Stackelberg Evolutionary Games of Cancer Treatment: What Treatment Strategy to Choose if Cancer Can be Stabilized?

Monica Salvioli, Hasti Garjani*, Mohammadreza Satouri, Mark Broom, Yannick Viossat, Joel S. Brown, Johan Dubbeldam, Katerina Stankova

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

We present a game-theoretic model of a polymorphic cancer cell population where the treatment-induced resistance is a quantitative evolving trait. When stabilization of the tumor burden is possible, we expand the model into a Stackelberg evolutionary game, where the physician is the leader and the cancer cells are followers. The physician chooses a treatment dose to maximize an objective function that is a proxy of the patient's quality of life. In response, the cancer cells evolve a resistance level that maximizes their proliferation and survival. Assuming that cancer is in its ecological equilibrium, we compare the outcomes of three different treatment strategies: giving the maximum tolerable dose throughout, corresponding to the standard of care for most metastatic cancers, an ecologically enlightened therapy, where the physician anticipates the short-run, ecological response of cancer cells to their treatment, but not the evolution of resistance to treatment, and an evolutionarily enlightened therapy, where the physician anticipates both ecological and evolutionary consequences of the treatment. Of the three therapeutic strategies, the evolutionarily enlightened therapy leads to the highest values of the objective function, the lowest treatment dose, and the lowest treatment-induced resistance. Conversely, in our model, the maximum tolerable dose leads to the worst values of the objective function, the highest treatment dose, and the highest treatment-induced resistance.
Original languageEnglish
Article number110699
Number of pages20
JournalDynamic Games and Applications
DOIs
Publication statusPublished - 1 Dec 2024

Keywords

  • Stackelberg evolutionary games
  • Evolutionary cancer therapy
  • Evolutionary game theory
  • Resistance
  • Heterogeneity
  • Mathematical oncology
  • DYNAMICS
  • CELLS
  • CHEMOTHERAPY
  • PHENOTYPE
  • THERAPY
  • HIV
  • END

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