title: Mathematical modeling of prostate cancer progression in response to androgen ablation therapy.
abstract: Prostate cancer progression depends in part on the complex interactions between testosterone, its active metabolite DHT, and androgen receptors. In a metastatic setting, the first line of treatment is the elimination of testosterone. However, such interventions are not curative because cancer cells evolve via multiple mechanisms to a castrate-resistant state, allowing progression to a lethal outcome. It is hypothesized that administration of antiandrogen therapy in an intermittent, as opposed to continuous, manner may bestow improved disease control with fewer treatment-related toxicities. The present study develops a biochemically motivated mathematical model of antiandrogen therapy that can be tested prospectively as a predictive tool. The model includes "personalized" parameters, which address the heterogeneity in the predicted course of the disease under various androgen-deprivation schedules. Model simulations are able to capture a variety of clinically observed outcomes for "average" patient data under different intermittent schedules. The model predicts that in the absence of a competitive advantage of androgen-dependent cancer cells over castration-resistant cancer cells, intermittent scheduling can lead to more rapid treatment failure as compared to continuous treatment. However, increasing a competitive advantage for hormone-sensitive cells swings the balance in favor of intermittent scheduling, delaying the acquisition of genetic or epigenetic alterations empowering androgen resistance. Given the near universal prevalence of antiandrogen treatment failure in the absence of competing mortality, such modeling has the potential of developing into a useful tool for incorporation into clinical research trials and ultimately as a prognostic tool for individual patients.
authors: Mathematical Biosciences Institute, Ohio State University, Columbus, OH 43210, USA. hjain@mbi.osu.edu
authors: Harsh Vardhan
authors: HV
authors: Jain
authors: Steven K
authors: SK
authors: Clinton
authors: Arvinder
authors: A
authors: Bhinder
authors: Avner
authors: A
authors: Friedman
mesh_terms: D000465:Algorithms; D000726:Androgen Antagonists / Q000097:blood / Q000627:therapeutic use*; D000818:Animals; D018931:Antineoplastic Agents, Hormonal / Q000627:therapeutic use; D002478:Cells, Cultured; D018450:Disease Progression; D004334:Drug Administration Schedule; D005485:Flutamide / Q000627:therapeutic use; D017273:Goserelin / Q000627:therapeutic use; D006801:Humans; D008297:Male; D008954:Models, Biological; D009919:Orchiectomy; D009929:Organ Size / Q000187:drug effects; D011467:Prostate / Q000187:drug effects / Q000254:growth & development / Q000378:metabolism; D017430:Prostate-Specific Antigen / Q000097:blood; D011471:Prostatic Neoplasms / Q000097:blood / Q000188:drug therapy* / Q000473:pathology; D051381:Rats; D017207:Rats, Sprague-Dawley; D011944:Receptors, Androgen / Q000378:metabolism; D013739:Testosterone / Q000097:blood / Q000493:pharmacokinetics / Q000494:pharmacology; D016896:Treatment Outcome
chemical_list: D000726:Androgen Antagonists; D018931:Antineoplastic Agents, Hormonal; D011944:Receptors, Androgen; D017273:Goserelin; D013739:Testosterone; D005485:Flutamide; D017430:Prostate-Specific Antigen