Modelling the spatiotemporal dynamics of chemovirotherapy cancer treatment
Chemovirotherapy is a combination therapy with chemotherapy and oncolytic viruses. It is gaining more interest and attracting more attention in the clinical setting due to its effective therapy and potential synergistic interactions against cancer. In this paper, we develop and analyse a mathematica...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2017-01-01
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| Series: | Journal of Biological Dynamics |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/17513758.2017.1328079 |
| _version_ | 1818517056996245504 |
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| author | Joseph Malinzi Amina Eladdadi Precious Sibanda |
| author_facet | Joseph Malinzi Amina Eladdadi Precious Sibanda |
| author_sort | Joseph Malinzi |
| collection | DOAJ |
| description | Chemovirotherapy is a combination therapy with chemotherapy and oncolytic viruses. It is gaining more interest and attracting more attention in the clinical setting due to its effective therapy and potential synergistic interactions against cancer. In this paper, we develop and analyse a mathematical model in the form of parabolic non-linear partial differential equations to investigate the spatiotemporal dynamics of tumour cells under chemovirotherapy treatment. The proposed model consists of uninfected and infected tumour cells, a free virus, and a chemotherapeutic drug. The analysis of the model is carried out for both the temporal and spatiotemporal cases. Travelling wave solutions to the spatiotemporal model are used to determine the minimum wave speed of tumour invasion. A sensitivity analysis is performed on the model parameters to establish the key parameters that promote cancer remission during chemovirotherapy treatment. Model analysis of the temporal model suggests that virus burst size and virus infection rate determine the success of the virotherapy treatment, whereas travelling wave solutions to the spatiotemporal model show that tumour diffusivity and growth rate are critical during chemovirotherapy. Simulation results reveal that chemovirotherapy is more effective and a good alternative to either chemotherapy or virotherapy, which is in agreement with the recent experimental studies. |
| first_indexed | 2024-12-11T00:51:03Z |
| format | Article |
| id | doaj.art-3d313740b8874450a725d773781fd1f6 |
| institution | Directory Open Access Journal |
| issn | 1751-3758 1751-3766 |
| language | English |
| last_indexed | 2024-12-11T00:51:03Z |
| publishDate | 2017-01-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Journal of Biological Dynamics |
| spelling | doaj.art-3d313740b8874450a725d773781fd1f62022-12-22T01:26:38ZengTaylor & Francis GroupJournal of Biological Dynamics1751-37581751-37662017-01-0111124427410.1080/17513758.2017.13280791328079Modelling the spatiotemporal dynamics of chemovirotherapy cancer treatmentJoseph Malinzi0Amina Eladdadi1Precious Sibanda2University of PretoriaThe College of Saint RoseUniversity of KwaZulu NatalChemovirotherapy is a combination therapy with chemotherapy and oncolytic viruses. It is gaining more interest and attracting more attention in the clinical setting due to its effective therapy and potential synergistic interactions against cancer. In this paper, we develop and analyse a mathematical model in the form of parabolic non-linear partial differential equations to investigate the spatiotemporal dynamics of tumour cells under chemovirotherapy treatment. The proposed model consists of uninfected and infected tumour cells, a free virus, and a chemotherapeutic drug. The analysis of the model is carried out for both the temporal and spatiotemporal cases. Travelling wave solutions to the spatiotemporal model are used to determine the minimum wave speed of tumour invasion. A sensitivity analysis is performed on the model parameters to establish the key parameters that promote cancer remission during chemovirotherapy treatment. Model analysis of the temporal model suggests that virus burst size and virus infection rate determine the success of the virotherapy treatment, whereas travelling wave solutions to the spatiotemporal model show that tumour diffusivity and growth rate are critical during chemovirotherapy. Simulation results reveal that chemovirotherapy is more effective and a good alternative to either chemotherapy or virotherapy, which is in agreement with the recent experimental studies.http://dx.doi.org/10.1080/17513758.2017.1328079Chemovirotherapyreaction–diffusion equationscancer treatmentvirotherapychemotherapytravelling wavessensitivity analysis |
| spellingShingle | Joseph Malinzi Amina Eladdadi Precious Sibanda Modelling the spatiotemporal dynamics of chemovirotherapy cancer treatment Journal of Biological Dynamics Chemovirotherapy reaction–diffusion equations cancer treatment virotherapy chemotherapy travelling waves sensitivity analysis |
| title | Modelling the spatiotemporal dynamics of chemovirotherapy cancer treatment |
| title_full | Modelling the spatiotemporal dynamics of chemovirotherapy cancer treatment |
| title_fullStr | Modelling the spatiotemporal dynamics of chemovirotherapy cancer treatment |
| title_full_unstemmed | Modelling the spatiotemporal dynamics of chemovirotherapy cancer treatment |
| title_short | Modelling the spatiotemporal dynamics of chemovirotherapy cancer treatment |
| title_sort | modelling the spatiotemporal dynamics of chemovirotherapy cancer treatment |
| topic | Chemovirotherapy reaction–diffusion equations cancer treatment virotherapy chemotherapy travelling waves sensitivity analysis |
| url | http://dx.doi.org/10.1080/17513758.2017.1328079 |
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