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

Jingsong Zhang, Jessica J. Cunningham, Joel S. Brown and Robert A. Gatenby ()
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Jingsong Zhang: Moffitt Cancer Center & Research Institute
Jessica J. Cunningham: Moffitt Cancer Center & Research Institute
Joel S. Brown: Moffitt Cancer Center & Research Institute
Robert A. Gatenby: Moffitt Cancer Center & Research Institute

Nature Communications, 2017, vol. 8, issue 1, 1-9

Abstract: 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.

Date: 2017
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DOI: 10.1038/s41467-017-01968-5

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