Speaker: Yang Kuang, Arizona State University
Title: Mathematical Models of Prostate Cancer Patients Undergoing Intermittent Androgen Deprivation Therapy

Abstract: Prostate cancer is commonly treated by a form of hormone therapy called androgen suppression. This form of treatment, while successful at reducing the cancer cell population, adversely affects quality of life and typically leads to a recurrence of the cancer in an androgen-independent form. Intermittent androgen suppression aims to alleviate some of these adverse affects by cycling the patient on and off treatment. Clinical studies have suggested that intermittent therapy is capable of maintaining androgen dependence over multiple treatment cycles while increasing quality of life during off-treatment periods. We present several mathematical models of prostate cancer growth to study the dynamics of androgen suppression therapy and the production of prostate- specific antigen (PSA), a clinical marker for prostate cancer. Biologically crude preliminary models were based on the assumption of an androgen-independent (AI) cell population with constant net growth rate. These models gave poor accuracy when fitting clinical data during simulation. The biologically more refined models presented hypothesizes an AI population with increased sensitivity to low levels of androgen. We also hypothesize that PSA production is heavily dependent on androgen. The high level of accuracy in fitting clinical data with these refined models confirms these hypotheses, which are also consistent with biological evidences.

Time: Friday, April 27, 2018, 1:30-2:30pm - JOINT CAGS and Computational and Applied Math Seminar

Place: Exploratory Hall, Room 4106

Department of Mathematical Sciences
George Mason University
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