) and daunorubicin (DNM; 60 mg/m2 for 3 days). His induction chemotherapy was complicated by severe palatine and uvular necrosis of indeterminate etiology (possible mucormycosis).

Bone marrow biopsy at day 28 demonstrated persistent disease with 10% bone marrow blasts (Fig. 1). Due to his complicated clinical course and the presence of a FLT3-ITD, salvage therapy with 5-azacitidine (5-AZA) and sorafenib (SFN) was instituted. Table 1.
The highlighted therapies were employed in this particular case at various time points as shown in Fig. 1.


    • [1]
    • J.E. Cortes, D.W. Kim, J. Pinilla-Ibarz, et al.
    • A phase 2 trial of ponatinib in Philadelphia chromosome-positive leukemias
    • New Engl. J. Med., 369 (19) (2013), pp. 1783–1796
    • [2]
    • F. Ravandi, M.L. Alattar, M.R. Grunwald, et al.
    • Phase 2 study of azacytidine plus sorafenib in patients with acute myeloid leukemia and FLT-3 internal tandem duplication mutation
    • Blood, 121 (23) (2013), pp. 4655–4662
    • [3]
    • N.P. Shah, M. Talpaz, M.W. Deininger, et al.
    • Ponatinib in patients with refractory acute myeloid leukaemia: findings from a phase 1 study
    • Br. J. Haematol., 162 (4) (2013), pp. 548–552
    • [4]
    • Y. Alvarado, H.M. Kantarjian, R. Luthra, et al.
    • Treatment with FLT3 inhibitor in patients with FLT3-mutated acute myeloid leukemia is associated with development of secondary FLT3-tyrosine kinase domain mutations
    • Cancer, 120 (14) (2014), pp. 2142–2149
    • [5]
    • C.C. Smith, C. Zhang, K.C. Lin, et al.
    • Characterizing and overriding the structural mechanism of the Quizartinib-Resistant FLT3 “Gatekeeper” F691L mutation with PLX3397
    • Cancer Discov. (2015)
    • [6]
    • M. Greaves, C.C. Maley
    • Clonal evolution in cancer
    • Nature, 481 (7381) (2012), pp. 306–313





Read Full Post »

Hypoxia Inducible Factor 1 (HIF-1)

Writer and Curator: Larry H Bernstein, MD, FCAP

7.9  Hypoxia Inducible Factor 1 (HIF-1)

7.9.1 Hypoxia and mitochondrial oxidative metabolism

7.9.2 Hypoxia promotes isocitrate dehydrogenase-dependent carboxylation of α-ketoglutarate to citrate to support cell growth and viability

7.9.3 Hypoxia-Inducible Factors in Physiology and Medicine

7.9.4 Hypoxia-inducible factor 1. Regulator of mitochondrial metabolism and mediator of ischemic preconditioning

7.9.5 Regulation of cancer cell metabolism by hypoxia-inducible factor 1

7.9.6 Coming up for air. HIF-1 and mitochondrial oxygen consumption

7.9.7 HIF-1 mediates adaptation to hypoxia by actively downregulating mitochondrial oxygen consumption

7.9.8 HIF-1. upstream and downstream of cancer metabolism

7.9.9 In Vivo HIF-Mediated Reductive Carboxylation

7.9.10 Evaluation of HIF-1 inhibitors as anticancer agents



7.9.1 Hypoxia and mitochondrial oxidative metabolism

Solaini G1Baracca ALenaz GSgarbi G.
Biochim Biophys Acta. 2010 Jun-Jul; 1797(6-7):1171-7

It is now clear that mitochondrial defects are associated with a large variety of clinical phenotypes. This is the result of the mitochondria’s central role in energy production, reactive oxygen species homeostasis, and cell death. These processes are interdependent and may occur under various stressing conditions, among which low oxygen levels (hypoxia) are certainly prominent. Cells exposed to hypoxia respond acutely with endogenous metabolites and proteins promptly regulating metabolic pathways, but if low oxygen levels are prolonged, cells activate adapting mechanisms, the master switch being the hypoxia-inducible factor 1 (HIF-1). Activation of this factor is strictly bound to the mitochondrial function, which in turn is related with the oxygen level. Therefore in hypoxia, mitochondria act as [O2] sensors, convey signals to HIF-1directly or indirectly, and contribute to the cell redox potential, ion homeostasis, and energy production. Although over the last two decades cellular responses to low oxygen tension have been studied extensively, mechanisms underlying these functions are still indefinite. Here we review current knowledge of the mitochondrial role in hypoxia, focusing mainly on their role in cellular energy and reactive oxygen species homeostasis in relation with HIF-1 stabilization. In addition, we address the involvement of HIF-1 and the inhibitor protein of F1F0 ATPase in the hypoxia-induced mitochondrial autophagy.

Over the last two decades a defective mitochondrial function associated with hypoxia has been invoked in many diverse complex disorders, such as type 2 diabetes [1] and [2], Alzheimer’s disease [3] and [4], cardiac ischemia/reperfusion injury [5] and [6], tissue inflammation [7], and cancer [8][9][10],[11] and [12].

The [O2] in air-saturated aqueous buffer at 37 °C is approx. 200 μM [13]; however, mitochondria in vivo are exposed to a considerably lower [O2] that varies with tissue and physiological state. Under physiological conditions, most human resting cells experience some 5% oxygen tension, however the [O2] gradient occurring between the extracellular environment and mitochondria, where oxygen is consumed by cytochrome c oxidase, results in a significantly lower [O2] exposition of mitochondria. Below this oxygen level, most mammalian tissues are exposed to hypoxic conditions  [14]. These may arise in normal development, or as a consequence of pathophysiological conditions where there is a reduced oxygen supply due to a respiratory insufficiency or to a defective vasculature. Such conditions include inflammatory diseases, diabetes, ischemic disorders (cerebral or cardiovascular), and solid tumors. Mitochondria consume the greatest amount (some 85–90%) of oxygen in cells to allow oxidative phosphorylation (OXPHOS), which is the primary metabolic pathway for ATP production. Therefore hypoxia will hamper this metabolic pathway, and if the oxygen level is very low, insufficient ATP availability might result in cell death [15].

When cells are exposed to an atmosphere with reduced oxygen concentration, cells readily “respond” by inducing adaptive reactions for their survival through the AMP-activated protein kinase (AMPK) pathway (see for a recent review [16]) which inter alia increases glycolysis driven by enhanced catalytic efficiency of some enzymes, including phosphofructokinase-1 and pyruvate kinase (of note, this oxidative flux is thermodynamically allowed due to both reduced phosphorylation potential [ATP]/([ADP][Pi]) and the physiological redox state of the cell). However, this is particularly efficient only in the short term, therefore cells respond to prolonged hypoxia also by stimulation of hypoxia-inducible factors (HIFs: HIF-1 being the mostly studied), which are heterodimeric transcription factors composed of α and β subunits, first described by Semenza and Wang [17]. These HIFs in the presence of hypoxic oxygen levels are activated through a complex mechanism in which the oxygen tension is critical (see below). Afterwards HIFs bind to hypoxia-responsive elements, activating the transcription of more than two hundred genes that allow cells to adapt to the hypoxic environment [18] and [19].

Several excellent reviews appeared in the last few years describing the array of changes induced by oxygen deficiency in both isolated cells and animal tissues. In in vivo models, a coordinated regulation of tissue perfusion through vasoactive molecules such as nitric oxide and the action of carotid bodies rapidly respond to changes in oxygen demand [20][21][22][23] and [24]. Within isolated cells, hypoxia induces significant metabolic changes due to both variation of metabolites level and activation/inhibition of enzymes and transporters; the most important intracellular effects induced by different pathways are expertly described elsewhere (for recent reviews, see [25][26] and [27]). It is reasonable to suppose that the type of cells and both the severity and duration of hypoxia may determine which pathways are activated/depressed and their timing of onset [3][6][10][12][23] and [28]. These pathways will eventually lead to preferential translation of key proteins required for adaptation and survival to hypoxic stress. Although in the past two decades, the discovery of HIF-1 by Gregg Semenza et al. provided a molecular platform to investigate the mechanism underlying responses to oxygen deprivation, the molecular and cellular biology of hypoxia has still to be completely elucidated. This review summarizes recent experimental data concerned with mitochondrial structure and function adaptation to hypoxia and evaluates it in light of the main structural and functional parameters defining the mitochondrial bioenergetics. Since mitochondria contain an inhibitor protein, IF1, whose action on the F1F0 ATPase has been considered for decades of critical importance in hypoxia/ischemia, particular notice will be dedicated to analyze molecular aspects of IF1 regulation of the enzyme and its possible role in the metabolic changes induced by low oxygen levels in cells.

Mechanism(s) of HIF-1 activation

HIF-1 consists of an oxygen-sensitive HIF-1α subunit that heterodimerizes with the HIF-1β subunit to bind DNA. In high O2 tension, HIF-1α is oxidized (hydroxylated) by prolyl hydroxylases (PHDs) using α-ketoglutarate derived from the tricarboxylic acid (TCA) cycle. The hydroxylated HIF-1α subunit interacts with the von Hippel–Lindau protein, a critical member of an E3 ubiquitin ligase complex that polyubiquitylates HIF. This is then catabolized by proteasomes, such that HIF-1α is continuously synthesized and degraded under normoxic conditions [18]. Under hypoxia, HIF-1α hydroxylation does not occur, thereby stabilizing HIF-1 (Fig. 1). The active HIF-1 complex in turn binds to a core hypoxia response element in a wide array of genes involved in a diversity of biological processes, and directly transactivates glycolytic enzyme genes [29]. Notably, O2 concentration, multiple mitochondrial products, including the TCA cycle intermediates and reactive oxygen species, can coordinate PHD activity, HIF stabilization, hence the cellular responses to O2 depletion [30] and [31]. Incidentally, impaired TCA cycle flux, particularly if it is caused by succinate dehydrogenase dysfunction, results in decreased or loss of energy production from both the electron-transport chain and the Krebs cycle, and also in overproduction of free radicals [32]. This leads to severe early-onset neurodegeneration or, as it occurs in individuals carrying mutations in the non-catalytic subunits of the same enzyme, to tumors such as phaeochromocytoma and paraganglioma. However, impairment of the TCA cycle may be relevant also for the metabolic changes occurring in mitochondria exposed to hypoxia, since accumulation of succinate has been reported to inhibit PHDs [33]. It has to be noticed that some authors believe reactive oxygen species (ROS) to be essential to activate HIF-1 [34], but others challenge this idea [35], therefore the role of mitochondrial ROS in the regulation of HIF-1 under hypoxia is still controversial [36]. Moreover, the contribution of functional mitochondria to HIF-1 regulation has also been questioned by others [37][38] and [39].

Major mitochondrial changes in hypoxia

Major mitochondrial changes in hypoxia

Fig. 1. Major mitochondrial changes in hypoxia. Hypoxia could decrease electron-transport rate determining Δψm reduction, increased ROS generation, and enhanced NO synthase. One (or more) of these factors likely contributes to HIF stabilization, that in turn induces metabolic adaptation of both hypoxic cells and mitophagy. The decreased Δψm could also induce an active binding of IF1, which might change mitochondrial morphology and/or dynamics, and inhibit mitophagy. Solid lines indicate well established hypoxic changes in cells, whilst dotted lines indicate changes not yet stated. Inset, relationships between extracellular O2concentration and oxygen tension.

Oxygen is a major determinant of cell metabolism and gene expression, and as cellular O2 levels decrease, either during isolated hypoxia or ischemia-associated hypoxia, metabolism and gene expression profiles in the cells are significantly altered. Low oxygen reduces OXPHOS and Krebs cycle rates, and participates in the generation of nitric oxide (NO), which also contributes to decrease respiration rate [23] and [40]. However, oxygen is also central in the generation of reactive oxygen species, which can participate in cell signaling processes or can induce irreversible cellular damage and death [41].

As specified above, cells adapt to oxygen reduction by inducing active HIF, whose major effect on cells energy homeostasis is the inactivation of anabolism, activation of anaerobic glycolysis, and inhibition of the mitochondrial aerobic metabolism: the TCA cycle, and OXPHOS. Since OXPHOS supplies the majority of ATP required for cellular processes, low oxygen tension will severely reduce cell energy availability. This occurs through several mechanisms: first, reduced oxygen tension decreases the respiration rate, due first to nonsaturating substrate for cytochrome c oxidase (COX), secondarily, to allosteric modulation of COX[42]. As a consequence, the phosphorylation potential decreases, with enhancement of the glycolysis rate primarily due to allosteric increase of phosphofructokinase activity; glycolysis however is poorly efficient and produces lactate in proportion of 0.5 mol/mol ATP, which eventually drops cellular pH if cells are not well perfused, as it occurs under defective vasculature or ischemic conditions  [6]. Besides this “spontaneous” (thermodynamically-driven) shift from aerobic to anaerobic metabolism which is mediated by the kinetic changes of most enzymes, the HIF-1 factor activates transcription of genes encoding glucose transporters and glycolytic enzymes to further increase flux of reducing equivalents from glucose to lactate[43] and [44]. Second, HIF-1 coordinates two different actions on the mitochondrial phase of glucose oxidation: it activates transcription of the PDK1 gene encoding a kinase that phosphorylates and inactivates pyruvate dehydrogenase, thereby shunting away pyruvate from the mitochondria by preventing its oxidative decarboxylation to acetyl-CoA [45] and [46]. Moreover, HIF-1 induces a switch in the composition of cytochrome c oxidase from COX4-1 to COX4-2 isoform, which enhances the specific activity of the enzyme. As a result, both respiration rate and ATP level of hypoxic cells carrying the COX4-2 isoform of cytochrome c oxidase were found significantly increased with respect to the same cells carrying the COX4-1 isoform [47]. Incidentally, HIF-1 can also increase the expression of carbonic anhydrase 9, which catalyses the reversible hydration of CO2 to HCO3 and H+, therefore contributing to pH regulation.

Effects of hypoxia on mitochondrial structure and dynamics

Mitochondria form a highly dynamic tubular network, the morphology of which is regulated by frequent fission and fusion events. The fusion/fission machineries are modulated in response to changes in the metabolic conditions of the cell, therefore one should expect that hypoxia affect mitochondrial dynamics. Oxygen availability to cells decreases glucose oxidation, whereas oxygen shortage consumes glucose faster in an attempt to produce ATP via the less efficient anaerobic glycolysis to lactate (Pasteur effect). Under these conditions, mitochondria are not fueled with substrates (acetyl-CoA and O2), inducing major changes of structure, function, and dynamics (for a recent review see [48]). Concerning structure and dynamics, one of the first correlates that emerge is that impairment of mitochondrial fusion leads to mitochondrial depolarization, loss of mtDNA that may be accompanied by altered respiration rate, and impaired distribution of the mitochondria within cells [49][50] and [51]. Indeed, exposure of cortical neurons to moderate hypoxic conditions for several hours, significantly altered mitochondrial morphology, decreased mitochondrial size and reduced mitochondrial mean velocity. Since these effects were either prevented by exposing the neurons to inhibitors of nitric oxide synthase or mimicked by NO donors in normoxia, the involvement of an NO-mediated pathway was suggested [52]. Mitochondrial motility was also found inhibited and controlled locally by the [ADP]/[ATP] ratio [53]. Interestingly, the author used an original approach in which mitochondria were visualized using tetramethylrhodamineethylester and their movements were followed by applying single-particle tracking.

Of notice in this chapter is that enzymes controlling mitochondrial morphology regulators provide a platform through which cellular signals are transduced within the cell in order to affect mitochondrial function [54]. Accordingly, one might expect that besides other mitochondrial factors [30] and [55] playing roles in HIF stabilization, also mitochondrial morphology might reasonably be associated with HIF stabilization. In order to better define the mechanisms involved in the morphology changes of mitochondria and in their dynamics when cells experience hypoxic conditions, these pioneering studies should be corroborated by and extended to observations on other types of cells focusing also on single proteins involved in both mitochondrial fusion/fission and motion.

Effects of hypoxia on the respiratory chain complexes

O2 is the terminal acceptor of electrons from cytochrome c oxidase (Complex IV), which has a very high affinity for it, being the oxygen concentration for half-maximal respiratory rate at pH 7.4 approximately 0.7 µM [56]. Measurements of mitochondrial oxidative phosphorylation indicated that it is not dependent on oxygen concentration up to at least 20 µM at pH 7.0 and the oxygen dependence becomes markedly greater as the pH is more alkaline [56]. Similarly, Moncada et al. [57] found that the rate of O2 consumption remained constant until [O2] fell below 15 µM. Accordingly, most reports in the literature consider hypoxic conditions occurring in cells at 5–0.5% O2, a range corresponding to 46–4.6 µM O2 in the cells culture medium (see Fig. 1 inset). Since between the extracellular environment and mitochondria an oxygen pressure gradient is established [58], the O2 concentration experienced by Complex IV falls in the range affecting its kinetics, as reported above.

Under these conditions, a number of changes on the OXPHOS machinery components, mostly mediated by HIF-1 have been found. Thus, Semenza et al. [59] and others thereafter [46] reported that activation of HIF-1α induces pyruvate dehydrogenase kinase, which inhibits pyruvate dehydrogenase, suggesting that respiration is decreased by substrate limitation. Besides, other HIF-1 dependent mechanisms capable to affect respiration rate have been reported. First, the subunit composition of COX is altered in hypoxic cells by increased degradation of the COX4-1 subunit, which optimizes COX activity under aerobic conditions, and increased expression of the COX4-2 subunit, which optimizes COX activity under hypoxic conditions [29]. On the other hand, direct assay of respiration rate in cells exposed to hypoxia resulted in a significant reduction of respiration [60]. According with the evidence of Zhang et al., the respiration rate decrease has to be ascribed to mitochondrial autophagy, due to HIF-1-mediated expression of BNIP3. This interpretation is in line with preliminary results obtained in our laboratory where the assay of the citrate synthase activity of cells exposed to different oxygen tensions was performed. Fig. 2 shows the citrate synthase activity, which is taken as an index of the mitochondrial mass [11], with respect to oxygen tension: [O2] and mitochondrial mass are directly linked.

Citrate synthase activity

Citrate synthase activity

Fig. 2. Citrate synthase activity. Human primary fibroblasts, obtained from skin biopsies of 5 healthy donors, were seeded at a density of 8,000 cells/cm2 in high glucose Dulbecco’s Modified Eagle Medium, DMEM (25 mM glucose, 110 mg/l pyruvate, and 4 mM glutamine) supplemented with 15% Foetal Bovine Serum (FBS). 18 h later, cell culture dishes were washed once with Hank’s Balanced Salt Solution (HBSS) and the medium was replaced with DMEM containing 5 mM glucose, 110 mg/l pyruvate, and 4 mM glutamine supplemented with 15% FBS. Cell culture dishes were then placed into an INVIVO2 humidified hypoxia workstation (Ruskinn Technologies, Bridgend, UK) for 72 h changing the medium at 48 h, and oxygen partial pressure (tension) conditions were: 20%, 4%, 2%, 1% and 0.5%. Cells were subsequently collected within the workstation with trypsin-EDTA (0.25%), washed with PBS and resuspended in a buffer containing 10 mM Tris/HCl, 0.1 M KCl, 5 mM KH2PO4, 1 mM EGTA, 3 mM EDTA, and 2 mM MgCl2 pH 7.4 (all the solutions were preconditioned to the appropriate oxygen tension condition). The citrate synthase activity was assayed essentially by incubating 40 µg of cells with 0.02% Triton X-100, and monitoring the reaction by measuring spectrophotometrically the rate of free coenzyme A released, as described in [90]. Enzymatic activity was expressed as nmol/min/mg of protein. Three independent experiments were carried out and assays were performed in either duplicate or triplicate.

However, the observations of Semenza et al. must be seen in relation with data reported by Moncada et al.[57] and confirmed by others [61] in which it is clearly shown that when cells (various cell lines) experience hypoxic conditions, nitric oxide synthases (NOSs) are activated, therefore NO is released. As already mentioned above, NO is a strong competitor of O2 for cytochrome c oxidase, whose apparent Km results increased, hence reduction of mitochondrial cytochromes and all the other redox centres of the respiratory chain occurs. In addition, very recent data indicate a potential de-activation of Complex I when oxygen is lacking, as it occurs in prolonged hypoxia [62]. According to Hagen et al. [63] the NO-dependent inhibition of cytochrome c oxidase should allow “saved” O2 to redistribute within the cell to be used by other enzymes, including PHDs which inactivate HIF. Therefore, unless NO inhibition of cytochrome c oxidase occurs only when [O2] is very low, inhibition of mitochondrial oxygen consumption creates the paradox of a situation in which the cell may fail to register hypoxia. It has been tempted to solve this paradox, but to date only hypotheses have been proposed [23] and [26]. Interestingly, recent observations on yeast cells exposed to hypoxia revealed abnormal protein carbonylation and protein tyrosine nitration that were ascribed to increased mitochondrially generated superoxide radicals and NO, two species typically produced at low oxygen levels, that combine to form ONOO [64]. Based on these studies a possible explanation has been proposed for the above paradox.

Finally, it has to be noticed that the mitochondrial respiratory deficiency observed in cardiomyocytes of dogs in which experimental heart failure had been induced lies in the supermolecular assembly rather than in the individual components of the electron-transport chain [65]. This observation is particularly intriguing since loss of respirasomes is thought to facilitate ROS generation in mitochondria [66], therefore supercomplexes disassembly might explain the paradox of reduced [O2] and the enhanced ROS found in hypoxic cells. Specifically, hypoxia could reduce mitochondrial fusion by impairing mitochondrial membrane potential, which in turn could induce supercomplexes disassembly, increasing ROS production[11].

Complex III and ROS production

It has been estimated that, under normoxic physiological conditions, 1–2% of electron flow through the mitochondrial respiratory chain gives rise to ROS [67] and [68]. It is now recognized that the major sites of ROS production are within Complexes I and III, being prevalent the contribution of Complex I [69] (Fig. 3). It might be expected that hypoxia would decrease ROS production, due to the low level of O2 and to the diminished mitochondrial respiration [6] and [46], but ROS level is paradoxically increased. Indeed, about a decade ago, Chandel et al. [70] provided good evidence that mitochondrial reactive oxygen species trigger hypoxia-induced transcription, and a few years later the same group [71] showed that ROS generated at Complex III of the mitochondrial respiratory chain stabilize HIF-1α during hypoxia (Fig. 1 and Fig. 3). Although others have proposed mechanisms indicating a key role of mitochondria in HIF-1α regulation during hypoxia (for reviews see [64] and [72]), the contribution of mitochondria to HIF-1 regulation has been questioned by others [35][36] and [37]. Results of Gong and Agani [35] for instance show that inhibition of electron-transport Complexes I, III, and IV, as well as inhibition of mitochondrial F0F1 ATPase, prevents HIF-1α expression and that mitochondrial reactive oxygen species are not involved in HIF-1α regulation during hypoxia. Concurrently, Tuttle et al. [73], by means of a non invasive, spectroscopic approach, could find no evidence to suggest that ROS, produced by mitochondria, are needed to stabilize HIF-1α under moderate hypoxia. The same authors found the levels of HIF-1α comparable in both normal and ρ0 cells (i.e. cells lacking mitochondrial DNA). On the contrary, experiments carried out on genetic models consisting of either cells lacking cytochrome c or ρ0 cells both could evidence the essential role of mitochondrial respiration to stabilize HIF-1α [74]. Thus, cytochrome c null cells, being incapable to respire, exposed to moderate hypoxia (1.5% O2) prevented oxidation of ubiquinol and generation of the ubisemiquinone radical, thus eliminating superoxide formation at Complex III [71]. Concurrently, ρ0 cells lacking electron transport, exposed 4 h to moderate hypoxia failed to stabilize HIF-1α, suggesting the essential role of the respiratory chain for the cellular sensing of low O2 levels. In addition, recent evidence obtained on genetic manipulated cells (i.e. cytochrome b deficient cybrids) showed increased ROS levels and stabilized HIF-1α protein during hypoxia [75]. Moreover, RNA interference of the Complex III subunit Rieske iron sulfur protein in the cytochrome b deficient cells, abolished ROS generation at the Qo site of Complex III, preventing HIF-1α stabilization. These observations, substantiated by experiments with MitoQ, an efficient mitochondria-targeted antioxidant, strongly support the involvement of mitochondrial ROS in regulating HIF-1α. Nonetheless, collectively, the available data do not allow to definitely state the precise role of mitochondrial ROS in regulating HIF-1α, but the pathway stabilizing HIF-1α appears undoubtedly mitochondria-dependent [30].

Overview of mitochondrial electron and proton flux in hypoxia

Overview of mitochondrial electron and proton flux in hypoxia

Overview of mitochondrial electron and proton flux in hypoxia

Fig. 3. Overview of mitochondrial electron and proton flux in hypoxia. Electrons released from reduced cofactors (NADH and FADH2) under normoxia flow through the redox centres of the respiratory chain (r.c.) to molecular oxygen (blue dotted line), to which a proton flux from the mitochondrial matrix to the intermembrane space is coupled (blue arrows). Protons then flow back to the matrix through the F0 sector of the ATP synthase complex, driving ATP synthesis. ATP is carried to the cell cytosol by the adenine nucleotide translocator (blue arrows). Under moderate to severe hypoxia, electrons escape the r.c. redox centres and reduce molecular oxygen to the superoxide anion radical before reaching the cytochrome c (red arrow). Under these conditions, to maintain an appropriate Δψm, ATP produced by cytosolic glycolysis enters the mitochondria where it is hydrolyzed by the F1F0ATPase with extrusion of protons from the mitochondrial matrix (red arrows).

Hypoxia and ATP synthase

The F1F0 ATPase (ATP synthase) is the enzyme responsible of catalysing ADP phosphorylation as the last step of OXPHOS. It is a rotary motor using the proton motive force across the mitochondrial inner membrane to drive the synthesis of ATP [76]. It is a reversible enzyme with ATP synthesis or hydrolysis taking place in the F1 sector at the matrix side of the membrane, chemical catalysis being coupled to H+transport through the transmembrane F0 sector.

Under normoxia the enzyme synthesizes ATP, but when mitochondria experience hypoxic conditions the mitochondrial membrane potential (Δψm) decreases below its endogenous steady-state level (some 140 mV, negative inside the matrix [77]) and the F1F0 ATPase may work in the reversal mode: it hydrolyses ATP (produced by anaerobic glycolysis) and uses the energy released to pump protons from the mitochondrial matrix to the intermembrane space, concurring with the adenine nucleotide translocator (i.e. in hypoxia it exchanges cytosolic ATP4− for matrix ADP3−) to maintain the physiological Δψm ( Fig. 3). Since under conditions of limited oxygen availability the decline in cytoplasmic high energy phosphates is mainly due to hydrolysis by the ATP synthase working in reverse [6] and [78], the enzyme must be strictly regulated in order to avoid ATP dissipation. This is achieved by a natural protein, the H+ψm-dependent IF1, that binds to the catalytic F1 sector at low pH and low Δψm (such as it occurs in hypoxia/ischemia) [79]. IF1 binding to the ATP synthase results in a rapid and reversible inhibition of the enzyme [80], which could reach about 50% of maximal activity (for recent reviews see [6] and [81]).

Besides this widely studied effect, IF1 appears to be associated with ROS production and mitochondrial autophagy (mitophagy). This is a mechanism involving the catabolic degradation of macromolecules and organelles via the lysosomal pathway that contributes to housekeeping and regenerate metabolites. Autophagic degradation is involved in the regulation of the ageing process and in several human diseases, such as myocardial ischemia/reperfusion [82], Alzheimer’s Disease, Huntington diseases, and inflammatory diseases (for recent reviews see [83] and [84], and, as mentioned above, it promotes cell survival by reducing ROS and mtDNA damage under hypoxic conditions.

Campanella et al. [81] reported that, in HeLa cells under normoxic conditions, basal autophagic activity varies in relation to the expression levels of IF1. Accordingly, cells overexpressing IF1 result in ROS production similar to controls, conversely cells in which IF1 expression is suppressed show an enhanced ROS production. In parallel, the latter cells show activation of the mitophagy pathway (Fig. 1), therefore suggesting that variations in IF1 expression level may play a significant role in defining two particularly important parameters in the context of the current review: rates of ROS generation and mitophagy. Thus, the hypoxia-induced enhanced expression level of IF1[81] should be associated with a decrease of both ROS production and autophagy, which is in apparent conflict with the hypoxia-induced ROS increase and with the HIF-1-dependent mitochondrial autophagy shown by Zhang et al. [60] as an adaptive metabolic response to hypoxia. However, in the experiments of Zhang et al. the cells were exposed to hypoxia for 48 h, whereas the F1F0-ATPase inhibitor exerts a prompt action on the enzyme and to our knowledge, it has never been reported whether its action persists during prolonged hypoxic expositions. Pertinent with this problem is the very recent observation that IEX-1 (immediate early response gene X-1), a stress-inducible gene that suppresses production of ROS and protects cells from apoptosis [85], targets the mitochondrial F1F0-ATPase inhibitor for degradation, reducing ROS by decreasing Δψm. It has to be noticed that the experiments described were carried out under normal oxygen availability, but it does not seem reasonable to rule out IEX-1 from playing a role under stress conditions as those induced by hypoxia in cells, therefore this issue might deserve an investigation also at low oxygen levels.

In conclusion, data are still emerging regarding the regulation of mitochondrial function by the F1F0 ATPase within hypoxic responses in different cellular and physiological contexts. Given the broad pathophysiological role of hypoxic cellular modulation, an understanding of the subtle tuning among different effectors of the ATP synthase is desirable to eventually target future therapeutics most effectively. Our laboratory is actually involved in carrying out investigations to clarify this context.

Conclusions and perspectives

The mitochondria are important cellular platforms that both propagate and initiate intracellular signals that lead to overall cellular and metabolic responses. During the last decades, a significant amount of relevant data has been obtained on the identification of mechanisms of cellular adaptation to hypoxia. In hypoxic cells there is an enhanced transcription and synthesis of several glycolytic pathway enzymes/transporters and reduction of synthesis of proteins involved in mitochondrial catabolism. Although well defined kinetic parameters of reactions in hypoxia are lacking, it is usually assumed that these transcriptional changes lead to metabolic flux modification. The required biochemical experimentation has been scarcely addressed until now and only in few of the molecular and cellular biology studies the transporter and enzyme kinetic parameters and flux rate have been determined, leaving some uncertainties.

Central to mitochondrial function and ROS generation is an electrochemical proton gradient across the mitochondrial inner membrane that is established by the proton pumping activity of the respiratory chain, and that is strictly linked to the F1F0-ATPase function. Evaluation of the mitochondrial membrane potential in hypoxia has only been studied using semiquantitative methods based on measurements of the fluorescence intensity of probes taken up by cells experiencing normal or hypoxic conditions. However, this approach is intrinsically incorrect due to the different capability that molecular oxygen has to quench fluorescence [86] and [87] and to the uncertain concentration the probe attains within mitochondria, whose mass may be reduced by a half in hypoxia [60]. In addition, the uncertainty about measurement of mitochondrial superoxide radical and H2O2 formation in vivo [88] hampers studies on the role of mitochondrial ROS in hypoxic oxidative damage, redox signaling, and HIF-1 stabilization.

The duration and severity of hypoxic stress differentially activate the responses discussed throughout and lead to substantial phenotypic variations amongst tissues and cell models, which are not consistently and definitely known. Certainly, understanding whether a hierarchy among hypoxia response mechanisms exists and which are the precise timing and conditions of each mechanism to activate, will improve our knowledge of the biochemical mechanisms underlying hypoxia in cells, which eventually may contribute to define therapeutic targets in hypoxia-associated diseases. To this aim it might be worth investigating the hypoxia-induced structural organization of both the respiratory chain enzymes in supramolecular complexes and the assembly of the ATP synthase to form oligomers affecting ROS production [65] and inner mitochondrial membrane structure [89], respectively.

7.9.2 Hypoxia promotes isocitrate dehydrogenase-dependent carboxylation of α-ketoglutarate to citrate to support cell growth and viability

DR WisePS WardJES ShayJR CrossJJ Gruber, UM Sachdeva, et al.
Proc Nat Acad Sci Oct 27, 2011; 108(49):19611–19616

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 concomitant increased synthesis of 2-hydroxyglutarate (2HG) in cells with wild-type IDH1 and IDH2. When either starved of glutamine or rendered IDH2-deficient by RNAi, hypoxic cells are unable to proliferate. The reductive carboxylation of glutamine 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 (45). 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 (67). 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 for this shift in mammalian cells has been linked to the activity of the transcription factor HIF1 (810). 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 glutamine metabolism can be rerouted through IDH2-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 cell line 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 (1213). 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.

SF188 glioblastoma cells proliferate at 0.5% O2 despite a profound reduction in glucose-dependent citrate synthesis.

SF188 glioblastoma cells proliferate at 0.5% O2 despite a profound reduction in glucose-dependent citrate synthesis.

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 13C-labeled 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 GC-MS 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.

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 by gas chromatography-mass spectrometry (GC-MS). In normoxia, the major 13C-enriched citrate species found was citrate enriched with two 13C atoms (cit+2), which can arise from the NAD+-dependent decarboxylation of pyruvate+3 to acetyl-CoA+2 by PDH, followed by the condensation of acetyl-CoA+2 with unenriched oxaloacetate (Fig. 1 E and F). Compared with the accumulation of cit+2, we observed minimal accumulation of cit+3 and cit+5 under normoxia. Cit+3 arises from pyruvate carboxylase (PC)-dependent conversion of pyruvate+3 to oxaloacetate+3, followed by the condensation of oxaloacetate+3 with unenriched acetyl-CoA. Cit+5 arises when PC-generated oxaloacetate+3 condenses with PDH-generated acetyl-CoA+2. The lack of cit+3 and cit+5 accumulation is consistent with PC activity not playing a major role in citrate production in normoxic SF188 cells, as reported (4).

In hypoxic cells, the major citrate species observed was unenriched. Cit+2, cit+3, and cit+5 all constituted minor fractions of the total citrate pool, consistent with glucose carbon not being incorporated into citrate through either PDH or PC-mediated metabolism under hypoxic conditions (Fig. 1F). These data demonstrate that in contrast to normoxic cells, where a large percentage of citrate production depends on glucose-derived carbon, hypoxic cells significantly reduce their rate of citrate production from glucose.

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.

Glutamine carbon is required for hypoxic cell viability

Glutamine carbon is required for hypoxic cell viability

Glutamine carbon is required for hypoxic cell viability

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.

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 (1517), 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.

Reductive carboxylation of glutamine-derived α-ketoglutarate to citrate in hypoxic cancer cells is dependent on mitochondrial IDH2

Reductive carboxylation of glutamine-derived α-ketoglutarate to citrate in hypoxic cancer cells is dependent on mitochondrial IDH2

Reductive carboxylation of glutamine-derived α-ketoglutarate to citrate in hypoxic cancer cells is dependent on mitochondrial IDH2

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 hemacytometer (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.

In an experiment to test this hypothesis, SF188 cells were transfected with either siRNA directed against mitochondrial IDH2 (siIDH2) or nontargeting control, incubated in hypoxia for 2 d, and then cultured for another 4 h in hypoxia in media containing 4 mM [U-13C]glutamine. After the labeling period, metabolites were extracted and analyzed by GC-MS (Fig. 4C). Hypoxic SF188 cells transfected with siIDH2 displayed a decreased contribution of cit+5 to the total citrate pool, supporting an important role for IDH2 in the reductive carboxylation of glutamine-derived α-ketoglutarate in hypoxic conditions. The contribution of cit+4 to the total citrate pool did not decrease with siIDH2 treatment, consistent with IDH2 knockdown specifically affecting the pathway of reductive carboxylation and not other fundamental TCA cycle-regulating processes. In confirmation of reverse flux occurring through IDH2, the contribution of 2HG+5 to the total 2HG pool decreased in siIDH2-treated cells. Supporting the importance of citrate production by IDH2-mediated reductive carboxylation for hypoxic cell proliferation, siIDH2-transfected SF188 cells displayed a defect in cellular accumulation in hypoxia. Decreased expression of IDH2 protein following siIDH2 transfection was confirmed by Western blot. Collectively, these data point to the importance of mitochondrial IDH2 for the increase in reductive carboxylation flux of glutamine-derived α-ketoglutarate to maintain citrate levels in hypoxia, and to the importance of this reductive pathway for hypoxic cell proliferation.

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 (1213). However, a shift to preferential reductive glutamine metabolism could also result from the active reprogramming of cellular metabolism by HIF1 (810), 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). RCC4 cells expressing either a nontargeting control shRNA (shCTRL) or an shRNA directed at HIF1α (shHIF1α) were incubated in normoxia and cultured in medium with 4 mM [U-13C]glutamine. Following a 4-h labeling period, metabolites were extracted and the cellular citrate pool was analyzed by GC-MS. In shCTRL cells, which have constitutive HIF1α expression despite incubation in normoxia, the majority of the total citrate pool was constituted by the cit+5 species, with low levels of all other species including cit+4 (Fig. 5C). By contrast, in HIF1α-deficient cells the contribution of cit+5 to the total citrate pool was greatly decreased, whereas the contribution of cit+4 to the total citrate pool increased and was the most abundant citrate species. These data demonstrate that the relative enhancement of the reductive carboxylation pathway for citrate synthesis can be recapitulated by constitutive HIF1 activation in normoxia.

Reprogramming of metabolism by HIF1 in the absence of hypoxia

Reprogramming of metabolism by HIF1 in the absence of hypoxia

Reprogramming of metabolism by HIF1 in the absence of hypoxia is sufficient to induce reductive carboxylation of glutamine-derived α-ketoglutarate.

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 (1920), 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 (2122), with the transfer of electrons from NADH to NADP+ to generate NADPH occurring through the activity of the mitochondrial transhydrogenase (23). Our data do not exclude a complementary role for cytosolic IDH1 in impacting reductive glutamine metabolism, potentially through its oxidative function in an IDH2/IDH1 shuttle that transfers high energy electrons in the form of NADPH from mitochondria to cytosol (1624).

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 IDH2 in 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.

The IDH2-dependent reductive carboxylation pathway that we propose in this report allows for continued citrate production from glutamine carbon when hypoxia and/or HIF1 activation prevents glucose carbon from contributing to citrate synthesis. Moreover, as opposed to continued oxidative TCA cycle functioning in hypoxia which can increase reactive oxygen species (ROS), reductive carboxylation of α-ketoglutarate in the mitochondria may serve as an electron sink that decreases the generation of ROS. HIF1 activity is not limited to the setting of hypoxia, as a common feature of several cancers is the normoxic stabilization of HIF1α through loss of the VHL tumor suppressor or other mechanisms. We demonstrate here that altered glutamine metabolism through a mitochondrial reductive pathway is a central aspect of hypoxic proliferating cell metabolism and HIF1-induced metabolic reprogramming. These findings are relevant for the understanding of numerous constitutive HIF1-expressing malignancies, as well as for populations, such as stem progenitor cells, which frequently proliferate in hypoxic conditions.

7.9.3 Hypoxia-Inducible Factors in Physiology and Medicine

Gregg L. Semenza
Cell. 2012 Feb 3; 148(3): 399–408.

Oxygen homeostasis represents an organizing principle for understanding metazoan evolution, development, physiology, and pathobiology. The hypoxia-inducible factors (HIFs) are transcriptional activators that function as master regulators of oxygen homeostasis in all metazoan species. Rapid progress is being made in elucidating homeostatic roles of HIFs in many physiological systems, determining pathological consequences of HIF dysregulation in chronic diseases, and investigating potential targeting of HIFs for therapeutic purposes. Oxygen homeostasis represents an organizing principle for understanding metazoan evolution, development, physiology, and pathobiology. The hypoxia-inducible factors (HIFs) are transcriptional activators that function as master regulators of oxygen homeostasis in all metazoan species. Rapid progress is being made in elucidating homeostatic roles of HIFs in many physiological systems, determining pathological consequences of HIF dysregulation in chronic diseases, and investigating potential targeting of HIFs for therapeutic purposes.


Oxygen is central to biology because of its utilization in the process of respiration. O2 serves as the final electron acceptor in oxidative phosphorylation, which carries with it the risk of generating reactive oxygen species (ROS) that react with cellular macromolecules and alter their biochemical or physical properties, resulting in cell dysfunction or death. As a consequence, metazoan organisms have evolved elaborate cellular metabolic and systemic physiological systems that are designed to maintain oxygen homeostasis. This review will focus on the role of hypoxia-inducible factors (HIFs) as master regulators of oxygen homeostasis and, in particular, on recent advances in understanding their roles in physiology and medicine. Due to space limitations and the remarkably pleiotropic effects of HIFs, the description of such roles will be illustrative rather than comprehensive.

O2 and Evolution, Part 1

Accumulation of O2 in Earth’s atmosphere starting ~2.5 billion years ago led to evolution of the extraordinarily efficient system of oxidative phosphorylation that transfers chemical energy stored in carbon bonds of organic molecules to the high-energy phosphate bond in ATP, which is used to power physicochemical reactions in living cells. Energy produced by mitochondrial respiration is sufficient to power the development and maintenance of multicellular organisms, which could not be sustained by energy produced by glycolysis alone (Lane and Martin, 2010). The modest dimensions of primitive metazoan species were such that O2 could diffuse from the atmosphere to all of the organism’s thousand cells, as is the case for the worm Caenorhabditis elegans. To escape the constraints placed on organismal growth by diffusion, systems designed to conduct air to cells deep within the body evolved and were sufficient for O2delivery to organisms with hundreds of thousands of cells, such as the fly Drosophila melanogaster. The final leap in body scale occurred in vertebrates and was associated with the evolution of complex respiratory, circulatory, and nervous systems designed to efficiently capture and distribute O2 to hundreds of millions of millions of cells in the case of the adult Homo sapiens.

