Inference of glioblastoma migration and proliferation rates using single time-point images.
Journal
Communications biology
ISSN: 2399-3642
Titre abrégé: Commun Biol
Pays: England
ID NLM: 101719179
Informations de publication
Date de publication:
13 04 2023
13 04 2023
Historique:
received:
31
08
2022
accepted:
23
03
2023
medline:
17
4
2023
entrez:
13
4
2023
pubmed:
14
4
2023
Statut:
epublish
Résumé
Cancer cell migration is a driving mechanism of invasion in solid malignant tumors. Anti-migratory treatments provide an alternative approach for managing disease progression. However, we currently lack scalable screening methods for identifying novel anti-migratory drugs. To this end, we develop a method that can estimate cell motility from single end-point images in vitro by estimating differences in the spatial distribution of cells and inferring proliferation and diffusion parameters using agent-based modeling and approximate Bayesian computation. To test the power of our method, we use it to investigate drug responses in a collection of 41 patient-derived glioblastoma cell cultures, identifying migration-associated pathways and drugs with potent anti-migratory effects. We validate our method and result in both in silico and in vitro using time-lapse imaging. Our proposed method applies to standard drug screen experiments, with no change needed, and emerges as a scalable approach to screen for anti-migratory drugs.
Identifiants
pubmed: 37055469
doi: 10.1038/s42003-023-04750-0
pii: 10.1038/s42003-023-04750-0
pmc: PMC10102065
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
402Informations de copyright
© 2023. The Author(s).
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