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 () and Kateřina Staňková ()
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Monica Salvioli: Delft University of Technology
Hasti Garjani: Delft University of Technology
Mohammadreza Satouri: Delft University of Technology
Mark Broom: City, University of London
Yannick Viossat: Université Paris Dauphine-PSL
Joel S. Brown: H. Lee Moffitt Cancer and Research Institute
Johan Dubbeldam: Delft University of Technology
Kateřina Staňková: Delft University of Technology

Dynamic Games and Applications, 2025, vol. 15, issue 5, No 10, 1750-1769

Abstract: 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.

Keywords: Stackelberg evolutionary games; Evolutionary cancer therapy; Evolutionary game theory; Resistance; Heterogeneity; Mathematical oncology (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s13235-024-00609-z

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