Non-local multiscale approach for the impact of go or grow hypothesis on tumour-viruses interactions

We propose and study computationally a novel non-local multiscale moving boundary mathematical model for tumour and oncolytic virus (OV) interactions when we consider the go or grow hypothesis for cancer dynamics. This spatio-temporal model focuses on two cancer cell phenotypes that can be infected...

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Autores principales:	Abdulhamed Alsisi, Raluca Eftimie, Dumitru Trucu
Formato:	article
Lenguaje:	EN
Publicado:	AIMS Press 2021
Materias:	multiscale cancer modelling non-local cell adhesion tumour-oncolytic viruses interactions go or grow hypothesis migration-proliferation dichotomy Biotechnology TP248.13-248.65 Mathematics QA1-939
Acceso en línea:	https://doaj.org/article/20ce4da2c0a64a8ab256811b720b3861
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spelling	oai:doaj.org-article:20ce4da2c0a64a8ab256811b720b38612021-11-09T02:01:21ZNon-local multiscale approach for the impact of go or grow hypothesis on tumour-viruses interactions10.3934/mbe.20212671551-0018https://doaj.org/article/20ce4da2c0a64a8ab256811b720b38612021-06-01T00:00:00Zhttps://www.aimspress.com/article/doi/10.3934/mbe.2021267?viewType=HTMLhttps://doaj.org/toc/1551-0018We propose and study computationally a novel non-local multiscale moving boundary mathematical model for tumour and oncolytic virus (OV) interactions when we consider the go or grow hypothesis for cancer dynamics. This spatio-temporal model focuses on two cancer cell phenotypes that can be infected with the OV or remain uninfected, and which can either move in response to the extracellular-matrix (ECM) density or proliferate. The interactions between cancer cells, those among cancer cells and ECM, and those among cells and OV occur at the macroscale. At the micro-scale, we focus on the interactions between cells and matrix degrading enzymes (MDEs) that impact the movement of tumour boundary. With the help of this multiscale model we explore the impact on tumour invasion patterns of two different assumptions that we consider in regard to cell-cell and cell-matrix interactions. In particular we investigate model dynamics when we assume that cancer cell fluxes are the result of local advection in response to the density of extracellular matrix (ECM), or of non-local advection in response to cell-ECM adhesion. We also investigate the role of the transition rates between mainly-moving and mainly-growing cancer cell sub-populations, as well as the role of virus infection rate and virus replication rate on the overall tumour dynamics.Abdulhamed AlsisiRaluca EftimieDumitru TrucuAIMS Pressarticlemultiscale cancer modellingnon-local cell adhesiontumour-oncolytic viruses interactionsgo or grow hypothesismigration-proliferation dichotomyBiotechnologyTP248.13-248.65MathematicsQA1-939ENMathematical Biosciences and Engineering, Vol 18, Iss 5, Pp 5252-5284 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	multiscale cancer modelling non-local cell adhesion tumour-oncolytic viruses interactions go or grow hypothesis migration-proliferation dichotomy Biotechnology TP248.13-248.65 Mathematics QA1-939
spellingShingle	multiscale cancer modelling non-local cell adhesion tumour-oncolytic viruses interactions go or grow hypothesis migration-proliferation dichotomy Biotechnology TP248.13-248.65 Mathematics QA1-939 Abdulhamed Alsisi Raluca Eftimie Dumitru Trucu Non-local multiscale approach for the impact of go or grow hypothesis on tumour-viruses interactions
description	We propose and study computationally a novel non-local multiscale moving boundary mathematical model for tumour and oncolytic virus (OV) interactions when we consider the go or grow hypothesis for cancer dynamics. This spatio-temporal model focuses on two cancer cell phenotypes that can be infected with the OV or remain uninfected, and which can either move in response to the extracellular-matrix (ECM) density or proliferate. The interactions between cancer cells, those among cancer cells and ECM, and those among cells and OV occur at the macroscale. At the micro-scale, we focus on the interactions between cells and matrix degrading enzymes (MDEs) that impact the movement of tumour boundary. With the help of this multiscale model we explore the impact on tumour invasion patterns of two different assumptions that we consider in regard to cell-cell and cell-matrix interactions. In particular we investigate model dynamics when we assume that cancer cell fluxes are the result of local advection in response to the density of extracellular matrix (ECM), or of non-local advection in response to cell-ECM adhesion. We also investigate the role of the transition rates between mainly-moving and mainly-growing cancer cell sub-populations, as well as the role of virus infection rate and virus replication rate on the overall tumour dynamics.
format	article
author	Abdulhamed Alsisi Raluca Eftimie Dumitru Trucu
author_facet	Abdulhamed Alsisi Raluca Eftimie Dumitru Trucu
author_sort	Abdulhamed Alsisi
title	Non-local multiscale approach for the impact of go or grow hypothesis on tumour-viruses interactions
title_short	Non-local multiscale approach for the impact of go or grow hypothesis on tumour-viruses interactions
title_full	Non-local multiscale approach for the impact of go or grow hypothesis on tumour-viruses interactions
title_fullStr	Non-local multiscale approach for the impact of go or grow hypothesis on tumour-viruses interactions
title_full_unstemmed	Non-local multiscale approach for the impact of go or grow hypothesis on tumour-viruses interactions
title_sort	non-local multiscale approach for the impact of go or grow hypothesis on tumour-viruses interactions
publisher	AIMS Press
publishDate	2021
url	https://doaj.org/article/20ce4da2c0a64a8ab256811b720b3861
work_keys_str_mv	AT abdulhamedalsisi nonlocalmultiscaleapproachfortheimpactofgoorgrowhypothesisontumourvirusesinteractions AT ralucaeftimie nonlocalmultiscaleapproachfortheimpactofgoorgrowhypothesisontumourvirusesinteractions AT dumitrutrucu nonlocalmultiscaleapproachfortheimpactofgoorgrowhypothesisontumourvirusesinteractions
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Non-local multiscale approach for the impact of go or grow hypothesis on tumour-viruses interactions

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