Hypoxia-Inducible Factors

Hypoxia-inducible factor 1 (HIF-1) is expressed by all extant metazoan species analyzed (Loenarz et al., 2011). HIF-1 consists of HIF-1α and HIF-1β subunits, which each contain basic helix-loop-helix-PAS (bHLH-PAS) domains (Wang et al., 1995) that mediate heterodimerization and DNA binding (Jiang et al., 1996a). HIF-1β heterodimerizes with other bHLH-PAS proteins and is present in excess, such that HIF-1α protein levels determine HIF-1 transcriptional activity (Semenza et al., 1996).

Under well-oxygenated conditions, HIF-1α is bound by the von Hippel-Lindau (VHL) protein, which recruits an ubiquitin ligase that targets HIF-1α for proteasomal degradation (Kaelin and Ratcliffe, 2008). VHL binding is dependent upon hydroxylation of a specific proline residue in HIF-1α by the prolyl hydroxylase PHD2, which uses O2 as a substrate such that its activity is inhibited under hypoxic conditions (Epstein et al., 2001). In the reaction, one oxygen atom is inserted into the prolyl residue and the other atom is inserted into the co-substrate α-ketoglutarate, splitting it into CO2 and succinate (Kaelin and Ratcliffe, 2008). Factor inhibiting HIF-1 (FIH-1) represses HIF-1α transactivation function (Mahon et al., 2001) by hydroxylating an asparaginyl residue, using O2 and α-ketoglutarate as substrates, thereby blocking the association of HIF-1α with the p300 coactivator protein (Lando et al., 2002). Dimethyloxalylglycine (DMOG), a competitive antagonist of α-ketoglutarate, inhibits the hydroxylases and induces HIF-1-dependent transcription (Epstein et al., 2001). HIF-1 activity is also induced by iron chelators (such as desferrioxamine) and cobalt chloride, which inhibit hydroxylases by displacing Fe(II) from the catalytic center (Epstein et al., 2001).

Studies in cultured cells (Jiang et al., 1996b) and isolated, perfused, and ventilated lung preparations (Yu et al., 1998) revealed an exponential increase in HIF-1α levels at O2 concentrations less than 6% (~40 mm Hg), which is not explained by known biochemical properties of the hydroxylases. In most adult tissues, O2concentrations are in the range of 3-5% and any decrease occurs along the steep portion of the dose-response curve, allowing a graded response to hypoxia. Analyses of cultured human cells have revealed that expression of hundreds of genes was increased in response to hypoxia in a HIF-1-dependent manner (as determined by RNA interference) with direct binding of HIF-1 to the gene (as determined by chromatin immunoprecipitation [ChIP] assays); in addition, the expression of hundreds of genes was decreased in response to hypoxia in a HIF-1-dependent manner but binding of HIF-1 to these genes was not detected (Mole et al., 2009), indicating that HIF-dependent repression occurs via indirect mechanisms, which include HIF-1-dependent expression of transcriptional repressors (Yun et al., 2002) and microRNAs (Kulshreshtha et al., 2007). ChIP-seq studies have revealed that only 40% of HIF-1 binding sites are located within 2.5 kb of the transcription start site (Schödel et al., 2011).

In vertebrates, HIF-2α is a HIF-1α paralog that is also regulated by prolyl and asparaginyl hydroxylation and dimerizes with HIF-1β, but is expressed in a cell-restricted manner and plays important roles in erythropoiesis, vascularization, and pulmonary development, as described below. In D. melanogaster, the gene encoding the HIF-1α ortholog is designated similar and its paralog is designated trachealess because inactivating mutations result in defective development of the tracheal tubes (Wilk et al., 1996). In contrast, C. elegans has only a single HIF-1α homolog (Epstein et al., 2001). Thus, in both invertebrates and vertebrates, evolution of specialized systems for O2 delivery was associated with the appearance of a HIF-1α paralog.

O2 and Metabolism

The regulation of metabolism is a principal and primordial function of HIF-1. Under hypoxic conditions, HIF-1 mediates a transition from oxidative to glycolytic metabolism through its regulation of: PDK1, encoding pyruvate dehydrogenase (PDH) kinase 1, which phosphorylates and inactivates PDH, thereby inhibiting the conversion of pyruvate to acetyl coenzyme A for entry into the tricarboxylic acid cycle (Kim et al., 2006Papandreou et al., 2006); LDHA, encoding lactate dehydrogenase A, which converts pyruvate to lactate (Semenza et al. 1996); and BNIP3 (Zhang et al. 2008) and BNIP3L (Bellot et al., 2009), which mediate selective mitochondrial autophagy (Figure 1). HIF-1 also mediates a subunit switch in cytochrome coxidase that improves the efficiency of electron transfer under hypoxic conditions (Fukuda et al., 2007). An analogous subunit switch is also observed in Saccharomyces cerevisiae, although it is mediated by a completely different mechanism (yeast lack HIF-1), suggesting that it may represent a fundamental response of eukaryotic cells to hypoxia.

Regulation of Glucose Metabolism nihms-350382-f0001

Regulation of Glucose Metabolism nihms-350382-f0001

Regulation of Glucose Metabolism
Figure 1
Regulation of Glucose Metabolism

It is conventional wisdom that cells switch to glycolysis when O2 becomes limiting for mitochondrial ATP production. Yet, HIF-1α-null mouse embryo fibroblasts, which do not down-regulate respiration under hypoxic conditions, have higher ATP levels at 1% O2 than wild-type cells at 20% O2, demonstrating that under these conditions O2 is not limiting for ATP production (Zhang et al., 2008). However, the HIF-1α-null cells die under prolonged hypoxic conditions due to ROS toxicity (Kim et al. 2006Zhang et al., 2008). These studies have led to a paradigm shift with regard to our understanding of the regulation of cellular metabolism (Semenza, 2011): the purpose of this switch is to prevent excess mitochondrial generation of ROS that would otherwise occur due to the reduced efficiency of electron transfer under hypoxic conditions (Chandel et al., 1998). This may be particularly important in stem cells, in which avoidance of DNA damage is critical (Suda et al., 2011).

Role of HIFs in Development

Much of mammalian embryogenesis occurs at O2 concentrations of 1-5% and O2 functions as a morphogen (through HIFs) in many developmental systems (Dunwoodie, 2009). Mice that are homozygous for a null allele at the locus encoding HIF-1α die by embryonic day 10.5 with cardiac malformations, vascular defects, and impaired erythropoiesis, indicating that all three components of the circulatory system are dependent upon HIF-1 for normal development (Iyer et al., 1998Yoon et al., 2011). Depending on the genetic background, mice lacking HIF-2α: die by embryonic day 12.5 with vascular defects (Peng et al., 2000) or bradycardia due to deficient catecholamine production (Tian et al., 1998); die as neonates due to impaired lung maturation (Compernolle et al., 2002); or die several months after birth due to ROS-mediated multi-organ failure (Scortegagna et al., 2003). Thus, while vertebrate evolution was associated with concomitant appearance of the circulatory system and HIF-2α, both HIF-1 and HIF-2 have important roles in circulatory system development. Conditional knockout of HIF-1α in specific cell types has demonstrated important roles in chondrogenesis (Schipani et al., 2001), adipogenesis (Yun et al., 2002), B-lymphocyte development (Kojima et al., 2002), osteogenesis (Wang et al., 2007), hematopoiesis (Takubo et al., 2010), T-lymphocyte differentiation (Dang et al., 2011), and innate immunity (Zinkernagel et al., 2007). While knockout mouse experiments point to the adverse effects of HIF-1 loss-of-function on development, it is also possible that increased HIF-1 activity, induced by hypoxia in embryonic tissues as a result of abnormalities in placental blood flow, may also dysregulate development and result in congenital malformations. For example, HIF-1α has been shown to interact with, and stimulate the transcriptional activity of, Notch, which plays a key role in many developmental pathways (Gustafsson et al., 2005).

Translational Prospects

Drug discovery programs have been initiated at many pharmaceutical and biotech companies to develop prolyl hydroxylase inhibitors (PHIs) that, as described above for DMOG, induce HIF activity for treatment of disorders in which HIF mediates protective physiological responses. Local and/or short term induction of HIF activity by PHIs, gene therapy, or other means are likely to be useful novel therapies for many of the diseases described above. In the case of ischemic cardiovascular disease, local therapy is needed to provide homing signals for the recruitment of BMDACs. Chronic systemic use of PHIs must be approached with great caution: individuals with genetic mutations that constitutively activate the HIF pathway (described below) have increased incidence of cardiovascular disease and mortality (Yoon et al., 2011). On the other hand, the profound inhibition of HIF activity and vascular responses to ischemia that are associated with aging suggest that systemic replacement therapy might be contemplated as a preventive measure for subjects in whom impaired HIF responses to hypoxia can be documented. In C. elegans, VHL loss-of-function increases lifespan in a HIF-1-dependent manner (Mehta et al., 2009), providing further evidence for a mutually antagonistic relationship between HIF-1 and aging.


Cancers contain hypoxic regions as a result of high rates of cell proliferation coupled with the formation of vasculature that is structurally and functionally abnormal. Increased HIF-1α and/or HIF-2α levels in diagnostic tumor biopsies are associated with increased risk of mortality in cancers of the bladder, brain, breast, colon, cervix, endometrium, head/neck, lung, ovary, pancreas, prostate, rectum, and stomach; these results are complemented by experimental studies, which demonstrate that genetic manipulations that increase HIF-1α expression result in increased tumor growth, whereas loss of HIF activity results in decreased tumor growth (Semenza, 2010). HIFs are also activated by genetic alterations, most notably, VHL loss of function in clear cell renal carcinoma (Majmunder et al., 2010). HIFs activate transcription of genes that play key roles in critical aspects of cancer biology, including stem cell maintenance (Wang et al., 2011), cell immortalization, epithelial-mesenchymal transition (Mak et al., 2010), genetic instability (Huang et al., 2007), vascularization (Liao and Johnson, 2007), glucose metabolism (Luo et al., 2011), pH regulation (Swietach et al., 2007), immune evasion (Lukashev et al., 2007), invasion and metastasis (Chan and Giaccia, 2007), and radiation resistance (Moeller et al., 2007). Given the extensive validation of HIF-1 as a potential therapeutic target, drugs that inhibit HIF-1 have been identified and shown to have anti-cancer effects in xenograft models (Table 1Semenza, 2010).

Table 1  Drugs that Inhibit HIF-1

Process Inhibited Drug Class Prototype
HIF-1 α synthesis Cardiac glycosidemTOR inhibitorMicrotubule targeting agent

Topoisomerase I inhibitor



HIF-1 α protein stability HDAC inhibitorHSP90 inhibitorCalcineurin inhibitor

Guanylate cyclase activator



Heterodimerization Antimicrobial agent Acriflavine
DNA binding AnthracyclineQuinoxaline antibiotic DoxorubicinEchinomycin
Transactivation Proteasome inhibitorAntifungal agent BortezomibAmphotericin B
Signal transduction BCR-ABL inhibitorCyclooxygenase inhibitorEGFR inhibitor

HER2 inhibitor

ImatinibIbuprofenErlotinib, Gefitinib


Over 100 women die every day of breast cancer in the U.S. The mean PO2 is 10 mm Hg in breast cancer as compared to > 60 mm Hg in normal breast tissue and cancers with PO2 < 10 mm Hg are associated with increased risk of metastasis and patient mortality (Vaupel et al., 2004). Increased HIF-1α protein levels, as identified by immunohistochemical analysis of tumor biopsies, are associated with increased risk of metastasis and/or patient mortality in unselected breast cancer patients and in lymph node-positive, lymph node-negative, HER2+, or estrogen receptor+ subpopulations (Semenza, 2011). Metastasis is responsible for > 90% of breast cancer mortality. The requirement for HIF-1 in breast cancer metastasis has been demonstrated for both autochthonous tumors in transgenic mice (Liao et al., 2007) and orthotopic transplants in immunodeficient mice (Zhang et al., 2011Wong et al., 2011). Primary tumors direct the recruitment of bone marrow-derived cells to the lungs and other sites of metastasis (Kaplan et al., 2005). In breast cancer, hypoxia induces the expression of lysyl oxidase (LOX), a secreted protein that remodels collagen at sites of metastatic niche formation (Erler et al., 2009). In addition to LOX, breast cancers also express LOX-like proteins 2 and 4. LOX, LOXL2, and LOXL4 are all HIF-1-regulated genes and HIF-1 inhibition blocks metastatic niche formation regardless of which LOX/LOXL protein is expressed, whereas available LOX inhibitors are not effective against all LOXL proteins (Wong et al., 2011), again illustrating the role of HIF-1 as a master regulator that controls the expression of multiple genes involved in a single (patho)physiological process.

Translational Prospects

Small molecule inhibitors of HIF activity that have anti-cancer effects in mouse models have been identified (Table 1). Inhibition of HIF impairs both vascular and metabolic adaptations to hypoxia, which may decrease O2 delivery and increase O2 utilization. These drugs are likely to be useful (as components of multidrug regimens) in the treatment of a subset of cancer patients in whom high HIF activity is driving progression. As with all novel cancer therapeutics, successful translation will require the development of methods for identifying the appropriate patient cohort. Effects of combination drug therapy also need to be considered. VEGF receptor tyrosine kinase inhibitors, which induce tumor hypoxia by blocking vascularization, have been reported to increase metastasis in mouse models (Ebos et al., 2009), which may be mediated by HIF-1; if so, combined use of HIF-1 inhibitors with these drugs may prevent unintended counter-therapeutic effects.

HIF inhibitors may also be useful in the treatment of other diseases in which dysregulated HIF activity is pathogenic. Proof of principle has been established in mouse models of ocular neovascularization, a major cause of blindness in the developed world, in which systemic or intraocular injection of the HIF-1 inhibitor digoxin is therapeutic (Yoshida et al., 2010). Systemic administration of HIF inhibitors for cancer therapy would be contraindicated in patients who also have ischemic cardiovascular disease, in which HIF activity is protective. The analysis of SNPs at the HIF1A locus described above suggests that the population may include HIF hypo-responders, who are at increased risk of severe ischemic cardiovascular disease. It is also possible that HIF hyper-responders, such as individuals with hereditary erythrocytosis, are at increased risk of particularly aggressive cancer.

O2 and Evolution, Part 2

When lowlanders sojourn to high altitude, hypobaric hypoxia induces erythropoiesis, which is a relatively ineffective response because the problem is not insufficient red cells, but rather insufficient ambient O2. Chronic erythrocytosis increases the risk of heart attack, stroke, and fetal loss during pregnancy. Many high-altitude Tibetans maintain the same hemoglobin concentration as lowlanders and yet, despite severe hypoxemia, they also maintain aerobic metabolism. The basis for this remarkable evolutionary adaptation appears to have involved the selection of genetic variants at multiple loci encoding components of the oxygen sensing system, particularly HIF-2α (Beall et al., 2010Simonson et al., 2010Yi et al., 2010). Given that hereditary erythrocytosis is associated with modest HIF-2α gain-of-function, the Tibetan genotype associated with absence of an erythrocytotic response to hypoxia may encode reduced HIF-2α activity along with other alterations that increase metabolic efficiency. Delineating the molecular mechanisms underlying these metabolic adaptations may lead to novel therapies for ischemic disorders, illustrating the importance of oxygen homeostasis as a nexus where evolution, biology, and medicine converge.

7.9.4 Hypoxia-inducible factor 1. Regulator of mitochondrial metabolism and mediator of ischemic preconditioning

Semenza GL1.
Biochim Biophys Acta. 2011 Jul; 1813(7):1263-8.

Hypoxia-inducible factor 1 (HIF-1) mediates adaptive responses to reduced oxygen availability by regulating gene expression. A critical cell-autonomous adaptive response to chronic hypoxia controlled by HIF-1 is reduced mitochondrial mass and/or metabolism. Exposure of HIF-1-deficient fibroblasts to chronic hypoxia results in cell death due to excessive levels of reactive oxygen species (ROS). HIF-1 reduces ROS production under hypoxic conditions by multiple mechanisms including: a subunit switch in cytochrome c oxidase from the COX4-1 to COX4-2 regulatory subunit that increases the efficiency of complex IV; induction of pyruvate dehydrogenase kinase 1, which shunts pyruvate away from the mitochondria; induction of BNIP3, which triggers mitochondrial selective autophagy; and induction of microRNA-210, which blocks assembly of Fe/S clusters that are required for oxidative phosphorylation. HIF-1 is also required for ischemic preconditioning and this effect may be due in part to its induction of CD73, the enzyme that produces adenosine. HIF-1-dependent regulation of mitochondrial metabolism may also contribute to the protective effects of ischemic preconditioning.

The story of life on Earth is a tale of oxygen production and utilization. Approximately 3 billion years ago, primitive single-celled organisms evolved the capacity for photosynthesis, a biochemical process in which photons of solar energy are captured by chlorophyll and used to power the reaction of CO2 and H2O to form glucose and O2. The subsequent rise in the atmospheric O2 concentration over the next billion years set the stage for the ascendance of organisms with the capacity for respiration, a process that consumes glucose and O2 and generates CO2, H2O, and energy in the form of ATP. Some of these single-celled organisms eventually took up residence within the cytoplasm of other cells and devoted all of their effort to energy production as mitochondria. Compared to the conversion of glucose to lactate by glycolysis, the complete oxidation of glucose by respiration provided such a large increase in energy production that it made possible the evolution of multicellular organisms. Among metazoan organisms, the progressive increase in body size during evolution was accompanied by progressively more complex anatomic structures that function to ensure the adequate delivery of O2 to all cells, ultimately resulting in the sophisticated circulatory and respiratory systems of vertebrates.

All metazoan cells can sense and respond to reduced O2 availability (hypoxia). Adaptive responses to hypoxia can be cell autonomous, such as the alterations in mitochondrial metabolism that are described below, or non-cell-autonomous, such as changes in tissue vascularization (reviewed in ref. 1). Primary responses to hypoxia need to be distinguished from secondary responses to sequelae of hypoxia, such as the adaptive responses to ATP depletion that are mediated by AMP kinase (reviewed in ref 2). In contrast, recent data suggest that O2 and redox homeostasis are inextricably linked and that changes in oxygenation are inevitably associated with changes in the levels of reactive oxygen species (ROS), as will be discussed below.

HIF-1 Regulates Oxygen Homeostasis in All Metazoan Species

A key regulator of the developmental and physiological networks required for the maintenance of O2homeostasis is hypoxia-inducible factor 1 (HIF-1). HIF-1 is a heterodimeric transcription factor that is composed of an O2-regulated HIF-1α subunit and a constitutively expressed HIF-1β subunit [3,4]. HIF-1 regulates the expression of hundreds of genes through several major mechanisms. First, HIF-1 binds directly to hypoxia response elements, which are cis-acting DNA sequences located within target genes [5]. The binding of HIF-1 results in the recruitment of co-activator proteins that activate gene transcription (Fig. 1A). Only rarely does HIF-1 binding result in transcriptional repression [6]. Instead, HIF-1 represses gene expression by indirect mechanisms, which are described below. Second, among the genes activated by HIF-1 are many that encode transcription factors [7], which when synthesized can bind to and regulate (either positively or negatively) secondary batteries of target genes (Fig. 1B). Third, another group of HIF-1 target genes encode members of the Jumonji domain family of histone demethylases [8,9], which regulate gene expression by modifying chromatin structure (Fig. 1C). Fourth, HIF-1 can activate the transcription of genes encoding microRNAs [10], which bind to specific mRNA molecules and either block their translation or mediate their degradation (Fig. 1D). Fifth, the isolated HIF-1α subunit can bind to other transcription factors [11,12] and inhibit (Fig. 1E) or potentiate (Fig. 1F) their activity.

Mechanisms by which HIF-1 regulates gene expression. nihms232046f1

Mechanisms by which HIF-1 regulates gene expression. nihms232046f1

Mechanisms by which HIF-1 regulates gene expression.

Fig. 1 Mechanisms by which HIF-1 regulates gene expression. (A) Top: HIF-1 binds directly to target genes at a cis-acting hypoxia response element (HRE) and recruits coactivator proteins such as p300 to increase gene transcription.

HIF-1α and HIF-1β are present in all metazoan species, including the simple roundworm Caenorhabitis elegans [13], which consists of ~103 cells and has no specialized systems for O2 delivery. The fruit flyDrosophila melanogaster evolved tracheal tubes, which conduct air into the interior of the body from which it diffuses to surrounding cells. In vertebrates, the development of the circulatory and respiratory systems was accompanied by the appearance of HIF-2α, which is also O2-regulated and heterodimerizes with HIF-1β [14] but is only expressed in a restricted number of cell types [15], whereas HIF-1α and HIF-1β are expressed in all human and mouse tissues [16]. In Drosophila, the ubiquitiously expressed HIF-1α ortholog is designatedSimilar [17] and the paralogous gene that is expressed specifically in tracheal tubes is designated Trachealess[18].

HIF-1 Activity is Regulated by Oxygen

In the presence of O2, HIF-1α and HIF-2α are subjected to hydroxylation by prolyl-4-hydroxylase domain proteins (PHDs) that use O2 and α-ketoglutarate as substrates and generate CO2 and succinate as by-products [19]. Prolyl hydroxylation is required for binding of the von Hipple-Lindau protein, which recruits a ubiquitin-protein ligase that targets HIF-1α and HIF-2α for proteasomal degradation (Fig. 2). Under hypoxic conditions, the rate of hydroxylation declines and the non-hydroxylated proteins accumulate. HIF-1α transactivation domain function is also O2-regulated [20,21]. Factor inhibiting HIF-1 (FIH-1) represses transactivation domain function [22] by hydroxylating asparagine residue 803 in HIF-1α, thereby blocking the binding of the co-activators p300 and CBP [23].

Negative regulation of HIF-1 activity by oxygen nihms232046f2

Negative regulation of HIF-1 activity by oxygen nihms232046f2

Negative regulation of HIF-1 activity by oxygen

Fig. 2 Negative regulation of HIF-1 activity by oxygen. Top: In the presence of O2: prolyl hydroxylation of HIF-1a leads to binding of the von Hippel-Lindau protein (VHL), which recruits a ubiquitin protein-ligase that targets HIF-1a for proteasomal degradation;

When cells are acutely exposed to hypoxic conditions, the generation of ROS at complex III of the mitochondrial electron transport chain (ETC) increases and is required for the induction of HIF-1α protein levels [24]. More than a decade after these observations were first made, the precise mechanism by which hypoxia increases ROS generation and by which ROS induces HIF-1α accumulation remain unknown. However, the prolyl and asparaginyl hydroxylases contain Fe2+ in their active site and oxidation to Fe3+would block their catalytic activity. Since O2 is a substrate for the hydroxylation reaction, anoxia also results in a loss of enzyme activity. However, the concentration at which O2 becomes limiting for prolyl or asparaginyl hydroxylase activity in vivo is not known.

HIF-1 Regulates the Balance Between Oxidative and Glycolytic Metabolism

All metazoan organisms depend on mitochondrial respiration as the primary mechanism for generating sufficient amounts of ATP to maintain cellular and systemic homeostasis. Respiration, in turn, is dependent on an adequate supply of O2 to serve as the final electron acceptor in the ETC. In this process, electrons are transferred from complex I (or complex II) to complex III, then to complex IV, and finally to O2, which is reduced to water. This orderly transfer of electrons generates a proton gradient across the inner mitochondrial membrane that is used to drive the synthesis of ATP. At each step of this process, some electrons combine with O2 prematurely, resulting in the production of superoxide anion, which is reduced to hydrogen peroxide through the activity of mitochondrial superoxide dismutase. The efficiency of electron transport appears to be optimized to the physiological range of O2 concentrations, such that ATP is produced without the production of excess superoxide, hydrogen peroxide, and other ROS at levels that would result in the increased oxidation of cellular macromolecules and subsequent cellular dysfunction or death. In contrast, when O2levels are acutely increased or decreased, an imbalance between O2 and electron flow occurs, which results in increased ROS production.

MEFs require HIF-1 activity to make two critical metabolic adaptations to chronic hypoxia. First, HIF-1 activates the gene encoding pyruvate dehydrogenase (PDH) kinase 1 (PDK1), which phosphorylates and inactivates the catalytic subunit of PDH, the enzyme that converts pyruvate to acetyl coenzyme A (AcCoA) for entry into the mitochondrial tricarboxylic acid (TCA) cycle [25]. Second, HIF-1 activates the gene encoding BNIP3, a member of the Bcl-2 family of mitochondrial proteins, which triggers selective mitochondrial autophagy [26]. Interference with the induction of either of these proteins in hypoxic cells results in increased ROS production and increased cell death. Overexpression of either PDK1 or BNIP3 rescues HIF-1α-null MEFs. By shunting pyruvate away from the mitochondria, PDK1 decreases flux through the ETC and thereby counteracts the reduced efficiency of electron transport under hypoxic conditions, which would otherwise increase ROS production. PDK1 functions cooperatively with the product of another HIF-1 target gene, LDHA [27], which converts pyruvate to lactate, thereby further reducing available substrate for the PDH reaction.

PDK1 effectively reduces flux through the TCA cycle and thereby reduces flux through the ETC in cells that primarily utilize glucose as a substrate for oxidative phosphorylation. However, PDK1 is predicted to have little effect on ROS generation in cells that utilize fatty acid oxidation as their source of AcCoA. Hence another strategy to reduce ROS generation under hypoxic conditions is selective mitochondrial autophagy [26]. MEFs reduce their mitochondrial mass and O2 consumption by >50% after only two days at 1% O2. BNIP3 competes with Beclin-1 for binding to Bcl-2, thereby freeing Beclin-1 to activate autophagy. Using short hairpin RNAs to knockdown expression of BNIP3, Beclin-1, or Atg5 (another component of the autophagy machinery) phenocopied HIF-1α-null cells by preventing hypoxia-induced reductions in mitochondrial mass and O2 consumption as a result of failure to induce autophagy [26]. HIF-1-regulated expression of BNIP3L also contributes to hypoxia-induced autophagy [28]. Remarkably, mice heterozygous for the HIF-1α KO allele have a significantly increased ratio of mitochondrial:nuclear DNA in their lungs (even though this is the organ that is exposed to the highest O2 concentrations), indicating that HIF-1 regulates mitochondrial mass under physiological conditions in vivo [26]. In contrast to the selective mitochondrial autophagy that is induced in response to hypoxia as described above, autophagy (of unspecified cellular components) induced by anoxia does not require HIF-1, BNIP3, or BNIP3L, but is instead regulated by AMP kinase [29].

The multiplicity of HIF-1-mediated mechanisms identified so far by which cells regulate mitochondrial metabolism in response to changes in cellular O2 concentration (Fig. 3) suggests that this is a critical adaptive response to hypoxia. The fundamental nature of this physiological response is underscored by the fact that yeast also switch COX4 subunits in an O2-dependent manner but do so by an entirely different molecular mechanism [33], since yeast do not have a HIF-1α homologue. Thus, it appears that by convergent evolution both unicellular and multicellular eukaryotes possess mechanisms by which they modulate mitochondrial metabolism to maintain redox homeostasis despite changes in O2 availability. Indeed, it is the balance between energy, oxygen, and redox homeostasis that represents the key to life with oxygen.

Regulation of mitochondrial metabolism by HIF-1  nihms232046f3

Regulation of mitochondrial metabolism by HIF-1 nihms232046f3

Regulation of mitochondrial metabolism by HIF-1α

Fig. 3 Regulation of mitochondrial metabolism by HIF-1α. Acute hypoxia leads to increased mitochondrial generation of reactive oxygen species (ROS). Decreased O2 and increased ROS levels lead to decreased HIF-1α hydroxylation (see Fig. 2) and increased HIF-1-dependent 


7.9.5 Regulation of cancer cell metabolism by hypoxia-inducible factor 1

Semenza GL1.
Semin Cancer Biol. 2009 Feb; 19(1):12-6.

The Warburg Effect: The Re-discovery of the Importance of Aerobic Glycolysis in Tumor Cells

The induction of hypoxia-inducible factor 1 (HIF-1) activity, either as a result of intratumoral hypoxia or loss-of-function mutations in the VHL gene, leads to a dramatic reprogramming of cancer cell metabolism involving increased glucose transport into the cell, increased conversion of glucose to pyruvate, and a concomitant decrease in mitochondrial metabolism and mitochondrial mass. Blocking these adaptive metabolic responses to hypoxia leads to cell death due to toxic levels of reactive oxygen species. Targeting HIF-1 or metabolic enzymes encoded by HIF-1 target genes may represent a novel therapeutic approach to cancer.

7.9.6 Coming up for air. HIF-1 and mitochondrial oxygen consumption

Simon MC1.
Cell Metab. 2006 Mar;3(3):150-1.

Hypoxic cells induce glycolytic enzymes; this HIF-1-mediated metabolic adaptation increases glucose flux to pyruvate and produces glycolytic ATP. Two papers in this issue of Cell Metabolism (Kim et al., 2006; Papandreou et al., 2006) demonstrate that HIF-1 also influences mitochondrial function, suppressing both the TCA cycle and respiration by inducing pyruvate dehydrogenase kinase 1 (PDK1). PDK1 regulation in hypoxic cells promotes cell survival.

Comment on

Oxygen deprivation (hypoxia) occurs in tissues when O2 supply via the cardiovascular system fails to meet the demand of O2-consuming cells. Hypoxia occurs naturally in physiological settings (e.g., embryonic development and exercising muscle), as well as in pathophysiological conditions (e.g., myocardial infarction, inflammation, and solid tumor formation). For over a century, it has been appreciated that O2-deprived cells exhibit increased conversion of glucose to lactate (the “Pasteur effect”). Activation of the Pasteur effect during hypoxia in mammalian cells is facilitated by HIF-1, which mediates the upregulation of glycolytic enzymes that support an increase in glycolytic ATP production as mitochondria become starved for O2, the substrate for oxidative phosphorylation (Seagroves et al., 2001). Thus, mitochondrial respiration passively decreases due to O2 depletion in hypoxic tissues. However, reports by Kim et al. (2006) and Papandreou et al. (2006) in this issue of Cell Metabolism demonstrate that this critical metabolic adaptation is more complex and includes an active suppression of mitochondrial pyruvate catabolism and O2consumption by HIF-1.

Mitochondrial oxidative phosphorylation is regulated by multiple mechanisms, including substrate availability. Major substrates include O2 (the terminal electron acceptor) and pyruvate (the primary carbon source). Pyruvate, as the end product of glycolysis, is converted to acetyl-CoA by the pyruvate dehydrogenase enzymatic complex and enters the tricarboxylic acid (TCA) cycle. Pyruvate conversion into acetyl-CoA is irreversible; this therefore represents an important regulatory point in cellular energy metabolism. Pyruvate dehydrogenase kinase (PDK) inhibits pyruvate dehydrogenase activity by phosphorylating its E1 subunit (Sugden and Holness, 2003). In the manuscripts by Kim et al. (2006) and Papandreou et al. (2006), the authors find that PDK1 is a HIF-1 target gene that actively regulates mitochondrial respiration by limiting pyruvate entry into the TCA cycle. By excluding pyruvate from mitochondrial metabolism, hypoxic cells accumulate pyruvate, which is then converted into lactate via lactate dehydrogenase (LDH), another HIF-1-regulated enzyme. Lactate in turn is released into the extracellular space, regenerating NAD+ for continued glycolysis by O2-starved cells (see Figure 1). This HIF-1-dependent block to mitochondrial O2 consumption promotes cell survival, especially when O2 deprivation is severe and prolonged.



Figure 1. Multiple hypoxia-induced cellular metabolic changes are regulated by HIF-1

By stimulating the expression of glucose transporters and glycolytic enzymes, HIF-1 promotes glycolysis to generate increased levels of pyruvate. In addition, HIF-1 promotes pyruvate reduction to lactate by activating lactate dehydrogenase (LDH). Pyruvate reduction to lactate regenerates NAD+, which permits continued glycolysis and ATP production by hypoxic cells. Furthermore, HIF-1 induces pyruvate dehydrogenase kinase 1 (PDK1), which inhibits pyruvate dehydrogenase and blocks conversion of pyruvate to acetyl CoA, resulting in decreased flux through the tricarboxylic acid (TCA) cycle. Decreased TCA cycle activity results in attenuation of oxidative phosphorylation and excessive mitochondrial reactive oxygen species (ROS) production. Because hypoxic cells already exhibit increased ROS, which have been shown to promote HIF-1 accumulation, the induction of PDK1 prevents the persistence of potentially harmful ROS levels.

Papandreou et al. demonstrate that hypoxic regulation of PDK has important implications for antitumor therapies. Recent interest has focused on cytotoxins that target hypoxic cells in tumor microenvironments, such as the drug tirapazamine (TPZ). Because intracellular O2 concentrations are decreased by mitochondrial O2 consumption, HIF-1 could protect tumor cells from TPZ-mediated cell death by maintaining intracellular O2 levels. Indeed, Papandreou et al. show that HIF-1-deficient cells grown at 2% O2 exhibit increased sensitivity to TPZ relative to wild-type cells, presumably due to higher rates of mitochondrial O2 consumption. HIF-1 inhibition in hypoxic tumor cells should have multiple therapeutic benefits, but the use of HIF-1 inhibitors in conjunction with other treatments has to be carefully evaluated for the most effective combination and sequence of drug delivery. One result of HIF-1 inhibition would be a relative decrease in intracellular O2 levels, making hypoxic cytotoxins such as TPZ more potent antitumor agents. Because PDK expression has been detected in multiple human tumor samples and appears to be induced by hypoxia (Koukourakis et al., 2005), small molecule inhibitors of HIF-1 combined with TPZ represent an attractive therapeutic approach for future clinical studies.

Hypoxic regulation of PDK1 has other important implications for cell survival during O2 depletion. Because the TCA cycle is coupled to electron transport, Kim et al. suggest that induction of the pyruvate dehydrogenase complex by PDK1 attenuates not only mitochondrial respiration but also the production of mitochondrial reactive oxygen species (ROS) in hypoxic cells. ROS are a byproduct of electron transfer to O2, and cells cultured at 1 to 5% O2 generate increased mitochondrial ROS relative to those cultured at 21% O2 (Chandel et al., 1998 and Guzy et al., 2005). In fact, hypoxia-induced mitochondrial ROS have also been shown to be necessary for the stabilization of HIF-1 in hypoxic cells (Brunelle et al., 2005Guzy et al., 2005 and Mansfield et al., 2005). However, the persistence of ROS could ultimately be lethal to tissues during chronic O2 deprivation, and PDK1 induction by HIF-1 should promote cell viability during long-term hypoxia. Kim et al. present evidence that HIF-1-deficient cells exhibit increased apoptosis after 72 hr of culture at 0.5% O2 compared to wild-type cells and that cell survival is rescued by enforced expression of exogenous PDK1. Furthermore, PDK1 reduces ROS production by the HIF-1 null cells. These findings support a novel prosurvival dimension of cellular hypoxic adaptation where PDK1 inhibits the TCA cycle, mitochondrial respiration, and chronic ROS production.

The HIF-1-mediated block to mitochondrial O2 consumption via PDK1 regulation also has implications for O2-sensing pathways by hypoxic cells. One school of thought suggests that perturbing mitochondrial O2consumption increases intracellular O2 concentrations and suppresses HIF-1 induction by promoting the activity of HIF prolyl hydroxylases, the O2-dependent enzymes that regulate HIF-1 stability (Hagen et al., 2003 and Doege et al., 2005). This model suggests that mitochondria function as “O2 sinks.” Although Papandreou et al. demonstrate that increased mitochondrial respiration due to PDK1 depletion results in decreased intracellular O2 levels (based on pimonidazole staining), these changes failed to reduce HIF-1 levels in hypoxic cells. Another model for hypoxic activation of HIF-1 describes a critical role for mitochondrial ROS in prolyl hydroxylase inhibition and HIF-1 stabilization in O2-starved cells (Brunelle et al., 2005Guzy et al., 2005 and Mansfield et al., 2005) (see Figure 1). The mitochondrial “O2 sink” hypothesis can account for some observations in the literature but fails to explain the inhibition of HIF-1 stabilization by ROS scavengers (Chandel et al., 1998Brunelle et al., 2005Guzy et al., 2005 and Sanjuán-Pla et al., 2005). While the relationship between HIF-1 stability, mitochondrial metabolism, ROS, and intracellular O2 redistribution will continue to be debated for some time, these most recent findings shed new light on findings by Louis Pasteur over a century ago.

Selected reading

Brunelle et al., 2005

J.K. Brunelle, E.L. Bell, N.M. Quesada, K. Vercauteren, V. Tiranti, M. Zeviani, R.C. Scarpulla, N.S. Chandel

Cell Metab., 1 (2005), pp. 409–414

Article  PDF (324 K) View Record in Scopus Citing articles (357)

Chandel et al., 1998

N.S. Chandel, E. Maltepe, E. Goldwasser, C.E. Mathieu, M.C. Simon, P.T. Schumacker

Proc. Natl. Acad. Sci. USA, 95 (1998), pp. 11715–11720

View Record in Scopus Full Text via CrossRef Citing articles (973)

Doege et al., 2005Doege, S. Heine, I. Jensen, W. Jelkmann, E. Metzen

Blood, 106 (2005), pp. 2311–2317

View Record in Scopus Full Text via CrossRef Citing articles (84)

Guzy et al., 2005

R.D. Guzy, B. Hoyos, E. Robin, H. Chen, L. Liu, K.D. Mansfield, M.C. Simon, U. Hammerling, P.T. Schumacker

Cell Metab., 1 (2005), pp. 401–408

Article  PDF (510 K) View Record in Scopus Citing articles (593)

Hagen et al., 2003

Hagen, C.T. Taylor, F. Lam, S. Moncada

Science, 302 (2003), pp. 1975–1978

View Record in Scopus Full Text via CrossRef Citing articles (450)

7.9.7 HIF-1 mediates adaptation to hypoxia by actively downregulating mitochondrial oxygen consumption

Papandreou I1Cairns RAFontana LLim ALDenko NC.
Cell Metab. 2006 Mar; 3(3):187-97.

The HIF-1 transcription factor drives hypoxic gene expression changes that are thought to be adaptive for cells exposed to a reduced-oxygen environment. For example, HIF-1 induces the expression of glycolytic genes. It is presumed that increased glycolysis is necessary to produce energy when low oxygen will not support oxidative phosphorylation at the mitochondria. However, we find that while HIF-1 stimulates glycolysis, it also actively represses mitochondrial function and oxygen consumption by inducing pyruvate dehydrogenase kinase 1 (PDK1). PDK1 phosphorylates and inhibits pyruvate dehydrogenase from using pyruvate to fuel the mitochondrial TCA cycle. This causes a drop in mitochondrial oxygen consumption and results in a relative increase in intracellular oxygen tension. We show by genetic means that HIF-1-dependent block to oxygen utilization results in increased oxygen availability, decreased cell death when total oxygen is limiting, and reduced cell death in response to the hypoxic cytotoxin tirapazamine.

Comment in

Tissue hypoxia results when supply of oxygen from the bloodstream does not meet demand from the cells in the tissue. Such a supply-demand mismatch can occur in physiologic conditions such as the exercising muscle, in the pathologic condition such as the ischemic heart, or in the tumor microenvironment (Hockel and Vaupel, 2001 and Semenza, 2004). In either the physiologic circumstance or pathologic conditions, there is a molecular response from the cell in which a program of gene expression changes is initiated by the hypoxia-inducible factor-1 (HIF-1) transcription factor. This program of gene expression changes is thought to help the cells adapt to the stressful environment. For example, HIF-1-dependent expression of erythropoietin and angiogenic compounds results in increased blood vessel formation for delivery of a richer supply of oxygenated blood to the hypoxic tissue. Additionally, HIF-1 induction of glycolytic enzymes allows for production of energy when the mitochondria are starved of oxygen as a substrate for oxidative phosphorylation. We now find that this metabolic adaptation is more complex, with HIF-1 not only regulating the supply of oxygen from the bloodstream, but also actively regulating the oxygen demand of the tissue by reducing the activity of the major cellular consumer of oxygen, the mitochondria.

Perhaps the best-studied example of chronic hypoxia is the hypoxia associated with the tumor microenvironment (Brown and Giaccia, 1998). The tumor suffers from poor oxygen supply through a chaotic jumble of blood vessels that are unable to adequately perfuse the tumor cells. The oxygen tension within the tumor is also a function of the demand within the tissue, with oxygen consumption influencing the extent of tumor hypoxia (Gulledge and Dewhirst, 1996 and Papandreou et al., 2005b). The net result is that a large fraction of the tumor cells are hypoxic. Oxygen tensions within the tumor range from near normal at the capillary wall, to near zero in the perinecrotic regions. This perfusion-limited hypoxia is a potent microenvironmental stress during tumor evolution (Graeber et al., 1996 and Hockel and Vaupel, 2001) and an important variable capable of predicting for poor patient outcome. (Brizel et al., 1996Cairns and Hill, 2004Hockel et al., 1996 and Nordsmark and Overgaard, 2004).

The HIF-1 transcription factor was first identified based on its ability to activate the erythropoetin gene in response to hypoxia (Wang and Semenza, 1993). Since then, it is has been shown to be activated by hypoxia in many cells and tissues, where it can induce hypoxia-responsive target genes such as VEGF and Glut1 (Airley et al., 2001 and Kimura et al., 2004). The connection between HIF-regulation and human cancer was directly linked when it was discovered that the VHL tumor suppressor gene was part of the molecular complex responsible for the oxic degradation of HIF-1α (Maxwell et al., 1999). In normoxia, a family of prolyl hydroxylase enzymes uses molecular oxygen as a substrate and modifies HIF-1α and HIF2α by hydroxylation of prolines 564 and 402 (Bruick and McKnight, 2001 and Epstein et al., 2001). VHL then recognizes the modified HIF-α proteins, acts as an E3-type of ubiquitin ligase, and along with elongins B and C is responsible for the polyubiquitination of HIF-αs and their proteosomal degradation (Bruick and McKnight, 2001Chan et al., 2002Ivan et al., 2001 and Jaakkola et al., 2001). Mutations in VHL lead to constitutive HIF-1 gene expression, and predispose humans to cancer. The ability to recognize modified HIF-αs is at least partly responsible for VHL activity as a tumor suppressor, as introduction of nondegradable HIF-2α is capable of overcoming the growth–inhibitory activity of wild-type (wt) VHL in renal cancer cells (Kondo et al., 2003).

