Abstract 3155: Harnessing synthetic rescues to evaluate and mitigate resistance to cancer therapy

Abstract

Abstract Significance: The emergence of resistance to cancer therapy remains a pressing challenge, as evident from numerous recent investigations identifying molecular events conferring resistance to cancer drugs. Here we demonstrate that many of these molecular events can be attributed to synthetic rescue (SR) genetic interactions, where altered activity of a specific (termed rescuer) gene restores cell viability caused by the inactivation (including through gene deletion or targeted pharmacological repression) of another gene. Methods: We present a computational approach termed INCISOR, which analyzes molecular, survival, and phylogenetic cancer data to predict SR genes pairs that are under positive selection and their presence decreases patient survival. It further screens for causal SR pairs that show in vitro evidence of rescue. Results: We applied INCISOR to mine 8000 patients’ omics and clinical data in TCGA to identify the first genome-wide SR network, composed of SR interactions common to many cancer types. The predicted SRs match drug-specific molecular resistance signatures that have been recently published in arduous clinical studies (with accuracy of 0.8 AUC). They chart pathways of resistance on a genome scale and as we show, can predict response and resistance to the majority of current cancer drugs in patients. We conducted new experiments to test new predicted SR-based combination therapies. Each combination consisted of a primary cancer drug and a second adjuvant therapy inhibiting a predicted key rescuer of the primary drug. Five of the 7 predicted combinations tested synergistically sensitized all the five head and neck cell lines to the original primary therapies. These results were further substantiated via siRNA knockdowns of the predicted rescuers in combination with the original treatment, confirming the effects observed with pharmacological inhibition. Focusing on mTOR, a major cancer driver gene, we combined drug treatment and pooled-shRNA to validate the rescue effect of 8 out of 10 predicted rescue interactions involving mTOR in a head and neck cancer cell-line. Finally, we analyzed patient-derived mouse 960 xenografts (PDX) treated with 25 different drug combinations. Mice exhibit much better progression-free survival when treated with a drug combination predicted by INCISOR compared with the mice treated with the primary drug alone, testifying to the in-vivo benefits of SR-based synergistic treatments. Conclusions: This work presents a new paradigm harnessing synthetic rescue gene-gene interactions to counteract resistance to cancer treatment. Future implementations of this approach will have two broad implications in the precision medicine era, first for determining the most effective treatment regimen based on the molecular characteristics of individual patient’s tumor; second for identifying supplemental drugs to counteract resistance to existing primary therapies. Citation Format: Avinash D. Sahu, Joo Sang Lee, Eytan Ruppin, Silvio Gutkind, Zhiyong Wang. Harnessing synthetic rescues to evaluate and mitigate resistance to cancer therapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3155. doi:10.1158/1538-7445.AM2017-3155