Organoid-evaluable clinical biomarkers predict drug responses and guide new breast cancer therapies
Bui, T. B. V.; Wolf, D. M.; Bruck, M. C.; Moore, K.; Lien, J.; Choi, S. D.; Warhadpande, S.; Parizadeh, A.; Dillon, D.; Overmoyer, B.; Lynce, F.; I-SPY 2 Investigators, ; Nijman, I. J.; Burgering, B. M.; Harris, I. S.; Esserman, L. J.; Van 't Veer, L. J.; Rosenbluth, J. M.
Show abstract
Poor therapeutic response in subsets of breast cancer (BC) patients poses an ongoing challenge. Here, we present a biomarker-guided characterization of 44 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 utilized patient transcriptomic and outcome data from the I-SPY2 clinical trial to develop predictive models of response to a range of therapies, using only organoid-detectable biomarkers as input. A model predicting response to veliparib-platinum chemotherapy (VP) in triple-negative BC (TNBC) was validated in organoids, showing that in vitro drug responses matched predictions from the patient data-derived model. A drug screen in VP-resistant TNBC organoids identified combination treatments that overcame resistance to cisplatin, including pro-apoptotic therapies. This demonstrates that gene expression-based resistance models derived from patient data can be successfully modeled in organoids that can then be used for therapeutic evaluation.
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