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Combination therapy for cancer with oncolytic virus and checkpoint inhibitor: A mathematical model
Oncolytic virus (OV) is a replication competent virus that selectively invades cancer cells; as these cells die under the viral burden, the released virus particles proceed to infect other cancer cells. Oncolytic viruses are designed to also be able to stimulate the anticancer immune response. Thus,...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5805294/ https://www.ncbi.nlm.nih.gov/pubmed/29420595 http://dx.doi.org/10.1371/journal.pone.0192449 |
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author | Friedman, Avner Lai, Xiulan |
author_facet | Friedman, Avner Lai, Xiulan |
author_sort | Friedman, Avner |
collection | PubMed |
description | Oncolytic virus (OV) is a replication competent virus that selectively invades cancer cells; as these cells die under the viral burden, the released virus particles proceed to infect other cancer cells. Oncolytic viruses are designed to also be able to stimulate the anticancer immune response. Thus, one may represent an OV by two parameters: its replication potential and its immunogenicity. In this paper we consider a combination therapy with OV and a checkpoint inhibitor, anti-PD-1. We evaluate the efficacy of the combination therapy in terms of the tumor volume at some later time, for example, 6 months from initial treatment. Since T cells kill not only virus-free cancer cells but also virus-infected cancer cells, the following question arises: Does increasing the amount of the checkpoint inhibitor always improve the efficacy? We address this question, by a mathematical model consisting of a system of partial differential equations. We use the model to construct, by simulations, an efficacy map in terms of the doses of the checkpoint inhibitor and the OV injection. We show that there are regions in the map where an increase in the checkpoint inhibitor actually decreases the efficacy of the treatment. We also construct efficacy maps with checkpoint inhibitor vs. the replication potential of the virus that show the same antagonism, namely, an increase in the checkpoint inhibitor may actually decrease the efficacy. These results have implications for clinical trials. |
format | Online Article Text |
id | pubmed-5805294 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-58052942018-02-23 Combination therapy for cancer with oncolytic virus and checkpoint inhibitor: A mathematical model Friedman, Avner Lai, Xiulan PLoS One Research Article Oncolytic virus (OV) is a replication competent virus that selectively invades cancer cells; as these cells die under the viral burden, the released virus particles proceed to infect other cancer cells. Oncolytic viruses are designed to also be able to stimulate the anticancer immune response. Thus, one may represent an OV by two parameters: its replication potential and its immunogenicity. In this paper we consider a combination therapy with OV and a checkpoint inhibitor, anti-PD-1. We evaluate the efficacy of the combination therapy in terms of the tumor volume at some later time, for example, 6 months from initial treatment. Since T cells kill not only virus-free cancer cells but also virus-infected cancer cells, the following question arises: Does increasing the amount of the checkpoint inhibitor always improve the efficacy? We address this question, by a mathematical model consisting of a system of partial differential equations. We use the model to construct, by simulations, an efficacy map in terms of the doses of the checkpoint inhibitor and the OV injection. We show that there are regions in the map where an increase in the checkpoint inhibitor actually decreases the efficacy of the treatment. We also construct efficacy maps with checkpoint inhibitor vs. the replication potential of the virus that show the same antagonism, namely, an increase in the checkpoint inhibitor may actually decrease the efficacy. These results have implications for clinical trials. Public Library of Science 2018-02-08 /pmc/articles/PMC5805294/ /pubmed/29420595 http://dx.doi.org/10.1371/journal.pone.0192449 Text en © 2018 Friedman, Lai http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Friedman, Avner Lai, Xiulan Combination therapy for cancer with oncolytic virus and checkpoint inhibitor: A mathematical model |
title | Combination therapy for cancer with oncolytic virus and checkpoint inhibitor: A mathematical model |
title_full | Combination therapy for cancer with oncolytic virus and checkpoint inhibitor: A mathematical model |
title_fullStr | Combination therapy for cancer with oncolytic virus and checkpoint inhibitor: A mathematical model |
title_full_unstemmed | Combination therapy for cancer with oncolytic virus and checkpoint inhibitor: A mathematical model |
title_short | Combination therapy for cancer with oncolytic virus and checkpoint inhibitor: A mathematical model |
title_sort | combination therapy for cancer with oncolytic virus and checkpoint inhibitor: a mathematical model |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5805294/ https://www.ncbi.nlm.nih.gov/pubmed/29420595 http://dx.doi.org/10.1371/journal.pone.0192449 |
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