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Feeling the Heat – the Link between Inflammation and Cancer
Reporter: Irina Robu, PhD
Researchers at Lerner Research Institute led by Dr. Xiaoxia Li revealed a new signaling pathway in a subset of hair follicle stem cells that can be linked to inflammation, wound healing and tumorigenesis giving new insights into how to potential target to slow or prevent tumor initiation. However, previous research shows that uncontrolled tissue repair is usually associated with tumor formation, but there is no direct connection between them.
The scientists found that the proinflammatory cytokine, IL-17A plays a vital role in aberrant tissue repair. They showed that when IL-17A signaling is turned on, Lrig1+ stem cells expanded and their progeny translocated to other layers of the skin in reply to injury. Through a series of investigations, Dr. Li showed that the presence and physical proximity of a series of proteins sets into motion a complex signaling cascade that results in activation of ERK5 (extracellular signal regulated kinase 5), which is ultimately responsible for the expansion and migration of Lrig1+ stem cells. While many proteins including interleukin-17 receptor, epidermal growth factor receptor and Act1 are involved, tumor necrosis factor receptor associated factor 4 is the first receptor to fail, setting the entire signaling cascade in motion.
Considering that this is the first study to show that a proinflammatory cytokine can recruit a growth factor receptor to activate stem cells in support of tissue repair and tumorigenesis. This proves that tumor necrosis factor receptor associated factor 4 may be a viable therapeutic target to pursue in upcoming studies.
DNA sequences were once thought to be the same in every cell, but the story is now known to be more complicated than that. The brain is a case in point: Mutations can arise at different times in brain development and affect only a percentage of neurons, forming a mosaic pattern.
Now, thanks to new technology described last week in Neuron, these subtle “somatic” brain mutations can be mapped spatially across the brain and even have their ancestry traced.
Like my family, who lived in Eastern Europe, migrated to lower Manhattan and branched off to Boston, California and elsewhere, brain mutations can be followed from the original mutant cells as they divide and migrate to their various brain destinations, carrying their altered DNA with them.
“Some mutations may occur on one side of the brain and not the other,” says Christopher Walsh, MD, PhD, chief of Genetics and Genomics at Boston Children’s Hospital and co-senior author on the paper. “Some may be ‘clumped,’ affecting just one gyrus [fold] of the brain, disrupting just a little part of the cortex at a time.”
This tracking capability represents a significant advance for genetics research. And for neuroscientists, it provides a new way to study both the normal brain and brain disorders like epilepsy, autism and intellectual disability.
Walsh and colleagues studied normal brain tissue from a teenage boy who had passed away from other causes. Sampling in more than 30 brain locations, they used deep, highly sensitive, whole-genome sequencing of one neuron at a time—unlike usual methods, which sequence thousands or millions of cells mixed together and simply read out an average.
The blue and green boxes indicate different degrees of mosaicism (based on proportion of cells affected) in the left half of this teen’s normal brain. The blue shaded area indicates that retrotransposon mutation #1 (blue boxes) is limited to a focal area in the middle frontal gyrus. The empty boxes indicate areas where mutation #1 was not detected. (Courtesy Gilad Evrony, PhD, Boston Children’s Hospital)
Next, using technology developed by Alice (Eunjung) Lee in the lab of Peter Park, PhD, at Harvard Medical School’s Center for Biomedical Informatics, they zeroed in on inserted bits of DNA caused by retrotransposons, one type of mutation that can arise as the brain develops. These essentially served as markers that allowed cell lineages to be traced.
“Our findings are intriguing because they suggest that every normal brain may in fact be a mosaic patchwork of focal somatic mutations, though in normal individuals most are likely silent or harmless,” says Gilad Evrony, PhD, in the Walsh Lab.
This model illustrates the origins of two somatic retrotransposon mutations during prenatal development and their subsequent dissemination in the brain. Insertion #2 (in green) occurred soon after conception; #1 (in blue) happened sometime later during brain development. The ‘pie slices’ show a closeup of the layers of the cerebral cortex. Later in development, additional somatic mutations occurred inside insertions #1 and #2, creating new, smaller sublineages of cells. (Courtesy Gilad Evrony, PhD)
A parallel study from Walsh’s lab in 2014 used single-neuron sequencing to find copy number variants— a different type of mutation affecting the number of copies of chromosomes or chromosome fragments. It, too, found the mutations to be present in normal brains as well as neurologically diseased brains.
Walsh and others speculate that some somatic brain mutations might play a role in autism, epilepsy, schizophrenia and other unsolved neuropsychiatric diseases whose causes are mostly still a mystery.
“It is possible that a whole new class of brain disorders may exist that has not been previously recognized,” says Evrony. “In such disorders, a somatic mutation may subtly affect only one small part of the brain involved in a specific ability, for example language, while sparing the rest of the brain.”
BOSTON, Jan. 7, 2015 /PRNewswire-USNewswire/ — DNA sequences were once thought to be identical from cell to cell, but it’s increasingly understood that mutations can arise during brain development that affect only certain groups of brain cells. A technique developed at Boston Children’s Hospital allows these subtle mutation patterns to be traced and mapped spatially for the first time. This capability is a significant advance for genetics research and provides a new way to study both the normal brain and brain disorders such as epilepsy and autism.
Described in the January 7th issue of Neuron, the technique uses “deep,” highly sensitive whole-genome sequencing of single neurons and a new technology that identifies inserted bits of DNA caused by retrotransposons, one of several kinds of so-called somatic mutations that can arise as the brain develops.
The technique picks up somatic mutations that affect just a fraction of the brain’s cells, in a “mosaic” pattern. It also allows “lineage tracing,” showing when during brain development the mutations arise and how they spread through brain tissue as the mutated cells grow, replicate and migrate, carrying the mutation with them.
“There is a lot of genetic diversity from one neuron to the other, and this work gets at how somatic mutations are distributed in the brain,” says Christopher Walsh, MD, PhD, chief of Genetics and Genomics at Boston Children’s and co-senior author on the paper. “Some mutations may occur on one side of the brain and not the other. Some may be ‘clumped,’ affecting just one gyrus [fold] of the brain, disrupting just a little part of the cortex at a time.”
The study examined brain tissue from a deceased 17-year-old who had been neurologically normal, sampling in more than 30 brain locations. It builds on work published by the Walsh lab in 2012, which developed methods to sequence the genomes of single neurons, and represents the first time single neurons have been sequenced in their entirety. The single-cell technique is better at detecting subtle mosaicism than usual DNA sequencing methods, which sequence many thousands or millions of cells mixed together and read out an average for the sample.
Somatic brain mutations, affecting just pockets of cells, can be harmful, and have been suggested as a possible cause of neurodevelopmental disorders such as autism, epilepsy or intellectual disability (see this review article for further background). But they also can be completely benign or have just a subtle effect.
“Our findings are intriguing because they suggest that every normal brain may in fact be a mosaic patchwork of focal somatic mutations, though in normal individuals most are likely silent or harmless,” says Gilad Evrony, PhD, in the Walsh Lab, co-first author on the Neuron paper. “These same technologies can now be used to study the brains of people who died from unexplained neuropsychiatric diseases to determine whether somatic mutations may be the cause.”
Finally, says Evrony, the findings provide a proof-of-principle for a systematic way of studying how brain cells disperse and migrate during development, “something that has not been possible to do before in humans,” he says.
Co-first author Alice Eunjung Lee, PhD, from the lab of Peter Park, PhD, at the Center for Biomedical Informatics at Harvard Medical School, developed the study’s retrotransposon analysis tool, which detects somatic retrotransposon mutations in single-cell sequencing data.
Mirroring these findings, study published by Walsh’s lab in 2014 used single-neuron sequencing to detect copy number variants—another type of mutation affecting the number of copies of chromosomes or chromosome fragments. The study found that these mutations can occur in both normal and neurologically diseased brains.
Evrony and Lee are first authors on the Neuron paper; Walsh and Park are senior authors. The research was supported by the National Institutes of Health (MSTP grant T32GM007753), the National Institute of Neurological Disorders and Stroke (R01 NS079277 and R01 NS032457), the Louis Lange III Scholarship in Translational Research, the Eleanor and Miles Shore Fellowship, the Research Connection and the Manton Center for Orphan Disease Research at Boston Children’s Hospital, the Paul G. Allen Family Foundation and the Howard Hughes Medical Institute.
SOURCE Boston Children’s Hospital
Beth Stevens: A transformative thinker in neuroscience
When 2015 MacArthur “genius” grant winner Beth Stevens, PhD, began studying the role of glia in the brain in the 1990s, these cells—“glue” from the Greek—weren’t given much thought. Traditionally, glia were thought to merely protect and support neurons, the brain’s real players.
But Stevens, from the Department of Neurology and the F.M. Kirby Neurobiology Center at Boston Children’s Hospital, has made the case that glia are key actors in the brain, not just caretakers. Her work—at the interface between the nervous and immune systems—is helping transform how neurologic disorders like autism, amyotrophic lateral sclerosis (ALS), Alzheimer’s disease and schizophrenia are viewed.
Soon after college graduation in 1993, without prior experience in neuroscience, she helped discoveran interplay between neurons and glial cells known as Schwann cells that controlled production of the nerve insulation known as myelin It was one of the early pieces of evidence that glia and neurons talk to each other.
In 2007, while still a postdoctoral fellow, Stevens showed how star-shaped glial cells called astrocytes influence the development of synapses, or brain connections. Studying neurons, her lab showed that a gene called C1q was markedly more active when astrocytes were present. C1q is an immune gene, one nobody had expected to see in a normal brain. In the context of disease, it initiates the complement cascade, an immunologic pathway for tagging unwanted cells and debris for clearance by other immune cells.
But in healthy developing brains, Stevens showed, C1q was concentrated at developing synapses, or brain connections, apparently marking certain synapses for pruning.
Then in 2012, the Stevens lab showed that microglia—another type of glia usually thought of as immune cells themselves—actively sculpt the brain’s wiring. They literally trim away unwanted, inappropriate synapses by eating them—in the same way they’d engulf and destroy invading bacteria.
Stevens’s current investigations are looking at synapse loss—a hallmark of neurodegenerative conditions such as Alzheimer’s—and trying to understand why it occurs. Her lab’s recent work suggests that normal pruning mechanisms that are active during early brain development get re-activated later in life. Intervening with this activation could lead to a new treatment approach, she believes.
Stevens isn’t the only brain researcher at Boston Children’s to become a MacArthur fellow. Neurosurgeon Benjamin Warf, MD, received the honor in 2012.
The above movie shows an immune cell caught in the act of tending the brain—it’s just eaten away unnecessary connections, or synapses, between neurons.
That’s not something these cells, known as microglia, were previously thought to do. As immune cells, it was thought that their job was to rid the body of unwanted pathogens and debris, by engulfing and digesting them.
The involvement of microglia in the brain’s development has started to be recognized only recently. The latest research finds that microglia tune into the brain’s cues, akin to the way they survey their environment for invading microbes, and get rid of excess synapses the same way they’d dispatch these invaders—by eating them.
It’s a whole other way of understanding how the healthy brain develops—at the hands of cells that were once thought to be merely nerve “glue” (the literal meaning of “glia” from the Greek), playing a protective role to neurons, say investigators Beth Stevens, PhD, and Dori Schafer, PhD, of the F.M. Kirby Neurobiology Center at Boston Children’s Hospital.
“In the field of neuroscience, glia have often been ignored,” says Stevens. “But glia aren’t the nerve glue, they’re actively communicating with neurons. People have gotten a new respect for glia and are hungry to know more about them.”
Such knowledge could eventually shed light on brain disorders ranging from autism to Alzheimer’s.
The “eat me” sign
We’re all born with more brain connections than we need. As we begin to encounter our world, they’re trimmed back to fine-tune our circuitry. It’s a bit of an oversimplification, but Stevens and Schafer demonstrated last week in the journal Neuron that when two neurons start talking to each other less – because their connection is no longer important to our lives– the microglia notice that and prune the synapse away.
To study microglia’s pruning activity, Stevens and Schafer used a time-honored model: the visual system. When you cover one eye soon after birth, you force the brain to rewire: Brain connections with the covered eye weaken and those synapses eventually get eliminated.
Using this model, Stevens and Schafer showed that microglia take their cues from a set of signals also used by the immune system, known as the complement cascade. Specifically, microglia carry receptors that recognize the complement protein C3—the same protein found on synapses that are destined for elimination.
“We think that weaker synapses are being tagged with C3, and that microglia are eliminating them just as macrophages would eliminate bacteria,” says Schafer. “C3 is like an ‘eat me’ signal.”
As a postdoctoral fellow in 2007, Stevens showed that neurons are loaded with complement proteins soon after birth, just when pruning is at its peak. In the new study, she and Schafer deliberately disrupted complement signaling in mice—stripping the microglia of C3 receptors, or blocking those receptors with a drug. When they did so, pruning of irrelevant synapses didn’t occur.
Stevens thinks their findings might have relevance for brain disorders. Developmental brain disorders such as autism, epilepsy or schizophrenia are increasingly seen as disorders of synapse development, and some data suggest that microglia and/or the complement cascade are involved.
At the other end of the spectrum, scientists have noted that microglia—normally in a resting state in adults—are activated in neurodegenerative diseases like glaucoma, Alzheimer’s disease, Lou Gehrig’s disease, Huntington’s disease and Parkinson’s disease. Subtle changes have been found in synapses that might cause them to be targeted for elimination.
So could targeting microglia or the complement cascade prevent synapse loss or alter pruning in these diseases? “All this is still very speculative,” Stevens cautions. “We first need to understand normal brain development.”
Beth Stevens
Neuroscientist
Assistant Professor of Neurology, F. M. Kirby Neurobiology Center, Boston Children’s Hospital
Beth Stevens is a neuroscientist whose research on microglial cells is prompting a significant shift in thinking about neuron communication in the healthy brain and the origins of adult neurological diseases. Until recently, it was believed that the primary function of microglia was immunological; they protected the brain by reducing inflammation and removing foreign bodies.
Stevens identified an additional, yet critical, role: the microglia are responsible for the “pruning” or removal of synaptic cells during brain development. Synapses form the connections, or means of communication, between nerve cells, and these pathways are the basis for all functions or jobs the brain performs. Using a novel model system that allows direct visualization of synapse pruning at various stages of brain development, Stevens demonstrated that the microglia’s pruning depends on the level of activity of neural pathways. She identified immune proteins called complement that “tag” (or bind) excess synapses with an “eat me” signal in the healthy developing brain. Through a process of phagocytosis, the microglia engulf or “eat” the synapses identified for elimination. This pruning optimizes the brain’s synaptic arrangements, ensuring that it has the most efficient “wiring.”
Stevens’s discoveries indicate that our adult neural circuitry is determined not only by the nerve cells but also by the brain’s immune cells. Her work suggests that adult diseases caused by deficient neural architecture (such as autism and schizophrenia) or states of neurodegeneration (such as Alzheimer’s or Huntington’s disease) may be the result of impaired microglial function and abnormal activation of this pruning pathway. Stevens is redefining our understanding of how the wiring in the brain occurs and changes in early life and shedding new light on how the nervous and immune systems interact in the brain, both in health and disease.
Beth Stevens received B.S. (1993) from Northeastern University and a Ph.D. (2003) from the University of Maryland. She was a postdoctoral fellow (2005–2008) at Stanford University and is currently an assistant professor in the Department of Neurology at Harvard Medical School and the F. M. Kirby Neurobiology Center at Boston Children’s Hospital. She is also an Institute Member of the Broad Institute of MIT and Harvard. Her scientific papers have appeared in such journals as Neuron, Science, Proceedings of the National Academy of Sciences, and Nature Neuroscience, among others.
Shortly after Beth Stevens launched her lab at Boston Children’s Hospital in 2008, she invited students from the Newton Montessori School, in a nearby suburb, to come for a visit. The children peered at mouse and rat brains bobbing in fluid-filled jars. They also learned how to position delicate slices of brain tissue on glass slides and inspect them with a microscope.
This visit sparked a running relationship with the school, with a steady stream of students visiting the growing lab each year. Soon it became too complicated to bring so many children to the lab, so Stevens decided to take her neuroscience lessons on the road, visiting a number of local elementary schools each year. Last year, she dropped in on the classrooms of her 5- and 8-year-old daughters, Zoe and Riley.
“The kids got really excited,” Stevens says. “It’s become such a thing that the principal wants me to come back for the whole school.”
Stevens’ enthusiasm for science has left a lasting impression on researchers, too. Her pioneering work points to a surprise role in brain development formicroglia, a type of cell once considered to simply be the brain’s immune defense system, cleaning up cellular debris, damaged tissue and pathogens. But thanks to Stevens, researchers now appreciate that these non-neuronal cells also play a critical role in shaping brain circuits.
In a 2012 discovery that created a buzz among autism researchers, Stevens and her colleagues discovered that microglia prune neuronal connections, calledsynapses, in the developing mouse brain. The trimming of synapses is thought to go awry in autism. And indeed, emerging work from Stevens’ lab hints at a role for microglia in the disorder.
Stevens has already earned praise and several prizes for her work. In 2012, shereceived the Presidential Early Career Award for Scientists and Engineers, the most prestigious award that the U.S. government bestows on young scientists. And in October, she’ll deliver one of four presidential lectures at the world’s largest gathering of neuroscientists — the annual meeting of the Society for Neuroscience — an honor she shares with three neuroscience heavyweights, including two Nobel laureates.
“The field is probably expecting a lot from Beth,” says Jonathan Kipnis, professor of neuroscience at the University of Virginia. Stevens has put microglia at the forefront, Kipnis says. “What used to be a stepchild of neuroscience research is now getting a lot of attention, and I think in part it’s due to her research.”
Curious mind:
Stevens was born in 1970 in Brockton, Massachusetts, where her mother taught elementary school and her father was the school’s principal. As a child, she was deeply inquisitive, eager to understand how things work. She enjoyed collecting bugs and worms, and would analyze these precious specimens in makeshift labs in her backyard.
But a career in science wasn’t on her radar until high school, when she took a biology class with an inspiring teacher named Anthony Cabral. “He totally made me realize that this could be a career, that I could be a scientist,” Stevens says. “It was that one class that changed it, and I’m like, ‘Okay, I’m going to do this.’”
In 1988, she began studying biology at Northeastern University in Boston, which offered an unusual opportunity. It had a unique cooperative education program that allowed Stevens to spend several semesters working full time in medical labs after finishing her coursework.
After that experience, Stevens knew she wanted to find a job in a research lab. After graduating in 1993, she joined her then-boyfriend Rob Graham, now her husband, in Washington, D.C., where he had landed a job in the U.S. Senate. Stevens headed to the National Institutes of Health (NIH) in Rockville, Maryland, to apply for a job as a research assistant.
At around the same time, neuroscientist R. Douglas Fields was launching his lab at the NIH. He studied how neural impulses influence glia — a class of non-neuronal cells that includes microglia — and shape the structure of the developing brain. Fields readily hired Stevens despite her lack of expertise in neuroscience. “I was impressed with her work ethic, energy and drive,” he says.
Stimulating research:
In Fields’ lab, Stevens used a multi-compartment cell culture system to investigate whether stimulating neurons influences the activity of Schwann cells, glial cells that produce a fatty substance called myelin, which insulates nerves1. She discovered that patterns of neural impulses similar to those that occur during early development influence the maturation of Schwann cells and the production of myelin.
The findings added to mounting evidence that glia and neurons communicate with each other, a newly emerging concept at the time.
“What I loved about the glia research was that there were so few neuroscientists studying it; it was such a mysterious part of neuroscience,” Stevens says. “Those years in Doug’s lab were really exciting because it was a new field.”
Stevens spent five years in Fields’ lab. “She was doing extraordinary work,” Fields says. “She had the potential and the interest to do neuroscience research, and I recommended that she should consider going to graduate school.”
But Stevens didn’t want to give up her position in the lab, and at that time, the NIH did not allow its researchers to have graduate students. So she and Fields convinced the University of Maryland, College Park, just 10 miles away, to allow her to take graduate courses in neuroscience while completing the necessary research for her Ph.D. in Fields’ lab.
In 2000, less than two years after starting graduate school, Stevens published a paper in Science showing that nerves in the peripheral nervous system (located outside the brain and spinal cord) use chemical signals to communicate with Schwann cells2. Two years later, she reported in Neuron that a similar form of communication occurs in the brain, between neurons and oligodendrocytes, the myelin-producing cells in the brain3.
As she was closing in on her Ph.D., Stevens sought career advice from Story Landis, then-director of the National Institute of Neurological Disorders and Stroke. Landis turned Stevens on to the possibility of starting her own lab one day. “I convinced her that she really had the abilities and energy and intelligence to run an independent research program,” Landis says.
In 2004, Stevens sought a postdoctoral fellowship with neurobiologist Ben Barres at Stanford University. “She was already seen as a leading researcher in the glial field,” recalls Barres, who promptly hired her. “She had done all sorts of beautiful work on glia.”
In Barres’ lab, Stevens continued to explore the dialogue between neurons and glia, turning her attention to star-shaped glia called astrocytes. Barres and his team had discovered that astrocytes help neurons form synapses4. To get a better handle on this process, Stevens examined how astrocytes influence gene expression in neurons in the developing mouse brain.
To her surprise, she found that astrocytes trigger neurons to produce a ‘complement’ protein that is best known for its role in the immune system. There, the protein serves as an ‘eat me’ signal, flagging pathogens and debris for removal. She found that neurons deposit this tag around immature synapses, but not mature ones, in mouse brain tissue, and mice that lack this protein have too many immature synapses. The findings suggested that astrocytes might help eliminate synapses by triggering the complement cascade5.
Young recruit: Beth Stevens’ daughter Riley inspects brain tissue during a visit to her mother’s lab. | Courtesy of Beth Stevens
But it was still unclear exactly how the tagged synapses are cleared. The prime suspects were microglia, the only cells in the brain known to have the receptor for the ‘eat me’ signal.
Stevens set out to test this hypothesis in her own lab: After four years as a postdoc, she had decided to branch out on her own. In 2008, neuroscientist Michael Greenberg — chair of the neurobiology department at Harvard — recruited her to the Harvard-affiliated Boston Children’s Hospital. Even when her lab was in its infancy, she had little trouble convincing new staff to join her.
“A lot of people might be a little hesitant to join a new lab,” says Dorothy Schafer, a former postdoctoral fellow in Stevens’ lab who is now assistant professor of neurobiology at the University of Massachusetts-Worcester. “But I was so excited by the research, and she was so energetic and extremely positive, and just seemed like a very nice person.”
One decision Stevens made early on was to continue to studying microglia in mice rather than experiment with new model systems. “You’ll never see her working on songbirds, because she has this aversion to birds,” Schafer says. “I think they think her curly blond hair is a nest or something, and she’s had really bad experiences with many types of birds dive-bombing her head.”
Just four years into her foray as an independent researcher, Stevens found the proof she had been looking for. In 2012, her team published evidence that microglia eat synapses, especially those that are weak and unused6.
The findings pinned down a new role for microglia in wiring the brain. They also helped to explain how the brain, which starts out with a surplus of neurons, trims some of the excess away. Neuron named the paper its most influential publication of 2012.
Stevens continues to study the function of microglia in the healthy brain, most recently uncovering preliminary evidence that a certain protein serves as a ‘don’t eat me’ tag that protects synapses from being engulfed by microglia. She is also exploring the role of microglia in disorders such as autism.
Several studies suggest that microglia are more active and more numerous in the brains of people with autism than in controls. Stevens and her team are looking at whether the activity of microglia is altered during brain development in mouse models of autism.
Immunodulatory Thalidomides in ~ conjugants unleash proteasome degradation on ~ oncoproteins with distinct mechanisms- BRD4,MYC & PIM1 & little collteral damage to 7429 other proteins!
Imagine being able to specifically target a cancer protein for immediate destruction, slipping Robert Louis Stevenson’s notorious black spot into a crevice in the secondary structure and spelling imminent death. Well, this is what Winter et al. (2015) describe in a recent drug discovery report for Science.1 Using phthalimide conjugation, the researchers not only specifically marked BRD4, a transcriptional coactivator important in MYC oncogene upregulation, for proteasomal degradation, but also achieved reduced tumor burdens in vivo.
The research team combined two drugs, thalidomide and JQ1, exploiting the properties of each to create a bifunctional compound, dBET1, that drives the proteasomal degradation of BRD4. JQ1, which in itself is anti-oncogenic, selectively binds BET bromodomains on the transcription factor, thus competitively inhibiting BRD4 activity on chromatin. Thalidomide, a phthalimide-based drug with immunomodulatory properties, binds cereblon (CRBN) in the cullin-RING ubiquitin ligase (CRL) complex, which is important in proteasomal protein degradation.
After confirming that the new phthalimide conjugate, dBET1, retained affinity for BRD4 and that this binding was specific, the team used a human acute myelocytic leukemia (AML) cell line, MV4;11, to show that treatment with the conjugate over 18 hours reduced BRD4 abundance. The researchers also found this with dBET1 treatment of other human cancer cell lines (SUM159, MOLM13). Following this, Winter et al. investigated the mechanisms by which dBET1 inhibits BRD4. By focusing primarily on proteasome function, the researchers determined that the reduction in BRD4 abundance in MV4;11 cells is proteasomal and dependent on CRBN binding activity.
Having established targeted proteasomal degradation using the dBET1 conjugate, Winter et al. then investigated the proteomic consequences of treatment in MV4;11 cells. Scientists at the Thermo Fisher Scientific Center for Multiplexed Proteomics (Harvard Medical School) used quantitative proteomics analysis with an isobaric tagging approach to compare the immediate effects of dBET1 treatment following two hours of incubation with the responses to JQ1 and vehicle control. Spectral data analysis identified 7,429 proteins with few differences in response to either treatment. JQ1 treatment reduced levels of MYC and oncoprotein PIM1 similarly to the response following dBET1 incubation. However, treatment with the latter also reduced BRD2, BRD3 and BRD4 abundance, findings that the research team confirmed with specific immunoblotting. Measuring expression of mRNA showed that both treatments reduced levels of MYC and PIM1 abundance. However, Winter et al. found no difference in BRD3 and BRD4, suggesting that dBET1 reduces the protein levels by post-transcriptional regulation.
Investigating the antiproliferative potential of the phthalimide conjugate, dBET1, Winter and coauthors examined apoptotic response in both MV4;11 and DHL4 lymphoma cells, and in primary human AML blast cultures. Compared to JQ1 treatment, dBET1 stimulated a profound and prolonged apoptotic response in both cell lines, suggesting that targeted degradation could be a more effective treatment than target inhibition.
shapes of proteins as they shift from one stable shape to a different, folded one Protein-structural-changes
Orchestrating the unfolded protein response in health and disease
Randal J. Kaufman Department of Biological Chemistry,
Howard Hughes Medical Institute, University of Michigan Medical Center, Ann Arbor, Michigan, USA J. Clin. Invest. 110:1389–1398 (2002). http://dx.doi.org:/10.1172/JCI200216886
The endoplasmic reticulum (ER), the entrance site for proteins destined to reside in the secretory pathway or the extracellular environment, is also the site of biosynthesis for steroids and for cholesterol and many lipids. Given the considerable number of resident structural proteins and biosynthetic enzymes and the high expression of many secreted proteins, the total concentration of proteins in the this organelle can reach 100 mg/ml. The ER relies on an efficient system of protein chaperones that prevent the accumulation of unfolded or aggregated proteins and correct misfolded proteins that are caught in low-energy kinetic traps (see Horwich, this Perspective series, ref. 1).
These chaperone-mediated processes expend metabolic energy to ensure high-fidelity protein folding in the lumen of the ER. For example, the most abundant ER chaperone, BiP/GRP78, uses the energy from ATP hydrolysis to promote folding and prevent aggregation of proteins within the ER. In addition, the oxidizing environment of the ER creates a constant demand for cellular protein disulfide isomerases to catalyze and monitor disulfide bond formation in a regulated and ordered manner. Operating in parallel with chaperone dependent protein folding are several “quality control” mechanisms, which ensure that, of all proteins translocated into the ER lumen, only those that are properly folded transit to the Golgi compartment. Proteins that are misfolded in the ER are retained until they reach their native conformation or are retrotranslocated back into the cytosol for degradation by the 26S proteasome. The ER has evolved highly specific signaling pathways to ensure that its protein-folding capacity is not overwhelmed. These pathways, collectively termed the unfolded protein response (UPR), are required if the cell is to survive the ER stress (see Ron, this Perspective series, ref. 2) that can result from perturbation in calcium homeostasis or redox status, elevated secretory protein synthesis, expression of misfolded proteins, sugar/glucose deprivation, or altered glycosylation. Upon accumulation of unfolded proteins in the ER lumen, the UPR is activated, reducing the amount of new protein translocated into the ER lumen, increasing retrotranslocation and degradation of ER-localized proteins, and bolstering the protein-folding capacity of the ER. The UPR is orchestrated by the coordinate transcriptional activation of multiple genes, a general decrease in translation initiation, and a concomitant shift in the mRNAs that are translated.
The recent discovery of the mechanisms of ER stress signaling, coupled with the ability to genetically engineer model organisms, has led to major new insights into the diverse cellular and physiological processes that are regulated by the UPR. Here, I summarize current discoveries that have offered insights into the complex regulation of the UPR and its relevance to human physiology and disease.
Glucose and protein folding Early studies demonstrated that both viral transformation and glucose depletion induce transcription of a set of related genes that were termed glucose-regulated proteins (GRPs) (3). Since viral transformation increases both the cellular metabolic rate and ATP utilization, it became evident that, in both cases, this signal emanates from the ER as a consequence of energy deprivation. Because proteins have different ATP requirements for protein folding prior to export, it has been proposed that the threshold for UPR activation might differ among various cell types, depending on their energy stores and the amount and nature of the secretory proteins they produce (4). Glucose not only provides the metabolic energy needed by cells but also participates directly in glycoprotein folding as a component of oligosaccharide structures.
The recognition and modification of oligosaccharide structures in the lumen of the ER is intimately coupled to polypeptide folding (5). As the growing nascent chain is translocated into the lumen of the ER, a 14-oligosaccharide core (GlcNAc2Man9Glc3) is added to consensus asparagine residues. Immediately after the addition of this core, the three terminal glucose residues are cleaved by the sequential action of glucosidases I and II to yield a GlcNAc2Man9 structure. If the polypeptide is not folded properly, a UDP-glucose:glycoprotein glucosyltransferase (UGGT) recognizes the unfolded nature of the glycoprotein and reglucosylates the core structure to re-establish the glucose-α(1, 3)–mannose glycosidic linkage. Monoglucosylated oligosaccharides containing this bond bind to the ER-resident protein chaperones calnexin and calreticulin.
This quality control process ensures that unfolded glycoproteins do not exit the ER. Treatment of cells with castanospermine, a transition-state analogue inhibitor of glucosidases I and II, inhibits this monoglucosylation cycle, prevents interaction of unfolded glycoproteins with calnexin and calreticulin, and activates the UPR. Genetic alterations that reduce the nucleotide sugar precursor pool or glycosyltransferase reactions likewise activate the UPR (6). Therefore, the recognition of altered carbohydrate structures is in some manner linked to UPR activation.
