Computational models of migration modes improve our understanding of metastasis.
Journal
APL bioengineering
ISSN: 2473-2877
Titre abrégé: APL Bioeng
Pays: United States
ID NLM: 101726398
Informations de publication
Date de publication:
Dec 2020
Dec 2020
Historique:
received:
31
07
2020
accepted:
23
10
2020
entrez:
16
11
2020
pubmed:
17
11
2020
medline:
17
11
2020
Statut:
epublish
Résumé
Tumor cells migrate through changing microenvironments of diseased and healthy tissue, making their migration particularly challenging to describe. To better understand this process, computational models have been developed for both the ameboid and mesenchymal modes of cell migration. Here, we review various approaches that have been used to account for the physical environment's effect on cell migration in computational models, with a focus on their application to understanding cancer metastasis and the related phenomenon of durotaxis. We then discuss how mesenchymal migration models typically simulate complex cell-extracellular matrix (ECM) interactions, while ameboid migration models use a cell-focused approach that largely ignores ECM when not acting as a physical barrier. This approach greatly simplifies or ignores the mechanosensing ability of ameboid migrating cells and should be reevaluated in future models. We conclude by describing future model elements that have not been included to date but would enhance model accuracy.
Identifiants
pubmed: 33195959
doi: 10.1063/5.0023748
pii: 5.0023748
pmc: PMC7647620
doi:
Types de publication
Journal Article
Review
Langues
eng
Pagination
041505Subventions
Organisme : NCI NIH HHS
ID : R01 CA206880
Pays : United States
Organisme : NINDS NIH HHS
ID : R01 NS116802
Pays : United States
Organisme : NCI NIH HHS
ID : R21 CA217735
Pays : United States
Organisme : NCI NIH HHS
ID : T32 CA009523
Pays : United States
Informations de copyright
© Author(s).
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