Author
Vic E. Myer
Other affiliations: Yale University, Howard Hughes Medical Institute
Bio: Vic E. Myer is an academic researcher from Novartis. The author has contributed to research in topics: Genome editing & Cas9. The author has an hindex of 24, co-authored 39 publications receiving 13226 citations. Previous affiliations of Vic E. Myer include Yale University & Howard Hughes Medical Institute.
Topics: Genome editing, Cas9, Wnt signaling pathway, Messenger RNA, Cancer
Papers
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TL;DR: The results indicate that large, annotated cell-line collections may help to enable preclinical stratification schemata for anticancer agents and the generation of genetic predictions of drug response in the preclinical setting and their incorporation into cancer clinical trial design could speed the emergence of ‘personalized’ therapeutic regimens.
Abstract: The systematic translation of cancer genomic data into knowledge of tumour biology and therapeutic possibilities remains challenging. Such efforts should be greatly aided by robust preclinical model systems that reflect the genomic diversity of human cancers and for which detailed genetic and pharmacological annotation is available. Here we describe the Cancer Cell Line Encyclopedia (CCLE): a compilation of gene expression, chromosomal copy number and massively parallel sequencing data from 947 human cancer cell lines. When coupled with pharmacological profiles for 24 anticancer drugs across 479 of the cell lines, this collection allowed identification of genetic, lineage, and gene-expression-based predictors of drug sensitivity. In addition to known predictors, we found that plasma cell lineage correlated with sensitivity to IGF1 receptor inhibitors; AHR expression was associated with MEK inhibitor efficacy in NRAS-mutant lines; and SLFN11 expression predicted sensitivity to topoisomerase inhibitors. Together, our results indicate that large, annotated cell-line collections may help to enable preclinical stratification schemata for anticancer agents. The generation of genetic predictions of drug response in the preclinical setting and their incorporation into cancer clinical trial design could speed the emergence of 'personalized' therapeutic regimens.
6,417 citations
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TL;DR: This study uses a chemical genetic screen to identify a small molecule, XAV939, which selectively inhibits β-catenin-mediated transcription and reveals new mechanistic insights into the regulation of axin protein homeostasis, which presents new avenues for targeted Wnt pathway therapies.
Abstract: The stability of the Wnt pathway transcription factor -catenin is tightly regulated by the multi-subunit destruction complex. Deregulated Wnt pathway activity has been implicated in many cancers, making this pathway an attractive target for anticancer therapies. However, the development of targeted Wnt pathway inhibitors has been hampered by the limited number of pathway components that are amenable to small molecule inhibition. Here, we used a chemical genetic screen to identify a small molecule, XAV939, which selectively inhibits -catenin-mediated transcription. XAV939 stimulates -catenin degradation by stabilizing axin, the concentration-limiting component of the destruction complex. Using a quantitative chemical proteomic approach, we discovered that XAV939 stabilizes axin by inhibiting the poly-ADP-ribosylating enzymes tankyrase 1 and tankyrase 2. Both tankyrase isoforms interact with a highly conserved domain of axin and stimulate its degradation through the ubiquitin-proteasome pathway. Thus, our study provides new mechanistic insights into the regulation of axin protein homeostasis and presents new avenues for targeted Wnt pathway therapies.
1,829 citations
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TL;DR: It is shown that cellular uptake of L-glutamine and its subsequent rapid efflux in the presence of essential amino acids (EAA) is the rate-limiting step that activates mTOR.
1,540 citations
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TL;DR: Together, these results provide new insights into resistance mechanisms involving the MAPK pathway and articulate an integrative approach through which high-throughput functional screens may inform the development of novel therapeutic strategies.
Abstract: Oncogenic mutations in the serine/threonine kinase B-RAF (also known as BRAF) are found in 50-70% of malignant melanomas. Pre-clinical studies have demonstrated that the B-RAF(V600E) mutation predicts a dependency on the mitogen-activated protein kinase (MAPK) signalling cascade in melanoma-an observation that has been validated by the success of RAF and MEK inhibitors in clinical trials. However, clinical responses to targeted anticancer therapeutics are frequently confounded by de novo or acquired resistance. Identification of resistance mechanisms in a manner that elucidates alternative 'druggable' targets may inform effective long-term treatment strategies. Here we expressed ∼600 kinase and kinase-related open reading frames (ORFs) in parallel to interrogate resistance to a selective RAF kinase inhibitor. We identified MAP3K8 (the gene encoding COT/Tpl2) as a MAPK pathway agonist that drives resistance to RAF inhibition in B-RAF(V600E) cell lines. COT activates ERK primarily through MEK-dependent mechanisms that do not require RAF signalling. Moreover, COT expression is associated with de novo resistance in B-RAF(V600E) cultured cell lines and acquired resistance in melanoma cells and tissue obtained from relapsing patients following treatment with MEK or RAF inhibitors. We further identify combinatorial MAPK pathway inhibition or targeting of COT kinase activity as possible therapeutic strategies for reducing MAPK pathway activation in this setting. Together, these results provide new insights into resistance mechanisms involving the MAPK pathway and articulate an integrative approach through which high-throughput functional screens may inform the development of novel therapeutic strategies.
1,326 citations
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TL;DR: A large-scale RNAi screen is conducted in which viability effects of mRNA knockdown were assessed for 7,837 genes using an average of 20 shRNAs per gene in 398 cancer cell lines, outlining the classes of cancer dependency genes and their relationships to genetic, expression, and lineage features.
494 citations
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TL;DR: A practical guide to the analysis and visualization features of the cBioPortal for Cancer Genomics, which makes complex cancer genomics profiles accessible to researchers and clinicians without requiring bioinformatics expertise, thus facilitating biological discoveries.
