The Severe Challenge for Cancer Population

Treatment of cancer remains a huge challenge in the existing medical system and scientists across the global need to find ways to battle with it. This effort also involves recruiting pharmaceutical companies, governments and patient groups to cope with the healthcare burden.

Although once considered a problem exclusive to high-income countries, cancer is a leading cause of death and disability in the developing world. Of the 169.3 million years of healthy life lost (YLLs) globally in 2008, approximately 70% occur in the low- and middle-income countries. Additionally, 12.7 million of new cases are estimated every year, equal to approximately 35,000 new cases every day.

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The researchers also determines that men in eastern Europe have the largest cancer burden worldwide (3,146 age-adjusted DALYs(disability-adjusted life-years) lost per 100,000 men). Among women, the highest burden is in sub-Saharan Africa(2,749 age-adjusted DALYs lost per 100,000 women).

Each year globally, about 14 million people learn they have cancer and 7.6 million people die from the disease. The fire types of cancer contribute to 51% of total death of cancer patients, including lung, stomach , liver ,colorectal, and breast cancer.

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Additionally, the study reveals that improved access to high-quality treatment has not improved survival for a number of common cancers associated with poor outcomes. This points to the crucial role that prevention needs to play if the worldwide cancer burden is to be reduced, said Dr. Isabelle Soerjomataram, of the International Agency for Research on Cancer (IARC) in Lyon, France, and colleagues.

Anti-PD-1 plus Anti-CTLA-4 Immunotherapy Shows Promise in Treating Advanced Melanoma

A phase 1b immunotherapy trial, conducted by Mario Sznol, a clinical research leader at Yale Cancer Center, originally shows encouraging results – long-lasting with high survival rates — in the long-term follow-up study. This study was published in the New England journal of Medicine and presented at ASCO in 2013.

The trial estimated the safety and efficacy of the combination regimen of nivolumab (anti-PD-1) and ipilimumab (anti-CTLA-4; Yervoy), given either concurrently or sequentially, to patients with advanced melanoma whose disease progressed after prior treatment. The one-year overall survival rate was 94% and the two-year rate was 88%.

Currently, scientists are detecting that when PD-1 blockers and CTLA4 blockers are used together, they have a much greater impact than either alone: knocking out CTLA4 allows the body to create an army of anti-cancer T-cells, and knocking out PD-1 or PD-L1 allows this army to attack.

Uncover the handshake of cancer cells with T cells

Cancer cells would develop a “secret handshake” to trick the body’s T-cells. Understanding what roles some inside molecules(such as PA-1) play is vital to unleashing the immune system’s lines of attack, and getting better results for patients. There are some significant strides in decoding the interaction of PD-1 and PD-L1 listed as follows.

In 1992, Japanese researchers found a molecule on the surface of T-cells they named “programmed death 1″, or PD-1, which subsequently turned out to be a key part of their molecular handshake.

In 1999, a lab in Minnesota isolated a molecule, which they called PD-L1 (for “programmed death ligand 1″). Researchers then discovered that cancers often produced large amounts of PD-L1 – this was one of the key ways in which they were tricking the body’s defenses. This fired the starting gun on a race to develop drugs to disrupt the handshake by targeting either PD-1 and PD-L1 and pretty much every major pharma company joined in.

By 2006, a lab in Atlanta, Georgia, had proved in mice, that disrupting the PD-1-PD-L1 handshake could cure chronic viral lung infections – blocking this process could be relevant for a wide range of other diseases. The pressure to bring these drugs through trials began to build.

Not yet ready for prime time

This combination regimen is hugely promising in treating metastatic cancer, while it can also cause some pretty fearsome side-effects – particularly a nasty inflammatory bowel condition called colitis, which leads to diarrhoea and stomach cramps.

“The treatment of advanced melanoma has changed dramatically in the last few years, but there continues to be a need to increase the number of patients who experience a long-term survival benefit,” Sznol said. “While these are phase 1b data, the duration of response and one- and two-year survival rates observed with the combination regimen of nivolumab and ipilimumab are very encouraging and support the rationale for the ongoing, late-stage trials of this combination regimen.”

As a concept, targeting the subtle molecular interactions between our immune system and cancer looks like a breakthrough that’s here to stay. In fact, some experts even think that the idea will eventually replace ‘traditional’ chemotherapy and radiotherapy, and become a new paradigm for treating the disease.

