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Resistance to therapeutic interventions contributes to poor long-term cancer patient outcomes. Adaptation to therapy, a common mechanism of drug resistance involving drug-induced activation of pro-survival oncogenic processes, poses a challenge for the implementation of effective precision therapies. Here, we addressed this challenge using the TargetScore network modeling method to nominate combination therapies that block adaptive responses in breast cancer. TargetScore identified therapeutically actionable adaptive responses as drug-induced concurrent changes in phospho-proteins connected within a signaling network. To study how apoptotic stress rewires cancer cells and uncover therapeutically actionable oncogenic dependencies, breast cancer cells were perturbed with inhibitors of anti-apoptotic mediators, particularly MCL1. TargetScore and phosphoproteomics analyses revealed the short-term (i.e., days) stress and long-term (i.e., months) acquired drug resistance to inhibitors of anti-apoptotic mediators. TargetScore predicted concurrent activation of growth and DNA repair pathways as cells evolved to resist apoptotic targeting. Validation of the predictions demonstrated strong responses to PARP1/2 and SHP2 inhibitor combination in vitro and in vivo. In genetically engineered mouse models, PARP1/2 and SHP2 co-targeting led to near-complete tumor eradication and durable responses with significant survival benefit, laying the groundwork for clinical evaluation. Functional proteomics and perturbation biology analyses proposed a mechanism of response to PARP1/2 and SHP2 co-targeting associated with molecular markers of DNA damage response, replication stress, and cell cycle arrest. This study demonstrates that TargetScore may advance precision oncology by matching drug combinations to molecular signatures and dependencies revealed under therapeutic stress.
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Luna et al. (2026) studied this question.
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