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

Author

Listed:
  • Monica Salvioli

    (Delft University of Technology
    Maastricht University)

  • 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)

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.

Suggested Citation

  • Monica Salvioli & Hasti Garjani & Mohammadreza Satouri & Mark Broom & Yannick Viossat & Joel S. Brown & Johan Dubbeldam & Kateřina Staňková, 2025. "Stackelberg Evolutionary Games of Cancer Treatment: What Treatment Strategy to Choose if Cancer Can be Stabilized?," Dynamic Games and Applications, Springer, vol. 15(5), pages 1750-1769, November.
  • Handle: RePEc:spr:dyngam:v:15:y:2025:i:5:d:10.1007_s13235-024-00609-z
    DOI: 10.1007/s13235-024-00609-z
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