Reference

Nivolumab plus ipilimumab in advanced melanoma. N Engl J Med. 2013 Jul 11;369(2):122-33.

Tumors impart hints at what drives their progression

In tumors, scientists can detect any number of point mutations and larger genomic alterations such as insertions, deletions, inversions and translocations, all of which make these diseased tissues dissimilar from healthy ones. Some mutations—driver mutations—lead a cancer to grow, spread and, often, take a patient’s life. Passenger mutations tend to not contribute to cancer growth.

The ability to discern between the two types of mutations can lead to a deeper understanding of cancer biology and empower the development of cancer therapeutics. But the complexity of cancer genomes does not make it easy for researchers to tell drivers and passengers apart. As second-generation sequencing matures, new tools and approaches are helping scientists discover what drives a given cancer.

Who could be driving?

There are around 100 genes that are known cancer drivers. When researchers look across the sequences of many tumor samples, they will find ‘mountains’, which are mutations occurring in many tumors. One such highly mutated driver is TP53, the gene encoding tumor protein p53; Kirsten rat sarcoma viral oncogene homolog (KRAS) is another.

Large-scale cancer genome sequencing projects such as The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) have created well-endowed gene catalogs and portals for the research community to use that render visible this variation in mutation frequency. As these projects reach the end of their first chapters, there are various ways to leverage these catalogs, hunt for signals of drivers in the data, and develop new methods and approaches.

Is there a rule for picking driver signals?

As a small lab, Kinzler says he, Bert Vogelstein and their colleagues do not sequence thousands of tumors at a time, nor do they have a large group of biostatisticians at their disposal. They have decided to focus on the genes that are “unequivocally, clearly driver genes,” Kinzler says.

They apply what they call the ratiometric rule, which is about mutation patterns as opposed to mutation frequencies. The rule distinguishes between oncogenes, which need to be hyperactive to cause cancer, and tumor suppressor genes, which cause cancer when they stop working. For an oncogene, 20% of the recorded mutations in the gene must occur at the same position and cause a single switched amino acid in the protein that the gene encodes. For a tumor suppressor gene, more than 20% of the mutations in the gene must be clearly inactivating.

Kinzler sees advantages to this ratiometric approach over other methods, which have “pretty significant false discovery rates”—perhaps even as high 10%, he says—which can skew a list of driver genes. “It’s a question of what you want your list to look like.”

Are there noncoding driver mutations?

Many approaches mainly analyze regions in the genome that encode proteins and that can be mutated to give overactive or defective forms. But recent studies indicate that noncoding regions of the genome, which can be responsible for regulating gene activity, might also harbor cancer drivers. Noncoding drivers could potentially outnumber coding ones, say Lawrence and Getz. But for now, the community is “completely blind to them” because whole-exome sequencing has been the workhorse to date.

The focus on coding regions has been a practical one. As a way to hold costs down, most cancer genome sequencing projects have focused on exome sequencing, says Lopez-Bigas. “Now with the focus and economics shifting to whole-genome sequencing, we’re all under the gun to get our act together beyond the splice sites,” say Lawrence and Getz.

A team of scientists at the Broad Institute, Dana-Farber Cancer Institute, Harvard Medical School and MD Anderson Cancer Center describe two highly recurrent mutations in melanoma that lie outside of protein-coding regions.

Specifically, they found two somatic mutations in a regulatory region, the promoter of the telomerase reverse transcriptase gene (TERT). They note that in addition to coding sequences, recurrent somatic mutations in regulatory genomic regions “may represent important driver events in cancer.”

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Scientists can then launch their analysis from positive clinical response—a phenotype—and work their way back to these patients’ genome to hunt for reasons that explain these different, positive responses. Finding driver mutations in cancer is a challenge and will stay important. In some cases, finding these mutations can be exceptionally good news.

Reference:

Cancer genomes: discerning drivers from passengers. Nature Methods. 2014;11:375-379

Cancer Genome Landscapes.Science.2013;339:1546–1558.

Highly Recurrent TERT Promoter Mutations in Human Melanoma.Science.2013;339:957-959

Network-based stratification (NBS) enables the subtyping of tumors

Identifying molecular markers that stratify tumor samples into meaningful subtypes is an important goal in cancer genomics. Ideally, these subtypes correlate with clinical features, such as the aggressiveness of a tumor or response to drugs, and thus can be used to guide treatment. Early successes in defining such subtypes include the identification of translocations in leukemias, ERRB2 (HER2) amplification in a subset of breast cancers, and others. Since the introduction in the late 1990s of microarray techniques, there has been an explosion of studies to define subtypes according to gene expression signatures. This work has led to some notable successes; but in many cancers, signatures or clinical correlations identified in one study were not reproduced in other studies.

