Integrating evolutionary dynamics into treatment of metastatic castrate-resistant prostate cancer

TLDR

Abiraterone treats metastatic castrate‑resistant prostate cancer by inhibiting CYP17A, but resistance typically develops after about 16.5 months of standard dosing. The study hypothesizes that incorporating evolutionary dynamics into therapy could extend time to progression. An evolutionary game‑theory model with Lotka‑Volterra equations describes three tumor subpopulations, and adaptive therapy schedules on/off abiraterone cycles based on patient‑specific dynamics to suppress androgen‑independent cells and reduce drug exposure. Simulations predict rapid selection for androgen‑independent cells under standard dosing, whereas the adaptive therapy pilot showed 10 of 11 patients with stable tumor oscillations, a median TTP of at least 27 months, a 47 % reduction in cumulative drug use, and outcomes superior to published controls.

Abstract

Abiraterone treats metastatic castrate-resistant prostate cancer by inhibiting CYP17A, an enzyme for testosterone auto-production. With standard dosing, evolution of resistance with treatment failure (radiographic progression) occurs at a median of ~16.5 months. We hypothesize time to progression (TTP) could be increased by integrating evolutionary dynamics into therapy. We developed an evolutionary game theory model using Lotka-Volterra equations with three competing cancer "species": androgen dependent, androgen producing, and androgen independent. Simulations with standard abiraterone dosing demonstrate strong selection for androgen-independent cells and rapid treatment failure. Adaptive therapy, using patient-specific tumor dynamics to inform on/off treatment cycles, suppresses proliferation of androgen-independent cells and lowers cumulative drug dose. In a pilot clinical trial, 10 of 11 patients maintained stable oscillations of tumor burdens; median TTP is at least 27 months with reduced cumulative drug use of 47% of standard dosing. The outcomes show significant improvement over published studies and a contemporaneous population.