Evolution-based mathematical models significantly prolong response to abiraterone in metastatic castrate-resistant prostate cancer and identify strategies to further improve outcomes

• DOI: 10.7554/elife.76284
• Publication Date: 2022-06-28T09:00:19Z
• Authors: Jingsong Zhang; Jessica Cunningham; Joel Brown; Robert Gatenby
• Keywords: Abiraterone acetate; Abiraterone

Background: Abiraterone acetate is an effective treatment for metastatic castrate-resistant prostate cancer (mCRPC), but evolution of resistance inevitably leads to progression. We present a pilot study in which abiraterone dosing guided by evolution-informed mathematical models delay onset resistance. Methods: In the cohort, was stopped when PSA <50% pretreatment value and resumed returned baseline. Results are compared contemporaneous cohort who had >50% decline after initial administration met trial eligibility requirements chose standard care (SOC) dosing. Results: 17 subjects were enrolled adaptive therapy group 16 SOC group. All have progressed, four patients remain stably cycling (range 53–70 months). The significantly improved median time progression (TTP; 33.5 months; p<0.001) overall survival (OS; 58.5 hazard ratio, 0.41, 95% confidence interval (CI), 0.20–0.83, 14.3 31.3 months cohort. On average, received no during 46% on trial. Longitudinal data demonstrated competition coefficient ratio ( α RS /α SR ) sensitive resistant populations, critical factor intratumoral evolution, two- threefold higher than pre-trial estimates. Computer simulations evolutionary dynamics long-term survivors found that, due larger SR, cycled decreased population. Simulations progressed predicted further increases OS could be achieved with prompt withdrawal achieving 50% reduction. Conclusions: Incorporation evolution-based into monotherapy mCRPC TTP OS. updated parameters from longitudinal can estimate each subject identify strategies improve outcomes. Funding: Moffitt internal grants NIH/NCI U54CA143970-05 (Physical Science Oncology Network).