Mitochondrial function can be regulated by PDK1 expression. Mitochondrial oxidative phosphorylation (OXPHOS) is regulated by several mechanisms, including substrate availability (Brown, 1992). The major substrates for OXPHOS are oxygen, which is the terminal electron acceptor, and pyruvate, which is the primary carbon source. Pyruvate is the end product of glycolysis and is converted to acetyl-CoA through the activity of the pyruvate dehydrogenase complex of enzymes. The acetyl-CoA then directly enters the TCA cycle at citrate synthase where it is combined with oxaloacetate to generate citrate. In metazoans, the conversion of pyruvate to acetyl-CoA is irreversible and therefore represents a critical regulatory point in cellular energy metabolism. Pyruvate dehydrogenase is regulated by three known mechanisms: it is inhibited by acetyl-CoA and NADH, it is stimulated by reduced energy in the cell, and it is inhibited by regulatory phosphorylation of its E1 subunit by pyruvate dehydrogenase kinase (PDK) (Holness and Sugden, 2003 and Sugden and Holness, 2003). There are four members of the PDK family in vertebrates, each with specific tissue distributions (Roche et al., 2001). PDK expression has been observed in human tumor biopsies (Koukourakis et al., 2005), and we have reported that PDK3 is hypoxia-inducible in some cell types (Denko et al., 2003). In this manuscript, we find that PDK1 is also a hypoxia-responsive protein that actively regulates the function of the mitochondria under hypoxic conditions by reducing pyruvate entry into the TCA cycle. By excluding pyruvate from mitochondrial consumption, PDK1 induction may increase the conversion of pyruvate to lactate, which is in turn shunted to the extracellular space, regenerating NAD for continued glycolysis.

Identification of HIF-dependent mitochondrial proteins through genomic and bioinformatics approaches

In order to help elucidate the role of HIF-1α in regulating metabolism, we undertook a genomic search for genes that were regulated by HIF-1 in tumor cells exposed to hypoxia in vitro. We used genetically matched human RCC4 cells that had lost VHL during tumorigenesis and displayed constitutive HIF-1 activity, and a cell line engineered to re-express VHL to establish hypoxia-dependent HIF activation. These cells were treated with 18 hr of stringent hypoxia (<0.01% oxygen), and microarray analysis performed. Using a strict 2.5-fold elevation as our cutoff, we identified 173 genes that were regulated by hypoxia and/or VHL status (Table S1 in the Supplemental Data available with this article online). We used the pattern of expression in these experiments to identify putative HIF-regulated genes—ones that were constitutively elevated in the parent RCC4s independent of hypoxia, downregulated in the RCC4VHL cells under normoxia, and elevated in response to hypoxia. Of the 173 hypoxia and VHL-regulated genes, 74 fit the putative HIF-1 target pattern. The open reading frames of these genes were run through a pair of bioinformatics engines in order to predict subcellular localization, and 10 proteins scored as mitochondrial on at least one engine. The genes, fold induction, and mitochondrial scores are listed in Table 1.

HIF-1 downregulates mitochondrial oxygen consumption

Having identified several putative HIF-1 responsive gene products that had the potential to regulate mitochondrial function, we then directly measured mitochondrial oxygen consumption in cells exposed to long-term hypoxia. While other groups have studied mitochondrial function under acute hypoxia (Chandel et al., 1997), this is one of the first descriptions of mitochondrial function after long-term hypoxia where there have been extensive hypoxia-induced gene expression changes. Figure 1A is an example of the primary oxygen trace from a Clark electrode showing a drop in oxygen concentration in cell suspensions of primary fibroblasts taken from normoxic and hypoxic cultures. The slope of the curve is a direct measure of the total cellular oxygen consumption rate. Exposure of either primary human or immortalized mouse fibroblasts to 24 hr of hypoxia resulted in a reduction of this rate by approximately 50% (Figures 1A and 1B). In these experiments, the oxygen consumption can be stimulated with the mitochondrial uncoupling agent CCCP (carbonyl cyanide 3-chloro phenylhydrazone) and was completely inhibited by 2 mM potassium cyanide. We determined that the change in total cellular oxygen consumption was due to changes in mitochondrial activity by the use of the cell-permeable poison of mitochondrial complex 3, Antimycin A. Figure 1C shows that the difference in the normoxic and hypoxic oxygen consumption in murine fibroblasts is entirely due to the Antimycin-sensitive mitochondrial consumption. The kinetics with which mitochondrial function slows in hypoxic tumor cells also suggests that it is due to gene expression changes because it takes over 6 hr to achieve maximal reduction, and the reversal of this repression requires at least another 6 hr of reoxygenation (Figure 1D). These effects are not likely due to proliferation or toxicity of the treatments as these conditions are not growth inhibitory or toxic to the cells (Papandreou et al., 2005a).

Since we had predicted from the gene expression data that the mitochondrial oxygen consumption changes were due to HIF-1-mediated expression changes, we tested several genetically matched systems to determine what role HIF-1 played in the process (Figure 2). We first tested the cell lines that had been used for microarray analysis and found that the parental RCC4 cells had reduced mitochondrial oxygen consumption when compared to the VHL-reintroduced cells. Oxygen consumption in the parental cells was insensitive to hypoxia, while it was reduced by hypoxia in the wild-type VHL-transfected cell lines. Interestingly, stable introduction of a tumor-derived mutant VHL (Y98H) that cannot degrade HIF was also unable to restore oxygen consumption. These results indicate that increased expression of HIF-1 is sufficient to reduce oxygen consumption (Figure 2A). We also investigated whether HIF-1 induction was required for the observed reduction in oxygen consumption in hypoxia using two genetically matched systems. We measured normoxic and hypoxic oxygen consumption in murine fibroblasts derived from wild-type or HIF-1α null embryos (Figure 2B) and from human RKO tumor cells and RKO cells constitutively expressing ShRNAs directed against the HIF-1α gene (Figures 2C and 4C). Neither of the HIF-deficient cell systems was able to reduce oxygen consumption in response to hypoxia. These data from the HIF-overexpressing RCC cells and the HIF-deficient cells indicate that HIF-1 is both necessary and sufficient for reducing mitochondrial oxygen consumption in hypoxia.

HIF-dependent mitochondrial changes are functional, not structural

Because addition of CCCP could increase oxygen consumption even in the hypoxia-treated cells, we hypothesized that the hypoxic inhibition was a regulated activity, not a structural change in the mitochondria in response to hypoxic stress. We confirmed this interpretation by examining several additional mitochondrial characteristics in hypoxic cells such as mitochondrial morphology, quantity, and membrane potential. We examined morphology by visual inspection of both the transiently transfected mitochondrially localized DsRed protein and the endogenous mitochondrial protein cytochrome C. Both markers were indistinguishable in the parental RCC4 and the RCC4VHL cells (Figure 3A). Likewise, we measured the mitochondrial membrane potential with the functional dye rhodamine 123 and found that it was identical in the matched RCC4 cells and the matched HIF wt and knockout (KO) cells when cultured in normoxia or hypoxia (Figure 3B). Finally, we determined that the quantity of mitochondria per cell was not altered in response to HIF or hypoxia by showing that the amount of the mitochondrial marker protein HSP60 was identical in the RCC4 and HIF cell lines (Figure 3C)

PDK1 is a HIF-1 inducible target protein

After examination of the list of putative HIF-regulated mitochondrial target genes, we hypothesized that PDK1 could mediate the functional changes that we observed in hypoxia. We therefore investigated PDK1 protein expression in response to HIF and hypoxia in the genetically matched cell systems. Figure 4A shows that in the RCC4 cells PDK1 and the HIF-target gene BNip3 (Greijer et al., 2005 and Papandreou et al., 2005a) were both induced by hypoxia in a VHL-dependent manner, with the expression of PDK1 inversely matching the oxygen consumption measured in Figure 1 above. Likewise, the HIF wt MEFs show oxygen-dependent induction of PDK1 and BNip3, while the HIF KO MEFs did not show any expression of either of these proteins under any oxygen conditions (Figure 4B). Finally, the parental RKO cells were able to induce PDK1 and the HIF target gene BNip3L in response to hypoxia, while the HIF-depleted ShRNA RKO cells could not induce either protein (Figure 4C). Therefore, in all three cell types, the HIF-1-dependent regulation of oxygen consumption seen in Figure 2, corresponds to the HIF-1-dependent induction of PDK1 seen in Figure 4.

In order to determine if PDK1 was a direct HIF-1 target gene, we analyzed the genomic sequence flanking the 5′ end of the gene for possible HIF-1 binding sites based on the consensus core HRE element (A/G)CGTG (Caro, 2001). Several such sites exist within the first 400 bases upstream, so we generated reporter constructs by fusing the genomic sequence from −400 to +30 of the start site of transcription to the firefly luciferase gene. In transfection experiments, the chimeric construct showed significant induction by either cotransfection with a constitutively active HIF proline mutant (P402A/P564G) (Chan et al., 2002) or exposure of the transfected cells to 0.5% oxygen (Figure 4D). Most noteworthy, when the reporter gene was transfected into the HIF-1α null cells, it did not show induction when the cells were cultured in hypoxia, but it did show induction when cotransfected with expression HIF-1α plasmid. We then generated deletions down to the first 36 bases upstream of transcription and found that even this short sequence was responsive to HIF-1 (Figure 4D). Analysis of this small fragment showed only one consensus HRE site located in an inverted orientation in the 5′ untranslated region. We synthesized and cloned a mutant promoter fragment in which the core element ACGTG was replaced with AAAAG, and this construct lost over 90% of its hypoxic induction. These experiments suggest that it is this HRE within the proximal 5′ UTR that HIF-1 uses to transactivate the endogenous PDK1 gene in response to hypoxia.

PDK1 is responsible for the HIF-dependent mitochondrial oxygen consumption changes

In order to directly test if PDK1 was the HIF-1 target gene responsible for the hypoxic reduction in mitochondrial oxygen consumption, we generated RKO cell lines with either knockdown or overexpression of PDK1 and measured the oxygen consumption in these derivatives. The PDK1 ShRNA stable knockdown line was generated as a pool of clones cotransfected with pSUPER ShPDK1 and pTK-hygro resistance gene. After selection for growth in hygromycin, the cells were tested by Western blot for the level of PDK1 protein expression. We found that normoxic PDK1 is reduced by 75%, however, there was measurable expression of PDK1 in these cells in response to hypoxia (Figure 5A). When we measured the corresponding oxygen consumption in these cells, we found a change commensurate with the level of PDK1. The knockdown cells show elevated baseline oxygen consumption, and partial reduction in this activity in response to hypoxia. Therefore, reduction of PDK1 expression by genetic means increased mitochondrial oxygen consumption in both normoxic and hypoxic conditions. Interestingly, these cells still induced HIF-1α (Figure 5A) and HIF-1 target genes such as BNip3L in response to hypoxia (data not shown), suggesting that altered PDK1 levels do not alter HIF-1α function.



PDK1 expression directly regulates cellular oxygen consumption rate

Figure 5. PDK1 expression directly regulates cellular oxygen consumption rate

  1. A)Western blot of RKO cell and ShRNAPDK1RKO cell lysates after exposure to 24 hr of normoxia or 0.5% O2. Blots were probed for HIF 1α, PDK1, and tubulin as a loading control.
  2. B)Oxygen consumption rate in RKO and ShRNAPDK1RKO cells after exposure to 24 hr of normoxia or 0.5% O2.
  3. C)Western blot of RKOiresGUS cell and RKOiresPDK1 cell lysates after exposure to 24 hr of normoxia or 0.5% O2. Blots were probed for HIF 1α, PDK1, and tubulin as a loading control.
  4. D)Oxygen consumption rate in RKOiresGUS and RKOiresPDK1 cells after exposure to 24 hr of normoxia or 0.5% O2.
  5. E)Model describing the interconnected effects of HIF-1 target gene activation on hypoxic cell metabolism. Reduced oxygen conditions causes HIF-1 to coordinately induce the enzymes shown in boxes. HIF-1 activation results in increased glucose transporter expression to increase intracellular glucose flux, induction of glycolytic enzymes increases the conversion of glucose to pyruvate generating energy and NADH, induction of PDK1 decreases mitochondrial utilization of pyruvate and oxygen, and induction of LDH increases the removal of excess pyruvate as lactate and also regenerates NAD+ for increased glycolysis.

For all graphs, the error bars represent the standard error of the mean.

We also determined if overexpression of PDK1 could lead to reduced mitochondrial oxygen consumption. A separate culture of RKO cells was transfected with a PDK1-IRES-puro expression plasmid and selected for resistance to puromycin. The pool of puromycin resistant cells was tested for PDK1 expression by Western blot. These cells showed a modest increase in PDK1 expression under control conditions when compared to the cells transfected with GUS-IRES-puro, with an additional increase in PDK1 protein in response to hypoxia (Figure 5C). The corresponding oxygen consumption measurements showed that the mitochondria is very sensitive to changes in the levels of PDK1, as even this slight increase was able to significantly reduce oxygen consumption in the normoxic PDK1-puro cultures. Further increase in PDK1 levels with hypoxia further reduced oxygen consumption in both cultures (Figure 5D). The model describing the relationship between hypoxia, HIF-1, PDK1, and intermediate metabolism is described inFigure 5E.

Altering oxygen consumption alters intracellular oxygen tension and sensitivity to hypoxia-dependent cell killing

The intracellular concentration of oxygen is a net result of the rate at which oxygen diffuses into the cell and the rate at which it is consumed. We hypothesized that the rate at which oxygen was consumed within the cell would significantly affect its steady-state intracellular concentrations. We tested this hypothesis in vitro using the hypoxic marker drug pimonidazole (Bennewith and Durand, 2004). We plated high density cultures of HIF wild-type and HIF knockout cells and placed these cultures in normoxic, 2% oxygen, and anoxic incubators for overnight treatment. The overnight treatment gives the cells time to adapt to the hypoxic conditions and establish altered oxygen consumption profiles. Pimonidozole was then added for the last 4 hr of the growth of the culture. Pimonidazole binding was detected after fixation of the cells using an FITC labeled anti-pimonidazole antibody and it was quantitated by flow cytometry. The quantity of the bound drug is a direct indication of the oxygen concentration within the cell (Bennewith and Durand, 2004). The histograms in Figure 6A show that the HIF-1 knockout and wild-type cells show similar staining in the cells grown in 0% oxygen. However, the cells treated with 2% oxygen show the consequence of the genetic removal of HIF-1. The HIF-proficient cells showed relatively less pimonidazole binding at 2% when compared to the 0% culture, while the HIF-deficient cells showed identical binding between the cells at 2% and those at 0%. We interpret these results to mean that the HIF-deficient cells have greater oxygen consumption, and this has lowered the intracellular oxygenation from the ambient 2% to close to zero intracellularly. The HIF-proficient cells reduced their oxygen consumption rate so that the rate of diffusion into the cell is greater than the rate of consumption.

Figure 6. HIF-dependent decrease in oxygen consumption raises intracellular oxygen concentration, protects when oxygen is limiting, and decreases sensitivity to tirapazamine in vitro

  1. A)Pimonidazole was used to determine the intracellular oxygen concentration of cells in culture. HIF wt and HIF KO MEFs were grown at high density and exposed to 2% O2or anoxia for 24 hr in glass dishes. For the last 4 hr of treatment, cells were exposed to 60 μg/ml pimonidazole. Pimonidazole binding was quantitated by flow cytometry after binding of an FITC conjugated anti-pimo mAb. Results are representative of two independent experiments.
  2. B)HIF1α reduces oxygen consumption and protects cells when total oxygen is limited. HIF wt and HIF KO cells were plated at high density and sealed in aluminum jigs at <0.02% oxygen. At the indicated times, cells were harvested, and dead cells were quantitated by trypan blue exclusion. Note both cell lines are equally sensitive to anoxia-induced apoptosis, so the death of the HIF null cells indicates that the increased oxygen consumption removed any residual oxygen in the jig and resulted in anoxia-induced death.
  3. C)PDK1 is responsible for HIF-1’s adaptive response when oxygen is limiting. A similar jig experiment was performed to measure survival in the parental RKO, the RKO ShRNAHIF1α, and the RKOShPDK1 cells. Cell death by trypan blue uptake was measured 48 hr after the jigs were sealed.
  4. D)HIF status alters sensitivity to TPZ in vitro. HIF wt and HIF KO MEFs were grown at high density in glass dishes and exposed to 21%, 2%, and <0.01% O2conditions for 18 hr in the presence of varying concentrations of Tirapazamine. After exposure, cells were harvested and replated under normoxia to determine clonogenic viability. Survival is calculated relative to the plating efficiency of cells exposed to 0 μM TPZ for each oxygen concentration.
  5. E)Cell density alters sensitivity to TPZ. HIF wt and HIF KO MEFs were grown at varying cell densities in glass dishes and exposed to 2% O2in the presence of 10 μM TPZ for 18 hr. After the exposure, survival was determined as described in (C).

For all graphs, the error bars represent the standard error of the mean.

HIF-induced PDK1 can reduce the total amount of oxygen consumed per cell. The reduction in the amount of oxygen consumed could be significant if there is a finite amount of oxygen available, as would be the case in the hours following a blood vessel occlusion. The tissue that is fed by the vessel would benefit from being economical with the oxygen that is present. We experimentally modeled such an event using aluminum jigs that could be sealed with defined amounts of cells and oxygen present (Siim et al., 1996). We placed 10 × 106 wild-type or HIF null cells in the sealed jig at 0.02% oxygen, waited for the cells to consume the remaining oxygen, and measured cell viability. We have previously shown that these two cell types are resistant to mild hypoxia and equally sensitive to anoxia-induced apoptosis (Papandreou et al., 2005a). Therefore, any death in this experiment would be the result of the cells consuming the small amount of remaining oxygen and dying in response to anoxia. We found that in sealed jigs, the wild-type cells are more able to adapt to the limited oxygen supply by reducing consumption. The HIF null cells continued to consume oxygen, reached anoxic levels, and started to lose viability within 36 hr (Figure 6B). This is a secondary adaptive effect of HIF1. We confirmed that PDK1 was responsible for this difference by performing a similar experiment using the parental RKO cells, the RKOShRNAHIF1α and the RKOShRNAPDK1 cells. We found similar results in which both the cells with HIF1α knockdown and PDK1 knockdown were sensitive to the long-term effects of being sealed in a jig with a defined amount of oxygen (Figure 6c). Note that the RKOShPDK1 cells are even more sensitive than the RKOShHIF1α cells, presumably because they have higher basal oxygen consumption rates (Figure 5B).

Because HIF-1 can help cells adapt to hypoxia and maintain some intracellular oxygen level, it may also protect tumor cells from killing by the hypoxic cytotoxin tirapazamine (TPZ). TPZ toxicity is very oxygen dependent, especially at oxygen levels between 1%–4% (Koch, 1993). We therefore tested the relative sensitivity of the HIF wt and HIF KO cells to TPZ killing in high density cultures (Figure 6D). We exposed the cells to the indicated concentrations of drug and oxygen concentrations overnight. The cells were then harvested and replated to determine reproductive viability by colony formation. Both cell types were equally resistant to TPZ at 21% oxygen, while both cell types are equally sensitive to TPZ in anoxic conditions where intracellular oxygen levels are equivalent (Figure 6A). The identical sensitivity of both cell types in anoxia indicates that both cell types are equally competent in repairing the TPZ-induced DNA damage that is presumed to be responsible for its toxicity. However, in 2% oxygen cultures, the HIF null cells displayed a significantly greater sensitivity to the drug than the wild-type cells. This suggests that the increased oxygen consumption rate in the HIF-deficient cells is sufficient to lower the intracellular oxygen concentration relative to that in the HIF-proficient cells. The lower oxygen level is significant enough to dramatically sensitize these cells to killing by TPZ.

If the increased sensitivity to TPZ in the HIF ko cells is determined by intracellular oxygen consumption differences, then this effect should also be cell-density dependent. We showed that this is indeed the case in Figure 6E where oxygen and TPZ concentrations were held constant, and increased cell density lead to increased TPZ toxicity. The effect was much more pronounced in the HIF KO cells, although the HIF wt cells showed some increased toxicity in the highest density cultures, consistent with the fact they were still consuming some oxygen, even with HIF present (Figure 1). The in vitro TPZ survival data is therefore consistent with our hypothesis that control of oxygen consumption can regulate intracellular oxygen concentration, and suggests that increased oxygen consumption could sensitize cells to hypoxia-dependent therapy.


The findings presented here show that HIF-1 is actively responsible for regulating energy production in hypoxic cells by an additional, previously unrecognized mechanism. It has been shown that HIF-1 induces the enzymes responsible for glycolysis when it was presumed that low oxygen did not support efficient oxidative phosphorylation (Iyer et al., 1998 and Seagroves et al., 2001). The use of glucose to generate ATP is capable of satisfying the energy requirements of a cell if glucose is in excess (Papandreou et al., 2005a). We now find that at the same time that glycolysis is increasing, mitochondrial respiration is decreasing. However, the decreased respiration is not because there is not enough oxygen present to act as a substrate for oxidative phosphorylation, but because the flow of pyruvate into the TCA cycle has been reduced by the activity of pyruvate dehydrogenase kinase. Other reports have suggested that oxygen utilization is shifted in cells exposed to hypoxia, but these reports have focused on other regulators such as nitric oxide synthase (Hagen et al., 2003). NO can reduce oxygen consumption through direct inhibition of cytochrome oxidase, but this effect seems to be more significant at physiologic oxygen concentrations, not at severe levels seen in the tumor (Palacios-Callender et al., 2004).

7.9.8 HIF-1. upstream and downstream of cancer metabolism

Semenza GL1.
Curr Opin Genet Dev. 2010 Feb; 20(1):51-6

Hypoxia-inducible factor 1 (HIF-1) plays a key role in the reprogramming of cancer metabolism by activating transcription of genes encoding glucose transporters and glycolytic enzymes, which take up glucose and convert it to lactate; pyruvate dehydrogenase kinase 1, which shunts pyruvate away from the mitochondria; and BNIP3, which triggers selective mitochondrial autophagy. The shift from oxidative to glycolytic metabolism allows maintenance of redox homeostasis and cell survival under conditions of prolonged hypoxia. Many metabolic abnormalities in cancer cells increase HIF-1 activity. As a result, a feed-forward mechanism can be activated that drives HIF-1 activation and may promote tumor progression. Hypoxia-inducible factor 1 (HIF-1) plays a key role in the reprogramming of cancer metabolism by activating transcription of genes encoding glucose transporters and glycolytic enzymes, which take up glucose and convert it to lactate; pyruvate dehydrogenase kinase 1, which shunts pyruvate away from the mitochondria; and BNIP3, which triggers selective mitochondrial autophagy. The shift from oxidative to glycolytic metabolism allows maintenance of redox homeostasis and cell survival under conditions of prolonged hypoxia. Many metabolic abnormalities in cancer cells increase HIF-1 activity. As a result, a feed-forward mechanism can be activated that drives HIF-1 activation and may promote tumor progression.

Metastatic cancer is characterized by reprogramming of cellular metabolism leading to increased uptake of glucose for use as both an anabolic and catabolic substrate. Increased glucose uptake is such a reliable feature that it is utilized clinically to detect metastases by positron emission tomography using 18F-fluorodeoxyglucose (FDG-PET) with a sensitivity of ~90% [1]. As with all aspects of cancer biology, the details of metabolic reprogramming differ widely among individual tumors. However, the role of specific signaling pathways and transcription factors in this process is now understood in considerable detail. This review will focus on the involvement of hypoxia-inducible factor 1 (HIF-1) in both mediating metabolic reprogramming and responding to metabolic alterations. The placement of HIF-1 both upstream and downstream of cancer metabolism results in a feed-forward mechanism that may play a major role in the development of the invasive, metastatic, and lethal cancer phenotype.

O2 concentrations are significantly reduced in many human cancers compared to the surrounding normal tissue. The median PO2 in breast cancers is ~10 mm Hg, as compared to ~65 mm Hg in normal breast tissue [2]. Reduced O2 availability induces HIF-1, which regulates the transcription of hundreds of genes [3*,4*] that encode proteins involved in every aspect of cancer biology, including: cell immortalization and stem cell maintenance; genetic instability; glucose and energy metabolism; vascularization; autocrine growth factor signaling; invasion and metastasis; immune evasion; and resistance to chemotherapy and radiation therapy [5].

HIF-1 is a transcription factor that consists of an O2-regulated HIF-1α and a constitutively expressed HIF-1β subunit [6]. In well-oxygenated cells, HIF-1α is hydroxylated on proline residue 402 (Pro-402) and/or Pro-564 by prolyl hydroxylase domain protein 2 (PHD2), which uses O2 and α-ketoglutarate as substrates in a reaction that generates CO2 and succinate as byproducts [7]. Prolyl-hydroxylated HIF-1α is bound by the von Hippel-Lindau tumor suppressor protein (VHL), which recruits an E3-ubiquitin ligase that targets HIF-1α for proteasomal degradation (Figure 1A). Asparagine 803 in the transactivation domain is hydroxylated in well-oxygenated cells by factor inhibiting HIF-1 (FIH-1), which blocks the binding of the coactivators p300 and CBP [7]. Under hypoxic conditions, the prolyl and asparaginyl hydroxylation reactions are inhibited by substrate (O2) deprivation and/or the mitochondrial generation of reactive oxygen species (ROS), which may oxidize Fe(II) present in the catalytic center of the hydroxylases [8].

HIF-1 and metabolism  nihms156580f1

HIF-1 and metabolism nihms156580f1

HIF-1 and metabolism

Figure 1 HIF-1 and metabolism. (A) Regulation of HIF-1α protein synthesis and stability and HIF-1-dependent metabolic reprogramming. The rate of translation of HIF-1α mRNA into protein in cancer cells is dependent upon the activity of the mammalian 

The finding that acute changes in PO2 increase mitochondrial ROS production suggests that cellular respiration is optimized at physiological PO2 to limit ROS generation and that any deviation in PO2 — up or down — results in increased ROS generation. If hypoxia persists, induction of HIF-1 leads to adaptive mechanisms to reduce ROS and re-establish homeostasis, as described below. Prolyl and asparaginyl hydroxylation provide a molecular mechanism by which changes in cellular oxygenation can be transduced to the nucleus as changes in HIF-1 activity. This review will focus on recent advances in our understanding of the role of HIF-1 in controlling glucose and energy metabolism, but it should be appreciated that any increase in HIF-1 activity that leads to changes in cell metabolism will also affect many other critical aspects of cancer biology [5] that will not be addressed here.

HIF-1 target genes involved in glucose and energy metabolism

HIF-1 activates the transcription of SLC2A1 and SLC2A3, which encode the glucose transporters GLUT1 and GLUT3, respectively, as well as HK1 and HK2, which encode hexokinase, the first enzyme of the Embden-Meyerhoff (glycolytic) pathway [9]. Once taken up by GLUT and phosphorylated by HK, FDG cannot be metabolized further; thus, FDG-PET signal is determined by FDG delivery to tissue (i.e. perfusion) and GLUT/HK expression/activity. Unlike FDG, glucose is further metabolized to pyruvate by the action of the glycolytic enzymes, which are all encoded by HIF-1 target genes (Figure 1A). Glycolytic intermediates are also utilized for nucleotide and lipid synthesis [10]. Lactate dehydrogenase A (LDHA), which converts pyruvate to lactate, and monocarboxylate transporter 4 (MCT4), which transports lactate out of the cell (Figure 1B), are also regulated by HIF-1 [9,11]. Remarkably, lactate produced by hypoxic cancer cells can be taken up by non-hypoxic cells and used as a respiratory substrate [12**].

Pyruvate represents a critical metabolic control point, as it can be converted to acetyl coenzyme A (AcCoA) by pyruvate dehydrogenase (PDH) for entry into the tricarboxylic acid (TCA) cycle or it can be converted to lactate by LDHA (Figure 1B). Pyruvate dehydrogenase kinase (PDK), which phosphorylates and inactivates the catalytic domain of PDH, is encoded by four genes and PDK1 is activated by HIF-1 [13,14]. (Further studies are required to determine whether PDK2PDK3, or PDK4 is regulated by HIF-1.) As a result of PDK1 activation, pyruvate is actively shunted away from the mitochondria, which reduces flux through the TCA cycle, thereby reducing delivery of NADH and FADH2 to the electron transport chain. This is a critical adaptive response to hypoxia, because in HIF-1α–null mouse embryo fibroblasts (MEFs), PDK1 expression is not induced by hypoxia and the cells die due to excess ROS production, which can be ameliorated by forced expression of PDK1 [13]. MYC, which is activated in ~40% of human cancers, cooperates with HIF-1 to activate transcription of PDK1, thereby amplifying the hypoxic response [15]. Pharmacological inhibition of HIF-1 or PDK1 activity increases O2 consumption by cancer cells and increases the efficacy of a hypoxia-specific cytotoxin [16].

Hypoxia also induces mitochondrial autophagy in many human cancer cell lines through HIF-1-dependent expression of BNIP3 and a related BH3 domain protein, BNIP3L [19**]. Autocrine signaling through the platelet-derived growth factor receptor in cancer cells increases HIF-1 activity and thereby increases autophagy and cell survival under hypoxic conditions [21]. Autophagy may also occur in a HIF-1-independent manner in response to other physiological stimuli that are associated with hypoxic conditions, such as a decrease in the cellular ATP:AMP ratio, which activates AMP kinase signaling [22].

In clear cell renal carcinoma, VHL loss of function (LoF) results in constitutive HIF-1 activation, which is associated with impaired mitochondrial biogenesis that results from HIF-1-dependent expression of MXI1, which blocks MYC-dependent expression of PGC-1β, a coactivator that is required for mitochondrial biogenesis [23]. Inhibition of wild type MYC activity in renal cell carcinoma contrasts with the synergistic effect of HIF-1 and oncogenic MYC in activating PDK1 transcription [24].

Genetic and metabolic activators of HIF-1

Hypoxia plays a critical role in cancer progression [2,5] but not all cancer cells are hypoxic and a growing number of O2-independent mechanisms have been identified by which HIF-1 is induced [5]. Several mechanisms that are particularly relevant to cancer metabolism are described below.

Activation of mTOR

Alterations in mitochondrial metabolism

NAD+ levels

It is of interest that the NAD+-dependent deacetylase sirtuin 1 (SIRT1) was found to bind to, deacetylate, and increase transcriptional activation by HIF-2α but not HIF-1α [42**]. Another NAD+-dependent enzyme is poly(ADP-ribose) polymerase 1 (PARP1), which was recently shown to bind to HIF-1α and promote transactivation through a mechanism that required the enzymatic activity of PARP1 [43]. Thus, transactivation mediated by both HIF-1α and HIF-2α can be modulated according to NAD+ levels.

Nitric oxide

Increased expression of nitric oxide (NO) synthase isoforms and increased levels of NO have been shown to increase HIF-1α protein stability in human oral squamous cell carcinoma [44]. In prostate cancer, nuclear co-localization of endothelial NO synthase, estrogen receptor β, HIF-1α, and HIF-2α was associated with aggressive disease and the proteins were found to form chromatin complexes on the promoter of TERT gene encoding telomerase [45**]. The NOS2 gene encoding inducible NO synthase is HIF-1 regulated [5], suggesting another possible feed-forward mechanism.

7.9.9 In Vivo HIF-Mediated Reductive Carboxylation

Gameiro PA1Yang JMetelo AMPérez-Carro R, et al.
Cell Metab. 2013 Mar 5; 17(3):372-85.

Hypoxic and VHL-deficient cells use glutamine to generate citrate and lipids through reductive carboxylation (RC) of α-ketoglutarate. To gain insights into the role of HIF and the molecular mechanisms underlying RC, we took advantage of a panel of disease-associated VHL mutants and showed that HIF expression is necessary and sufficient for the induction of RC in human renal cell carcinoma (RCC) cells. HIF expression drastically reduced intracellular citrate levels. Feeding VHL-deficient RCC cells with acetate or citrate or knocking down PDK-1 and ACLY restored citrate levels and suppressed RC. These data suggest that HIF-induced low intracellular citrate levels promote the reductive flux by mass action to maintain lipogenesis. Using [1–13C] glutamine, we demonstrated in vivo RC activity in VHL-deficient tumors growing as xenografts in mice. Lastly, HIF rendered VHL-deficient cells sensitive to glutamine deprivation in vitro, and systemic administration of glutaminase inhibitors suppressed the growth of RCC cells as mice xenografts.

Cancer cells undergo fundamental changes in their metabolism to support rapid growth, adapt to limited nutrient resources, and compete for these supplies with surrounding normal cells. One of the metabolic hallmarks of cancer is the activation of glycolysis and lactate production even in the presence of adequate oxygen. This is termed the Warburg effect, and efforts in cancer biology have revealed some of the molecular mechanisms responsible for this phenotype (Cairns et al., 2011). More recently, 13C isotopic studies have elucidated the complementary switch of glutamine metabolism that supports efficient carbon utilization for anabolism and growth (DeBerardinis and Cheng, 2010). Acetyl-CoA is a central biosynthetic precursor for lipid synthesis, being generated from glucose-derived citrate in well-oxygenated cells (Hatzivassiliou et al., 2005). Warburg-like cells, and those exposed to hypoxia, divert glucose to lactate, raising the question of how the tricarboxylic acid (TCA) cycle is supplied with acetyl-CoA to support lipogenesis. We and others demonstrated, using 13C isotopic tracers, that cells under hypoxic conditions or defective mitochondria primarily utilize glutamine to generate citrate and lipids through reductive carboxylation (RC) of α-ketoglutarate by isocitrate dehydrogenase 1 (IDH1) or 2 (IDH2) (Filipp et al., 2012Metallo et al., 2012;Mullen et al., 2012Wise et al., 2011).

The transcription factors hypoxia inducible factors 1α and 2α (HIF-1α, HIF-2α) have been established as master regulators of the hypoxic program and tumor phenotype (Gordan and Simon, 2007Semenza, 2010). In addition to tumor-associated hypoxia, HIF can be directly activated by cancer-associated mutations. The von Hippel-Lindau (VHL) tumor suppressor is inactivated in the majority of sporadic clear-cell renal carcinomas (RCC), with VHL-deficient RCC cells exhibiting constitutive HIF-1α and/or HIF-2α activity irrespective of oxygen availability (Kim and Kaelin, 2003). Previously, we showed that VHL-deficient cells also relied on RC for lipid synthesis even under normoxia. Moreover, metabolic profiling of two isogenic clones that differ in pVHL expression (WT8 and PRC3) suggested that reintroduction of wild-type VHL can restore glucose utilization for lipogenesis (Metallo et al., 2012). The VHL tumor suppressor protein (pVHL) has been reported to have several functions other than the well-studied targeting of HIF. Specifically, it has been reported that pVHL regulates the large subunit of RNA polymerase (Pol) II (Mikhaylova et al., 2008), p53 (Roe et al., 2006), and the Wnt signaling regulator Jade-1. VHL has also been implicated in regulation of NF-κB signaling, tubulin polymerization, cilia biogenesis, and proper assembly of extracellular fibronectin (Chitalia et al., 2008Kim and Kaelin, 2003Ohh et al., 1998Thoma et al., 2007Yang et al., 2007). Hypoxia inactivates the α-ketoglutarate-dependent HIF prolyl hydroxylases, leading to stabilization of HIF. In addition to this well-established function, oxygen tension regulates a larger family of α-ketoglutarate-dependent cellular oxygenases, leading to posttranslational modification of several substrates, among which are chromatin modifiers (Melvin and Rocha, 2012). It is therefore conceivable that the effect of hypoxia on RC that was reported previously may be mediated by signaling mechanisms independent of the disruption of the pVHL-HIF interaction. Here we (1) demonstrate that HIF is necessary and sufficient for RC, (2) provide insights into the molecular mechanisms that link HIF to RC, (3) detected RC activity in vivo in human VHL-deficient RCC cells growing as tumors in nude mice, (4) provide evidence that the reductive phenotype ofVHL-deficient cells renders them sensitive to glutamine restriction in vitro, and (5) show that inhibition of glutaminase suppresses growth of VHL-deficient cells in nude mice. These observations lay the ground for metabolism-based therapeutic strategies for targeting HIF-driven tumors (such as RCC) and possibly the hypoxic compartment of solid tumors in general.

Functional Interaction between pVHL and HIF Is Necessary to Inhibit RC

Figure 1  HIF Inactivation Is Necessary for Downregulation of Reductive Carboxylation by pVHL

We observed a concurrent regulation in glucose metabolism in the different VHL mutants. Reintroduction of wild-type or type 2C pVHL mutant, which can meditate HIF-α destruction, stimulated glucose oxidation via pyruvate dehydrogenase (PDH), as determined by the degree of 13C-labeled TCA cycle metabolites (M2 enrichment) (Figures 1D and 1E). In contrast, reintroduction of an HIF nonbinding Type 2B pVHL mutant failed to stimulate glucose oxidation, resembling the phenotype observed in VHL-deficient cells (Figures 1D and 1E). Additional evidence for the overall glucose utilization was obtained from the enrichment of M3 isotopomers using [U13-C6]glucose (Figure S1A), which shows a lower contribution of glucose-derived carbons to the TCA cycle in VHL-deficient RCC cells (via pyruvate carboxylase and/or continued TCA cycling).

To test the effect of HIF activation on the overall glutamine incorporation in the TCA cycle, we labeled an isogenic pair of VHL-deficient and VHL-reconstituted UMRC2 cells with [U-13C5]glutamine, which generates M4 fumarate, M4 malate, M4 aspartate, and M4 citrate isotopomers through glutamine oxidation. As seen in Figure S1BVHL-deficient/VHL-positive UMRC2 cells exhibit similar enrichment of M4 fumarate, M4 malate, and M4 asparate (but not citrate) showing that VHL-deficient cells upregulate reductive carboxylation without compromising oxidative metabolism from glutamine. …  Labeled carbon derived from [5-13C1]glutamine can be incorporated into fatty acids exclusively through RC, and the labeled carbon cannot be transferred to palmitate through the oxidative TCA cycle (Figure 1B, red carbons). Tracer incorporation from [5-13C1]glutamine occurs in the one carbon (C1) of acetyl-CoA, which results in labeling of palmitate at M1, M2, M3, M4, M5, M6, M7, and M8 mass isotopomers. In contrast, lipogenic acetyl-CoA molecules originating from [U-13C6]glucose are fully labeled, and the labeled palmitate is represented by M2, M4, M6, M8, M10, M12, M14, and M16 mass isotopomers.

Figure 2 HIF Inactivation Is Necessary for Downregulation of Reductive Lipogenesis by pVHL

To determine the specific contribution from glucose oxidation or glutamine reduction to lipogenic acetyl-CoA, we performed isotopomer spectral analysis (ISA) of palmitate labeling patterns. ISA indicates that wild-type pVHL or pVHL L188V mutant-reconstituted UMRC2 cells relied mainly on glucose oxidation to produce lipogenic acetyl-CoA, while UMRC2 cells reconstituted with a pVHL mutant defective in HIF inactivation (Y112N or Y98N) primarily employed RC. Upon disruption of the pVHL-HIF interaction, glutamine becomes the preferred substrate for lipogenesis, supplying 70%–80% of the lipogenic acetyl-CoA (Figure 2C). This is not a cell-line-specific phenomenon, but it applies to VHL-deficient human RCC cells in general; the same changes are observed in 786-O cells reconstituted with wild-type pVHL or mutant pVHL or infected with vector only as control (Figure S2).

HIF Is Sufficient to Induce RC (reductive carboxylation) from Glutamine in RCC Cells

As shown in Figure 3C, reintroduction of wild-type VHLinto 786-O cells suppressed RC, whereas the expression of the constitutively active HIF-2α mutant was sufficient to stimulate this reaction, restoring the M1 enrichment of TCA cycle metabolites observed in VHL-deficient 786-O cells. Expression of HIF-2α P-A also led to a concomitant decrease in glucose oxidation, corroborating the metabolic alterations observed in glutamine metabolism (Figures 3D and 3E).

Figure 3 Expression of HIF-2α Is Sufficient to Induce Reductive Carboxylation and Lipogenesis from Glutamine in RCC Cells

Expression of HIF-2α P-A in 786-O cells phenocopied the loss-of-VHL with regards to glutamine reduction for lipogenesis (Figure 3G), suggesting that HIF-2α can induce the glutamine-to-lipid pathway in RCC cells per se. Although reintroduction of wild-type VHL restored glucose oxidation in UMRC2 and UMRC3 cells (Figures S3B–S3I), HIF-2α P-A expression did not measurably affect the contribution of each substrate to the TCA cycle or lipid synthesis in these RCC cells (data not shown). UMRC2 and UMRC3 cells endogenously express both HIF-1α and HIF-2α, whereas 786-O cells exclusively express HIF-2α. There is compelling evidence suggesting, at least in RCC cells, that HIF-α isoforms have overlapping—but also distinct—functions and their roles in regulating bioenergetic processes remain an area of active investigation. Overall, HIF-1α has an antiproliferative effect, and its expression in vitro leads to rapid death of RCC cells while HIF-2α promotes tumor growth (Keith et al., 2011Raval et al., 2005).

