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


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2017-12

AUTHORS

Jingsong Zhang, Jessica J. Cunningham, Joel S. Brown, Robert A. Gatenby

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. More... »

PAGES

1816

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/s41467-017-01968-5

DOI

http://dx.doi.org/10.1038/s41467-017-01968-5

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1092917896

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/29180633


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