Systematic Identification of Combinatorial Drivers and Targets in Cancer Cell Lines

Abstract

There is an urgent need to elicit and validate highly efficacious targets for combinatorial intervention from large scale ongoing molecular characterization efforts of tumors. We established an in silico bioinformatic platform in concert with a high throughput screening platform evaluating 37 novel targeted agents in 669 extensively characterized cancer cell lines reflecting the genomic and tissue-type diversity of human cancers, to systematically identify combinatorial biomarkers of response and co-actionable targets in cancer. Genomic biomarkers discovered in a 141 cell line training set were validated in an independent 359 cell line test set. We identified co-occurring and mutually exclusive genomic events that represent potential drivers and combinatorial targets in cancer. We demonstrate multiple cooperating genomic events that predict sensitivity to drug intervention independent of tumor lineage. The coupling of scalable in silico and biologic high throughput cancer cell line platforms for the identification of co-events in cancer delivers rational combinatorial targets for synthetic lethal approaches with a high potential to pre-empt the emergence of resistance.