The UPR in yeast and higher eukaryotes On a cellular level, the accumulation of unfolded proteins in the ER lumen induces the transcription of a large set of genes whose products increase the ER’s volume or its capacity for protein folding or promote the degradation of misfolded proteins through the process of ER-associated protein degradation (ERAD) (7). For example, transcription of the ER protein chaperone BiP is a classical marker for UPR activation in yeast and mammalian cells (8). BiP binds hydrophobic exposed patches on the surfaces of unfolded proteins and interactive sites on unassembled protein subunits, and it releases its polypeptide substrates upon ATP binding.
In parallel, as Ron (this Perspective series, ref. 2) details in his accompanying article, translation is attenuated to decrease the protein-folding load. The complex network of physiological responses to ER stress is regulated by only a few ER transmembrane proteins: IRE1, PERK, and ATF6 (9). IRE1, PERK, and ATF6 are proximal sensors that regulate the production and/or quality of basic leucine zipper–containing (bZIP-containing) transcription factors that may form homo- and heterodimers. Combinatorial interactions of these factors generate diversity in responses for different subsets of UPRresponsive genes. In multicellular organisms, if these adaptive responses are not sufficient to relieve ER stress, the cell dies through apoptosis or necrosis.
IRE1-dependent splicing The UPR-signaling pathway was first described less than ten years ago in the budding yeast Saccharomyces cerevisiae. Elegant studies identified IRE1 as the sensor of unfolded proteins in the ER lumen. IRE1 is a type 1 transmembrane Ser/Thr protein kinase that also has a site-specific endoribonuclease (RNase) activity. The presence of unfolded proteins in the ER lumen promotes dimerization and trans-autophosphorylation, rendering IRE1 active as an RNase, and allowing it to cleave a 252-base intron from the mRNA encoding the transcription factor HAC1 (10). The 5′ and 3′ ends of HAC1 mRNA are spliced together by tRNA ligase in a process that is independent of the spliceosome and the usual intranuclear machinery for mRNA splicing. Splicing of HAC1 mRNA increases its translational efficiency and alters sequence of the encoded HAC1 protein, yielding a potent transcriptional activator (11) that can bind and activate the UPR elements (UPREs) upstream of many UPR-inducible genes. In S. cerevisiae, the UPR activates transcription of approximately 381 genes (7).
All eukaryotic cells appear to have maintained the essential and unique properties of the UPR present in S. cerevisiae, but higher eukaryotes possess additional sensors that generate diverse, coordinately regulated responses that promote stress adaptation or cell death. The mammalian genome contains two homologues of yeast IRE1 — IRE1α and IRE1β. Whereas IRE1α is expressed in most cells and tissues, with high-level expression in the pancreas and placenta (12), IRE1β expression is prominent only in intestinal epithelial cells (13). Both IRE1 molecules respond to the accumulation of unfolded proteins in the ER, which activate their kinase and, thereby, their RNase activities. The cleavage specificities of IRE1α and IRE1β are similar, if not identical, suggesting that they do not recognize different sets of substrates but rather generate temporally specific and tissue-specific expression (14, 15).
Searching for transcription factors that mediate the UPR, Yoshida et al. defined a mammalian ER stress response element [ERSEI; CCAAT(N9)CCACG] that is necessary and sufficient for UPR gene activation. Using a yeast one-hybrid screen, these authors isolated XBP1, a bZIP transcription factor X-box DNA binding protein (16). Subsequently, several groups demonstrated that XBP1 mRNA is a substrate for mammalian IRE1, much as the HAC1 mRNA in S. cerevisiae is processed by the yeast IRE1; this pathway is also conserved in Caenorhabditis elegans (17–20). On activation of the UPR, XBP1 mRNA is cleaved by IRE1 to remove a 26-nucleotide intron and generate a translational frameshift. As expected given the precedent of HAC1 regulation in yeast, the resulting processed mRNA encodes a protein with a novel carboxy-terminus that acts as a potent transcriptional activator.
Overexpression of either IRE1α or IRE1β is sufficient to activate transcription from a BiP promoter reporter construct (15). Analysis of a minimal UPRE motif (TGACGTGC/A) (21) uncovered a transcriptional defect in IRE1α-null mouse embryo fibroblasts that could be complemented by expression of spliced XBP1 mRNA (20), and Yoshida et al. (unpublished data) recently identified a UPR-inducible gene that uniquely requires IRE1α-mediated splicing of XBP1 mRNA. However, neither IRE1α nor IRE1β is necessary for transcriptional activation of the BiP gene, as judged by the phenotype of IRE1α/β–deleted murine cells (20, 22, 23). These results indicate that a subset of UPR targets require IRE1 but that at least one IRE1-independent pathway exists for UPR-mediated transcriptional induction. Deletion of IRE1α causes embryonic lethality at embryonic day 10.5 (E10.5) (20, 22, 23). Therefore, although IRE1α is not required for the UPR, it is clearly required for mammalian embryogenesis. XBP1 deletion also causes embryonic lethality, but the mutant embryos can survive up to day E14.5, consistent with the notion that XBP1 acts downstream of IRE1α. XBP1 deletion causes cardiomyopathy and liver hypoplasia (24, 25). In contrast, IRE1β-null mice develop normally but exhibit increased susceptibility to experimentally induced colitis, a phenotype that is consistent with the specific expression of this kinase in the intestinal epithelium (26).
Activation of ATF6 and PERK by ER stress The activating transcription factor ATF6 (16) has been identified as another regulatory protein that, like XBP1, can bind ERSEI elements in the promoters of UPRresponsive genes. There are two forms of ATF6, both synthesized as ER transmembrane proteins. ATF6α (90 kDa) and ATF6β (110 kDa, also known as CREB-RP) both require the presence of the transcription factor CBF (also called NF-Y) to bind ERSEI (27–30).
On activation of the UPR, both forms of ATF6 are processed to generate 50- to 60-kDa cytosolic, bZIP containing transcription factors that migrate to the nucleus (27). Processing of ATF6 by site-1 protease (S1P) and site-2 protease (S2P) occurs within the transmembrane segment and at an adjacent site exposed to the ER lumen. S1P and S2P are the processing enzymes that cleave the ER-associated transmembrane sterolresponse element–binding protein (SREBP) upon cholesterol deprivation (31). The cytosolic fragment of cleaved SREBP migrates to the nucleus to activate transcription of genes required for sterol biosynthesis. Interestingly, although the mechanism regulating ATF6 processing is similar to that regulating SREBP processing (32), the UPR only elicits ATF6 processing, whereas sterol deprivation alone induces SREBP processing. The SREBP cleavage–activating protein (SCAP) confers specificity for SREBP transport to the Golgi compartment, and consequently cleavage in response to sterol deprivation (33). It is unknown whether another cleavage-activating protein, analogous to SCAP but active only following induction of the UPR, promotes the specific cleavage and activation of ATF6 by S1P and S2P.
Transcription of UPR-responsive genes is induced when the cleaved form of ATF6 activates the XBP1 promoter. Therefore, signaling through ATF6 and IRE1 merges to induce XBP1 transcription and mRNA splicing, respectively (Figure 1, a and b). ATF6 increases XBP1 transcription to produce more substrate for IRE1- mediated splicing that generates more active XBP1, providing a positive feedback for UPR activation. However, cells that lack either IRE1α or ATF6 cleavage can induce XBP1 mRNA (20). These two pathways may thus provide parallel signaling pathways for XBP1 transcriptional induction. Alternatively, another pathway — possibly mediated by the ER-localized protein kinase PERK (see Ron, this Perspective series, ref. 2) — may also contribute to induction of XBP1 mRNA. The binding specificities of XBP1 and ATF6 are similar, although ATF6 binding requires CBF binding to an adjacent site, whereas XBP1 binds independently (17, 20, 21, 34). These binding specificities provide another avenue for complementary interaction between the IRE1-XBP1 and ATF6 pathways at the level of transcriptional activation. In addition, these transcription factors might regulate transcription from a second ERSE (ERSEII), which also contains a CCACG motif (35).
In parallel with the activation of ATF6 processing and the consequent changes in gene transcription, the accumulation of unfolded proteins in the ER also alters cellular patterns of translation. The protein kinase PERK has been implicated in this aspect of the ER stress response (see Ron, this Perspective series, ref. 2). Activated PERK phosphorylates the α subunit of eukaryotic translation initiation factor 2 (eIF2α) and attenuates general protein synthesis. Inactivation of the PERK-eIF2α phosphorylation pathway decreases cells’ ability to survive ER stress (36, 37). The PERK pathway promotes cell survival not only by limiting the protein-folding load on the ER, but also by inducing transcription of UPR- activated genes, one-third of which require phosphorylation of eIF2α for their induction (36). Preferential translation of the transcription factor ATF4 allows for continued activation of these genes under conditions of stress, when general protein synthesis is inhibited (36, 37).
A coordinated mechanism for activation One puzzling question about the UPR is how three independent sensors are activated by a common stimulus, the accumulation of unfolded proteins in the ER lumen. BiP, which negatively regulates the UPR, interacts with all three sensors, IRE1, PERK, and ATF6, under nonstressed conditions and may indeed be the master regulator of UPR activation.
Upon accumulation of unfolded proteins in the ER, BiP is released from IRE1, PERK, and ATF6. It is believed that the unfolded proteins bind BiP and sequester it from interacting with IRE1, PERK, and ATF6 to elicit their activation. In this manner, BiP senses both the level of unfolded proteins and the energy (ATP) level in the cell in regulating the UPR. Following release from BiP, IRE1 and PERK are each free to undergo spontaneous homodimerization mediated by their lumenal domains and to become phosphorylated by their endogenous kinase activities (38, 39). BiP interaction with ATF6 prevents trafficking of ATF6 to the Golgi compartment. For this reason, BiP release permits ATF6 transport to the Golgi compartment, where it gains access to S1P and S2P proteases (32). The regulation of signaling through the free level of BiP is an attractive hypothesis providing a direct mechanism by which all three ER stress sensors could be activated by the same stimulus. In addition, the increase in BiP during the UPR would provide a negative feedback to turn off UPR signaling. However, in certain cells, different stress conditions can selectively activate only one or two of the ER stress sensors. For example, in pancreatic β cells, glucose limitation appears to activate PERK prior to activation of IRE1 (D. Scheuner and R.J. Kaufman, unpublished results). It will be important to elucidate how general BiP repression permits the selective activation of individual components of the UPR that mediate various downstream effects.
Three proximal sensors, IRE1, PERK, and ATF6, coordinately regulate the UPR through their various signaling pathways. Whereas IRE1 and PERK are dispensable for many aspects of the response, ATF6 cleavage is required for UPR transcriptional induction and appears to be the most significant of these effectors in mammalian cells. BiP negatively regulates these pathways. BiP interacts with ATF6 to prevent its transport to the Golgi compartment (a). BiP binds to the lumenal domains of IRE1 (b) and PERK (c) to prevent their dimerization. As unfolded proteins accumulate, they bind BiP and reduce the amount of BiP available to bind and inhibit activation of IRE1, PERK, and ATF6. (a) BiP release from ATF6 permits transport to the Golgi compartment. In the Golgi, ATF6 is cleaved by S1P and S2P proteases to yield a cytosolic fragment that migrates to the nucleus to activate transcription of responsive genes, including XBP1. (b) BiP release from IRE1 permits dimerization to activate its kinase and RNase activities to initiate XBP1 mRNA splicing. XBP1 splicing removes a 26-base intron, creating a translational frameshift to yield a more potent transcriptional activator. (c) BiP release permits PERK dimerization and activation to phosphorylate Ser51 on eIF2α to reduce the frequency of AUG initiation codon recognition. As eIF2α phosphorylation reduces the functional level of eIF2, the general rate of translation initiation is reduced. However, selective mRNAs, such as ATF4 mRNA, are preferentially translated under these conditions, possibly by the presence of open reading frames within the 5′ untranslated region of the mRNA. Upon recovery from the UPR, GADD34 targets PP1 to dephosphorylate eIF2α and increase protein translation.
The UPR as a mediator of programmed cell death In contrast to UPR-signaling adaptation in response to ER stress, prolonged UPR activation leads to apoptotic cell death (Figure 2). The roles of several death-promoting signaling pathways have been shown by analysis of specific gene-deleted cells. Activated IRE1 recruits c-Jun-N-terminal inhibitory kinase (JIK) and the cytosolic adaptor TRAF2 to the ER membrane (22, 40). TRAF2 activates the apoptosis-signaling kinase 1 (ASK1), a mitogen-activated protein kinase kinase kinase (MAPKKK) (41). Activated ASK1 leads to activation of the JNK protein kinase and mitochondriadependent caspase activation (40–42).
ER insults lead to caspase activation by mitochondria/APAF-1–dependent and –independent pathways. ER stress promotes cytochrome c release from mitochondria, possibly by c-ABL kinase (43) or calcium (44). However, APAF1–/– cells are susceptible to ER stress–induced apoptosis, indicating that the mitochondrial pathway is not essential (45). Caspase-12 is an ER-associated proximal effector in the caspase activation cascade, and cells lacking this enzyme are partially resistant to inducers of ER stress (46). ER stress induces TRAF2 release from procaspase 12, allowing it to bind activated IRE1. As shown in Figure 2, release of TRAF2 permits clustering of procaspase-12 at the ER membrane, leading to its activation (40). Caspase-12 can activate caspase-9, which in turn activates caspase- 3 (47). Procaspase-12 can also be activated by m-calpain in response to calcium release from the ER, although the physiological significance of this pathway is not known (48). In addition, upon ER stress, procaspase-7 is activated and recruited to the ER membrane (49). These findings support the notion that ER stress leads to several redundant pathways for caspase activation.
A second death-signaling pathway activated by ER stress is mediated by transcriptional activation of genes encoding proapoptotic functions. Activation of UPR sensor IRE1, PERK, or ATF6 leads to transcriptional activation of CHOP/GADD153, a bZIP transcription factor that potentiates apoptosis (see Ron, this Perspective series, ref. 2).
The UPR in health and disease Primary amino acid sequence contains all the information for a protein to attain its final folded conformation. However, many folding intermediates exist along the folding pathway (see Horwich, this Perspective series, ref. 1), and some of these intermediates can become irreversibly trapped in low-energy states and activate the UPR. Clearance of such misfolded species requires a functional ER-associated degradation (ERAD) pathway, which is regulated by the UPR. Proteasomal degradation of ER-associated misfolded proteins is required to protect from UPR activation. Proteasomal inhibition is sufficient to activate the UPR, and, in turn, genes encoding several components of ERAD are transcriptionally induced by the UPR (7). Therefore, it is to be expected that UPR activation and impaired ERAD function might contribute to a variety of diseases and that polymorphisms affecting the UPR and ERAD responses could modify disease progression. The following examples provide the best available evidence linking the UPR pathway to the natural history of human diseases and animal models of these diseases.
The UPR and ERAD in genetic disease Many recessive inherited genetic diseases are due to loss of-function mutations that disturb productive folding and that produce proteins that are either not secreted or not functional. In other cases, protein-folding mutations can interfere with cellular processes, resulting in a gain of function and a dominant pattern of inheritance. In several instances, UPR activation by the accumulation of unfolded proteins in the ER is known to contribute to disease progression. The distinction between these two classes of genetic disease is important, because gain-of-function protein-misfolding mutations will be less amenable to treatment by gene therapy to deliver a wild-type copy of the mutant gene.
One well-characterized protein-folding defect results from a mutation that leads to type 1 diabetes. The Akita mouse has a gain-of-function Cys96Tyr mutation in the proinsulin 2 (Ins2) gene; this mutation disrupts proinsulin folding. The mutant protein is retained in the ER of the pancreatic β cell and activates the UPR. Crucially, the progressive development of diabetes in this model is not solely due to the lack of insulin but is rather a consequence of the misfolded protein accumulation, UPR activation, and β cell death. When bred into a Chop–/–background, the Akita mutation causes a lesser degree of β cell death and delayed onset of diabetes (50), indicating that the loss of at least one downstream signaling component of the UPR can ameliorate pathogenesis in this setting.
The activation of procaspase-12 is likely the major pathway that induces apoptosis in response to ER stress. Upon activation of the UPR, c-Jun-N-terminal inhibitory kinase (JIK) release from procaspase-12 permits clustering and activation of procaspase-12. Caspase-12 activates procaspase-9 to activate procaspase-3, the executioner of cell death. In addition, activated IRE1 binds JIK and recruits TRAF2, which signals through apoptosis-signaling kinase 1 (ASK1) and JNK to promote mitochondria-dependent apoptosis. In addition, in vitro studies suggest that localized calcium release from the ER activates m-calpain to cleave and activate procaspase-12. Upon UPR activation, procaspase-7 is activated and recruited to the ER membrane. Finally, IRE1, PERK, and ATF6 induce transcription of several genes encoding apoptotic functions, including CHOP/GADD153. CSP, caspase; pCSP, procaspase.
Deficiency in α1-proteinase inhibitor (α1-PI, also known as α1-antitrypsin) results in emphysema and destructive lung disease in one out of 1,800 births. However, a subgroup of affected individuals develop chronic liver disease and hepatocellular carcinoma as a consequence of a secretion defect in the misfolded protein at the site of synthesis, the hepatocyte. This is the most common genetic cause of liver disease in children. The Z allele of the α1 gene PI (Glu342Lys mutation) produces a protein that polymerizes and is retained in the ER for degradation by the proteasome (see Lomas and Mahadeva, this Perspective series, ref. 51; and Perlmutter, this series, ref. 52). While α1-PI Z neither binds BiP nor activates the UPR, analysis of fibroblasts obtained from these patients demonstrates that individuals susceptible to liver disease have inherited a second trait that slows degradation of the misfolded protein in the ER (53), consistent with the idea that polymorphisms that reduce ERAD function can exacerbate pathogenesis of certain diseases.
There are numerous additional genetic misfolding diseases that are also likely influenced by UPR signaling. Because BiP release from IRE1, PERK, or ATF6 can activate the UPR, the expression of any wild-type or mutant protein that binds BiP can have a similar effect. In contrast, misfolded proteins that do not bind BiP are unlikely to activate the UPR. For example, cystic fibrosis is due to mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) protein. Approximately 70% of patients with this disease carry a common mutation, deletion of Phe508, that results in a molecule that is retained in the ER and eventually degraded by the proteosome (see Gelman and Kopito, this Perspective series, ref. 54). Although expression of ∆508 CFTR does not activate the UPR in cultured cells, the protein does interact with calnexin, as well as HSP70, and requires ERAD function for cell survival.
Osteogenesis imperfecta (OI) results from misfolding mutations in procollagen that produce molecules that bind BiP and activate the UPR (55). Interestingly, Wolcott-Rallison syndrome is due to inactivating mutations in the PERK gene. Affected individuals, as well as mice with deletions in Perk, display osteoporosis and deficient mineralization throughout the skeletal system (56, 57), the same defects that are observed in OI. Procollagen type I accumulates to high levels and mature collagen is not detected in bone and osteoblasts from PERKnull mice. Osteoblasts from PERK-null humans and mice display fragmented and distended ER that is filled with electron-dense material (56, 57). These observations suggest that procollagen type 1 uniquely requires PERK function to maintain its transport out of the ER, processing, and secretion In this case, PERK may be required to limit procollagen synthesis so that it does not saturate the ER protein-folding capacity.
The UPR and ERAD in conformational diseases Diseases caused by expansion of polyglutamine repeats and neurodegenerative diseases, such as Alzheimer disease and Parkinson disease, represent a large class of conformational diseases associated with accumulation of abnormal protein aggregates in and around affected neurons. Recent evidence indicates that the pathogenesis of these diseases is due to a defect in proteasomal function that results in UPR activation, leading to cell death. The protein aggregates in these diseases are localized to the nucleus or the cytoplasm and would not be predicted to disturb ER function directly. Nevertheless, they have been found in some cases to activate the UPR and to promote cell death. Analysis of the polyglutamine repeat associated with the spinocerebrocellular atrophy protein (SCA3) in Machado-Joseph disease suggests that cytoplasmic accumulation of the SCA3 aggregate can inhibit proteasome function, thereby interfering with ERAD to induce the UPR and elicit caspase-12 activation (41, 58). These findings support the idea that the UPR can signal the accumulation of unfolded proteins in the cytosol via proteasomal inhibition and disruption of ERAD function.
Parkinson disease is the most common movement disorder, affecting about 1% of individuals 65 years of age or older. Autosomal recessive juvenile parkinsonism (AR-JP) results from defects in the Parkin gene (59), which encodes a ubiquitin protein ligase (E3) that functions with ubiquitin-conjugating enzyme UbcH7 or UbcH8 to tag proteins for degradation. Overexpression of Parkin suppresses cell death associated with ER stress (60). Inherited Parkinson disease is associated with the accumulation in the ER of dopaminergic neurons of PAEL-R, a putative transmembrane receptor protein that is detected in an insoluble form in the brains of AR-JP patients (61). The accumulation of PAEL-R results from defective Parkin that does not maintain the proteasome-degrading activity necessary to maintain ER function (62). Other, still-unidentified substrates of the Parkin E3 ligase may also be relevant to the pathogenesis of AR-JP.
The UPR in diabetes The metabolism of glucose is tightly controlled at the levels of synthesis and utilization through hormonal regulation. The most dramatic phenotype in Wolcott-Rallison syndrome is pancreatic β cell death with infancy onset diabetes (56). A similar defect is observed in PERK-null mice; this defect also correlated with increased apoptosis of β cells (57, 63). In addition, mice with a homozygous Ser51Ala mutation at the PERK phosphorylation site in eIF2α display an even greater β cell loss that appears in utero (36). Therefore, translational control through PERK-mediated phosphorylation of eIF2α is required to maintain β cell survival (see Ron, this Perspective series, ref. 2). The more severe β cell loss in mice harboring the Ser51Ala eIF2α mutation suggests that additional eIF2α kinases partially complement the requirement for PERK in β cell function (36)
Glucose not only promotes the secretion of insulin but also stimulates insulin transcription and translation (64–66). Our group has proposed that glucose stimulated proinsulin mRNA translation is regulated by PERK-mediated phosphorylation of eIF2α in response to UPR activation 36). As blood glucose declines, energy may become limiting for protein folding in the ER and therefore activate the UPR to promote PERK-mediated phosphorylation of eIF2α. Conversely, a rise in blood glucose would turn off the UPR so that translation would accelerate, allowing entry of new preproinsulin into the ER. In this manner, PERK mediated phosphorylation of eIF2α provides a brake on protein synthesis, including proinsulin translation. Continual elevation of blood glucose may also prolong elevated proinsulin translation, eventually activating the UPR as the secretion capacity of the ER is overwhelmed. Therefore, a delicate balance between glucose levels and eIF2α phosphorylation needs to be maintained: Disturbances in either direction may lead to excessive UPR activation, with eventual β cell death.
The insulin resistance and hyperglycemia associated with type 2 diabetes is accommodated by an increase in proinsulin translation. Under these conditions the UPR is activated to compensate for the increased protein-folding requirement in the ER. Prolonged activation of the UPR could contribute to the β cell death associated with insulin resistance. Thus, the signaling mechanisms that β cells use for sensing glucose levels, triggering insulin secretion, and rapidly controlling insulin biosynthesis may have coevolved with ER signaling pathways to support these specialized functions. Pancreatic β cells are exquisitely sensitive to physiological fluctuations in blood glucose, because, in contrast to other cell types, they lack hexokinase, an enzyme with a low affinity but a high capacity for binding glucose. Therefore, in β cells, the production of glucose 6-phosphate and the production of ATP through glycolysis are controlled by glucokinase (67), and the ratio of ATP to ADP correlates directly with the blood glucose level. Periodic decreases in blood glucose level (as occurs between meals) would decrease the ATP/ADP ratio and compromise protein folding in the ER so that the UPR may be frequently activated in these cells. Hence, when glucose levels vary within the normal physiological range, the ER compartment of the β cell may be exposed to greater energy fluctuations than is the ER of other cell types, making the β cell uniquely dependent on the UPR for survival during intermittent decreases in blood glucose levels, as happens between meals. Additionally, the high-level expression of PERK and IRE1α in the pancreas may predispose these kinases to dimerization and activation in response to intermittent stress.
The UPR in organelle expansion The UPR is required for ER expansion that occurs upon differentiation of highly specialized secretory cells, but ER membrane expansion can also proceed independently of UPR activation. Overexpression of membrane proteins, such as HMG CoA reductase or the peroxisomal protein Pex15, promotes the expansion of smooth membranes without UPR activation (68, 69), as does overexpression of the p180 ribosome acceptor in the rough ER membrane (70). Conversely, protein overexpression, even under circumstances in which secretory capacity is unchanged (as occurs following the induction of high levels of cytochrome p450), can activate the UPR to induce ER chaperone levels to match the expanded membrane area (71, 72).
During the terminal differentiation of certain secretory cells, such as those in the pancreas or liver, membrane expansion is accompanied by a dramatic increase in protein secretion. Likewise, upon B cell maturation into high-level antibody-secreting plasma cells, the ER compartment expands approximately fivefold to accommodate the large increase in Ig synthesis. The requirement for the UPR in this latter process has been demonstrated in XBP1–/– cells. Since deletion of XBP1 produces an embryonic-lethal phenotype at day E14.5, the role of XBP1 in B and T cell development had to be studied in immunoincompetent RAG1–/– mice reconstituted with XBP1–/– embryonic stem cells (73). Work in these chimeric mice demonstrated that XBP1 is required for high-level Ig production. Interestingly, the induction of Ig heavy-chain and light-chain gene rearrangement and the assembly and transport of Igµ to the surface of the B cells occurred normally. However, plasma cells were not detected, suggesting a role for XBP1 in plasma cell differentiation or survival.
These findings support the hypothesis that induction of Ig synthesis activates the UPR to induce ER expansion to accommodate the high-level antibody expression. Alternatively, activation of the UPR may be part of the differentiation program that occurs prior to induction of high-level antibody synthesis. Plasma cell differentiation is stimulated in vivo by treatment with LPS or by ligation of CD40 receptors, treatments that activate the innate immune response and have been shown to induce XBP1 mRNA splicing (19). Thus, the UPR may contribute to a programmed response to signals that increase a cell’s protein-secretory demand.
The UPR in hyperhomocysteinemia. The association between high levels of serum homocysteine and the development of ischemic heart disease and stroke is supported by substantial epidemiological data. Unfortunately, it is not known whether homocysteine is the underlying cause of atherosclerosis and thrombosis. Severe hyperhomocysteinemia is caused by mutation in the cystathionine β-synthase (CBS) gene, whose product is a vitamin B6–dependent enzyme required for the conversion of homocysteine to cysteine. Elevated homocysteine is also associated with vitamin B deficiency. In cultured vascular endothelial cells, homocysteine induces protein misfolding in the ER by interfering with disulfide bond formation, and it activates the UPR to induce expression of several ER stress response proteins, such as BiP, GRP94, CHOP, and HERP (74–76). Homocysteine also activates apoptosis in a manner that requires an intact IRE1-signaling pathway (76).
These findings suggest that homocysteine acts intracellularly to disrupt ER homoeostasis. Indeed, recent studies confirm that induction of hyperhomocysteinemia elicits UPR activation in the livers of normal or Cbs+/– mice (77). In addition, hyperhomocysteinemia activates SREBP cleavage, leading to intracellular accumulation of cholesterol (77). Increased cholesterol biosynthesis may explain the hepatic steatosis and possibly the atherosclerotic lesions associated with hyperhomocysteinemia. Finally, hyperhomocysteinemia accelerates atherosclerosis in ApoE–/– mice (78, 79), although the molecular mechanisms remain to be elucidated.
Hyperhomocysteinemia is also associated with increased amyloid production and increased amyloid-mediated neuronal death in animal models of Alzheimer disease (80). These observations suggest that the UPR may link the disease etiologies of hyperhomocysteinemia and Alzheimer disease. HERP, a homocysteine-induced ER stress–responsive gene, appears to be involved in amyloid β-protein (Aβ) accumulation, including the formation of senile plaques and vascular Aβ deposits (81), and that it interacts with both presenilin-1 (PS1) and presenilin-2 (PS2), thus regulating presenilin-mediated Aβ generation. Immunohistochemical analysis of brains from patients with Alzheimer disease reveals intense HERP staining in activated microglia in senile plaques.
The UPR in cancer Hypoxia is a common feature of solid tumors that display increased malignancy, resistance to therapy, and poor prognosis. Hypoxia in the tumor results from increased demand due to dysregulated cell growth and from vascular abnormalities associated with cancerous tissue. The importance of hypoxia has been seen in the clinic, since it predicts for poor outcome of treatments, independent of treatment modality. Hypoxia activates the UPR, whose downstream signaling events can undermine the efficacy of treatment. Tumor cells need to adapt to the increasingly hypoxic environment that surrounds them as they grow, and the induction of the UPR is key to this response. Induction of the ER stress response genes, for example BiP and GRP94, in cancerous tissue correlates with malignancy, consistent with their antiapoptotic function (82). In addition, the UPR confers resistance to topoisomerase inhibitors, such as etoposide, and some UPR-induced genes directly mediate drug resistance via the multi-drug-resistance gene MDR. Therefore, approaches to prevent UPR activation in cancerous cells may significantly improve treatment outcome.
The proteasome inhibitor PS-341 is now in earlyphase clinical evaluation for the treatment of multiple myeloma, a clonal B cell tumor of differentiated plasma cells (83). The mechanism of PS-341 function is thought to be inhibition of IκB degradation, which prevents activation of the antiapoptotic transcription factor NF-κB. However, proteasomal inhibition would also prevent ERAD. As high-level heavy- or light-chain Ig production is likely associated with a certain degree of protein misfolding, it is possible that inhibition of ERAD function may be selectively toxic to B cell myelomas through activation of the UPR and apoptosis.
The UPR and viral pathogenesis The two major mediators of the IFN-induced arm of the innate immune response are evolutionarily related to IRE1 and PERK. The kinase/endoribonuclease domain of IRE1 is homologous to RNaseL, and the protein kinase domain of PERK is related to the double-stranded RNA–activated (dsRNA-activated) eIF2α protein kinase PKR. RNase L and PKR mediate the IFN induced antiviral response of the host, which is required to limit viral protein synthesis and pathogenesis. As part of the innate immune response to viral infection, RNase L and PKR are activated by dsRNAs produced as intermediates in viral replication. In contrast to activation by dsRNA, IRE1 and PERK are activated by ER stress, which can be induced by high-level viral glycoprotein expression. All enveloped viruses produce excess glycoproteins that could elicit PERK and IRE1 activation to meet the need for increased folding and secretory capacity. More studies will be required to elucidate the role of the UPR in various viral diseases.
Hepatitis C virus (HCV) is a positive-stranded RNA virus encoding a single polyprotein. Polyprotein cleavage generates at least ten polypeptides, including two glycoproteins, E1 and E2. A large amount of E1 forms disulfide–cross-linked aggregates with E2 in the ER (84). Since the accumulation of misfolded α1-PI elicits UPR activation, with subsequent hepatocyte death and hepatocellular carcinoma, it is possible that the aggregated E1/E2 complexes in the HCV-infected hepatocyte also contribute to hepatitis and hepatocellular carcinoma. Future studies should identify whether these glycoprotein aggregates activate the UPR to mediate the hepatocyte cell death and transformation associated with the pathogenesis of HCV infection.
