Abstract

Abstract There is an urgent need in oncology to link molecular aberrations in tumors with therapeutics that can be administered in a personalized fashion. One approach identifies synthetic-lethal genetic interactions or emergent dependencies that cancer cells acquire in the presence of specific mutations. Using engineered isogenic cells, we generated an unbiased and quantitative chemical-genetic interaction map that measures the influence of 51 aberrant cancer genes on 90 drug responses. The dataset strongly predicts drug responses found in cancer cell line collections, indicating that isogenic cells can model more complex cellular contexts. Applied to triple-negative breast cancer, we report clinically actionable interactions with the MYC oncogene including resistance to AKT/PI3K pathway inhibitors and an unexpected sensitivity to dasatinib through LYN inhibition in a synthetic-lethal manner, providing new drug and biomarker pairs for clinical investigation. This scalable approach enables the prediction of drug responses from patient data and can be used to accelerate the development of new genotype-directed therapies. Citation Format: Alicia Y. Zhou, Maria M. Martins, Alexandra Corella, Dai Horiuchi, Christina Yau, Taha Rakshandehroo, John D. Gordan, Rebecca S. Levin, Jeff Johnson, John Jascur, Mike Shales, Antonio Sorrentino, Jaime Cheah, Paul A. Clemons, Alykhan Shamji, Stuart L. Schreiber, Nevan J. Krogan, Kevan M. Shokat, Frank McCormick, Andrei Goga, Sourav Bandyopadhyay. Identification of novel drug interactions with MYC via a quantitative chemical-genetic interaction map. [abstract]. In: Proceedings of the AACR Special Conference on Myc: From Biology to Therapy; Jan 7-10, 2015; La Jolla, CA. Philadelphia (PA): AACR; Mol Cancer Res 2015;13(10 Suppl):Abstract nr B48.

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