2020
DOI: 10.1101/2020.12.02.20241703
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The contribution of evolutionary game theory to understanding and treating cancer

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 h… Show more

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Cited by 21 publications
(33 citation statements)
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References 207 publications
(443 reference statements)
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“…Since we tend to view the change in gene-frequencies as the most important aspect, we tend to treat cancer as a disease of individual aberrant cells. But given that frequency-dependent selection can so drastically transform the mode of evolution, we need to also focus on the aberrant ecology of cells [33, 34, 46, 5052]. That means, that if we want to design drugs that do not allow for the evolution of resistance, we cannot have these drugs produce fitness landscapes that are hard for just strict algorithmic Darwinism but instead we need to design drugs that produce game landscapes that are hard for the ecologically extended algorithmic Darwinism.…”
Section: Discussionmentioning
confidence: 99%
“…Since we tend to view the change in gene-frequencies as the most important aspect, we tend to treat cancer as a disease of individual aberrant cells. But given that frequency-dependent selection can so drastically transform the mode of evolution, we need to also focus on the aberrant ecology of cells [33, 34, 46, 5052]. That means, that if we want to design drugs that do not allow for the evolution of resistance, we cannot have these drugs produce fitness landscapes that are hard for just strict algorithmic Darwinism but instead we need to design drugs that produce game landscapes that are hard for the ecologically extended algorithmic Darwinism.…”
Section: Discussionmentioning
confidence: 99%
“…As a population becomes increasingly resistant to a new treatment, it is common for that population to pay a ‘fitness cost’ to maintain that resistant mechanism, leading to a reduced growth rate when compared to the ancestor from which it was derived. This has led many researchers to suggest that the sensitive ancestor is likely to out-compete the resistant clone when selection is removed, and thus treatment holidays may be beneficial to the maintenance of a treatable cancer population 27, 40 . In some cases the fitness cost may be significant enough to result in competitive exclusion of the resistant strain upon treatment withdrawal.…”
Section: Introductionmentioning
confidence: 99%
“…The distinction is complex, since phenotypic plasticity is genetically based but also underlain by epigenetic mechanisms that can be independent of genetic differences (Richards et al, 2006(Richards et al, , 2010(Richards et al, , 2017Cortijo et al, 2014;Banta and Richards, 2018). Furthermore, the molecular-level mechanisms that contribute to such plastic responses can ultimately lead to genetic changes or non-genetic inheritance (West-Eberhard, 1989;Day, 2009, 2018;Klironomos et al, 2013;Kronholm and Collins, 2016;Kronholm et al, 2017;Wölfl et al, 2020). A particularly striking example of the disconnect between genetic variation and heritable phenotypic response is in the single octoploid clone of Japanese knotweed that has spread aggressively through a broad range of habitats in temperate Europe and North America (Beerling et al, 1994;Bailey and Conolly, 2000;Grimsby et al, 2007;Gerber et al, 2008;Bailey et al, 2009;Richards et al, 2012;Zhang et al, 2016).…”
Section: Determinants Of Evolutionary Speedmentioning
confidence: 99%
“…While the first two are strictly qualitative, the last type can also be quantitative in terms of the amount of testosterone produced. Strictly qualitative resistance traits have been explored in detail by modelers (You et al, 2017;Zhang et al, 2017;West et al, 2018;Cunningham et al, 2020;Bayer et al, 2021;Kim et al, 2021;Viossat and Noble, 2021), strictly quantitative less so (Staňková et al, 2019;Reed et al, 2020;Wölfl et al, 2020), and the combination, to our knowledge, has not been explored at all. Our models can be used to consider all three contexts (strictly qualitative, strictly quantitative or both).…”
Section: Modeling Eco-evolutionary Dynamics Of Cancer In Response To Treatmentmentioning
confidence: 99%
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