Preventing evolutionary rescue in cancer using two-strike therapy

Area of Science:

• Oncology
• Mathematical Biology
• Evolutionary Dynamics

Background:

• First-line cancer therapies often fail due to emerging therapeutic resistance.
• Clinical challenge lies in scheduling subsequent treatments for optimal tumor eradication.
• Understanding tumor vulnerability during minimal size is key.

Purpose of the Study:

• To provide a theoretical framework for optimizing cancer treatment scheduling.
• To determine the ideal timing for switching to a second treatment based on evolutionary principles.
• To explore the impact of tumor parameters and treatment efficacy on eradication success.

Main Methods:

• Mathematical analysis and extensive stochastic simulations.
• Application of evolutionary rescue theory.
• Investigation of tumor extinction probability at different sizes and treatment timings.

Main Results:

• The optimal time to switch treatment is near the tumor's minimum size (nadir) before relapse.
• Switching after relapse begins is often preferable to switching too early.
• Treatment efficacy and tumor evolutionary parameters significantly influence outcomes.
• A strategy for scheduling drugs with unequal efficacy was determined.

Conclusions:

• An evolutionarily-informed multi-strike treatment strategy can enhance tumor eradication.
• Optimal treatment scheduling exploits tumor vulnerability at its smallest, undetectable phase.
• Findings provide a foundation for experimental and clinical investigation into adaptive cancer therapy.