OncoLoop: A network-based precision cancer medicine framework.

Prioritizing cancer treatment at the individual patient level remains challenging and performing co-clinical studies using patient-derived models in real-time is often unfeasible. To circumvent these challenges, we introduce OncoLoop, a precision medicine framework to predict drug sensitivity in both a human tumor and its highest-fidelity (cognate) model(s)—for contextual in vivo validation— by leveraging perturbational profiles of clinically-relevant oncology drugs. As proof-of-concept, we applied OncoLoop to prostate cancer using a series of genetically engineered mouse models (GEMMs) that capture the broad spectrum of disease states, including metastatic, castration-resistant, and neuroendocrine prostate cancer. Interrogation of published cohorts revealed that most patients were represented by at least one cognate GEMM-derived tumor (GEMM-DT), based on Master Regulator (MR) conservation analysis. Drugs recurrently predicted to invert MR protein activity in patients and their cognate GEMM-DTs were successfully validated, including in two cognate allografts and one patient derived xenograft (PDX). OncoLoop is highly generalizable and can be extended to other cancers and other pathologies.

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