title: 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.
authors: Division of Radiologic Sciences - Center for Bioinformatics and Systems Biology, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC 27157, USA.
authors: Huiming
authors: H
authors: Peng
authors: Division of Radiologic Sciences - Center for Bioinformatics and Systems Biology, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC 27157, USA.
authors: Weiling
authors: W
authors: Zhao
authors: Division of Radiologic Sciences - Center for Bioinformatics and Systems Biology, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC 27157, USA.
authors: Hua
authors: H
authors: Tan
authors: Division of Radiologic Sciences - Center for Bioinformatics and Systems Biology, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC 27157, USA.
authors: Zhiwei
authors: Z
authors: Ji
authors: College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China.
authors: Jingsong
authors: J
authors: Li
authors: Division of Radiologic Sciences - Center for Bioinformatics and Systems Biology, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC 27157, USA.
authors: King
authors: K
authors: Li
authors: Division of Radiologic Sciences - Center for Bioinformatics and Systems Biology, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC 27157, USA.
authors: Xiaobo
authors: X
authors: Zhou
mesh_terms: D000728:Androgens / Q000378:metabolism; D000818:Animals; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D004360:Drug Therapy, Computer-Assisted / Q000379:methods*; D006801:Humans; D007376:Interleukin-2 / Q000037:antagonists & inhibitors; D008297:Male; D008954:Models, Biological; D008962:Models, Theoretical; D009919:Orchiectomy; D011379:Prognosis; D011471:Prostatic Neoplasms / Q000276:immunology / Q000628:therapy*; D050378:T-Lymphocytes, Regulatory / Q000378:metabolism; D016896:Treatment Outcome; D059016:Tumor Microenvironment; D014611:Vaccination
chemical_list: D000728:Androgens; D007376:Interleukin-2