Gaming the cancer–immunity cycle by synchronizing the dose schedules - Saeedeh Mahmoodifar; Kristina Stuckey; Paul K. Newton (Proceedings of the National Academy of Sciences, 2025)
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.