The Contribution of Evolutionary Game Theory to Understanding and Treating Cancer

Review (2021)
Author(s)

Benjamin Wölfl (University of Vienna)

Hedy te Rietmole (University Medical Center Utrecht)

Monica Salvioli (Maastricht University, Università degli Studi di Trento, TU Delft - Transport and Logistics)

Artem Kaznatcheev (University of Oxford, University of Pennsylvania)

Frank Thuijsman (Maastricht University)

Joel S. Brown (University of Illinois at Chicago, Lee Moffitt Cancer Center and Research Institute)

Boudewijn Burgering (The Oncode Institute, University Medical Center Utrecht)

Kateřina Staňková (Maastricht University, TU Delft - Transport and Logistics, TU Delft - Mathematical Physics)

Research Group
Transport and Logistics
DOI related publication
https://doi.org/10.1007/s13235-021-00397-w
More Info
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Publication Year
2021
Language
English
Research Group
Transport and Logistics
Journal title
Dynamic Games and Applications
Issue number
2
Volume number
12
Pages (from-to)
313-342
Downloads counter
445
Collections
Institutional Repository
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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 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.