The UPR in tissue ischemia Finally, neuronal death due to reperfusion after ischemic injury is associated with activation of the UPR (85, 86). Immediately after reperfusion, protein synthesis is inhibited, due at least in part to phosphorylation of eIF2α; this inhibition may represent a protective mechanism to prevent further neuron damage. Recent studies support the idea that eIF2α phosphorylation in response to reperfusion injury is mediated by PERK and hence that it depends on the UPR (87). If so, UPR activation prior to ischemic injury might protect the brain and other tissues from cell death during periods of reperfusion.
Summary A variety of approaches have been employed to identify the UPR signaling components, their function, and their physiological role. Yeast genetics allowed the definition of the basic ER stress–signaling pathway. The identification of homologous and parallel signaling pathways in higher eukaryotes has produced a mechanistic framework the cell uses to sense and compensate for ER over-load and stress. The high-level tissue-specific expression patterns of several ER stress–signaling molecules indicated the pancreas and intestine as organs that require UPR for physiological function. Analysis of UPR-induced gene expression established that protein degradation is required to reduce the stress of unfolded protein accumulation in the ER. Major advances in identifying UPR function and rele vance to disease were derived from mutation of UPR signaling components in model organisms and the identification of mutations in humans.
Despite tremendous progress, our knowledge of the UPR pathway remains incomplete. Further studies promise to expand our understanding of how ER stress impacts the other cellular signaling pathways. It will be very exciting and informative to understand how the UPR varies when critical components are genetically manipulated by deletion or other types of mutations. In addition, although the accumulation of unfolded protein in the ER is now known to contribute to pathogenesis in a variety of diseases, there are still few therapeutic approaches that target these events. With a greater understanding of protein-folding processes, pharmacological intervention with chemical chaperones to promote proper folding becomes feasible, as observed with sodium phenylbutyrate for ∆508 CFTR (see Gelman and Kopito, this Perspective series, ref. 53). Future intervention should consider activation of different subpathways of the UPR or overexpression of appropriate protein chaperones, as in the case of overexpression of the J domain of cytosolic HSP70, which suppresses polyglutamine toxicity in flies (88). Treatments that activate the ERAD response may also ameliorate pathogenesis in a number of the conformational diseases.
Over the past ten years, tremendous progress has been made in understanding the mechanisms and physiological significance of the UPR. The processes of protein folding and secretion, transcriptional and translational activation, and protein degradation are intimately interconnected to maintain homeostasis in the ER. A variety of environmental insults, genetic disease, and underlying genetic modifiers of UPR function contribute to the pathogenesis of different disease states. As we gain a greater understanding of the mechanisms that control UPR activation, it should be possible to discover methods to activate or inhibit the UPR as desired for therapeutic benefit.
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Citation: Cell Death and Disease (2014) 5, e1578; doi:10.1038/cddis.2014.539
Published online 18 December 2014
T Rana1, V M Shinde1, C R Starr1, A A Kruglov1, E R Boitet1, P Kotla1, S Zolotukhin2, A K Gross1 and M S Gorbatyuk1
1Department of Vision Sciences, University of Alabama at Birmingham, AL, USA
2Department of Pediatrics, University of Florida, FL, USA
Correspondence: M Gorbatyuk, Department of Vision Sciences, University of Alabama at Birmingham, 1670 University Boulevard, Birmingham, 35233 AL, USA. Tel: +1 205 934 6762; Fax: +1 205 934 3425; E-mail:mgortk@uab.edu
Received 20 July 2014; Revised 23 October 2014; Accepted 27 November 2014
Edited by P Ekert
Recent studies on the endoplasmic reticulum stress have shown that the unfolded protein response (UPR) is involved in the pathogenesis of inherited retinal degeneration caused by mutant rhodopsin. However, the main question of whether UPR activation actually triggers retinal degeneration remains to be addressed. Thus, in this study, we created a mouse model for retinal degeneration caused by a persistently activated UPR to assess the physiological and morphological parameters associated with this disease state and to highlight a potential mechanism by which the UPR can promote retinal degeneration. We performed an intraocular injection in C57BL6 mice with a known unfolded protein response (UPR) inducer, tunicamycin (Tn) and examined animals by electroretinography (ERG), spectral domain optical coherence tomography (SD-OCT) and histological analyses. We detected a significant loss of photoreceptor function (over 60%) and retinal structure (35%) 30 days post treatment. Analysis of retinal protein extracts demonstrated a significant upregulation of inflammatory markers including interleukin-1β (IL-1β), IL-6, tumor necrosis factor-α (TNF-α), monocyte chemoattractant protein-1 (MCP-1) and IBA1. Similarly, we detected a strong inflammatory response in mice expressing either Ter349Glu or T17M rhodopsin (RHO). These mutant rhodopsin species induce severe retinal degeneration and T17M rhodopsin elicits UPR activation when expressed in mice. RNA and protein analysis revealed a significant upregulation of pro- and anti-inflammatory markers such as IL-1β, IL-6, p65 nuclear factor kappa B (NF-kB) and MCP-1, as well as activation of F4/80 and IBA1 microglial markers in both the retinas expressing mutant rhodopsins. We then assessed if the Tn-induced inflammatory marker IL-1β was capable of inducing retinal degeneration by injecting C57BL6 mice with a recombinant IL-1β. We observed ~19%reduction in ERG a-wave amplitudes and a 29% loss of photoreceptor cells compared with control retinas, suggesting a potential link between pro-inflammatory cytokines and retinal pathophysiological effects. Our work demonstrates that in the context of an established animal model for ocular disease, the persistent activation of the UPR could be responsible for promoting retinal degeneration via the UPR-induced pro-inflammatory cytokine IL-1β.
Neuroinflammation and endoplasmic reticulum (ER) stress are associated with many neurological diseases. ER stress is brought on by misfolded proteins. In turn, cells respond with activation of the unfolded protein response (UPR). The UPR is a highly conserved pathway that transmits both adaptive and apoptotic signals to restore homeostasis or eliminate the irreparably damaged cell. Recent evidence indicates that ER stress and inflammation are linked. In this study, we have examined the interaction between ER stress and JAK/STAT-dependent inflammation in astrocytes. The JAK/STAT pathway mediates the biological actions of many cytokines and growth factors. We have found that ER stress leads to the activation of STAT3 in a JAK1-dependent fashion. ER stress-induced activation of the JAK1/STAT3 axis leads to expression of IL-6 and several chemokines. The activation of STAT3 signaling is dependent on the protein kinase PERK, a central component of the UPR. Knockdown of PERK abrogates ER stress-induced activation of STAT3 and overexpression of PERK is sufficient to activate STAT3. Additionally, ER stressed astrocytes, via paracrine signaling, can stimulate activation of microglia leading to production of oncostatin M (OSM). OSM can then synergize with ER stress in astrocytes to drive inflammation. Together, this work describes a new PERK-JAK1-STAT3 signaling pathway that may elicit a feed-forward inflammatory loop involving astrocytes and microglia to drive neuroinflammation.
1Ikerbasque Foundation, 48011 Bilbao, Spain 2Achucarro Basque Center for Neuroscience, Bizkaia Science and Technology Park, 48170 Zamudio, Spain 3Department of Neurosciences, University of the Basque Country, 48940 Leioa, Spain 4Centre de Recherche du CHU de Québec, Axe Neurosciences, Canada G1P 4C7 5Département de Médecine Moléculaire, Université Laval, Canada G1V 4G2
Received 10 December 2013; Accepted 11 February 2014; Published 19 March 2014
Microglia cells are the major orchestrator of the brain inflammatory response. As such, they are traditionally studied in various contexts of trauma, injury, and disease, where they are well-known for regulating a wide range of physiological processes by their release of proinflammatory cytokines, reactive oxygen species, and trophic factors, among other crucial mediators. In the last few years, however, this classical view of microglia was challenged by a series of discoveries showing their active and positive contribution to normal brain functions. In light of these discoveries, surveillant microglia are now emerging as an important effector of cellular plasticity in the healthy brain, alongside astrocytes and other types of inflammatory cells. Here, we will review the roles of microglia in adult hippocampal neurogenesis and their regulation by inflammation during chronic stress, aging, and neurodegenerative diseases, with a particular emphasis on their underlying molecular mechanisms and their functional consequences for learning and memory.
Microglia: The Resident Immune Cells of the Brain
Microglia were first described in 1919 by the Spanish neuroanatomist Pío del Río Hortega, a disciple of the renowned Santiago Ramón y Cajal, almost half a century later than neurons and astrocytes and just before oligodendrocytes [1]. This delayed appearance into the neuroscience arena is still apparent today, as microglia remain one of the least understood cell types of the brain. Traditionally, microglia were simply considered as “brain macrophages” controlling the inflammatory response during acute insults and neurodegenerative conditions, and only recently was their unique origin revealed. Indeed, microglia were shown to derive from primitive myeloid progenitors of the yolk sac that invade the central nervous system (CNS) during early embryonic development (reviewed in [2]). In contrast, circulating monocytes and lymphocytes, as well as most tissue macrophages, derive from hematopoietic stem cells located initially in the foetal liver and later in the bone marrow [3]. In the adult brain, the microglial population is maintained exclusively by self-renewal during normal physiological conditions [2]. As a consequence, microglia are the only immune cells which permanently reside in the CNS parenchyma, alongside neural tube-derived neurons, astrocytes, and oligodendrocytes.
These past few years, unprecedented insights were also provided into their extreme dynamism and functional behaviour, in health as much as in disease. Indeed, microglia were revealed to be exceptional sensors of their environment, responding on a time scale of minutes to even subtle variations of their milieu, by undergoing concerted changes in morphology and gene expression [4, 5]. During pathological insults, “activated” microglia were particularly shown to thicken and retract their processes, extend filopodia, proliferate and migrate, release factors and compounds influencing neuronal survival (such as proinflammatory cytokines, trophic factors, reactive oxygen species (ROS), etc.), and phagocytose pathogens, degenerating cells and debris, thus providing better understanding of their roles in orchestrating the inflammatory response [6]. These abilities as immune cells are also recruited during normal physiological conditions, where “surveillant” microglia further participate in the remodeling of neuronal circuits by their phagocytic elimination of synapses and their regulation of glutamatergic receptors maturation and synaptic transmission, among other previously unexpected roles [7–9], in addition to their crucial involvement in the phagocytic elimination of newborn cells in the context of adult neurogenesis [10].
Our review will discuss the emerging roles of microglia in adult hippocampal neurogenesis and their regulation by inflammation during chronic stress, aging, and neurodegenerative diseases, with a particular emphasis on their underlying molecular mechanisms and their functional consequences for learning and memory (Figure 1).
Figure 1: The effects of surveillant and inflammatory microglia on the adult hippocampal neurogenic cascade. During physiological conditions, surveillant microglia effectively phagocytose the excess of apoptotic newborn cells and may release antineurogenic factors such as TGF. This anti-inflammatory state is maintained by neuronal (tethered or released) fractalkine. Enriched environment drives microglia towards a phenotype supportive of neurogenesis, via the production of IGF-1. In contrast, inflammatory challenge triggered by LPS, irradiation, aging, or AD induces the production of proinflammatory cytokines such as IL-1, TNF, and IL-6 by microglia as well as resident astrocytes and infiltrating monocytes, neutrophils, and lymphocytes. These cytokines have profound detrimental effects on adult neurogenesis by reducing the proliferation, survival, integration, and differentiation of the newborn neurons and decreasing their recall during learning and memory paradigms.
A Brief Overview of Adult Hippocampal Neurogenesis
Adult hippocampal neurogenesis is continuously maintained by the proliferation of neural stem cells located in the subgranular zone (SGZ) [11–13]. These neuroprogenitors have been named “radial glia-like cells” (rNSCs), or type 1 cells, since they morphologically and functionally resemble the embryonic radial glia. They have also been defined as “quiescent neuroprogenitors” because only a small percentage of the population is actively dividing during normal physiological conditions. The lineage of these cells is frequently traced by using analogs of the nucleotide thymidine, such as bromodeoxyuridine (BrdU) which gets incorporated into the DNA of dividing cells during the S phase and can be detected by immunofluorescence. Alternatively, their lineage can be traced by labeling with fluorescent reporters which are delivered to dividing cells by retroviral vectors or expressed by specific cell type promoters via inducible transgenic mice (for a review of the methods commonly used to study adult neurogenesis, see [14]). The daughter cells of rNSCs, also called type 2 cells or amplifying neuroprogenitors (ANPs), rapidly expand their pool by proliferating before becoming postmitotic neuroblasts. Within a month, these neuroblasts differentiate and integrate as mature neurons into the hippocampal circuitry [15]. They however display unique electrophysiological characteristics during several months, being more excitable than mature neurons [16], and constitute a special cell population that is particularly inclined to undergo synaptic remodeling and activity-dependent plasticity [17].
These unique properties of the newborn neurons and the neurogenic cascade in general suggested that adult hippocampal neurogenesis could play an important role in hippocampal-dependent functions that require extensive neuroplasticity such as learning and memory. Indeed, activity-dependent plasticity and learning are long known for modulating adult neurogenesis in a complex, yet specific manner, with adult hippocampal neurogenesis being influenced by learning tasks which depend on the hippocampus [44, 45]. For instance, hippocampal-dependent learning paradigms were found to regulate the survival of newborn neurons, in a positive manner that depends on the timing between their birth and the phases of learning [46, 47]. Young (1.5–2 months old) newborn neurons were also shown to be preferentially activated during memory recall in a water maze task, compared to mature neurons, as determined by colabeling of BrdU with immediate early genes such as c-Fos and Arc, in which expression correlates with neuronal firing [48]. Nonetheless, it has only been in the last few years that loss-of-function and gain-of-function approaches with inducible transgenic mice were able to confirm that adult hippocampal neurogenesis is necessary for synaptic transmission and plasticity, including the induction of long-term potentiation (LTP) and long-term depression [49], as well as trace learning in conditioned protocols [50], memory retention in spatial learning tasks [51, 52], and encoding of overlapping input patterns, that is, pattern separation [53].
Adult hippocampal neurogenesis and its functional implications for learning and memory are however influenced negatively by a variety of conditions that are commonly associated with microglial activation and inflammation in the brain, such as chronic stress, aging, and neurodegenerative diseases, as we will review herein. Indeed, inflammation caused by irradiation produces a sustained inhibition of neurogenesis, notably by decreasing the proliferation and neuronal differentiation of the progenitors, and therefore, exposure to therapeutic doses of cranial irradiation has been widely used for modulating neurogenesis experimentally before the development of more specific approaches [54].
Regulation of Adult Hippocampal Neurogenesis by Inflammation
Inflammation is a natural bodily response to damage or infection that is generally mediated by proinflammatory cytokines such as interleukin 1 beta (IL-1), interleukin 6 (IL-6), and tumour necrosis factor alpha (TNF), in addition to lipidic mediators such as prostaglandins and leukotrienes. Oftentimes, it is associated with an increased production of ROS, as well as nitric oxide (NO). Together, these proinflammatory mediators lead to an increase in local blood flow, adhesion, and extravasation of circulating monocytes, neutrophils, and lymphocytes [55]. In the brain, microglia are the main orchestrator of the neuroinflammatory response, but other resident cell types, including astrocytes, endothelial cells, mast cells, perivascular and meningeal macrophages, and even neurons, can produce proinflammatory mediators, though perhaps not to the same extent as microglia [56]. In addition, peripheral immune cells invading the CNS during inflammation can further produce proinflammatory mediators, but the respective contribution of microglia versus other cell types in the inflammatory response of the brain is poorly understood.
The harmful effects of inflammation are also widely determined by the actual levels of proinflammatory mediators released, rather than the occurrence or absence of an inflammatory response in itself. For instance, TNF regulates synaptic plasticity by potentiating the cell surface expression of AMPA glutamatergic receptors, thus resulting in a homeostatic scaling following prolonged blockage of neuronal activity during visual system development [57]. However, TNF also produces differential effects at higher concentrations,ranging from an inhibition of long-term potentiation to an enhancement of glutamate-mediated excitotoxicityin vitro [58]. Inflammation induced by chronic ventricular infusion of bacterial lipopolysaccharides (LPS; a main component of the outer membrane of Gram-negative bacteria), that is, the most widely used method for inducing an inflammatory challenge, also increases ex vivo the hippocampal levels of TNF and IL-1, thereby impairing novel place recognition, spatial learning, and memory formation, but all these cognitive deficits can be restored by pharmacological treatment with a TNF protein synthesis inhibitor, a novel analog of thalidomide, 3,6′-dithiothalidomide [59].
The impact of inflammation on adult hippocampal neurogenesis was originally discovered by Olle Lindvall and Theo Palmer’s groups in 2003, showing that systemic or intrahippocampal administration of LPS reduces the formation of newborn neurons in the adult hippocampus, an effect that is prevented by indomethacin, a nonsteroidal anti-inflammatory drug (NSAID) which inhibits the synthesis of proinflammatory prostaglandins [60, 61]. Similarly, inflammation can determine the increase in neurogenesis that is driven by seizures, a context in which neurogenesis can be prevented by LPS and increased by the anti-inflammatory antibiotic minocycline [60]. In these studies, hippocampal proliferation remained unaffected by LPS or minocycline and thus it is likely that inflammation targeted the survival of newborn cells [60, 61], as LPS is known to increase SGZ apoptosis [62]. Inflammation also has further downstream effects on the neurogenic cascade. For instance, LPS increases the number of thin dendritic spines and the expression of the excitatory synapses marker “postsynaptic density protein of 95kDa” (PSD95) in newborn neurons. LPS in addition increases the expression of GABAA receptors at early stages of synapse formation, leading to suggesting a possible imbalance of excitatory and inhibitory neurotransmission in these young neurons [63]. Finally, LPS also prevents the integration of newborn neurons into behaviourally relevant networks, including most notably their activation during spatial exploration, as determined by the percentage of BrdU cells colabeled with the immediate early gene Arc [64].
Importantly, none of these manipulations is specific to microglia and may directly or indirectly affect other brain cells involved in the inflammatory response of the brain. For instance, both LPS and minocycline affect astrocytic function in vitro and in vivo [65–69]. Furthermore, LPS is known to drive infiltration of monocytes and neutrophils into the brain parenchyma [70]. Monocytes and neutrophils produce major proinflammatory mediators and could therefore act on the neurogenic cascade as well. The implication of microglia in LPS-induced decrease in neurogenesis is nonetheless supported in vivo by the negative correlation between the number of newborn neurons (BrdU+, NeuN+ cells) and the number of “activated” microglia (i.e., expressing ED1) [60]. ED1, also called CD68 or macrosialin, is a lysosomal protein which is overexpressed during inflammatory challenge. While the location of ED1 previously suggested its involvement in phagocytosis, its loss of function did not result in phagocytosis deficits and thus, its function still remains unknown (reviewed in [10]). The number of ED1-positive microglia also negatively correlates with neurogenesis during inflammation provoked by cranial irradiation [61]. While correlation does not involve causation, nor can pinpoint to the underlying mechanism, these experiments were the first to reveal a potential role for “activated” microglia in the regulation of adult hippocampal neurogenesis. More direct evidence of microglial mediation in LPS deleterious effects was obtained from in vitro experiments, as it was shown that conditioned media from LPS-challenged microglia contained IL-6, which in turn caused apoptosis of neuroblasts [61]. Nonetheless, astrocytes can also release IL-6 when stimulated with TNF or IL-1 [71] and chronic astrocytic release of IL-6 in transgenic mice reduced proliferation, survival, and differentiation of newborn cells, thus resulting in a net decrease in neurogenesis [72]. In summary, while the detrimental impact of inflammation on neurogenesis is well established, more work is needed to define the specific roles played by the various inflammatory cells populating the brain.
Inflammation Associated with Chronic Stress
Across health and disease, the most prevalent condition that is associated with neuroinflammation is “chronic stress,” which commonly refers to the repeated or sustained inability to cope with stressful environmental, social, and psychological constraints. Chronic stress is characterized by an imbalanced secretion of glucocorticoids by the hypothalamic-pituitary-adrenal (HPA) axis (most notably cortisol in humans and corticosterone in rodents), which leads to an altered brain remodeling, massive loss of synapses, and compromised cognitive function [73]. In particular, an impairment of spatial learning, working memory, novelty seeking, and decision making has been associated with chronic stress [74]. Glucocorticoids are well known for their anti-inflammatory properties, as they interfere with NF-B-mediated cytokine transcription, ultimately delaying wound healing [75]. They are also potent anti-inflammatory mediators in vivo [76] and in purified microglia cultures [77]. Recently, repeated administration of high doses of glucocorticoids by intraperitoneal injection, to mimic their release by chronic stress, was also shown to induce a loss of dendritic spines in the motor cortex, while impairing learning of a motor task. A transcription-dependent pathway acting downstream of the glucocorticoid receptor GR was proposed [78, 79] but the particular cell types involved were not identified.
Microglia are considered to be a direct target of the glucocorticoids, as they were shown to express GR during normal physiological conditions in vivo [77]. In fact, transgenic mice lacking GR in microglia and macrophages show an increased production of proinflammatory mediators (including TNF and IL-1) and greater neuronal damage in response to an intraparenchymal injection of LPS, compared to wild-type mice [80]. In contrast, glucocorticoids are considered to be proinflammatory in the chronically stressed brain [81], where among other changes they can promote inflammation, oxidative stress, neurodegeneration, and microglial activation [82]. For example, repeated restraint stress induces microglial proliferation and morphological changes, including a hyperramification of their processes in the adult hippocampus following restraint stress [83], but a nearly complete loss of processes in the context of social defeat [84]. Prenatal restraint stress also causes an increase in the basal levels of TNF and IL-1, while increasing the proportion of microglia showing a reactive morphology in the adult hippocampus [85]. Similarly, social defeat leads to an enhanced response to the inflammatory challenge induced by intraperitoneal injection of LPS, including an increased production of TNF and IL-1, and expression of inducible NO synthase (iNOS) by microglia, accompanied by an increased infiltration of circulating monocytes [84, 86]. Therefore, microglia are a strong candidate for mediating some of the effects of stress on adult neurogenesis, as will be discussed below, in synergy with other types of inflammatory cells.
Chronic stress is well known for its negative effects on hippocampal neurogenesis (reviewed in [87, 88]), although not all stress paradigms are equally effective [89]. Several stress paradigms can decrease neuroprogenitors proliferation in the tree shrew [90] and in mice [91, 92], although this effect seems to be compensated by an increased survival of newborn neurons [92] and whether stress results in a net increase or decrease in neurogenesis remains controversial (reviewed in [87, 88]). The effects of stress on adult neurogenesis seem to be mediated at least partially by glucocorticoids, because mice lacking a single copy of the GR gene show behavioural symptoms of depression including learned helplessness, neuroendocrine alterations of the HPA axis, and impaired neurogenesis [93]. In parallel, chronic stress is associated with an increased inflammatory response, which may inhibit neurogenesis as well. For instance, serum levels of IL-1and IL-6 are significantly increased in depressed patients [94]. In mice, restraint stress leads to a widespread activation of NF-B in the hippocampus, including at the level of neuroprogenitors [95] and increased protein levels of IL-1 [96]. In addition to the direct role of glucocorticoids, IL-1 also seems to mediate some of the effects of mild chronic stress, because in vivo manipulations that block IL-1 (either pharmacologically or in null transgenic mice) prevent the anhedonic stress response and the antineurogenic effect of stress [91, 96]. Moreover, the corticoids and IL-1 pathways may regulate each other in a bidirectional manner because the administration of a GR antagonist can blunt the LPS-induced production of hippocampal IL-1 in stressed mice [97], whereas mice knockout for the IL-1 receptor (IL-1R1) fail to display the characteristic elevation of corticosterone induced by mild chronic stress [96]. Another stress-related cytokine, IL-6, induces depressive phenotypes and prevents the antidepressant actions of fluoxetine when administered to mice in vivo [98]. So far the effects of stress on neurogenesis via corticosteroids and inflammation have been assumed to be cell autonomous, as neuroprogenitors express both GR [99] and IL-1R1 [95]. The potential participation of microglia is yet to be determined, but there are some reports of a direct effect of stress on microglial activation. For instance, microglia acutely isolated from mice subjected to acute stress (by inescapable tail shock) showed a primed response to LPS challenge by producing higher levels of IL-1 mRNA ex vivo [100], and the specific loss of expression of GR in microglia leads to a blunted inflammatory response in vitro and to a decreased neuronal damage in vivo in response to LPS [80]. In stress paradigms, these enhanced responses of microglia to inflammatory challenges are similar to their age-related “priming” which has been associated with and is possibly due to an increased basal production of proinflammatory mediators. However, whether microglia express increased levels of IL-1 and other proinflammatory cytokines in response to stressful events is presently unclear [101]. It is thus possible that some of the antineurogenic effects of stress are exerted by means of microglial-dependent inflammation, but this hypothesis remains to be experimentally tested.
Inflammation Associated with Aging and Neurodegenerative Diseases
Inflammation is also commonly associated with normal aging and neurodegenerative diseases and, therefore, could represent a putative underlying mechanism that explains their decrease in hippocampal neurogenesis. Nonetheless, inflammation is also associated with neurological diseases, such as epilepsy or stroke, where neurogenesis is thought to be increased, although the data from rodents and humans is somewhat conflictive [102]. Neurogenesis is well known to decline throughout adulthood and normal aging in rodents and humans [103, 104], but the decay is more pronounced and occurs later in life in mice than in humans [105]. The aging-associated decrease in neurogenesis has been shown to occur mainly as a consequence of exhaustion of the rNSC population which, after being recruited and activated, undergo three rounds of mitosis in average and then terminally differentiate into astrocytes [12, 106]. In addition, a reduced mitotic capacity of the neuroprogenitors could further contribute to decreasing neurogenesis [106], and moreover, an age-related increase in the levels of proinflammatory cytokines could also hinder neurogenesis in the aging brain. Serum levels of IL-1, IL-6, and TNF are elevated in elderly patients [107, 108]. Aged microglia express higher levels of these proinflammatory cytokines and show a greater response to LPS inflammatory challenge, that is, a “primed” response, than their younger counterparts [109]. The origin of this low-grade age-related inflammation (“inflamm-aging” [110]) remains unknown and may be related to both aging and damage to the surrounding neurons, as well as aging of the immune system per se.
At the cellular level, stress to the endoplasmic reticulum (ER) caused by various perturbations, such as nutrient depletion, disturbances in calcium or redox status, or increased levels of misfolded proteins, can induce a cell-autonomous inflammatory response to neurons. Stress to the ER, a multifunctional organelle which is involved in protein folding, lipid biosynthesis, and calcium storage triggers a homeostatic response mechanism named the unfolding protein response (UPR), aiming to clear the unfolded proteins in order to restore normal ER homeostasis [111]. However, if the ER stress cannot be resolved, the UPR also initiates inflammatory and apoptotic pathways via activation of the transcription factor NF-B which controls the expression of most proinflammatory cytokines [112]. In the brain, ER stress is often initiated by the formation of abnormal protein aggregates in several neurodegenerative diseases such as Alzheimer’s disease (AD), Parkinson’s disease (PD), amyotrophic lateral sclerosis (ALS), Huntington’s disease (HD), and prion-related disorders [113]. This neurodegeneration-associated ER stress is assumed to occur mostly in neurons, but there are some examples of microglial protein misfolding as well. For instance, both microglia and neurons overexpress CHOP (C/EBP homologous protein), a transcription factor which is activated during ER stress in human patients and mouse models of ALS [114]. Inflammation has been speculated to be a main negative contributor to the pathology of ALS [115], but a direct microglial involvement in mediating the inflammatory response to abnormal protein aggregation in ALS and other neurodegenerative conditions remains to be tested. Finally, ER stress has been linked to a variety of inflammatory conditions [116, 117], including chronic stress, diet-induced obesity, and drug abuse, as well as atherosclerosis and arthritis [118–120]. During normal aging, a progressive decline in expression and activity of key ER molecular chaperones and folding enzymes could also compromise the adaptive response of the UPR, thereby contributing to the age-associated decline in cellular functions [118]. Therefore, aging is strongly associated with a chronic ER stress which leads to increased activation of NF-B [112]; however, the contribution of the different brain cell types to “inflamm-aging” is still poorly understood. The detrimental effects on neurogenesis of increased proinflammatory cytokines in the aging brain are not necessarily related to microglia, but also to stressed neurons. Furthermore, ER stress may also cause a cell-autonomous response in neural stem cells [121], although its impact on neurogenesis remains to be experimentally determined.
In addition, aging is accompanied by an increased level of mitochondrial oxidative stress, which in turn activates the “Inflammasome” [122], a group of multimeric proteins comprising the interleukin 1 converting enzyme (ICE, caspase 1) which serves to release the active form of the cytokine [123]. IL-1 may act directly on rNSCs (visualised by labeling with the Sox2 marker), as they express IL-1R1 in the adult hippocampus [91]. Treatment with IL-1 decreases hippocampal proliferation in young mice [91] and pharmacological inhibition of ICE partially restores the number of newborn neurons in aged mice without significantly affecting their differentiation rate [124]. Transgenic IL-1 overexpression results in chronic inflammation and depletion of doublecortin-labeled neuroblasts, thus mimicking the aging-associated depletion of neurogenesis [125]. The actual mechanism of action of IL-1 on neurogenesis in aged mice, including decreased proliferation of rNSCs/ANPs and survival of newborn neurons, remains undetermined. Microglia are a main source of IL-1in the aging brain, but the hypothesis that microglia-derived IL-1 is responsible for depleting neurogenesis in the aging brain remains to be directly tested.
The regulation of neurogenesis by IL-1 in the aging brain has been further linked to the activity of another cytokine, the chemokine fractalkine, or CX3CL1. Fractalkine has soluble and membrane-tethered forms and is exclusively expressed by neurons, while the fractalkine receptor (CX3CR1) is expressed in the brain by microglia alone [126]. This module forms a unique neuron-microglia signalling unit that controls the extent of microglial inflammation in several neurodegenerative conditions including PD, ALS [127], or AD [128]. In fact, CX3CR1 blocking antibodies increase the production of hippocampal IL-1 when administered to young adult rats [129]. Importantly, chronic treatment with fractalkine increases hippocampal proliferation and the number of neuroblasts in aged (22 months old) but not young (3 months old) or middle-aged rats (12 months old), whereas an antagonists of CX3CR1 has the opposite effects in young, but not in middle-aged nor old rats [129]. Since fractalkine expression is decreased during aging [129], a reduced neuron-microglia signalling might be releasing the brake on microglial contribution to inflammatory responses, although increased levels of fractalkine were instead reported in aged rat hippocampus by other studies [68]. Additional insights into the role of fractalkine signalling come from knock-in mice in which the endogenous CX3CR1 locus is replaced by the fluorescent reporter GFP [126]. The initial studies suggested that (i.e., ) mice have no significant differences in brain development and functions [130], but more systematic investigations recently revealed a long list of hippocampal-dependent changes in young (3 months old) and mice compared to wild-type mice. These changes notably included decreased neuroprogenitors proliferation and neuroblasts number, impaired LTP, performance in contextual fear conditioning and water maze spatial learning and memory, and, importantly, increased IL-1 protein levels [131]. The signalling pathway of fractalkine-IL-1 is functionally relevant, because IL-1R1 antagonists rescued LTP and cognitive function in mice [131]. In sum, even though neuronal fractalkine seems to be sufficient for restraining the inflammatory activity of microglia in young rats, its downregulation during aging could activate the microglial inflammatory response and thereby subsequently reduce the proliferation of remaining neuroprogenitors.
