Stackelberg Evolutionary Games of Cancer Treatment: What Treatment Strategy to Choose if Cancer Can be Stabilized?
Open Access
- 14 December 2024
- journal article
- research article
- Published by Springer Nature in Dynamic Games and Applications
- Vol. 15 (5) , 1750-1769
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
Funding Information
- Dutch Research Council Project (OCENW.KLEIN.277, OCENW.KLEIN.277, OCENW.KLEIN.277, OCENW.KLEIN.277)
- European Union's Horizon 2020 Research and Innovation program under the Marie Sklodowska-Curie grant agreement (No 955708, No 955708, No 955708, No 955708, No 955708, No 955708)
This publication has 91 references indexed in Scilit:
- Tumor containment: a more general mathematical analysisJournal of Mathematical Biology, 2024
- Theoretical modeling of collaterally sensitive drug cycles: shaping heterogeneity to allow adaptive therapyJournal of Mathematical Biology, 2021
- An evolutionary framework for treating pediatric sarcomasCancer, 2020
- Annual report to the nation on the status of cancer, part I: National cancer statisticsCancer, 2020
- Optimizing Cancer Treatment Using Game TheoryJAMA Oncology, 2019
- UICC Manual of Clinical Oncology2015
- Relationship between whole‐body tumor burden, clinical phenotype, and quality of life in patients with neurofibromatosisAmerican Journal of Medical Genetics Part A, 2014
- An Introduction to Mathematical Population Dynamics2014
- Maximum tolerated dose: clinical endpoint for a bygone era?Targeted Oncology, 2009
- On the Stackelberg strategy in nonzero-sum gamesJournal of Optimization Theory and Applications, 1973