Prediction of treatment efficacy for prostate cancer using a mathematical model

Huiming Peng, Weiling Zhao, Hua Tan, Zhiwei Ji, Jingsong Li, King Li, Xiaobo Zhou

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish (US)
Article number21599
JournalScientific reports
Volume6
DOIs
StatePublished - Feb 12 2016
Externally publishedYes

ASJC Scopus subject areas

  • General

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