Biomarker-guided responses in patient-derived organoids predict effective therapies in breast cancer.

Poor therapeutic response in subsets of breast cancer (BC) patients poses an ongoing challenge. Here, we present a biomarker-guided characterization of 40 patient-derived BC organoids, with the aim of modeling resistant disease with greater fidelity and developing an in vitro system grounded in clinical data for testing alternative treatment strategies. We utilize patient data from the I-SPY2 clinical trial (NCT01042379) to develop predictive models of response to a range of therapies, using only organoid-detectable biomarkers as input, and validate a model predicting response to veliparib-platinum chemotherapy (VP) in triple-negative BC (TNBC) organoids. A drug screen in VP-resistant TNBC organoids reveals combination treatments that overcome resistance to cisplatin, including pro-apoptotic therapies. Another class of hits, HSP90 inhibitors, links organoid drug sensitivity to improved recurrence-free survival in a biomarker-defined patient subset. These findings establish organoid-based functional modeling as a bridge between clinical biomarkers and precision treatment strategies in breast cancer.