Metabolic Flux Analysis Shows Net Reversion of the IDH Flux upon HIF Activation

To determine absolute fluxes in RCC cells, we employed 13C metabolic flux analysis (MFA) as previously described (Metallo et al., 2012). Herein, we performed MFA using a combined model of [U-13C6]glucose and [1-13C1]glutamine tracer data sets from the 786-O derived isogenic clones PRC3 (VHL−/ −)/WT8 (VHL+) cells, which show a robust metabolic regulation by reintroduction of pVHL. To this end, we first determined specific glucose/glutamine consumption and lactate/glutamate secretion rates. As expected, PRC3 exhibited increased glucose consumption and lactate production when compared to WT8 counterparts (Figure 4A). While PRC3 exhibited both higher glutamine consumption and glutamate production rates than WT8 (Figure 4A), the net carbon influx was higher in PRC3 cells (Figure 4B). Importantly, the fitted data show that the flux of citrate to α-ketoglutarate was negative in PRC3 cells (Figure 4C). This indicates that the net (forward plus reverse) flux of isocitrate dehydrogenase and aconitase (IDH + ACO) is toward citrate production. The exchange flux was also higher in PRC3 than WT8 cells, whereas the PDH flux was lower in PRC3 cells. In agreement with the tracer data, these MFA results strongly suggest that the reverse IDH + ACO fluxes surpass the forward flux in VHL-deficient cells. The estimated ATP citrate lyase (ACLY) flux was also lower in PRC3 than in WT8 cells. Furthermore, the malate dehydrogenase (MDH) flux was negative, reflecting a net conversion of oxaloacetate into malate in VHL-deficient cells (Figure 4C). This indicates an increased flux through the reductive pathway downstream of IDH, ACO, and ACLY. Additionally, some TCA cycle flux estimates downstream of α-ketoglutarate were not significantly different between PRC and WT8 (Table S1). This shows that VHL-deficient cells maintain glutamine oxidation while upregulating reductive carboxylation (Figure S1B). This finding is in agreement with the higher glutamine uptake observed in VHL-deficient cells. Table S1 shows the metabolic network and complete MFA results. …

Addition of citrate in the medium, in contrast to acetate, led to an increase in the citrate-to-α-ketoglutarate ratio (Figure 5L) and absolute citrate levels (Figure S4H) not only in VHL-deficient but alsoVHL-reconstituted cells. The ability of exogenous citrate, but not acetate, to also affect RC in VHL-reconstituted cells may be explained by compartmentalization differences or by allosteric inhibition of citrate synthase (Lehninger, 2005); that is, the ability of acetate to raise the intracellular levels of citrate may be limited in (VHL-reconstituted) cells that exhibit high endogenous levels of citrate. Whatever the mechanism, the results imply that increasing the pools of intracellular citrate has a direct biochemical effect in cells with regards to their reliance on RC. Finally, we assayed the transcript and protein levels of enzymes involved in the reductive utilization of glutamine and did not observe significant differences between VHL-deficient andVHL-reconstituted UMRC2 cells (Figures S4I and S4J), suggesting that HIF does not promote RC by direct transactivation of these enzymes. The IDH1/IDH2 equilibrium is defined as follows:


Figure 5 Regulation of HIF-Mediated Reductive Carboxylation by Citrate Levels

We sought to investigate whether HIF could affect the driving force of the IDH reaction by also enhancing NADPH production. We did not observe a significant alteration of the NADP+/NADPH ratio between VHL-deficient and VHL-positive cells in the cell lysate (Figure S4I). Yet, we determined the ratio of the free dinucleotides using the measured ratios of suitable oxidized (α-ketoglutarate) and reduced (isocitrate/citrate) metabolites that are linked to the NADP-dependent IDH enzymes. The determined ratios (Figure S4J) are in close agreement with the values initially reported by the Krebs lab (Veech et al., 1969) and showed that HIF-expressing UMRC2 cells exhibit a higher NADP+/NADPH ratio. Collectively, these data strongly suggest that HIF-regulated citrate levels modulate the reductive flux to maintain adequate lipogenesis.

Reductive Carboxylation from Glutamine Is Detectable In Vivo

Figure 6 Evidence for Reductive Carboxylation Activity In Vivo

Loss of VHL Renders RCC Cells Sensitive to Glutamine Deprivation

We hypothesized that VHL deficiency results in cell addiction to glutamine for proliferation. We treated the isogenic clones PRC3 (VHL-deficient cells) and WT8 (VHL-reconstituted cells) with the glutaminase inhibitor 968 (Wang et al., 2010a). VHL-deficient PRC3 cells were more sensitive to treatment with 968, compared to the VHL-reconstituted WT8 cells (Figure 7A). To confirm that this is not only a cell-line-specific phenomenon, we also cultured UMRC2 cells in the presence of 968 or diluent control and showed selective sensitivity of VHL-deficient cells (Figure 7B).

Figure 7 VHL-Deficient Cells and Tumors Are Sensitive to Glutamine Deprivation

(A–E) Cell proliferation is normalized to the corresponding cell type grown in 1 mM glutamine-containing medium. Effect of treatment with glutaminase (GLS) inhibitor 968 in PRC3/WT8 (A) and UMRC2 cells (B). Rescue of GLS inhibition with dimethyl alpha-ketoglutarate (DM-Akg; 4 mM) or acetate (4 mM) in PRC3/WT8 clonal cells (C) and polyclonal 786-O cells (D). Effect of GLS inhibitor BPTES in UMRC2 cells (E). Student’s t test compares VHL-reconstituted cells to control cells in (A), (B), and (E) and DM-Akg or acetate-rescued cells to correspondent control cells treated with 968 only in (C) and (D) (asterisk in parenthesis indicates comparison between VHL-reconstituted to control cells). Error bars represent SEM.

(F) GLS inhibitor BPTES suppresses growth of human UMRC3 RCC cells as xenografts in nu/nu mice. When the tumors reached 100mm3, injections with BPTES or vehicle control were carried out daily for 14 days (n = 12). BPTES treatment decreases tumor size and mass (see insert). Student’s t test compares control to BPTES-treated mice (F). Error bars represent SEM.

(G) Diagram showing the regulation of reductive carboxylation by HIF.

In summary, our findings show that HIF is necessary and sufficient to promote RC from glutamine. By inhibiting glucose oxidation in the TCA cycle and reducing citrate levels, HIF shifts the IDH reaction toward RC to support citrate production and lipogenesis (Figure 7G). The reductive flux is active in vivo, fuels tumor growth, and can potentially be targeted pharmacologically. Understanding the significance of reductive glutamine metabolism in tumors may lead to metabolism-based therapeutic strategies.

Along with others, we reported that hypoxia and loss of VHL engage cells in reductive carboxylation (RC) from glutamine to support citrate and lipid synthesis (Filipp et al., 2012Metallo et al., 2012Wise et al., 2011). Wise et al. (2011) suggested that inactivation of HIF in VHL-deficient cells leads to reduction of RC. These observations raise the hypothesis that HIF, which is induced by hypoxia and is constitutively active inVHL-deficient cells, mediates RC. In our current work, we provide mechanistic insights that link HIF to RC. First, we demonstrate that polyclonal reconstitution of VHL in several human VHL-deficient RCC cell lines inhibits RC and restores glucose oxidation. Second, the VHL mutational analysis demonstrates that the ability of pVHL to mitigate reductive lipogenesis is mediated by HIF and is not the outcome of previously reported, HIF-independent pVHL function(s). Third, to prove our hypothesis we showed that constitutive expression of a VHL-independent HIF mutant is sufficient to phenocopy the reductive phenotype observed in VHL-deficient cells. In addition, we showed that RC is not a mere in vitro phenomenon, but it can be detected in vivo in human tumors growing as mouse xenografts. Lastly, treatment of VHL-deficient human xenografts with glutaminase inhibitors led to suppression of their growth as tumors.

7.9.10 Evaluation of HIF-1 inhibitors as anticancer agents

Semenza GL1.
Drug Discov Today. 2007 Oct; 12(19-20):853-9

Hypoxia-inducible factor 1 (HIF-1) regulates the transcription of many genes involved in key aspects of cancer biology, including immortalization, maintenance of stem cell pools, cellular dedifferentiation, genetic instability, vascularization, metabolic reprogramming, autocrine growth factor signaling, invasion/metastasis, and treatment failure. In animal models, HIF-1 overexpression is associated with increased tumor growth, vascularization, and metastasis, whereas HIF-1 loss-of-function has the opposite effect, thus validating HIF-1 as a target. In further support of this conclusion, immunohistochemical detection of HIF-1α overexpression in biopsy sections is a prognostic factor in many cancers. A growing number of novel anticancer agents have been shown to inhibit HIF-1 through a variety of molecular mechanisms. Determining which combination of drugs to administer to any given patient remains a major obstacle to improving cancer treatment outcomes.

Aurelian Udristioiu


Aurelian Udristioiu

Lab Director at Emergency County Hospital Targu Jiu

Mechanisms that control T cell metabolic reprogramming are now coming to light, and many of the same oncogenes importance in cancer metabolism are also crucial to drive T cell metabolic transformations, most notably Myc, hypoxia inducible factor (HIF)1a, estrogen-related receptor (ERR) a, and the mTOR pathway.
The proto-oncogenic transcription factor, Myc, is known to promote transcription of genes for the cell cycle, as well as aerobic glycolysis and glutamine metabolism. Recently, Myc has been shown to play an essential role in inducing the expression of glycolytic and glutamine metabolism genes in the initial hours of T cell activation. In a similar fashion, the transcription factor (HIF)1a can up-regulate glycolytic genes to allow cancer cells to survive under hypoxic conditions

Read Full Post »

The Metabolic View of Epigenetic Expression

Writer and Curator: Larry H Bernstein, MD, FCAP


This is the fifth contribution to a series of articles on cancer, genomics, and metabolism.   I begin this after reading an article by Stephen Williams “War on Cancer May Need to Refocus Says Cancer Expert on NPR”, and after listening to NPR “On the Media”. This is an unplanned experience, perhaps partly related to an Op-Ed in the New York Times two days before by Angelina Jolie Pittman.  Taking her article prior to pre-emptive breast surgery for the BRCA1 mutation two years ago and her salpingo-oophorectomy at age 39 years with her family history, and her adoption of several children even prior to her marriage to Brad Pitt, reveals an unusual self-knowledge as well as perspective on the disease risk balanced with her maternal instincts.  I sense (but don’t know) that she had a good knowledge not stated about the estrogen sensitivity of breast cancer for some years, and balanced that knowledge in her life decisions.

Tracing the history of cancer and the Lyndon Johnson initiated “War on Cancer” the initiative is presented as misguided.  Moreover, the imbalance is posed aas focused overly on genomics, and there is an imbalnced in the attention to the types of cancer, bladder cancer (urothelial) receiving too little attention. However, the events that drive this are complex, and not surprising.  The funding is driven partly by media attention (a film star or President’s wife) and not to be overlooked, watch where the money flows.  People who have the ability to donate and also have a family experience will give, regardless of the statistics because it is 100 percent in their eyes.

Insofar as the scientific endeavor goes, young scientists are committed to a successful research career, and they also need funding, so they have to balance the risk of success and failure in the choice of problems they choose to work on.  But until the 20th century, the biological sciences were largely descriptive. The emergence of a “Molecular Biology” is a unique 20th century development. The work of Pathology – pioneered by Rokitansky, Virchow, and to an extent also the anatomist/surgeon John Harvey – was observational science.  The description of Hodgkin’s lymphoma was observational, and it was a breakthrough in medicine.

With the emergence of genomics from biochemistry and genetics in molecular biology (biology at the subcellular level), a part of medicine that was well founded became an afterthought.  After all, after many years of the history of medicine and pathology, it is well known that cancers are not only a dysmetabolism of cellular replication and cellular regulation, but cancers have a natural history related to organ system, tissue specificity, sex, and age of occurrence. This should be well known to the experienced practitioner, but not necessarily to the basic researcher with no little clinical exposure.  Consequently, it was quite remarkable to me to find that the truly amazing biochemist who gave a “Harvey Lecture” at Harvard on the pyridine nucleotide transhydrogenases, and who shared in the discovery of Coenzyme A, had made the observation that organs that are primarily involved with synthetic activity -adrenal, pituitary, and thyroid, testis, ovary, breast (most notably) – have a more benign course than those of stomach, colon, pancreas, melanoma, hematopoietic, and sarcomas. The liver is highly synthetic, but doesn’t fit so nicely because of the role in detoxification and the large role in glucose and fat catabolism.  Further, this was at a time that we knew nothing about the cell death pathway and cellular repair, and how is it in concert with cell proliferation.

The first important reasoning about cancer metabolism was opened by Otto Warburg in the late 1920s.  I have  little reason to doubt his influence on Nathan Kaplan, who used the terms DPN(+/H) and TPN(+/H), disregarding the terms NAD(+/H) and NADP(+/H), although I was told it was because of the synthesis of the pyridine nucleotide adducts for study (APDPN, etc.).

In a recent article, I had an interesting response from Jose ES Rosalino:

In mRNA Translation and Energy Metabolism in Cancer

Topisirovic and N. Sonenberg – Cold Spring Harbor Symposia on Quantitative Biology, Volume LXXVI –

“A prominent feature of cancer cells is the use of aerobic glycolysis under conditions in which oxygen levels are sufficient to support energy production in the mitochondria (Jones and Thompson 2009; Cairns et al. 2010). This phenomenon, named the “Warburg effect,” after its discoverer Otto Warburg, is thought to fuel the biosynthetic requirements of the neoplastic growth (Warburg 1956; Koppenol et al. 2011) and has recently been acknowledged as one of the hallmarks of cancer (Hanahan and Weinberg 2011). mRNA translation is the most energy-demanding process in the cell (Buttgereit and Brand 1995). Again, the use of aerobic glycolysis expression has being twisted.”

To understand my critical observation consider this: Aerobic glycolysis is the carbon flow that goes from Glucose to CO2 and water (includes Krebs cycle and respiratory chain for the restoration of NAD, FAD etc.

Anerobic glyclysis is the carbon flow that goes from glucose to lactate. It uses conversion of pyruvate to lactate to regenerate NAD.

“Pasteur effect” is an expression coined by Warburg it refers to the reduction in the carbon flow from glucose when oxygen is offered to yeasts. The major reason for that is in general terms, derived from the fact that carbon flow is regulated by several cell requirements but majorly by the ATP needs of the cell. Therefore, as ATP is generated 10 more efficiently in aerobiosis than under anaerobiosis, less carbon flow is required under aerobiosis than under anaerobiosis to maintain ATP levels. Warburg, after searching for the same regulatory mechanism in normal and cancer cells for comparison found that transformed cell continued their large flow of glucose carbons to lactate despite of the presence of oxygen.

So, it is wrong to describe that aerobic glycolysis continues in the presence of oxygen. It is what it is expected to occur. The wrong thing is that anaerobic glycolysis continues under aerobiosis.

In our discussion of transcription and cell regulatory processes, we have already encountered a substantial amount of “enzymology” that drives what is referred to as “epigenetics”.  Enzymatic reactions are involved almost everywhere we look at the processes involved in RNA nontranscriptional affairs.

Enzyme catalysis

Pyruvate carboxylase is critical for non–small-cell lung cancer proliferation
K Sellers,…, TW-M Fan
J Clin Invest. Jan 2015; xx

Anabolic biosynthesis requires precursors supplied by the Krebs cycle, which in turn requires anaplerosis to replenish precursor intermediates. The major anaplerotic sources are pyruvate and glutamine, which require the activity of pyruvate carboxylase (PC) and glutaminase 1 (GLS1), respectively. Due to their rapid proliferation, cancer cells have increased anabolic and energy demands; however, different cancer cell types exhibit differential requirements for PC- and GLS-mediated pathways for anaplerosis and cell proliferation. Here, we infused patients with early-stage non–small-cell lung cancer (NSCLC) with uniformly 13C-labeled glucose before tissue resection and determined that the cancerous tissues in these patients had enhanced PC activity. Freshly resected paired lung tissue slices cultured in 13C6-glucose or 13C5, 15N2-glutamine tracers confirmed selective activation of PC over GLS in NSCLC. Compared with noncancerous tissues, PC expression was greatly enhanced in cancerous tissues, whereas GLS1 expression showed no trend. Moreover, immunohistochemical analysis of paired lung tissues showed PC overexpression in cancer cells rather than in stromal cells of tumor tissues. PC knockdown induced multinucleation, decreased cell proliferation and colony formation in human NSCLC cells, and reduced tumor growth in a mouse xenograft model. Growth inhibition was accompanied by perturbed Krebs cycle activity, inhibition of lipid and nucleotide biosynthesis, and altered glutathione homeostasis. These findings indicate that PC-mediated anaplerosis in early stage NSCLC is required for tumor survival and proliferation.

Accelerated glycolysis under aerobic conditions (the “Warburg effect”) has been a hallmark of cancer for many decades (1). It is now recognized that cancer cells must undergo many other metabolic reprograming changes (2) to meet the increased anabolic and energetic demands of proliferation (3, 4). It is also becoming clear that different cancer types may utilize a variety of metabolic adaptations that are context dependent, commensurate with the notion that altered metabolism is a hallmark of cancer (12). Enhanced glucose uptake and aerobic glycolysis generates both energy (i.e., ATP) and molecular precursors for the biosynthesis of complex carbohydrates, sugar nucleotides, lipids, proteins, and nucleic acids. However, increased glycolysis alone is insufficient to meet the total metabolic demands of proliferating cancer cells. The Krebs cycle is also a source of energy via the oxidation of pyruvate, fatty acids, and amino acids such as glutamine. Moreover, several Krebs cycle intermediates are essential for anabolic and glutathione metabolism, including citrate, oxaloacetate, and α-ketoglutarate (Figure 1A).

Figure 1. PC is activated in human NSCLC tumors. (A) PC and GLS1 catalyze the major anaplerotic inputs (blue) into the Krebs cycle to support the anabolic demand for biosynthesis (green). Also shown is the fate of 13C from 13C6-glucose through glycolysis and into the Krebs cycle via PC (red).
(B) Representative Western blots of PC and GLS1 protein expression levels in human NC lung (N) and NSCLC (C) tissues. (C) Pairwise PC and GLS1 expression (n = 86) was normalized to α-tubulin and plotted as the log10 ratio of CA/NC tissues. For PC, nearly all log ratios were positive (82 of 86), with a clustering in the 0.5–1 range (i.e., typically 3- to 10-fold higher expression in the tumor tissue; Wilcoxon test, P < 0.0001). In contrast, GLS1 expression was nearly evenly distributed between positive and negative log10 ratios and showed no statistically significant difference between the CA and NC tissues (Wilcoxon test, P = 0.213). Horizontal bar represents the median. (D) In vivo PC activity was enhanced in CA tissue compared with that in paired NC lung tissues (n = 34) resected from the same human patients given 13C6-glucose 2.5–3 hours before tumor resection. PC activity was inferred from the enrichment of 13C3-citrate (Cit+3), 13C5-Cit (Cit+5), 13C3-malate (Mal+3), and 13C3-aspartate (Asp+3) as determined by GC-MS. *P < 0.05 and **P < 0.01 by paired Student t test. Error bars represent the SEM.

Continued functioning of the Krebs cycle requires the replenishment of intermediates that are diverted for anabolic uses or glutathione synthesis. This replenishment process, or anaplerosis, is accomplished via 2 major pathways: glutaminolysis (deamidation of glutamine via glutaminase [GLS] plus transamination of glutamate to α-ketoglutarate) and carboxylation of pyruvate to oxaloacetate via ATP-dependent pyruvate carboxylase (PC) (EC (refs. 3, 20, 21, and Figure 1A). The relative importance of these pathways is likely to depend on the nature of the cancer and its specific metabolic adaptations, including those to the microenvironment (20, 22). For example, glutaminolysis was shown to be activated in the glioma cell line SF188, while PC activity was absent, despite the high PC activity present in normal astrocytes. However, SF188 cells use PC to compensate for GLS1 suppression or glutamine restriction (20), and PC, rather than GLS1, was shown to be the major anaplerotic input to the Krebs cycle in primary glioma xenografts in mice. It is also unclear as to the relative importance of PC and GLS1 in other cancer cell types or, most relevantly, in human tumor tissues in situ. Our preliminary evidence from 5 non–small-cell lung cancer (NSCLC) patients indicated that PC expression and activity are upregulated in cancerous (CA) compared with paired noncancerous (NC) lung tissues (21), although it was unclear whether PC activation applies to a larger NSCLC cohort or whether PC expression was associated with the cancer and/or stromal cells

Here, we have greatly extended our previous findings (21) in a larger cohort (n = 86) by assessing glutaminase 1 (GLS1) status and analyzing in detail the biochemical and phenotypic consequences of PC suppression in NSCLC. We found PC activity and protein expression levels to be, on average, respectively, 100% and 5- to 10-fold higher in cancerous (CA) lung tissues than in paired NC lung tissues resected from NSCLC patients, whereas GLS1 expression showed no significant trend. We have also applied stable isotope–resolved metabolomic (SIRM) analysis to paired freshly resected CA and NC lung tissue slices in culture (analogous to the Warburg slices; ref. 25) using either [U-13C] glucose or [U-13C,15N] glutamine as tracers. This novel method provided information about tumor metabolic pathways and dynamics without the complication of whole-body metabolism in vivo.

PC expression and activity, but not glutaminase expression, are significantly enhanced in early stages of malignant NSCLC tumors. PC protein expression was significantly higher in primary NSCLC tumors than in paired adjacent NC lung tissues (n = 86, P < 0.0001, Wilcoxon test) (Figure 1, B and C). The median PC expression was 7-fold higher in the tumor, and the most probable (modal) overexpression in the tumor was approximately 3-fold higher (see Supple-mental Table 1; supplemental material available online with this article; We found that PC expression was also higher in the tumor tissue compared with that detected in the NC tissue in 82 of 86 patients. In contrast, GLS1 expression was not significantly different between the tumor and NC tissues (P = 0.213, Wilcoxon test) (Figure 1C and Supplemental Table 1). The 13C3-Asp produced from 13C6-glucose (Figure 1A) infused into NSCLC patients was determined by gas chromatography–mass spectrometry (GC-MS) to estimate in vivo PC activity. A bolus injection of 10 g 13C6-glucose in 50 ml saline led to an average of 44% 13C enrichment in the plasma glucose immediately after infusion (Supplemental Table 2). Because the labeled glucose was absorbed by various tissues over the approximately 2.5 hours between infusion and tumor resection, plasma glucose enrichment dropped to 17% (Supplemental Table 2). The labeled glucose in both CA and NC lung tissues was metabolized to labeled lactate, but this occurred to a much greater extent in the CA tissues (Supplemental Figure 1A), which indicates accelerated glycolysis in these tissues.

Fresh tissue (Warburg) slices confirm enhanced PC and Krebs cycle activity in NSCLC. To further assess PC activity relative to GLS1 activity in human lung tissues, thin (<1 mm thick) slices of paired CA and NC lung tissues freshly resected from 13 human NSCLC patients were cultured in 13C6-glucose or 13C5,15N2-glutamine for 24 hours. These tissues maintain biochemical activity and histological integrity for at least 24 hours under culture conditions (Figure 2A, Supplemental Figure 2, A and B, and ref. 26). When the tissues were incubated with 13C6-glucose, CA slices showed a significantly greater percentage of enrichment in glycolytic 13C3-lactate (3 in Figure 2B) than did the NC slices, indicative of the Warburg effect. In addition, the CA tissues had significantly higher fractions of 13C4-, 13C5-, and 13C6-citrate (4, 5, and 6 of citrate, respectively, in Figure 2B) than did the NC tissues. These isotopologs require the combined action of PDH, PC, and multiple turns of the Krebs cycle (Figure 2C). Consistent with the labeled citrate data, the increase in the percentage of enrichment of 13C3-, 13C4-, and 13C5-glutamate (3, 4, and 5 of glutamate, respectively, in Figure 2B) in the CA tissues indicates enhanced Krebs cycle and PC activity.

Figure 2. Ex vivo CA lung tissue slices have enhanced oxidation of glucose through glycolysis and the Krebs cycle with and without PC input compared with that of paired NC lung slices. Thin slices of CA and NC lung tissues freshly resected from 13 human NSCLC patients were incubated with 13C6-glucose for 24 hours as described in the Methods. The percentage of enrichment of lactate, citrate, glutamate, and aspartate was determined by GC-MS. (A) 1H{13C} HSQC NMR showed an increase in labeled lactate, glutamate, and aspartate. In addition, CA tissues had elevated 13C abundance in the ribose moiety of the adenine-containing nucleotides (1′-AXP), indicating that the tissues were viable and had enhanced capacity for nucleotide synthesis. (B) CA tissue slices (n = 13) showed increased glucose metabolism through glycolysis based on the increased percentage of enrichment of 13C3-lactate (“3”), and through the Krebs cycle based on the increased percentage of enrichment of 13C4–6-citrate (“4–6”) and 13C3–5-glutamate (“3–5”) (see 13C fate tracing in C). *P < 0.05 and **P < 0.01 by paired Student’s t test. Error bars represent the SEM. (C) An atom-resolved map illustrates how PC, PDH, and 2 turns of the Krebs cycle activity produced the 13C isotopologs of citrate and glutamate in B, whose enrichment were significantly enhanced in CA tissue slices.

Figure 4. PC suppression via shRNA inhibits proliferation and tumorigenicity of human NSCLC cell lines in vitro and in vivo. Proliferation and colony-formation assays were initiated 1 week after transduction and selection with puromycin. A549 xenograft in NSG mice was performed 8 days after transduction. *P < 0.01, **P < 0.001, ***P < 0.0001, and ****P < 0.00001 by Student t test, assuming unequal variances. Error bars represent the SEM. (A) NSCLC cells lines were transduced with shPC55 or shEV. Proliferation assays (n = 6) revealed substantial growth inhibition induced by PC knockdown in all 5 cell lines after a relatively long latency period. (B) Colony-formation assays indicated that PC knockdown reduced the capacity of A549 and PC9 cells to form colonies in soft agar (n = 3). (C) Tumor xenografts from shPC55-transduced A549 cells showed a 2-fold slower growth rate than did control shEV tumors (P < 0.001 by the unpaired Welch version of the t test). Tumor size was calculated as πab/4, where a and b are the x,y diameters. Each point represents an average of 6 mice. The solid lines are the nonlinear regression fits to the equation: size = a + bt2, as described in the Methods. (D) The extent of PC knockdown in the mouse xenografts (n = 6) was lesser than that in cell cultures, leading to less attenuation of PC expression (30%–60% of control) and growth inhibition. In addition, PC expression in the excised tumors correlated with the individual growth rates, as determined by Pearson’s correlation coefficient.

Fatty acyl synthesis from 13C5-glutamine (“Even” in Figure 6B) via glutaminolysis and the Krebs cycle was greatly attenuated in PC-suppressed cells. Taken together, these results suggest that PC knockdown severely inhibits lipid production by blocking the biosynthesis of fatty acyl components but not the glucose-derived glycerol backbone. This is consistent with decreased Krebs cycle activity (Figure 5), which in turn curtails citrate export from the mitochondria to supply the fatty acid precursor acetyl CoA in the cytoplasm.

Figure 5. PC knockdown perturbs glucose and glutamine flux through the Krebs cycle. 13C Isotopolog concentrations were determined by GC-MS (n = 3). Values represent the averages of triplicates, with standard errors. *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001 by Student’s t test, assuming unequal variances. The experiments were repeated 3 times. (A) A549 cells were transduced with shPC55 for 10 days before incubation with 13C6-glucose for 24 hours. As expected, the 13C isotopologs of Krebs cycle metabolites produced via PC and Krebs cycle activity were depleted in PC-deficient cells (tracked by blue dots in the atom-resolved map and blue circles in the bar graphs; see also Figure 2C). In addition, 13C6-glucose metabolism via PDH was also perturbed (indicated by red dots and circles). (B) Treatment of PC-knockdown cells with 13C5,15N2-glutamine revealed that anaplerotic input via GLS did not compensate for the loss of PC activity, since GLS activity was attenuated, as inferred from the activity markers (indicated by red dots and circles). Decarboxylation of glutamine-derived malate by malic enzyme (ME) and reentry of glutamine-derived pyruvate into the Krebs cycle via PC or PDH (shown in blue and green, respectively) were also attenuated. Purple diamonds denote 15N; black diamonds denote 14N.

Figure 6. PC suppression hinders Krebs cycle–fueled biosynthesis. (A) 13C atom–resolved pyrimidine biosynthesis from 13C6-glucose and 13C5-glutamine is depicted with a 13C5-ribose moiety (red dots) produced via the pentose phosphate pathway (PPP) and 13C1-3  uracil ring (blue dots) derived from  13C2-4-aspartate produced via the Krebs cycle or the combined action of ME and PC (blue dots). A549 cells transduced with shPC55 or shEV were incubated with 13C6-glucose or 13C5-glutamine for 24 hours. Fractional enrichment of UTP and CTP isotopologs from FT-ICR-MS analysis of polar cell extracts showed reduced enrichment of 13C6-glucose–derived 13C5-ribose (the “5” isotopolog) and 13C6-glucose– or 13C5-glutamine–derived 13C1-3-pyrimidine rings (the “6–8” or “1–3” isotopologs, highlighted by dashed green rectangles; for the “6–8” isotopologs, 5 13Cs arose from ribose and 1–3 13Cs from the ring) (10, 45). These data suggest that PC knockdown inhibits de novo pyrimidine biosynthesis from both glucose and glutamine. (B) Glucose and glutamine carbons enter fatty acids via citrate. FT-ICR-MS analysis of labeled lipids from the nonpolar cell extracts showed that PC knockdown severely inhibited the incorporation of glucose and glutamine carbons into the fatty acyl chains (even) and fatty acyl chains plus glycerol backbone (odd >3) of phosphatidylcholine lipids. However, synthesis of the 13C3-glycerol backbone (the “3” isotopolog) or its precursor 13C3-α-glycerol-3-phosphate (αG3P, m+3) from 13C6-glucose was enhanced rather than inhibited by PC knockdown. These data suggest that PC suppression specifically hinders fatty acid synthesis in A549 cells. Values represent the averages of triplicates (n = 3), with standard errors. *P < 0.05, **P < 0.01,  and ***P < 0.001 by Student’s t test, assuming unequal variances.

De novo glutathione synthesis was analyzed by 1H{13C} HSQC NMR. Glutathione synthesis from both glucose and glutamine was suppressed by PC knockdown (Supplemental Figure 9, A and B). Reduced de novo synthesis led to a large decrease in the total level of reduced glutathione (GSH; Supplemental Figure 12, A and B). At the same time, PC-knockdown cells accumulated slightly more oxidized GSH (GSSG; Supplemental Figure 12, A and B), leading to a significantly reduced GSH/GSSG ratio both in cell culture and in vivo (Supplemental Figure 12C). To determine whether this perturbation of glutathione homeostasis compromises the ability of PC-suppressed cells to handle oxidative stress, we measured ROS production by DCFDA fluorescence. PC-knockdown cells had over 70% more basal ROS than did control cells (0 mM H2O2; Supplemental Figure 12D). When cells were exposed to increasing concentrations of H2O2, the knockdown cells were less able to quench ROS, as they produced up to 300% more ROS than did control cells (Supplemental Figure 12D). However, N-acetylcysteine (NAC) at 10 mM did not rescue the growth of PC-knockdown cells, suggesting that such a growth effect is not simply related to an inability to regenerate GSH from GSSG. Altogether, these results show that PC suppression compromises anaplerotic input into the Krebs cycle, which in turn reduces the activity of the Krebs cycle, while limiting the ability of A549 cells to synthesize nucleotides, lipids, and glutathione. These downstream effects of PC knockdown were also evident when comparing the metabolism of shPC55-transduced A549 cells against that of A549 cells transduced with a scrambled vector (shScr) (Supplemental Figure 13), which suggests that they are on-target effects of PC knockdown.

  1. Warburg O. On the origin of cancer cells. Science. 1956;123(3191):309–314. 2. Dang CV, Semenza GL. Oncogenic alterations of metabolism. Trends Biochem Sci. 1999; 24(2):68–72.
    3. Fan TW, et al. Rhabdomyosarcoma cells show an energy producing anabolic metabolic phenotype compared with primary myocytes. Mol Cancer. 2008;7:79.
    4. Vander Heiden MG, Cantley LC, Thompson CB. Understanding the Warburg effect: the metabolic requirements of cell proliferation. Science. 2009;324(5930):1029–1033.
    10. Le A, et al. Glucose-independent glutamine metabolism via TCA cycling for proliferation and survival in B cells. Cell Metab. 2012;15(1):110–121
    20. Cheng T, et al. Pyruvate carboxylase is required for glutamine-independent growth of tumor cells. Proc Natl Acad Sci U S A. 2011;108(21):8674–8679.
    21. Fan TW, et al. Altered regulation of metabolic pathways in human lung cancer discerned by (13) C stable isotope-resolved metabolomics (SIRM). Mol Cancer. 2009;8:41.
    22. Marin-Valencia I, et al. Analysis of tumor metabolism reveals mitochondrial glucose oxidation in genetically diverse human glioblastomas in the mouse brain in vivo. Cell Metab. 2012;15(6):827–837.
    25. Warburg O. Versuche an überlebendem Carcinomgewebe (Methoden). Biochem Zeitschr. 1923;142:317–333.
    45. Lorkiewicz P, Higashi RM, Lane AN, Fan TW. High information throughput analysis of nucleotides and their isotopically enriched isotopologues by direct-infusion FTICR-MS. Metabolomics. 2012;8(5):930–939.

In vivo HIF-mediated reductive carboxylation is regulated by citrate levels and sensitizes VHL-deficient cells to glutamine deprivation.
Gameiro PA, Yang J, Metelo AM,…, Stephanopoulos G, Iliopoulos O.
Cell Metab. 2013 Mar 5; 17(3):372-85.

Hypoxic and VHL-deficient cells use glutamine to generate citrate and lipids through reductive carboxylation (RC) of α-ketoglutarate. To gain insights into the role of HIF and the molecular mechanisms underlying RC, we took advantage of a panel of disease-associated VHL mutants and showed that HIF expression is necessary and sufficient for the induction of RC in human renal cell carcinoma (RCC) cells. HIF expression drastically reduced intracellular citrate levels. Feeding VHL-deficient RCC cells with acetate or citrate or knocking down PDK-1 and ACLY restored citrate levels and suppressed RC. These data suggest that HIF-induced low intracellular citrate levels promote the reductive flux by mass action to maintain lipogenesis. Using [(1-13)C]glutamine, we demonstrated in vivo RC activity in VHL-deficient tumors growing as xenografts in mice. Lastly, HIF rendered VHL-deficient cells sensitive to glutamine deprivation in vitro, and systemic administration of glutaminase inhibitors suppressed the growth of RCC cells as mice xenografts.

Cancer cells undergo fundamental changes in their metabolism to support rapid growth, adapt to limited nutrient resources, and compete for these supplies with surrounding normal cells. One of the metabolic hallmarks of cancer is the activation of glycolysis and lactate production even in the presence of adequate oxygen. This is termed the Warburg effect, and efforts in cancer biology have revealed some of the molecular mechanisms responsible for this phenotype (Cairns et al., 2011). More recently, 13C isotopic studies have elucidated the complementary switch of glutamine metabolism that supports efficient carbon utilization for anabolism and growth (DeBerardinis and Cheng, 2010). Acetyl-CoA is a central biosynthetic precursor for lipid synthesis, being generated from glucose-derived citrate in well-oxygenated cells (Hatzivassiliou et al., 2005). Warburg-like cells, and those exposed to hypoxia, divert glucose to lactate, raising the question of how the tricarboxylic acid (TCA) cycle is supplied with acetyl-CoA to support lipogenesis. We and others demonstrated, using 13C isotopic tracers, that cells under hypoxic conditions or defective mitochondria primarily utilize glutamine to generate citrate and lipids through reductive carboxylation (RC) of α-ketoglutarate by isocitrate dehydrogenase 1 (IDH1) or 2 (IDH2) (Filipp et al., 2012; Metallo et al., 2012; Mullen et al., 2012; Wise et al., 2011).

The transcription factors hypoxia inducible factors 1α and 2α (HIF-1α, HIF-2α) have been established as master regulators of the hypoxic program and tumor phenotype (Gordan and Simon, 2007; Semenza, 2010). In addition to tumor-associated hypoxia, HIF can be directly activated by cancer-associated mutations. The von Hippel-Lindau (VHL) tumor suppressor is inactivated in the majority of sporadic clear-cell renal carcinomas (RCC), with VHL-deficient RCC cells exhibiting constitutive HIF-1α and/or HIF-2α activity irrespective of oxygen availability (Kim and Kaelin, 2003). Previously, we showed that VHL-deficient cells also relied on RC for lipid synthesis even under normoxia. Moreover, metabolic profiling of two isogenic clones that differ in pVHL expression (WT8 and PRC3) suggested that reintroduction of wild-type VHL can restore glucose utilization for lipogenesis (Metallo et al., 2012). The VHL tumor suppressor protein (pVHL) has been reported to have several functions other than the well-studied targeting of HIF. Specifically, it has been reported that pVHL regulates the large subunit of RNA polymerase (Pol) II (Mikhaylova et al., 2008), p53 (Roe et al., 2006), and the Wnt signaling regulator Jade-1. VHL has also been implicated in regulation of NF-κB signaling, tubulin polymerization, cilia biogenesis, and proper assembly of extracellular fibronectin (Chitalia et al., 2008; Kim and Kaelin, 2003; Ohh et al., 1998; Thoma et al., 2007; Yang et al., 2007). Hypoxia inactivates the α-ketoglutarate-dependent HIF prolyl hydroxylases, leading to stabilization of HIF. In addition to this well-established function, oxygen tension regulates a larger family of α-ketoglutarate-dependent cellular oxygenases, leading to posttranslational modification of several substrates, among which are chromatin modifiers (Melvin and Rocha, 2012). It is therefore conceivable that the effect of hypoxia on RC that was reported previously may be mediated by signaling mechanisms independent of the disruption of the pVHL-HIF interaction. Here we

  • demonstrate that HIF is necessary and sufficient for RC,
  • provide insights into the molecular mechanisms that link HIF to RC,
  • detected RC activity in vivo in human VHL-deficient RCC cells growing as tumors in nude mice,
  • provide evidence that the reductive phenotype of VHL-deficient cells renders them sensitive to glutamine restriction in vitro, and
  • show that inhibition of glutaminase suppresses growth of VHL-deficient cells in nude mice.

These observations lay the ground for metabolism-based therapeutic strategies for targeting HIF-driven tumors (such as RCC) and possibly the hypoxic compartment of solid tumors in general.

HIF Inactivation Is Necessary for Downregulation of Reductive Carboxylation by pVHL

(A) Expression of HIF-1 α, HIF-2α, and their target protein GLUT1 in UMRC2-derived cell lines, as indicated.

(B) Carbon atom transition map: the fate of [1-13C1] and [5-13C1]glutamine used to trace reductive carboxylation in this work (carbon atoms are represented by circles). The [1-13C1] (green circle) and [5-13C1] (red circle) glutamine-derived isotopic labels are retained during the reductive TCA cycle (bold red pathway). Metabolites containing the acetyl-CoA carbon skeleton are highlighted by dashed circles.

(C) Relative contribution of reductive carboxylation.

(D and E) Relative contribution of glucose oxidation to the carbons of indicated metabolites (D) and citrate (E). Student’s t test compared VHL-reconstituted to vector-only or to VHL mutants (Y98N/Y112N). Error bars represent SEM. Pyr, pyruvate; Lac, lactate; AcCoA, acetyl-CoA, Cit, citrate; IsoCit, isocitrate; Akg, α-ketoglutarate; Suc, succinate; Fum, fumarate; Mal, malate; OAA, oxaloacetate; Asp, aspartate; Glu, glutamate; PDH, pyruvate dehydrogenase; ME, malic enzyme; IDH, isocitrate dehydrogenase enzymes; ACO, aconitase enzymes; ACLY, ATP-citrate lyase; GLS, glutaminase.

To test the effect of HIF activation on the overall glutamine incorporation in the TCA cycle, we labeled an isogenic pair of VHL-deficient and VHL-reconstituted UMRC2 cells with [U-13C5]glutamine, which generates M4 fumarate, M4 malate, M4 aspartate, and M4 citrate isotopomers through glutamine oxidation. As seen in Figure S1B, VHL-deficient/VHL-positive UMRC2 cells exhibit similar enrichment of M4 fumarate, M4 malate, and M4 asparate (but not citrate) showing that VHL-deficient cells upregulate reductive carboxylation without compromising oxidative metabolism from glutamine. Next, we tested whether HIF inactivation by pVHL is necessary to regulate the reductive utilization of glutamine for lipogenesis. To this end, we traced the relative incorporation of [U-13C6]glucose or [5-13C1]glutamine into palmitate. Labeled carbon derived from [5-13C1]glutamine can be incorporated into fatty acids exclusively through RC, and the labeled carbon cannot be transferred to palmitate through the oxidative TCA cycle (Figure 1B, red carbons). Tracer incorporation from [5-13C1]glutamine occurs in the one carbon (C1) of acetyl-CoA, which results in labeling of palmitate at M1, M2, M3, M4, M5, M6, M7, and M8 mass isotopomers. In contrast, lipogenic acetyl-CoA molecules originating from [U-13C6]glucose are fully labeled, and the labeled palmitate is represented by M2, M4, M6, M8, M10, M12, M14, and M16 mass isotopomers. VHL-deficient control cells and cells expressing pVHL type 2B mutants exhibited high palmitate labeling from the [5-13C1]glutamine; conversely, reintroduction of wild-type or type 2C pVHL mutant (L188V) resulted in high labeling from [U-13C6]glucose (Figures 2A and 2B, box inserts highlight the heavier mass isotopomers).



Figure 2.  HIF Inactivation Is Necessary for Downregulation of Reductive Lipogenesis by pVHL

Next, to determine the specific contribution from glucose oxidation or glutamine reduction to lipogenic acetyl-CoA, we performed isotopomer spectral analysis (ISA) of palmitate labeling patterns. ISA indicates that wild-type pVHL or pVHL L188V mutant-reconstituted UMRC2 cells relied mainly on glucose oxidation to produce lipogenic acetyl-CoA, while UMRC2 cells reconstituted with a pVHL mutant defective in HIF inactivation (Y112N or Y98N) primarily employed RC. Upon disruption of the pVHL-HIF interaction, glutamine becomes the preferred substrate for lipogenesis, supplying 70%–80% of the lipogenic acetyl-CoA (Figure 2C). This is not a cell-line-specific phenomenon, but it applies to VHL-deficient human RCC cells in general; the same changes are observed in 786-O cells reconstituted with wild-type pVHL or mutant pVHL or infected with vector only as control (Figure S2). Type 2A pVHL mutants (Y112H, which retain partial HIF binding) confer an intermediate reductive phenotype between wild-type VHL (which inactivates HIF) and type 2B pVHL mutants (which are totally defective in HIF regulation) as seen in Figures 1 and ​and 2.2. Taken together, these data demonstrate that the ability of pVHL to regulate reductive carboxylation and lipogenesis from glutamine tracks genetically with its ability to bind and degrade HIF, at least in RCC cells.

