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Fibroblasts and alectinib switch the evolutionary games played by non-small cell lung cancer


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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Image analysis code is available on GitHub at The game assay analysis code is available on GitHub at

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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

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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.

Author information

A.K., J.P., A.M. and J.G.S. conceived and designed the study. J.P. and A.M. performed the experiments. A.K. designed the mathematical model, wrote the image analysis and game assay code, and analysed the data. A.K., A.M. and J.G.S. wrote the main text. A.K. and J.P. wrote the Supplementary Information. D.B., A.M. and J.G.S. supervised the project. All authors discussed the results and implications, commented on the work at all stages and approved the final submission.

Competing interests

The authors declare no competing interests.

Correspondence to Artem Kaznatcheev or Andriy Marusyk or Jacob G. Scott.

Supplementary information

  1. Supplementary Information

    Supplementary Sections A–F, including Supplementary Figures 1–8 and Supplementary References

  2. Reporting Summary

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Fig. 1: Monotypic culture exponential growth rates for parental and resistant cells under the indicated experimental conditions.
Fig. 2: Co-culture growth rates across four experimental conditions.
Fig. 3: Fitness functions for competition of parental versus resistant NSCLC.
Fig. 4: Measured games.