In AD, inflammatory cytokines such as IL-1 are overexpressed in the microglia associated with the amyloid beta (A) plaques of postmortem samples [132] and in transgenic mice modeling the disease [133]. The loss of synapses (from hippocampus to frontal cortex) is one of the main pathological substrates in this disease, but adult neurogenesis is also severely reduced in most mouse models of AD, possibly due to a decreased proliferation of neuroprogenitors and a decreased survival of newborn cells, even though the putative changes in the neurogenic cascade in postmortem samples remain controversial (reviewed in [102]). This lack of agreement is possibly explained by the fact that the vast majority of AD cases have a late onset over 65 years of age, when little neurogenesis remains. In contrast, in most transgenic AD mouse models, the Aaccumulation, cognitive deficits, and changes in neurogenesis are already detectable in young animals (2-3 months old). The study of AD is further hindered by the difficulty in comparing the time course and pathology across different mouse models. For instance, early treatment with minocycline can improve cognition and reduce A burden in mice expressing the human amyloid precursor protein (APP) [134]. In contrast, in mice expressing APP and a mutated form of presenilin 1 (PS1), which is part of the secretase pathway that cleaves A, inflammation is reduced without any detectable changes in A plaques deposition [135]. Concomitantly with a decrease in tissue inflammatory cytokines and number of microglial cells, minocycline restores neurogenesis and hippocampus-dependent memory deficits in these APP/PS1 mice [135], indirectly suggesting that cognitive decay in AD may be at least in part related to a detrimental effect of inflammation on hippocampal neurogenesis. Direct evidence that neurogenesis is associated with the cognitive performance in AD is still lacking. Further research is also necessary to determine the neurogenic targets of AD-related inflammation. One central open question for future therapies aiming at increasing neurogenesis and cognition in AD is whether neuroprogenitors are spared or whether their age-induced loss becomes accelerated. Rather than increasing the proliferation and neurogenic output of the few rNSCs remaining in an old AD brain, it may be more relevant to develop strategies that prevent the age-related loss of neuroprogenitors in presymptomatic patients.
In summary, inflammation associated with a wide variety of experimental models of disease produces strong detrimental effects on hippocampal neurogenesis. These effects on human neurogenesis are however not so well described and, in vitro, IL-1 increases the proliferation of hippocampal embryonic neuroprogenitors but decreases their differentiation into neurons [136]. Novel methods to assess hippocampal neurogenesis in the living human brain, from metabolomics of neuroprogenitors to hippocampal blood brain volume (reviewed in [102]), will help to determine the contribution of inflammation to adult neurogenesis in the healthy and diseased human brain during aging.
Normal Physiological Conditions
In the healthy mature brain, microglia are an essential component of the neurogenic SGZ niche, where they physically intermingle with neuroprogenitors, neuroblasts, and newborn neurons [62]. Here, surveillant microglia effectively and rapidly phagocytose the excess of newborn cells undergoing apoptosis [62]. Importantly, microglial phagocytosis in the adult SGZ is not disturbed by inflammation associated with aging or by LPS challenge, as the phagocytic index (i.e., the proportion of apoptotic cells completely engulfed by microglia) is maintained over 90% in these conditions [62]. Nonetheless, the consequences of microglial phagocytosis on adult hippocampal neurogenesis remain elusive. Treatment of mice with annexin V, which binds to the phosphatidylserine (PS) receptor and prevents the recognition of PS on the surface of apoptotic cells, presumably blocking phagocytosis, increases the number of apoptotic cells in the SGZ [40]. Concomitantly, annexin V reduces neurogenesis by decreasing the survival of neuroblasts without affecting neuroprogenitors proliferation [40]. Similar results were obtained in transgenic mice knock-out for ELMO1, a cytoplasm protein which promotes the internalization of apoptotic cells, although the effects on neurogenesis were ascribed to a decreased phagocytic activity of neuroblasts [40]. The actual phagocytic target of the neuroblasts remains undetermined, but the newborn apoptotic cells in the adult SGZ are exclusively phagocytosed by microglia, at least in physiological conditions [62]. Nevertheless, none of the above manipulations has specifically tested the role of microglial phagocytosis in hippocampal-dependent learning and memory and thus, the functional impact of microglial phagocytosis in adult neurogenic niches during normal physiological conditions remains to be elucidated.
Microglial phagocytosis of apoptotic cells is actively anti-inflammatory, at least in vitro, and thus it has been hypothesized that anti-inflammatory cytokines produced by phagocytic microglia may further regulate neurogenesis [10]. For instance, transforming growth factor beta (TGF), which is produced by phagocytic microglia in vitro [137], inhibits the proliferation of SGZ neuroprogenitors [138]. Microglia are further able to produce proneurogenic factors in vitro [139]. When primed with cytokines associated with T helper cells such as interleukin 4 (IL-4) or low doses of interferon gamma (IFN), cultured microglia support neurogenesis and oligodendrogenesis through decreased production of TNF and increased production of insulin-like growth factor 1 (IGF-1) [139], an inducer of neuroprogenitor proliferation [26]. A list of potential factors produced by microglia and known to act on neuroprogenitor proliferation can be found in Table 1. In addition, recent observations suggest that neuroprogenitor cells may not only regulate their own environment, but also influence microglial functions. For instance, vascular endothelial growth factor (VEGF) produced by cultured neuroprecursor cells directly affects microglial proliferation, migration, and phagocytosis [20]. More potential factors produced by neuroprogenitors shown to be influencing microglial activity and function can be found in Table 2. However, it has to be taken into account that most of these observations were obtained in culture and that further research is needed in order to elucidate whether those factors are also secreted and have the same regulatory responses in vivo.
Table 1: Summary of factors secreted by microglia and the potential effect they have on neuroprogenitors in vitro.
Table 2: Summary of factors secreted by neuroprogenitors and the potential effect they have on microglia in vitro.
In addition, microglial capacity to remodel and eliminate synaptic structures during normal physiological conditions has suggested that microglia could also control the synaptic integration of the newborn neurons generated during adult hippocampal neurogenesis [140]. Three main mechanisms were proposed: (1) the phagocytic elimination of nonapoptotic axon terminals and dendritic spines, (2) the proteolytic remodeling of the perisynaptic environment, and (3) the concomitant structural remodeling of dendritic spines [7, 140]. Indeed, microglial contacts with synaptic elements are frequently observed in the cortex during normal physiological conditions, sometimes accompanied by their engulfment and phagocytic elimination [141–143], as in the developing retinogeniculate system [144]. Microglial cells are distinctively surrounded by pockets of extracellular space, contrarily to all the other cellular elements [142], suggesting that microglia could remodel the volume and geometry of the extracellular space, and thus the concentration of various ions, neurotransmitters, and signalling molecules in the synaptic environment. Whether microglia create the pockets of extracellular space themselves or not remains unknown, but these pockets could result from microglial release of extracellular proteases such as metalloproteinases and cathepsins [145], which are well known for influencing the formation, structural remodeling, and elimination of dendritic spines in situ and also experience-dependent plasticity in vivo [7, 146]. More recently, microglial phagocytosis of synaptic components was also observed in the developing hippocampus, in the unique time window of synaptogenesis, a process which is notably regulated by fractalkine-CX3CR1 signalling [147]. Therefore, the attractive hypothesis that microglial sculpts the circuitry of newborn cells in the adult hippocampus deserves further attention.
Lastly, microglia were also involved in increasing adult hippocampal neurogenesis in the enriched environment (EE) experimental paradigm. EE is a paradigm mimicking some features of the normal living circumstances of wild animals, as it gives them access to social interactions, toys, running wheels, and edible treats. EE has long been known to enhance neurogenesis by acting on newborn cells survival, resulting ultimately in an enlargement of the dentate gyrus [148]. Functionally, these changes are accompanied by enhanced spatial learning and memory formation with the water maze paradigm [149]. Similar increases in neurogenesis are obtained by subjecting mice to voluntary running paradigms, although in this case the effect is mediated by increased neuroprogenitor proliferation [150]. During inflammatory conditions, EE is antiapoptotic and neuroprotective [151] and it limits the hippocampal response to LPS challenge by decreasing the expression of several cytokines and chemokines, including IL1- and TNF [152]. In fact, EE is believed to counteract the inflammatory environment and rescue the decreased number of neuroblasts in mice compared to wild-type mice [153]. The effects of EE are independent of the IL-1 signalling pathway, as it increases neurogenesis in mice that are null for IL-1R1 [154]. EE also induces microglial proliferation and expression of the proneurogenic IGF-1 [155], but the full phenotype of microglia in EE compared to standard housing and its impact on the neurogenic cascade remains to be determined.
The mechanisms behind the anti-inflammatory actions of EE are unknown, but they were suggested to involve microglial interactions with T lymphocytes through an increased expression of the major histocompatibility complex of class II (MHC-II) during EE [155]. MHC-II is responsible for presenting the phagocytosed and degraded antigens to the antibodies expressed on the surface of a subtype of T lymphocytes (T helper or CD4+ cells), thus initiating their activation and production of antigen-specific antibodies. Severe combined immunodeficient (SCID) mice lacking either T and B lymphocytes or nude mice lacking only T cells have impaired proliferation and neurogenesis in normal and EE housing compared to wild-type mice [155], as well as impaired performance in the water maze [156]. Similarly, antibody-based depletion of T helper lymphocytes impairs basal and exercise-induced proliferation and neurogenesis [157]. Furthermore, a genetic study in heterogeneous stock mice, which descend from eight inbred progenitor strains, has found a significant positive correlation between genetic loci associated to hippocampal proliferation and to the proportion of CD4+ cells among blood CD3+ lymphocytes [158]. Additional experiments are needed to fully determine the possible interactions between microglia and T cells in neurogenesis, because, at least in normal physiological conditions, (1) T cell surveillance of the brain parenchyma is minimal, (2) microglia are poor antigen presenting cells, and (3) antigen presentation by means of MHC-II family of molecules is thought to occur outside the brain, that is, in the meninges and choroid plexus [159]. In fact, during voluntary exercise, there are no significant changes in T cell surveillance of the hippocampus, nor a direct interaction between T cells and microglia, nor any changes in the gene expression profile of microglia, including that of IGF-1, IL-1, and TNF [160]. The number of microglia is also inversely correlated with the number of hippocampal proliferating cells, rNSCs, and neuroblasts in aged (8 months) mice subjected to voluntary running, as well asin vitro cocultures of microglia and neuroprogenitors, which has been interpreted as resulting from an overall inhibitory effect of microglia on adult neurogenesis [161]. Even though EE is clearly a more complex environmental factor than voluntary running, further research is necessary to disregard nonspecific or indirect effects of genetic or antibody-based T cells depletion on microglia and other brain cell populations, including rNSCs. For instance, adoptive transfer of T helper cells treated with glatiramer acetate, a synthetic analog of myelin basic protein (MBP) approved for the treatment of multiple sclerosis, produces a bystander effect on resident astrocytes and microglia by increasing their expression of anti-inflammatory cytokines such as TGF[162]. Alternatively, it has been suggested that T cells may mediate an indirect effect on adult hippocampal neurogenesis by increasing the production of brain-derived neurotrophic factor (BDNF) [157], which is involved in the proneurogenic actions of EE [163]. Whether BDNF can counteract the detrimental effects of T cell depletion on neurogenesis remains unknown. Overall, the roles of microglia in EE and running-induced neurogenesis are unclear and have to be addressed with more precise experimental designs. In summary, surveillant microglia are part of the physical niche surrounding the neural stem cells and newborn neurons of the mature hippocampus, where they continuously phagocytose the excess of newborn cells. Microglia were also linked to the proneurogenic and anti-inflammatory effects of voluntary running and EE, but direct evidence is missing. The overall contribution of microglia to neurogenesis and learning and memory in normal physiological conditions remains largely unexplored at this early stage in the field.
Conclusion
In light of these observations, microglia are now emerging as important effector cells during normal brain development and functions, including adult hippocampal neurogenesis. Microglia can exert a positive or negative influence on the proliferation, survival, or differentiation of newborn cells, depending on the inflammatory context. For instance, microglia can compromise the neurogenic cascade during chronic stress, aging, and neurodegenerative diseases, by their release of proinflammatory cytokines such as IL-1, IL-6, and TNF. A reduced fractalkine signalling between neurons and microglia could also be involved during normal aging. However, microglia are not necessarily the only cell type implicated because astrocytes, endothelial cells, mast cells, perivascular and meningeal macrophages, and to a lesser extent neurons and invading peripheral immune cells could further contribute by releasing proinflammatory mediators.
Additionally, microglia were shown to phagocytose the excess of newborn neurons undergoing apoptosis in the hippocampal neurogenic niche during normal physiological conditions, while a similar role in the synaptic integration of newborn cells was also proposed in light of their capacity to phagocytose synaptic elements. Lastly, microglial interactions with T cells, leading to the release of anti-inflammatory cytokines, neurotrophic factors, and other proneurogenic mediators (notably during EE and voluntary running), could counteract the detrimental effects of inflammation on adult hippocampal neurogenesis and their functional implications for learning and memory.
However, further research is necessary to assess the relative contribution of microglia versus other types of resident and infiltrating inflammatory cells and to determine the nature of the effector cytokines and other inflammatory mediators involved, as well as their cellular and molecular targets in the neurogenic cascade. Such research will undoubtedly help to develop novel strategies aiming at protecting the neurogenic potential and ultimately its essential contribution to learning and memory.
Abbreviations
AD:
Alzheimer’s disease
ANPs:
Amplifying neuroprogenitors
APP:
Amyloid precursor protein
A:
Amyloid beta
BDNF:
Brain-derived neurotrophic factor
BrdU:
5-Bromo-2′-Deoxyuridine
CX3CL1:
Fractalkine
CX3CR1:
Fractalkine receptor
EAE:
Experimental acute encephalomyelitis
EE:
Enriched environment
EGF:
Epidermal growth factor
FGFb:
Basic fibroblast growth factor
GDNF:
Glial cell line-derived neurotrophic factor
GFAP:
Glial fibrillary acidic protein
GR:
Glucocorticoid receptor
HPA:
Hypothalamic-pituitary-adrenal axis
ICE:
Interleukin 1 converting enzyme
IL-1:
Interleukin 1 beta
IL-1R1:
Interleukin 1 beta receptor
IL-4:
Interleukin 4
IL-6:
Interleukin 6
IL-7:
Interleukin 7
IL-11:
Interleukin 11
IFN:
Interferon gamma
IGF-1:
Insulin-like growth factor 1
iNOS:
Inducible nitric oxide synthase
LPS:
Bacterial lipopolysaccharides
LTP:
Long term potentiation
M-CSF:
Macrophage colony-stimulating factor
MBP:
Myelin basic protein
MHC-II:
Major histocompatibility complex class II
MOG:
Myelin oligodendrocyte glycoprotein
NF-B:
Nuclear factor kappa-light-chain-enhancer of activated B cells
NGF:
Nerve growth factor
NO:
Nitric oxide
NSAID:
Nonsteroidal anti-inflammatory drug
NT-4:
Neurotrophin-4
PDGF:
Platelet-derived growth factor
PS:
Phosphatidylserine
PS1:
Presenilin 1
ROS:
Radical oxygen species
SCID:
Severe combined immunodeficiency
SGZ:
Subgranular zone
TGF:
Transforming growth factor beta
TNF:
Tumor necrosis factor alpha
VEGF:
Vascular endothelial growth factor.
Conflict of Interests
The authors declare that there is no conflict of interests regarding the publication of this paper.
Acknowledgments
This work was supported by grants from the Spanish Ministry of Economy and Competitiveness to Amanda Sierra (BFU2012-32089) and Juan M. Encinas (SAF2012-40085), from Basque Government (Saiotek S-PC 12UN014) and Ikerbasque start-up funds to Juan M. Encinas and Amanda Sierra, and from The Banting Research Foundation, the Scottish Rite Charitable Foundation of Canada, and start-up funds from Université Laval and Centre de recherche du CHU de Québec to Marie-Ève Tremblay.
References
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The endoplasmic reticulum (ER) responds to the accumulation of unfolded proteins in its lumen (ER stress) by activating intracellular signal transduction pathways — cumulatively called the unfolded protein response (UPR). Together, at least three mechanistically distinct arms of the UPR regulate the expression of numerous genes that function within the secretory pathway but also affect broad aspects of cell fate and the metabolism of proteins, amino acids and lipids. The arms of the UPR are integrated to provide a response that remodels the secretory apparatus and aligns cellular physiology to the demands imposed by ER stress.
Figure 1: The unfolded protein response (UPR) signalling pathways.
Upon endoplasmic reticulum (ER) stress, unfolded and misfolded proteins bind and sequester immunoglobulin heavy-chain binding protein (BIP), thereby activating the UPR. The UPR comprises three parallel signalling branches: PRKR-like ER kinase (PERK)–eukaryotic translation initiation factor 2α (eIF2α), inositol-requiring protein 1α (IRE1α)–X-box binding protein 1 (XBP1) and activating transcription factor 6α (ATF6α). The outcome of UPR activation increases protein folding, transport and ER-associated protein degradation (ERAD), while attenuating protein synthesis. If protein misfolding is not resolved, cells enter apoptosis. CHOP, C/EBP homologous protein; GADD34, growth arrest and DNA damage-inducible protein 34; JNK, JUN N-terminal kinase; P, phosphorylation; RIDD, regulated IRE1-dependent decay; ROS, reactive oxygen species; XBP1s, transcriptionally active XBP1; XBP1u, unspliced XBP1.
Figure 3: The unfolded protein response (UPR) and inflammation.
The three UPR pathways augment the production of reactive oxygen species (ROS) and activate nuclear factor-κB (NF-κB) and activator protein 1 (AP1) pathways, thereby leading to inflammation. NF-κB, which is a master transcriptional regulator of pro-inflammatory pathways, can be activated through binding to the inositol-requiring protein 1α (IRE1α)–TNF receptor-associated factor 2 (TRAF2) complex in response to endoplasmic reticulum (ER) stress, leading to recruitment of the IκB kinase (IKK), IκB phosphorylation (P) and degradation, and nuclear translocation of NF-κB196. Moreover, the IRE1α–TRAF2 complex can recruit apoptosis signal-regulating kinase 1 (ASK1) and activate JUN N-terminal kinase (JNK), increasing the expression of pro-inflammatory genes through enhanced AP1 activity197. The PRKR-like ER kinase (PERK)–eukaryotic translation initiation factor 2α (eIF2α) and activating transcription factor 6α (ATF6α) branches of the UPR activate NF-κB through different mechanisms. Engaging PERK–eIF2α signalling halts overall protein synthesis and increases the ratio of NF-κB to IκB, owing to the short half-life of IκB, thereby freeing NF-κB for nuclear translocation198, 199. ATF6α activation following exposure to the bacterial subtilase cytotoxin that cleaves immunoglobulin heavy-chain binding protein (BIP) leads to AKT phosphorylation and consequent NF-κB activation109, 200.
Liver cancer stem cells (CSCs) harbor self-renewal and differentiation properties, accounting for chemotherapy resistance and recurrence. However, the molecular mechanisms to sustain liver CSCs remain largely unknown. In this study, based on analysis of several hepatocellular carcinoma (HCC) transcriptome datasets and our experimental data, we find that C8orf4 is weakly expressed in HCC tumors and liver CSCs. C8orf4 attenuates the self-renewal capacity of liver CSCs and tumor propagation. We show that NOTCH2 is activated in liver CSCs. C8orf4 is located in the cytoplasm of HCC tumor cells and associates with the NOTCH2 intracellular domain, which impedes the nuclear translocation of N2ICD. C8orf4 deletion causes the nuclear translocation of N2ICD that triggers the NOTCH2 signaling, which sustains the stemness of liver CSCs. Finally, NOTCH2 activation levels are consistent with clinical severity and prognosis of HCC patients. Altogether, C8orf4 negatively regulates the self-renewal of liver CSCs via suppression of NOTCH2 signaling.
Like stem cells, CSCs are characterized by self-renewal and differentiation simultaneously9. Not surprisingly, CSCs share core regulatory genes and developmental pathways with normal tissue stem cells. Accumulating evidence shows that NOTCH, Hedgehog and Wnt signaling pathways are implicated in the regulation of CSC self-renewal4. NOTCH signaling modulates many aspects of metazoan development and tissue stemness10, 11. NOTCH receptors contain four members (NOTCH1–4) in mammals, which are activated by engagement with various ligands. The aberrant NOTCH signaling was first reported to be involved in the tumorigenesis of human T-cell leukaemia12, 13. Recently, a number of studies have reported that the NOTCH signaling pathway is implicated in regulating self-renewal of breast stem cells and mammary CSCs14, 15. However, how the NOTCH signaling regulates the liver CSC self-renewal remains largely unknown.
C8orf4, also called thyroid cancer 1 (TC1), was originally cloned from a papillary thyroid carcinoma and its surrounding normal thyroid tissue16. C8orf4 is ubiquitously expressed across a wide range of vertebrates with the sequence conservation across species. A number of studies have reported that C8orf4 is highly expressed in several tumors and implicated in tumorigenesis17, 18, 19. In addition, C8orf4 augments Wnt/β-catenin signaling in some cancer cells20, 21, suggesting it may be involved in the regulation of self-renewal of CSCs. However, the biological function of C8orf4 in the modulation of liver CSC self-renewal is still unknown. Here we show that C8orf4 is weakly expressed in HCC and liver CSCs. NOTCH2 signaling is highly activated in HCC tumors and liver CSCs. C8orf4 negatively regulates the self-renewal of liver CSCs via suppression of NOTCH2 signaling.
C8orf4 is weakly expressed in HCC tissues and liver CSCs
To search for driver genes in the oncogenesis of HCC, we performed genome-wide analyses using several online-available HCC transcriptome datasets by R language and Bioconductor approaches. After analysing gene expression profiles of HCC tumor and peri-tumor tissues, we identified >360 differentially expressed genes from both Park’s cohort (GSE36376; ref. 22) and Wang’s cohort (GSE14520; refs 23, 24). Of these changed genes, we focused on C8orf4, which was weakly expressed in HCC tumors derived from both Park’s cohort (GSE36376) and Wang’s cohort (GSE14520) (Fig. 1a). Lower expression of C8orf4 was further confirmed in HCC samples by quantitative reverse transcription–PCR (qRT–PCR) and immunoblotting (Fig. 1b,c). In this study, HCC patient samples we used included all subtypes of HCC. In addition, these observations were further validated by immunohistochemical (IHC) staining (Fig. 1d). These data indicate that C8orf4 is weakly expressed in HCC tumor tissues.
C8orf4 is weakly expressed in HCC tumours and liver CSCs
Figure 1. C8orf4 is weakly expressed in HCC tumours and liver CSCs
(a)C8orf4 is weakly expressed in HCC patients. Using R language and Bioconductor methods, we analyzed C8orf4 expression in HCC tumor and peri-tumor tissues provided by Park’s cohort (GSE36376) and Wang’s cohort (GSE14520) datasets. (b,c) C8orf4 expression levels were verified in HCC patient samples by quantitative RT–PCR (qRT–PCR) (b) and immunoblotting (c). β-actin served as a loading control. 18S: 18S rRNA. (d) HCC samples were assayed by immunohistochemical staining. Scale bar—left: 50 μm; right: 20 μm. (e) C8orf4 is weakly expressed in CD13+CD133+ cells sorted from Huh7 cells and primary HCC samples. C8orf4 messenger RNA (mRNA) was measured by qRT–PCR. Six HCC samples got similar results. (f) C8orf4 is much more weakly expressed in oncospheres than non-sphere tumor cells. Non-sphere: Huh7 or HCC primary cells that failed to form spheres. (g) HCC sample tissues were co-stained with anti-C8orf4 and anti-CD13 or anti-CD133 antibodies, then counterstained with DAPI for confocal microscopy. White arrows indicate CD13+ or CD133+ cells. Scale bars: 20 μm. For a,b, data are shown as box and whisker plot. Boxes represent interquartile range (IQR); upper and lower edge corresponds to the 75th and 25th percentiles, respectively. Horizontal lines within boxes represent median levels of gene intensity. Whiskers below and above boxes extend to the 5th and 95th percentiles, respectively. For e and f, Student’s t-test was used for statistical analysis, *P<0.05;**P<0.01, data are shown as mean ± standard deviation. Data are representative of at least three independent experiments. P, peri-tumor; T, tumor.
Notably, C8orf4 was also weakly expressed in embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSCs) by analysis of its expression profiles derived from online datasets (GSE14897; ref. 25 and GSE25417; ref. 26) (Supplementary Fig. 1a,b). C8orf4 was also lowly expressed in normal liver stem cells (Supplementary Fig. 1c,d), suggesting that C8orf4 may be involved in the regulation of self-renewal of liver stem cells. Thus, we propose that C8orf4 might play a role in the maintenance of liver CSCs. Since CD13 and CD133 were widely used as liver CSC surface markers, we sorted CD13+CD133+ cells from Huh7 and Hep3B HCC cell lines as well as HCC samples, serving as liver CSCs. We observed that C8orf4 was weakly expressed in liver CSCs enriched from both HCC cell lines and patient samples (Fig. 1e). Six HCC samples were analyzed for these experiments. Similar results were obtained in CD13+CD133+ cells from Hep3B cells. Furthermore, we performed sphere formation experiments using Huh7 cells and HCC primary sample cells, and detected expression levels of C8orf4. We observed that C8orf4 was dramatically reduced in the oncospheres generated by both HCC cell lines and patient samples (Fig. 1f). In addition, we noticed that C8orf4 expression was negatively correlated with liver CSC markers such as CD13 and CD133 in HCC samples (Fig. 1g), suggesting lower expression of C8orf4 in liver CSCs. Moreover, C8orf4 was mainly located in the cytoplasm of tumour cells. Altogether, C8orf4 is weakly expressed in HCC tumor tissues and liver CSCs.
C8orf4 negatively regulates self-renewal of liver CSCs
We then wanted to look at whether C8orf4 plays a critical role in the self-renewal maintenance of liver CSCs. C8orf4 was knocked out in Huh7 cells through a CRISPR/Cas9 system (Fig. 2a). TwoC8orf4-knockout (KO) cell strains were established and C8orf4 was completely deleted in these two strains. C8orf4 deletion dramatically enhanced oncosphere formation (Fig. 2b). We co-stained SOX9, a widely used progenitor marker, and Ki67, a well-known proliferation marker, in C8orf4 KO sphere cells. We found that SOX9 was strongly stained in C8orf4 KO sphere cells (Supplementary Fig. 2a). In contrast, Ki67 staining was not significantly altered in C8orf4 KO sphere cells versus WT sphere cells. We also digested sphere cells and examined the SOX9 and Ki67 expression by flow cytometry. Similar results were achieved (Supplementary Fig. 2b). Importantly, through serial passage of CSC sphere cells, similar observations were obtained in the fourth generation oncosphere assay (Supplementary Fig. 2c,d). These data suggest that C8orf4 is involved in the regulation of liver CSC self-renewal.
(not shown)
Figure 2: C8orf4 knockout enhances self-renewal of liver CSCs.
C8orf4-deficient Huh7 cells were established using a CRISPR/Cas9 system. T7 endonuclease I cleavage confirmed the efficiency of sgRNA (left panel, white arrowheads), and C8orf4-knockout efficiency was confirmed by western blot (right panel). Two knockout cell lines were used. C8KO#1:C8orf4KO#1; C8KO#2: C8orf4KO#2. (b) C8orf4-deficient cells enhanced sphere formation activity. Calculated ratios are shown in the right panel. (c) C8orf4-deficient or WT Huh7 cells (1 × 106) were injected into BALB/c nude mice. Tumor sizes were observed every 5 days. (d) C8orf4 deficiency enhances tumor-initiating capacity. Diluted cell numbers of Huh7 cells were implanted into BALB/c nude mice for tumor initiation. Percentages of tumor-formation mice were calculated (left panel), and frequency of tumor-initiating cells was calculated using extreme limiting dilution analysis (right panel). Error bars represent the 95% confidence intervals of the estimation. (e) Expression levels of CD13 andCD133 were analyzed in C8orf4-knockout Huh7 cells. (f) C8orf4 was silenced in HCC primary cells and C8orf4 depletion enhanced sphere formation activity. Calculated ratios are shown at the right panel. Three HCC specimens obtained similar results. (g) C8orf4-overexpressing Huh7 cells were established (left panel). C8orf4-overexpressing Huh7 cells and control Huh7 cells were cultured for sphere formation. (h,i) Xenograft tumor growth (h) and frequency of tumor-initiating cells (i) for C8orf4-overexpressing Huh7 cells were analyzed as c,d. (j) C8orf4 overexpression reduces expression of CD133 and CD13 in Huh7 cells. (k) C8orf4 was transfected in HCC primary cells and cultured for sphere formation. Three HCC patient samples obtained similar results. Scale bars: b,f,g,k, 500 μm. Student’s t-test was used for statistical analysis, *P<0.05; **P<0.01; ***P<0.001, data are shown as mean ± standard deviation. Data represent at least three independent experiments. oeC8orf4, overexpression of C8orf4; oeVec, overexpression vector.
In addition, C8orf4-deficient Huh7 cells overtly increased xenograft tumour growth (Fig. 2c). We then performed sphere formation and digested oncospheres formed by C8orf4-deficient or WT cells into single-cell suspension, then subcutaneously implanted 1 × 104, 1 × 103, 1 × 102 and 10 cells into BALB/c nude mice. Tumour formation was examined for tumour-initiating capacity at the third month. C8orf4 deficiency remarkably enhanced tumour-initiating capacity and liver CSC ratios (Fig. 2d). In addition, C8orf4 deletion significantly enhanced expression levels of the liver CSC markers such as CD13 and CD133 (Fig. 2e). We also silenced C8orf4 in HCC primary cells using a lentivirus infection system and established C8orf4-silenced cells. Two pairs of short hairpin RNA (shRNA) sequences obtained similar knockdown efficiency. C8orf4 knockdown remarkably promoted sphere formation and xenograft tumour growth (Fig. 2f and Supplementary Fig. 2e). These data indicate that C8orf4 deletion potentiates the self-renewal of liver CSCs.
We next overexpressed C8orf4 in Huh7 cells and HCC primary cells using lentivirus infection. We observed that C8orf4 overexpression in Huh7 cells remarkably reduced sphere formation and xenograft tumour growth (Fig. 2g,h). In addition, C8orf4 overexpression remarkably reduced tumour-initiating capacity and expression of liver CSC markers (Fig. 2i,j). Similar results were observed by C8orf4 overexpression in HCC primary cells (Fig. 2k). We tested three HCC samples with similar results. Overall, C8orf4 negatively regulates the maintenance of liver CSC self-renewal and tumour propagation.
