Heterogeneity in strategies for survival and proliferation among the cells that constitute a tumour is a driving force behind the evolution of resistance to cancer therapy. The rules mapping the tumour’s strategy distribution to the fitness of individual strategies can be represented as an evolutionary game. We develop a game assay to measure effective evolutionary games in co-cultures of non-small cell lung cancer cells that are sensitive and resistant to the anaplastic lymphoma kinase inhibitor alectinib. The games are not only quantitatively different between different environments, but targeted therapy and cancer-associated fibroblasts qualitatively switch the type of game being played by the in vitro population from Leader to Deadlock. This observation provides empirical confirmation of a central theoretical postulate of evolutionary game theory in oncology: we can treat not only the player, but also the game. Although we concentrate on measuring games played by cancer cells, the measurement methodology we develop can be used to advance the study of games in other microscopic systems by providing a quantitative description of non-cell-autonomous effects.
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Due to size constraints, raw image data from experiments are available upon request. Post-image processing data (that is, population size time-series for each experimental replicate) are available on GitHub at https://github.com/kaznatcheev/GameAssay.
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J.G.S. acknowledges the NIH Loan Repayment Programs for generous support of his research in general, as well as Miles for Moffitt and the NIH Case Comprehensive Cancer Center (support grant P30CA043703), and the Calabresi Clinical Oncology Research Program, National Cancer Institute (award number K12CA076917). We also thank M. Abazeed, P. Jeavons and K. Kaznatcheev for helpful feedback and discussions.
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Nature Ecology & Evolution (2019)