Abstract: The cBioPortal for Cancer Genomics (http://cbioportal.org) provides a Web resource for exploring, visualizing, and analyzing multidimensional cancer genomics data. The portal reduces molecular profiling data from cancer tissues and cell lines into readily understandable genetic, epigenetic, gene expression, and proteomic events. The query interface combined with customized data storage enables researchers to interactively explore genetic alterations across samples, genes, and pathways and, when available in the underlying data, to link these to clinical outcomes. The portal provides graphical summaries of gene-level data from multiple platforms, network visualization and analysis, survival analysis, patient-centric queries, and software programmatic access. The intuitive Web interface of the portal makes complex cancer genomics profiles accessible to researchers and clinicians without requiring bioinformatics expertise, thus facilitating biological discoveries. Here, we provide a practical guide to the analysis and visualization features of the cBioPortal for Cancer Genomics.
10,947 citations
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Memorial Sloan Kettering Cancer Center1, University of Kiel2, Institut Gustave Roussy3, Netherlands Cancer Institute4, The Royal Marsden NHS Foundation Trust5, University of Zurich6, University of Tübingen7, University of Manchester8, University of Paris9, University of Duisburg-Essen10, University of California, Los Angeles11, Vanderbilt University12, University of Pittsburgh13, University of Nantes14, Plexxikon15, Hoffmann-La Roche16, Genentech17, Harvard University18, Peter MacCallum Cancer Centre19
TL;DR: Vemurafenib produced improved rates of overall and progression-free survival in patients with previously untreated melanoma with the BRAF V600E mutation in a phase 3 randomized clinical trial.
Abstract: At 6 months, overall survival was 84% (95% confidence interval [CI], 78 to 89) in the vemurafenib group and 64% (95% CI, 56 to 73) in the dacarbazine group. In the interim analysis for overall survival and final analysis for progression-free survival, vemurafenib was associated with a relative reduction of 63% in the risk of death and of 74% in the risk of either death or disease progression, as compared with dacarbazine (P<0.001 for both comparisons). After review of the interim analysis by an independent data and safety monitoring board, crossover from dacarbazine to vemurafenib was recommended. Response rates were 48% for vemurafenib and 5% for dacarbazine. Common adverse events associated with vemurafenib were arthralgia, rash, fatigue, alopecia, keratoacanthoma or squamous-cell carcinoma, photosensitivity, nausea, and diarrhea; 38% of patients required dose modification because of toxic effects. Conclusions Vemurafenib produced improved rates of overall and progression-free survival in patients with previously untreated melanoma with the BRAF V600E mutation. (Funded by Hoffmann–La Roche; BRIM-3 ClinicalTrials.gov number, NCT01006980.)
6,773 citations
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TL;DR: A combination of automated approaches and expert curation is used to develop a collection of "hallmark" gene sets, derived from multiple "founder" sets, that conveys a specific biological state or process and displays coherent expression in MSigDB.
Abstract: The Molecular Signatures Database (MSigDB) is one of the most widely used and comprehensive databases of gene sets for performing gene set enrichment analysis. Since its creation, MSigDB has grown beyond its roots in metabolic disease and cancer to include >10,000 gene sets. These better represent a wider range of biological processes and diseases, but the utility of the database is reduced by increased redundancy across, and heterogeneity within, gene sets. To address this challenge, here we use a combination of automated approaches and expert curation to develop a collection of “hallmark” gene sets as part of MSigDB. Each hallmark in this collection consists of a “refined” gene set, derived from multiple “founder” sets, that conveys a specific biological state or process and displays coherent expression. The hallmarks effectively summarize most of the relevant information of the original founder sets and, by reducing both variation and redundancy, provide more refined and concise inputs for gene set enrichment analysis.
6,062 citations
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John N. Weinstein1, John N. Weinstein2, Eric A. Collisson3, Gordon B. Mills2 +376 more•Institutions (31)
TL;DR: The Pan-Cancer initiative compares the first 12 tumor types profiled by TCGA with a major opportunity to develop an integrated picture of commonalities, differences and emergent themes across tumor lineages.
Abstract: The Cancer Genome Atlas (TCGA) Research Network has profiled and analyzed large numbers of human tumors to discover molecular aberrations at the DNA, RNA, protein and epigenetic levels. The resulting rich data provide a major opportunity to develop an integrated picture of commonalities, differences and emergent themes across tumor lineages. The Pan-Cancer initiative compares the first 12 tumor types profiled by TCGA. Analysis of the molecular aberrations and their functional roles across tumor types will teach us how to extend therapies effective in one cancer type to others with a similar genomic profile.
5,294 citations
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TL;DR: In this paper, the authors present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macro-autophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes.
Abstract: In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes.
For example, a key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process versus those that measure flux through the autophagy pathway (i.e., the complete process including the amount and rate of cargo sequestered and degraded). In particular, a block in macroautophagy that results in autophagosome accumulation must be differentiated from stimuli that increase autophagic activity, defined as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (in most higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. It is worth emphasizing here that lysosomal digestion is a stage of autophagy and evaluating its competence is a crucial part of the evaluation of autophagic flux, or complete autophagy.
Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. Along these lines, because of the potential for pleiotropic effects due to blocking autophagy through genetic manipulation, it is imperative to target by gene knockout or RNA interference more than one autophagy-related protein. In addition, some individual Atg proteins, or groups of proteins, are involved in other cellular pathways implying that not all Atg proteins can be used as a specific marker for an autophagic process. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular assays, we hope to encourage technical innovation in the field.
5,187 citations