Ingham-Dempster, T.A., Rosser, R., Corfe, B.M. et al. (1 more author) (2020) From cell to multi-crypt: Agent-based models of the human colon suggests novel processes of field cancerisation. Journal of Computational Science, 41. 101066. ISSN 1877-7503
Abstract
Colorectal cancer (CRC) is a major cause of cancer mortality. It is known that loss of APC gene function through mutation is followed by the expansion of a field of mutated tissue, but the mechanisms behind this expansion are poorly understood.
This study aimed to examine the processes involved in field expansion using two agent-based computational models: a cell-scale model allowing mapping of Apc-mutated cell expansion in small multcrypt arrays, and a tissue-scale model allowing simulation of the entire colon over oncologically relevant timescales.
The cell scale model predicts that mutated cells spread through the flat mucosa of the simulated tissue without invading neighbouring crypts - a process not previously hypothesised in the literature. The crypt-scale model’s predictions of field sizes correspond to those estimated in the literature from in vivo studies. Our dual-scale modelling approach renders the spatial and temporal scales at which field cancerisation processes occur in vivo accessible to exploration by simulation for the first time.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
Keywords: | Agent-based modelling; colorectal cancer; multi-scale modelling; simulation |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 17 Jan 2020 14:29 |
Last Modified: | 21 Oct 2021 10:35 |
Status: | Published |
Publisher: | Elsevier BV |
Refereed: | Yes |
Identification Number: | 10.1016/j.jocs.2019.101066 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:155727 |