HIF Is Sufficient to Induce RC from Glutamine in RCC Cells

To test the hypothesis that HIF-2α is sufficient to promote RC from glutamine, we expressed a pVHL-insensitive HIF-2α mutant (HIF-2α P405A/P531A, marked as HIF-2α P-A) in VHL-reconstituted 786-O cells (Figure 3). HIF-2α P-A is constitutively expressed in this polyclonal cell population, despite the reintroduction of wild-type VHL, reflecting a pseudohypoxia condition (Figure 3A). We confirmed that this mutant is transcriptionally active by assaying for the expression of its targets genes GLUT1, LDHA, HK1, EGLN, HIG2, and VEGF (Figures 3B and S3A). As shown in Figure 3C, reintroduction of wild-type VHLinto 786-O cells suppressed RC, whereas the expression of the constitutively active HIF-2α mutant was sufficient to stimulate this reaction, restoring the M1 enrichment of TCA cycle metabolites observed in VHL-deficient 786-O cells. Expression of HIF-2α P-A also led to a concomitant decrease in glucose oxidation, corroborating the metabolic alterations observed in glutamine metabolism (Figures 3D and 3E). Additional evidence of the HIF2α-regulation on the reductive phenotype was obtained with [U-13C5]glutamine, which generates M5 citrate, M3 fumarate, M3 malate, and M3 aspartate through RC (Figure 3F).

Our current work showed that HIF-2α is sufficient to induce the reductive program in RCC cells that express only the HIF-2α paralog, while mouse NEK cells appeared to use HIF-1α preferentially to promote RC. Together with the evidence that HIF-1α and HIF-2α may have opposite roles in tumor growth, it is possible that the cellular context dictates which paralog activates RC. It is also possible that HIF-2α adopts the RC regulatory function of HIF-1α upon deletion of the latter in RCC cells. Further studies are warranted in understanding the relative role of HIF-α paralogs in regulating RC in different cell types.

Finally, the selective sensitivity to glutaminase inhibitors exhibited by VHL-deficient cells, together with the observed RC activity in vivo, strongly suggests that reductive glutamine metabolism may fuel tumor growth. Investigating whether the reductive flux correlates with tumor hypoxia and/or contributes to the actual cell survival under low oxygen conditions is warranted. Together, our findings underscore the biological significance of reductive carboxylation in VHL-deficient RCC cells. Targeting this metabolic signature of HIF may open viable therapeutic opportunities for the treatment of hypoxic and VHL-deficient tumors.

Elevated levels of 14-3-3 proteins, serotonin, gamma enolase and pyruvate kinase identified in clinical samples from patients diagnosed with colorectal cancer
Dowling P, Hughes DJ, Larkin AM, Meiller J, …, Clynes M
Clin Chim Acta. 2015 Feb 20;441:133-41.


  • Identification of a number of significant proteins and metabolites in CRC patients
  • 14-3-3 proteins, serotonin, gamma enolase and pyruvate kinase all significant
  • Intense staining for 14-3-3 epsilon in tissue specimens from CRC patients
  • Tissue 14-3-3 epsilon levels concordant with abundance in the circulation
  • Biomolecules provide insight into the biology associated with tumor development

Background: Colorectal cancer (CRC), a heterogeneous disease that is common in both men and women, continues to be one of the predominant cancers worldwide. Lifestyle, diet, environmental factors and gene defects all contribute towards CRC development risk. Therefore, the identification of novel biomarkers to aid in the management of CRC is crucial. The aim of the present study was to identify candidate biomarkers for CRC, and to develop a better understanding of their role in tumorogenesis. Methods: In this study, both plasma and tissue samples from patients diagnosed with CRC, together with non-malignant and normal controls were examined using mass spectrometry based proteomics and metabolomics approaches.
Results: It was established that the level of several biomolecules, including serotonin, gamma enolase, pyruvate kinase and members of the 14-3-3 family of proteins, showed statistically significant changes when comparing malignant versus non-malignant patient samples, with a distinct pattern emerging mirroring cancer cell energy production. Conclusion: The diagnosis and management of CRC could be enhanced by the discovery and validation of new candidate biomarkers, as found in this study, aimed at facilitating early detection and/or patient stratification together with providing information on the complex behavior of cancer cells.

Table 2 – List of proteins found to show statistically significant differences between control (n=10) and CRC (n=16; 8 stage III/8 stage IV) patient plasma samples fractionated using Proteominer beads. Information provided in the table includes accession number, discovery platform used, protein description, the number of unique peptides for quantitation, a mascot score for protein identification (confidence number), ANOVA p-values(≥0.05), fold change in protein abundance (≥2-fold) and highest/lowest mean change.

Table 3 – List of metabolites found to show statistically significant differences between control (n=8) and CRC (n=16; 8 stage III/8 stage IV) patient plasma samples. Included in the table is the Human Metabolome Database (HMDB) entry, platform used to analyse the biochemicals, biochemical name, ANOVA p-values (≥0.05), fold-change and highest/lowest mean change.

Fig.1. Box and whisker plots for: (A) M2-PK, (B) gamma enolase, (C) 14-3-3 (pan) and (D) serotonin. ELISA analysisofM2-PK, gamma enolase, serotonin and 14-3-3 (pan) in plasma samples from control (n = 20), polyps (n = 10), adenoma (n = 10), stage I/II CRC (n= 20) and stage III/IV (n= 20)patients. The figures show statistically significant p-value for various comparisons between the different sample groups. This ELISA measurement for 14-3-3 detects all known isoforms of mammalian 14-3-3 proteins (β/α, γ, ε, η, ζ/δ, θ/τ and σ).

Role of lipid peroxidation derived 4-hydroxynonenal (4-HNE) in cancer- Focusing on mitochondria
Huiqin Zhonga, Huiyong Yin
Redox Biol Apr 2015; 4: 193–199

Oxidative stress-induced lipid peroxidation has been associated with human physiology and diseases including cancer. Overwhelming data suggest that reactive lipid mediators generated from this process, such as 4-hydroxynonenal (4-HNE), are biomarkers for oxidative stress and important players for mediating a number of signaling pathways. The biological effects of 4-HNE are primarily due to covalent modification of important biomolecules including proteins, DNA, and phospholipids containing amino group. In this review, we summarize recent progress on the role of 4-HNE in pathogenesis of cancer and focus on the involvement of mitochondria: generation of 4-HNE from oxidation of mitochondria-specific phospholipid cardiolipin; covalent modification of mitochondrial proteins, lipids, and DNA; potential therapeutic strategies for targeting mitochondrial ROS generation, lipid peroxidation, and 4-HNE.

Reactive oxygen species (ROS), such as superoxide anion, hydrogen peroxide, hydroxyl radicals, singlet oxygen, and lipid peroxyl radicals, are ubiquitous and considered as byproducts of aerobic life [1]. Most of these chemically reactive molecules are short-lived and react with surrounding molecules at the site of formation while some of the more stable molecules diffuse and cause damages far away from their sites of generation. Overproduction of these ROS, termed oxidative stress, may provoke oxidation of polyunsaturated fatty acids (PUFAs) in cellular membranes through free radical chain reactions and form lipid hydroperoxides as primary products [2]; some of these primary oxidation products may decompose and lead to the formation of reactive lipid electrophiles. Among these lipid peroxidation (LPO) products, 4-hydroxy-2-nonenals (4-HNE) represents one of the most bioactive and well-studied lipid alkenals [3]. 4-HNE can modulate a number of signaling processes mainly through forming covalent adducts with nucleophilic functional groups in proteins, nucleic acids, and membrane lipids. These properties have been extensively summarized in some excellent reviews [4], [5], [6], [7], [8], [9] and [10].


Lipid peroxidation-derived 4-HNE is a prototypical reactive lipid electrophile that readily forms covalent adducts with nucleophilic functional groups in macromolecule such as proteins, DNA, and lipids (Fig. 3). A body of work have shown that generation of 4-HNE macromolecule adducts plays important pathological roles in cancer through interactions with mitochondria. First of all, mitochondria are one of the most important cellular sites of 4-HNE production, presumably from oxidation of abundant PUFA-containing lipids, such as L4CL. Emerging evidence suggest that this process play a critical role in apoptosis. Secondly, in response to the toxicity of 4-HNE, mitochondria have developed a number of defense mechanisms to convert 4-HNE to less reactive chemical species and minimize its toxic effects. Thirdly, 4-HNE macromolecule adducts in mitochondria are involved in the cancer initiation and progression by modulating mitochondrial function and metabolic reprogramming. 4-HNE protein adducts have been widely studied but the mtDNA modification by lipid electrophiles has yet to emerge. The biological consequence of PE modification remains to be defined, especially in the context of cancer. Last but not the least, manipulation of mitochondrial ROS generation, lipid peroxidation, and production of lipid electrophiles may be a viable approach for cancer prevention and treatment.

K.J. Davies. Oxidative stress, antioxidant defenses, and damage removal, repair, and replacement systems. IUBMB Life, 50 (4–5) (2000): 279–289.

Shoeb, N.H. Ansari, S.K. Srivastava, K.V. Ramana. 4-hydroxynonenal in the pathogenesis and progression of human diseases. Current Medicinal Chemistry, 21 (2) (2014):230–237 23848536

J.D. West, L.J. Marnett. Endogenous reactive intermediates as modulators of cell signaling and cell death. Chemical Research in Toxicology, 19 (2)(2006): 173–194

Barrera, S. Pizzimenti,…, A. Lepore, et al. Role of 4-hydroxynonenal-protein adducts in human diseases. Antioxidants & Redox Signaling (2014) 25365742

J.R. Roede, D.P. Jones. Reactive species and mitochondrial dysfunction: mechanistic significance of 4-hydroxynonenal. Environmental and Molecular Mutagenesis, 51 (5) (2010):380–390 20544880

Guéraud, M. Atalay, N. Bresgen, …, I. Jouanin, W. Siems, K. Uchida. Chemistry and biochemistry of lipid peroxidation products. Free Radical Research, 44 (10) (2010): 1098–1124

Z.H. Chen, E. Niki. 4-hydroxynonenal (4-HNE) has been widely accepted as an inducer of oxidative stress. Is this the whole truth about it or can 4-HNE also exert protective effects? IUBMB Life, 58 (5–6) (2006): 372–373. 16754333

Aldini, M. Carini, K.-J. Yeum, G. Vistoli. Novel molecular approaches for improving enzymatic and nonenzymatic detoxification of 4-hydroxynonenal: toward the discovery of a novel class of bioactive compounds. Free Radical Biology and Medicine, 69 (0) (2014): 145–156 24456906

Fig. 2.   Catabolism of 4-HNE in mitochondria. ROS induced lipid peroxidation in IMM and OMM (outer membrane of mitochondria) leads to 4-HNE formation. In matrix, 4-HNE conjugation with GSH produces glutathionyl-HNE (GS-HNE); this process occurs spontaneously or can be catalyzed by GSTs. 4-HNE is reduced to 1,4-dihydroxy-2-nonene (DHN) catalyzed ADH or AKRs. ALDH2 catalyzes the oxidation of 4-HNE to form 4-hydroxy-2-nonenoic acid (HNA).

Role of 4-hydroxynonenal in cancer focusing on mitochondria

Role of 4-hydroxynonenal in cancer focusing on mitochondria

Role of 4-hydroxynonenal in cancer focusing on mitochondria

Fig. 3. A schematic view of 4-HNE macromolecule adducts in cancer cell. 4-HNE macromolecule adducts are involved in cancer initiation, progression, metabolic reprogramming, and cell death. 4-HNE (depicted as a zigzag line) is produced through ROS-induced lipid peroxidation of mitochondrial and plasma membranes. Biological consequences of 4-HNE adduction:

  1. reducing membrane integrity;
  2. affecting protein function in cytosol;
  3. causing nuclear and mitochondrial DNA damage;
  4. inhibiting ETC activity;
  5. activating UCPs activity;
  6. reducing TCA activity;
  7. inhibiting ALDH2 activity.

DNA methylation paradigm shift: 15-lipoxygenase-1 upregulation in prostatic intraepithelial neoplasia and prostate cancer by atypical promoter hypermethylation.
Kelavkar UP1, Harya NS, … , Chandran U, Dhir R, O’Keefe DS.
Prostaglandins Other Lipid Mediat. 2007 Jan; 82(1-4):185-97

Fifteen (15)-lipoxygenase type 1 (15-LO-1, ALOX15), a highly regulated, tissue- and cell-type-specific lipid-peroxidating enzyme has several functions ranging from physiological membrane remodeling, pathogenesis of atherosclerosis, inflammation and carcinogenesis. Several of our findings support a possible role for 15-LO-1 in prostate cancer (PCa) tumorigenesis. In the present study, we identified a CpG island in the 15-LO-1 promoter and demonstrate that the methylation status of a specific CpG within this island region is associated with transcriptional activation or repression of the 15-LO-1 gene. High levels of 15-LO-1 expression was exclusively correlated with one of the CpG dinucleotides within the 15-LO-1 promoter in all examined PCa cell-lines expressing 15-LO-1 mRNA. We examined the methylation status of this specific CpG in microdissected high grade prostatic intraepithelial neoplasia (HGPIN), PCa, metastatic human prostate tissues, normal prostate cell lines and human donor (normal) prostates. Methylation of this CpG correlated with HGPIN, PCa and metastatic human prostate tissues, while this CpG was unmethylated in all of the normal prostate cell lines and human donor (normal) prostates that either did not display or had minimal basal 15-LO-1 expression. Immunohistochemistry for 15-LO-1 was performed in prostates from PCa patients with Gleason scores 6, 7 [(4+3) and (3+4)], >7 with metastasis, (8-10) and 5 normal (donor) individual males. Quantitative reverse transcription-polymerase chain reaction (qRT-PCR) was used to detect 15-LO-1 in PrEC, RWPE-1, BPH-1, DU-145, LAPC-4, LNCaP, MDAPCa2b and PC-3 cell lines. The specific methylated CpG dinucleotide within the CpG island of the 15-LO-1 promoter was identified by bisulfite sequencing from these cell lines. The methylation status was determined by COBRA analyses of one specific CpG dinucleotide within the 15-LO-1 promoter in these cell lines and in prostates from patients and normal individuals. Fifteen-LO-1, GSTPi and beta-actin mRNA expression in BPH-1, LNCaP and MDAPCa2b cell lines with or without 5-aza-2′-deoxycytidine (5-aza-dC) and trichostatin-A (TSA) treatment were investigated by qRT-PCR. Complete or partial methylation of 15-LO-1 promoter was observed in all PCa patients but the normal donor prostates showed significantly less or no methylation. Exposure of LNCAP and MDAPCa2b cell lines to 5-aza-dC and TSA resulted in the downregulation of 15-LO-1 gene expression. Our results demonstrate that 15-LO-1 promoter methylation is frequently present in PCa patients and identify a new role for epigenetic phenomenon in PCa wherein hypermethylation of the 15-LO-1 promoter leads to the upregulation of 15-LO-1 expression and enzyme activity contributes to PCa initiation and progression.

Transcriptional regulation of 15-lipoxygenase expression by promoter methylation.
Liu C1, Xu D, Sjöberg J, Forsell P, Björkholm M, Claesson H
Exp Cell Res. 2004 Jul 1; 297(1):61-7.

15-Lipoxygenase type 1 (15-LO), a lipid-peroxidating enzyme implicated in physiological membrane remodeling and the pathogenesis of atherosclerosis, inflammation, and carcinogenesis, is highly regulated and expressed in a tissue- and cell-type-specific fashion. It is known that interleukins (IL) 4 and 13 play important roles in transactivating the 15-LO gene. However, the fact that they only exert such effects on a few types of cells suggests additional mechanism(s) for the profile control of 15-LO expression. In the present study, we demonstrate that hyper- and hypomethylation of CpG islands in the 15-LO promoter region is intimately associated with the transcriptional repression and activation of the 15-LO gene, respectively. The 15-LO promoter was exclusively methylated in all examined cells incapable of expressing 15-LO (certain solid tumor and human lymphoma cell lines and human T lymphocytes) while unmethylated in 15-LO-competent cells (the human airway epithelial cell line A549 and human monocytes) where 15-LO expression is IL4-inducible. Inhibition of DNA methylation in L428 lymphoma cells restores IL4 inducibility to 15-LO expression. Consistent with this, the unmethylated 15-LO promoter reporter construct exhibited threefold higher activity in A549 cells compared to its methylated counterpart. Taken together, demethylation of the 15-LO promoter is a prerequisite for the gene transactivation, which contributes to tissue- and cell-type-specific regulation of 15-LO expression.

mechanism of the lipoxygenase reaction

Radical mechanism of the lipoxygenase reaction pattabhiraman

Radical mechanism of the lipoxygenase reaction pattabhiraman

Position determinants of lipoxygenase reaction pattabhiraman

Position determinants of lipoxygenase reaction pattabhiraman

Position determinants of lipoxygenase reaction

This suggests that the space inside the active site cavity plays an important role in the positional specificity (Borngräber et al., 1999). The reverse process on 12-LOX works equally well (Suzuki et al., 1994; Watanabe and Haeggstrom, 1993). However, conversion to 5-LOX by mutagenesis has not been successful. The positional determinant residues on 15-LOX were mutated to those of 5-LOX but the enzyme was inactive (Sloane et al., 1990). 15-LOX possess the ability to oxygenate 15-HpETE to form 5, 15-diHpETE. Methylation of carboxy end of the substrate increased the activity significantly. This phenomenon was hypothesised to be due to an inverse orientation of the substrate at the active site. In this case the caroboxy end may slide into the cavity as suggested by experiments with modified [page 6↓]substrates and site directed mutagenesis (Schwarz et al., 1998; Walther et al., 2001). Thus, the determinant of positional specificity is not only the volume but also the orientation of the substrate in the active site.

The N-terminal domain of the enzyme does not play a major role in the dioxygenation reaction of 12/15 lipoxygenase. N-terminal domain truncations did not impair the lipoxygenase activity. The ability of the enzyme to bind to membranes, however, is impaired in the mutants (point and truncations) of the N-ternimal domain without significant alterations to the catalytic activity (Walther et al., 2002). Mutation to Trp 181, which is localised in the catalytic domain, also impaired membrane binding function. This suggests that the C-terminal domain is responsible for the catalytic activity and a concerted action of N-terminal and C-terminal domain was necessary for effective membrane binding.

Metabolomic studies

New paradigms for metabolic modeling of human cells

Mardinoglu A, Nielsen J
Curr Opin Biotechnol. 2015 Jan 2; 34C:91-97.

integration of genetic and biochemical knowledge

integration of genetic and biochemical knowledge


  • We presented the timeline of generation and evaluation of global reconstructions of human metabolism.
  • We reviewed the generation of the context specific GEMs through the use of human generic GEMs.
  • We discussed the generation of multi-tissue GEMs in the context of whole-body metabolism.
  • We finally discussed the integration of GEMs with other biological networks.

Abnormalities in cellular functions are associated with the progression of human diseases, often resulting in metabolic reprogramming. GEnome-scale metabolic Models (GEMs) have enabled studying global metabolic reprogramming in connection with disease development in a systematic manner. Here we review recent work on reconstruction of GEMs for human cell/tissue types and cancer, and the use of GEMs for identification of metabolic changes occurring in response to disease development. We further discuss how GEMs can be used for the development of efficient therapeutic strategies. Finally, challenges in integration of cell/tissue models for simulation of whole body functions as well as integration of GEMs with other biological networks for generating complete cell/tissue models are presented.

Inter- and intra-tumor profiling of multi-regional colon cancer and metastasis
Kogita A, Yoshioka Y, …, Nakai T, Okuno K, Nishio K
Biochem Biophys Res Commun. 2015 Feb 27; 458(1):52-6.


  • Mutation profiling of tumors of multi-regional colon cancers using targeted sequencing.
  • Formalin-fixed paraffin embedded samples were available for next-generation sequencing.
  • Different clones existed in primary tumors and metastatic tumors.
  • Muti-clonalities between intra- and inter-tumors.

Intra- and inter-tumor heterogeneity may hinder personalized molecular-target treatment that depends on the somatic mutation profiles. We performed mutation profiling of formalin-fixed paraffin embedded tumors of multi-regional colon cancer and characterized the consequences of intra- and inter-tumor heterogeneity and metastasis using targeted re-sequencing. We performed targeted re-sequencing on multiple spatially separated samples obtained from multi-regional primary colon carcinoma and associated metastatic sites in two patients using next-generation sequencing. In Patient 1 with four primary tumors (P1-1, P1-2, P1-3, and P1-4) and one liver metastasis (H1), mutually exclusive pattern of mutations was observed in four primary tumors. Mutations in primary tumors were identified in three regions; KARS (G13D) and APC (R876*) in P1-2, TP53 (A161S) in P1-3, and KRAS (G12D), PIK3CA (Q546R), and ERBB4 (T272A) in P1-4. Similar combinatorial mutations were observed between P1-4 and H1. The ERBB4 (T272A) mutation observed in P1-4, however, disappeared in H1. In Patient 2 with two primary tumors (P2-1 and P2-2) and one liver metastasis (H2), mutually exclusive pattern of mutations were observed in two primary tumors. We identified mutations; KRAS (G12V), SMAD4 (N129K, R445*, and G508D), TP53 (R175H), and FGFR3 (R805W) in P2-1, and NRAS (Q61K) and FBXW7 (R425C) in P2-2. Similar combinatorial mutations were observed between P2-1 and H2. The SMAD4 (N129K and G508D) mutations observed in P2-1, however, were nor detected in H2. These results suggested that different clones existed in primary tumors and metastatic tumor in Patient 1 and 2 likely originated from P1-4 and P2-1, respectively. In conclusion, we detected the muti-clonalities between intra- and inter-tumors based on mutational profiling in multi-regional colon cancer using next-generation sequencing. Primary region from which metastasis originated could be speculated by mutation profile. Characterization of inter- and inter-tumor heterogeneity can lead to underestimation of the tumor genomics landscape and treatment strategy of personal medicine.

Fig.1. Treatment timelines for the two patients. A) Patient 1 (a 55-year-old man) had multifocal sigmoid colon cancers, and all of which were surgically resected in their entirety (P1-1, P1-2, P1-3, and P1-4). The patient received adjuvant chemotherapy (8 courses of XELOX). Eight months later, a single liver metastasis (H1) was detected, and the patients received neoadjuvant treatment of XELOX plus bevacizumab. Thereafter, he received a partial hepatectomy. B) Patient 2 (an 84-year-old woman) had cecal and sigmoid colon cancers (P2-1 and P2-2, respectively) with a single liver metastasis (H2). She received a subtotal colectomy and subsegmental hepatectomy.

Fig. 2. Schematic representation of intra-tumor heterogeneity in two patients. A) In patient 1, primary tumor (P1-4) contains two or more subclones. The clone without the ERBB4 (T272A) mutation created the liver metastasis. B) In patient 2, primary tumor (P2-1) contains two or more subclones. The clone without the SMAD4 (N129K and G508D) mutation created the liver metastasis.

Loss of Raf-1 Kinase Inhibitor Protein Expression Is Associated With Tumor Progression and Metastasis in Colorectal Cancer

Parham MinooInti ZlobecKristi BakerLuigi TornilloLuigi TerraccianoJeremy R. Jass, and Alessandro Lugli
American Journal of Clinical Pathology, 127, 820-827

Raf-1 kinase inhibitor protein (RKIP) is known as a critical down-regulator of the mitogen-activated protein kinase signaling pathway and a potential molecular determinant of malignant metastasis. The aim of this study was to determine the prognostic significance of RKIP expression in colorectal cancer (CRC). Immunohistochemical staining for RKIP was performed on a tissue microarray comprising 1,197 mismatch repair (MMR)-proficient and 141 MMR-deficient CRCs. The association of RKIP with clinicopathologic features was analyzed. Loss of cytoplasmic RKIP was associated with distant metastasis (P = .038), higher N stage (P = .032), vascular invasion (P = .01), and worse survival (P = .001) in the MMR-proficient group. In MMR-deficient CRCs, loss of cytoplasmic RKIP was associated with distant metastasis (P = .043) and independently predicted worse survival (P = .004). Methylation analysis of 28 cases showed that loss of RKIP expression is unlikely to be due to promoter methylation.

Raf-1 kinase inhibitor protein (RKIP) is a ubiquitously expressed and highly conserved protein that belongs to the phosphatidylethanolamine-binding protein family.1,2 RKIP is present in the cytoplasm and at the cell membrane3 and appears to have multiple biologic functions that implicate spermatogenesis, neural development, cardiac function, and membrane biogenesis.4-6 RKIP has also been shown to have a role in the regulation of multiple signaling pathways. Originally, RKIP was identified as a phospholipid-binding protein and, subsequently, as an interacting partner of Raf-1 kinase that blocks mitogen-activated protein kinase (MAPK) initiated by Raf-1.7 Initial studies showed that RKIP achieves this role by competitive interference with the binding of MEK to Raf-1.8 Recently, RKIP was shown to inhibit activation of Raf-1 by blocking phosphorylation of Raf-1 by p21-activated kinase and Src family kinases.9 It has also been suggested that RKIP could be involved in regulation of apoptosis by modulating the NF-κB pathway10 and in regulation of the spindle checkpoint via Aurora B.11 RKIP has also been implicated in tumor biology. In breast and prostate cancers, ectopic expression of RKIP sensitized cells to chemotherapeutic-induced apoptosis, and reduced expression of RKIP led to resistance to chemotherapy.12 A link between RKIP and cancer was first established in prostate cancer, with RKIP showing reduced expression in prostate cancer cells and the lowest expression levels in metastatic cells, suggesting that RKIP expression is inversely associated with the invasiveness of prostate cancer.13 Restoration of RKIP expression in metastatic prostate cancer cells inhibited invasiveness of the cells in vitro and in vivo in spontaneous lung metastasis but not the growth of the primary tumor in a murine model.13

Clinicopathologic Parameters The clinicopathologic data for 1,420 patients included T stage (T1, T2, T3, and T4), N stage (N0, N1, and N2), tumor grade (G1, G2, and G3), vascular invasion (presence or absence), and survival. The distribution of these features has been described previously.18-20 For 478 patients, information on local recurrence and distant metastasis was also available.

Methylation of RKIP Methylation of RKIP promoter was examined by methylation-specific polymerase chain reaction (PCR) using an AmpliTaq Gold kit (Roche, Branchburg, NJ) as described previously.25 The primers for amplification of the unmethylated sequence were 5′-TTTAGTGATATTTTTTGAGATATGA-3′ and 3′-CACTCCCTAACCTCTAATTAACCAA-5′ and for the methylated reaction were 5′-TTTAGCGATATTTTTTGAGATACGA-3′ and 3′-GCTCCCTAACCTCTAATTAACCG- 5′. The conditions for amplification were 10 minutes at 95°C followed by 39 cycles of denaturing at 95°C for 30 seconds, annealing at 52°C for 30 seconds, and 30 seconds of extension at 72°C. The PCR products were subjected to electrophoresis on 8% acrylamide gels and visualized by SYBR gold nucleic acid gel stain (Molecular Probes, Eugene, OR). CpGenome Universal Methylated DNA (Chemicon, Temecula, CA) was used as a positive control sample for methylation. Randomization of MMR-Proficient CRCs The 1,197 MMR-proficient CRCs were randomly assigned into 2 groups consisting of 599 (group 1) and 598 (group 2) cases and matched for sex, tumor location, T stage, N stage, tumor grade, vascular invasion, and survival ❚Table 1❚. Immunohistochemical cutoff scores for RKIP expression were determined for group 1, and the association of RKIP expression and T stage, N stage, tumor grade, vascular invasion, local recurrence, distant metastasis, and 10-year survival were studied in group 2.

❚Table 1❚ Characteristics of the Randomized Mismatch Repair–Proficient Subgroups of Colorectal Cancer Cases*

Variable p
Group Gp 1 (n=599) Gp 2 (n=598) 0.235
Sex M F M F
288 (48.3) 308






Tumor location Right-sided 417 (70.6) 417 (71.2) Left-sided 174 (29.4) 169 (28.8)
T1 T2 T3 T4
T stage 25 (4.3) 35 (6.0) 92(15.8) 97(16.7) 375(64.2)
N stage N0 N1 N2
289(50.7) 154(27.0) 154(26.9) 127(22.3) 120(21.0) 0.847
Tumor grade G1 G2 G3
14 (2.4) 13 (2.2) 503(86.7) 507(86.7) 63 (10.9) 65 (11.1) 0.969
Vascular invasion Presence 412 (70.9) 422 (72.1) Absence 169 (29.1) 163 (27.9) 0.643
Median survival, mo 68.0 (57.0-91.0) 76.0 (62.0-88.0) 0.59

(95% confidence interval) * Data are given as number (percentage) unless otherwise indicated.
Data were not available for all cases; percentages are based on the number of cases available for the variable, not the total number of cases in the group. Cases were assigned into groups matched for all variables listed. †
The χ2 test was used for sex, tumor location, T stage, N stage, tumor grade, and vascular invasion and log-rank test for survival analysis. P > .05 indicates that there is no difference between groups 1 and 2.
Breast and prostate cancer: more similar than different

Gail P. Risbridger1, Ian D. Davis2, Stephen N. Birrell3 & Wayne D. Tilley3
Nature Reviews Cancer 10, 205-212 (March 2010)

Breast cancer and prostate cancer are the two most common invasive cancers in women and men, respectively. Although these cancers arise in organs that are different in terms of anatomy and physiological function both organs require gonadal steroids for their development, and tumours that arise from them are typically hormone-dependent and have remarkable underlying biological similarities. Many of the recent advances in understanding the pathophysiology of breast and prostate cancers have paved the way for new treatment strategies. In this Opinion article we discuss some key issues common to breast and prostate cancer and how new insights into these cancers could improve patient outcomes.

Emerging field of metabolomics. Big promise for cancer biomarker identification and drug discovery
Patel S, Ahmed S.
J Pharm Biomed Anal. 2015 Mar 25; 107C:63-74.


  • Mass spectrometry, nuclear magnetic resonance and chemometrics have enabled cancer biomarker discovery.
  • Metabolomics can non-invasively identify biomarkers for diagnosis, prognosis and treatment of cancer.
  • All major types of cancers and their biomarkers discovered by metabolomics have been discussed.
  • This review sheds light on the pitfalls and potentials of metabolomics with respect to oncology.

Most cancers are lethal and metabolic alterations are considered a hallmark of this deadly disease. Genomics and proteomics have contributed vastly to understand cancer biology. Still there are missing links as downstream to them molecular divergence occurs. Metabolomics, the omic science that furnishes a dynamic portrait of metabolic profile is expected to bridge these gaps and boost cancer research. Metabolites being the end products are more stable than mRNAs or proteins. Previous studies have shown the efficacy of metabolomics in identifying biomarkers associated with diagnosis, prognosis and treatment of cancer. Metabolites are highly informative about the functional status of the biological system, owing to their proximity to organismal phenotypes. Scores of publications have reported about high-throughput data generation by cutting-edge analytic platforms (mass spectrometry and nuclear magnetic resonance). Further sophisticated statistical softwares (chemometrics) have enabled meaningful information extraction from the metabolomic data. Metabolomics studies have demonstrated the perturbation in glycolysis, tricarboxylic acid cycle, choline and fatty acid metabolism as traits of cancer cells. This review discusses the latest progress in this field, the future trends and the deficiencies to be surmounted for optimally implementation in oncology. The authors scoured through the most recent, high-impact papers archived in Pubmed, ScienceDirect, Wiley and Springer databases to compile this review to pique the interest of researchers towards cancer metabolomics.

Table.  Novel Cancer Markers Identified by Metabolomics

Quantitative analysis of acetyl-CoA production in hypoxic cancer cells reveals substantial contribution from acetate
Jurre J Kamphorst, Michelle K Chung, Jing Fan and Joshua D Rabinowitz
Cancer & Metabolism 2014, 2:23

Background: Cell growth requires fatty acids for membrane synthesis. Fatty acids are assembled from 2-carbon units in the form of acetyl-CoA (AcCoA). In nutrient and oxygen replete conditions, acetyl-CoA is predominantly derived from glucose. In hypoxia, however, flux from glucose to acetyl-CoA decreases, and the fractional contribution of glutamine to acetyl-CoA increases. The significance of other acetyl-CoA sources, however, has not been rigorously evaluated. Here we investigate quantitatively, using 13C-tracers and mass spectrometry, the sources of acetyl-CoA in hypoxia. Results: In normoxic conditions, cultured cells produced more than 90% of acetyl-CoA from glucose and glutamine-derived carbon. In hypoxic cells, this contribution dropped, ranging across cell lines from 50% to 80%. Thus, under hypoxia, one or more additional substrates significantly contribute to acetyl-CoA production. 13C-tracer experiments revealed that neither amino acids nor fatty acids are the primary source of this acetyl-CoA. Instead, the main additional source is acetate. A large contribution from acetate occurs despite it being present in the medium at a low concentration (50–500 μM). Conclusions: Acetate is an important source of acetyl-CoA in hypoxia. Inhibition of acetate metabolism may impair tumor growth.

Cancer cells have genetic mutations that drive proliferation. Such proliferation creates a continuous demand for structural components to produce daughter cells [13]. This includes demand for fatty acids for lipid membranes. Cancer cells can obtain fatty acids both through uptake from extracellular sources and through de novo synthesis, with the latter as a major route by which non-essential fatty acids are acquired in many cancer types [4,5].

The first fatty acid to be produced by de novo fatty acid synthesis is palmitate. The enzyme fatty acid synthase (FAS) makes palmitate by catalyzing the ligation and reduction of 8-acetyl (2-carbon) units donated by cytosolic acetyl-CoA. This 16-carbon fatty acid palmitate is then incorporated into structural lipids or subjected to additional elongation (again using acetyl-CoA) and desaturation reactions to produce the diversity of fatty acids required by the cell.

Acetyl-CoA sits at the interface between central carbon and fatty acid metabolism. In well-oxygenated conditions with abundant nutrients, its 2-carbon acetyl unit is largely produced from glucose. First, pyruvate dehydrogenase produces acetyl-CoA from glucose-derived pyruvate in the mitochondrion, followed by ligation of the acetyl group to oxaloacetate to produce citrate. Citrate is then transported into the cytosol and cytosolic acetyl-CoA produced by ATP citrate lyase.

In hypoxia, flux from glucose to acetyl-CoA is impaired. Low oxygen leads to the stabilization of the HIF1 complex, blocking pyruvate dehydrogenase (PDH) activity via activation of HIF1-responsive pyruvate dehydrogenase kinase 1 (PDK1) [6,7]. As a result, the glucose-derived carbon is shunted towards lactate rather than being used for generating acetyl-CoA, affecting carbon availability for fatty acid synthesis.

To understand how proliferating cells rearrange metabolism to maintain fatty acid synthesis under hypoxia, multiple studies focused on the role of glutamine as an alternative carbon donor[810]. The observation that citrate M+5 labeling from U-13C-glutamine increased in hypoxia led to the hypothesis that reductive carboxylation of glutamine-derived α-ketoglutarate enables hypoxic cells to maintain citrate and acetyl-CoA production. As was noted later, though, dropping citrate levels in hypoxic cells make the α-ketoglutarate to citrate conversion more reversible and an alternative explanation of the extensive citrate and fatty acid labeling from glutamine in hypoxia is isotope exchange without a net reductive flux [11]. Instead, we and others found that hypoxic cells can at least in part bypass the need for acetyl-CoA for fatty acid synthesis by scavenging serum fatty acids [12,13].

In addition to increased serum fatty acid scavenging, we observed a large fraction of fatty acid carbon (20%–50% depending on the cell line) in hypoxic cells not coming from either glucose or glutamine. Here, we used 13C-tracers and mass spectrometry to quantify the contribution from various carbon sources to acetyl-CoA and hence identify this unknown source. We found only a minor contribution of non-glutamine amino acids and of fatty acids to acetyl-CoA in hypoxia. Instead, acetate is the major previously unaccounted for carbon donor. Thus, acetate assimilation is a route by which hypoxic cells can maintain lipogenesis and thus proliferation.

Figure 1. Percentage 13C-labeling of cytosolic acetyl-CoA can be quantified from palmitate labeling. (A) Increasing 13C2-acetyl-CoA labeling shifts palmitate labeling pattern to the right. 13C2-acetyl-CoA labeling can be quantified by determining a best fit between observed palmitate labeling and computed binomial distributions (shown on right-hand side) from varying fractions of acetyl-CoA (AcCoA) labeling. (B) Steady-state palmitate labeling from U-13C-glucose and U-13C-glutamine in MDA-MB-468 cells. (C) Percentage acetyl-CoA production from glucose and glutamine. For (B) and (C), data are means ± SD of n = 3.

Fraction palmitate M + x = (16/x)(p)x (1−p)(16−x)

We applied this approach to MDA-MB-468 cells grown in medium containing U-13C-glucose and U-13C-glutamine. The resulting steady-state palmitate labeling patterns showed multiple heavily 13C-labeled forms as well as a remaining unlabeled M0 peak (Figure 1B). The M0-labeled form results from scavenging of unlabeled serum fatty acids and can be disregarded for the purpose of determining AcCoA labeling. From the remaining labeling distribution, we calculated 87% AcCoA labeling from glucose and 6% from glutamine, with 93% collectively accounted for by these two major carbon sources (Additional file 1: Figure S1). Similar results were also obtained for HeLa and A549 cells (Figure 1C)

Figure 2. Acetyl-CoA labeling from 13C-glucose and 13C-glutamine decreases in hypoxia. (A) Steady-state palmitate labeling from U-13C-glucose and U-13C-glutamine in normoxic and hypoxic (1% O2) conditions. (B) Percentage acetyl-CoA production from glucose and glutamine in hypoxia. (C) One or more additional carbon donors contribute substantially to acetyl-CoA production in hypoxia. Abbreviations: Gluc, glucose; Gln, glutamine. Data are means ± SD of n = 3.

Figure 3.  Amino acids (other than glutamine) and fatty acids are not major sources of cytosolic acetyl-CoA in hypoxia. (A) Palmitate labeling in hypoxic (1% O2) MDA-MB-468 cells, grown for 48 h in medium where branched chain amino acids plus lysine and threonine were substituted with their respective U-13C-labeled forms. (B) Same conditions, except that glucose and glutamine only or glucose and all amino acids, were substituted with the U-13C-labeled forms. (C) Palmitate labeling in hypoxic (1% O2) MDA-MB-468 cells, grown in medium supplemented with 20 μM U-13C-palmitate for 48 h. Data are means ± SD of n = 3.

Acetate is the main additional AcCoA carbon source in hypoxia

We next investigated if hypoxic cells could activate acetate to AcCoA. Although we used dialyzed serum in our experiments and acetate is not a component of DMEM, we contemplated the possibility that trace levels could still be present or that acetate is produced as a catabolic intermediate from other sources (for example from protein de-acetylation). We cultured MDA-MB-468 cells in 1% O2 in DMEM containing U-13C-glucose and U-13C-glutamine and added increasing amounts of U-13C-acetate (Figure 4A). AcCoA labeling rose considerably with increasing U-13C-acetate concentrations, from approximately 50% to 86% with 500 μM U-13C-acetate. No significant increase in labeling of AcCoA was observed in normoxic cells following incubation with U-13C-acetate. Thus, acetate selectively contributes to AcCoA in hypoxia.

Figure 4.  The main additional AcCoA source in hypoxia is acetate. (A) Percentage 13C2-acetyl-CoA labeling quantified from palmitate labeling in hypoxic (1% O2) and normoxic MDA-MB-468 cells grown in medium with U-13C-glucose and U-13C-glutamine and additionally supplemented with indicated concentrations of U-13C-acetate. (B) Acetate concentrations in fresh 10% DFBS, DMEM, and DMEM with 10% DFBS. (C) Percentage 13C2-acetyl-CoA labeling for hypoxic (1% O2) HeLa and A549 cells. For (A) and (C), data are means ± SD of n ≥ 2. For (B), data are means ± SEM of n = 3.

Tumors require a constant supply of fatty acids to sustain cellular replication. It is thought that most cancers derive a considerable fraction of the non-essential fatty acids through de novo synthesis. This requires AcCoA with its 2-carbon acetyl group acting as the carbon donor. In nutrient replete and well-oxygenated conditions, AcCoA is predominantly made from glucose. However, tumor cells often experience hypoxia, causing limited entry of glucose-carbon into the TCA cycle. This in turn affects AcCoA production, and it has been proposed that hypoxic cells can compensate by increasing AcCoA production from glutamine-derived carbon in a pathway involving reductive carboxylation of α-ketoglutarate [810].

Irrespective of the precise net contribution of acetate in hypoxia, a remarkable aspect is that a significant contribution occurs based only on contaminating acetate (~300 μM) in the culturing medium. This is considerably less than glucose (25 mM) or glutamine (4 mM). Acetate concentrations in the plasma of human subjects have been reported in the range of 50 to 650 μM [2225], and therefore, significant acetate conversion to AcCoA may occur in human tumors. This is supported by clinical observations that 11C-acetate PET can be used to image tumors, in particular those where conventional FDG-PET typically fails [26]. Our results indicate that 11C-acetate PET could be particularly important in notoriously hypoxic tumors, such as pancreatic cancer. Preliminary results provide evidence in this direction [27].

Finally, as our measurements of fatty acid labeling reflect specifically cytosolic AcCoA, it is likely that the cytosolic acetyl-CoA synthetase ACSS2 plays an important role in the observed acetate assimilation. Accordingly, inhibition of ACSS2 merits investigation as a potential therapeutic approach.

