Optimizing Cancer Treatment Using Game Theory: A Review

Area of Science:

• Oncology
• Evolutionary Biology
• Game Theory

Background:

• Systemic cancer therapy often fails due to malignant cells evolving resistance.
• Cancer cell resistance, driven by genomic adaptations, presents a significant barrier to treatment.
• Current precision oncology and clinical trial designs rarely integrate cancer's evolutionary dynamics.

Purpose of the Study:

• To investigate cancer treatment as a game theoretic contest between physician therapy and cancer cell resistance.
• To analyze the inherent asymmetries in the cancer treatment game.
• To propose novel therapeutic strategies that exploit these asymmetries.

Main Methods:

• Framing cancer treatment as a leader-follower (Stackelberg) game.
• Analyzing the rational play asymmetry where only the physician can anticipate future moves.
• Evaluating current treatment protocols for their failure to exploit these game dynamics.

Main Results:

• Standard cancer therapy often leads to "Nash solutions" where outcomes are suboptimal.
• Physicians currently cede leadership to cancer cells by treating only upon progression.
• Existing protocols do not leverage the physician's ability to play rationally and anticipate resistance.

Conclusions:

• Physicians can improve cancer treatment outcomes by adopting dynamic protocols.
• Integrating eco-evolutionary dynamics and modulating therapy is key.
• New metrics are needed to track both ecological and evolutionary tumor changes for adaptive therapy.