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Hofree et al. introduce a novel approach to stratify patients on the basis of the somatic mutations present in their tumors. Cancer is a disease driven by such somatic mutations, which accumulate in the genome during the lifetime of the individual. Recent advances in high-throughput DNA sequencing technologies now enable whole-genome or whole-exome measurement of somatic mutations. In particular, The Cancer Genome Atlas (TCGA) is using whole-exome sequencing to measure somatic mutations in protein-coding regions of genomes from ~500 samples from each of ~25 cancer types. Similar projects are underway by other groups, including dozens of national consortia under the umbrella of the International Cancer Genome Consortium.

The initial results from these large-scale sequencing studies demonstrated a major impediment to the use of somatic mutations for patient stratification, namely, cancers exhibit extensive mutational heterogeneity, with mutated genes varying widely across individuals. Moreover, an individual cancer sample may have somatic mutations in only a few to a few dozen of the ~21,000 human genes. In other words, if one builds a somatic mutation profile for a sample, where each gene is assigned a 1 or a 0 if the gene is mutated or not mutated, respectively, then the resulting profiles will be sparse, or nearly all 0s . Consequently, comparison or clustering of such mutation profiles will not yield additional information beyond that revealed by direct examination of the handful of commonly mutated genes.

Hofree et al. apply NBS to somatic mutation data from TCGA studies of ovarian carcinoma, endometrial carcinoma and lung adenocarcinoma. On the ovarian and lung cancer data sets, NBS computes subtypes that discriminate the survival time of patients better than can subtypes derived from gene expression data. On the endometrial data set, NBS subtypes are closely associated with histological subtypes. Interestingly, although NBS significantly outperforms microarray-based gene expression for patient stratification, its gain over mRNA-Seq is smaller on the lung and endometrial data sets, suggesting an overall advantage for sequencing data (DNA or mRNA) over microarray data.

Given that driver mutations are by definition directly responsible for cancer, one might anticipate that mutation profiles, or network-smoothed mutation profiles, would provide more functional insights than would gene expression signatures.Not all genes in the NBS subtype networks are well-known cancer genes: on the contrary, some are proposed to be genes containing an unusually high number of random, ‘passenger’ mutations.

NBS makes it possible to derive clinically and biologically meaningful subtypes directly from whole-exome and whole-genome cancer sequencing data sets. As these data sets continue to increase in size and scope, NBS may have a prominent role in cancer research and in precision oncology.

Reference:

Making connections: using networks to stratify human tumors.  Nature methods. 2013; 10:1077-1078

Insight into one single cell

Single-cell genome and transcriptome sequencing methods are generating a fresh wave of biological insights into development, cancer and neuroscience. Kelly Rae Chi reports in Nature Methods.

As reported in the article, one of several groups applying single-cell genome sequencing to IVF, Sunney Xie at Harvard University and his collaborators have tested their new whole-genome amplification methods on the first and second polar bodies, small cellular castoffs of the fertilized donor egg that reflect its chromosomal health. In a recent paper, Xie’s team showed that in eight female donors, polar-body biopsy and single-cell sequencing could correctly infer both embryo aneuploidy—too many chromosomes, as in the case of Down’s syndrome, or too few—and single-nucleotide variations inherited from either parent. Detecting aneuploidy may require sequencing as little as one out of every hundred genomic regions on average, making the strategy cheaper and more accurate than traditional methods, Xie says.

Xie and his collaborators on the paper, Fuchou Tang of Peking University and Jie Qiao of Peking University Third Hospital, have launched a clinical study of women undergoing IVF. The team will amplify and sequence whole genomes of the polar bodies of participants’ embryos to see whether they are fit for transfer. Such a step toward the clinic seemed impossible only 2 years ago, says Xie, adding that people desperate to have a baby free of a devastating genetic disorder have been e-mailing him. The study’s first baby could be born within the year. “I didn’t anticipate that [our technique] would be used so quickly for patients,” he says.

