Gaming the cancer–immunity cycle by synchronizing the dose schedules

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 time-dependent selection pressure. A key 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 (normal) cells, and T cells, which conceptually form a nontransitive rock-paper-scissor chain. The chemotherapy and immunotherapy dosing schedules each act as control functions whose timing and magnitudes 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 pulse-dosing schedules do not commute; the best duration of the chemotherapy is one-quarter of the cancer-immunity cycle, whereas for immunotherapy it is one-half cycle; immunotherapy dosing should precede chemotherapy dosing and last twice as long. 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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Publication Details

Journal
Proceedings of the National Academy of Sciences
Published
2025-08-08
DOI
https://doi.org/10.1073/pnas.2423775122
Citations
1
Primary Topic
Mathematical Biology Tumor Growth
Type
article
Field-Weighted Citation Impact
1.37

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article

Gaming the cancer–immunity cycle by synchronizing the dose schedules

Paul K. Newton, Saeedeh Mahmoodifar, K. Stuckey
1 citations
Proceedings of the National Academy of Sciences
Mathematical Biology Tumor Growth
1.37
article

Gaming the cancer–immunity cycle by synchronizing the dose schedules

Paul K. Newton, Saeedeh Mahmoodifar, K. Stuckey
article en
1 citations

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 time-dependent selection pressure. A key 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 (normal) cells, and T cells, which conceptually form a nontransitive rock-paper-scissor chain. The chemotherapy and immunotherapy dosing schedules each act as control functions whose timing and magnitudes 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 pulse-dosing schedules do not commute; the best duration of the chemotherapy is one-quarter of the cancer-immunity cycle, whereas for immunotherapy it is one-half cycle; immunotherapy dosing should precede chemotherapy dosing and last twice as long. 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.

Proceedings of the National Academy of SciencesVol. 122(32)
University of Southern California (US), Viterbo University (US), California Southern University (US), Larry Ellison Foundation (US), Biologie Computationnelle, Quantitative et Synthétique (FR), Quantitative BioSciences (US), Finnish Society of Sciences and Letters (FI), Engineering Arts (United States) (US)
John Simon Guggenheim Memorial Foundation, Life Sciences Division, Army Research Office
Good health and well-being
Openalex Percentile: Top 18%
Mathematical Biology Tumor Growth
1.37
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