Using an Ex Vivo Organ Culture System to Predict Patient Response to Cancer Therapy

Introduction: Current cancer personalized medicine utilizes genomic analysis to determine optimal treatment for patients where the treatment protocol is poorly defined. However, recent studies have shown that patients using general genomic profiling on a wide panel of genes show no better overall survival than patients who do not use these assays. To advance cancer precision diagnostics, we have developed an Ex Vivo Organ Culture (EVOC) drug sensitivity platform to create individualized patient treatment regimens. Currently we are conducting clinical trials to demonstrate the predictive capabilities of the method and to show that our test accurately indicates the patients outcome.

Materials & Methods: A subsection of patients undergoing Transurethral Resection of Bladder Tumors (TURBT) with muscle invasive bladder cancer (MIBC) receive neoadjuvant chemotherapy in the form of Cisplatin and Gemcitabine on days 1 and 8 in 3 week cycles for 2 months. Patients receiving treatment demonstrate a variety of responses, ranging from no response (NR) to complete response (CR), which is determined upon cystectomy. To predict patient response to chemotherapy, bladder cancer removed from patients undergoing TURBT was tested in the EVOC platform. Samples were received within 6 hours of extraction and were cultured for 5 days with the relevant drug combination.

Results & Discussion: MIBC samples from EVOC were analyzed and matched with patient response to establish a diagnostic outcome and provide predictive read outs. A combination of histological and morphological markers evaluating cell proliferation, cell death and tissue dynamic were classified and computed to provide a final overall score ranking response levels. Additionally, these samples underwent RNA sequencing to evaluate potential markers to distinguish between different levels of patient response to treatment.

Conclusions: The EVOC platform has been show to successfully maintain bladder cancer tissue at high viability in vitro, during which time several potential drug treatments were tested. The platform is currently undergoing clinical evaluation to demonstrate predictive capabilities. In the future, the integration of this platform in the decision making progress of bladder oncologists may open new treatment options for bladder cancer and other cancer patients. The combination of this tool with next generation sequencing could potentially focus the sequencing results to those treatment options that demonstrated response in vitro.