In hypoxic cultured cancer cells, one-quarter to one-half of cytosolic acetyl-CoA is not derived from glucose, glutamine, or other amino acids. A major additional acetyl-CoA source is acetate. Low concentrations of acetate (e.g., 50–650 μM) are found in the human plasma and also occur as contaminants in typical tissue culture media. These amounts are avidly incorporated into cellular acetyl-CoA selectively in hypoxia. Thus, 11C-acetate PET imaging may be useful for probing hypoxic tumors or tumor regions. Moreover, inhibiting acetate assimilation by targeting acetyl-CoA synthetases (e.g., ACSS2) may impair tumor growth.

Differential metabolomic analysis of the potential antiproliferative mechanism of olive leaf extract on the JIMT-1 breast cancer cell line
Barrajón-Catalán E, Taamalli A, Quirantes-Piné R, …, Micol V, Zarrouk M
J Pharm Biomed Anal. 2015 Feb; 105:156-62.

A new differential metabolomic approach has been developed to identify the phenolic cellular metabolites derived from breast cancer cells treated with a supercritical fluid extracted (SFE) olive leaf extract. The SFE extract was previously shown to have significant antiproliferative activity relative to several other olive leaf extracts examined in the same model. Upon SFE extract incubation of JIMT-1 human breast cancer cells, major metabolites were identified by using HPLC coupled to electrospray ionization quadrupole-time-of-flight mass spectrometry (ESI-Q-TOF-MS). After treatment, diosmetin was the most abundant intracellular metabolite, and it was accompanied by minor quantities of apigenin and luteolin. To identify the putative antiproliferative mechanism, the major metabolites and the complete extract were assayed for cell cycle, MAPK and PI3K proliferation pathways modulation. Incubation with only luteolin showed a significant effect in cell survival. Luteolin induced apoptosis, whereas the whole olive leaf extract incubation led to a significant cell cycle arrest at the G1 phase. The antiproliferative activity of both pure luteolin and olive leaf extract was mediated by the inactivation of the MAPK-proliferation pathway at the extracellular signal-related kinase (ERK1/2). However, the flavone concentration of the olive leaf extract did not fully explain the strong antiproliferative activity of the extract. Therefore, the effects of other compounds in the extract, probably at the membrane level, must be considered. The potential synergistic effects of the extract also deserve further attention. Our differential metabolomics approach identified the putative intracellular metabolites from a botanical extract that have antiproliferative effects, and this metabolomics approach can be expanded to other herbal extracts or pharmacological complex mixtures.

Pancreatic cancer early detection. Expanding higher-risk group with clinical and metabolomics parameters
Shiro Urayama
World J Gastroenterol. 2015 Feb 14; 21(6): 1707–1717.

Pancreatic ductal adenocarcinoma (PDAC) is the fourth and fifth leading cause of cancer death for each gender in developed countries. With lack of effective treatment and screening scheme available for the general population, the mortality rate is expected to increase over the next several decades in contrast to the other major malignancies such as lung, breast, prostate and colorectal cancers. Endoscopic ultrasound, with its highest level of detection capacity of smaller pancreatic lesions, is the commonly employed and preferred clinical imaging-based PDAC detection method. Various molecular biomarkers have been investigated for characterization of the disease, but none are shown to be useful or validated for clinical utilization for early detection. As seen from studies of a small subset of familial or genetically high-risk PDAC groups, the higher yield and utility of imaging-based screening methods are demonstrated for these groups. Multiple recent studies on the unique cancer metabolism including PDAC, demonstrate the potential for utility of the metabolites as the discriminant markers for this disease. In order to generate an early PDAC detection screening strategy available for a wider population, we propose to expand the population of higher risk PDAC group with combination clinical and metabolomics parameters.

Core tip: This is a summary of current pancreatic cancer cohort early detection studies and a potential approach being considered for future application. This is an area that requires heightened efforts as lack of effective treatment and screening scheme for wider population is leading this particular disease to be the second lethal cancer by 2030.

Currently, pancreatic ductal adenocarcinoma (PDAC) is the fourth major cause of cancer mortality in the United States[1]. It is predicted that 46420 new cases and 39590 deaths would result from pancreatic cancer in the United States in 2014[2]. Worldwide, there were 277668 new cases and 266029 deaths from this cancer in 2008[3]. In comparison to other major malignancies such as breast, colon, lung and prostate cancers with their respective 89%, 64%, 16%, 99% 5-year survival rate, PDAC at 6% is conspicuously low[2]. For PDAC, the only curative option is surgical resection, which is applicable in only 10%-15% of patients due to the common discovery of late stage at diagnosis[4]. In fact, PDAC is notorious for late stage discovery as evidenced by the low percentage of localized disease at diagnosis, compared to other malignancies: breast (61%), colon (40%), lung (16%), ovarian (19%), prostate (91%), and pancreatic cancer (7%) [5]. With the existing effective screening methods, the decreasing trends of cancer death rate are seen in major malignancies such as breast, prostate and colorectal cancer. In contrast, it is estimated that PDAC is expected to be surfacing as the second leading cause of cancer death by 2030[6].

With the distinct contribution of late-stage discovery and general lack of effective medical therapy, a critical approach in reversing the poor outcome of pancreatic cancer is to develop an early detection scheme for the tumor. In support of this, we see the trend that despite the poor prognosis of the disease, for those who have undergone curative resection with negative margins, the 5-year survival rate is 22% in contrast to 2% for the advanced-stage with distant metastasis[7,8]. An earlier diagnosis with tumor less than 2 cm (T1) is associated with a better 5-year survival of 58% compared to 17% for stage IIB PDAC[9]. Ariyama et al. [10] reported complete survival of 79 patients with less than 1 cm tumors after surgical resection. Furthermore, as a recent report indicates, the estimated time from the transformation to pre-metastatic growths of pancreatic cancer is approximately 15 years[11]; there is a wide potential window of opportunity to apply developing technologies in early detection of this cancer.

Current screening programs have demonstrated that the EUS evaluation can detect premalignant lesions and early cancers in certain small subset of high-risk groups. However, as the overwhelming majority of PDAC cases involve patients who develop the disease sporadically without a recognized genetic abnormality, the application of this modality for PDAC detection screening is very limited for the general adult population.

Select population based approach

Identification of a higher-PDAC-risk group: As the prevalence of PDAC in the general United States population over the age 55 is approximately 68 per 100000, a candidate discriminant test with a specificity of 98% and a sensitivity of 100% would generate 1999 false-positive test results and 68 true-positives[74]. Thus, relying on a single determinant for distinguishing the PDAC early-stage cases from the general population would necessitate a highly accurate test with a specificity of greater than 99%. More practical approach, then, would be to begin with a subset of population with a higher prevalence, and in conjunction with novel surrogate markers to curtail the at-risk subset, we could begin to identify the group with significantly increased PDAC risk for whom the endoscopic/imaging-based screening strategy could be applied.

An initial approach in selection of the screening population is to utilize selective clinical parameters that could be used to curtail the subset of the general population at increased PDAC risk. For instance, based on the epidemiological evidence, such clinical parameters include hyperglycemia or diabetes, which are noted in 50%-80% of pancreatic cancer patients [7579]. Though not encompassing all PDAC patients, this subset includes a much larger proportion of PDAC patients for whom we may select further for screening. Similarly, patients with a history of chronic pancreatitis or obesity are reported to have increased PDAC risk during their lifetime[8085].

With the recent advancement in the technology and resumed interest in the cancer-associated metabolic abnormality [89,90], application of metabolomics in the cancer field has attracted more attention [91]. Cancer-related metabolic reprogramming, Warburg effect, has been known since nearly a century ago in association with various solid tumors including PDAC [92], as cancer cells undergo energetically inefficient glycolysis even in the presence of oxygen in the environment (aerobic glycolysis)[93]. A number of common cancer mutations including Akt1, HIF (hypoxia-inducible factor), and p53 have been shown to support the Warburg effect through glycolysis and down-regulation of metabolite flux through the Krebs cycle [94101]. In PDAC, increased phosphorylation or activation of Akt1 has also been reported (illuminating on the importance of enzyme functionality)[102] as well as involvement of HIF1 in the tumor growth via effects on glycolytic process [103,104] and membrane-bound glycoprotein (MUC17) regulation [105] – reflective of activation of metabolic pathways. Further evidences of loss-of-function genetic mutations in key mitochondrial metabolic enzymes such as succinate dehydrogenase and fumarate hydratase, isocitrate dehydrogenase, phosphoglycerate dehydrogenase support carcinogenesis and the Warburg effect [106110]. Other important alternative pathways in cancer metabolism such as glutaminolysis and pyruvate kinase isoform suppression have been shown to accumulate respective upstream intermediates and reduction of associated end products such as NADPH, ribose-5-phosphate and nucleic acids [111-116]. As such, various groups have reported metabolomics biomarker applications for different cancers [117,118].

As a major organ involved in metabolic regulation in a healthy individual, pancreatic disorder such as malignancy is anticipated to influence the normal metabolism, presenting further rationale and interest in elucidating the implication of malignant transformation and PDAC development. Proteomic analysis of the pancreatic cancer cells demonstrated alteration in proteins involved in metabolic pathways including increased expression of glycolytic and reduced Krebs cycle enzymes, and accumulation of key proteins involved in glutamine metabolism, in support of Warburg effect. These in turn play significant role in nucleotide and amino acid biosynthesis required for sustaining the proliferating cancer cells[119]. Applications of sensitive mass spectrometric techniques in metabolomics study of PDAC detection biomarkers have led to identification of a set of small molecules or metabolites (or biochemical intermediates) that are potent discriminants of developing PDAC and the controls (See Figure ​1  as an example of metabolomics based analysis, allowing segregation of PDAC from benign cases). Recent reports from our group as well as others have demonstrated that specific candidate metabolites consisting of amino acids, bile acids, and a number of lipids and fatty acids – suspected to be reflective of tumor proliferation as well as many systemic response yet to be determined – were identified as potential discriminant for blood-based PDAC biomarkers[120-123]. As a further supporting data, elucidation of lipids and fatty acids as discriminant factors from PDAC and benign lesions from the cancer tissue and adjacent normal tissue has been reported recently[124].

metabolomics based analysis for PDC WJG-21-1707-g001

metabolomics based analysis for PDC WJG-21-1707-g001

Figure 1 Example of metabolomics based analysis, allowing segregation of pancreatic ductal adenocarcinoma from benign cases. Heat map illustration of discriminant capability of a metabolite set derived from gas chromatography and liquid chromatography/mass spectrometry …

By virtue of simultaneously depicting the multiple metabolite levels, metabolomics approach reveals various biochemical pathways that are uniquely involved in malignant conditions and has led to findings such as abnormalities of glycine and its mitochondrial biosynthetic pathway, as a potential therapeutic target in certain cancers[125]. Moreover, in combination with other systems biology approaches such as transcriptomics and proteomics, further refinement in characterization of cancer development and therapeutic targets as well as identification of potential biomarkers could be realized for PDAC. Since many enzymes in a metabolic network determine metabolites’ level and nonlinear quantitative relationship from the genes to the proteome and metabolome levels exist, a metabolome cannot be easily decomposed to a specific single marker, which will designate the cancer state[126]. Thus, in order to delineate a pathological state such as PDAC, multiple metabolomic features might be required for accurate depiction of a developing cancer. Future studies are anticipated to incorporate cancer systems’ biological knowledge, including metabolomics, for optimal designation of PDAC biomarkers, which would be utilized in conjunction with a clinical-parameter-derived population subset for establishing the PDAC screening population. Subsequently, further validation studies for the PDAC biomarkers need to be performed.

Current imaging-based detection and diagnostic methods for PDAC is effectively providing answers to clinical questions raised for patients with signs or symptoms of suspected pancreatic lesions. However, the endoscopic/imaging-based screening schemes are currently limited in applications to early PDAC detection in asymptomatic patients, aside from a small group of known genetically high-risk groups. There is a high demand for developing a method of selecting distinct subsets among the general population for implementing the endoscopic/imaging screening test effectively. Application of combinations of clinical risk parameters/factors with the developing molecular biomarkers from translational science such as metabolomics analysis brings hopes of providing us with early PDAC detection markers, and developing effective early detection screening scheme for the patients in the near future.

Serum metabolomic profiles evaluated after surgery may identify patients with estrogen receptor negative early breast cancer at increased risk of disease recurrence
Tenori L, Oakman C, Morris PG, …, Luchinat C, Di Leo A.
Mol Oncol. 2015 Jan; 9(1):128-39.

Purpose: Metabolomics is a global study of metabolites in biological samples. In this study we explored whether serum metabolomic spectra could distinguish between early and metastatic breast cancer patients and predict disease relapse. Methods: Serum samples were analysed from women with metastatic (n = 95) and predominantly oestrogen receptor (ER) negative early stage (n = 80) breast cancer using high resolution nuclear magnetic resonance spectroscopy. Multivariate statistics and a Random Forest classifier were used to create a prognostic model for disease relapse in early patients.
Results: In the early breast cancer training set (n = 40), metabolomics correctly distinguished between early and metastatic disease in 83.7% of cases. A prognostic risk model predicted relapse with 90% sensitivity (95% CI 74.9-94.8%), 67% specificity (95% CI 63.0-73.4%) and 73% predictive accuracy (95% CI 70.6-74.8%). These results were reproduced in an independent early breast cancer set (n = 40), with 82% sensitivity, 72% specificity and 75% predictive accuracy. Disease relapse was associated with significantly lower levels of histidine (p = 0.0003) and higher levels of glucose (p = 0.01), and lipids (p = 0.0003), compared with patients with no relapse.
Conclusions: The performance of a serum metabolomic prognostic model for disease relapse in individuals with ER-negative early stage breast cancer is promising. A confirmation study is ongoing to better define the potential of metabolomics as a host and tumour-derived prognostic tool.

Figure 1 e Clusterization of serum metabolomic profiles. Discrimination between metastatic (green, n [ 95) and early (red, n [ 40) breast cancer patients using the random forest classifier. (a) CPMG; (b) NOESY1D; (c) Diffusion.

Figure 2 e Training set. Comparison between metabolomic classification and actual relapse. The receiver operator curves (ROC) and the area under the curve (AUC) scores are presented for CPMG, NOESY1D and Diffusion.

Figure 3 e Validation set. Comparison between CPMG random forest risk score metabolomic classification and actual relapse The receiver operator curve (ROC) and the area under the curve (AUC) score are presented for the CPMG analysis.

Figure 4 e Discriminant metabolites. Discriminant metabolites (p < 0.05) between profiles from early (green, n [ 80) and metastatic (red, n [ 95) breast cancer patients. Box and whisker plots: horizontal line within the box [ mean; bottom and top lines of the box [ 25th and 75th percentiles, respectively; bottom and top whiskers [ 5th and 95th percentiles, respectively. Median values (arbitrary units) are provided in the associated table, along with raw p values and p values adjusted for multiple testing. pts: patients.

Transparency in metabolic network reconstruction enables scalable biological discovery
Benjamin D Heavner, Nathan D Price
Current Opinion in Biotechnology, Aug 2015; 34: 105–109

  • Assembling a network reconstruction can reveal knowledge gaps.
  • Building a functional metabolic model enables testable prediction.
  • Recent work has found that most models contain the same reactions.
  • Reconstruction and functional model building should be explicitly separated.

Reconstructing metabolic pathways has long been a focus of active research. Now, draft models can be generated from genomic annotation and used to simulate metabolic fluxes of mass and energy at the whole-cell scale. This approach has led to an explosion in the number of functional metabolic network models. However, more models have not led to expanded coverage of metabolic reactions known to occur in the biosphere. Thus, there exists opportunity to reconsider the process of reconstruction and model derivation to better support the less-scalable investigative processes of biocuration and experimentation. Realizing this opportunity to improve our knowledge of metabolism requires developing new tools that make reconstructions more useful by highlighting metabolic network knowledge limitations to guide future research.

metabolic network reconstruction

metabolic network reconstruction

Mapping metabolic pathways has been a focus of significant scientific efforts dating from the emergence of biochemistry as a distinct scientific field in the late 19th century [1]. This endeavor remains an important effort for at least two compelling reasons. First, cataloguing and characterizing the full range of metabolic processes across species (which because of genomics are being discovered at an incredible pace) is a fundamentally important step towards a complete understanding of our ecological environment. Second, mapping metabolic pathways in organisms — many of which can be found with specialized properties shaped by their environment — facilitates metabolic engineering to advance nascent industrial biotechnology efforts ranging from augmenting/replacing petroleum-derived chemical precursors or fuels to biopharmaceutical production [2]. However, despite laudable efforts to enable high-throughput ‘genomic enzymology’ [3•], the traditional biochemical approaches of enzyme expression, purification, and characterization remain time-intensive, capital-intensive, and labor-intensive, and have not expanded in scale like our ability to identify and characterize life genomically. Characterizing new metabolic function is further hampered by the challenge of cultivating environmental isolates in laboratory conditions [4]. Fortunately, recent efforts to leverage genome functional annotation and established knowledge of biochemistry have enabled the computational assembly of ‘draft metabolic reconstructions’ [5], which are parts lists of metabolic network components. In this context, a reconstruction is not just the information embodied in the stoichiometric matrix describing metabolic network structure, but also the associated metadata and annotation that entails an organism-specific knowledge base. Such a reconstruction can serve as the basis for making functional models amenable to mathematical simulation. Thus, a reconstruction is a bottom-up assembly of biochemical information, and a model can serve as a framework for integrating top-down information (for example, model constraints can be generated from statistically inferred gene regulatory networks [6]). Such computational approaches are significantly faster and less expensive than biochemical characterization [7]. They are also providing new resources facilitate cultivation of novel environmental isolates [8], and the scope of draft metabolic network coverage across the biome has increased much faster than wet lab characterization. If the distinction between reconstruction and model formulation can be strengthened and supported through software implementation, there is great opportunity for using both tasks to further advance rapid discovery of biological function.

The iterative process of manual curation of a draft metabolic network reconstruction to assemble a higher confidence compendium of organism-specific metabolism (a process termed ‘biocuration’ [9 and 10]) remains time-intensive and labor-intensive. Biocuration of metabolic reconstructions currently advances on a decadal time scale [11 and 12]. Thus, much research effort has focused instead on developing techniques for rapid development of models that are amenable to simulation [13 and 14]. Thousands of models have been derived from automatically assembled draft reconstructions [15], but most of these models consist of highly conserved portions of metabolism since they are propagated primarily via orthology. Though the number of models is large, they do not reflect the true diversity of cellular metabolic capabilities across different organisms [16•]. Applying the rapid and scalable process of draft network reconstruction to support and accelerate the less-scalable processes of biocuration and in vitro or in vivo experimentation remains an unrealized opportunity. The path forward should focus on increased emphasis on transparently documenting the reconstruction process and developing tools to highlight, rather than obscure, knowledge limitations that ultimately cause limitations to model predictive accuracy.

More explicit annotation of metabolic network reconstruction and model derivation steps can help direct research efforts

Testing implicit hypotheses arising from reconstruction assembly provides one opportunity for guiding experimental efforts. However, the very act of identifying ambiguous information in the literature should also be exploited to contribute to experimental efforts, independent of the choices a researcher makes in assembling a reconstruction. Preliminary steps to facilitate large-scale computational identification of biological uncertainty have been made, such as the development of the Evidence Ontology [18]. However, realizing the potential for using reconstruction assembly to highlight experimental opportunities will require a broader shift to emphasize the limits of our knowledge, rather than only the predictive power of a model that can be derived from a reconstruction. Computational reconstruction of metabolic networks provides two distinct opportunities for guiding experimental efforts even before a mathematically computable model is derived from the assembled knowledge: highlighting areas of uncertainty in the current knowledge of an organism, and introducing hypotheses of metabolic function as choices are made throughout biocuration efforts.

The subsequent process of deriving a mathematically computable model from a reconstruction provides additional opportunities for scalable hypothesis generation that could be exploited to inform experimental efforts. While stoichiometrically constrained models derived from reconstructions are ‘parameter-light’ when compared to dynamic enzyme kinetic models, they are not really ‘parameter free’ [19]. As modelers derive a model from an assembled reconstruction, they must make choices. And, like the ambiguities and choices that are made and should be highlighted in assembling a reconstruction, highlighting the choices made in deriving a model provides further opportunity for scalable hypothesis generation. Examples of choices that often arise in deriving a functional model include adding intracellular transport reactions, filling network gaps, or trimming network dead ends to improve network connectivity [20]. Researchers seeking to conduct Flux Balance Analysis (FBA) [21] or similar approaches must formulate an objective function, can include testable parameters such as ATP maintenance requirements, and can compare model predictions to designated reference phenotype observations. Each of these model-building and tuning activities presents opportunities to rapidly develop and prioritize new hypotheses of metabolic function.

The effort to computationally reconstruct biochemical knowledge to compile organism-specific reconstructions, and to derive computable models from these reconstructions, is a relatively young field of research with abundant opportunity for facilitating biological discovery of metabolic function. Judgment is required in assembling a reconstruction, and there should be careful consideration of the fact that judgment calls represent an implicit hypothesis. Making these hypotheses more explicit would help guide subsequent investigation. Bernhard Palsson and colleagues call for ‘an open discussion to define the minimal quality criteria for a genome scale reconstruction’ [16•] — an effort we fully support. We believe that such a beneficial ‘minimal quality criteria’ should be guided by the goals of reproducibility and transparency, including those aspects that can help to guide discovery of novel gene functions.

Read Full Post »

Mitochondrial Dysfunction and Cardiac Disorders

Curator: Larry H Bernstein, MD, FACP

This article is the THIRD in a four-article Series covering the topic of the Roles of the Mitochondria in Cardiovascular Diseases. They include the following;

  • Mitochondria and Cardiovascular Disease: A Tribute to Richard Bing, Larry H Bernstein, MD, FACP

  • Mitochondrial Metabolism and Cardiac Function, Larry H Bernstein, MD, FACP

  • Mitochondrial Dysfunction and Cardiac Disorders, Larry H Bernstein, MD, FACP

Mitochondrial Metabolism in Impaired Cardiac Function

Mitochondrial Dysfunction and the Heart

Chronically elevated plasma free fatty acid levels in heart failure are associated with
  • decreased metabolic efficiency and cellular insulin resistance.
The mitochondrial theory of aging (MTA) and the free-radical theory of aging (FRTA) are closely related.
They were in fact proposed by the same researcher about 20 years apart. MTA adds
  • the mitochondria and its production of free radicals
  • into the concept that free-radicals damage DNA over time.
Tissue hypoxia, resulting from low cardiac output with or independent of endothelial impairment,
This dysfunctional state causes loss of mitochondrial mass. Therapies aimed at protecting mitochondrial function
  • have shown promise in patients and animal models with heart failure that will be the subject of Chapter III.

Myocardial function in hypertension

Genetic variation in vitamin D-dependent signaling
  • is associated with congestive heart failure in human subjects with hypertension.
Functional polymorphisms were selected from five candidate genes:
  1. CYP27B1,
  2. CYP24A1,
  3. VDR,
  4. REN and
  5. ACE.
Using the Marshfield Clinic Personalized Medicine Research Project,
  • 205 subjects with hypertension and congestive heart failure,
  • 206 subjects with hypertension alone and
  • 206 controls (frequency matched by age and gender) were genotyped.
In the context of hypertension, a SNP in CYP27B1 was associated with congestive heart failure
(odds ratio: 2.14 for subjects homozygous for the C allele; 95% CI: 1.05–4.39).
Genetic variation in vitamin D biosynthesis is associated with increased risk of heart failure.
RA Wilke, RU Simpson, BN Mukesh, SV Bhupathi, et al. Genetic variation in CYP27B1 is associated

Heart Failure and Coronary Circulation

There is a decrease in resting and peak stress myocardial function in chronic heart failure patients,
  • with recovery of skeletal muscle phosphocreatine following exercise induced by perhexiline treatment.
This suggested that mitochondrial deficiencies, caused by excessive free fatty acids (FFAs)
  • underlie a common cardiac and skeletal muscle myopathy in heart failure patients.
Tissue hypoxia in chronic heart failure from inadequate circulation in heart failure
  • increases the oxidative stress in lean body mass and in the heart itself.
The heterodimeric transcription factor hypoxia-inducible factor (HIF)-1
  • induces changes in the transcription of genes that encode proteins involved in the adaptation to hypoxia.
HIF-1 activity depends on levels of the HIF-1a subunit, which has a short half-life.
HIF-1a increases in rats with experimentally induced myocardial infarction together with elevated levels of
  • GLUT1 and haemoxygenase-1 in the peri-infarct region of the heart
The cardiac metabolic response to hypoxia is considered to be
  • a return to a pattern of fetal metabolism, in which
  • carbohydrates predominate as substrates for energy metabolism.
The reliance on carbohydrate energy source is thought to be a result of  the downregulation of PPARa with a decreased activity of
The sarcolemmal fatty acid transporter protein (FATP) levels are also decreased with palmitate oxidation,
  • transitioning away from fatty acid metabolism proportional to the degree of cardiac impairment.
The hypoxic changes of heart failure drives a switch toward
  1. glycolysis and glucose oxidation
  2. restriction of myocardial fatty acid uptake.
Nevertheless, late in the progression of heart failure, substrate metabolism is insufficient to support cardiac function, because
  • the hypoxic failing heart is no longer able to oxidize fats and may also be insulin resistant.
The author surmises that mitochondrial dysfunction caused by tissue hypoxia might be mediated by the
  • proapoptotic protein BCL2/adenovirus E1B 19kDa interacting protein (Bnip)3.
It  is strongly upregulated in response to hypoxia. In the isolated, perfused rat heart, Bnip3 expression was
  • induced after 1h of hypoxia, with Bnip3 integrating into the mitochondria of hypoxic ventricular myocytes.
This resulted in mitochondrial defects associated with
  1. opening of the permeability transition pore, leading to
  2. loss of inner membrane integrity and
  3. loss of mitochondrial mass.

Mitochondrial Dysfunction caused by Bnip3 Precedes Cell Death.

Experimentally induced myocardial ischemia had evidence of contractile dysfunction but preserved viability. A progressive
  • decline in circulating levels of endothelial progenitor cells was documented 3 months following instrumentation (P<0.001).
Quantitative polymerase chain reaction analysis revealed that
  • chronic myocardial ischemia produced a biphasic response in both
    • hypoxic-inducible factor 1 and
    • stromal-derived factor 1 mRNA expression.
While initially unregulated, a gradual decline was observed over time (from day 45 to 90), in
  • hypoxic-inducible factor 1 and
  • stromal-derived factor 1 mRNA expression .
On serial assessment, endothelial progenitor cell migration was progressively impaired in response to chemo-attractant gradients of:
  1. vascular endothelial growth factor (10-200 ng/mL)
  2. and stromal cell-derived factor-1 (10-100 ng/mL) .
Decreased circulating levels and migratory dysfunction of bone marrow derived endothelial progenitor cells
  • were documented in a reproducible clinically relevant model of myocardial ischemia.

Nitric Oxide (NO) in Myocardial Ischemia and Infarct

Nitric oxide (NO) is a free radical with an unpaired electron; it is an important physiologic messenger,
  • produced by nitric oxide synthases, which catalyze the reaction l-arginine to citrulline and NO.
The constitutive isoforms exists in neuronal and endothelial cells and is calcium dependent. Calcium binds to calmodulin and
  1. the calcium calmodulin complex activates the constitutive NO synthase that releases NO,
  2. relaxing smooth muscle cells through activation of guanylate cyclase and the production cGMP.
Therefore, the NO produced has a negative inotropic effect on the heart and is instrumental in the autoregulation of the coronary circulation.
The inducible form of NO synthase (iNOS), mostly produced in macrophages, is activated by cytokines and endotoxin. It eliminates intracellular pathogens,
damaging cells by inhibiting
  1. ATP production
  2. oxidative phosphorylation
  3. DNA synthesis.
In infection, lipopolysaccharide released from bacterial walls, stimulates production of iNOS. The large amount of NO produced
  • causes extensive vasodilation and hypotension.
We sought to assess whether oxidation products of
  • nitric oxide (NO), nitrite (NO2−) and nitrate (NO3−), referred to as NOx,
  • are released by the heart of patients after acute myocardial infarction (AMI) and
  • whether NOx can be determined in peripheral blood of these patients.
Previously we reported that in experimental myocardial infarction (rabbits) NOx is released mainly by inflammatory cells
  • (macrophages) in the myocardium 3 days after onset of  ischemia.
NOx is formed in heart muscle from NO; It originates through the activity of the inducible form of nitric oxide synthase (iNOS).
Eight patients with acute anterior MI and an equal number of controls were studied. Coronary venous blood was obtained by
coronary sinus catheterization; NOx concentrations in coronary sinus, in arterial and peripheral venous plasma were measured.
Left ventricular end-diastolic pressure was determined. Measurements were carried out 24, 48 and 72 h after onset of symptoms.
The type and location of coronary arterial lesions were determined by coronary angiography. Plasma NO3− was reduced to NO2−
by nitrate reductase before determination of NO2− concentration by chemiluminescence.
The results provided evidence that in patients with acute anterior MI, the myocardial production of nitrite and nitrate (NOx) was increased,
  • as well as the coronary arterial–venous difference.
Increased NOx production by the infarcted heart accounted for the increase of NOx concentration in arterial and the peripheral venous plasma.
The peak elevation of NOx occurred on days 2 and 3 after onset of the symptoms, suggesting that NOx production was at least in part the result of
  • production of NO by inflammatory cells (macrophages) in the heart.
The appearance of oxidative products of NO (NO2− and NO3−) in peripheral blood of patients with acute MI is
  • the result of their increased release from infarcted heart during the inflammatory phase of myocardial ischemia.
Further studies are needed to define the clinical value of these observations.
K Akiyama,  A Kimura, H Suzuki, Y Takeyama, …. R Bing.  Production of oxidative products of nitric oxide in infarcted human heart.  J Am Coll Cardiol. 1998;32(2):373-379.
OPA1 Mutation and Late-Onset Cardiomyopathy
No cardiac disorders have been described in patients with OPA1 or similar mutations
  • involving the fission/fusion genes as seen in inherited maladies like Charcot–Marie–Tooth disease.
Our results indicate that, at least for OPA1, cardiac abnormalities are not completely
  • manifest until the development of blindness.

The OPA1-mutant mice survived more than 1 year and appeared healthy.

In patients with these diseases, reduced cardiac function may go undetected
secondary to reduced physical activity secondary to loss of vision.
It would be expected that patients with such mutations would have impaired cardiac reserve with
  • reduced ability to respond to high-stress disease states such as myocardial infarction and sepsis.
The OPA1-mutant mice have reduced cardiac reserve, as shown by
  • the lack of response to isoproterenol or to ischemia/reperfusion injury,
This suggests that patients with OPA1 and related inherited mitochondrial diseases
  • should be screened for abnormalities of cardiac function.
Le Chen; T Liu; A Tran; Xiyuan Lu; …AA. Knowlton. OPA1 Mutation and Late-Onset Cardiomyopathy:
Mitochondrial Dysfunction and mtDNA Instability.

Oxidative Stress and Mitochondria in the Failing Heart

The major problem in tissue hypoxia in the failing heart is oxidative stress. Reactive oxygen species (ROS), including
  • superoxide,
  • hydroxyl radicals and
  • hydrogen peroxide,
are generated by a number of cellular processes, including
  • mitochondrial electron transport,
  • NADPH oxidase and
  • xanthine dehydrogenase/xanthine oxidase.
The low availability of oxygen, the final receptor of mitochondrial electron transport (ET), results in
  • electron accumulation in the ET chain as the complexes become highly reduced.
A number of experimental and clinical studies have suggested that ROS generation is
  • enhanced in heart failure because of electron leak, and complexes I and II
  • are implicated as the primary sites of this loss.
Prolonged oxidative stress in cardiac failure results in damage to mitochondrial DNA.
The continued ROS generation and consequent cellular injury leads to functional decline.
Thus, mitochondria are both the sources and targets of a cycle of ROS-mediated injury in the failing heart.
Mice with a cardiac/skeletal muscle specific deficiency in the scavenger enzyme superoxide dismutase
  • developed progressive congestive heart failure
  • with defects in mitochondrial respiration.
Oxidative stress in these mice also caused specific morphological changes in cardiac mitochondria
  • characterized by decreased ATP levels,
  • impaired contractility,
  • dramatically restricted exercise capacity and
  • decreased survival.
This was in part corrected by treatment with the antioxidant superoxide dismutase mimetic, namely
  • manganese5,10,15,20-tetrakis-(4-benzoic acid)-porphyrin.
EUK-8, a superoxide dismutase and catalase mimetic improved survival and contractile parameters in a mutant mouse model
  • of pressure overload-induced oxidative stress and heart failure and in wild-type mice subjected to pressure overload.
In addition, mitochondria show
  • functional impairment and
  • morphological disorganization
in the left ventricle of Hypertrophic Cardiomyopathy (HCM)  patients without baseline systolic dysfunction.
These mitochondrial changes were associated with impaired myocardial contractile and relaxation reserves.
A strategy to protect the heart against oxidative stress could lie with
  • the modulation of mitochondrial electron transport itself.
Mild mitochondrial uncoupling may offer a potential cardioprotective effect by decreasing ROS production
  • preventing electron accumulation at complex III and
  • the Fe–S centres of complex I, and may therefore

mtDNA, Autophagy, and Heart Failure

Mitochondria are evolutionary endosymbionts derived from bacteria and contain DNA similar to bacterial DNA.
Mitochondria damaged by external haemodynamic stress are degraded by the autophagy/lysosome system in cardiomyocytes.
Mitochondrial DNA (mtDNA) that escapes from autophagy cell-autonomously leads to Toll-like receptor (TLR) 9-mediated
  • inflammatory responses in cardiomyocytes and
  • is capable of inducing myocarditis and dilated cardiomyopathy.
Cardiac-specific deletion of lysosomal deoxyribonuclease (DNase) II showed no cardiac phenotypes under baseline conditions,
but increased mortality and caused severe myocarditis and dilated cardiomyopathy 10 days after treatment with pressure overload.
Early in the pathogenesis, DNase II-deficient hearts showed
  • infiltration of inflammatory cells
  • increased messenger RNA expression of inflammatory cytokines
  • accumulation of mitochondrial DNA deposits in autolysosomes in the myocardium.
Administration of inhibitory oligodeoxynucleotides against TLR9, which is known to be activated by bacterial DNA6, or ablation of Tlr9
  • attenuated the development of cardiomyopathy in DNase II-deficient mice.
Furthermore, Tlr9 ablation
  • improved pressure overload-induced cardiac dysfunction and
  • inflammation even in mice with wild-type Dnase2a alleles.
These data provide new perspectives on the mechanism of genesis of chronic inflammation in failing hearts.
T Oka, S Hikoso, O Yamaguchi, M Taneike, T Takeda, T Tamai, et al.  Mitochondrial DNA that escapes from autophagy causes inflammation and heart failure.

Mitochondrial Dysfunction Increases Expression of Endothelin-1 and Induces Apoptosis

We developed an in vitro model of mitochondrial dysfunction using rotenone, a mitochondrial respiratory chain complex I inhibitor, and studied
  • preproendothelin-1 gene expression and apoptosis.
Rotenone greatly increased the gene expression of preproendothelin-1 in cardiomyocytes.
This result suggests that the gene expression of preproendothelin-1 is induced by the mitochondrial dysfunction.
Furthermore, treatment of cardiomyocytes with rotenone induced an elevation of caspase-3 activity, and caused a marked
  • increase in DNA laddering, an indication of apoptosis.
In conclusion, it is suggested that mitochondrial impairment in primary cultured cardiomyocytes induced by rotenone in vitro,
  • mimics some of the pathophysiological features of heart failure in vivo, and that ET-1 may have a role in myocardial dysfunction
    • with impairment of mitochondria in the failing heart.


This review focused on the evidence accumulated to the effect that mitochondria are key players in
  • the progression of congestive heart failure (CHF).
Mitochondria are the primary source of energy in the form of adenosine triphosphate that fuels the contractile apparatus,
  • essential for the mechanical activity and the Starling Effect of the heart.
We evaluate changes in mitochondrial morphology and alterations in the main components of mitochondrial energetics, such as
  • substrate utilization and
  • oxidative phosphorylation,
in the context of their contribution to the chronic energy deficit and mechanical dysfunction in HF.
Zachman AL, Page JM, Prabhakar G, Guelcher SA, and Sung HJ, “Elucidation of adhesion-dependent spontaneous apoptosis in macrophages using phase separated PEG/polyurethane films.”
Acta Biomater. 2012 Nov 2. S1742-7061(12)00530-2. 10.1016/j.actbio.2012.10.038.

Other Related articles published on this Open Access Scientific Journal, include the following:

Perspectives on Nitric Oxide in Disease Mechanisms: The Nitric Oxide Discovery, Function, and Targeted Therapy  Opportunities, 2013, Aviral Vatsa, PhD and Larry H Bernstein, MD, FACP, Editors, Amazon e-Books (forthcoming).

Mitochondria: More than just the “powerhouse of the cell” Ritu Saxena, Ph.D. Consultants: Aviva Lev-Ari, PhD, RN and Pnina G. Abir-Am, PhD 7/9/2012

Mitochondrial dynamics and cardiovascular diseases, Ritu Saxena, PhD 11/14/2012

Mitochondrial Damage and Repair under Oxidative Stress, Larry H Bernstein, MD, FACP 10/28/2012

Mitochondria: Origin from oxygen free environment, role in aerobic glycolysis, metabolic adaptation, Larry H Bernstein, MD, FACP 9/26/2012

Ca2+ signaling: transcriptional control, Larry H Bernstein, MD, FACP 3/6/2-13

MIT Scientists on Proteomics: All the Proteins in the Mitochondrial Matrix identified, Aviva Lev-Ari, PhD, RN 2/3/2013

Nitric Oxide has a ubiquitous role in the regulation of glycolysis -with a concomitant influence on mitochondrial function, Larry H Bernstein, MD, FACP 9/16/2012

Ubiquinin-Proteosome pathway, autophagy, the mitochondrion, proteolysis and cell apoptosis, Larry H Bernstein, MD, FACP 2/14/2013

Low Bioavailability of Nitric Oxide due to Misbalance in Cell Free Hemoglobin in Sickle Cell Disease – A Computational Model   Anamika Sarkar, PhD 11/9/2012

The rationale and use of inhaled NO in Pulmonary Artery Hypertension and Right Sided Heart Failure, , Larry H Bernstein, MD, FACP 8/20/2012

Clinical Trials Results for Endothelin System: Pathophysiological role in Chronic Heart Failure, Acute Coronary Syndromes and MI – Marker of Disease Severity or Genetic Determination? Aviva Lev-Ari, PhD, RN 10/19/2012

Endothelin Receptors in Cardiovascular Diseases: The Role of eNOS Stimulation, Aviva Lev-Ari, PhD, RN 10/4/2012

Inhibition of ET-1, ETA and ETA-ETB, Induction of NO production, stimulation of eNOS and Treatment Regime with PPAR-gamma agonists (TZD): cEPCs Endogenous Augmentation for Cardiovascular Risk Reduction – A Bibliography, Aviva Lev-Ari, PhD, RN 10/4/2012

Genomics & Genetics of Cardiovascular Disease Diagnoses: A Literature Survey of AHA’s Circulation Cardiovascular Genetics, 3/2010 – 3/2013, L H Bernstein, MD, FACP and Aviva Lev-Ari,PhD, RN  3/7/2013

Cardiovascular Disease (CVD) and the Role of agent alternatives in endothelial Nitric Oxide Synthase (eNOS) Activation and Nitric Oxide Production, Aviva Lev-Ari, PhD, RN 7/19/2012

Cardiovascular Risk Inflammatory Marker: Risk Assessment for Coronary Heart Disease and Ischemic Stroke – Atherosclerosis.

Aviva Lev-Ari, PhD, RN 10/30/2012

Cholesteryl Ester Transfer Protein (CETP) Inhibitor: Potential of Anacetrapib to treat Atherosclerosis and CAD, Aviva Lev-Ari, PhD, RN 4/7/2013

Hypertriglyceridemia concurrent Hyperlipidemia: Vertical Density Gradient Ultracentrifugation a Better Test to Prevent Undertreatment of High-Risk Cardiac Patients, Aviva Lev-Ari, PhD, RN  4/4/2013

Fight against Atherosclerotic Cardiovascular Disease: A Biologics not a Small Molecule – Recombinant Human lecithin-cholesterol acyltransferase (rhLCAT) attracted AstraZeneca to acquire AlphaCore, Aviva Lev-Ari, PhD, RN 4/3/2013

High-Density Lipoprotein (HDL): An Independent Predictor of Endothelial Function & Atherosclerosis, A Modulator, An Agonist, A Biomarker for Cardiovascular Risk, Aviva Lev-Ari, PhD, RN 3/31/2013

Peroxisome proliferator-activated receptor (PPAR-gamma) Receptors Activation: PPARγ transrepression for Angiogenesis in Cardiovascular Disease and PPARγ transactivation for Treatment of Diabetes, Aviva Lev-Ari, PhD, RN 11/13/2012γ-transrepression-for-angiogenesis-in-cardiovascular-disease-and-pparγ-transactivation-for-treatment-of-dia/

Sulfur-Deficiciency and Hyperhomocysteinemia, L H Bernstein, MD, FACP

Mitochondrial metabolism and cardiac function, L H Bernstein, MD, FACP
Cardiotoxicity and Cardiomyopathy Related to Drugs Adverse Effects, L H Bernstein, MD, FACP
Lp(a) Gene Variant Association, L H Bernstein, MD, FACP

Predicting Drug Toxicity for Acute Cardiac Events, L H Bernstein, MD, FACP

Amyloidosis with Cardiomyopathy, L H Bernstein, MD, FACP

Mitochondria and Cardiovascular Disease: A Tribute to Richard Bing, Larry H Bernstein, MD, FACP

Mitochondrial Metabolism and Cardiac Function, Larry H Bernstein, MD, FACP

Mitochondrial Dysfunction and Cardiac Disorders, Larry H Bernstein, MD, FACP

Reversal of Cardiac mitochondrial dysfunction, Larry H Bernstein, MD, FACP

Related articles

Diagram taken from the paper "Dissection ...

