The Contribution of Evolutionary Game Theory to Understanding and Treating Cancer
Wölfl, Benjamin; te Rietmole, Hedy; Salvioli, Monica; Kaznatcheev, Artem; Thuijsman, Frank; Brown, Joel S.; Burgering, Boudewijn; Staňková, Kateřina
(2022) Dynamic Games and Applications, volume 12, issue 2, pp. 313 - 342
(Article)
Abstract
Evolutionary game theory mathematically conceptualizes and analyzes biological interactions where one’s fitness not only depends on one’s own traits, but also on the traits of others. Typically, the individuals are not overtly rational and do not select, but rather inherit their traits. Cancer can be framed as such an evolutionary
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game, as it is composed of cells of heterogeneous types undergoing frequency-dependent selection. In this article, we first summarize existing works where evolutionary game theory has been employed in modeling cancer and improving its treatment. Some of these game-theoretic models suggest how one could anticipate and steer cancer’s eco-evolutionary dynamics into states more desirable for the patient via evolutionary therapies. Such therapies offer great promise for increasing patient survival and decreasing drug toxicity, as demonstrated by some recent studies and clinical trials. We discuss clinical relevance of the existing game-theoretic models of cancer and its treatment, and opportunities for future applications. Moreover, we discuss the developments in cancer biology that are needed to better utilize the full potential of game-theoretic models. Ultimately, we demonstrate that viewing tumors with evolutionary game theory has medically useful implications that can inform and create a lockstep between empirical findings and mathematical modeling. We suggest that cancer progression is an evolutionary competition between different cell types and therefore needs to be viewed as an evolutionary game.
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Keywords: Competitive release, Eco-evolutionary dynamics, Evolutionary game theory, Genetics, Resistance, Stackelberg evolutionary games, Computational Mathematics, Applied Mathematics, Economics and Econometrics, Statistics and Probability, Computer Science Applications, Computational Theory and Mathematics, Computer Graphics and Computer-Aided Design, Review, Journal Article
ISSN: 2153-0785
Publisher: Springer Science + Business Media
Note: Funding Information: This research was supported by European Union’s Horizon 2020 research and innovation programs under the Marie Skłodowska-Curie Grants 690817 and 955708, the Dutch National Foundation projects ENWPR.020.006 and OCENW.KLEIN.277, two James S. McDonnell Foundation grants, Cancer therapy: Perturbing a complex adaptive system and a postdoctoral fellowship Award (#2020-1423), a V Foundation Grant, NIH/National Cancer Institute (NCI) R01CA170595, Application of Evolutionary Principles to Maintain Cancer Control (PQ21), NIH/NCI U54CA143970-05 Physical Science Oncology Network (PSON) Cancer as a complex adaptive system and Austrian Science Fund (FWF): DK W1225-B20. Publisher Copyright: © 2021, The Author(s).
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