A QSP model of prostate cancer immunotherapy to identify effective combination therapies

Roberta Coletti,Lorena Leonardelli,Luca Marchetti,Silvia Parolo

doi:10.1038/s41598-020-65590-0

Abstract

Immunotherapy, by enhancing the endogenous anti-tumor immune responses, is showing promising results for the treatment of numerous cancers refractory to conventional therapies. However, its effectiveness for advanced castration-resistant prostate cancer remains unsatisfactory and new therapeutic strategies need to be developed. To this end, systems pharmacology modeling provides a quantitative framework to test in silico the efficacy of new treatments and combination therapies. In this paper we present a new Quantitative Systems Pharmacology (QSP) model of prostate cancer immunotherapy, calibrated using data from pre-clinical experiments in prostate cancer mouse models. We developed the model by using Ordinary Differential Equations (ODEs) describing the tumor, key components of the immune system, and seven treatments. Numerous combination therapies were evaluated considering both the degree of tumor inhibition and the predicted synergistic effects, integrated into a decision tree. Our simulations predicted cancer vaccine combined with immune checkpoint blockade as the most effective dual-drug combination immunotherapy for subjects treated with androgen-deprivation therapy that developed resistance. Overall, the model presented here serves as a computational framework to support drug development, by generating hypotheses that can be tested experimentally in pre-clinical models.

Highlights

Immunotherapy, by enhancing the endogenous anti-tumor immune responses, is showing promising results for the treatment of numerous cancers refractory to conventional therapies
Peng and coworkers already described the action of Cytotoxic T Lymphocytes (CTLs), dendritic cells, Tregs, androgens and interleukin-2 (IL-2) in the tumor microenvironment, we extended the characterization of the immune system by including Myeloid-Derived Suppressor Cells (MDSCs) and Natural Killer (NK) cells as potential targets for new prostate cancer therapies
Starting from the model introduced by Peng et al.[46], we built a mathematical model based on Ordinary Differential Equations (ODEs) describing the prostate cancer and its interaction with the immune system

Summary

Introduction

Immunotherapy, by enhancing the endogenous anti-tumor immune responses, is showing promising results for the treatment of numerous cancers refractory to conventional therapies. Its effectiveness for advanced castration-resistant prostate cancer remains unsatisfactory and new therapeutic strategies need to be developed To this end, systems pharmacology modeling provides a quantitative framework to test in silico the efficacy of new treatments and combination therapies. QSP models allow the inclusion of several data from different sources, integrated in compartmental and hierarchical mathematical models This approach tests different therapeutic protocols, studying drug responses and effects as well as understanding in a more accurate way the mechanisms behind a modeled phenomenon[22]. Since PCa cell proliferation is dependent on androgen signaling, androgen deprivation therapy, either by chemical or surgical castration, is the first-line treatment for advanced PCa40 This therapy is initially highly effective in most of the patients, in some cases the tumor evolves into an androgen independent form that currently lacks efficacious therapeutic options[41]. Evaluating combination therapies is another important step to improve therapeutic benefits[45]

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Conclusion