PT  - JOURNAL ARTICLE
AU  - George, Jason T.
AU  - Levine, Herbert
TI  - Optimal Cancer Evasion in a Dynamic Immune Microenvironment
AID  - 10.1101/2022.08.03.502723
DP  - 2022 Jan 01
TA  - bioRxiv
PG  - 2022.08.03.502723
4099  - http://biorxiv.org/content/early/2022/08/05/2022.08.03.502723.short
4100  - http://biorxiv.org/content/early/2022/08/05/2022.08.03.502723.full
AB  - The failure of cancer treatments, including immunotherapy, continues to be a major obstacle in preventing durable remission. This failure often results from tumor evolution, both genotypic and phenotypic, away from sensitive cell states. Here, we propose a mathematical framework for studying the dynamics of adaptive immune evasion that tracks the number of tumor-associated antigens available for immune targeting. We solve for the unique optimal cancer evasion strategy using stochastic dynamic programming and demonstrate that this policy results in increased cancer evasion rates when compared to a passive, fixed strategy. Our foundational model relates the likelihood and temporal dynamics of cancer evasion to features of the immune microenvironment, where tumor immunogenicity reflects a balance between cancer adaptation and host recognition. In contrast with a passive strategy, optimally adaptive evaders navigating varying selective environments result in substantially heterogeneous post-escape tumor antigenicity, giving rise to immunogenically hot and cold tumors.Competing Interest StatementThe authors have declared no competing interest.