RT Journal Article
SR Electronic
T1 Optimal Cancer Evasion in a Dynamic Immune Microenvironment
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2022.08.03.502723
DO 10.1101/2022.08.03.502723
A1 George, Jason T.
A1 Levine, Herbert
YR 2022
UL http://biorxiv.org/content/early/2022/08/05/2022.08.03.502723.abstract
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.