Abstract 1304: Identification of responders for Anti-CTLA4 in refractory colorectal cancers using CANScript™ platform

Predicting clinical response to anticancer drugs remains a major challenge in the treatment of cancer. Indeed, while biomarker-guided strategies for personalizing anticancer drugs have shown strong promise in certain cases, recent studies have shown that the tumor microenvironment and heterogeneity can limit the predictive power of biomarkers alone. Here we have engineered a personalized tumor ecosystems, termed CANScript™, that contextually conserve tumor heterogeneity and phenocopy the tumor ecosystem using thin tumor explants maintained in defined tumor grade-matched matrix support and autologous ligands from patients. We then demonstrated that the CANScript™ platform can be used to predict clinical response. Specifically, functional readouts obtained by exposing the CANScript™ ecosystems from more than 1100 patients to a panel of anticancer drugs, together with the corresponding clinical outcomes, were used to train a novel machine learning algorithm; the learned model was then applied to predict clinical response to anticancer drugs in a test group comprising of 900 new patients, where it achieved 100% sensitivity in its predictions while also keeping specificity in a desired high range. We have also observed that CANScript™ retains patient tumor immune environment which is important for clinical response of not only immunomodulators but other anti-cancer drugs. Here we report the effect of immunomodulators in refractory CRC tumors which remains difficult to treat. Data demonstrates that Anti-CTLA-4 has profound antitumor effect in refractory CRC tumors by increasing cytotoxic T-Cells. In this cohort of 16 patients’ tumors CANScript™ platform identifies 31% as responders (5/16) where conventional tumor sections culture model shows only 6% as (1/16) responders. Citation Format: Biswanath Majumder, Baraneedharan Ulaganathan, Allen Thayakumar, Saravanan Thiyagarajan, Nilesh Brijwani, Biplab Tewari, Basavaraja U. Santhappa, Padhma Radhakrishnan, Pradip K. Majumder. Identification of responders for Anti-CTLA4 in refractory colorectal cancers using CANScript™ platform. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 1304. doi:10.1158/1538-7445.AM2015-1304