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

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 str...

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Vydané v:Scientific reports Ročník 10; číslo 1; s. 9063
Hlavní autori: Coletti, Roberta, Leonardelli, Lorena, Parolo, Silvia, Marchetti, Luca
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: London Nature Publishing Group UK 03.06.2020
Nature Publishing Group
Predmet:
119/118
631/114/2397
631/553/2700
631/67/1059/2325
631/67/589/466
692/4028/67/589/466
Animal models
Animals
Cancer immunotherapy
Cancer therapies
Cancer vaccines
Cancer Vaccines - immunology
Castration
Cell Line, Tumor
Combined Modality Therapy - methods
Combined vaccines
Computer applications
Differential equations
Drug development
Humanities and Social Sciences
Humans
Immune checkpoint
Immune response
Immune system
Immunologic Factors - immunology
Immunotherapy
Immunotherapy - methods
Male
Mice
Models, Biological
multidisciplinary
Ordinary differential equations
Pharmacology
Prostate - immunology
Prostate cancer
Prostatic Neoplasms, Castration-Resistant - immunology
Prostatic Neoplasms, Castration-Resistant - therapy
Science
Science (multidisciplinary)
Synergistic effect
ISSN:2045-2322, 2045-2322
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Shrnutí: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.
Bibliografia:ObjectType-Article-1
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ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-020-65590-0