Purpose: Translating the cancer genome into highly efficacious targets to guide rational therapeutic combinations is a major emerging challenge.

Methods: We established an in silico bioinformatic platform in parallel with a high throughput screening platform evaluating the pharmacological activity of 37 novel targeted agents across 669 highly characterized cell lines representing the genetic and tumor-type heterogeneity of human cancers. Analysis of large scale pharmacological data coupled to massive sequencing data on cell lines was performed to systematically identify combinatorial biomarkers of sensitivity and resistance to cancer therapeutics. Genomic predictors discovered in a 141 cell line training set were validated in an independent non-overlapping test set of 359 cell lines screened on 14 of the compounds.

Results: We demonstrate combinations of genomic events that are co-occurring or mutually exclusive and act as co-drivers in various tumors, representing potential targets for combinatorial intervention in cancer. We find that multiple cooperating genomic events predict response to drug intervention independent of tumor lineage.

Conclusions: The coupling of scalable in silico and functional 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 prevent the emergence of resistance.

Citation Format: Adel Tabchy, Nevine Eltonsy, Gordon B. Mills. Systematic identification of combinatorial markers of drug sensitivity in cancer cell lines. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 2218. doi:10.1158/1538-7445.AM2013-2218