Abstract 1195: Stochastic co-evolution of the adaptive immune system and an evading cancer population

Abstract Recent advances in immunotherapy have revolutionized modern cancer treatment. While encouraging, robust therapies that lead to durable remission outcomes still remain a challenge in curing many malignancies as cancer cells may acquire clones that effectively evade the immune system. Cancer immunotherapeutic treatment strategies are quite complex. In extreme cases, hematopoietic stem cell recipients enlist an entire allogeneic T-cell repertoire to fight against a growing malignancy. Perhaps most importantly, the adaptive nature of the immune system uniquely enables this treatment approach to co-evolve alongside an evasive threat. However, this process is poorly quantified and thus merits further study in order to maximally benefit cancer patients. Here, we develop a theoretical framework to quantify the dynamics between a growing collection of cancer cells capable of acquiring multiple evasive clones and a T-cell repertoire that may eventually recognize the evading populations. We create the first mathematical model of stochastic tumor-immune co-evolution by applying principles of stochastic process theory. We demonstrate that our model agrees with experimental time-course data in solid and liquid cancers and relate differences in branched vs. clonal evolution to the stringency of immunosurveillance present during early cancer progression. We argue that the clonal dynamics observed in leukemia patients treated with T-cell transplant therapy likely arise from the selection of pre-existent immune-evasive clones. In conclusion, our co-evolutionary model recapitulates empirical observations and offers a framework for quantifiable predictions to further improve cancer immunotherapy. Citation Format: Jason Thomas George, Jeffrey J. Molldrem, Herbert Levine. Stochastic co-evolution of the adaptive immune system and an evading cancer population [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1195.