Department of Mathematics, University College London, London, UK.
J R Soc Interface. 2022 Aug;19(193):20220346. doi: 10.1098/rsif.2022.0346. Epub 2022 Aug 17.
Evolutionary game theory (EGT) is a branch of mathematics which considers populations of individuals interacting with each other to receive pay-offs. An individual's pay-off is dependent on the strategy of its opponent(s) as well as on its own, and the higher its pay-off, the higher its reproductive fitness. Its offspring generally inherit its interaction strategy, subject to random mutation. Over time, the composition of the population shifts as different strategies spread or are driven extinct. In the last 25 years there has been a flood of interest in applying EGT to cancer modelling, with the aim of explaining how cancerous mutations spread through healthy tissue and how intercellular cooperation persists in tumour-cell populations. This review traces this body of work from theoretical analyses of well-mixed infinite populations through to more realistic spatial models of the development of cooperation between epithelial cells. We also consider work in which EGT has been used to make experimental predictions about the evolution of cancer, and discuss work that remains to be done before EGT can make large-scale contributions to clinical treatment and patient outcomes.
进化博弈论(EGT)是数学的一个分支,它考虑了相互作用以获得收益的个体群体。个体的收益取决于其对手的策略以及自身的策略,收益越高,繁殖适应性越强。其后代通常会继承其相互作用策略,但受到随机突变的影响。随着时间的推移,不同策略的传播或灭绝会导致种群组成发生变化。在过去的 25 年中,人们对将 EGT 应用于癌症建模产生了浓厚的兴趣,目的是解释癌细胞突变如何在健康组织中传播,以及细胞间合作如何在肿瘤细胞群体中持续存在。这篇综述追溯了从均匀无限群体的理论分析到上皮细胞间合作发展的更现实空间模型的这一领域的工作。我们还考虑了将 EGT 用于对癌症进化进行实验预测的工作,并讨论了在 EGT 能够对临床治疗和患者预后做出重大贡献之前需要完成的工作。