Abstract
A scientific interrogation-driven approach to the clinical management of cancer patients is based on molecular profiling of the tumor. Empowered by the knowledge of oncogenic drivers and biomarkers, oncologists chart an optimal treatment path toward increasing the mathematical probability of a positive outcome. In this entire chain of events, an experimental proof of logical interrogation has never been incorporated before. Here, we provide the first evidence that the result of ex vivo testing of a drug matched to the genomic profiling of an N-of-1 tumor can deliver meaningful insight connecting scientific interrogation and a clinical event. Using resected tissues from endometrial (EC) and ovarian (OC) cancer patients, we designed a personalized ex vivo platform to test combinations of drugs in the default histological architecture of the individual tumors. Following the CART-T cells' principle, we co-cultured with autologous T-cells to test targeted drugs and immune checkpoint inhibitors. The study was designed with a limited clinical information window from patient registration/consent to obtaining the tumor tissues, and adjuvant treatment/post-surgery event (PSE) data were accessed retrospectively. Using a checkerboard analysis, we found that PSE-free survival time was longer in patients whose therapy "matched" the effective drug combination in ex vivo culture/co-cultures compared to those with no effect. Specifically, out of 32 EC patients in the "test & treatment-matched" category whose tumor cells failed to respond to ex vivo drug testing, none achieved > 4 and > 3 years of PSE-free survival. In contrast, out of 38 EC patients in the "test & treatment-matched" category, 4 and 6 patients, whose tumor cells responded to drugs in ex vivo culture, achieved > 4 and > 3 years of PSE-free survival, respectively. Cases with genomically-guided ex vivo testing showed that a "match" between an effective ex vivo drug combination and therapy resulted in late PSE, whereas a "match" between prescribed treatment and an ineffective drug combination in ex vivo testing led to early PSE. Our study demonstrates that integrating genomic data with personalized drug testing on an ex vivo culture/co-culture platform is an effective tool for modeling functional precision medicine in gynecological cancers. This approach bridges the gap between next-generation drug testing in translational research and patient care, providing insight for improved treatment outcomes.