TY - JOUR
T1 - Stackelberg Evolutionary Games of Cancer Treatment
T2 - What Treatment Strategy to Choose if Cancer Can be Stabilized?
AU - Salvioli, Monica
AU - Garjani, Hasti
AU - Satouri, Mohammadreza
AU - Broom, Mark
AU - Viossat, Yannick
AU - Brown, Joel S.
AU - Dubbeldam, Johan
AU - Stankova, Katerina
PY - 2024/12/1
Y1 - 2024/12/1
N2 - 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.
AB - 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.
KW - Stackelberg evolutionary games
KW - Evolutionary cancer therapy
KW - Evolutionary game theory
KW - Resistance
KW - Heterogeneity
KW - Mathematical oncology
KW - DYNAMICS
KW - CELLS
KW - CHEMOTHERAPY
KW - PHENOTYPE
KW - THERAPY
KW - HIV
KW - END
U2 - 10.1007/s13235-024-00609-z
DO - 10.1007/s13235-024-00609-z
M3 - Article
SN - 2153-0785
JO - Dynamic Games and Applications
JF - Dynamic Games and Applications
M1 - 110699
ER -