C8orf4 suppresses NOTCH2 signaling in liver CSCs
To further determine the underlying mechanism of C8orf4 in the regulation of liver CSCs, we analyzed three major self-renewal signaling pathways, including Wnt/β-catenin, Hedgehog and NOTCH pathways, in C8orf4-deleted Huh7 cells and HCC primary cells. We found that only NOTCH target genes were remarkably upregulated in C8orf4-deficient cells (Fig. 3a), whereasC8orf4 deficiency did not significantly affect the Wnt/β-catenin or the Hedgehog pathway. Given that the NOTCH family receptors have four members, we wanted to determine which NOTCH member was involved in the C8orf4-mediated suppression of liver CSC stemness. We noticed that only NOTCH2 was highly expressed in both Huh7 cells and HCC samples (Fig. 3b). In addition, this result was also confirmed by analysis of NOTCH expression levels derived from Wang’s cohort (GSE14520) and Petel’s cohort (E-TABM-36; ref. 27) (Fig. 3c). Moreover, we analysed expression profiles of C8orf4 and NOTCH target genes using Park’s cohort (GSE36376) and Wurmbach’s cohort (GSE6764; ref. 28). These cohort datasets provided several Notch signaling and its target genes. HEY1, NRARP and HES6 genes were highly expressed in HCC tumour tissues (GSE6764; ref. 28), which were further confirmed in HCC samples by real-time PCR (Supplementary Fig. 3a,b). Furthermore, HEY1, NRARP and HES6 genes have been reported to be relatively specific NOTCH target genes. We then examined these three genes as the NOTCH2 target genes throughout this study. We found that the C8orf4 expression level was negatively correlated with the expression levels of HEY1 and HES6, suggesting that C8orf4 inhibited NOTCH signaling in HCC patients (Fig. 3d). Finally these results were further confirmed in HCC samples by qRT-PCR (Fig. 3e). To further explore the activation status of NOTCH2 signaling in liver CSCs, we examined the expression levels of NOTCH downstream target genes in oncospheres and CD13+CD133+ cells derived from both Huh7 cells and HCC cells. We observed that NOTCH target genes were highly expressed in liver CSCs (Fig. 3f,g). These observations were verified by immunoblotting (Fig. 3h). In addition, the expression levels of NRARP, HES6 and HEY1 were positively related to the expression levels of EpCAM and CD133 derived from Zhang’s cohort (GSE25097; ref. 29) and Wang’s cohort (GSE14520; Supplementary Fig. 3c,d). These data suggest that the NOTCH2 signaling plays a critical role in the maintenance of self-renewal of liver CSCs.
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Figure 3: C8orf4 suppresses NOTCH2 signaling in liver CSCs.
(a) C8orf4 deficiency or depletion activates NOTCH signaling. The indicated major stemness signalling pathways were analysed in C8orf4-knockout Huh7 cells (left panel) and C8orf4-silenced primary cells of HCC samples (right panel). (b) Four receptor members of NOTCH family were examined in both Huh7 cells (left panel) and 29 pairs of HCC samples (right panel). (c) NOTCH receptors were analyzed from Wang’s cohort (left panel) and Petel’s cohort (right panel) datasets. (d) HEY1 and HES6 were highly expressed in C8orf4low samples by analysis of Park’s cohort (upper panel) and Wurmbach’s cohort (lower panel). (e) Expression levels of HEY1 and HES6 along with C8orf4 were analysed in HCC samples by qRT–PCR. (f,g) Expression levels of NRARP, HEY1 and HES6 in spheres generated by Huh7 cells and HCC primary cells (f) and in CD13+CD133+ cells sorted from Huh7 cells and HCC primary cells (g). Non-sphere: Huh7 cells or HCC cells that failed to form spheres. (h) HEY1, HES6 and NRARP expression in sphere and non-sphere cells was detected by immunoblotting. β-actin was used as a loading control. For c,d, data are shown as box and whisker plot. Box: interquartile range (IQR); horizontal line within box: median; whiskers: 5–95 percentile. For a,b,f,g, Student’s t-test was used for statistical analysis, *P<0.05;**P<0.01; ***P<0.001, data are shown as mean ± standard deviation. Data are representative of at least three independent experiments.
C8orf4 interacts with NOTCH2 that is critical for liver CSCs
On ligand–receptor binding, the NOTCH receptor experiences a proteolytic cleavage by metalloprotease and γ-secretase, releasing a NOTCH extracellular domain (NECD) and a NOTCH intracellular domain (NICD), respectively30. Then the active NICD undergoes nuclear translocation and activates the expression of NOTCH downstream target genes31.Then we constructed the NOTCH2 extracellular domain (N2ECD) and intracellular domain (N2ICD) and examined the interaction with C8orf4 via a yeast two-hybrid approach. Interestingly, we found that C8orf4 interacted with N2ICD, but not N2ECD (Fig. 4a). The interaction was validated by co-immunoprecipitation (Fig. 4b). Through domain mapping, the ankyrin repeat domain of NOTCH2 was essential and sufficient for its association with C8orf4 (Fig. 4c). Taken together, C8orf4 interacts with the N2ICD domain of NOTCH2.
Figure 4: C8orf4 interacts with NOTCH2 that is required for the self-renewal maintenance of liver CSCs.
C8orf4 interacts with NOTCH2 that is required for the self-renewal maintenance of liver CSCs
(a) C8orf4 interacts with N2ICD. Yeast strain AH109 was co-transfected with Gal4 DNA-binding domain (BD) fused C8orf4 and Gal4-activating domain (AD) fused N2ICD. p53 and large T antigen were used as a positive control. (b) Recombinant Flag-N2ICD and GFP–C8orf4 were incubated for co-immunoprecipitation. (c) The ankyrin repeat AR domain is essential and sufficient for the interaction of C8orf4 with N2ICD. Various N2ICD truncation constructs were co-transfected with GFP–C8orf4 for domain mapping. NLS: nuclear location signal. (d) NOTCH2 was knocked down in Huh7 cells and detected by qRT–PCR and immunoblotting. (e) NOTCH2-silenced Huh7 cells were cultured for sphere formation assays. Two pairs of shRNAs against NOTCH2 obtained similar results. (f,g) Xenograft tumor growth (f) and frequency of tumor-initiating cells (g) for NOTCH2-silenced Huh7 cells were analyzed. (h) NOTCH2 was silenced in HCC primary cells and NOTCH2 depletion declined sphere formation activity. Three HCC specimens obtained similar results. (i) Sphere formation capacity was examined in differently treated HCC primary cells. (j) HCC primary cells were treated with indicated lentivirus and implanted into BALB/c nude mice for xenograft tumor growth assays. Scale bars: e,h,i, 500 μm, Student’s t-test was used for statistical analysis, *P<0.05; **P<0.01; ***P<0.001, data are shown as mean ± standard deviation. Data are representative of at least three independent experiments. IB, immunoblotting; IP, immunoprecipitation; NS, not significant.
To further verify the role of NOTCH2 in the maintenance of liver CSC self-renewal, we knocked down NOTCH2 in Huh7 cells and established stably depleted cell lines by two pairs of NOTCH2 shRNAs (Fig. 4d). NOTCH2 knockdown dramatically reduced sphere formation (Fig. 4e), as well as attenuated xenograft tumor growth and tumor-initiating capacity (Fig. 4f,g). Similar observations were achieved in NOTCH2-depleted HCC primary cells (Fig. 4h). In addition, we found that simultaneous knockdown of NOTCH2 and overexpression of C8orf4 failed to reduce sphere formation capacity compared with individual knockdown of NOTCH2 (Fig. 4i), suggesting that NOTCH2 and C8orf4 affected sphere formation through the same pathway. Meanwhile, C8orf4 knockdown failed to rescue the sphere formation ability of NOTCH2-depleted HCC primary cells (Fig. 4i). Similar observations were obtained in Huh7 cells (Supplementary Fig. 4). Finally, NOTCH2 depletion in C8orf4-silenced Huh7 cells or HCC primary cells also abrogated the C8orf4 depletion-mediated enhancement of xenograft tumor growth (Fig. 4j), suggesting that C8orf4 acted as upstream of NOTCH2 signaling. These data suggest that C8orf4 suppresses the liver CSC stemness through inhibiting the NOTCH2 signaling pathway.
C8orf4 blocks nuclear translocation of N2ICD
As shown in Fig. 1g, C8orf4 was mainly localized in the cytoplasm in tumor cells of HCC samples. To confirm these observations, we stained C8orf4 in several HCC cell lines and noticed that C8orf4 also resided in the cytoplasm of Huh7 cells and Hep3B cells (Fig. 5a and Supplementary Fig. 5a). These results were further validated by cellular fractionation (Fig. 5b). Importantly, C8orf4 KO led to nuclear translocation of N2ICD (Fig. 5c). In addition, we also examined the intracellular location of N2ICD in Huh7 spheres. We found that C8orf4 deletion caused complete nuclear translocation of N2ICD in oncosphere cells (Fig. 5d,e), while N2ICD was mainly located in the cytoplasm of WT oncosphere cells. However, we found that C8orf4 KO did not affect subcellular localization of β-catenin (Supplementary Fig. 5b,c). Through luciferase assays, C8orf4 transfection did not significantly influence promoter transcription activity of Wnt target genes such as TCF1, LEF and SOX4 (Supplementary Fig. 5d). These data indicate that C8orf4 resides in the cytoplasm of HCC cells and inhibits nuclear translocation of N2ICD.
C8orf4 deletion causes the nuclear translocation of N2ICD
Figure 5: C8orf4 deletion causes the nuclear translocation of N2ICD.
(a) C8orf4 resides in the cytoplasm of Huh7 cells. Huh7 cells were permeabilized and stained with anti-C8orf4 antibody, then counterstained with PI for confocal microscopy. (b) Cellular fractionation was performed and detected by immunoblotting. (c,d) C8orf4 knockout causes the nuclear translocation of N2ICD. C8orf4-deficient Huh7 cells (c) and sphere cells (d) were permeabilized and stained with anti-C8orf4 and anti-N2ICD antibodies, then counterstained with DAPI followed by confocal microscopy. (e) Cellular fractionation was performed in C8orf4-deficient sphere and WT sphere cells followed by immunoblotting. (f) C8orf4-deficient Huh7 cells were implanted into BALB/c nude mice. Xenograft tumors were analyzed by immunohistochemical staining. Red arrowheads denote nuclear translocation of N2ICD. (g) C8orf4-overexpressing Huh7 cells were permeabilized for immunofluorescence staining. (h) Cellular fractionation was performed in C8orf4-overexpressing Huh7 cells for immunoblotting. (i,j) C8orf4 was overexpressed in N2ICD-overexpressing Huh7 cells followed by immunofluorescence staining (i) and immunoblotting (j). (k) NOTCH target genes were measured in cells treated as in i by real-time PCR. Scale bars: a,c,d,g,i, 10 μm; f, 40 μm. Student’s t-test was used for statistical analysis, **P<0.01;***P<0.001, data are shown as mean±s.d.. Data represent at least three independent experiments.
To further determine whether C8orf4 inhibits the NOTCH2 signaling in the propagation of xenograft tumors, we examined the distribution of N2ICD and NOTCH2 target gene activation inC8orf4-deficient xenograft tumor tissues. We found that C8orf4-deficient tumors displayed much more nuclear translocation of N2ICD compared with WT tumors (Fig. 5f). Expectedly, C8orf4-deficient tumors showed elevated expression levels of NOTCH2 target genes such as HEY1, HES6 and NRARP (Supplementary Fig. 5e). Furthermore, C8orf4 overexpression blocked the nuclear translocation of N2ICD (Fig. 5g,h). Consequently, C8orf4-overexpressing tumors showed much less N2ICD nuclear translocation and reduced expression levels of NOTCH2 target genes compared with control tumors (Supplementary Fig. 5f,g). Of note, C8orf4 overexpression in N2ICD-overexpressing Huh7 cells still blocked nuclear translocation of N2ICD (Fig. 5i,j). Consequently, C8orf4 overexpression abolished the activation of Notch2 signaling (Fig. 5k). These results suggest that C8orf4 deletion causes the nuclear translocation of N2ICD leading to activation of NOTCH2 signaling.
NOTCH2 signalling is required for the stemness of liver CSCs
To further verify the role of NRARP and HEY1 in the maintenance of liver CSC self-renewal, we knocked down these two genes in Huh7 cells and established stably depleted cell lines by two pairs of shRNAs. As expected, NRARP knockdown dramatically reduced sphere formation (Fig. 6a,b). NRARP knockdown also attenuated tumor-initiating capacity and liver CSC ratios (Fig. 6c). Similar results were achieved in NRARP-silenced HCC primary cells (Fig. 6d,e). Similarly, HEY1 silencing remarkably reduced sphere formation derived from Huh7 and HCC primary cells (Fig. 6f–i), as well as declined xenograft tumor growth and tumor-initiating capacity (Supplementary Fig. 6a,b). In sum, NOTCH2 signaling is required for the maintenance of liver CSC self-renewal.
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Figure 6: Depletion of NRARP and HEY1 impairs stemness of liver CSCs.
(a,b) NRARP-silenced Huh7 cells were established (a) and showed reduced sphere formation capacity (b). Two pairs of shRNAs against NRARP obtained similar results. (c) NRARP-silenced Huh7 cells decline tumour-initiating capacity (left panel) and reduce liver CSC frequency (right panel). Error bars represent the 95% confidence intervals of the estimation. (d,e) NRARP was knocked down in HCC primary cells (d) and sphere formation was detected (e). Three HCC samples were tested with similar results. (f,g) HEY1-silenced Huh7 cells were established (f) and sphere formation was assayed (g). Two pairs of shRNAs against HEY1 obtained similar results. (h,i) HEY1 was knocked down in HCC primary cells (h) and HEY1 depletion impaired sphere formation capacity (i). Three HCC samples were tested with similar results. Scale bars: b,e,g,i, 500 μm. For a,b,d–i, Student’s t-test was used for statistical analysis, *P<0.05; **P<0.01; ***P<0.001, data are shown as mean ± standard deviation. Data are representative of at least three independent experiments.
NOTCH2 signaling is correlated with HCC severity
As shown above, the NOTCH2 signaling was highly activated in liver CSCs and involved in the regulation of liver CSC stemness. We further examined the relationship of NOTCH2 signaling with the progression of HCC. First, we analyzed NOTCH2 activation levels in HCC tumor tissues and peri-tumor tissues derived from Park’s cohort (GSE36376). We observed that HEY1, HES6 and NRARP were highly expressed in the tumor tissues of HCC patients (Fig. 7a). Consistently, high expression levels of HEY1, HES6 and NRARP in HCC tumors were validated by Zhang’s cohort (GSE25097) (Fig. 7b). Importantly, high expression of these three genes was confirmed in HCC samples through quantitative RT–PCR (Fig. 7c), as well as immunoblotting (Fig. 7d). To confirm a causative link between low C8orf4 expression level and nuclear N2ICD, we examined 93 HCC samples (31 peri-tumor, 37 early stage of HCC patients and 25 advanced stage of HCC patients) with immunohistochemistry staining. We observed that nuclear staining of N2ICD appeared in ~10% tumor cells in the majority of early HCC patients we tested (Fig. 7e,f). In advanced HCC patients, nuclear staining of N2ICD in tumor cells increased to ~30% in almost all the advanced HCC patients we examined. Consequently, HEY1 staining existed in ~10% tumor cells with scattered distribution and increased to 30% tumor cells in the advanced HCC patients (Fig. 7e). Consistently, low expression of C8orf4 was well correlated with activation of NOTCH2 signaling (Fig. 7e,f).
NOTCH2 activation levels are consistent with clinical severity and prognosis of HCC patients
Figure 7: NOTCH2 activation levels are consistent with clinical severity and prognosis of HCC patients.
(a,b) NOTCH target genes were highly expressed in HCC tumour tissues derived from Park’s cohort (a) and Zhang’s cohort (b). (c) High expression levels of NOTCH target genes in HCC tumor tissues were verified by qRT–PCR. (d) HEY1 expression in HCC tumor tissues was detected by western blot. (e) IHC staining for N2ICD, C8orf4 and HEY1. These images represent 93 HCC samples. Scale bars, 50 μm. (f) IHC images were calculated using Image-Pro Plus 6. (g) Expression levels of NOTCH target genes were elevated in HCC tumors and advanced HCC patients derived from Wang’s cohort. (h) HEY1 expression level was positively correlated with prognosis prediction of HCC patients analyzed by Petel’s cohort and Wang’s cohort. HCC samples were divided into two groups according to HEY1 expression levels followed by Kaplan–Meier survival analysis. For a–c, data are shown as box and whisker plot, Box: interquartile range (IQR); horizontal line within box: median; whiskers: 5–95 percentile. For f,g, Student’s t-test was used for statistical analysis, *P<0.05; **P<0.01; ***P<0.001; data are shown as mean ± standard deviation. Experiments were repeated at least three times. aHCC, advanced HCC; CL, cirrhosis liver; eHCC, early HCC; IL, inflammatory liver; NL, normal liver; NS, not significant.
Serial passages of colonies or sphere formation in vitro, as well as transplantation of tumor cells, are frequently used to assess the long-term self-renewal capacities of CSCs32. We used HCC primary cells for serial passage growth in vitro and tested the expression levels of C8orf4, HEY1 and SOX9. We found that C8orf4 expression was gradually reduced over serial passages in oncosphere cells (Supplementary Fig. 7a). Consequently, the expression of NOTCH2 targets such as HEY1 and SOX9 was gradually increased in oncosphere cells during serial passages (Supplementary Fig. 7b). In addition, N2ICD nuclear translocation appeared in oncosphere cells with high expression of HEY1 plus low expression of C8orf4 (termed as C8orf4−/N2ICDnuc/HEY1+cells) (Supplementary Fig. 7c). These data suggest that the C8orf4−/N2ICDnuc/HEY1+ fraction cells represent a subset of liver CSCs.
Through analyzing Wang’s cohort (GSE54238), we noticed that the NOTCH2 activation levels were positively correlated with the development and progression of HCC (Fig. 7g). By contrast, the NOTCH2 pathway was not activated in inflammation liver, cirrhosis liver and normal liver (Fig. 7f). Consistently, similar observations were achieved by analysis of Zhang’s cohort (GSE25097) (Supplementary Fig. 7d). In addition, the NOTCH2 activation levels were consistent with clinicopathological stages of HCC patients derived from Wang’s cohort (GSE14520) (Supplementary Fig. 7e). Finally, HCC patients with higher expression of HEY1 displayed worse prognosis derived from Petel’s cohort (E-TABM-36) and Wang’s cohort (GSE14520) (Fig. 7h). These two cohorts (E-TABM-36 and GSE14520) have survival information of HCC patients. Taken together, the NOTCH2 activation levels in tumor tissues are consistent with clinical severity and prognosis of HCC patients.
Discussion
CSC have been identified in many solid tumors, including breast, lung, brain, liver, colon, prostate and bladder cancers4, 6, 33. CSCs have similar characteristics associated with normal tissue stem cells, including self-renewal, differentiation and the ability to form new tumors. CSCs may be responsible for cancer relapse and metastasis due to their invasive and drug-resistant capacities34. Thus, targeting CSCs may become a promising therapeutic strategy to deadly malignancies35, 36. However, it remains largely unknown about hepatic CSC biology. In this study, we used CD13 and CD133 to enrich CD13+CD133+
subpopulation cells as liver CSCs. Based on analysis of several online-available HCC transcriptome datasets, we found that C8orf4 is weakly expressed in HCC tumors as well as in CD13+CD133+ liver CSCs. NOTCH2 signaling is required for the maintenance of liver CSC self-renewal. C8orf4 resides in the cytoplasm of tumor cells and interacts with N2ICD, blocking the nuclear translocation of N2ICD. Lower expression of C8orf4 causes nuclear translocation of N2ICD that activates NOTCH2 signaling in liver CSCs. NOTCH2 activation levels are consistent with clinical severity and prognosis of HCC patients. Therefore, C8orf4 negatively regulates self-renewal of liver CSCs via suppression of NOTCH2 signaling.
Elucidating signaling pathways that maintains self-renewal of liver CSCs is pivotal for the understanding of hepatic CSC biology and the development of novel therapies against HCC. Several signaling pathways, such as Wnt/β-catenin, transforming growth factor-beta, AKT and STAT3 pathways, have been defined to be implicated in the regulation of liver CSCs37. Not surprisingly, some liver CSC subsets and normal tissue stem cells may share core regulatory genes and common signaling pathways. The NOTCH signaling pathway plays an important role in development via cell-fate determination, proliferation and cell survival38, 39. The NOTCH family receptors contain four members in mammals (NOTCH1–4), which are activated by binding to their corresponding ligands. A large body of evidence provides that NOTCH signaling is implicated in carcinogenesis40. However, the role of NOTCH signaling in liver cancer is controversial. A previous study reported that NOTCH1 signaling suppresses tumor growth of HCC41. Recently, several reports showed that NOTCH signaling enhances liver tumor initiation42, 43, 44. Importantly, a recent study showed that various NOTCH receptors have differential functions in the development of liver cancer45. Here we demonstrate that NOTCH2 signaling is activated in HCC tumor tissues and liver CSCs, which is required for the maintenance of liver CSC self-renewal.
C8orf4, also known as TC1, was originally cloned from a papillary thyroid cancer16, 46. The copy number variations of C8orf4 are associated with acute myeloid leukemia and other hematological malignancies19, 47. C8orf4 has been reported to be implicated in various cancers. C8orf4 was highly expressed in thyroid cancer, gastric cancer and breast cancer16, 20, 46. C8orf4 has been reported to enhance Wnt/β-catenin signaling in cancer cells that is associated with poor prognosis20, 21. However, C8orf4 is downregulated in colon cancer48. In this study, we show that C8orf4 is weakly expressed in HCC tumor tissues and liver CSCs. Our observations were confirmed by two HCC cohort datasets. Importantly, C8orf4 negatively regulates the NOTCH2 signaling to suppress the self-renewal of liver CSCs. Therefore, C8orf4 may exert distinct functions in the regulation of various malignancies.
NOTCH receptors consist of noncovalently bound extracellular and transmembrane domains. Once binding with membrane-bound Delta or Jagged ligands, the NOTCH receptors undergoes a proteolytic step by metalloprotease and γ-secretase, generating NECD and NICD fragments11, 31. The NICD, a soluble fragment, is released in the cytoplasm on proteolysis. Then the NICD translocates to the nucleus and binds to the transcription initiation complex, leading to activation of NOTCH-associated target genes49. However, it is largely unclear how the NICD is regulated during NOTCH signaling activation. Here we show that N2ICD binds to C8orf4 in the cytoplasm of liver non-CSC tumor cells, which impedes the nuclear translocation of N2ICD. By contrast, in liver CSCs, lower expression of C8orf4 causes the nuclear translocation of N2ICD, leading to activation of NOTCH signaling.
CSCs or tumour-initiating cells, behave like tissue stem cells in that they are capable of self-renewal and of giving rise to hierarchical organization of heterogeneous cancer cells4. Thus, CSCs harbour the stem cell properties of self-renewal and differentiation. Actually, the CSC model cannot account for tumorigenesis in all tumours. CSCs could undergo genetic evolution, and the non-CSCs might switch to CSC-like cells4. These results highlight the dynamic nature of CSCs, suggesting that the clonal evolution and CSC models can act in concert for tumorigenesis. Furthermore, low C8orf4 expression in tumor cells results in overall Notch2 activation, which then may have more of a progenitor signature and be more aggressive. These cells would likely have a growth advantage in non-adherent conditions and express many of the stemness markers. The dynamic nature of CSCs or persistent NOTCH2 activation may contribute to the high number of C8orf4−/N2ICDnuc/HEY1+ cells in advanced HCC tumors and correlation in the patient cohort.
A recent study showed that NOTCH2 and its ligand Jag1 are highly expressed in human HCC tumors, suggesting activation of NOTCH2 signaling in HCC45. In addition, inhibiting NOTCH2 or Jag1 dramatically reduces tumor burden and growth. However, suppression of NOTCH3 has no effect on tumor growth. Dill et al.43 reported that Notch2 is an oncogene in HCC. Notch2-driven HCC are poorly differentiated with a high expression level of the progenitor marker Sox9, indicating a critical role of Notch2 signaling in liver CSCs. Here we found that NOTCH2 and its target genes such as NRARP, HEY1 and HES6 are highly expressed in HCC samples. In addition, depletion of NRARP and HEY1 impairs the stemness maintenance of liver CSCs and tumor propagation. Moreover, the expression levels of NRARP, HEY1 and HES6 in tumors are positively correlated with clinical severity and prognosis of HCC patients. Finally, the NOTCH2 activation status is positively related to the clinicopathological stages of HCC patients. Altogether, C8orf4 and NOTCH2 signaling can be detected for the diagnosis and prognosis prediction of HCC patients, as well as used as targets for eradicating liver CSCs for future therapy.
11.2.3.2 Quantifying the Landscape for Development and Cancer from a Core Cancer Stem Cell Circuit
The authors developed a landscape and path theoretical framework to investigate the global natures and dynamics for a core cancer stem cell gene network. The landscape exhibits four basins of attraction, representing cancer stem cell, stem cell, cancer and normal cell states. They also uncovered certain key genes and regulations responsible for determining the switching between different states. [Cancer Res]
Cancer presents a serious threat to human health. The understanding of the cell fate determination during development and tumor genesis remains challenging in current cancer biology. It was suggested that cancer stem cell (CSC) may arise from normal stem cells, or be transformed from normal differentiated cells. This gives hints on the connection between cancer and development. However, the molecular mechanisms of these cell type transitions and the CSC formation remain elusive. We quantified landscape, dominant paths and switching rates between cell types from a core gene regulatory network for cancer and development. Stem cell, CSC, cancer, and normal cell types emerge as basins of attraction on associated landscape. The dominant paths quantify the transition processes among CSC, stem cell, normal cell and cancer cell attractors. Transition actions of the dominant paths are shown to be closely related to switching rates between cell types, but not always to the barriers in between, due to the presence of the curl flux. During the process of P53 gene activation, landscape topography changes gradually from a CSC attractor to a normal cell attractor. This confirms the roles of P53 of preventing the formation of CSC, through suppressing self-renewal and inducing differentiation. By global sensitivity analysis according to landscape topography and action, we identified key regulations determining cell type switchings and suggested testable predictions. From landscape view, the emergence of the CSCs and the associated switching to other cell types are the results of underlying interactions among cancer and developmental marker genes. This indicates that the cancer and development are intimately connected. This landscape and flux theoretical framework provides a quantitative way to understand the underlying mechanisms of CSC formation and interplay between cancer and development. Major Findings: We developed a landscape and path theoretical framework to investigate the global natures and dynamics for a core cancer stem cell gene network. Landscape exhibits four basins of attraction, representing CSC, stem cell, cancer and normal cell states. We quantified the kinetic rate and paths between different attractor states. We uncovered certain key genes and regulations responsible for determining the switching between different states.
11.2.3.3 IMP3 Promotes Stem-Like Properties in Triple-Negative Breast Cancer by Regulating SLUG
Scientists observed that insulin-like growth factor-2 mRNA binding protein 3 (IMP3) expression is significantly higher in tumor initiating than in non-tumor initiating breast cancer cells and demonstrated that IMP3 contributes to self-renewal and tumor initiation, properties associated with cancer stem cells. [Oncogene]
IMP3 (insulin-like growth factor-2 mRNA binding protein 3) is an oncofetal protein whose expression is prognostic for poor outcome in several cancers. Although IMP3 is expressed preferentially in triple-negative breast cancer (TNBC), its function is poorly understood. We observed that IMP3 expression is significantly higher in tumor initiating than in non-tumor initiating breast cancer cells and we demonstrate that IMP3 contributes to self-renewal and tumor initiation, properties associated with cancer stem cells (CSCs). The mechanism by which IMP3 contributes to this phenotype involves its ability to induce the stem cell factor SOX2. IMP3 does not interact with SOX2 mRNA significantly or regulate SOX2 expression directly. We discovered that IMP3 binds avidly to SNAI2 (SLUG) mRNA and regulates its expression by binding to the 5′ UTR. This finding is significant because SLUG has been implicated in breast CSCs and TNBC. Moreover, we show that SOX2 is a transcriptional target of SLUG. These data establish a novel mechanism of breast tumor initiation involving IMP3 and they provide a rationale for its association with aggressive disease and poor outcome.
11.2.3.4 Type II Transglutaminase Stimulates Epidermal Cancer Stem Cell Epithelial-Mesenchymal Transition
Researchers investigated the role of type II transglutaminase (TG2) in regulating epithelial mesenchymal transition (EMT) in epidermal cancer stem cells. They showed that TG2 knockdown or treatment with TG2 inhibitor, resulted in a reduced EMT marker expression, and reduced cell migration and invasion. [Oncotarget]
ML Fisher, G Adhikary, W Xu, C Kerr, JW Keillor, RL Ecker
Oncotarget May 08, 2015;
Type II transglutaminase (TG2) is a multifunctional protein that has recently been implicated as having a role in ECS cell survival. In the present study we investigate the role of TG2 in regulating epithelial mesenchymal transition (EMT) in ECS cells. Our studies show that TG2 knockdown or treatment with TG2 inhibitor, results in a reduced EMT marker expression, and reduced cell migration and invasion. TG2 has several activities, but the most prominent are its transamidase and GTP binding activity. Analysis of a series of TG2 mutants reveals that TG2 GTP binding activity, but not the transamidase activity, is required for expression of EMT markers (Twist, Snail, Slug, vimentin, fibronectin, N-cadherin and HIF-1α), and increased ECS cell invasion and migration. This coupled with reduced expression of E-cadherin. Additional studies indicate that NFϰB signaling, which has been implicated as mediating TG2 impact on EMT in breast cancer cells, is not involved in TG2 regulation of EMT in skin cancer. These studies suggest that TG2 is required for maintenance of ECS cell EMT, invasion and migration, and suggests that inhibiting TG2 GTP binding/G-protein related activity may reduce skin cancer tumor survival.
Epidermal squamous cell carcinoma (SCC) is among the most common cancers and the frequency is increasing at a rapid rate [1,2]. SCC is treated by surgical excision, but the rate of recurrence approaches 10% and the recurrent tumors are aggressive and difficult to treat [2]. We propose that human epidermal cancer stem (ECS) cells survive at the site of tumor excision, that these cells give rise to tumor regrowth, and that therapies targeted to kill ECS cells constitute a viable anti-cancer strategy. An important goal in this context is identifying and inhibiting activity of key proteins that are essential for ECS cell survival. Working towards this goal, we have developed systems for propagation of human ECS cells [3]. These cells display properties of cancer stem cells including self-renew and high level expression of stem cell marker proteins [3].
In the present study we demonstrate that ECS cells express proteins characteristic of cells undergoing EMT (epithelial-mesenchymal transition). EMT is a morphogenetic process whereby epithelial cells lose epithelial properties and assume mesenchymal characteristics [4]. The epithelial cells lose cell-cell contact and polarity, and assume a mesenchymal migratory phenotype. There are three types of EMT. This first is an embryonic process, during gastrulation, when the epithelial sheet gives rise to the mesoderm [5]. The second is a growth factor and cytokine-stimulated EMT that occurs at sites of tissue injury to facilitate wound repair [6]. The third is associated with epithelial cancer cell acquisition of a mesenchymal migratory/invasive phenotype. This process mimics normal EMT, but is not as well controlled and coordinated [4, 7, 8]. A number of transcription factors (ZEB1, ZEB2, snail, slug, and twist) that are expressed during EMT suppress expression of epithelial makers, including E-cadherin, desmoplakin and claudins [4]. Snail proteins also activate expression of vimentin, fibronectin and metalloproteinases [4]. Snail factors are not present in normal epithelial cells, but are present in the tumor cells and are prognostic factors for poor survival [4].
