| Autor: |
Mahasa KJ; DST/NRF Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA), University of Stellenbosch, Stellenbosch, South Africa., Eladdadi A; The College of Saint Rose, Albany, NY, United States of America., de Pillis L; Harvey Mudd College, Claremont, CA, United States of America., Ouifki R; Department of Mathematics and Applied Mathematics, University of Pretoria, Pretoria, South Africa. |
| Jazyk: |
angličtina |
| Zdroj: |
PloS one [PLoS One] 2017 Sep 21; Vol. 12 (9), pp. e0184347. Date of Electronic Publication: 2017 Sep 21 (Print Publication: 2017). |
| DOI: |
10.1371/journal.pone.0184347 |
| Abstrakt: |
In the present paper, we address by means of mathematical modeling the following main question: How can oncolytic virus infection of some normal cells in the vicinity of tumor cells enhance oncolytic virotherapy? We formulate a mathematical model describing the interactions between the oncolytic virus, the tumor cells, the normal cells, and the antitumoral and antiviral immune responses. The model consists of a system of delay differential equations with one (discrete) delay. We derive the model's basic reproductive number within tumor and normal cell populations and use their ratio as a metric for virus tumor-specificity. Numerical simulations are performed for different values of the basic reproduction numbers and their ratios to investigate potential trade-offs between tumor reduction and normal cells losses. A fundamental feature unravelled by the model simulations is its great sensitivity to parameters that account for most variation in the early or late stages of oncolytic virotherapy. From a clinical point of view, our findings indicate that designing an oncolytic virus that is not 100% tumor-specific can increase virus particles, which in turn, can further infect tumor cells. Moreover, our findings indicate that when infected tissues can be regenerated, oncolytic viral infection of normal cells could improve cancer treatment. |
| Databáze: |
MEDLINE |
| Externí odkaz: |
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