Because of this, cancer therapy is a leader-follower game. Even if the molecular machinery of resistance is present prior to treatment, it is not under selection as a resistance strategy until treatment. Second, there is a consistent sequence in the game because the physician always makes the first move by applying therapy and only then can cancer cells “play” by responding through the evolution of resistance strategies. In particular, cancer cells can never anticipate or adapt to future conditions that differ from current or prior circumstances. In contrast, cancer cells, typical of evolving organisms in nature, can only respond to what is happening or has happened. 13įirst, only the physician is rational and can anticipate future events. However, cancer therapy also contains elements of social/economic games 12 that result in asymmetries that confer critical advantages on the physician, as follows. The cancer therapy predator-prey game differs from those in nature in ways that limit the physician: he or she does not gain a fitness advantage from killing cancer cells and his or her strategies are constrained by costs, ethics, and treatment toxic effects. Game theoretic approaches have been applied to management of antibiotic resistance 8 and control of agricultural pests, 9 as well as cancer progression 10 and treatment. In evolutionary games, 7 the players inherit rather than choose their strategies, and their payoffs are survival and proliferation. Although initially focused on conflict 4 and cooperation in economics, 5 Maynard-Smith and Price 6 pioneered its application to evolutionary dynamics. Developed by Von Neumann and Morgenstern, 1Nash, 2 and others, 3 game theory describes the strategies (choices), payoffs (consequences), and dynamical interactions involving both individuals and populations. The physician-predator can also “evolve” in the sense that he or she can vary treatments over time.Ĭontests such as between the physician and cancer cells can be framed mathematically using game theory. They respond to treatment by evolving effective strategies of therapy resistance. But, for most metastatic cancers, extinction is not achievable because the cancer cells are active “players” in the game. Cure occurs if therapy drives the cancer populations extinct. ![]() Therapy options represent the physician’s strategies. Herein, we frame cancer treatment as a contest in which the physician enters a predator-prey–like game with the patient’s cancer cells. Without fundamental changes in strategy, standard-of-care cancer therapy typically results in “Nash solutions” in which no unilateral change in treatment can favorably alter the outcome. ![]() Furthermore, by changing treatment only when the tumor progresses, the physician cedes leadership to the cancer cells and treatment failure becomes nearly inevitable. By repeatedly administering the same drug(s) until disease progression, the physician “plays” a fixed strategy even as the opposing cancer cells continuously evolve successful adaptive responses. ![]() Current treatment protocols for metastatic cancer typically exploit neither asymmetry. (2) It has a distinctive leader-follower (or “Stackelberg”) dynamics the “leader” oncologist plays first and the “follower” cancer cells then respond and adapt to therapy. Cancer cells, like all evolving organisms, can only adapt to current conditions they can neither anticipate nor evolve adaptations for treatments that the physician has not yet applied. This game has 2 critical asymmetries: (1) Only the physician can play rationally. We investigate cancer treatment as a game theoretic contest between the physician’s therapy and the cancer cells’ resistance strategies.
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