Cancer Evolvability Determines Therapy Outcomes

Abstract

Cancer progression following treatment failure is an evolutionary process in which therapy acts as a selection pressure driving Darwinian selection on heritable variation to favor resistant clones. This ability to generate variation, i.e., the cancers evolvability, is a key determinant of how rapidly tumors adapt to therapy. Here, we present an evolutionary game-theoretic model to evaluate how evolvability shapes resistance dynamics under two treatment modalities: targeted therapy and chemotherapy. We first compare cancer populations with fixed evolvabilities: low or high. Targeted therapy imposes a steep selection gradient, enabling rapid resistance evolution, while chemotherapy exerts a flatter gradient but drives tumors toward more extreme resistance strategies. We show that targeted therapy works better in low-evolvability cancers, whereas chemotherapy better controls high-evolvability populations. We then extend the model to incorporate facultative evolvability in which cancer cells dynamically adjust their evolvability in response to therapy-induced stress in which cells fine-tune the trade-off between acquiring higher resistance and limiting the costs of resistance and evolvability. The latter strategy sustains a higher tumor burden than fixed-evolvability populations. To address the challenges of facultative evolvability for therapy efficacy, we develop and simulate an evolutionary double bind using sequential cycles of chemotherapy and targeted therapy. With an appropriate sequence and timing, this strategy can drive cancer cells with facultative evolvability to extinction. Our results highlight the importance of evolvability in shaping treatment response and underscore the need to incorporate evolutionary principles into therapy design.