Single-cell sequencing

Single-cell sequencing is no small feat. The amount of DNA or RNA in a single cell starts at a few picograms—not even close to the quantity that today’s sequencing machines demand. So scientists must amplify these molecules and do so in ways that minimize technical errors while surveying sequences as broadly and evenly as possible. Until recently, many researchers doubted that sequencing of single cells could be reliably conducted by any but a few experts.

Although a handful of groups sowed the seeds for single-cell genome and transcriptome sequencing approaches years ago, the methods have more recently started to make their way to the masses, and a community has formed around their application in areas including neuroscience, cancer and microbial ecology. “Almost since the first day that PCR was invented, people began trying to use it to do single-cell gene expression and genome analysis,” says Stephen Quake at Stanford University, cofounder of Fluidigm. “But [single-cell sequencing] really is just taking off for a bunch of reasons.”

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From a few molecules of RNA

Sequencing a cell’s transcriptome hinges on the ability to amplify large amounts of the complementary DNA (cDNA) that is synthesized from RNA. Capturing small amounts of RNA as cDNA and amplifying the cDNA extensively are difficult to do evenly and efficiently.

In 1990, transcriptome analysis at the resolution of single cells was made possible by Norman Iscove’s group, who amplified cDNAs exponentially using PCR. In the early 1990s, Eberwine and his colleagues came up with a technique that generated cDNA from single live neurons and performed linear amplification by transcribing RNA from the cDNA. With the advent of microarrays, scientists used both linear and exponential amplification strategies to identify differences in gene expression among single cells.

High-throughput RNA sequencing (RNA-seq) came onto the scene in 2008, and shortly after, researchers coupled it to such amplification techniques to get a more detailed look at single-cell transcriptomes. For a 2009 study, Tang, then working in M. Azim Surani’s laboratory at the Gurdon Institute at the University of Cambridge, showed that it was possible to detect—from a single mouse blastomere—the expression of thousands more genes than had been revealed using microarrays .

Amplifying the genome

Developing a way to amplify whole genomes of single cells took a bit longer because only one or two unique copies of DNA exist in the cell. The method lagged behind RNA amplification until 2005, when Roger Lasken’s group became the first to amplify and sequence DNA from a single cell, that of an Escherichia coli bacterium, using the multiple displacement amplification (MDA) method that they had developed. That sparked a vigorous effort by microbiologists to generate reference genomes for diverse, uncultivable bacterial species.

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The cellular patchwork of cancer

From prognostics to disease monitoring, cancer research stands to benefit enormously from single-cell sequencing approaches. Cancer cells often undergo high mutation rates, and tumors tend to be heterogeneous. Identifying which subsets of cells, called clones, are present and evolve into metastases or respond in a certain way to chemotherapy is critical to understanding and fighting the disease. In particular, circulating tumor cells (CTCs)—which break off from a tumor and seed a cancer’s metastasis—are those rare cells whose genomes or transcriptomes might offer clues for diagnosis, monitoring or treatment.

Reference:

Singled out for sequencing. Nature Methods. 2014;11:13-17

mRNA-Seq whole-transcriptome analysis of a single cell. Nature Methods.2009;6:377-382

Insight into Immunotherapy: Research Review and Drug Discovery

Immunotherapy is just a concept for a long while, and real advances in our understanding about how to do this have been made in recent years. Scientists now learn the cancer microenvironment plays essential roles in cancer growth, cancer spread and responses to therapy, and involves cells and molecules of the immune system implementing fundamental functions.  Also, they learn how Tumors make use of these control mechanisms to evade an attack from the immune system.

The immune system is recruited to specifically target cancer cells for therapeutic purposes. It shows promise for causing long-lasting regression and preventing relapse in cancer patients, by means of Tumor-specific immunological memory. Scientists investigate immunomodulatory mechanism of Tumors, including the blockage of immune checkpoints, in order to enhance anti-cancer immune responses.

The composition and characteristics of the cancer microenvironment are important in determining the anti-Tumor immune response. For example, certain cells of the immune system, such as effector T cells, dendritic cells (DCs), and natural killer cells, are capable of driving potent anti-Tumor responses. However, Tumor cells often make their microenvironment immunosuppressive, and thereby favour the development of immunosuppressive populations of immune cells, such as regulatory T cells.

Recent research reviews

12 representative citations, focusing on Tumor immunology & immunotherapy, are specifically retrieved from Nature Reviews Cancer (IF=35,2013 year)and Nature Reviews Immunology(IF=33,2013 year) , and are listed as follows. They are available for describing research progress in understanding the complexity of the immune system in cancer biology and the promise of immunotherapy.