An important goal is identifying factors that provide overarching control of EMT in cancer stem cells. In this context, several recent papers implicate type II transglutaminase (TG2) as a regulator of EMT [9–12]. TG2, the best studied transglutaminase, was isolated in 1957 from guinea pig liver extract as an enzyme involved in the covalent crosslinks proteins via formation of isopeptide bonds [13]. However, subsequent studies reveal that TG2 also serves as a scaffolding protein, regulates cell adhesion, and modulates signal transduction as a GTP binding protein that participates in G protein signaling [14]. TG2 is markedly overexpressed in cancer cells, is involved in cancer development [15–18], and has been implicated in maintaining and enhancing EMT in breast and ovarian cancer [10, 12, 19, 20]. The G protein function may have an important role in these processes [10, 21–23].
In the present manuscript we study the role of TG2 in regulating EMT in human ECS cells. Our studies show that TG2 is highly enriched in ECS cells. We further show that these cells express EMT markers and that TG2 is required to maintain EMT protein expression. TG2 knockdown, or treatment with TG2 inhibitor, reduces EMT marker expression and ECS cell survival, invasion and migration. TG2 GTP binding activity is absolutely required for maintenance of EMT protein expression and EMT-related responses. However, in contrast to breast cancer [9, 10], we show that TG2 regulation of EMT is not mediated via NFκB signaling.
TG2 is required for expression of EMT markers
EMT is a property of tumor stem cells that confers an ability to migrate and invade surrounding tissue [24–26]. We first examined whether ECS cells express EMT markers. Non-stem cancer cells and ECS cells, derived from the SCC-13 cancer cell line, were analyzed for expression of EMT markers. Fig. 1A shows that a host of EMT transcriptional regulators, including Twist, Snail and Slug, are increased in ECS cells (spheroid) as compared to non-stem cancer cells (monolayer). This is associated with increased levels of vimentin, fibronectin and N-cadherin, which are mesenchymal proteins, and reduced expression of E-cadherin, an epithelial marker. HIF-1α, an additional marker frequently associated with EMT, is also elevated. We next examined whether TG2 is required to maintain EMT marker expression. SCC-13 cell-derived ECS cells were grown in the presence of control- or TG2-siRNA, to reduce TG2, and the impact on EMT marker level was measured. Fig. 1B shows that loss of TG2 is associated with reduced expression of Twist, Snail, vimentin and HIF-1α. To further assess the role of TG2, we utilized SCC13-Control-shRNA and SCC13-TG2-shRNA2 cell lines. These lines were produced by infection of SCC-13 cells with lentiviruses encoding control- or TG2-specific shRNA. Fig. 1C shows that SCC13-TG2-shRNA2 cells express markedly reduced levels of TG2 and that this is associated with reduced expression of EMT associated transcription factors and target proteins, and increased expression of E-cadherin. To confirm this, we grew SCC13-Control-shRNA and SCC13-TG2-shRNA2 cells as monolayer cultures for immunostain detection of EMT markers. As shown in Fig. 2A, TG2 levels are reduced in TG2-shRNA expressing cells, and this is associated with the anticipated changes in epithelial and mesenchymal marker expression.
Tumor cells that express EMT markers display enhanced migration and invasion ability [24–26]. We therefore examined the impact of TG2 reduction on these responses. To measure invasion, control-shRNA and TG2-shRNA cells were monitored for ability to move through matrigel. Fig. 2B shows that loss of TG2 reduces movement through matrigel by 50%. We further show that this is associated with a reduction in cell migration using a monolayer culture wound closure assay. The control cells close the wound completely within 14 h, while TG2 knockdown reduces closure rate (Fig. 2C).
TG2 inhibitor reduces EMT marker expression and EMT functional responses
NC9 is a recently developed TG2-specific inhibitor [27, 28]. We therefore asked whether pharmacologic inhibition of TG2 suppresses EMT. SCC-13 cells were treated with 0 or 20 μM NC9. Fig. 3A shows that NC9 treatment reduces EMT transcription factor (Twist, Snail, Slug) and EMT marker (vimentin, fibronectin, N-cadherin, HIF-1α) levels. Consistent with these changes, the level of the epithelial marker, E-cadherin, is elevated. Fig. 3B and 3C show that pharmacologic inhibition of TG2 activity also reduces EMT biological response. Invasion (Fig. 3B) and cell migration (Fig. 3C) are also reduced.
Identification of TG2 functional domain required for EMT
We next performed studies to identify the functional domains and activities required for TG2 regulation of EMT. TG2 is a multifunctional enzyme that serves as a scaffolding protein, as a transamidase, as a kinase, and as a GTP binding protein [21]. The two best studied functions are the transamidase and GTP binding/G-protein related activities [21]. Transamidase activity is observed in the presence of elevated intracellular calcium, while GTP binding-related signaling is favored by low calcium conditions (reviewed in [21]). To identify the TG2 activity required for EMT, we measured the ability of wild-type and mutant TG2 to restore EMT in SCC13-TG2-shRNA2 cells, which have reduced TG2 expression (Fig. 4A). SCC13-TG2-shRNA2 cells display reduced expression of EMT markers including Twist, Snail, Slug, vimentin, fibronectin, N-cadherin and HIF-1α, and increased expression of the epithelial maker, E-cadherin, as compared to SCC13-Control-shRNA cells. Expression of wild-type TG2, or the TG2-C277S or TG2-W241A mutants, restores marker expression in SCC13-TG2-shRNA2 cells (Fig. 4A). TG2-C277S and TG2-W241A lack transamidase activity [10,29–31]. In contrast, TG2-R580A, which lacks G-protein activity [29–31], and TG2-Y516F, which retains only partial G-protein activity [30], do not efficiently restore marker expression. These findings suggest that the TG2 GTP binding function is required for EMT.
We next assayed the ability of the TG2 mutants to restore EMT functional responses-invasion and migration. Fig. 4B, 4C shows that wild-type TG2, TG2-C277S and TG2-W241A restore the ability of SCC13-TG2-shRNA2 cells to invade matrigel, but TG2-R580A and Y516F are less active. Fig. 4D shows a similar finding for cell migration, in that the TG2-R580A and Y517F mutant are only partially able to restore SCC13-TG2-shRNA2 cell migration. These findings suggest that TG2 GTP binding/G-protein related activity is required for EMT-related migration and invasion by skin cancer cells.
Role of TG2 in regulating EMT in A431 cells
The number of available epidermis-derived squamous cell carcinoma cell lines is limited, and so we compared our findings with A431 cells. A431 cells are squamous cell carcinoma cells established from human vulvar skin. A431 cells were grown as monolayer (non-stem cancer cells) and spheroids (ECS cells) and after 10 d the cells were harvested and assayed for expression of TG2 and EMT makers. Fig. 5A shows that TG2 levels are elevated in ECS cells and that this is associated with increased levels of mesenchymal markers, including Twist, Snail, Slug, vimentin, fibronectin, N-cadherin and HIF-1α. In contrast, E-cadherin levels are reduced. We next examined the impact of TG2 knockdown on EMT marker expression. Fig. 5B shows that mesenchymal markers are globally reduced and E-cadherin level is increased. As a biological endpoint of EMT, we examine the impact of TG2 knockdown on spheroid formation and found that TG2 loss leads to reduced spheroid formation (Fig. 5C). We next examined the impact of NC9 treatment on EMT and found a reduction in EMT markers expression associated with an increase in epithelial (E-cadherin) marker level (Fig. 5D). This loss of EMT marker expression is associated with reduced matrigel invasion (Fig. 5E), reduced spheroid formation (Fig. 5F) and reduced cell migration (Fig. 5G).
Role of NFκB
Previous studies in breast [18, 32–36], ovarian cancer [12, 37, 38], and epidermoid carcinoma [11] indicate that NFκB signaling mediates TG2 impact on EMT. We therefore assessed the role of NFκB in skin cancer cells. As shown in Fig. 6A, the increase in TG2 level observed in ECS cells (spheroids) is associated with reduced NFκB level. In addition, NFκB level is increased in TG2 knockdown cells (Fig. 6B). Thus, increased NFκB is not associated with increased TG2. We next assessed the impact of NFκB knockdown on TG2 control of EMT marker expression. Fig. 6C shows that TG2 is required for increased expression of EMT markers (HIF-1α, snail, twist, N-cadherin, vimentin and fibronectin) and reduced expression of the E-cadherin epithelial marker; however, knockdown of NFκB expression does not interfere with TG2 regulation of these endpoints. We next examined the effect of TG2 knockdown on NFκB and IκBα localization. The fluorescence images in Fig. 6D suggest that TG2 knockdown with TG2-siRNA does not alter the intracellular localization of NFκB or IκBα. This is confirmed by subcellular fractionation assay (Fig. 6E) which compares NFκB level in SCC13-TG2-Control and SCC13-TG2-shRNA2 (TG2 knockdown) cells. We also monitored NFκB subcellular distribution following treatment with NC9, the TG2 inhibitor. Fig. 6F shows that cytoplasmic/nuclear distribution of NFκB is not altered by NC9. Finally, we monitored the impact of TG2 expression on NFκB binding to a canonical NFκB-response element. Increased NFκB binding to the response element is a direct measure of NFκB activity [10]. Fig. 6G shows that overall binding is reduced in nuclear (N) extract prepared from ECS cells (spheroids) as compared to non-stem cancer cells (monolayer), and that NFkB binding, as indicated by gel supershift assay, is also slightly reduced in ECS cell extracts. These findings indicate that NFkB binding is slightly reduced in ECS cells, which are TG2-enriched (Fig. 1A).
We next monitored the role of NFκB on biological endpoints of EMT. Fig. 7A and 7B show that TG2 knockdown reduces migration through matrigel, but NFκB knockdown has no impact. Likewise, TG2 knockdown reduces wound closure, but NFκB knockdown does not. These findings suggest that NFκB does not mediate the pro-EMT actions of TG2 in epidermal squamous cell carcinoma.
The metastatic cascade, from primary tumor to metastasis, is a complex process involving multiple pathways and signaling cascades [39–41]. Cells that complete the metastatic cascade migrate away from the primary tumor through the blood to a distant site and there form a secondary tumor. Identifying the mechanisms that allow cells to survive this journey and form secondary tumors is an important goal. The processes involved in epithelial-mesenchymal transition (EMT) are important cancer therapy targets, as EMT is associated with enhanced cancer cell migration and stem cell self-renewal. EMT regulators, including Snail, Twist, Slug, are increased in expression in EMT and control expression of genes associated with the EMT phenotype [42].
TG2 is required for EMT
We have characterized a population of ECS cells derived from epidermal squamous cell carcinoma [3]. The present studies show that these cells, which display enhanced migration and invasion, possess elevated levels of TG2. Moreover, these cells are enriched in expression of transcription factors associated with EMT (Snail, Slug, and Twist, HIF-1α) as well as mesenchymal structural proteins including vimentin, fibronectin and N-cadherin. Consistent with a shift to mesenchymal phenotype, E-cadherin, an epithelial marker, is reduced in level. Additional studies show that TG2 knockdown results in a marked reduction in EMT marker expression and that this is associated with reduced ability of the cells to migrate to close a scratch wound and reduced movement in matrigel invasion assays. We also examined the impact of treatment with a TG2 inhibitor. NC9 is an irreversible active site inhibitor of TG2, that locks the enzyme in an open conformation [28, 43–45]. NC9 treatment of ECS cells results in decreased levels of Snail, Slug and Twist. These transcription factors suppress E-cadherin expression [46] and their decline in level is associated with increased levels of E-cadherin. NC9 inhibition of TG2 also reduces expression of vimentin, fibronectin and N-cadherin, and these changes are associated with reduced cell migration and reduced invasion through matrigel.
(Figures are not shown)
We also examined the role of TG2 in A431 squamous cell carcinoma cells derived from the vulva epithelium. TG2 is elevated in A431-derived ECS cells, as are EMT markers, and knockdown of TG2, with TG2-siRNA, reduces EMT marker expression and spheroid formation. Studies with NC9 indicate that NC9 inhibits A431 spheroid formation, EMT, migration and invasion. These studies indicate that TG2 is also required for EMT and migration and invasion in A431 cells. Based on these findings we conclude that TG2 is essential for EMT, migration and invasion, and is likely to contribute to metastasis in squamous cell carcinoma.
TG2 GTP binding activity is required for EMT
TG2 is a multifunctional enzyme that can act as a transamidase, GTP binding protein, protein disulfide isomerase, protein kinase, protein scaffold, and DNA hydrolase [21, 29, 44, 47]. The two most studied functions are the transamidase and GTP binding functions [29, 44, 47]. To identify the TG2 activity responsible for induction of EMT, we studied the ability of TG2 mutants to restore EMT in SCC13-TG2-shRNA2 cells, which express low levels of TG2 and do not express elevated levels of EMT markers or display EMT-related biological responses. These studies show that wild-type TG2 restores EMT marker expression and the ability of the cells to migrate on plastic and invade matrigel. TG2 mutants that retain GTP binding activity (TG2-C277S and TG2-W241A) also restore EMT. In contrast, TG2-R580A, which lacks GTP binding function, does not restore EMT. This evidence suggests that the GTP binding function is essential for TG2 induction of the EMT phenotype in ECS cells. Recent reports suggest that the TG2 is important for maintenance of stem cell survival in breast [9, 10, 17] and ovarian [12, 38, 48] cancer cells. Moreover, our findings are in agreement of those of Mehta and colleagues who reported that the TG2 GTP binding function, but not the crosslinking function, is required for TG2 induction of EMT in breast cancer cells [10].
TG2, NFκB signaling and EMT
To gain further insight into the mechanism of TG2 mediated EMT, we examined the role of NFκB. NFκB has been implicated as mediating EMT in breast, ovarian, and pancreatic cancer; however, NFκB may have a unique role in epidermal squamous cell carcinoma. In keratinocytes, NFκB has been implicated in keratinocyte dysplasia and hyperproliferation [49]. However, inhibition of NFκB function has also been shown to predispose murine epidermis to cancer [50]. Here we show that TG2 levels are elevated and NFκB levels are reduced in ECS cells as compared to non-stem cancer cells, and that TG2 knockdown is associated with increased NFκB level. In addition, TG2 knockdown, or inhibition of TG2 by treatment with NC9, does not altered the nuclear/cytoplasmic distribution of NFκB. We further show that elevated levels of TG2 in spheroid culture results in a slight reduction in NFκB binding to the NFκB response element, as measured by gel mobility supershift assay. These molecular assays strongly suggest that NFκB does not mediate the action of TG2 in epidermal cancer stem cells. Moreover, knockdown of NFκB-p65 in TG2 positive cells does not result in a reduction in Snail, Slug and Twist, or mesenchymal marker proteins expression, and concurrent knockdown of TG2 and NFκB does not reduce EMT marker protein levels beyond that of TG2 knockdown alone. These findings suggest that NFκB is not an intermediary in TG2-stimulated EMT in ECS cells. This is in contrast to the required role of NFκB in mediating TG2 induction of cell survival and EMT in breast cancer cells [18, 32, 33] and ovarian cancer [12, 37, 38] and epidermoid carcinoma [11].
11.2.3.5 CD24+ Ovarian Cancer Cells are Enriched for Cancer Initiating Cells and Dependent on JAK2 Signaling for Growth and Metastasis
Investigators showed that CD24+ and CD133+ cells have increased tumorsphere forming capacity. CD133+ cells demonstrated a trend for increased tumor initiation while CD24+ cells vs CD24– cells, had significantly greater tumor initiation and tumor growth capacity. [Mol Cancer Ther]
D Burgos-Ojeda, R Wu, K McLean, Yu-Chih Chen, M Talpaz, et al.
Molec Cancer Ther May 12, 2015; 14(5) http://dx.doi.org:/10.1158/1535-7163.MCT-14-0607 Ovarian cancer is known to be composed of distinct populations of cancer cells, some of which demonstrate increased capacity for cancer initiation and/or metastasis. The study of human cancer cell populations is difficult due to long requirements for tumor growth, inter-patient variability and the need for tumor growth in immune-deficient mice. We therefore characterized the cancer initiation capacity of distinct cancer cell populations in a transgenic murine model of ovarian cancer. In this model, conditional deletion of Apc, Pten, and Trp53 in the ovarian surface epithelium (OSE) results in the generation of high grade metastatic ovarian carcinomas. Cell lines derived from these murine tumors express numerous putative stem cell markers including CD24, CD44, CD90, CD117, CD133 and ALDH. We show that CD24+ and CD133+ cells have increased tumor sphere forming capacity. CD133+ cells demonstrated a trend for increased tumor initiation while CD24+ cells vs CD24- cells, had significantly greater tumor initiation and tumor growth capacity. No preferential tumor initiating or growth capacity was observed for CD44+, CD90+, CD117+, or ALDH+ versus their negative counterparts. We have found that CD24+ cells, compared to CD24- cells, have increased phosphorylation of STAT3 and increased expression of STAT3 target Nanog and c-myc. JAK2 inhibition of STAT3 phosphorylation preferentially induced cytotoxicity in CD24+ cells. In vivo JAK2 inhibitor therapy dramatically reduced tumor metastases, and prolonged overall survival. These findings indicate that CD24+ cells play a role in tumor migration and metastasis and support JAK2 as a therapeutic target in ovarian cancer.
11.2.3.6 EpCAM-Antibody-Labeled Noncytotoxic Polymer Vesicles for Cancer Stem Cells-Targeted Delivery of Anticancer Drug and siRNA
Researchers designed and synthesized a novel anti-epithelial cell adhesion molecule (EpCAM)-monoclonal-antibody-labeled cancer stem cells (CSCs)-targeting, noncytotoxic and pH-sensitive block copolymer vesicle as a nano-carrier of anticancer drug and siRNA. [Biomacromolecules]
Cancer stem cells (CSCs) have the capability to initiate tumor, to sustain tumor growth, to maintain the heterogeneity of tumor, and are closely linked to the failure of chemotherapy due to their self-renewal and multilineage differentiation capability with an innate resistance to cytotoxic agents. Herein, we designed and synthesized a novel anti-EpCAM (epithelial cell adhesion molecule)-monoclonal-antibody-labeled CSCs-targeting, noncytotoxic and pH-sensitive block copolymer vesicle as a nano-carrier of anticancer drug and siRNA (to overcome CSCs drug resistance by silencing the expression of oncogenes). This vesicle shows high delivery efficacy of both anticancer drug doxorubicin hydrochloride (DOX∙HCl) and siRNA to the CSCs because it is labeled by the monoclonal antibodies to the CSCs-surface-specific marker. Compared to non-CSCs-targeting vesicles, the DOX∙HCl or siRNA loaded CSCs-targeting vesicles exhibited much better CSCs killing and tumor growth inhibition capabilities with lower toxicity to normal cells (IC50,DOX decreased by 80%), demonstrating promising potential applications in nanomedicine.
11.2.3.7 Survival of Skin Cancer Stem Cells Requires the Ezh2 Polycomb Group Protein
Investigators showed that Ezh2 is required for epidermal cancer stem (ECS) cell survival, migration, invasion and tumor formation, and that this is associated with increased histone H3 trimethylation on lysine 27, a mark of Ezh2 action. They also showed that Ezh2 knockdown or treatment with Ezh2 inhibitors, GSK126 or EPZ-6438, reduced Ezh2 level and activity, leading to reduced ECS cell spheroid formation, migration, invasion and tumor growth. [Carcinogenesis]
Polycomb group (PcG) proteins, including Ezh2, are important candidate stem cell maintenance proteins in epidermal squamous cell carcinoma. We previously showed that epidermal cancer stem cells (ECS cells) represent a minority of cells in tumors, are highly enriched in Ezh2 and drive aggressive tumor formation. We now show that Ezh2 is required for ECS cell survival, migration, invasion and tumor formation, and that this is associated with increased histone H3 trimethylation on lysine 27, a mark of Ezh2 action. We also show that Ezh2 knockdown or treatment with Ezh2 inhibitors, GSK126 or EPZ-6438, reduces Ezh2 level and activity, leading to reduced ECS cell spheroid formation, migration, invasion and tumor growth. These studies indicate that epidermal squamous cell carcinoma cells contain a subpopulation of cancer stem (tumor-initiating) cells that are enriched in Ezh2, that Ezh2 is required for optimal ECS cell survival and tumor formation, and that treatment with Ezh2 inhibitors may be a strategy for reducing epidermal cancer stem cell survival and suppressing tumor formation.
11.2.3.8 Inhibition of STAT3, FAK and Src mediated signaling reduces cancer stem cell load, tumorigenic potential and metastasis in breast cancer
Cancer stem cells (CSCs) are responsible for aggressive tumor growth, metastasis and therapy resistance. In this study, we evaluated the effects of Shikonin (Shk) on breast cancer and found its anti-CSC potential. Shk treatment decreased the expression of various epithelial to mesenchymal transition (EMT) and CSC associated markers. Kinase profiling array and western blot analysis indicated that Shk inhibits STAT3, FAK and Src activation. Inhibition of these signaling proteins using standard inhibitors revealed that STAT3 inhibition affected CSCs properties more significantly than FAK or Src inhibition. We observed a significant decrease in cell migration upon FAK and Src inhibition and decrease in invasion upon inhibition of STAT3, FAK and Src. Combined inhibition of STAT3 with Src or FAK reduced the mammosphere formation, migration and invasion more significantly than the individual inhibitions. These observations indicated that the anti-breast cancer properties of Shk are due to its potential to inhibit multiple signaling proteins. Shk also reduced the activation and expression of STAT3, FAK and Src in vivo and reduced tumorigenicity, growth and metastasis of 4T1 cells. Collectively, this study underscores the translational relevance of using a single inhibitor (Shk) for compromising multiple tumor-associated signaling pathways to check cancer metastasis and stem cell load.
Breast cancer is the most common endocrine cancer and the second leading cause of cancer-related deaths in women. In spite of the diverse therapeutic regimens available for breast cancer treatment, development of chemo-resistance and disease relapse is constantly on the rise. The most common cause of disease relapse and chemo-resistance is attributed to the presence of stem cell like cells (or CSCs) in tumor tissues1, 2. CSCs represent a small population within the tumor mass, capable of inducing independent tumors in vivo and are hard to eradicate2. Multiple signaling pathways including Receptor Tyrosine Kinase (RTKs), Wnt/β-catenin, TGF-β, STAT3, Integrin/FAK, Notch and Hedgehog signaling pathway helps in maintaining the stem cell programs in normal as well as in cancer cells3, 4, 5, 6. These pathways also support the epithelial-mesenchymal transition (EMT) and expression of various drug transporters in cancer cells. Cells undergoing EMT are known to acquire stem cell and chemo-resistant traits7. Thus, the induction of EMT programs, drug resistance and stem cell like properties are interlinked7. Commonly used anti-cancer drugs eradicate most of the tumor cells, but CSCs due to their robust survival mechanisms remain viable and lead to disease relapse8. Studies carried out on patient derived tumor samples and in vivo mouse models have demonstrated that the CSCs metastasize very efficiently than non-CSCs9, 10, 11. Therefore, drugs capable of compromising CSCs proliferation and self-renewal are urgently required as the inhibition of CSC will induce the inhibition of tumor growth, chemo-resistance, metastasis and metastatic colonization in breast cancer.
Shikonin, a natural dietary component is a potent anti-cancer compound12, 13. Previous studies have shown that Shk inhibits the cancer cell growth, migration, invasion and tumorigenic potential12. Shk has good bioavailability, less toxicity and favorable pharmacokinetic and pharmacodynamic profiles in vivo12. In a recent report, it was shown that the prolonged exposure of Shk to cancer cells does not cause chemo-resistance13.Other studies have shown that it inhibits the expression of various key inflammatory cytokines and associated signaling pathways12, 14. It decreases the expression of TNFα, IL12, IL6, IL1β, IL2, IFNγ, inhibits ERK1/2 and JNK signaling and reduces the expression of NFκB and STAT3 transcription factors14, 15. It inhibits proteasome and also modulates the cancer cell metabolism by inhibiting tumor specific pyurvate kinase-M214,15, 16. Skh causes cell cycle arrest and induces necroptosis in various cancer types14. Shk also inhibits the expression of MMP9, integrin β1 and decreases invasive potential of cancer cells14, 17. Collectively, Shk modulates various signaling pathways and elicits anti-cancer responses in a variety of cancer types.
In breast cancer, Shk has been reported to induce the cell death and inhibit cell migration, but the mechanisms responsible for its effect are not well studied18, 19. Signaling pathways modulated by Shk in cancerous and non-cancerous models have previously been shown important for breast cancer growth, metastasis and tumorigenicity20. Therefore in the current study, we investigated the effect of Shk on various hallmark associated properties of breast cancer cells, including migration, invasion, clonogenicity, cancer stem cell load and in vivo tumor growth and metastasis.
Shk inhibits cancer hallmarks in breast cancer cell lines and primary cells
We first examined the effect of Shk on various cancer hallmark capabilities (proliferation, invasion, migration, colony and mammosphere forming potential) in breast cancer cells. MTT assay was used to find out effect of Shk on viability of breast cancer cells. Semi-confluent cultures were exposed to various concentrations of Shk for 24 h. Shk showed specific anti-breast cancer activity with IC50 values ranging from 1.38 μM to 8.3 μM in MDA-MB 231, MDA-MB 468, BT-20, MCF7, T47D, SK-BR-3 and 4T1 cells (Fig. 1A). Whereas the IC50 values in non-cancerous HEK-293 and human PBMCs were significantly higher indicating that it is relatively safe for normal cells (Fig. S1A). Shk was found to induce necroptotic cell death consistent with previous reports (Fig. S1B). Treatment of breast cancer cells for 24 h with 1.25 μM, 2.5 μM and 5.0 μM of Shk significantly reduced their colony forming potential (Fig. 1B). To check the effect of Shk on the heterogeneous cancer cell population, we tested it on patient derived primary breast cancer cells. Shk reduced the viability and colony forming potential of primary breast cancer cells in dose dependent manner (Fig. 1C,D). Further we checked its effects on migration and invasion of breast cancer cells. Shk (2.5 μM) significantly inhibited the migration of MDA-MB 231, MDA-MB 468, MCF7 and 4T1 cells (Fig. 1E). It also inhibited the cell invasion in dose dependent manner (Fig. 1F and S1C, S1D, S1E,S1F). We further examined its effect on mammosphere formation. MDA-MB 231, MDA-MB 468, MCF7 and 4T1 cell mammosphere cultures were grown in presence or absence of 1.25 μM, 2.5 μM and 5.0 μM Shk for 24 h. After 8 days of culture, a dose dependent decrease in the mammosphere forming potential of these cells was observed (Figs. 1G,H). Collectively, these results indicated that Shk effectively inhibits the various hallmarks associated with aggressive breast cancer.
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Figure 1: Shk inhibits multiple cancer hallmarks
Shk reduces cancer stem cell load in breast cancer
As Shk exhibited strong anti-mammosphere forming potential; therefore it was further examined for its anti-cancer stem cell (CSC) properties. Cancer stem cell loads in breast cancer cells were assessed using Aldefluor assay which measures ALDH1 expression. MDA-MB 231 cells with the highest number of ALDH1+ cells were selected for further studies (Fig. S2A). We also checked the correlation between ALDH1 expression and mammosphere formation. Sorted ALDH1+ cells were subjected to mammosphere cultures. ALDH1+ cells formed highest number of mammospheres compared to ALDH1-/low and parent cell population, indicating that ALDH1+ cells are enriched in CSCs (Fig. S2B). Shk reduced the Aldefluor positive cells in MDA-MB 231 cells after 24 h of treatment (Fig. 2A,B). Next, we examined the effect of Shk on the expression of stem cell (Sox2, Oct3/4, Nanog, AldhA1 and c-Myc) and EMT (Snail, Slug, ZEB1, Twist, β-Catenin) markers, associated with the sustenance of breast CSCs. Shk (2.5 μM) treatment for 24 h reduced the expression of these markers (Fig. 2C and S2D). Shk also reduced protein expression of these markers in dose dependent manner (Fig. 2D,E and S2C).
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Figure 2: Shk decreases stem cell load in breast cancer cells and enriched CD44+,CD24−/low breast cancer stem cells.
To further confirm anti-CSC properties of Shk, we checked the effect of shikonin on the load of CD44+ CD24− breast CSCs in MCF7 cells grown on matrigel. Shikonin reduced CD44+ CD24− cell load in dose dependent manner after 24 h of treatment (Fig S2E). We also tested its effects on the enriched CSC population. CD44+ CD24− cells were enriched from MCF7 cells using MagCellect CD24− CD44+ Breast CSC Isolation Kit (Fig. S2F). Enriched CSCs formed highest number of mammosphere in comparison to parent MCF7 cell population or negatively selected CD24+ cells (Fig. S2G). Enriched CSCs were treated with indicated doses of Shk (0.625 μM, 1.25 μM and 2.5 μM) for 24 h and were either analyzed for ALDH1 positivity or subjected to colony or mammosphere formation. 2.5 μM dose of Shk reduced ALDH1+ cells by 50% and inhibited colony and mammosphere formation (Fig. S2H, 2F, 2G and 2H). Shk also reduced the mRNA expression of CSC markers in CD44+ CD24− cells and patient derived primary cancer cells (Fig. 2I,J). These results collectively indicated that Shk inhibits CSC load and associated programs in breast cancer.
Shk is a potent inhibitor of STAT3 and poorly inhibits FAK and Src
To identify the molecular mechanism responsible for anti-cancer properties of Shk, we used a human phospho-kinase antibody array to study a subset of phosphorylation events in MDA-MB 231 cells after 6h of treatment with 2.5 μM Shk. Amongst the 46 phospho-antibodies spotted on the array, the relative extent of phosphorylation of three proteins decreased to about ≳ 2 fold (STAT3, 3.3 fold; FAK, 2.5 fold and Src, 1.8 fold) upon Shk treatment (Fig. 3A,B). These proteins (STAT3, FAK and Src) are known to regulate CSC proliferation and self renewal21, 22, 23. Therefore, we focused on these proteins and the result of kinase-array was confirmed by western blotting. Shk effectively inhibits STAT3 at early time point (1 h) while activation of FAK and Src decreased on or after 3 h (Fig. 3C) confirming Shk as a potent inhibitor of STAT3. Shk also reduced the protein expression of STAT3, FAK and Src at 24 h (Fig. 3C).
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Figure 3. Shk inhibits STAT3, FAK and Src signaling pathways.
We also observed that Shk does not inhibit JAK2 at initial time-points (Fig. 3C). This raised a possibility that Shk either regulates STAT3 independent of JAK2 or it binds directly to STAT3. To check the first probability, we activated STAT3 by treating the cells with IL6 (100 ng ml−1) for 1 h followed by treatment with Shk (2.5 μM) for 1 h. Both immunofluorescence and western-blotting results showed that Shk inhibited activated STAT3 without inhibiting JAK2 (Fig. S3A, S3B) confirming that Shk inhibits JAK2 mediated activation of STAT3 possibly by binding directly to STAT3. For further confirmation, we performed an in silico molecular docking analysis to examine binding of Shk with the STAT3 SH2 domain. In a major conformational cluster, Shk occupied Lys-707, Lys-709 and Phe-710 binding sites in the STAT3 SH2 domain similar to the STAT3 standard inhibitor S3I-201 (Fig. S3C and S3D). The binding energy of Shk to STAT3 was −4.20 kcal mol−1. Collectively, these results showed that Shk potently inhibits STAT3 activation and also attenuates FAK and Src activation.
