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Spatio-temporal modelling of phenotypic heterogeneity in tumour tissues and its impact on radiotherapy treatment

Celora, Giulia L; Byrne, Helen M; Kevrekidis, PG; (2023) Spatio-temporal modelling of phenotypic heterogeneity in tumour tissues and its impact on radiotherapy treatment. Journal of Theoretical Biology , 556 , Article 111248. 10.1016/j.jtbi.2022.111248. (In press). Green open access

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Abstract

We present a mathematical model that describes how tumour heterogeneity evolves in a tissue slice that is oxygenated by a single blood vessel. Phenotype is identified with the stemness level of a cell and determines its proliferative capacity, apoptosis propensity and response to treatment. Our study is based on numerical bifurcation analysis and dynamical simulations of a system of coupled, non-local (in phenotypic “space”) partial differential equations that link the phenotypic evolution of the tumour cells to local tissue oxygen levels. In our formulation, we consider a 1D geometry where oxygen is supplied by a blood vessel located on the domain boundary and consumed by the tumour cells as it diffuses through the tissue. For biologically relevant parameter values, the system exhibits multiple steady states; in particular, depending on the initial conditions, the tumour is either eliminated (“tumour-extinction”) or it persists (“tumour-invasion”). We conclude by using the model to investigate tumour responses to radiotherapy, and focus on identifying radiotherapy strategies which can eliminate the tumour. Numerical simulations reveal how phenotypic heterogeneity evolves during treatment and highlight the critical role of tissue oxygen levels on the efficacy of radiation protocols that are commonly used in the clinic.

Type: Article
Title: Spatio-temporal modelling of phenotypic heterogeneity in tumour tissues and its impact on radiotherapy treatment
Location: England
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.jtbi.2022.111248
Publisher version: https://doi.org/10.1016/j.jtbi.2022.111248
Language: English
Additional information: © 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Keywords: Science & Technology, Life Sciences & Biomedicine, Biology, Mathematical & Computational Biology, Life Sciences & Biomedicine - Other Topics, Cancer stem cells, Radio-resistance, Heterogeneity, DRUG-RESISTANCE, SOLID TUMOR, GROWTH, HYPOXIA, RADIORESISTANCE, PLASTICITY, EMERGENCE, EVOLUTION, HALLMARKS, SELECTION
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Mathematics
URI: https://discovery-pp.ucl.ac.uk/id/eprint/10162493
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