A platform of patient-derived microtumors identifies individual treatment responses and therapeutic vulnerabilities in ovarian cancer

Abstract

AbstractIn light of the frequent development of therapeutic resistance in cancer treatment, there is a strong need for personalized model systems accurately representing tumor heterogeneity, while enabling parallel drug testing and prediction of appropriate treatment responses in individual patients. Using ovarian cancer as a prime example of a heterogeneous tumor disease with complex microenvironment, we demonstrate the efficient isolation of highly viable patient-derived microtumors (PDM). Importantly, our data demonstrate histopathological comparability of ovarian cancer PDM with corresponding patient tumor tissue. The establishment of Reverse Phase Protein Array (RPPA)-based analyses of >110 total and phospho-proteins using small amounts of PDM enabled the identification of sensitivities to standard, platinum-based as well as experimental, selumetinib-based therapy, and thereby the prediction of treatment-responders. Strikingly, clinical follow-up of corresponding patients confirmed significantly increased metastasis-free survival of identified carboplatin-responders. Finally, combining PDM and autologous TILs for individual efficacy testing of immune checkpoint inhibitors demonstrated the potential for patient-specific enhancement of cytotoxic TIL activity by this therapeutic approach.TeaserMicrotumors represent the cellular complexity of individual patient tumors and enable treatment response prediction.