Gaming the cancer-immunity cycle by synchronizing the dose schedules

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Abstract

We introduce a mathematical model of the cancer-immunity cycle and use it to test several hypotheses regarding the combination, timing, and optimization associated with chemotherapy and immunotherapy dosing schedules in the context of competition and selection pressure. A key conceptual idea is the value of synchronizing the dosing schedules with the fundamental period of the cancer-immunity cycle. The competitors in the population dynamics evolutionary game are the cancer cells, healthy cells, and T-cells, which form a non-transitive rock-paper-scissor chain, mediated by the tumor microenvironment. The chemotherapy and immunotherapy dosing schedules each act as control functions whose timing we synchronize with the fundamental period of the underlying nonlinear dynamical system. With the model, we show among other more detailed results, that chemotherapy and immunotherapy schedules are non-transitive; the best duration of the chemotherapy is around one-quarter of the cancer-immunity cycle, whereas for immunotherapy it is one-half cycle; immunotherapy dosing should preceed chemotherapy dosing. A general conclusion is that optimized timing of the dosing schedules can make up for lower total dose, opening up new possibilities for designing less toxic and more efficacious dosing regimens with drugs currently in use. Obtaining and calibrating more accurate measurements of the cycle-period across patient populations would be an important step in making some of these ideas clinically actionable.
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Abstract We introduce a mathematical model of the cancer-immunity cycle and use it to test several hypotheses regarding the combination, timing, and optimization associated with chemotherapy and immunotherapy dosing schedules in the context of competition and selection pressure. A key conceptual idea is the value of synchronizing the dosing schedules with the fundamental period of the cancer-immunity cycle. The competitors in the population dynamics evolutionary game are the cancer cells, healthy cells, and T-cells, which form a non-transitive rock-paper-scissor chain, mediated by the tumor microenvironment. The chemotherapy and immunotherapy dosing schedules each act as control functions whose timing we synchronize with the fundamental period of the underlying nonlinear dynamical system. With the model, we show among other more detailed results, that chemotherapy and immunotherapy schedules are non-transitive; the best duration of the chemotherapy is around one-quarter of the cancer-immunity cycle, whereas for immunotherapy it is one-half cycle; immunotherapy dosing should preceed chemotherapy dosing. A general conclusion is that optimized timing of the dosing schedules can make up for lower total dose, opening up new possibilities for designing less toxic and more efficacious dosing regimens with drugs currently in use. Obtaining and calibrating more accurate measurements of the cycle-period across patient populations would be an important step in making some of these ideas clinically actionable. Competing Interest Statement The authors have declared no competing interest. Footnotes ↵* saeedehm{at}usc.edu

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europepmc
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License: CC-BY-ND-4.0