STAT3, Src and FAK are differentially expressed and activated in breast CSCs (BCSCs)
STAT3 and FAK are known to play an important role in proliferation and self-renewal of CSCs in various cancer types including breast cancer21, 22, 24. Src also support CSC phenotype in some cancer types, but there are limited reports of its involvement in breast cancer25. Therefore, we checked the expression and activation of STAT3, FAK and Src in CSCs and non-CSCs. Here we used two methods to enrich the CSCs and non-CSCs. In the first method, the MDA-MB 231 cells were subjected to mammosphere formation for 96 h. After 96 h, mammosphere and non-mammosphere forming cells were clearly visible (Fig. 4A). These mammosphere and non-mammosphere forming cells were separated by using a 70 micron cell strainer. Mammospheres were subjected to two subculture cycles to enrich CSCs. With each passage, the viable single cells (non-mammosphere forming cells) and mammospheres were collected in RIPA lysis buffer and western blotting was done (Fig. 4B). We found that the activation and expression of the STAT3, FAK and Src is higher in enriched mammosphere cultures (Fig. 4C). In the second method, CD44+ CD24− cells were isolated from MCF7 cultures using MagCellect Breast CSC Isolation Kit. STAT3, FAK and Src activation and their mRNA and protein expression were assessed in enriched CSCs and were compared to parent MCF7 cell population. STAT3, FAK and Src all were differentially activated in CSCs (Fig. 4E). High mRNA as well as protein expressions of all the three genes was also observed in CSCs (Fig. 4D,E). Collectively, these results indicate that STAT3, FAK and Src are over expressed and activated in BCSCs.
Figure 4: STAT3, FAK and Src are differentially activated and expressed in breast cancer cells.
Representative picture indicating mammosphere and single suspended cells. (B) Schematic outline of mammosphere enrichment. (C) Protein expression and activation of STAT3, FAK and Src was determined in single suspended cells (non-mammosphere forming cells) and mammospheres by western blot. The full size blots corresponding to the cropped blot images are given in S10. (D) Gene expression of STAT3, FAK and Src was determined in MCF7 parent population and CD44+ CD24−/low MCF7 cells using PCR. The full agarose gel images corresponding to the cropped images are given in Fig. S10. (E) Protein expression and activation of STAT3, FAK and Src was in CD44+ 24− cells and parent population.
STAT3, FAK and Src are differentially activated and expressed in breast cancer cells.
STAT3 is important for mammosphere formation and CSC programs in breast cancer
As our results indicated that the expression and activation of STAT3, FAK and Src is high in BCSCs and Shk is capable of inhibiting these signaling proteins; therefore to find out functional relevance of each protein and associated effects on their pharmacological inhibition by Shk, we used specific inhibitors against these three. Effect of these inhibitors was first tested on the mammosphere forming potential of MDA-MB 231, MDA-MB 468 and MCF7 cells. A drastic reduction in the mammosphere formation was observed upon STAT3 inhibition. FAK and Src inhibition also reduced the primary and secondary mammosphere formation but STAT3 inhibition showed most potent effect (Fig. 5A and S4). Further, we also checked the effect of these inhibitors on the expression of various CSC and EMT related markers in MDA-MB 231 cells. STAT3 inhibition decreased the expression of most of the CSC and EMT markers (Fig. 5B). These two findings indicated that STAT3 inhibition is more effective in reducing mammosphere forming potential and weakens major CSC programs and the anti-CSC potential of Shk is possibly due to its strong STAT3 inhibitory effect.
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STAT3, FAK and Src activation status correlates with mammosphere forming potential in breast cancer
Figure 5: STAT3, FAK and Src activation status correlates with mammosphere forming potential in breast cancer.
(A) Bar graph represents number of mammospheres formed from 2500 cells in presence and absence of indicated treatments. MDA-MB 231, MDA-MB 468 and MCF7 24 h mammosphere cultures were treated with Shk (2.5 μM), FAK inhibitor (FAK inhibitor 14; 2.5 μM), Src inhibitor (AZM 475271; 10 μM) and STAT3 inhibitor (WP1066; 10 μM). After 24 h, treatments were removed and cells were allowed to grow in fresh mammosphere culture media for 8 days. (B) Expression of various stem cell and EMT related transcription factors and markers were detected using western blotting in MDA-MB 231 cells with or without indicated treatments. The full size blots corresponding to the cropped blot images are given in Fig. S10. (C) MDA-MB 231, MDA-MB 468 and MCF7 cells were pre-treated with either IL6 (100 ng ml−1), Fibronectin (1 μg ml−1) or EGF (25 ng ml−1) for two population doublings and subjected to mammosphere formation. Bar graph represents average of three independent experiments. (D) MCF7 cells were pre-treated with either IL6 (100 ng ml−1), Fibronectin (1 μg ml−1) or EGF (25 ng ml−1) for two population doublings and subjected to mammosphere formation. After 24 h, cells were treated with DMSO (untreated) or Shk (treated) as indicated in the bar graph. Data are shown as the mean ±SD. (*) p < 0.05 and (**) p < 0.01.
To further check the involvement of these pathways in CSCs, we cultured MDA-MB 231, MDA-MB 468 and MCF7 cells in the presence of either IL6 (100ng ml−1), EGF (25 ng ml−1) or Fibronectin (1 μg ml−1) coated surface for two population doublings. Cells were then subjected to mammosphere formation. In IL6 pre-treated cultures, there was a sharp rise in mammosphere formation, indicating that the STAT3 activation shifts CSC and non-CSC dynamics towards CSCs (Fig. 5C). IL6 is previously known to induce the conversion of non-CSC to CSC via STAT3 activation26. In MCF7 cells, mammosphere forming potential after IL6 pre-treatment increased nearly by three fold. Therefore, we further checked the effectiveness of Shk on mammosphere forming potential in pre-treated MCF7 cells. It was found that Shk inhibits mammosphere formation most effectively in IL6 pre-treated cultures (Fig. 5D). However, in EGF and Fibronectin pre-treated cultures, Shk was relatively less effective. This was possibly due to its weak FAK and Src inhibitory potential. Collectively, these results illustrated that STAT3 activation is significantly correlated with the mammosphere forming potential of breast cancer cells and its inhibition by a standard inhibitor or Shk potently reduce the mammosphere formation.
Shk inhibit CSCs load by disrupting the STAT3-Oct3/4 axis
In breast cancer, STAT3 mediated expression of Oct3/4 is a major regulator of CSC self-renewal26, 27. As we observed that both Shk and STAT3 inhibitors decreased the Oct3/4 expression (Figs. 2C and 5B), we further checked the effect of STAT3 activation on ALDH1+ CSCs and Oct3/4 expression. On IL6 pre-treatment, number of ALDH1+ cells increased in all three (MDA-MB 231, MDA-MB 468 and MCF7) cancer cells (Fig. 6A). MCF7 cells showed highest increase. Therefore, to check the effect of STAT3 inhibition on CSC load, we incubated IL6 pre-treated MCF7 cells with Shk and STAT3 inhibitor for 24 h and analyzed for ALDH1 positivity. It was observed that both Shk and STAT3 inhibitor reduced the IL6 induced ALDH1 positivity from 10% to < 2% (Fig. 6B). These results suggested that Shk induced inhibition of STAT3 and decrease in BCSC load is interlinked. We further checked the effect of STAT3 activation status on Oct3/4 expression in MDA-MB 231, MDA-MB 468 and MCF7 cells. We observed that expression of Oct3/4 increases with the increase in STAT3 activation (Fig. 6C–E).
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Figure 6: STAT3 activation status and its effect on cancer stem cell load
STAT3 transcriptional activity is important in maintaining CSC programs28, 29. Therefore, we also examined the effect of Shk on STAT3 promoter activity. STAT3 reporter assay was performed in presence of IL6 and Shk; it was found that Shk reduced the promoter activity of STAT3 in a dose dependent manner (Fig. S5). Collectively, these results showed that Shk mediated STAT3 inhibition are responsible for decrease in CSC load and Oct3/4 associated stem cell programs.
Shk inhibits mammosphere formation, migration and invasion through inhibition of STAT3, FAK and Src in breast cancer cells
As the earlier results (Fig. 1) showed that Shk inhibits cell migration and invasion in breast cancer cells, we further examined the effect of STAT3, FAK and Src inhibitors on cell migration and invasion in MDA-MB 231 cells. It was found that STAT3 inhibitor poorly inhibits cell migration while both Src and FAK inhibitors were effective in reducing cell migration (Fig. 7A). All the three inhibitors decreased the cell invasion and MMP9 expression significantly (Fig. 7B and S6). It was also observed that effect of all these inhibitors, except STAT3 inhibitor on mammosphere formation and FAK inhibitor on cell migration, were not comparable to that of Shk. Shk inhibited all these properties more effectively than individual inhibition of STAT3, FAK and Src. This made us to assume that the ability of Shk to inhibit multiple signaling molecules simultaneously is the reason behind its potent anti-cancer effect. To check this notion, we combined STAT3, FAK and Src inhibitors with each other and examined the effect of combinations on invasion, migration and mammosphere forming potential in MDA-MB 231 cells. We observed further decrease in cell migration and invasion on combining STAT3 and FAK, STAT3 and Src, or FAK and Src (Figs. 7A,B). Combination of FAK and Src was not very effective in inhibiting mammosphere formation in MDA-MB 231 cells and CD44+ CD24− MCF7 CSCs. However, their combination with STAT3 decreased the mammosphere forming potential equivalent to that of Shk (Fig. 7C,D). We also compared the mammosphere forming potential of Shk with Salinomycin (another anti-CSC agent) and found that at 2.5 μM dose of Shk was almost two times more potent than Salinomycin (Fig. S7). Collectively, these results indicated that Shk inhibits multiple signaling proteins (STAT3, FAK and Src) to compromise various aggressive breast cancer hallmarks.
Figure 7: Combination of FAK, Src and STAT3 inhibitors is more potent than individual inhibition against various cancer hallmarks.
Cell migration and (B) cell invasion potential of MDA-MB 231 cells was assessed in the presence of Shk (2.5 μM), FAK inhibitor (FAK inhibitor 14; 2.5 μM), Src inhibitor (AZM 475271; 10 μM) and STAT3 inhibitor (WP1066; 10 μM). Various combinations of these inhibitors were also used STAT3+FAK inhibitor (WP1066; 10 μM + FAK inhibitor 14; 2.5 μM), STAT3 + Src Inhibitor (WP1066; 10 μM + AZM 475271; 10 μM) and FAK+Src Inhibitor (FAK inhibitor 14; 2.5 μM + AZM 475271; 10 μM). Cell migration and cell invasion was assessed through scratch cell migration assay and transwell invasion after 24 h of treatments. (C,D) Mammosphere forming potential of MDA-MB 231 cells and CD44+ CD24−/low enriched MCF7 cells was assessed in presence of similar combination of STAT3+FAK inhibitor (WP1066; 10 μM + FAK inhibitor 14; 2.5 μM), STAT3 + Src Inhibitor (WP1066; 10 μM+ AZM 475271; 10 μM) and FAK + Src Inhibitor (FAK inhibitor 14; 2.5 μM + AZM 475271; 10 μM). Cells were subjected to mammosphere cultures for 24 h and treated with the indicated inhibitors for next 24 h, followed by media change and growth of mammospheres were monitored for next 8 days. Data are shown as the mean ±SD. (**) p < 0.01.
Shk inhibits breast cancer growth, metastasis and decreases tumorigenicity
To explore whether Shk may have therapeutic potential for breast cancer treatment in vivo, we tested Shk against 4T1-induced breast cancer syngenic mouse model. 4T1 cells (mouse breast cancer cells) are capable of growing fast and metastasize efficiently in vivo30. Prior to the in vivo experiments, we checked the effect of Shk on ALDH1 positivity and on activation of STAT3, FAK and Src in 4T1 cells in vitro. Shk effectively decreased the ALDH1+ cells and inhibited STAT3, FAK and Src in 4T1 cells in vitro (Fig. S8A and S8B). For in vivo tumor generation, 1 × 106 cells were injected subcutaneously in the fourth nipple mammary fat pad of BALB/c mice. When the average size of tumors reached around 50 mm3, mice were divided into three groups, vehicle and two Shk treated groups each received either 2.5 mg Kg−1 or 5.0 mg Kg−1 Shk. Shk was administered via the intraperitoneal injection on every alternate day. It significantly suppressed the tumor growth in 4T1 induced syngenic mouse model (Fig. 8A). The average reduction in 4T1 tumor growth was 49.78% and 89.73% in 2.5 mg Kg−1 and 5.0 mg Kg−1 groups respectively compared with the vehicle treated group (Fig. 8A). No considerable change in body weight of the treated group animals was observed (Fig. S9A). We further examined the effect of Shk on the tumor initiating potential of breast cancer cells. 4T1 induced tumors were excised from the control and treatment groups on the second day after 4th dose of Shk was administered. Tumors were dissociated; cells were allowed to adhere and then re-injected into new animals for secondary tumor formation. Growth of secondary tumors was monitored till day 15 post-reinjection. Shk treated groups showed a marked decrease in secondary tumor formation (Fig. 8D). We also observed a drastic reduction in the number of metastatic nodules in the lungs of treatment group animals (Fig. 8F). The reduction in the metastatic load was not proportional to the decrease in tumor sizes; however within the treatment group, some animals with small tumors were carrying higher number of metastatic nodules. As FAK is an important mediator of cancer metastasis and metastatic colonization, we further examined the effects of Shk on metastatic colonization. For this, 1 × 105 4T1 cells were injected to BALB/c mice through tail vein. Animals were divided into three groups, as indicated above. Shk and vehicle were administered through intraperitoneal injections at alternate days starting from the 2nd day post tail vein injections till 33rd day. The average reduction in total number of metastatic nodules was 88.6% – 90.5% in Shk treated mice compared to vehicle control (Fig. 8F). An inset picture (Fig. 8A lower panel) represents lung morphology of vehicle control and treated groups. We further examined the activation and expression status of STAT3, FAK and Src between vehicle control and treated group tumors. There were low expression and activation of STAT3, FAK and Src in treated tumors as compared to the vehicle control (Fig. 8B,C). Similar trend was observed in ALDH1 expressions (Fig. 8B). Further, the mice tumor sections were subjected to immunohistochemistry, immunofluorescence and hematoxylin and eosin (H&E) staining to study histology and expression of key proteins being examined in this study. Fig. 8G shows representative images of H&E staining, proliferating cell nuclear antigen (PCNA), terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL), STAT3 and Oct3/4 immunostaining. PCNA expression was low while TUNEL positive cells were high in tumor tissues of Shk treated groups. STAT3 and Oct3/4 expression was low in Shk treated groups. These results collectively demonstrated that Shk modulates the expression and activation of STAT3, FAK and Src in vivo and is effective in suppressing tumorigenic potential and metastasis in syngenic mouse model.
Figure 8: Shk inhibits breast cancer growth, tumorigenicity and metastasisin vivo.
Shk inhibits breast cancer growth, tumorigenicity and metastasis in vivo
Shk inhibited 4T1 tumor growth. Bar graph represents the average tumor volumes in vehicle control and Shk treated tumor bearing mice (n = 6). (*) p < 0.05 and (**) p < 0.01. Inset picture of upper panel represents tumor sizes and lower pane represents lung morphology in vehicle control and Shk treatment groups. (B) Western blot examination of indicated proteins for their expression and activation in vehicle control and treated tumor groups. The full size blots corresponding to the cropped blot images are given in Fig. S10. (C) Gene expression of stem cell and EMT markers in tumor tissues excised from the vehicle control and Shk treated groups (n = 3). (D) Number of secondary tumors formed after injecting indicated cell dilutions from Vehicle treated and Shk treated 4T1 tumors. (E) Number of lung nodules formed in mice injected with 4T1 mouse mammary tumor cells in the mammary fat pad and administered with 2.5 mg Kg−1 Shk or vehicle control on every alternate day for 3 weeks (n = 6). (F) Number of lung nodules in mice injected with 4T1 mouse mammary tumor cells through tail vein and administered with 2.5 mg Kg−1 Shk or vehicle control on every alternate day for 3 weeks. (n = 8) (G) Representative panel of the histological H&E staining, immunofluorescence staining for the STAT3, Oct3/4, cell proliferation marker PCNA and DNA damage indicator-TUNEL staining of tumor sections from vehicle and treatment groups.
Recent studies have shown that aggressiveness, therapy resistance and disease relapse in breast cancer is attributed to a small population of CSCs involved in continuous self-renewal and differentiation through signaling pathways similar to that of the normal stem cells31. Therapeutic targeting of CSCs therefore, has profound clinical implications for cancer treatment31. Recent studies indicated that therapies / agents targeting both differentiated cancer cells and CSCs may possibly have significant therapeutic advantages32. Therefore, it is imperative to look for novel therapeutic agents with lesser side effects urgently for effective targeting of CSCs. In search of novel, nontoxic anti-CSC agents, attention has been focused on natural agents in recent times33,34. In this study, we have used a natural napthoquinone compound, Shk with established antitumorigenic, favorable pharmacokinetic and toxicity profiles and report for the first time its potent anti-CSC properties. Shk significantly inhibits breast cancer cell proliferation in vitro, ex vivoand in vivo. It decreases the cell migration and invasion of breast cancer cells in vivo, as well as inhibits tumorigenicity, metastasis and metastatic colonization in a syngenic mouse model of breast cancer in vivo. These finding suggest a strong potential of Shk in breast cancer therapy.
We assessed the effect of Shk on the CSC load in breast cancer cells through various functional assays (tumorsphere in vitro and syngenic mouse model of breast cancer in vivo) and quantification of specific stem cell markers. In breast cancer, CD44+ CD24− cells and ALDH1+ cells are considered to be BCSCs21, 25. Shk significantly decreased the mammosphere formation (Fig. 1H, S1G and 2H), ALDH1+ cell and CD44+ CD24− cell loads in vitro (Fig. 2B, S2E and S2H). It also reduced the expression of CSC markers (Oct3/4, Sox2, Nanog, c-Myc and Aldh1) in vivo andin vitro (Fig. 2C,D, S2C and S2D). These genes are known to regulate stem cell programs and in cancer, they are established promoters and regulators of CSC phenotype35, 36, 37, 38, 39, 40. Decrease in the expression of these genes on Shk treatment indicates its potential to suppress CSC programs. Tumor initiating potential (tumorigenicity) is the bona fide measure of CSCs. Reduction in the tumorigenic potential of cells isolated form Shk treated tumors indicates in vivoanti-CSC effects of Shk.
We further demonstrated that Shk is a potent inhibitor of STAT3 and it also inhibits FAK and Src (Fig. 3A–C). Its STAT3 inhibitory property was found to be responsible for its anti-CSC effects (Figs. 6B and 7B). STAT3 and FAK inhibitors are previously known to compromise CSC growth41,42. Here, we found that pharmacological inhibition of STAT3 was more effective in compromising CSC load than FAK and Src inhibitions (Fig. 5A). STAT3 activation through IL6 increases mammosphere formation more significantly than Src and FAK activation through EGF and Fibronectin (Fig. 5C). This indicates that IL6-STAT3 axis is a key regulator of BCSC dynamics.
11.2.3.9 Ovatodiolide Sensitizes Aggressive Breast Cancer Cells to Doxorubicin Anticancer Activity, Eliminates Their Cancer Stem Cell-Like Phenotype, and Reduces Doxorubicin-Associated Toxicity
Investigators evaluated the usability of ovatodiolide (Ova) in sensitizing triple negative breast cancer (TNBC) cells to doxorubicin (Doxo), cytotoxicity, so as to reduce Doxo effective dose and consequently its adverse effects. Ova-sensitized TNBC cells also lost their cancer stem cell-like phenotype evidenced by significant dissolution and necrosis of formed mammospheres, as well as their terminal differentiation. [Cancer Lett]
11.2.3.10 Glabridin Inhibits Cancer Stem Cell-Like Properties of Human Breast Cancer Cells: An Epigenetic Regulation of miR-148a/SMAd2 Signaling
The authors report that glabridin (GLA) attenuated the cancer stem cell (CSC)-like properties through microRNA-148a (miR-148a)/transforming growth factor beta-SMAD2 signal pathway in vitro and in vivo. In MDA-MB-231 and Hs-578T breast cancer cell lines, GLA enhanced the expression of miR-148a through DNA demethylation. [Mol Carcinog]
11.2.3.11 Ginsenoside Rh2 Inhibits Cancer Stem-Like Cells in Skin Squamous Cell Carcinoma
The effects of ginsenoside Rh2 (GRh2) on Lgr5-positive cancer stem cells (CSCs) were determined by flow cytometry and by tumor sphere formation. Scientists found that GRh2 dose-dependently reduced skin squamous cell carcinoma viability, possibly through reduced the number of Lgr5-positive CSCs. [Cell Physiol Biochem]
Background/Aims: Treatments targeting cancer stem cells (CSCs) are most effective cancer therapy, whereas determination of CSCs is challenging. We have recently reported that Lgr5-positive cells are cancer stem cells (CSCs) in human skin squamous cell carcinoma (SCC). Ginsenoside Rh2 (GRh2) has been shown to significantly inhibit growth of some types of cancers, whereas its effects on the SCC have not been examined. Methods: Here, we transduced human SCC cells with lentivirus carrying GFP reporter under Lgr5 promoter. The transduced SCC cells were treated with different doses of GRh2, and then analyzed cell viability by CCK-8 assay and MTT assay. The effects of GRh2 on Lgr5-positive CSCs were determined by fow cytometry and by tumor sphere formation. Autophagy-associated protein and β-catenin were measured by Western blot. Expression of short hairpin small interfering RNA (shRNA) for Atg7 and β-catenin were used to inhibit autophagy and β-catenin signaling pathway, respectively, as loss-of-function experiments. Results: We found that GRh2 dose-dependently reduced SCC viability, possibly through reduced the number of Lgr5-positive CSCs. GRh2 increased autophagy and reduced β-catenin signaling in SCC cells. Inhibition of autophagy abolished the effects of GRh2 on β-catenin and cell viability, while increasing β-catenin abolished the effects of GRh2 on autophagy and cell viability. Conclusion: Taken together, our data suggest that GRh2 inhibited SCC growth, possibly through reduced the number of Lgr5-positive CSCs. This may be conducted through an interaction Carcinoma account for more than 80% of all types of cancer worldwide, and squamous cell carcinoma (SCC) is the most frequent carcinoma. Skin SCC causes a lot of mortality yearly, which requires a better understanding of the molecular carcinogesis of skin SCC for developing efficient therapy [1,2]. Ginsenoside Rh2 (GRh2) is a characterized component in red ginseng, and has proven therapeutic effects on inflammation [3] and a number of cancers [4,5,6,7,8,9,10,11,12,13,14], whereas its effects on the skin SCC have not been examined.
Cancer stem cells (CSCs) are cancer cells with great similarity to normal stem cells, e.g., the ability to give rise to various cell types in a particular cancer [15,16]. CSCs are highly tumorigenic, compared to other non-CSCs. CSCs appear to persist in tumors as a distinct population and CSCs are believed to be responsible for cancer relapse and metastasis after primary tumor resection [15,16,17,18]. Recently, the appreciation of the critical roles of CSCs in cancer therapy have been continuously increasing, although the identification of CSCs in a particular cancer is still challenging.
To date, different cell surface proteins have been used to isolate CSCs from a variety of cancers by flow cytometry. Among these markers for identification of CSCs, the most popular ones are prominin-1 (CD133), side population (SP) and increased activity of aldehyde dehydrogenase (ALDH). CD133 is originally detected in hematopoietic stem cells, endothelial progenitor cells and neuronal and glial stem cells. Later on, CD133 has been shown to be expressed in the CSCs from some tumors [19,20,21,22,23], but with exceptions [24]. SP is a sub-population of cells that efflux chemotherapy drugs, which accounts for the resistance of cancer to chemotherapy. Hoechst (HO) has been experimentally used for isolation of SP cells, while the enrichment of CSCs by SP appears to be limited [25]. Increased activity of ALDH, a detoxifying enzyme responsible for the oxidation of intracellular aldehydes [26,27], has also been used to identify CSCs, using aldefluor assay [28,29]. However, ALDH has also been detected in other cell types, which creates doubts on the purity of CSCs using ALDH method [30,31]. Moreover, all these methods appear to be lack of cancer specificity.
The Wnt target gene Lgr5 has been recently identified as a stem cell marker of the intestinal epithelium, and of the hair follicle [32,33]. Recently, we reported that Lgr5 may be a potential CSC marker for skin SCC [34]. We detected extremely high Lgr5 levels in the resected skin SCC specimen from the patients. In vitro, Lgr5-positive SCC cells grew significantly faster than Lgr5-negative cells, and the fold increase in growth of Lgr5-positive vs Lgr5-negative cells is significantly higher than SP vs non-SP, or ALDH-high vs ALDH-low, or CD133-positive vs CD133-negative cells. Elimination of Lgr5-positive SCC cells completely inhibited cancer cell growth in vitro.
Here, we transduced human SCC cells with lentivirus carrying GFP reporter under Lgr5 promoter. The transduced SCC cells were treated with different doses of GRh2, and then analyzed cell viability by CCK-8 assay and MTT assay. The effects of GRh2 on Lgr5-positive CSCs were determined by flow cytometry and by tumor sphere formation. Autophagy-associated protein and β-catenin were measured by Western blot. Expression of short hairpin small interfering RNA (shRNA) for autophagy-related protein 7 (Atg7) and β-catenin were used to inhibit autophagy and β-catenin signaling pathway, respectively, as loss-of-function experiments. Atg7 was identified based on homology to Pichia pastoris GSA7 and Saccharomyces cerevisiae APG7. In the yeast, the protein appears to be required for fusion of peroxisomal and vacuolar membranes. The protein shows homology to the ATP-binding and catalytic sites of the E1 ubiquitin activating enzymes. Atg7 is a mediator of autophagosomal biogenesis, and is a putative regulator of autophagic function [35,36,37,38]. We found that GRh2 dose-dependently reduced SCC viability, possibly through reduced the number of Lgr5-positive CSCs. GRh2 increased autophagy and reduced β-catenin signaling in SCC cells. Inhibition of autophagy abolished the effects of GRh2 on β-catenin and cell viability, while increasing β-catenin abolished the effects of GRh2 on autophagy and cell viability.
Transduction of SCC cells with GFP under Lgr5 promoter
We have recently shown that Lgr5 is CSC marker for skin SCC [34]. In order to examine the role of GRh2 on SCC cells, as well as a possible effect on CSCs, we transduced human skin SCC cells A431 [34] with a lentivirus carrying GFP reporter under Lgr5 promoter (Fig. 1A). The Lgr5-positive cells were green fluorescent in culture (Fig. 1B), and could be analyzed or isolated by flow cytometry, based on GFP (Fig. 1C).
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Fig. 1. Transduction of SCC cells with GFP under Lgr5 promoter. (A) The structure of lentivirus carrying GFP reporter under Lgr5 promoter. (B) The pLgr5-GFP-transduced A431 cells in culture. Lgr5-positive cells were green fluorescent. Nuclear staining was done by DAPI. (C) Representative flow chart for analyzing pLgr5-GFP-transduced A431 cells by flow cytometry based on GFP. Gated cells were Lgr5-positive cells. Scar bar is 20µm.
GRh2 dose-dependently inhibits SCC cell growth
Then, we examined the effect of GRh2 on the viability of SCC cells. We gave GRh2 at different doses (0.01mg/ml, 0.1mg/ml and 1mg/ml) to the cultured pLgr5-GFP-transduced A431 cells. We found that from 0.01mg/ml to 1mg/ml, GRh2 dose-dependently deceased the cell viability in either a CCK-8 assay (Fig. 2A), or a MTT assay (Fig. 2B). Next, we questioned whether GRh2 may have a specific effect on CSCs in SCC cells. Thus, we analyzed GFP+ cells, which represent Lgr5-positive CSCs in pLgr5-GFP-transduced A431 cells after GRh2 treatment. We found that GRh2 dose-dependently deceased the percentage of GFP+ cells, by representative flow charts (Fig. 2C), and by quantification (Fig. 2D). We also examined the capability of the GRh2-treated cells in the formation of tumor sphere. We found that GRh2 dose-dependently deceased the formation of tumor sphere-like structure, by quantification (Fig. 2E), and by representative images (Fig. 2F). Together, these data suggest that GRh2 dose-dependently inhibited SCC cell growth, possibly through inhibition of CSCs.
Fig. 2. GRh2 dose-dependently inhibits SCC cell growth. We gave GRh2 at different doses (0.01mg/ml, 0.1mg/ml and 1mg/ml) to the cultured pLgr5-GFP-transduced A431 cells. (A-B) GRh2 dose-dependently deceased the cell viability in either a CCK-8 assay (A), or a MTT assay (B). (C-D) GFP+ cells after GRh2 treatment were analyzed by flow cytometry, showing that GRh2 dose-dependently deceased the percentage of GFP+ cells, by representative flow charts (C), and by quantification (D). The capability of the GRh2-treated cells to form tumor sphere-like structures was examined, shown by quantification (E), and by representative images (F). *p
GRh2 treatment decreases β-catenin and increases autophagy in SCC cells
We analyzed the molecular mechanisms underlying the cancer inhibitory effects of GRh2 on SCC cells. We thus examined the growth-regulatory proteins in SCC. From a variety of proteins, we found that GRh2 treatment dose-dependently decreases β-catenin, and dose-dependently upregulated autophagy-related proteins Beclin, Atg7 and increased the ratio of LC3 II to LC3 I, by quantification (Fig. 3A), and by representative Western blots (Fig.3B). Since β-catenin signaling is a strong cell-growth stimulator and autophagy can usually lead to stop of cell-growth and cell death, we feel that the alteration in these pathways may be responsible for the GRh2-mediated suppression of SCC growth.
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Figure 3. GRh2 treatment decreases β-catenin and increases autophagy in SCC cells.
Inhibition of autophagy abolishes the effects of GRh2 on β-catenin
In order to find out the relationship between β-catenin and autophagy in this model, we inhibited autophagy using a shRNA for Atg7, and examined its effect on the changes of β-catenin by GRh2. First, the inhibition of Atg7 in A431 cells by shAtg7 was confirmed by RT-qPCR (Fig. 4A), and by Western blot (Fig. 4B). Inhibition of Atg7 resulted in abolishment of the effects of GRh2 on other autophagy-associated proteins (Fig. 4B), and resulted in abolishment of the inhibitory effect of GRh2 on β-catenin (Fig. 4B). Moreover, the effects of GRh2 on cell viability were completely inhibited (Fig. 4C). Together, inhibition of autophagy abolishes the effects of GRh2 on β-catenin. Thus, the regulation of GRh2 on β-catenin needs autophagy-associated proteins.
