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

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.

Antibiotics can be used to contain drug-resistant bacteria by maintaining sufficiently large sensitive populations

“…In fact, recent work suggests that aggressive treatment strategies can hasten the emergence and spread of resistance [30][31][32][33][34][35][36][37][38][39][40][41]. In addition, numerous studies, both experimental and theoretical, provide evidence that less aggressive treatment strategies may be called for under some conditions [42][43][44][45][46][47][48][49][50], while several clinical trials have also demonstrated advantages of lower dose therapies [50][51][52][53][54][55][56][57][58]. The most frequently cited advantages of less aggressive therapies are reduced off-target selection for resistance and fewer adverse effects for the patient.…”

Why is cancer not more common? A changing microenvironment may help to explain why, and suggests strategies for anti-cancer therapy

“…Our model supports the use of therapeutic strategies that target the TME, causing the optimum to change and potentially driving the cancer cell population to extinction 1,16 . A similar approach, termed "adaptive therapy" or "metronomic chemotherapy", has been proposed previously 39,40 , where treatments have been adjusted with or without evolutionary modelling and there is clear evidence of improved patient outcome by cyclic dosing 41 . It is challenging to identify a phenotypic optimum that the cancer cells can actually respond to, but there have been clinical trials based on this philosophy 42 .…”

A two‐drug combination simulation study for metastatic castrate resistant prostate cancer

“…In order to gauge the influence of genetic background, tumor heterogeneity, and drug potency on plausible eradication of mCRPC we used a computational simulation approach. In particular, we used theoretical evolutionary dynamics which provides insights into how prostate cancer evolves and evades resistance . Here, we apply a recently developed stochastic branching process model to estimate the probability that resistance will emerge to two‐drug therapy.…”