Abstract PL03-01: Discovery of candidate biomarkers of anticancer drug sensitivity by high-throughput cell line screening.

Recent years have seen important progress in the development and application of targeted molecular therapeutics for treating cancer. These rationally designed drugs produce dramatic responses in a subset of treated patients. The paradigm established by the treatment of chronic myelogenous leukemia with Abl inhibitors has been expanded to other disease, or rather disease subtypes, albeit with often less life transforming outcomes. Some of the most encouraging progress has been recently achieved in the treatment of BRAF mutated tumors using RAF inhibitors and in diverse subtypes of non-small cell lung cancer bearing specific genetic alteration in EGFR or other receptor tyrosine kinase. In each case, a specific genetic alteration found in the tumors of a subset of patients affected by a given disease offers a unique opportunity for treatment. Consequently, the identification of additional sensitizing genotypes matched to specific treatment is a clear path for the continuous improvement of personalized cancer care. However, cancer heterogeneity, now understood at the molecular level, remains a major hurdle for the design and deployment of cancer therapeutics. Even in the best-understood cases the response to therapy is variable. For example, at least 20% of BRAF V600E melanoma patients do not demonstrate significant response to BRAF inhibitors therapy. Although many factors are likely to contribute to differences in treatment response, some genetic and epigenetic factors are likely to be cell autonomous. Systematic molecular characterization of human tumors, in particular using next-generation sequencing of genomes and transcriptomes, is yielding a comprehensive view of the heterogeneity of cancers at the molecular level. Moreover, it will soon be possible to characterize individual tumors at a similar level as part of a novel generation of diagnostics. To translate this knowledge into cancer care there is a need to understand how variations in genome and other dimensions (epigenome etc.) influence the therapeutic response and which of these variations might also constitute targeting opportunity. Building on the pioneering efforts of the national cancer institute using human tumor derived cell lines as tractable model for the study of drug sensitivity (the panel of 60 cell lines known as the NCI60) we have assembled a collection of 1,000 cell lines representative of the majority of adult and childhood cancers. The Wellcome Trust Sanger Institute has performed a genomic characterization of these cell lines encompassing the complete exon sequence of 70 cancer genes, as well as genome wide transcript and copy number variation analysis. Further characterization will yield full exome and transcriptome sequence information in the near future. We use this cell line collection to define molecular determinant of drug sensitivity in vitro as a first step towards defining biomarkers of drug response in patients. During the first phase of this international research program performed in collaboration with investigators at the Wellcome Trust Sanger Institute we have focused our screening efforts on molecules already clinically approved, in clinical development or on compounds issued from cutting-edge oncology programs in academia or industry. Sensitivity profiles were obtained across the cell line collection using a high-throughput screening platform measuring cellular viability. Strikingly, even when reduced to the in vitro environment of the cell culture our approach captures essentially all genotype-drug sensitivity associations reported to date and leveraged in the clinic through the most recent rationally designed therapies. In order to leverage the richness of the resulting dataset and start to define how the complex genomic making of the tumor cell can influence drug sensitivity we have adopted a multiplicity of statistical approaches. First, seeking to discover how single genetic events might strongly influence drug response we have used a multivariate analysis of variance (MANOVA) across the 70 most commonly mutated cancer genes and to determine preferential sensitivity of cancer sub-types. This analysis captured many of the known associations and revealed a large number of novel correlates of drug sensitivity. While a number of these associations between cancer gene mutation and drug sensitivity concern direct drug targets, many of them do not and are not readily explained by our current understanding of the mechanisms of cancer biology. In some cases these associations might correspond to lineage effects, whereby mutations enriched in a given cancer type are statistically linked to a drug sensitivity without direct mechanistic meaning. However, it is likely that in other cases this analysis identifies unexpected mechanistic links between the genes most commonly affected in human tumors and a large number of drugs currently used clinically. Perhaps related to the variations in therapeutic response observed even in selected patients treated with matched therapies, screening of many cell lines reveals a broad variation in sensitivity within lines of a given sensitizing genotype. For example, while BRAF mutant cell lines are, as a group, extremely sensitive to BRAF inhibition compared to almost all BRAF wt cell lines, a number of these lines are not sensitive to a panel of RAF and MEK1/2 inhibitors. Only in few instances are these unexpected resistances explained by a second mutation in a known mechanistically related gene (such as KRAS, or NRAS). Similarly, subsets of cell lines that do not bear the sensitizing genotype are sensitive to a given drug. To tackle this complexity we have adopted a multivariate linear regression approach incorporating copy number variations across 426 cancer genes and genome wide mRNA expression changes in addition to the available DNA sequence data. The models that have started to emerge describe the drug sensitivity more accurately than univariate models and give a unique perspective on the interaction between the cancer genome and the cellular response to cancer drugs. These genome “features” that are linked to drug sensitivity represent a plethora of candidate biomarkers and pathway nodes that could influence drug sensitivity upon targeting. Overall, our study has identified many novel sensitizing and drug resistance events that could lead to the development of biomarkers useful for the development and application of cancer therapeutics. We believe that such a large-scale drug profiling dataset soon to be made publicly available in its entirety will represent a rich resource to be used by the cancer research community. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2011 Nov 12-16; San Francisco, CA. Philadelphia (PA): AACR; Mol Cancer Ther 2011;10(11 Suppl):Abstract nr PL03-01.