Research Reviews by Year(2012-2014)

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Novel Drug Discovery

There are more than a hundred other trials going on for cancer, a large number of them for immunotherapy drugs. As we know, significant immunotherapy compounds include Merck’s MK3475 for melanoma and other cancers, Roche’s MPDL3280A for lung cancer, and Bristol-Myers Squibb’s Elotuzumab. Many of these drugs are based on a discovery made two decades ago, called immune checkpoints, used by the body to prevent the attack of normal cells by the immune system.

Immune checkpoints are used to prevent the body from rejecting cells that are beneficial. While cancer cells use this mechanism to trick the immune system, and companies are developing drugs to stop the cancer cells from exploiting immune checkpoints.

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References:

1. Tumor immunotherapy — leukocytes take up the fight. Nat Rev Immunol. 2012 Apr;12(4):237.

2. Sepsis-induced immunosuppression: from cellular dysfunctions to immunotherapy. Nat Rev Immunol. 2013 Dec;13(12):862-74.

3. Immunotherapy: Cancer mutation-specific immune responses. Nat Rev Cancer. 2014 May 23;14(6):387.

Early monitoring of cancer

Angiogenesis is a fundamental physiological process to form new blood vessel to support cancer growth and development by providing nutrients and oxygen. It occurs for almost all solid tumors such as glioblastoma(GBM) and thus anti-angiogenesis therapeutics are increasingly applied to treat various cancers. GBM is the most aggressive primary malignant brain tumor in humans with a 5-year survival rate under 5% and median overall survival of only 12–14 months . GBM features rich vascularization due to the high expression of various pro-angiogenic factors, which makes anti-angiogenesis as an attractively newly emerging targeted therapy strategy of GBM, although the standard treatments of GBM are still surgical operation, radiotherapy, and chemotherapy at present.

For instance, vascular endothelial growth factor inhibitor, bevacizumab, has been the sole anti-angiogenesis targeted therapeutic licensed by the FDA for use in GBM. In order to discover more effective anticancer agents, multi-targeted tyrosine kinase inhibitors (TKIs), such as Sunitinib, are being under clinical investigations owing to their antitumor capabilities via the pathways of anti-angiogenesis as well as anti-proliferation. Sunitinib (marketed as Sutent by Pfizer, and previously known as SU11248) is an oral, small-molecule, multi-targeted TKI that was approved by the FDA for the treatment of renal cell carcinoma (RCC) and imatinib-resistant gastrointestinal stromal tumor (GIST) on January 26, 2006. Sunitinib was the first cancer drug simultaneously approved for two different indications. Sunitinib as antiangiogenic therapeutic has already been used to treat renal carcinoma, gastrointestinal stromal tumors, lung cancer, and other solid tumors.

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Xiao bao at Fudan University Shanghai Cancer Center, Shanghai, published an article aimed to monitor early treatment response of Sunitinib in U87MG models mimicking glioblastoma multiforme by longitudinal 18F-FLT microPET/CT imaging. Immunohistochemistry results show

representative tumor sections of haematoxylin and eosin (H&E), CD31, and Ki-67 staining for the control and Sunitinib groups on days 0,1,3,7,and13 after therapy. CD31-positive staining was broadly observed in all untreated tumor sections, which demonstrated relatively abundant microvessel density (MVD). Ater Sunitinib treatment, the MVD level in tumor sections decreased remarkably, which indicated effective anti-angiogenic activity of the drug.

Reference:

Early Monitoring Antiangiogenesis Treatment Response of Sunitinib in U87MG Tumor Xenograft by (18)F-FLT MicroPET/CT Imaging. Biomed Res Int. 2013;2013:218578.

Cancer vaccine: leading to further improved clinical outcomes

Unlike prophylactic vaccines that are generally administered to healthy individuals, cancer vaccines are aiming at treating existing cancer or preventing the development of cancer in certain high-risk individuals. Vaccines that treat existing cancer are known as therapeutic cancer vaccines; therapeutic cancer vaccines are administered to cancer patients and are designed to eradicate cancer cells through strengthening the patient’s own immune responses. The various immune effector mechanisms mobilized by therapeutic vaccination specifically attack and destroy cancer cells and spare normal cells. Thus, therapeutic cancer vaccines, in principle, may be utilized to inhibit further growth of advanced cancers and/or relapsed tumors that are refractory to conventional therapies such as surgery, radiation therapy, and chemotherapy.