Diagram taken from the paper “Dissection of mitochondrial superhaplogroup H using coding region SNPs” (Photo credit: Asparagirl)

English: Treatment Guidelines for Chronic Hear...

English: Treatment Guidelines for Chronic Heart Failure (Photo credit: Wikipedia)

Nitric Oxide Synthase

Nitric Oxide Synthase (Photo credit: Wikipedia)

Apoptosis Network

Apoptosis Network (Photo credit: sjcockell)

Read Full Post »

Biochemistry of the Coagulation Cascade and Platelet Aggregation: Nitric Oxide: Platelets, Circulatory Disorders, and Coagulation Effects

Curator/Editor/Author: Larry H. Bernstein, MD, FCAP 



Subtitle: Nitric Oxide: Platelets, Circulatory Disorders, and Coagulation Effects.  (Part I)

Summary: This portion of the Nitric Oxide series on PharmaceuticalIntelligence( is the first of a two part treatment of platelets, the coagulation cascade, and protein-membrane interactions with low flow states, local and systemic inflammatory disease, and hematologic disorders.  It is highly complex as the lines separating intrinsic and extrinsic pathways become blurred as a result of endothelial shear stress, distinctly different than penetrating or traumatic injury.  In addition, other factors that come into play are also considered.  The 2nd piece will be concerned with oxidative stress and the diverse effects on NO on the vasoactive endothelium, on platelet endothelial interaction, and changes in blood viscosity.

Coagulation Pathway

The workhorse tests of the modern coagulation laboratory, the prothrombin time (PT) and the activated partial thromboplastin time (aPTT), are the basis for the published extrinsic and intrinsic coagulation pathways.  This is, however, a much simpler model than one encounters delving into the mechanism and interactions involved in hemostasis and thrombosis, or in hemorrhagic disorders.

We first note that there are three components of the hemostatic system in all vertebrates:

  • Platelets,
  • vascular endothelium, and
  • plasma proteins.

The liver is the largest synthetic organ, which synthesizes

  • albumin,
  • acute phase proteins,
  • hormonal and metal binding proteins,
  • albumin,
  • IGF-1, and
  • prothrombin, mainly responsible for the distinction between plasma and serum (defibrinated plasma).

According to WH Seegers [Seegers WH,  Postclotting fates of thrombin.  Semin Thromb Hemost 1986;12(3):181-3], prothrombin is virtually all converted to thrombin in clotting, but Factor X is not. Large quantities of thrombin are inhibited by plasma and platelet AT III (heparin cofactor I), by heparin cofactor II, and by fibrin.  Antithrombin III, a serine protease, is a main inhibitor of thrombin and factor Xa in blood coagulation. The inhibitory function of antithrombin III is accelerated by heparin, but at the same time antithrombin III activity is also reduced. Heparin retards the thrombin-fibrinogen reaction, but otherwise the effectiveness of heparin as an anticoagulant depends on antithrombin III in laboratory experiments, as well as in therapeutics. The activation of prothrombin is inhibited, thereby inactivating  any thrombin or other vulnerable protease that might otherwise be generated. [Seegers WH, Antithrombin III. Theory and clinical applications. H. P. Smith Memorial Lecture. Am J Clin Pathol. 1978;69(4):299-359)].  With respect to platelet aggregation, platelets aggregate with thrombin-free autoprothrombin II-A. Aggregation is dependent on an intact release mechanism since inhibition of aggregation occurred with adenosine, colchicine, or EDTA. Autoprothrombin II-A reduces the sensitivity of platelets to aggregate with thrombin, but enhances epinephrine-mediated aggregation. [Herman GE, Seegers WH, Henry RL. Autoprothrombin ii-a, thrombin, and epinephrine: interrelated effects on platelet aggregation. Bibl Haematol 1977;44:21-7.]

A tetrapeptide, residues 6 to 9 in normal prothrombin, was isolated from the NH(2)-terminal, Ca(2+)-binding part of normal prothrombin. The peptide contained two residues of modified glutamic acid, gamma-carboxyglutamic acid. This amino acid gives normal prothrombin the Ca(2+)-binding ability that is necessary for its activation.

Abnormal prothrombin, induced by the vitamin K antagonist, dicoumarol, lacks these modified glutamic acid residues and that this is the reason why abnormal prothrombin does not bind Ca(2+) and is nonfunctioning in blood coagulation. [Stenflo J, Fernlund P, Egan W, Roepstorff P. Vitamin K dependent modifications of glutamic acid residues in prothrombinProc Natl Acad Sci U S A. 1974;71(7):2730-3.]

Interestingly, a murine monoclonal antibody (H-11) binds a conserved epitope found at the amino terminal of the vitamin K-dependent blood proteins prothrombin, factors VII and X, and protein C. The sequence of polypeptide recognized contains 2 residues of gamma-carboxyglutamic acid, and binding of the antibody is inhibited by divalent metal ions.  The antibody bound specifically to a synthetic peptide corresponding to residues 1-12 of human prothrombin that was synthesized as the gamma-carboxyglutamic acid-containing derivative, but binding to the peptide was not inhibited by calcium ion. This suggested that binding by divalent metal ions is not due simply to neutralization of negative charge by Ca2+. [Church WR, Boulanger LL, Messier TL, Mann KG. Evidence for a common metal ion-dependent transition in the 4-carboxyglutamic acid domains of several vitamin K-dependent proteins. J Biol Chem. 1989;264(30):17882-7.]

Role of vascular endothelium.

I have identified the importance of prothrombin, thrombin, and the divalent cation Ca 2+ (1% of the total body pool), mention of heparin action, and of vitamin K (inhibited by warfarin).  Endothelial functions are inherently related to procoagulation and anticoagulation. The subendothelial matrix is a complex of many materials, most important related to coagulation being collagen and von Willebrand factor.

What about extrinsic and intrinsic pathways?  Tissue factor, when bound to factor VIIa, is the major activator of the extrinsic pathway of coagulation. Classically, tissue factor is not present in the plasma but only presented on cell surfaces at a wound site, which is “extrinsic” to the circulation.  Or is it that simple?

Endothelium is the major synthetic and storage site for von Willebrand factor (vWF).  vWF is…

  • secreted from the endothelial cell both into the plasma and also
  • abluminally into the subendothelial matrix, and
  • acts as the intercellular glue binding platelets to one another and also to the subendothelial matrix at an injury site.
  • acts as a carrier protein for factor VIII (antihemophilic factor).
  • It  binds to the platelet glycoprotein Ib/IX/V receptor and
  • mediates platelet adhesion to the vascular wall under shear. [Lefkowitz JB. Coagulation Pathway and Physiology. Chapter I. in Hemostasis Physiology. In ( ???), pp1-12].

Ca++ and phospholipids are necessary for all of the reactions that result in the activation of prothrombin to thrombin. Coagulation is initiated by an extrinsic mechanism that

  • generates small amounts of factor Xa, which in turn
  • activates small amounts of thrombin.

The tissue factor/factorVIIa proteolysis of factor X is quickly inhibited by tissue factor pathway inhibitor (TFPI).The small amounts of thrombin generated from the initial activation feedback

  • to create activated cofactors, factors Va and VIIIa, which in turn help to
  • generate more thrombin.
  • Tissue factor/factor VIIa is also capable of indirectly activating factor X through the activation of factor IX to factor IXa.
  • Finally, as more thrombin is created, it activates factor XI to factor XIa, thereby enhancing the ability to ultimately make more thrombin.


Coagulation Cascade

The procoagulant plasma coagulation cascade has traditionally been divided into the intrinsic and extrinsic pathways. The Waterfall/Cascade model consists of two separate initiations,

  • intrinsic (contact) and
    • The intrinsic pathway is initiated by a complex activation process of the so-called contact phase components,
      • prekallikrein,
      •  high-molecular weight kininogen (HMWK) and
      • factor XII

Activation of the intrinsic pathway is promoted by non-biological surfaces, such as glass in a test tube, and is probably not of physiological importance, at least not in coagulation induced by trauma.

Instead, the physiological activation of coagulation is mediated exclusively via the extrinsic pathway, also known as the tissue factor pathway.

  • extrinsic pathways,

Tissue factor (TF) is a membrane protein which is normally found in tissues. TF forms a procoagulant complex with factor VII, which activates factor IX and factor X.

  • which ultimately merge at the level of Factor Xa (common pathway).

Regulation of thrombin generation. Coagulation is triggered (initiation) by circulating trace amounts of fVIIa and locally exposed tissue factor (TF). Subsequent formations of fXa and thrombin are regulated by a tissue factor pathway inhibitor (TFPI) and antithrombin (AT). When the threshold level of thrombin is exceeded, thrombin activates platelets, fV, fVIII, and fXI to augment its own generation (propagation).

Activated factors IX and X (IXa and Xa) will activate prothrombin to thrombin and finally the formation of fibrin. Several of these reactions are much more efficient in the presence of phospholipids and protein cofactors factors V and VIII, which thrombin activates to Va and VIIIa by positive feedback reactions.

We depict the plasma coagulation emphasizing the importance of membrane surfaces for the coagulation processes. Coagulation is initiated when tissue factor (TF), an integral membrane protein, is exposed to plasma. TF is expressed on subendothelial cells (e.g. smooth muscle cells and fibroblasts), which are exposed after endothelium damage. Activated monocytes are also capable of exposing TF.

A small amount, approximately 1%, of activated factor VII (VIIa) is present in circulating blood and binds to TF. Free factor VIIa has poor enzymatic activity and the initiation is limited by the availability of its cofactor TF. The first steps in the formation of a blood clot is the specific activation of factor IX and X by the TF-VIIa complex. (Initiation of coagulation: Factor VIIa binds to tissue factor and activates factors IX and X). Coagulation is propagated by procoagulant enzymatic complexes that assemble on the negatively charged membrane surfaces of activated platelets. (Propagation of coagulation: Activation of factor X and prothrombin).  Once thrombin has been formed it will activate the procofactors, factor V and factor VIII, and these will then assemble in enzyme complexes. Factor IXa forms the tenase complex together with its cofactor factor VIIIa, and factor Xa is the enzymatic component of the prothrombinase complex with factor Va as cofactor.

Activation of protein C takes place on the surface of intact endothelial cells. When thrombin (IIa) reaches intact endothelium it binds with high affinity to a specific receptor called thrombomodulin. This shifts the specific activity of thrombin from being a procoagulant enzyme to an anticoagulant enzyme that activates protein C to activated protein C (APC).  The localization of protein C to the thrombin-thrombomodulin complex can be enhanced by the endothelial protein C receptor (EPCR), which is a transmembrane protein with high affinity for protein C.  Activated protein C (APC) binds to procoagulant surfaces such as the membrane of activated platelets where it finds and degrades the procoagulant cofactors Va and VIIIa, thereby shutting down the plasma coagulation.  Protein S (PS) is an important nonenzymatic  cofactor to APC in these reactions. (Degradation of factors Va and VIIIa).

The common theme in activation and regulation of plasma coagulation is the reduction in dimensionality. Most reactions take place in a 2D world that will increase the efficiency of the reactions dramatically. The localization and timing of the coagulation processes are also dependent on the formation of protein complexes on the surface of membranes. The coagulation processes can also be controlled by certain drugs that destroy the membrane binding ability of some coagulation proteins – these proteins will be lost in the 3D world and not able to form procoagulant complexes on surfaces.

Assembly of proteins on membranes – making a 3D world flat

• The timing and efficiency of coagulation processes are handled by reduction in dimensionality

– Make 3 dimensions to 2 dimensions

• Coagulation proteins have membrane binding capacity

• Membranes provide non-coagulant and procoagulant surfaces

– Intact cells/activated cells

• Membrane binding is a target for anticoagulant drugs

– Anti-vitamin K (e.g. warfarin)

Modern View

It can be divided into the phases of initiation, amplification and propagation.

  • In the initiation phase, small amounts of thrombin can be formed after exposure of tissue factor to blood.
  • In the amplification phase, the traces of thrombin will be inactivated or used for amplification of the coagulation process.

At this stage there is not enough thrombin to form insoluble fibrin. In order to proceed further thrombin  activates platelets, which provide a procoagulant surface for the coagulation factors. Thrombin will also activate the vital cofactors V and VIII that will assemble on the surface of activated platelets. Thrombin can also activate factor XI, which is important in a feedback mechanism.

In the final step, the propagation phase, the highly efficient tenase and prothrombinase complexes have been assembled on the membrane surface. This yields large amounts of thrombin at the site of injury that can cleave fibrinogen to insoluble fibrin. Factor XI activation by thrombin then activates factor IX, which leads to the formation of more tenase complexes. This ensures enough thrombin is formed, despite regulation of the initiating TF-FVIIa complex, thus ensuring formation of a stable fibrin clot. Factor XIII stabilizes the fibrin clot through crosslinking when activated by thrombin.

English: Gene expression pattern of the VWF gene.

English: Gene expression pattern of the VWF gene. (Photo credit: Wikipedia)

Coagulation cascade

Coagulation cascade (Photo credit: Wikipedia)

Blood Coagulation (Thrombin) and Protein C Pat...

Fibrinolytic pathway

Fibrinolysis is the physiological breakdown of fibrin to limit and resolve blood clots. Fibrin is degraded primarily by the serine protease, plasmin, which circulates as plasminogen. In an auto-regulatory manner, fibrin serves as both the co-factor for the activation of plasminogen and the substrate for plasmin.

In the presence of fibrin, tissue plasminogen activator (tPA) cleaves plasminogen producing plasmin, which proteolyzes the fibrin. This reaction produces the protein fragment D-dimer, which is a useful marker of fibrinolysis, and a marker of thrombin activity because fibrin is cleaved from fibrinogen to fibrin.

Bleeding after Coronary Artery bypass Graft

Cardiac surgery with concomitant CPB can profoundly alter haemostasis, predisposing patients to major haemorrhagic complications and possibly early bypass conduit-related thrombotic events as well. Five to seven percent of patients lose more than 2 litres of blood within the first 24 hours after surgery, between 1% and 5% require re-operation for bleeding. Re-operation for bleeding increases hospital mortality 3 to 4 fold, substantially increases post-operative hospital stay and has a sizeable effect on health care costs. Nevertheless, re-exploration is a strong risk factor associated with increased operative mortality and morbidity, including sepsis, renal failure, respiratory failure and arrhythmias.

(Gábor Veres. New Drug Therapies Reduce Bleeding in Cardiac Surgery. Ph.D. Doctoral Dissertation. 2010. Semmelweis University)

Read Full Post »

Is the Warburg Effect the Cause or the Effect of Cancer: A 21st Century View?

Author: Larry H. Bernstein, MD, FCAP  

A Critical Review

What is the Warburg effect?

“Warburg Effect” describes the preference of glycolysis and lactate fermentation rather than oxidative phosphorylation for energy production in cancer cells. Mitochondrial metabolism is an important and necessary component in the functioning and maintenance of the organelle, and accumulating evidence suggests that dysfunction of mitochondrial metabolism plays a role in cancer. Progress has demonstrated the mechanisms of the mitochondrial metabolism-to-glycolysis switch in cancer development and how to target this metabolic switch.
In vertebrates, food is digested and supplied to cells mainly in the form of glucose. Glucose is broken down further to make Adenosine Triphosphate (ATP) by two pathways. One is via anaerobic metabolism occurring in the cytoplasm, also known as glycolysis. The major physiological significance of glycolysis lies in making ATP quickly, but in a minuscule amount. The breakdown process continues in the mitochondria via the Krebs’s cycle coupled with oxidative phosphorylation, which is more efficient for ATP production. Cancer cells seem to be well-adjust to glycolysis. In the 1920s, Otto Warburg first proposed that cancer cells show increased levels of glucose consumption and lactate fermentation even in the presence of ample oxygen (known as “Warburg Effect”). Based on this theory, oxidative phosphorylation switches to glycolysis which promotes the proliferation of cancer cells. Many studies have demonstrated glycolysis as the main metabolic pathway in cancer cells.
Why cancer cells prefer glycolysis, an inefficient metabolic pathway?

It is now accepted that glycolysis provides cancer cells with the most abundant extracellular nutrient, glucose, to make ample ATP metabolic intermediates, such as ribose sugars, glycerol and citrate, nonessential amino acids, and the oxidative pentose phosphate pathway, which serve as building blocks for cancer cells.
Since, cancer cells have increased rates of aerobic glycolysis, investigators argue over the function of mitochondria in cancer cells. Mitochondrion, a one of the smaller organelles, produces most of the energy in the form of ATP to supply the body. In Warburg’s theory, the function of cellular mitochondrial respiration is dampened and mitochondria are not fully functional. There are many studies backing this theory. A recent review on hypoxia nicely summarizes some current studies and speculates that the “Warburg Effect” provides a benefit to the tumor not by increasing glycolysis but by decreasing mitochondrial activity.
Glycolysis is enhanced and beneficial to cancer cells. The mammalian target of rapamycin (mTOR) has been well discussed in its role to promote glycolysis; recent literature has revealed some new mechanisms of how glycolysis is promoted during skin cancer development.
On the other hand, Akt is not only involved in the regulation of mitochondrial metabolism in skin cancer but also of glycolysis. Activation of Akt has been found to phosphorylate FoxO3a, a downstream transcription factor of Akt, which promotes glycolysis by inhibiting apoptosis in melanoma. In addition, activated Akt is also associated with stabilized c-Myc and activation of mTOR, which both increase glycolysis for cancer cells.
Nevertheless, ras mutational activation prevails in skin cancer. Oncogenic ras induces glycolysis. In human squamous cell carcinoma, the c-Jun NH(2)-terminal Kinase (JNK) is activated as a mediator of ras signaling, and is essential for ras-induced glycolysis, since pharmacological inhibitors if JNK suppress glycolysis. CD147/basigin, a member of the immunoglobulin superfamily, is high expressed in melanoma and other cancers.
Glyoxalase I (GLO1) is a ubiquitous cellular defense enzyme involved in the detoxification of methylglyoxal, a cytotoxic byproduct of glycolysis. In human melanoma tissue, GLO1 is upregulated at both the mRNA and protein levels.
Knockdown of GLO1 sensitizes A375 and G361 human metastatic melanoma cells to apoptosis.
The transcription factor HIF-1 upregulates a number of genes in low oxygen conditions including glycolytic enzymes, which promotes ATP synthesis in an oxygen independent manner. Studies have demonstrated that hypoxia induces HIF-1 overexpression and its transcriptional activity increases in parallel with the progression of many tumor types. A recent study demonstrated that in malignant melanoma cells, HIF-1 is upregulated, leading to elevated expression of Pyruvate Dehydrogenase Kinase 1 (PDK1), and downregulated mitochondrial oxygen consumption.
The M2 isoform of Pyruvate Kinase (PKM2), which is required for catalyzing the final step of aerobic glycolysis, is highly expressed in cancer cells; whereas the M1 isoform (PKM1) is expressed in normal cells. Studies using the skin cell promotion model (JB6 cells) demonstrated that PKM2 is activated whereas PKM1 is inactivated upon tumor promoter treatment. Acute increases in ROS inhibited PKM2 through oxidation of Cys358 in human lung cancer cells. The levels of ROS and stage of tumor development may be pivotal for the role of PKM2.

Mitochondrial metabolism and glycolysis targeting for cancer drug delivery
In cancer cells including skin cancer cells, the metabolic shift is composed of increased glycolysis, activation of anabolic pathways including amino acid and pentose phosphate production, and increased fatty acid biosynthesis. More and more studies have converged on particular glycolytic and mitochondrial metabolic targets for cancer drug discovery.
A marker for increased glycolysis in melanoma is the elevated levels of Lactate Dehydrogenase (LDH) in the blood of patients with melanoma, which has proven to be an accurate predictor of prognosis and response to treatments. LDH converts pyruvate, the final product of glycolysis, to lactate when oxygen is absent. High concentrations of lactate, in turn, negatively regulate LDH. Therefore, targeting acid excretion may provide a feasible and effective therapeutic approach for melanoma. For instance, JugloSne, a main active component in walnut, has been used in traditional medicines. Studies have shown that Juglone causes cell membrane damage and increased LDH levels in a concentration-dependent manner in cultured melanoma cells. As one of the rate-limiting enzyme of glycolysis, 6-phosphofructo-2-kinase/fructose-2,6-bisphosphatase isozyme 3 (PFKFB3) is activated in neoplastic cells. Studies have confirmed that an inhibitor of PFKFB3, 3-(3-pyridinyl)-1-(4-pyridinyl)-2-propen-1-one (3PO), suppresses glycolysis in neoplastic cells. In melanoma cell lines, the concentrations of Fru-2, 6-BP, lactate, ATP, NAD+, and NADH are diminished by 3PO. Therefore, targeting PFKFB3 using 3PO and other PFKFB3 specific inhibitors could be effective in melanoma chemotherapy.
A new NO (nitric oxide) donating compound [(S,R)-3-phenyl-4,5-dihydro-5-isoxazole acetic acid–nitric oxide (GIT-27NO)] has been tested in treating melanoma cells. The results suggest that GIT-27/NO causes a dose-dependent reduction of mitochondrial respiration in treated A375 human melanoma cells.

At least two mitochondrial enzymes are affected by angiostatin which include malate dehydrogenase, a member of the Kreb’s cycle enzymes; and adenosine triphosphate synthase. Both are identified potential angiostatin-binding partners. Treated with angiostatin, the ATP concentrations of A2058 cells were decreased. Meanwhile, using siRNA of these two enzymes also inhibited the ATP production. PKM2 is up regulated in the early stage of skin carcinogenesis, therefore, targeting PKM2 could serve as a new approach for skin cancer prevention and therapy.
The signaling pathways critical for this glycolytic activation could serve as preventive and therapeutic targets for human skin cancer.

The Historical Challenge posed by the Warburg Hypothesis.

Impaired cellular energy metabolism is the defining characteristic of nearly all cancers regardless of cellular or tissue origin. In contrast to normal cells, which derive most of their usable energy from oxidative phosphorylation, most cancer cells become heavily dependent on substrate level phosphorylation to meet energy demands. Evidence is reviewed supporting a general hypothesis that genomic instability and essentially all hallmarks of cancer, including aerobic glycolysis (Warburg effect), can be linked to impaired mitochondrial function and energy metabolism.
In a landmark review, six essential alterations in cell physiology could underlie malignant cell growth. These six alterations were described as the hallmarks of nearly all cancers and included,

  • self-sufficiency in growth signals,
  • insensitivity to growth inhibitory (antigrowth) signals,
  • evasion of programmed cell death (apoptosis),
  • limitless replicative potential,
  • sustained vascularity (angiogenesis), and
  • tissue invasion and metastasis.

Genome instability, leading to increased mutability, was considered the essential enabling characteristic for manifesting the six hallmarks. The loss of genomic “caretakers” or “guardians”, involved in sensing and repairing DNA damage, was proposed to explain the increased mutability of tumor cells. The loss of these caretaker systems would allow genomic instability thus enabling pre-malignant cells to reach the six essential hallmarks of cancer.
In addition to the six recognized hallmarks of cancer, aerobic glycolysis or the Warburg effect is also a robust metabolic hallmark of most tumors. Aerobic glycolysis in cancer cells involves elevated glucose uptake with lactic acid production in the presence of oxygen. This metabolic phenotype is the basis for tumor imaging using labeled glucose analogues and has become an important diagnostic tool for cancer detection and management. Genes for glycolysis are overexpressed in the majority of cancers examined.
Although aerobic glycolysis and anaerobic glycolysis are similar in that lactic acid is produced under both situations, aerobic glycolysis can arise in tumor cells from damaged respiration whereas anaerobic glycolysis arises from the absence of oxygen. As oxygen will reduce anaerobic glycolysis and lactic acid production in most normal cells (Pasteur effect), the continued production of lactic acid in the presence of oxygen can represent an abnormal Pasteur effect. This is the situation in most tumor cells.
Warburg proposed with considerable certainty and insight that irreversible damage to respiration was the prime cause of cancer. Warburg’s biographer, Hans Krebs, mentioned that Warburg’s idea on the primary cause of cancer, i.e., the replacement of respiration by fermentation (glycolysis), was only a symptom of cancer and not the cause. While there is renewed interest in the energy metabolism of cancer cells, it is widely thought that the Warburg effect and the metabolic defects expressed in cancer cells arise primarily from genomic mutability selected during tumor progression. Emerging evidence, however, questions the genetic origin of cancer and suggests that cancer is primarily a metabolic disease.
Genomic mutability and essentially all hallmarks of cancer, including the Warburg effect, can be linked to impaired respiration and energy metabolism. In brief, damage to cellular respiration precedes and underlies the genome instability that accompanies tumor development. Once established, genome instability contributes to further respiratory impairment, genome mutability, and tumor progression. In other words, effects become causes. This hypothesis is based on evidence that nuclear genome integrity is largely dependent on mitochondrial energy homeostasis and that all cells require a constant level of useable energy to maintain viability. While Warburg recognized the centrality of impaired respiration in the origin of cancer, he did not link this phenomenon to what are now recognize as the hallmarks of cancer.
Abnormal metabolism of tumors, a selective advantage
The initial observation of Warburg 1916 on tumor glycolysis with lactate production is still a crucial observation. Two fundamental findings complete the metabolic picture:

  • the discovery of the M2 pyruvate kinase (PK) typical of tumors
  • and the implication of tyrosine kinase signals and subsequent phosphorylations in the M2 PK blockade.

A typical feature of tumor cells is a glycolysis associated to an inhibition of apoptosis. Tumors overexpress the high affinity hexokinase 2, which strongly interacts with the mitochondrial ANT-VDAC-PTP complex. In this position, close to the ATP/ADP exchanger (ANT), the hexokinase receives efficiently its ATP substrate. As long as hexokinase occupies this mitochondria site, glycolysis is efficient. However, this has another consequence, hexokinase pushes away from the mitochondria site the permeability transition pore (PTP), which inhibits the release of cytochrome C, the apoptotic trigger. The site also contains a voltage dependent anion channel (VDAC) and other proteins. The repulsion of PTP by hexokinase would reduce the pore size and the release of cytochrome C. Thus, the apoptosome-caspase proteolytic structure does not assemble in the cytoplasm. The liver hexokinase or glucokinase, is different it has less interaction with the site, has a lower affinity for glucose; because of this difference, glucose goes preferentially to the brain.
Further, phosphofructokinase gives fructose 1-6 bisphosphate; glycolysis is stimulated if an allosteric analogue, fructose 2-6 bis phosphate increases in response to a decrease of cAMP. The activation of insulin receptors in tumors has multiple effects, among them; a decrease of cAMP, which will stimulate glycolysis. Another control point is glyceraldehyde P dehydrogenase that requires NAD+ in the glycolytic direction. If the oxygen supply is normal, the mitochondria malate/aspartate (MAL/ASP) shuttle forms the required NAD+ in the cytosol and NADH in the mitochondria. In hypoxic conditions, the NAD+ will essentially come via lactate dehydrogenase converting pyruvate into lactate. This reaction is prominent in tumor cells; it is the first discovery of Warburg on cancer.
At the last step of glycolysis, pyruvate kinase (PK) converts phospho-enolpyruvate (PEP) into pyruvate, which enters in the mitochondria as acetyl- CoA, starting the citric acid cycle and oxidative metabolism. To explain the PK situation in tumors we must recall that PK only works in the glycolytic direction, from PEP to pyruvate, which implies that gluconeogenesis uses other enzymes for converting pyruvate into PEP. In starvation, when cells need glucose, one switches from glycolysis to gluconeogenesis and ketogenesis; PK and pyruvate dehydrogenase (PDH) are off, in a phosphorylated form, presumably following a cAMP-glucagon-adrenergic signal. In parallel, pyruvate carboxylase (Pcarb) becomes active.
Moreover, in starvation, much alanine comes from muscle protein proteolysis, and is transaminated into pyruvate. Pyruvate carboxylase first converts pyruvate to OAA and then, PEP carboxykinase converts OAA to PEP etc…, until glucose. The inhibition of PK is necessary, if not one would go back to pyruvate. Phosphorylation of PK, and alanine, inhibit the enzyme.
PK and a PDH of tumors are inhibited by phosphorylation and alanine, like for gluconeogenesis, in spite of an increased glycolysis! Moreover, in tumors, one finds a particular PK, the M2 embryonic enzyme [2,9,10] the dimeric, phosphorylated form is inactive, leading to a “bottleneck “. The M2 PK has to be activated by fructose 1-6 bis P its allosteric activator, whereas the M1 adult enzyme is a constitutive active form. The M2 PK bottleneck between glycolysis and the citric acid cycle is a typical feature of tumor cell glycolysis.
Above the bottleneck, the massive entry of glucose accumulates PEP, which converts to OAA via mitochondria PEP carboxykinase, an enzyme requiring biotine-CO2-GDP. This source of OAA is abnormal, since Pcarb, another biotin-requiring enzyme, should have provided OAA. Tumors may indeed contain “morule inclusions” of biotin-enzyme suggesting an inhibition of Pcarb, presumably a consequence of the maintained citrate synthase activity, and decrease of ketone bodies that normally stimulate Pcarb. The OAA coming via PEP carboxykinase and OAA coming from aspartate transamination or via malate dehydrogenase condenses with acetyl CoA, feeding the elevated tumoral citric acid condensation starting the Krebs cycle.
Thus, tumors have to find large amounts of acetyl CoA for their condensation reaction; it comes essentially from lipolysis and β oxidation of fatty acids, and enters in the mitochondria via the carnitine transporter. This is the major source of acetyl CoA. It is as if the mechanism switching from gluconeogenesis to glycolysis was jammed in tumors, PK and PDH are at rest, like for gluconeogenesis, but citrate synthase is on. Thus, citric acid condensation pulls the glucose flux in the glycolytic direction, which needs NAD+; it will come from the pyruvate to lactate conversion by lactate dehydrogenase (LDH) no longer in competition with a quiescent Pcarb.
Since the citrate condensation consumes acetyl CoA, ketone bodies do not form; while citrate will support the synthesis of triglycerides via ATP citrate lyase and fatty acid synthesis… The cytosolic OAA drives the transaminases in a direction consuming amino acid. The result of these metabolic changes is that tumors burn glucose while consuming muscle protein and lipid stores of the organism. In a normal physiological situation, one mobilizes stores for making glucose or ketone bodies, but not while burning glucose!
The 21st Century Genomic Challenge?
According to the modern understanding of cancer, it is a disease caused by genetic and epigenetic alterations. Although this is now widely accepted, perhaps more emphasis has been given to the fact that cancer is a genetic disease. Numerous studies, including our earlier works, have supported the notion that carcinogenesis involves the activation of tumor-promoting oncogenes and the inactivation of growth-inhibiting tumor suppressor genes. It should be noted that in the post-genome sequencing project period of the 21st century, an in depth investigation of the factors associated with tumorigenesis is required for achieving it. Extensive research is warranted in two areas, namely, tumor bioenergetics and the cancer stem cell (CSC) hypothesis, neither of which received the required attention after the success of the genome sequencing project. An investigation of these two concepts would give rise to a new era in the study of cancer biology. Indeed, recent studies have indicated that the two apparently distinct fields might be related to each other and can converge more rapidly than previously recognized.
Warburg Effect Revisited
Cancer cells rarely depend on mitochondria for respiration and obtain almost half of their ATP by directly metabolizing glucose to lactic acid, even in the presence of oxygen. However, with the discovery that tumors do not show any shift to glycolysis, Warburg’s cancer theory (high lactate production and low mitochondrial respiration in tumor under normal oxygen pressure) was gradually discredited. Otto Warburg won a Nobel Prize in 1931 for the discovery of tumor bioenergetics, which is now commonly used as the basis of positron emission tomography (PET), a highly sensitive noninvasive technique used in cancer diagnosis. The increasing number of recent reports on the Warburg effect has reestablished the significance of this effect in tumorigenesis, indicating that bioenergetics may play a critical role in malignant transformation. Furthermore, it has been reported that TP53, which is one of the most commonly mutated genes in cancer, can trigger the Warburg effect. Glycolytic conversion is initiated in the early stages in cells that are genetically engineered to become cancerous, and the conversion was enhanced as the cells became more malignant. Therefore, the Warburg effect might directly contribute to the initiation of cancer formation not only by enhanced glycolysis but also via decreased respiration in the presence of oxygen, which suppresses apoptosis. This effect may also produce a metabolic shift to enhanced glycolysis and play a role in the early stages of multistep tumorigenesis in vivo.

Cancer Stem Cells (CSC) and Embryonic Stem Cells (ESC)
The importance of the cancer stem cell (CSC) hypothesis in therapy-related resistance and metastasis has been recognized during the past 2 decades. Accumulating evidence suggests that tumor bioenergetics plays a critical role in CSC regulation; this finding has opened up a new era of cancer medicine, which goes beyond cancer genomics.

Embryonic stem (ES) cells and immortalized primary and cancerous cells show a common concerted metabolic shift, including:

  • enhanced glycolysis,
  • decreased apoptosis, and
  • reduced mitochondrial respiration.

This finding reinforces the use of somatic stem cells or metastatic tumor cells in hypoxic niches. Hypoxia appears to regulate the functions of hematopoietic stem cells in the bone marrow and metastatic tumor cells by preserving important stem cell functions, such as:

  • cell cycle control,
  • survival,
  • metabolism, and
  • protection against oxidative stress.

Several companies and laboratories are now attempting to evaluate the bioenergetics associated with tumorigenesis by testing and challenging the available anticancer drugs.

A small population of cancer-initiating cells plays a very important role in current investigations. These CSCs may cause resistance to chemotherapy or radiation therapy or lead to post-therapy recurrence even when most of the cancer cells appear to be dead. In addition to their genetic alterations, CSCs are believed to mimic normal adult stem cells with regard to properties like self-renewal and undifferentiated status, which eventually leads to the formation of differentiated cells. Unlike well-differentiated daughter cells, small populations of CSCs are believed to be more resistant to toxic injuries and chemoradiotherapy. Indeed, the conventional cancer therapies have always been targeted toward proliferating cells. The control of CSCs, which is often exercised in the dormant phase of the cell cycle, can now be applied to achieve complete tumor regression.
Identification of cancer-specific markers
Due to their potential use in clinical applications, the surface markers of CSCs have been studied and identified. Adult stem cells and their malignant counterparts share similar intrinsic and extrinsic factors that regulate the

  • self renewal,
  • differentiation, and
  • proliferation pathways.

The following are the examples of candidate markers: musashi-1 (Msi-1), hairy and enhancer of split homolog-1 (Hes-1), CD133 (prominin-1, Prom1), epithelial cellular adhesion molecule (EpCam), claudin-7,29 CD44 variant isoforms, Lgr5,30Hedgehog (Hh), bone morphogenic protein (Bmp), Notch, and Wnt.
Is cancer a metabolic disease and genomic instability a secondary effect?
Bioenergetics of Cancer Stem Cells
The bioenergetics associated with the adaptation of CSCs to their micro-environment still requires extensive research. Although numerous studied suggested the association between Warburg effect and reduced oxidative stress in cancer, the relevant molecular mechanism was not known until very recently when Ruckenstuhl, et al. reported their findings in a yeast model.

How cancer cells achieve one of the most common phenotypes, namely, the “Warburg effect,” i.e., elevated glycolysis in the presence of oxygen, is still a topic of hypothesis, unless the involvement of glycolysis genes is considered.
The Warburg effect has been observed in differentiating cancer cells (e.g., cells that undergo epithelial-to-mesenchymal and mesenchymal-to-amoeboid transition), cells resistant to anoikis, and cells which interact with the stromal components of the metastatic niche. The epithelial-to-mesenchymal transition is involved in the resistance to chemotherapy in gastrointestinal cancer cells.

Cancer metastasis can be regarded as an integrated “escape program” triggered by redox changes. These alterations might be associated with avoiding oxidative stress in the niche of the tumor cells, or presumably with the response to treatments aimed at genetic targets, such as chemotherapy and radiation.
The introduction of induced pluripotent stem (iPS) cell genes was necessary for inducing the expression of immature status-related proteins in gastrointestinal cancer cells, and that the induced pluripotent cancer (iPC) cells were distinct from natural cancer cells with regard to their sensitivity to differentiation inducing treatment. For the complete eradication of cancer, however, future efforts should be directed toward improving translational research.
Cancer metabolism.
Glycolysis is elevated in tumors, but a pyruvate kinase (PK) “bottleneck” interrupts phosphoenol pyruvate (PEP) to pyruvate conversion. Thus, alanine following muscle proteolysis transaminates to pyruvate, feeding lactate dehydrogenase, converting pyruvate to lactate, (Warburg effect) and NAD+ required for glycolysis. Cytosolic malate dehydrogenase also provides NAD+ (in OAA to MAL direction). Malate moves through the shuttle giving back OAA in the mitochondria. Below the PK-bottleneck, pyruvate dehydrogenase (PDH) is phosphorylated (second bottleneck). However, citrate condensation increases: acetyl-CoA, will thus come from fatty acids b-oxydation and lipolysis, while OAA sources are via PEP carboxy kinase, and malate dehydrogenase, (pyruvate carboxylase is inactive). Citrate quits the mitochondria, (note interrupted Krebs cycle). In the cytosol, ATP citrate lyase cleaves citrate into acetyl CoA and OAA.
Acetyl CoA will make fatty acids-triglycerides. Above all, OAA pushes transaminases in a direction usually associated to gluconeogenesis! This consumes protein stores, providing alanine (ALA); like glutamine, it is essential for tumors. The transaminases output is aspartate (ASP) it joins with ASP from the shuttle and feeds ASP transcarbamylase, starting pyrimidine synthesis. ASP in not processed by argininosuccinate synthetase, which is blocked, interrupting the urea cycle.
Arginine gives ornithine via arginase, ornithine is decarboxylated into putrescine by ornithine decarboxylase. Putrescine and SAM form polyamines (spermine spermidine) via SAM decarboxylase. The other product 5-methylthioadenosine provides adenine. Arginine deprivation should affect tumors. The SAM destruction impairs methylations, particularly of PP2A, removing the “signaling kinase brake”, PP2A also fails to dephosphorylate PK and PDH, forming the “bottlenecks”.

Insulin or IGF actions boost the cellular influx of glucose and glycolysis. However, if the signaling pathway gets out of control, the tyrosine kinase phosphorylations may lead to a parallel PK blockade explaining the tumor bottleneck at the end of glycolysis. Since an activation of enyme kinases may indeed block essential enzymes (PK, PDH and others); in principle, the inactivation of phosphatases may also keep these enzymes in a phosphorylated form and lead to a similar bottleneck and we do know that oncogenes bind and affect PP2A phosphatase. In sum, a perturbed MAP kinase pathway, elicits metabolic features that would give to tumor cells their metabolic advantage.

Warburg effect and the prognostic value of stromal caveolin-1 as a marker of a lethal tumor microenvironment
Cancer cells show a broad spectrum of bioenergetic states, with some cells using aerobic glycolysis while others rely on oxidative phosphorylation as their main source of energy. In addition, there is mounting evidence that metabolic coupling occurs in aggressive tumors, between epithelial cancer cells and the stromal compartment, and between well-oxygenated and hypoxic compartments. We recently showed that oxidative stress in the tumor stroma, due to aerobic glycolysis and mitochondrial dysfunction, is important for cancer cell mutagenesis and tumor progression. More specifically, increased autophagy/mitophagy in the tumor stroma drives a form of parasitic epithelial-stromal metabolic coupling. These findings explain why it is effective to treat tumors with either inducers or inhibitors of autophagy, as both would disrupt this energetic coupling. We also discuss evidence that glutamine addiction in cancer cells produces ammonia via oxidative mitochondrial metabolism.

Ammonia production in cancer cells, in turn, could then help maintain autophagy in the tumor stromal compartment. In this vicious cycle, the initial glutamine provided to cancer cells would be produced by autophagy in the tumor stroma. Thus, we believe that parasitic epithelial-stromal metabolic coupling has important implications for cancer diagnosis and therapy, for example, in designing novel metabolic imaging techniques and establishing new targeted therapies. In direct support of this notion, we identified a loss of stromal caveolin-1 as a marker of oxidative stress, hypoxia, and autophagy in the tumor microenvironment, explaining its powerful predictive value. Loss of stromal caveolin-1 in breast cancers is associated with early tumor recurrence, metastasis, and drug resistance, leading to poor clinical outcome.
The conventional ‘Warburg effect’ versus oxidative mitochondrial metabolism
Warburg’s original work indicated that while glucose uptake and lactate production are greatly elevated, a cancer cell’s rate of mitochondrial respiration is similar to that of normal cells. He, however, described it as a ‘respiratory impairment’ due to the fact that, in cancer cells, mitochondrial respiration is smaller, relative to their glycolytic power, but not smaller relative to normal cells. He recognized that oxygen consumption is not diminished in tumor cells, but that respiration is disturbed because glycolysis persists in the presence of oxygen. Unfortunately, the perception of his original findings was simplified over the years, and most subsequent papers validated that cancer cells undergo aerobic glycolysis and produce lactate, but did not measure mitochondrial respiration, and just presumed decreased tricarboxylic acid (TCA) cycle activity and reduced oxidative phosphorylation [1,2]. It is indeed well documented that, as a consequence of intra-tumoral hypoxia, the hypoxia-inducible factor (HIF)1α pathway is activated in many tumors cells, resulting in the direct up-regulation of lactate dehydrogenase (LDH) and increased glucose consumption.
It is now clear that cancer cells utilize both glycolysis and oxidative phosphorylation to satisfy their metabolic needs. Experimental assessments of ATP production in cancer cells have demonstrated that oxidative pathways play a signifi cant role in energy generation, and may be responsible for about 50 to 80% of the ATP generated. several studies now clearly indicate that mitochondrial activity and oxidative phosphorylation support tumor growth. Loss-of-function mutations in the TCA cycle gene IDH1 (isocitrate dehydrogenase 1) are found in about 70% of gliomas, but, interestingly, correlate with a better prognosis and improved survival, suggesting that severely decreased activity in one of the TCA cycle enzymes does not favor tumor aggressiveness. The mitochondrial protein p32 was shown to maintain high levels of oxidative phosphorylation in human cancer cells and to sustain tumorigenicity in vivo. In addition, STAT3 is known to enhance tumor growth and to predict poor prognosis in human cancers. Interestingly, a pool of STAT3 localizes to the mitochondria, to sustain high levels of mitochondrial respiration and to augment transformation by oncogenic Ras. Similarly, the mitochondrial transcription factor A (TFAM), which is required for mitochondrial DNA replication and oxidative phosphorylation, is also required for K-Ras induced lung tumorigenesis.
There is also evidence that pro-oncogenic molecules regulate mitochondrial function. Cyclin D1 inhibits mitochondrial function in breast cancer cells. Overexpression of cyclin D1 is observed in about 50% of invasive breast cancers and is associated with a good clinical outcome, indicating that inhibition of mitochondrial activity correlates with favorable prognosis. Importantly, it was shown that the oncogene c-Myc stimulates mitochondrial biogenesis, and enhances glutamine metabolism by regulating the expression of mitochondrial glutaminase, the first enzyme in the glutamine utilization pathway. Glutamine is an essential metabolic fuel that is converted to alpha-ketoglutarate and serves as a substrate for the TCA cycle or for glutathione synthesis, to promote energy production and cellular biosynthesis, and to protect against oxidative stress. Interestingly, pharmacological targeting of mitochondrial glutaminase inhibits cancer cell transforming activity, suggesting that glutamine metabolism and its role in fueling and replenishing the TCA cycle are required for neoplastic transformation.
Reverse Warburg Effect.
It is increasingly apparent that the tumor microenvironment regulates neoplastic growth and progression. Activation of the stroma is a critical step required for tumor formation. Among the stromal players, cancer associated fi broblasts (CAFs) have recently taken center stage [25]. CAFs are activated, contractile        fibroblasts that display features of myo-fibroblasts, express muscle specific actin, and show an increased ability to secrete and remodel the extracellular matrix. They are not just neutral spectators, but actively support malignant transformation and metastasis, as compared to normal resting fibroblasts.

