AUTHOR=Pressley Mariyah , Salvioli Monica , Lewis David B. , Richards Christina L. , Brown Joel S. , Staňková Kateřina TITLE=Evolutionary Dynamics of Treatment-Induced Resistance in Cancer Informs Understanding of Rapid Evolution in Natural Systems JOURNAL=Frontiers in Ecology and Evolution VOLUME=Volume 9 - 2021 YEAR=2021 URL=https://www.frontiersin.org/journals/ecology-and-evolution/articles/10.3389/fevo.2021.681121 DOI=10.3389/fevo.2021.681121 ISSN=2296-701X ABSTRACT=Rapid evolution is ubiquitous in nature in response to anthropogenic disturbances and changes. We will briefly review some of this quite broadly. Nowhere is this more evident, replicated and accessible to study than in cancer. Curiously cancer has been late - relative to fisheries, antibiotic resistance, pest management and evolution in human dominated landscapes - in recognizing the need for evolutionarily informed management strategies. The speed of evolution matters. Here, we employed game-theoretic modelling to compare time to progression with continuous maximum tolerable dose to that of adaptive therapy where treatment is discontinued when the cancer cells' population gets below half of its initial size and re-administered when the cancer cells recover, forming cycles with and without treatment. We show that the success of adaptive therapy relative to continuous maximum tolerable dose therapy is much higher if the population of cancer cells is defined by only two cell types (sensitive versus resistant or "polymorphic"). Additionally, the relative increase in time to progression increases with the speed of evolution. These results hold with and without cost of resistance in cancer cells. On the other hand, when treatment-induced resistance is modeled as a quantitative trait in a monomorphic cancer population, when evolution is rapid, there is no advantage to the adaptive therapy as there is insufficient initial response to treatment in cancer cells, who evolve resistance too quickly. Our study emphasizes how cancer provides a unique system for studying rapid evolutionary changes within tumor ecosystems in response to human interventions and progressive diseases; and allows us to contrast and compare this system to other human managed or dominated systems in nature.