In a review of cancer vaccine, scientists mentioned the most of the cancer vaccines such DC vaccines. DCs(Dendritic cells) are the most potent professional antigen-presenting cells (APCs). They act as sentinels at peripheral tissues where they uptake, process, and present pathogen- or host-derived antigenic peptides to naive T lymphocytes at the lymphoid organs in the context of major histocompatibility (MHC). Scientists generated DCs vaccines ex vivo through loading tumor-associated antigen(TTA) to patients’ autologous DCs that are simultaneously treated with adjuvants. DC vaccines that may be used alone or in combination with conventional therapies such as radiotherapy.

TUMOR-INDUCED IMMUNE SUPPRESSION

Active immunization with therapeutic vaccines generally targets the host DCs for effective presentation of tumor-associated antigens and subsequent priming of CD8þ CTLs and CD4þ T helper cells. These tumor-specific T effector cells together with other innate immune cells can result in inhibition or destruction of cancer cells. In the tumor microenvironment, cancer cells produce immunosuppressive soluble factors (TGF- , IL-10, IDO, galectin, and VEGF) and expand or recruit immune regulatory cells (MDSCs, Tregs, and TAMs), which establish an immunosuppressive state at the tumor site. This complex molecular and cellular network attenuates vaccine-induced antitumor immune responses and promotes tumor escape from immune attack. To overcome the immune suppressive mechanisms, novel immune modulators (anti-CTLA-4 and anti-PD1 antibodies) may be used to enhance vaccine potency and restore durable antitumor immunity. Cancer vaccines can also be combined with conventional cancer treatments, such as radiotherapy and chemotherapy, to engage multivalent antitumor effects for optimized therapeutic efficacy.

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Effective, safe, and enduring cancer treatments constitute major challenges of medical sciences, with therapeutic cancer vaccines emerging as attractive approaches for provoking long-lasting protective antitumor immunity. Strategically combining vaccine strategies with other agents or approaches that synergistically enhance antitumor immunity and/or engage complementary antitumor responses should also lead to further improved clinical outcomes.

Reference:

Therapeutic cancer vaccines: past, present, and future. Adv Cancer Res. 2013;119:421-75

A patient-selection strategy for the clinical development of MCL1 inhibitors

Inhibition of apoptosis is a critical step in the pathogenesis of cancers, and is a major barrier to effective treatment. It is now thought that one or more components of the apoptosis pathway are dysregulated in all cancers either by genetic mutation of the genes encoding these proteins (e.g., point mutations, copy-number abnormalities, or chromosomal translocation) or by other mechanisms (e.g., epigenetic mechanisms or upstream oncogenic mutations). Despite this central importance in the development and maintenance of cancer, few apoptosis-targeted therapeutics have reached clinical evaluation.

MCL1, which encodes the anti-apoptotic protein MCL1, is among the most frequently amplified genes in human cancer. A chemical genomic screen identified compounds, including anthracyclines, that decreased MCL1 expression. Genomic profiling indicated that these compounds were global transcriptional repressors that preferentially affect MCL1 due to its short mRNA half-life. Transcriptional repressors and MCL1 shRNAs induced apoptosis in the same cancer cell lines and could be rescued by physiological levels of ectopic MCL1 expression. Repression of MCL1 released the pro-apoptotic protein BAK from MCL1, and Bak deficiency conferred resistance to transcriptional repressors. A computational model, validated in vivo, indicated that high BCL-xL expression confers resistance to MCL1 repression, thereby identifying a patient-selection strategy for the clinical development of MCL1 inhibitors.

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Dr Guo Wei et al. have elucidated a strategy for the development of MCL1 inhibitors as cancer therapeutics. The multiplexed, gene-expression-based high-throughput screening approach holds promise for the future discovery of specific inhibitors of MCL1 expression and for the use of chemical genomic approaches to elucidate small-molecule mechanisms of action. Their study also highlights the power of genomically characterized cell lines for the discovery of predictive biomarkers of drug response. Most immediately, their work suggests an approach to the clinical development of any MCL1 inhibitor in breast and NSCLC tumors, focusing on tumors expressing low levels of BCL-xL as a patient-selection strategy.

Reference:

Chemical genomics identifies small-molecule MCL1 repressors and BCL-xL as a predictor of MCL1 dependency. Cancer Cell. 2012 Apr 17;21(4):547-62.