Importantly, the tumor stroma dictates clinical outcome and constitutes a source of potential biomarkers. Expression profiling has identified a cancer-associated stromal signature that predicts good and poor clinical prognosis in breast cancer patients, independently of other factors.

A loss of caveolin-1 (Cav-1) in the stromal compartment is a novel biomarker for predicting poor clinical outcome in all of the most common subtypes of human breast cancer, including the more lethal triple negative subtype. A loss of stromal Cav-1 predicts early tumor recurrence, lymph node metastasis, tamoxifen-resistance, and poor survival.

Overall, breast cancer patients with a loss of stromal Cav-1show a 20% 5-year survival rate, compared to the 80% 5-year survival of patients with high stromal Cav-1 expression. In triple negative patients, the 5-year survival rate is 75.5% for high stromal Cav-1 versus 9.4% for absent stromal Cav-1. A loss of stromal Cav-1 also predicts progression to invasive disease in ductal carcinoma in situ patients, suggesting that a loss of Cav-1 regulates tumor progression. Similarly, a loss of stromal Cav-1 is associated with advanced disease and metastasis, as well as a high Gleason score, in prostate cancer patients.

The autophagic tumor stroma model of cancer metabolism.
Cancer cells induce oxidative stress in adjacent cancer-associated fibroblasts (CAFs). This activates reactive oxygen species (ROS) production and autophagy. ROS production in CAFs, via the bystander eff ect, serves to induce random mutagenesis in epithelial cancer cells, leading to double-strand DNA breaks and aneuploidy. Cancer cells mount an anti-oxidant defense and upregulate molecules that protect them against ROS and autophagy, preventing them from undergoing apoptosis. So, stromal fibroblasts conveniently feed and mutagenize cancer cells, while protecting them against death. See the text for more details. A+, autophagy positive; A-, autophagy negative; AR, autophagy resistant.

1. Recycled Nutrients
2. Random Mutagenesis
3. Protection Against Apoptosis
The clinical use of PET is well established in Hodgkin’s lymphomas which are composed of less than 10% tumor cells, the rest being stromal and inflammatory cells. Yet, Hodgkin’s lymphomas are very PET avid tumors, suggesting that 2-deoxy-glucose uptake may be associated with the tumor stroma. That the fibrotic component may be glucose avid is further supported by the notion that PET is clinically used to assess the therapeutic response in gastrointestinal stromal tumors (GIST), which are a subset of tumors of mesenchymal origin.
The reverse Warburg effect can be described as ‘metabolic coupling’ between supporting glycolytic stromal cells and oxidative tumor cells. Metabolic cooperativity between adjacent cell-compartments is observed in several normal physiological settings.
The reverse Warburg effect.
Via oxidative stress, cancer cells activate two major transcription factors in adjacent stromal fibroblasts (hypoxia-inducible factor (HIF)1α and NFκB).
This leads to the onset of both autophagy and mitophagy, as well as aerobic glycolysis, which then produces recycled nutrients (such as lactate, ketones, and glutamine).
These high-energy chemical building blocks can then be transferred and used as fuel in the tricarboxylic acid cycle (TCA) in adjacent cancer cells.
The outcome is high ATP production in cancer cells, and protection against cell death. ROS, reactive oxygen species.
The methylation hypothesis and the role of PP2A phosphatase
Diethanolamine decreased choline derivatives and methyl donors in the liver, like seen in a choline deficient diet. Such conditions trigger tumors in mice, particularly in the B6C3F1 strain. Again, the historical perspective recalled by Newberne’s comment brings us back to insulin. Indeed, after the discovery of insulin in 1922, Banting and Best were able to keep alive for several months depancreatized dogs, treated with pure insulin. However, these dogs developed a fatty liver and died. Unlike pure insulin, the total pancreatic extract contained a substance that prevented fatty liver: a lipotropic substance identified later as being choline. Like other lipotropes, (methionine, folate, B12) choline supports transmethylation reactions, of a variety of substrates, that would change their cellular fate, or action, after methylation. In the particular case concerned here, the removal of triglycerides from the liver, as very low-density lipoprotein particles (VLDL), requires the synthesis of lecithin, which might decrease if choline and S-adenosyl methionine (SAM) are missing. Hence, a choline deficient diet decreases the removal of triglycerides from the liver; a fatty liver and tumors may then form. In sum, we have seen that pathways exemplified by the insulin-tyrosine kinase signaling pathway, which control anabolic processes, mitosis, growth and cell death, are at each step targets for oncogenes; we now find that insulin may also provoke fatty liver and cancer, when choline is not associated to insulin.

We know that after the tyrosine kinase reaction, serine-threonine kinases take over along the signaling route. It is thus highly probable that serine-threonine phosphatases will counteract the kinases and limit the intensity of the insulin or insulin like signals. One of the phosphatases involved is PP2A, itself the target of DNA viral oncogenes (Polyoma or SV40 antigens react with PP2A subunits and cause tumors). We found a possible link between the PP2A phosphatase brake and choline. the catalytic C subunit of PP2A is associated to a structural subunit A. When C receives a methyl, the dimer recruits a regulatory subunit B. The trimer then targets specific proteins that are dephosphorylated. choline, via SAM, methylates PP2A, which is targeted toward the serine-threonine kinases that are counteracted along the insulin-signaling pathway.

The choline dependent methylation of PP2A is the brake, the “antidote”, which limits “the poison” resulting from an excess of insulin signaling. Moreover, it seems that choline deficiency is involved in the L to M2 transition of PK isoenzymes. The negative regulation of Ras/MAP kinase signals mediated by PP2A phosphatase seems to be complex. The serine-threonine phosphatase does more than simply counteracting kinases; it binds to the intermediate Shc protein on the signaling cascade, which is inhibited. The targeting of PP2A towards proteins of the signaling pathway depends of the assembly of the different holoenzymes.

The relative decrease of methylated PP2A in the cytosol, not only cancels the brake over the signaling kinases, but also favors the inactivation of PK and PDH, which remain phosphorylated, contributing to the metabolic anomaly of tumor cells. In order to prevent tumors, one should then favor the methylation route rather than the phosphorylation route for choline metabolism. This would decrease triglycerides, promote the methylation of PP2A and keep it in the cytosol, reestablishing the brake over signaling kinases. Moreover, PK, and PDH would become active after the phosphatase action. One would also gain to inhibit their kinases as recently done with dichloroacetate for PDH kinase. The nuclear or cytosolic targeting of PP2A isoforms is a hypothesis also inspired by several works.
Hypoxic adaptations in the presence of oxygen
Through different biochemical and biophysical pathways, which are characteristic to cancer cells, tumor cells adopt this phenotype, i.e., high glycolysis and decreased respiration, in the presence of oxygen. It has been shown that although the induction of hypoxia and cellular proliferation engage entirely different cellular pathways, they often coexist during tumor growth. The ability of cells to grow during hypoxia results, in part, from the crosstalk between hypoxia-inducible factors (Hifs) and the proto-oncogene c-Myc. These genes partially regulate the development of complex adaptations of tumor cells growing in low O2, and contribute to fine tuning the adaptive responses of cells to hypoxic environments.

Hypoxic conditions seem to trigger back the expression of the fetal gene packet via HIF1-Von-Hippel signals. The mechanism would depend of a double switch since not all fetal genes become active after hypoxia. First, the histones have to be in an acetylated form, opening the way to transcription factors, this depends either of histone eacetylase (HDAC) inhibition or of histone acetyltransferase (HAT) activation, and represents the main switch

Growth hormone-IGF actions, the control of asymmetrical mitosis
When IGF – Growth hormone operate, the fatty acid source of acetyl CoA takes over. Indeed, GH stimulates a triglyceride lipase in adipocytes, increasing the release of fatty acids and their b oxidation. In parallel, GH would close the glycolytic source of acetyl CoA, perhaps inhibiting the hexokinase interaction with the mitochondrial ANT site. This effect, which renders apoptosis possible, does not occur in tumor cells. GH mobilizes the fatty acid source of acetyl CoA from adipocytes, which should help the formation of ketone bodies. Since citrate synthase activity is elevated in tumors, ketone bodies do not form. This result silences several genes like PETEN, P53, or methylase inhibitory genes. It is probable that the IGFBP gene gets silent as well.

Uncoupling Proteins in Cancer
Uncoupling proteins (UCPs) are a family of inner mitochondrial membrane proteins whose function is to allow the re-entry of protons to the mitochondrial matrix, by dissipating the proton gradient and, subsequently, decreasing membrane potential and production of reactive oxygen species (ROS). Due to their pivotal role in the intersection between energy efficiency and oxidative stress, UCPs are being investigated for a potential role in cancer.

Mitochondria have been shown to be key players in numerous cellular events tightly related with the biology of cancer. Although energy production relies on the glycolytic pathway in cancer cells, these organelles also participate in many other processes essential for cell survival and proliferation such as ROS production, apoptotic and necrotic cell death, modulation of oxygen concentration, calcium and iron homeostasis, and certain metabolic and biosynthetic pathways. Many of these mitochondrial-dependent processes are altered in cancer cells, leading to a phenotype characterized, among others, by higher oxidative stress, inhibition of apoptosis, enhanced cell proliferation, chemoresistance, induction of angiogenic genes and aggressive fatty acid oxidation. Uncoupling proteins, a family of inner mitochondrial membrane proteins specialized in energy-dissipation, has aroused enormous interest in cancer due to their relevant impact on such processes and their potential for the development of novel therapeutic strategies.
Briefly, oxidation of reduced nutrient molecules, such as carbohydrates, lipids, and proteins, through cellular metabolism yields electrons in the form of reduced hydrogen carriers NADH+ and FADH2. These reduced cofactors donate electrons to a series of protein complexes embedded in the inner mitochondrial membrane known as the electron transport chain (ETC). These complexes use the energy released from electron transport for active pumping of protons across the inner membrane, generating an electrochemical gradient. Mitochondria orchestrate conversions between different forms of energy, coupling aerobic respiration to phosphorylation.
Conversion of metabolic fuel into ATP is not a fully efficient process. Some of the energy of the electrochemical gradient is not coupled to ATP production due to a phenomenon known as proton leak, which consists of the return of protons to the mitochondrial matrix through alternative pathways that bypass ATP synthase. Although this apparently futile cycle of protons is physiologically important, accounting for 20-25% of basal metabolic rate, its function is still a subject of debate. Several different functions have been suggested for proton leak, including thermogenesis, regulation of energy metabolism, and control of body weight and attenuation of reactive oxygen species (ROS) production. Although a part of the proton leak may be attributed to biophysical properties of the inner membrane, such as protein/lipid interfaces, the bulk of the proton conductance is linked to the action of a family of mitochondrial proteins termed uncoupling proteins.

Mitochondria are the major sources of reactive oxygen species (ROS). Aerobic respiration involves the complete reduction of oxygen to water, which is catalysed by complex IV (or cytochrome c oxidase). Nevertheless, during the transfer of electrons along the electron transport complexes, single electrons sometimes escape and result in a single electron reduction of molecular oxygen to form a superoxide anion, which, in turn is the precursor of other ROS.

One of the most interesting functions attributed to UCPs is their ability to decrease the formation of mitochondrial ROS. Mitochondria are the main source of ROS in cells. Superoxide formation is strongly activated under resting (state 4) conditions when the membrane potential is high and the rate of electron transport is limited by lack of ADP and Pi. Thus, there is a well established strong positive correlation between membrane potential and ROS production.
A small increase in membrane potential gives rise to a large stimulation of ROS production, whereas a small decrease in membrane potential (10 mV) is able to inhibit ROS production by 70% . Therefore, mild uncoupling, i.e., a small decrease in membrane potential, has been suggested to have a natural antioxidant effect.

Consistent with such a proposal, the inhibition of UCPs by GDP in mitochondria has been shown to increase membrane potential and mitochondrial ROS production. The loss of UCP2 or UCP3 in knockouts yielded increased ROS production concurrent with elevated membrane potential specifically in those tissues normally expressing the missing protein.
The hypothesis of UCPs as an antioxidant defense has been strongly supported by the fact that these proteins have been shown to be activated by ROS or by-products of lipid peroxidation, showing that UCPs would form part of a negative feed-back mechanism aimed to mitigate excessive ROS production and oxidative damage.
ROS and Cancer
ROS are thought to play multiple roles in tumor initiation, progression and maintenance, eliciting cellular responses that range from proliferation to cell death. In normal cells, ROS play crucial roles in several biological mechanisms including phagocytosis, proliferation, apoptosis, detoxification and other biochemical reactions. Low levels of ROS regulate cellular signaling and play an important role in normal cell proliferation. During initiation of cancer, ROS may cause DNA damage and mutagenesis, while ROS acting as second messengers stimulate proliferation and inhibit apoptosis, conferring growth advantage to established cancer cells. Cancer cells have been found to have increased ROS levels.

One of the functional roles of these elevated ROS levels during tumor progression is constant activation of transcription factors such as NF-kappaB and AP-1 which induce genes that promote proliferation and inhibit apoptosis. In addition, oxidative stress can induce DNA damage which leads to genomic instability and the acquisition of new mutations, which may contribute to cancer progression.

Role of ROS in control of proliferation and apoptosis
ROS are also essential mediators of apoptosis which eliminates cancer and other cells that threaten our health [81–86]. Many chemotherapeutic drugs and radiotherapy are aimed at increasing ROS levels to promote apoptosis by stimulating pro-apoptotic singaling molecules such as ASK1, JNK and p38. Because of the pivotal role of ROS in triggering apoptosis, antioxidants can inhibit this protective mechanism by depleting ROS. Thus, antioxidant mechanisms are thought to interfere with the therapeutic activity of anticancer drugs that kill advanced stage cancer cells by apoptosis.

Effect of uncoupling proteins on proliferation and apoptosis in relation to ROS levels

Uncoupling-to-survive hypothesis (proposed by Brand)

  • the ability of UCP2 to increase lifespan is mediated by decreased ROS production and oxidative stress.
  • the ability of mild uncoupling to avoid ROS formation, gives a reasonable argument to hypothesize about a role for UCPs in cancer prevention

Consistently, Derdák et al. showed that Ucp2−/− mice treated with the carcinogen azoxymethane were found to develop more aberrant crypt foci and colon tumours than Ucp2+/+ in relation with increased oxidative stress and enhanced NF-kappaB activation.

Roles of UCPs in Cancer Progression
The growth of a tumor from a single genetically altered cell is a stepwise progression requiring the alterations of several genes which contribute to the acquisition of a malignant phenotype. Such genetic alterations are positively selected when in the tumor, they confer a proliferative, survival or treatment resistance advantage for the host cell. In addition, several mutations, such as those silencing tumour suppressor genes, trigger the probability of accumulating new mutations, so the process of malignant transformation is progressively self-accelerated.

Considering the ability of UCPs to modulate mutagenic ROS, as well as mitochondrial bioenergetics and membrane potential, both involved in regulation of cell survival, an interesting question is whether UCPs can be involved in the progression of cancer.

Increased uncoupled respiration may be a mechanism to lower cellular oxygen concentration and, thus, alter molecular pathways of oxygen sensing such as those regulated by hypoxia-inducible factor (HIF). In normoxia, the alpha subunit of HIF-1 is a target for prolyl hydroxylase, which makes HIF-1alpha a target for degradation by the proteasome. During hypoxia, prolyl hydroxylase is inhibited since it requires oxygen as a cosubstrate. Thus, hypoxia allows HIF to accumulate and translocate into the nucleus for induction of target genes regulating glycolysis, angiogenesis and hematopoiesis. By this mechanism, UCPs activity may contribute to increase the expression of genes related to the formation of blood vessels, and thus promote tumor growth.

Roles of UCPs in Cancer Energy Metabolism
Lynen and colleagues proposed that the root of the Warburg effect is not in the inability of mitochondria to carry out respiration, but rather would rely on their incapacity to synthesize ATP in response to membrane potential.

The ability of UCPs to uncouple ATP synthesis from respiration and the fact that UCP2 is overexpressed in several chemoresistant cancer cell lines and primary human colon cancers have lead to speculate about the existence of a link between UCPs and the Warburg effect. As mentioned above, uncoupling induced by overexpression of UCP2 has been shown to prevent ROS formation, and, in turn, increase apoptotic threshold in cancer cells, providing a pro-survival advantage and a resistance mechanism to cope with ROS-inducing chemo-therapeutic agents.

Mitochondrial Krebs cycle is one of the sources for these anabolic precursors. The export of these metabolites to cytoplasm for anabolic purposes involves the replenishment of the cycle intermediates by anaplerotic substrates such as pyruvate and glutamate. Thus, glycolysis-derived pyruvate, as well as alpha-ketoglutarate derived from glutaminolysis, may be necessary to sustain anaplerotic reactions. At the same time, to keep Krebs cycle functional, the reduced cofactors NADH and FADH2 would have to be re-oxidized, a function which relies on the mitochondrial respiratory chain. Once again, uncoupling may be crucial for cancer cell mitochondrial metabolism, allowing Krebs cycle to be kept functional to meet the vigorous biosynthetic demand of cancer cells.

Several cancer cells resistant to chemotherapeutics and radiation often exhibit higher rates of fatty acid oxidation and it has been observed that inhibition of fatty acid oxidation potentiates apoptotic death induced by chemotherapeutic agents. These findings are in agreement with the proposed need of fatty acid for the activity of UCPs, suggesting that the lack of these potential substrates or activators would decrease uncoupling activity, subsequently increasing membrane potential, ROS production and therefore lowering apoptotic threshold.

Roles of UCPs in Cancer Cachexia
Cachexia is a wasting syndrome characterized by weakness, weight and fat loss, and muscle atrophy which is often seen in patients with advanced cancer or AIDS. Cachexia has been suggested to be responsible for at least 20 % of cancer deaths and also plays an important part in the compromised immunity leading to death from infection. The imbalance between energy intake and energy expenditure underlying cachexia cannot be reversed nutritionally.

Alterations leading to high energy expenditure, such as excessive proton leak or mitochondrial uncoupling, are likely mechanisms underlying cachexia. In fact, increased expression of UCP1 in BAT and UCP2 and UCP3 in skeletal muscle have been shown in several murine models of cancer cachexia

Roles of UCPs in Chemoresistance

Cancer cells acquire drug resistance as a result of selection pressure dictated by unfavorable microenvironments. Although mild uncoupling may clearly be useful under normal conditions or under severe or chronic metabolic stress such as hypoxia or anoxia, it may be a mechanism to elude oxidative stress-induced apoptosis in advanced cancer cells. Several anti-cancer treatments are based on promotion of ROS formation, to induce cell growth arrest and apoptosis. Thus, increased UCP levels in cancer cells, rather than a marker of oxidative stress, may be a mechanisms conferring anti-apoptotic advantages to the malignant cell, increasing their ability to survive in adverse microenvironments, radiotherapy and chemotherapy. UCPs appear to play a permissive role in tumor cell survival and growth.

Expression of UCPs promote bioenergetics adaptation and cell survival. UCPs appear to be critical to determine the sensitivity of cancer cells to several chemotherapeutic agents and radiotherapy, interfering with the activation of mitochondria driven apoptosis.

From a therapeutic viewpoint, inhibition of glycolysis in UCP2 expressing tumours or specific inhibition of UCP2 are, respectively, attractive strategies to target the specific metabolic signature of cancer cells.

Hypoxia-inducible factor-1 in tumour angiogenesis
HIF-b subunits, is a heterodimeric transcriptional activator. In response to

  • stimulation of growth factors, and
  • activation of oncogenes as well as carcinogens,

HIF-1a is overexpressed and/or activated and targets those genes which are required for angiogenesis, metabolic adaptation to low oxygen and promotes survival.

Several dozens of putative direct HIF-1 target genes have been identified on the basis of one or more cis-acting hypoxia-response elements that contain an HIF-1 binding site. Activation of HIF-1 in combination with activated signaling pathways and regulators is implicated in tumour progression and prognosis.
In order for a macroscopic tumour to grow, adequate oxygen delivery must be effected via tumor angiogenesis that results from an increased synthesis of angiogenic factors and a decreased synthesis of anti-angiogenic factors. The metabolic adaptation of tumor cells to reduced oxygen availability by increasing glucose transport and glycolysis to promote survival are important consequences in response to hypoxia.

Hypoxia and HIF-1
Hypoxia is one of the major drivers to tumour progression as hypoxic areas form in human tumours when the growth of tumour cells in a given area outstrips local neovascularization, thereby creating areas of inadequate perfusion. Although several transcriptional factors have been reported to be involved
in the response to hypoxic stress such as AP-1, NF-kB and HIF-1, HIF-1 is the most potent inducer of the expression of genes such as those encoding for glycolytic enzymes, VEGF and erythropoietin.

HIF-a subunit exists as at least three isoforms, HIF-1a, HIF-2a and HIF-3a. HIF-1a and HIF-2a can form heterodimers with HIF-b. Although HIF-b subunits are constitutive nuclear proteins, both HIF-1a andHIF-2a subunits are strongly induced by hypoxia in a similar manner. HIF-1a is up-regulated in hypoxic tumour cells and activates the transcription of target genes by binding to cis-acting enhancers, hypoxic responsive element (HRE) close to the promoters of these genes with a result of tumour cellular adaptation to hypoxia and tumour angiogenesis, and promotion of further growth of the primary tumour. Studies have shown HIF-1a to be over-expressed by both tumour cells and such stromal cells as macrophages in many forms of human malignancy.

Regulation of HIF-1
The first regulator of HIF-1 is oxygen. HIF-1α appears to be the HIF-1 subunit regulated by hypoxia. The oxygen sensors in the HIF-1α pathway are two kinds of oxygen dependent hydroxylases. One is prolyl hydroxylase which could hydroxylize the proline residues 402 and 564 at the oxygen dependent domain (ODD) of HIF-1 in the presence of oxygen and iron with a result of HIF-α degradation. The other is hydroxylation of Asn803 at the C-terminal transactivation domain (TAD-C) by FIH-1, which could inhibit the interaction of HIF-1α with co-activator p300 with a subsequent inhibition of HIF-1α transactivity. The hydroxylation of proline 564 at ODD of HIF-1α under normoxia was shown using a novel hydroxylation-specific antibody to detect hydroxylized HIF-1α.

Oncogene comes as the second regulator. Many oncogenes have effects on HIF-1α. Among them, some function in regulation of HIF-1α protein stability or degradation, others play roles in several activated signaling pathways. Tumor suppressor genes as p53 and von Hippel-Lindau (VHL) influence the levels and functions of HIF-1. The wild type (wt) form of p53 protein was involved in inhibiting HIF-1 activity by targeting the HIF-1a subunit for Mdm2-mediated ubiquitination and proteasomal degradation, and in inducing inhibitors of angiogenesis such as thrombospondin-1, while loss of wt p53 (by gene deletion or mutation) could enhance HIF-1α accumulation in hypoxia.

The third regulator is a battery of growth factors and cytokines from stromal and parenchymal cells such as

  • EGF,
  • transforming growth factor-α,
  • insulin-like growth factors 1 and 2,
  • heregulin, and interleukin-1b

via autocrine and paracrine pathways. These regulators not only induce the expression of HIF-1α protein, HIF-1 DNA binding activity and transactivity, but also make HIF-1 target gene expression under normoxia or hypoxia.
The fourth one is a group of reactive oxygen species (ROS) resulting from carcinogens such as Vanadate and Cr (VI) or stimulation of cytokines such as angiotensin and TNFa. However, it seems controversial when it comes to the production of ROS under hypoxia and their individual role in regulation of HIF-1a. It is well known that ROS plays an important role in carcinogenesis induced by a variety of carcinogens.

Signaling Pathways Involved in Regulation of HIF-1α
HIF-1 is a phosphorylated protein and its phosphorylation is involved in HIF-1a subunit expression and/or stabilization as well as in the regulation of HIF-1 transcriptional activity. Three signaling pathways involved in the regulation of HIF-1α have been reported to date.

  • The PI-3k pathway has been mainly and frequently implicated in regulation of HIF-1α protein expression and stability.
  • Akt is also activated by hypoxia. Activated Akt initiates two different pathways in regulation of HIF-1α. The function of these two pathways appears to show consistent impact on HIF-1α activation.
  • Signal transduction pathway in HIF-1α regulation.Oncogenes, growth factors and hypoxia have been documented to regulate HIF-1α protein and increase its transactivity. GSK and mTOR were two target events of Akt and could contribute to decreasing HIF-1α degradation and increasing HIF-1α protein synthesis. Activated ERK1/2 could mainly up-regulate.

HIF-1a, Angiogenesis and Tumour Prognosis
Hypoxia, oncogenes and a variety of growth factors and cytokines increase HIF-1α stability and/or synthesis and transactivation to initiate tumour angiogenesis, metabolic adaptation to hypoxic situation and promote cell survival or anti-apoptosis resulting from a consequence of more than sixty putative direct HIF-1 target gene expressions.

The crucial role of HIF-1 in tumour angiogenesis has sparked scientists and clinical researchers to try their best to understand the whole diagram of HIF-1 so as to find out novel approaches to inhibit HIF-1 overexpression. Indeed, the combination of anti-angiogenic agent and inhibitor of HIF-1 might be particularly efficacious, as the angiogenesis inhibitor would cut off the tumour’s blood supply and HIF-1 inhibitor would reduce the ability of tumour adaptation to hypoxia and suppress the proliferation and promote apoptosis. Screens for small-molecule inhibitors of HIF-1 are underway and several agents that inhibit HIF-1, angiogenesis and xenograft growth have been identified.

Hypoxia, autophagy, and mitophagy in the tumor stroma
Metabolomic profiling reveals that Cav-1(-/-) null mammary fat pads display a highly catabolic metabolism, with the increased release of several metabolites, such as amino acids, ribose and nucleotides, and a shift towards gluconeogenesis, as well as mitochondrial dysfunction. These changes are consistent with increased autophagy, mitophagy and aerobic glycolysis, all processes that are induced by oxidative stress. Autophagy or ‘self-eating’ is the process by which cells degrade their own cellular components to survive during starvation or to eliminate damaged organelles after oxidative stress. Mitophagy, or mitochondrial-autophagy, is particularly important to remove damaged ROS-generating mitochondria.

An autophagy/mitophagy program is also triggered by hypoxia. Hypoxia is a common feature of solid tumors, and promotes cancer progression, invasion and metastasis. Interestingly, via induction of autophagy, hypoxia is sufficient to induce a dramatic loss of Cav-1 in fibroblasts. The hypoxia-induced loss of Cav-1 can be inhibited by the autophagy inhibitor chloroquine, or by pharmacological inhibition of HIF1α. Conversely, small interfering RNA-mediated Cav-1 knock-down is sufficient to induce pseudo-hypoxia, with HIF1α and NFκB activation, and to promote autophagy/mitophagy, as well as a loss of mitochondrial membrane potential in stromal cells. These results indicate that a loss of stromal Cav-1 is a marker of hypoxia and oxidative stress.

In a co-culture model, autophagy in cancer-associated fibroblasts was shown to promote tumor cell survival via the induction of the pro-autophagic HIF1α and NFκB pathways in the tumor stromal microenvironment. Finally, the mitophagy marker Bnip3L is selectively upregulated in the stroma of human breast cancers lacking Cav-1, but is notably absent from the adjacent breast cancer epithelial cells.

Metabolome profiling of several types of human cancer tissues versus corresponding normal tissues have consistently shown that cancer tissues are highly catabolic, with the significant accumulation of many amino acids and TCA cycle metabolites. The levels of reduced glutathione were decreased in primary and metastatic prostate cancers compared to benign adjacent prostate tissue, suggesting that aggressive disease is associated with increased oxidative stress. Also, these data show that the tumor microenvironment has increased oxidative-stress-induced autophagy and increased catabolism.

Taken together, all these findings suggest an integrated model whereby
A loss of stromal Cav-1 induces autophagy/mitophagy in the tumor stroma, via oxidative stress.

This creates a catabolic micro-environment with the local accumulation of chemical building blocks and recycled nutrients (such as amino acids and nucleotides), directly feeding cancer cells to sustain their survival and growth.
This novel idea is termed the ‘autophagic tumor stroma model of cancer’ .
This new paradigm may explain the ‘autophagy paradox’, which is based on the fact that both the systemic inhibition and systemic stimulation of autophagy prevent tumor formation.

What is presented suggests that vectorial energy transfer from the tumor stroma to cancer cells directly sustains tumor growth, and that interruption of such metabolic coupling will block tumor growth. Autophagy inhibitors (such as chloroquine) functionally block the catabolic transfer of metabolites from the stroma to the tumor, inducing cancer cell starvation and death. Conversely, autophagy inducers (such as rapamycin) promote autophagy in tumor cells and induce cell death. Thus, both inhibitors and inducers of autophagy will have a similar effect by severing the metabolic coupling of the stroma and tumor cells, resulting in tumor growth inhibition (cutting ‘off ’ the fuel supply).

This model may also explain why enthusiasm for antiangiogenic therapy has been dampened. In most cases, the clinical benefits are short term, and more importantly, new data suggest an unexpected link between anti-angiogenic treatments and metastasis. In pre-clinical models, anti-vascular endothelial growth factor (anti-VEGF) drugs (sunitinib and anti-VEGFR2 blocking antibodies) were shown to inhibit localized tumor formation, but potently induced relapse and metastasis. Thus, by inducing hypoxia in the tumor microenvironment, antiangiogenic drugs may create a more favorable metastatic niche.
Glutamine, glutaminolysis.
In direct support that cancer cells use mitochondrial oxidative metabolism, many investigators have shown that cancer cells are ‘addicted’ to glutamine. Glutamine is a non-essential amino acid that is metabolized to glutamate and enters the TCA cycle as α-ketoglutarate, resulting in high ATP generation via oxidative phosphorylation. Recent studies also show that ammonia is a by-product of glutaminolysis. In addition, ammonia can act as a diffusible inducer of autophagy. Given these observations, glutamine addiction in cancer cells provides another mechanism for driving and maintaining autophagy in the tumor micro-environment .

In support of this idea, a loss of Cav-1 in the stroma is sufficient to drive autophagy, resulting in increased glutamine production in the tumor micro-environment. Thus, this concept defines a new vicious cycle in which autophagy in the tumor stroma transfers glutamine to cancer cells, and the by-product of this metabolism, ammonia, maintains autophagic glutamine production. This model fits well with the ‘autophagic tumor stroma model of cancer metabolism’, in which energy rich recycled nutrients (lactate, ketones, and glutamine) fuel oxidative mitochondrial metabolism in cancer cells.

Glutamine utilization in cancer cells and the tumor stroma. Oxidative mitochondrial metabolism of glutamine in cancer cells produces ammonia. Ammonia production is sufficient to induce autophagy. Thus, autophagy in cancer-associated fibroblasts provides cancer cells with an abundant source of glutamine. In turn, the ammonia produced maintains the autophagic phenotype of the adjacent stromal fibroblasts.

Lessons from other paradigms

an infectious parasitic cancer cell that metastasizes and captures mitochondrial DNA from host cells
Cancer cells behave like ‘parasites’, by inducing oxidative stress in normal host fibroblasts, resulting in the production of recycled nutrients via autophagy.

This is exactly the same mechanism by which infectious parasites (such as malaria) obtain nutrients and are propagated by inducing oxidative stress and autophagy in host cells. In this regard, malaria is an ‘intracellular’ parasite, while cancer cells may be thought of as ‘extracellular’ parasites. This explains why chloroquine is both an effective antimalarial drug and an effective anti-tumor agent, as it functions as an autophagy inhibitor, cutting off the ‘fuel supply’ in both disease states.

Human cancer cells can ‘steal’ live mitochondria or mitochondrial DNA from adjacent mesenchymal stem cells in culture, which then rescues aerobic glycolysis in these cancer cells. This is known as mitochondrial transfer. Interestingly, metastatic breast cancer cells show the up-regulation of numerous mitochondrial proteins, specifically associated with oxidative phosphorylation, as seen by unbiased proteomic analysis.

Thus, increased mitochondrial oxidative metabolism may be a key driver of tumor cell metastasis. In further support of this argument, treatment of MCF7 cancer cells with lactate is indeed sufficient to induce mitochondrial biogenesis in these cells.

To determine if these findings may be clinically relevant, a lactate-induced gene signature was recently generated using MCF7 cells. This gene signature shows that lactate induces ‘stemness’ in cancer cells, and this lactate induced gene signature predicts poor clinical outcome (including tumor recurrence and metastasis) in breast cancer patients.


Li W and Zhao Y. “Warburg Effect” and Mitochondrial Metabolism in Skin Cancer. Epidermal Pigmentation, Nucleotide Excision Repair and Risk of Skin Cancer. J Carcinogene Mutagene 2012; S4:002 doi:10.4172/2157-2518.
Seyfried TN, Shelton LM. Cancer as a metabolic disease. Nutrition & Metabolism 2010; 7:7(22 pg). doi:10.1186/1743-7075-7-7
Israël M, Schwartz L. The metabolic advantage of tumor cells. Molecular Cancer 2011, 10:70-82.
Valle A, Oliver J, Roca P. Role of Uncoupling Proteins in Cancer. Cancers 2010, 2, 567-591; doi:10.3390/cancers2020567
Ishii H, Doki Y, Mori M. Perspective beyond Cancer Genomics: Bioenergetics of Cancer Stem Cells. Yonsei Med J 2010; 51(5):617-621. DOI 10.3349/ymj. 2010.51.5.617 pISSN: 0513-5796, eISSN: 1976-2437
Sotgia F, Martinez-Outschoorn, Pavlides S,Howell A . Understanding the Warburg effect and the prognostic value of stromal caveolin-1 as a marker of a lethal tumor microenvironment. Breast Cancer Research 2011, 13:213-26.
Yong-Hong Shi, Wei-Gang Fang. Hypoxia-inducible factor-1 in tumour angiogenesis. World J Gastroenterol 2004; 10(8): 1082-1087. http:// /1007-9327/10/1082.asp

English: Glycolysis pathway overview.

English: Glycolysis pathway overview. (Photo credit: Wikipedia)

Adenosine triphosphate





/* Style Definitions */
{mso-style-name:”Table Normal”;
mso-padding-alt:0in 5.4pt 0in 5.4pt;

Warburg Effect, glycolysis, pyruvate kinase, PKM2, PIM2, mtDNA, complex I, NSCLC

Ribeirão Preto Area, Brazil|Government Relations
Current- University, USP-FMRP Physiology – Biochemistry
Previous- Imperial Cancer Research Fund Lab, Instituto de Investigaciones Bioquimicas, Luta armada e CIA
Education – FMRP-USP
While exile interrupted ny graduation in Medicine, started a port grade at Leloir´s Instituto Investigaciones bioquímicas Buenos Aires Argentina Jan 1970 – jan 1972. PhD from 1972- jan 1976 FMRP-USP . Post Doc ICRF London England 1979 -1980

“Those…..whose acquitance with scientific research is derived chiefly from its practical results easily develop a completely false notion of the { scientific } mentality.”

My goal and previous experience besides laboratory work was dedicated to solve this apparent conflict.

When Pasteur did his work studying the chemistry outside yeast-cells, he was able to perceive that in anaerobiosis yeast cells were able to convert sugar at a great velocity to its end products. While the same yeast cells, therefore with the same genome did it at a very slow speed in aerobiosis. Warburg tested tumor cells for the same and found that while normal cells from the organ in which he has found tumors presented a similar metabolic regulatory response to anaerobic/aerobic transition tumor cells did not. Tumos cells continued to display strong acidification (producing great amounts of lactate in the culture media) in aerobiosis.

Tumor cells displayed a failure in this regulatory mechanism that, he O. Warburg, named Pasteur effect. He also noticed that this defect continues from old cancer cells to newer ones. Therefore, for him, it is a genetic defect. Furthermore, as mitochondria generates newer mitochondria in the cells, the genetic component is in the mitochondria that were the site of core metabolism in aerobiosis.

Larry Bernstein
Part of what you describe is in Warburg biography by Hans Krebs (out of print). He also refers to a Meyerhof Quotient to express the degree of metabolic anaerobiosis. I don’t recall a reference to a mitochondrial “genetic” defect. That is farsighted. He did conclude that once the cancer cells were truly anaplastic, metastatic behavior was irreversible. It was only later that another Nobelist who described fatty acid synthesis, I think, concluded that the synthetic process tied up the same aerobic pathway so that anaerobic glycolysis became essential for the cells energetics. You can correct me if I’m in error. Where does the substrate come from? Lean body mass breaks down to provide gluconeogenic precursors. Points of concern are – deamination of branch chain AAs, the splitting of a 6 carbon sugar into 2 3-carbon chains, and the conversion of pyruvate to lactate with the reverse reaction blocked. There is also evidence that there is an impairment in the TCA cycle at the point of fumarase. Then there is never any consideration of the flow of substrates back and forth across the mitochondrial membrane (malate, aspartate), and the redox potentials.

Jose: For reasons independent of my will, the copy of Science,123(3191):309-14,1956 translation of O Warburg original article is not in my hands. Some that do not find any alternative form to respond to my critics concerning molecular biology distortion of biochemistry left on purpose, almost all of my older reprints on the rain. Anyway, O. Warburg refers to mitochondria using the expression of “grana” or “grains” if my recollections are correct. The original work of O Warburg is one of 1924 – Biochemisch ZeiTschrift.,152:51-60.1924. “Weberssert method zur messing der atmung un glycolyse, drese zeitschr.” Other aspects of your interesting comment I will try to comment latter.

By Jose Eduardo de Salles Roselino
Larry Bernstein, not as a correction but , following my line of reasoning about carbono fluxes…It is almost impossible to figure out what was really inside the mind-set of a scientific researcher at the time he has performed his work. Anyway, by the knowledge available at his time, we may conjecture about, even when we acknowledge that, what he may have had in mind at the start could be quite different from what he have latter published from his results.
In case, we try to present the ideas behind Warburg´s works we may take into account the following pre-existing knowledge: Lavoisier (done by 1779-1784) measured very carefully the amount of heat released by respiration and chemical oxidative processes. Reached the conclusion that respiration was slower but essentially similar to carbon combustion by chemical oxidative processes. By early XIX caloric values for gram of sugar, lipids and proteins where made clear. T Schwann recognized that yeast cells convert sugar in ethanol plus a volatile acid (carbon dioxide). Pasteur-effect was seen just as a change in the velocity of product production from a same sugar and/or a decrease in sugar concentration in the growth medium. This is a change in carbon flux velocity in the oxidative process calorimetrically measured by Lavoisier.
In Germany, however, the preponderance of organic chemical point of view has great scientists as Berzelius, Liebig etc. to consider that yeast where similar to inorganic catalysts. The oxidative process was caused by oxygen only. You may amuse yourself reading, how they attack T. Schwann proposal in Annalen, 29: 100 (1839). When O Warburg paid tribute to L. Pasteur, we can see clearly on which side he was. Furthermore, his apparatus, in which I was introduced to this line of research, a rather modern version at that time (1960s) that look like a very futuristic robotic version of the original with a pair of blinking red and green round lights as two eyes on a metallic head, offers a very important clue about the change in carbon flow.
Inside a Warburg glass flask, kept at very finely controlled temperature to avoid changes in pressure derived from changes in the temperature, you would certainly find a central well in which the volatile acid must be trapped in order to determine a pressure reduction only due to the decrease in oxygen pressure. Inside this central well, you could determine one product (carbon dioxide) and in the outside of it where tissues or cells where in the media you could also determine the other end product of the oxidative combustion of sugar (lactate). This has provide him with the result that indicate not only a change in the velocity as originally found by Pasteur in yeast cells but in the organic flow of sugar carbons.

comment –  E-mail:

-About carcinogenesis- Electronegativity is a nucleus of an atom’s ability to attract and maintain a cloud of electrons. Copper atom electronegativity is higher than the Iron atom electronegativity. Atom with lower electronegativity (Iron),remove the atom with higher electronegativity (Copper) of combinations. This means that,in conditions of acidosis, we have cytochrome oxidase with iron (red, neoplastic), instead of cytochrome oxidase with copper (green, normal).I think this is the key to carcinogenesis. Siincerely, Dr. Viorel Bungau

Read Full Post »