Adaptation of tumors to therapeutic interventions contributes to dismal long-term patient outcomes. Adaptation to therapy involves the co-action of functionally related proteins that together activate cell survival programs and compensate for the therapeutic impact. Oncogenic dependencies to such adaptive events, however, can generate new therapeutic vulnerabilities that can be targeted with drug combinations. The precision medicine approaches in which targeted drugs are matched to pre-existing genomic aberrations fail to address the adaptive responses and resulting vulnerabilities. Here, we provide the mathematical formulation, implementation, and validation of the TargetScore method. The TargetScore identifies collective adaptive responses to targeted interventions as concurrent changes of phospho-proteins that are connected within a signaling network. Based on the adaptive responses, the method predicts drug-induced vulnerabilities. Using TargetScore, we inferred the adaptive responses with short-term (i.e., days) stress and long-term (i.e., months) acquired resistance to inhibitors of antiapoptotic mediators, MCL1 and BCL2. With experiments guided by the predictions, we identified synergistic interactions between inhibitors of PARP, SHP2, and MCL1 in breast cancer cells. TargetScore is readily applicable to existing precision oncology efforts by matching targeted drug combinations to emerging molecular signatures under therapeutic stress.

Citation Format: Heping Wang, Augustin Luna, Gonghong Yan, Xubin Li, Ozgun Babur, Chris Sander, Gordon Mills. Targeting adaptation to cancer treatment by drug combinations [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1002.