Prediction of treatment efficacy for prostate cancer using a mathematical model

Abstract

Prostate immune system plays a critical role in the regulation of prostate cancer development regarding androgen-deprivation therapy (ADT) and/or immunotherapy (vaccination). In this study, we developed a mathematical model to explore the interactions between prostate tumor and immune microenvironment. This model was used to predict treatment outcomes for prostate cancer with ADT, vaccination, Treg depletion and/or IL-2 neutralization. Animal data were used to guide construction, parameter selection, and validation of our model. Our analysis shows that Treg depletion and/or IL-2 neutralization can effectively improve the treatment efficacy of combined therapy with ADT and vaccination. Treg depletion has a higher synergetic effect than that from IL-2 neutralization. This study highlights a potential therapeutic strategy in effectively managing prostate tumor growth and provides a framework of systems biology approach in studying tumor-related immune mechanism and consequent selection of therapeutic regimens.