Alterations in cancer genomes strongly influence clinical responses to treatment and in many instances are potent biomarkers for response to drugs. The Genomics of Drug Sensitivity in Cancer (GDSC) database (www.cancerRxgene.org) is the largest public resource for information on drug sensitivity in cancer cells and molecular markers of drug response. Data are freely available without restriction. GDSC currently contains drug sensitivity data for almost 75 000 experiments, describing response to 138 anticancer drugs across almost 700 cancer cell lines. To identify molecular markers of drug response, cell line drug sensitivity data are integrated with large genomic datasets obtained from the Catalogue of Somatic Mutations in Cancer database, including information on somatic mutations in cancer genes, gene amplification and deletion, tissue type and transcriptional data. Analysis of GDSC data is through a web portal focused on identifying molecular biomarkers of drug sensitivity based on queries of specific anticancer drugs or cancer genes. Graphical representations of the data are used throughout with links to related resources and all datasets are fully downloadable. GDSC provides a unique resource incorporating large drug sensitivity and genomic datasets to facilitate the discovery of new therapeutic biomarkers for cancer therapies.

Clinical responses to anticancer therapies are often restricted to a subset of patients. In some cases, mutated cancer genes are potent biomarkers of response to targeted agents. To uncover new biomarkers of sensitivity and resistance to cancer therapeutics, we screened a panel of several hundred cancer cell lines, which represent much of the tissue-type and genetic diversity of human cancers, with 130 drugs under clinical and preclinical investigation. In aggregate, we found mutated cancer genes were associated with cellular response to most currently available cancer drugs. Classic oncogene addiction paradigms were modified by additional tissue-specific or expression biomarkers, and some frequently mutated genes were associated with sensitivity to a broad range of therapeutic agents. Unexpected relationships were revealed, including the marked sensitivity of Ewing’s sarcoma cells harboring the EWS-FLI1 gene translocation to PARP inhibitors. By linking drug activity to the functional complexity of cancer genomes, systematic pharmacogenomic profiling in cancer cell lines provides a powerful biomarker discovery platform to guide rational cancer therapeutic strategies.

SummarySystematic studies of cancer genomes have provided unprecedented insights into the molecular nature of cancer. Using this information to guide the development and application of therapies in the clinic is challenging. Here, we report how cancer-driven alterations identified in 11,289 tumors from 29 tissues (integrating somatic mutations, copy number alterations, DNA methylation, and gene expression) can be mapped onto 1,001 molecularly annotated human cancer cell lines and correlated with sensitivity to 265 drugs. We find that cell lines faithfully recapitulate oncogenic alterations identified in tumors, find that many of these associate with drug sensitivity/resistance, and highlight the importance of tissue lineage in mediating drug response. Logic-based modeling uncovers combinations of alterations that sensitize to drugs, while machine learning demonstrates the relative importance of different data types in predicting drug response. Our analysis and datasets are rich resources to link genotypes with cellular phenotypes and to identify therapeutic options for selected cancer sub-populations.

SUMMARY K-Ras mutations occur frequently in epithelial cancers. Using shRNAs to deplete K-Ras in lung and pancreatic cancer cell lines harboring K-Ras mutations, two classes were identified—lines that do or do not require K-Ras to maintain viability. Comparing these two classes of cancer cells revealed a gene expression signature in K-Ras-dependent cells, associated with a well-differentiated epithelial phenotype, which was also seen in primary tumors. Several of these genes encode pharmacologically tractable proteins, such as Syk and Ron kinases and integrin beta6, depletion of which induces epithelial-mesenchymal transformation (EMT) and apoptosis specifically in K-Ras-dependent cells. These findings indicate that epithelial differentiation and tumor cell viability are associated, and that EMT regulators in “K-Ras-addicted” cancers represent candidate therapeutic targets. SIGNIFICANCE K-Ras is the most frequently mutated oncogene in solid tumors and when aberrantly activated, is a potent tumor initiator. However, the identification of the critical effectors of K-Ras-mediated tumorigenesis and the development of clinically effective therapeutic strategies in this setting remain challenging. We have found that cancer cell lines harboring K-Ras mutations can be broadly classified into K-Ras-dependent and K-Ras-independent groups. By establishing a gene expression signature that can distinguish these two groups, we identified genes that are specifically up-regulated in K-Ras-dependent cells and are required for their viability. Therefore, the K-Ras dependency signature has revealed several potential therapeutic targets in a subset of otherwise pharmacologically intractable human cancers.