Fig. 4. Inhibition of autophagy abolishes the effects of GRh2 on β-catenin.
A431 cells were transfected with shRNA for Atg7, or scrambled sequence (scr) as a control. (A) RT-qPCR for Atg7. (B) Quantification of β-catenin, Beclin, Atg7 and LC3 by Western blot. (C) Cell viability by CCK-8 assay. *p
Overexpression of β-catenin abolishes the effects of GRh2 on autophagy
Next, we inhibited the effects of GRh2 on β-catenin by overexpression of β-catenin in A431 cells. First, the overexpression of β-catenin in A431 cells was confirmed by RT-qPCR (Fig. 5A), and by Western blot (Fig. 5B). Overexpression of β-catenin resulted in abolishment of the effects of GRh2 on autophagy-associated proteins (Fig. 5B). Moreover, the effects of GRh2 on cell viability were completely inhibited (Fig. 5C). Together, inhibition of β-catenin signaling abolishes the effects of GRh2 on autophagy. Thus, the regulation of GRh2 on autophagy needs β-catenin signaling. This model is thus summarized in a schematic (Fig. 6), suggesting that GRh2 may target both β-catenin signaling and autophagy, which interacts with each other in the regulation of SCC cell viability and growth.
Fig. 5. Overexpression of β-catenin abolishes the effects of GRh2 on autophagy. A431 cells were transfected with β-catenin, or scrambled sequence (scr) as a control. (A) RT-qPCR for β-catenin. (B) Quantification of β-catenin, Beclin, Atg7 and LC3 by Western blot. (C) Cell viability by CCK-8 assay. *p
Fig. 6. Schematic of the model. GRh2 may target both β-catenin signaling and autophagy, which interacts with each other in the regulation of SCC cell viability and growth.
Understanding the cancer molecular biology of skin SCC and identification of an effective treatment are both critical for improving the current therapy [1]. Lgr5 has been recently identified as a novel stem cell marker of the intestinal epithelium and the hair follicle, in which Lgr5 is expressed in actively cycling cells [32,33]. Moreover, we recently showed that Lgr5-positive are CSCs in skin SCC [34]. Thus, specific targeting Lgr5-positive cells may be a promising therapy for skin SCC.
In the current study, we analyzed the effects of GRh2 on the viability of SCC. Importantly, we not only found that GRh2 dose-dependently decreases SCC cell viability, but also dose-dependently decreased the number of Lgr5-positive CSCs in SCC cells. These data suggest that the CSCs in SCC may be more susceptible for the GRh2 treatment, and the decreases in CSCs may result in the decreased viability in total SCC cells. This point was supported by following mechanism studies. Activated β-catenin signaling by WNT/GSK3β prevents degradation of β-catenin and induces its nuclear translocation [39]. Nuclear β-catenin thus activates c-myc, cyclinD1 and c-jun to promote cell proliferation, and activates Bcl-2 to inhibit apoptosis [39]. High β-catenin levels thus are a signature of CSCs. Therefore, it is not surprising that CSCs are more affected than other cells when GRh2 targets β-catenin signaling.
In addition, GRh2 appears to target autophagy. Although altered metabolism may be beneficial to the cancer cells, it can create an increased demand for nutrients to support cell growth and proliferation, which creates metabolic stress and subsequently induces autophagy, a catabolic process leading to degradation of cellular components through the lysosomal system [40]. Cancer cells use autophagy as a survival strategy to provide essential biomolecules that are required for cell viability under metabolic stress [40]. However, autophagy not only results in a staring in cell growth, but also may result in cell death [40]. Increases in autophagy may substantially decrease cancer cell growth. Thus, GRh2 has its inhibitory effect on skin SCC cells through a combined effect on cell proliferation (by decreasing β-catenin) and autophagy [40].
Interestingly, our data suggest an interaction between β-catenin and autophagy. This finding is consistent with previous reports showing that autophagy negatively modulates Wnt/β-catenin signaling by promoting Dvl instability [41,42], and with other studies showing that β-catenin regulates autophagy [38,43,44].
Of note, we have checked other SCC lines and essentially got same results. Together with our previous reports showing that Lgr5-positive cells are CSCs in skin SCC [34], these findings thus highlight a future engagement of Lgr5-directed GRh2 therapy, which could be performed in a sufficiently frequent manner, to substantially improve the current treatment for skin SCC.
Normal vs Cancer Thyroid Stem Cells: The Road to Transformation The authors discuss new insights into thyroid stem cells as a potential source of cancer formation in light of the available information on the oncogenic role of genetic modifications that occur during thyroid cancer development. Understanding the fine mechanisms that regulate tumor transformation may provide new ground for clinical intervention in terms of prevention, diagnosis and therapy. [Oncogene] Abstract
Cancer Stem Cells: A Potential Target for Cancer Therapy The identification of cancer stem cells (CSCs) and a better understanding of the complex characteristics of CSCs will provide invaluable diagnostic, therapeutic and prognostic targets for clinical application. The authors introduce the dysregulated properties of CSCs in cancers and discuss the possible challenges in targeting CSCs for cancer treatment. [Cell Mol Life Sci] Abstract
When mothers breastfeed their babies, they depend upon a unique interaction of genes and hormones to produce milk and deliver it to their hungry little tyke. Unfortunately, this same cocktail of genes and hormones can also lead to breast cancer, especially if the mother has her first pregnancy after age 30.
A medical research group at the Medical College of Georgia at Georgia Regents University has established that a gene called DNMT1 plays a central role in the maintenance of the breast (mammary gland) stem cells that enable normal rapid growth of the breasts during pregnancy. This same gene, however, can also maintain those cancer stem cells that enable breast cancer. According to their work, the DNMT1 gene is highly expressed in the most common types of breast cancer.
Also, another gene called ISL1, which encodes a protein that puts the brakes on the growth of breast stem cells, is nearly silent in the breasts during pregnancy and in breast cancer stem cells.
Dr. Muthusamy Thangaraju, a biochemist at the Medical College of Georgia, who is the corresponding author of this study, which was published in the journal Nature Communications, said, “DNMT1 directly regulates ISL1. If the DNMT1 expression is high, this ISL1 gene is low.” Thangaraju and his team first observed the connection between DNMT1 and ISL1 when they knocked out the DNMT1 gene mice and noted an increase in the expression of ISL1. These results inspired them to examine the relationship of these two genes in human breast cancer cells.
Thangaraju and his co-workers discovered that ISL1 is silent in most human breast cancers. Furthermore, they demonstrated that restoring higher levels of ISL1 to human breast cancer cells dramatically reduced cancer stem cell populations, the growth of these cells, and their ability to spread throughout the tissue; all of which are hallmarks of cancer.
Conversely, Thangaraju and his team knocked out the DNMT1 gene in a breast-cancer mouse model, the breast will not develop as well. However, according to Thangaraju, this same deletion will also prevent the formation of about 80 percent of breast tumors. In fact, DNMT1 also down-graded super-aggressive, triple-negative breast cancers, which are negative for the estrogen receptor (ER-), progesterone receptor (PR-), and HER2 (HER2-).
The findings from this work also point toward new therapeutic targets for breast cancer and new strategies to diagnose early breast cancer. For example, a blood test for ISL1 might provide a marker for the presence of early breast cancer. Additionally, the anti-seizure medication valproic acid is presently being used in combination with chemotherapy to treat breast cancer, and this drug increases the expression of ISL1. This might explain why valproic acid works for these patients, according to Thangaraju. Workers in Thangaraju’s laboratory are already screening other small molecules that might work as well or better than valproic acid.
Mammary stem cells maintain the breasts during puberty as well as pregnancy, which are both periods of dynamic breast cell growth. During pregnancy, breasts may generate 300 times more cells as they prepare for milk production. Unfortunately, these increased levels of cell growth might also include the production of tumor cells, and the mutations that lead to breast cancer increase in frequency with age. If the developing fetus dies before she comes to term, immature breast cells that were destined to become mature mammary gland cells can more easily become cancer, according to Rajneesh Pathania, a GRU graduate student who is the first author of this study.
DNMT1 is essential for maintaining a variety of stem cell types, such as hematopoietic stem cells, which produce all types of blood cells. However, the role of DNMT1 in the regulation of breast-specific stem cells that make mammary gland tissue and may enable breast cancer has not been studied to this point.
For reasons that are unclear, there is an increased risk of breast cancer if the first pregnancy occurs after age 30 or if mothers lose their baby during pregnancy or have an abortion. Women who never have children also are at increased risk, but multiple term pregnancies further decrease the risk, according to data compiled and analyzed by the American Cancer Society.
Theories to explain these phenomena include the coupling of the hormone-induced maturation of breast cells that occurs during pregnancy with an increase in the potential to produce breast cancer stem cells. Most breast cancers thrive on estrogen and progesterone, which are both highly expressed during pregnancy and help fuel stem cell growth. During pregnancy, stem cells also divide extensively and as their population increases, DNMT1 levels also increase.
In five different types of human breast cancer, researchers found high levels of DNMT1 and ISL1 turned off. Even in a laboratory dish, when they reestablished normal expression levels of ISL1, human breast cancer cells and stem cell activity were much reduced, Thangaraju said.
CRACKING THE CODE OF HUMAN LIFE: Recent Advances in Genomic Analysis and Disease – Part IIC
Author: Larry H. Bernstein, MD, FCAP, Triplex Medical Science
Article 1.4 CRACKING THE CODE OF HUMAN LIFE: Recent Advances in Genomics Analysis and Disease – Part IIC
Part I: The Initiation and Growth of Molecular Biology and Genomics – Part I From Molecular Biology to Translational Medicine: How Far Have We Come, and Where Does It Lead Us?
Part IIB. “CRACKING THE CODE OF HUMAN LIFE: The Birth of BioInformatics & Computational Genomics” lays the manifold multivariate systems analytical tools that has moved the science forward to a groung that ensures clinical application.
Part IIC. “CRACKING THE CODE OF HUMAN LIFE: Recent Advances in Genomic Analysis and Disease “ will extend the discussion to advances in the management of patients as well as providing a roadmap for pharmaceutical drug targeting.
This final paper of Part II concludes a thorough review of the scientific events leading to the discovery of the human genome, the purification and identification of the components of the chromosome and the DNA structure and role in regulation of embryogenesis, and potential targets for cancer.
The first two articles, Part IIA, Part IIB, go into some depth to elucidate the problems and breakthoughs encountered in the Human Genome Project, and the construction of a 3-D model necessary to explain interactions at a distance.
Part IIC, the final article, is entirely concerned with clinical application of this treasure trove of knowledge to resolving diseases of epigenetic nature in the young and the old, chronic inflammatory diseases, autoimmune diseases, infectious disease, gastrointestinal disorders, neurological and neurodegenerative diseases, and cancer.
Recently, large studies have identified some of the genetic basis for important common diseases such as heart disease and diabetes, but most of the genetic contribution to them remains undiscovered. Now researchers at the University of Massachusetts Amherst led by biostatistician Andrea Foulkes have applied sophisticated statistical tools to existing large databases to reveal substantial new information about genes that cause such conditions as high cholesterol linked to heart disease.
Foulkes says, “This new approach to data analysis provides opportunities for developing new treatments.” It also advances approaches
to identifying people at greatest risk for heart disease. Another important point is that our method is straightforward to use with freely
available computer software and can be applied broadly to advance genetic knowledge of many diseases.
The new analytical approach she developed with cardiologist Dr. Muredach Reilly at the University of Pennsylvania and others is called “Mixed modeling of Meta-Analysis P-values” or MixMAP. Because it makes use of existing public databases, the powerful new method
represents a low-cost tool for investigators.
MixMAP draws on a principled statistical modeling framework and the vast array of summary data now available from genetic association
studies to formally test at a new, locus-level, association.
While that traditional statistical method looks for one unusual “needle in a haystack” as a possible disease signal, Foulkes and colleagues’
new method uses knowledge of DNA regions in the genome that are likely to
contain several genetic signals for disease variation clumped together in one region.
Thus, it is able to detect groups of unusual variants rather than just single SNPs, offering a way to “call out” gene
regions that have a consistent signal above normal variation.
The LPA gene codes for apolipoprotein(a), which, when linked with low-density lipoprotein particles, forms lipoprotein(a) [Lp(a)] —
a well-studied molecule associated with coronary artery disease (CAD). The Lp(a) molecule has both atherogenic and thrombogenic effects in vitro , but the extent to which these translate to differences in how atherothrombotic disease presents is unknown.
LPA contains many single-nucleotide polymorphisms, and 2 have been identified by previous groups as being strongly associated with
levels of Lp(a) and, as a consequence, strongly associated with CAD.
However, because atherosclerosis is thought to be a systemic disease, it is unclear to what extent Lp(a) leads to atherosclerosis in other arterial beds (eg, carotid, abdominal aorta, and lower extremity),
as well as to other thrombotic disorders (eg, ischemic/cardioembolic stroke and venous thromboembolism).
Such distinctions are important, because therapies that might lower Lp(a) could potentially reduce forms of atherosclerosis beyond the coronary tree.
To answer this question, Helgadottir and colleagues compiled clinical and genetic data on the LPA gene from thousands of previous
participants in genetic research studies from across the world. They did not have access to Lp(a) levels, but by knowing the genotypes for
2 LPA variants, they inferred the levels of Lp(a) on the basis of prior associations between these variants and Lp(a) levels. [1]
Their studies included not only individuals of white European descent but also a significant proportion of black persons, in order to
widen the generalizability of their results.
Their main findings are that LPA variants (and, by proxy, Lp(a) levels) are associated with
CAD,
peripheral arterial disease,
abdominal aortic aneurysm,
number of CAD vessels,
age at onset of CAD diagnosis, and
large-artery atherosclerosis-type stroke.
They did not find an association with
cardioembolic or small-vessel disease-type stroke;
intracranial aneurysm;
venous thrombosis;
carotid intima thickness; or,
in a small subset of individuals, myocardial infarction.
English: Structure of the LPA protein. Based on PyMOL rendering of PDB 1i71. (Photo credit: Wikipedia)
Micrograph of an artery that supplies the heart with significant atherosclerosis and marked luminal narrowing. Tissue has been stained using Masson’s trichrome. (Photo credit: Wikipedia)
Scientists at the Gladstone Institutes have revealed the precise order and timing of hundreds of genetic “switches” required to construct a fully
functional heart from embryonic heart cells — providing new clues into the genetic basis for some forms of congenital heart disease.
In a study being published online today in the journal Cell, researchers in the laboratory of Gladstone Senior Investigator Benoit Bruneau, PhD,
employed stem cell technology, next-generation DNA sequencing and computing tools to piece together the instruction manual, or “genomic
blueprint” for how a heart becomes a heart. These findings offer renewed hope for combating life-threatening heart defects such as arrhythmias (irregular heart beat) and ventricular septal defects (“holes in the heart”).
They approach heart formation with a wide-angle lens by
looking at the entirety of the genetic material that gives heart cells their unique identity.
The news comes at a time of emerging importance for the biological process called “epigenetics,” in which a non-genetic factor impacts a cell’s genetic
makeup early during development — but sometimes with longer-term consequences. All of the cells in an organism contain the same DNA, but the
epigenetic instructions encoded in specific DNA sequences give the cell its identity. Epigenetics is of particular interest in heart formation, as the
incorrect on-and-off switching of genes during fetal development can lead to congenital heart disease — some forms of which may not be apparent until adulthood.
the scientists took embryonic stem cells from mice and reprogrammed them into beating heart cells by mimicking embryonic development in a petri dish. Next, they extracted the DNA from developing and mature heart cells, using an advanced gene-sequencing technique called ChIP-seq that lets scientists “see” the epigenetic signatures written in the DNA.
Map of Heart Disease Death Rates in US White Males from 2000-2004 (Photo credit: Wikipedia)
Estimated propability of death or non-fatal myocardial-infarction over one year corresponding ti selectet values of the individual scores. Ordinate: individual score, abscissa: Propability of death or non-fatal myocardial infarction in 1 year (in %) (Photo credit: Wikipedia)
simply finding these signatures was only half the battle — we next had to decipher which aspects of heart formation they encoded
To do that, we harnessed the computing power of the Gladstone Bioinformatics Core. This allowed us to take the mountains of data collected from
gene sequencing and organize it into a readable, meaningful blueprint for how a heart becomes a heart.”
For each of the above datasets, an upstream analysis from the identified transcription factors correctly identified the stimulus. IPA’s tools were very
easy to use and the
analysis time for the above experiments was less than one minute.
The performance, speed, and ease of use can only be characterized as very good, perhaps leading to breakthroughs when extended and used creatively. Ingenuity’s new transcription factor analysis tool in IPA, coupled with Ingenuity’s established upstream grow tools, should be strongly considered for every lab analyzing differential expression data.
NF-E2-related factor 2 (Nrf2) is an important transcription factor that
activates the expression of cellular detoxifying enzymes.
Nrf2 expression is largely regulated through the association of Nrf2 with Kelch-like ECH-associated protein 1 (Keap1), which
results in cytoplasmic Nrf2 degradation.
Conversely, little is known concerning the regulation of Keap1 expression. Until now, a regulatory role for microRNAs (miRs) in controlling Keap1 gene expression had not been characterized. By using miR array-
based screening, we observed miR-200a silencing in breast cancer cells and
demonstrated that upon re-expression, miR-200a
targets the Keap1 3′-untranslated region (3′-UTR), leading to Keap1 mRNA degradation. Loss of this regulatory mechanism may
contribute to the dysregulation of Nrf2 activity in breast cancer. Previously, we have identified epigenetic repression of miR-200a
in breast cancer cells. Here, we find that treatment with epigenetic therapy, the histone deacetylase inhibitor suberoylanilide hydroxamic acid, restored miR-200a expression and reduced Keap1 levels. This reduction in Keap1 levels corresponded with
Nrf2 nuclear translocation
and activation of Nrf2-dependent NAD(P)H-quinone oxidoreductase 1 (NQO1) gene transcription.
Moreover, we found that Nrf2 activation inhibited the anchorage-independent growth of breast cancer cells. Finally, our in vitro observations were confirmed in a model of carcinogen-induced mammary hyperplasia in vivo. In conclusion, our study demonstrates
that miR-200a regulates the Keap1/Nrf2 pathway in mammary epithelium, and we find that epigenetic therapy can restore miR-200a
regulation of Keap1 expression,
reactivating the Nrf2-dependent antioxidant pathway in breast cancer.
Nuclear factor-like 2 (erythroid-derived 2, also known as NFE2L2 or Nrf2, is a transcription factor that in humans is encoded by the NFE2L2 gene.[1]) NFE2L2 induces the expression of various genes including those that encode for several antioxidant enzymes, and it may play a physiological role in the regulation of oxidative stress. Investigational drugs that target NFE2L2 are of interest as potential therapeutic interventions for
oxidative-stress related pathologies.
4. Highly active zinc finger nucleases by extended modular assembly
Zinc finger nucleases (ZFNs) are important tools for genome engineering. Despite intense interest by many academic groups,
the lack of robust non-commercial methods has hindered their widespread use. The modular assembly (MA) of ZFNs from
publicly-available one-finger archives provides a rapid method to create proteins that can recognize a very broad spectrum of DNA sequences.
However, three- and four-finger arrays often fail to produce active nucleases. Efforts to improve the specificity of the one-finger archives have not increased the success rate above 25%, suggesting that the MA method might
be inherently inefficient due to its insensitivity to context-dependent effects.
Here we present the first systematic study on the effect of array length on ZFN activity. ZFNs composed of six-finger MA arrays produced mutations at 15 of 21 (71%) targeted
loci in human and mouse cells. A novel Drop-Out Linker scheme was used to rapidly assess three- to six-finger combinations,
demonstrating that shorter arrays could improve activity in some cases. Analysis of 268 array variants revealed that half of
MA ZFNs of any array composition that exceed an ab initio
B-score cut-off of 15 were active.
MA ZFNs are able to target more DNA sequences with higher success rates than other methods.
These insightful reviews are based on the strategic data and insights from Thomson Reuters Cortellis™ for Competitive Intelligence. (A Review of April-June 2012).
The majority of diseases are complex and multi-factorial, involving multiple genes interacting with environmental factors. At the genetic level,
information from genome-wide association studies that elucidate common patterns of genetic variation across various human populations,
in addition to profiling, technologies can be utilized in discovery research to provide snapshots of genes and expression profiles that are controlled
by the same regulatory mechanism and are altered between healthy and diseased states.
The characterization of genes that are abnormally expressed in disease tissues could further be employed as
diagnostic markers,
prognostic indicators of efficacy and/or toxicity, or as
targets for therapeutic intervention.
As the defining catalyst that exponentially paved the way for personalized medicine, information from the published genome sequence revealed that much of the genetic variations in humans are concentrated in about 0.1 percent of the over 3 billion base pairs in the haploid DNA. Most of these variations involve substitution of a single nucleotide for another at a given location in the genetic sequence, known as single nucleotide polymorphism (SNP).
Combinations of linked SNPs aggregate together to form haplotypes and
together these serve as markers for locating genetic variations in DNA sequences.
SNPs located within the protein-coding region of a gene or within the control regions of DNA that regulate a gene’s activity could
have a substantial effect on the encoded protein and thus influence phenotypic outcomes.
Analyzing SNPs between patient population cohorts could highlight specific genotypic variations which can be correlated with specific phenotypic variations in disease predisposition and drug responses.
Prior to the genomic revolution, many of the established therapies were directed against less than 500 drug targets, with many of the top selling drugs acting on well defined protein pathways. However, the sequencing of the human genome has massively expanded the pool of molecular targets that could be exploited in unmet medical needs and currently, of the approximately 22,300 protein-coding genes in the human code, it has been estimated that up to 3000 are druggable. Furthermore, genomic technologies such as
high-throughput sequencing
and transcription profiling,
can be used to identify and validate biologically relevant target molecules, or can be applied to cell-based and mice disease models or directly to in vivo human tissues,
helping to correlate gene targets with phenotypic traits of complex diseases.
This is particularly important, as
insufficient validation of target gene/proteins in complex diseases may be a contributing factor in the decline in R&D productivity.
Personalized medicine no doubt is already having a tremendous impact on drug development pipelines. According to a study conducted by the Tufts Center for the Study of Drug Development, more than 90 percent of biopharmaceutical companies now utilize at least some
genomics-derived targets in their drug discovery programs.
However, pipeline analysis from Cortellis for Competitive Intelligence suggests that there is still a scientific gap that has resulted in difficulty optimizing these novel genomic targets into the clinical R&D portfolios of major pharmaceutical companies, particularly outside the oncology field. Selected examples of personalized medicine product candidates in clinical development include (see TABLE 4).
Mutations in Melanomaare in regions that control genes, not in the genes themselves. The mutations are exactly the type caused by exposure to ultraviolet light. The findings are reported in two papers in http://Science.com/ScienceExpress/
The findings do not suggest new treatments, but they help explain how melanomas – and possibly – other cancers – develop and what drives their growth. This is a modification found in the “dark matter”, according to Dr. Levi A. Garraway, the 99 percent of DNA in a region that regulates genes. A small control region was mutated in 7 out of 10 of the tumors, commonly of one or two tiny changes. A German Team led by Rajiv Kumar (Heidelberg) and Dirk Schadendorf (Essen) looked at a family whose members tended to get melanomas. Their findings indicate that those inherited with the mutations might be born with cells that have taken the first step toward cancer.
The mutations spur cells to make telomerase, that keeps the cells immortal by preventing them from losing the ends of their chromosome, the telomere. Abundant telomerase occurs in 90 percent of cancers, according to Immaculata De Vivo at Harvard Medical School.
The importance of the findings is that the mechanism of telomerase involvement in cancer is now within view. But it is not clear how to block the telomerase production in cancer cells.
A slight mutation in the matched nucleotides can lead to chromosomal aberrations and unintentional genetic rearrangement. (Photo credit: Wikipedia)
Comment
This discussion addresses the issues raised about the direction to follow in personalized medicine. Despite the amount of work necessary to bring the clarity that is sought after, the experiments and experimental design is most essential.
The arrest of ciliogenesis in ovarian cancer cell lines compared to wild type (WT) ovarian epithelial cells, and
The link to suppressing ciliogenesis by AURA protein and CHFR at the base of the cilium, which disappears at mitosis or with proliferation.
There is no accumulation by upregulation of PDGF under starvation by the cancer cells compared to the effect in WT OSE.
Here we have a systematic combination of signaling events tied to changes in putative biomarkers that occur synchronously in Ov cancer cell lines.
These changes are identified with changes in
proliferation,
loss of ciliary structure, and
proliferation.
In this described scenario,
WT OSE cells would be arrested, and
it appears that they would take the path to apoptosis (under starvation).
Even without more information, this cluster is what one wants to have in a “syndromic classification”. The information used to form the classification entails the identification of strong‘signaling-related’ biomarkers. The Gli2 peptide has to be part of this.
In principle, a syndromic classification would be ideally expected to have no less than 64 classes. If the classification is “weak”, then the class frequencies would be close to what one would expect in the WT OSE. In this case, in reality,
several combinatorial classes would have low frequency, and
others would be quite high.
This obeys the classification rules established by feature identification, and the information gain described by Solomon Kullback and extended by Akaike.
Does this have to be the case for all different cancer types? I don’t think so. The cells are different in ontogenesis. In this case, even the WT OSE have mesenchymal features and so, are not fully directed to epithelial expression. This happens to be the case in actual anatomic expression of the ovary. On the other hand, one would expect shared features of the
ovary,
testes,
thyroid,
adrenals, and
pituitary.
There is biochemical expression in terms of their synthetic function – TPN organs. I would have to put the liver into that broad class. Other organs – skeletal muscle & heart – transform substrate into energy or work. (Where you might also put intestinal smooth muscle).
They have to have different biomarker expressions, even though they much less often don’t form neoplasms. (Bone is not just a bioenergetic force. It is maintained by muscle action. It forms sarcomas. But there has to be a balance between bone removal by osteoclasts and refill by osteoblasts.)
Viewpoint: What we have learned
The Watson-Crick model proposed in 1953 is limited for explaining fully genome effects
The Pauling triplex model may have been prescient because of a more full anticipation of molecular bonding variants
A more adequate triple-helix model has been proposed and is consistent with a compact genome in the nucleus
The structure of the genome is not as we assumed – based on the application of Fractal Geometry. Current body of evidence is building that can reveal a more complete view of genome function.
transcription
cell regulation
mutations
Summary
I have just completed a most comprehensive review of the Human Genome Project. There are key research collaborations, problems in deciphering the underlying structure of the genome, and there are also both obstacles and insights to elucidating the complexity of the final model.
This is because of frequent observations of molecular problems in folding and other interactions between nucleotides that challenge the sufficiency of the original DNA model proposed by Watson and Crick. This has come about because of breakthrough innovation in technology and in computational methods.
Radoslav Bozov •
Molecular biology and growth was primarily initiated on biochemical structural paradigms aiming to define functional spatial dynamics of molecules via assignation of various types of bondings – covalent and non-covalent – hydrogen, ionic , dipole-dipole, hydrophobic interactions.
Lab techniques based on z/m paradigm allowed separation, isolation and identification of bio substances with a general marker identity finding correlation between physiological/cellular states.
The development of electronic/x-ray technologies allowed zooming in nano space without capturing time.
NMR technology identified the existence of space topology of initial and final atomic states giving a highly limited light on time – energy axis of atomic interactions.
Sequence technology and genomic perturbations shed light on uncertainty of genomic dynamics and regulators of functional ever expanding networks.
Transition state theory coupled to structural complexity identification and enzymatic mechanisms ran up parallel to work on various phenomena of strings of nucleotides (oligomers and polymers) – illusion/observation of constructing models on the dynamics of protein-dna-rna interference.
The physical energetic constrains of biochemistry were inapplicable in open biological systems. Biologists have accepted observation as a sole driver towards re-evaluating models.
The separation of matter and time constrains emerged as deviation of energy and space constrains transforming into the full acceptance of code theory of life. One simple thing was left unnoticed over time –
the amount of information of quantum matter within a single codon is larger than that of a single amino acid. This violated all physical laws/principles known to work with a limited degree of certainty.
The limited amount of information analyzed by conventional sequence identity led to the notion of applicability of statistical measures of and PCR technology. Mutations were identified over larger scale of data.
Quantum chemistry itself is being limited due discrete space/energy constrains, thus it transformed into concepts/principles in biology that possess highly limited physical values whatsoever.
The central dogma is partially broken as a result of
regulatory constrains
epigenetic phenomena and
iRNA.
Large scale code computational data run into uncertainty of the processes of evolution and its consequence of signaling transformation. All drugs were ‘lucky based’ applicability and/or discovery with largely unpredictable side effect over time.
Other Related articles on this Open Access Online Sceintific Journal include the following:
Early in the month of September, Nature, published 30 research papers on the results found from the ambitious and one time felt risky project, named, ENCODE (Encyclopedia of DNA Elements). The results of ENCODE revealed that 80% of human genome is not “junk”, as thought before, rather act as regulatory domains for further signaling events.
When human genome was first sequenced, more than a decade ago, scientists were surprised with the low ratio of coding regions transcribing genes to the number of bases in human DNA. Out of 3 billion bases in human DNA scientists found only 21,000 genes. This unexpected finding led to few basic questions:
Why do humans have so many base pairs?
How highly regulated complex behaviors of biochemical, cellular and physiological processes can be translated to regulation at genetic levels?
ENCODE project results unveil our limited knowledge about human genome until now. Their results open up new ways of thinking human DNA and its functional domains. It also brings in huge challenges for both experimental developments and data driven computational approaches for better understanding and applications of these new findings.
To gain insight from large scale data and identifying key players from a large pool of data, Bioinformatics approaches will probably be the only way to move forward. This also means importance of developing new algorithms which will include the capability of including regulatory functions linking with gene regulation. Presently, most algorithms are targeted toward identifying genes and their connections in a linear fashion. However, regulatory domains and their functional activities might be non linear, something which will be revealed with many more experimental results in coming years.
The functional characteristics of human genome will also lead to better understanding of genetic differences between normal states and disease states. Moreover, with proper identification of functional characteristics of a particular gene regulation, drugs can be targeted with much more precision in future. However, to make success of such a complicated problem, it will require visionary design and execution of experiment and computational biology teams working together.
It is well recognized already that Bioinformatics approaches can hugely help in identifying key players in regulation of genes. However many times it is not easy to translate information at the genetic levels directly to cellular or physiological levels. Some of the main reasons are – a) the complex cross talks between proteins which lead to intracellular signaling events and b) highly non linear information sharing among receptors and ligands for extra cellular signaling processes. To achieve efficient understanding of the functional characteristics of non-coding regions of DNA in context with regulation of genes, an effort should be given to map the functional network of gene regulation to signaling pathways of protein networks. This will require development of experimental as well as computational approaches to capture genetic as well as proteomics analysis together. Furthermore, for better understanding of cellular and physiological decisions, mapping between regulations of genes and intracellular signaling pathways should be extended for dynamic analysis with time.
The extraordinary findings from ENCODE project pose many challenges in front for getting answers to many unknowns for next decade or so but also give solutions to some basic questions which have haunted scientific world for almost a decade.
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Srinivas Sriram
stuartlpbi
Dr. Sudipta Saha
tildabarliya
vaishnavee24
zraviv06
zs22