Targeted cancer therapies have produced substantial clinical responses but most tumors develop resistance to these drugs. Here we describe a pharmacogenomic platform that facilitates rapid discovery of drug combinations that can overcome resistance. We established cell culture models derived from biopsy samples of lung cancer patients whose disease had progressed while on treatment with EGFR or ALK tyrosine kinase inhibitors and then subjected these cells to genetic analyses and a pharmacological screen. Multiple effective drug combinations were identified. For example, the combination of ALK and MEK inhibitors was active in an ALK-positive resistant tumor that had developed a MAP2K1 activating mutation, and the combination of EGFR and FGFR inhibitors was active in an EGFR mutant resistant cancer with a novel mutation in FGFR3. Combined ALK and SRC inhibition was effective in several ALK-driven patient-derived models, a result not predicted by genetic analysis alone. With further refinements, this strategy could help direct therapeutic choices for individual patients.

Bromodomain inhibition comprises a promising therapeutic strategy in cancer, particularly for hematologic malignancies. To date, however, genomic biomarkers to direct clinical translation have been lacking. We conducted a cell-based screen of genetically-defined cancer cell lines using a prototypical inhibitor of BET bromodomains. Integration of genetic features with chemosensitivity data revealed a robust correlation between MYCN amplification and sensitivity to bromodomain inhibition. We characterized the mechanistic and translational significance of this finding in neuroblastoma, a childhood cancer with frequent amplification of MYCN. Genome-wide expression analysis demonstrated downregulation of the MYCN transcriptional program accompanied by suppression of MYCN transcription. Functionally, bromodomain-mediated inhibition of MYCN impaired growth and induced apoptosis in neuroblastoma. BRD4 knock-down phenocopied these effects, establishing BET bromodomains as transcriptional regulators of MYCN. BET inhibition conferred a significant survival advantage in three in vivo neuroblastoma models, providing a compelling rationale for developing BET bromodomain inhibitors in patients with neuroblastoma. Significance Biomarkers of response to small-molecule inhibitors of BET bromodomains, a new compound class with promising anti-cancer activity, have been lacking. Here, we reveal MYCN amplification as a strong genetic predictor of sensitivity to BET bromodomain inhibitors, demonstrate a mechanistic rationale for this finding, and provide a translational framework for clinical trial development of BET bromodomain inhibitors for pediatric patients with MYCN-amplified neuroblastoma.

Kinase inhibitors constitute an important new class of cancer drugs, whose selective efficacy is largely determined by underlying tumor cell genetics. We established a high-throughput platform to profile 500 cell lines derived from diverse epithelial cancers for sensitivity to 14 kinase inhibitors. Most inhibitors were ineffective against unselected cell lines but exhibited dramatic cell killing of small nonoverlapping subsets. Cells with exquisite sensitivity to EGFR, HER2, MET, or BRAF kinase inhibitors were marked by activating mutations or amplification of the drug target. Although most cell lines recapitulated known tumor-associated genotypes, the screen revealed lowfrequency drug-sensitizing genotypes in tumor types not previously associated with drug susceptibility. Furthermore, comparing drugs thought to target the same kinase revealed striking differences, predictive of clinical efficacy. Genetically defined cancer subsets, irrespective of tissue type, predict response to kinase inhibitors, and provide an important preclinical model to guide early clinical applications of novel targeted inhibitors.

SUMMARY KRAS is the most commonly mutated oncogene, yet no effective targeted therapies exist for KRAS mutant cancers. We developed a pooled shRNA-drug screen strategy to identify genes that, when inhibited, cooperate with MEK inhibitors to effectively treat KRAS mutant cancer cells. The anti-apoptotic BH3 family gene BCL-XL emerged as a top hit through this approach. ABT-263 (navitoclax), a chemical inhibitor that blocks the ability of BCL-XL to bind and inhibit pro-apoptotic proteins, in combination with a MEK inhibitor led to dramatic apoptosis in many KRAS mutant cell lines from different tissue types. This combination caused marked in vivo tumor regressions in KRAS mutant xenografts and in a genetically engineered KRAS-driven lung cancer mouse model, supporting combined BCL-XL/MEK inhibition as a potential therapeutic approach for KRAS mutant cancers.