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Identifying the spatial and temporal dynamics of molecularly-distinct glioblastoma sub-populations

Morris, Bethan; Curtin, Lee; Hawkins-Daarud, Andrea; Hubbard, Matthew E; Rahman, Ruman; Smith, Stuart J; Auer, Dorothee; Tran, Nhan L; Hu, Leland S; Eschbacher, Jennifer M; Smith, Kris A; Stokes, Ashley; Swanson, Kristin R; Owen, Markus R

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Authors

Bethan Morris

Lee Curtin

Andrea Hawkins-Daarud

MATTHEW HUBBARD MATTHEW.HUBBARD@NOTTINGHAM.AC.UK
Professor of Computational and Applied Mathematics

Stuart J Smith

DOROTHEE AUER dorothee.auer@nottingham.ac.uk
Professor of Neuroimaging

Nhan L Tran

Leland S Hu

Jennifer M Eschbacher

Kris A Smith

Ashley Stokes

Kristin R Swanson



Abstract

Glioblastomas (GBMs) are the most aggressive primary brain tumours and have no known cure. Each individual tumour comprises multiple sub-populations of genetically-distinct cells that may respond differently to targeted therapies and may contribute to disappointing clinical trial results. Image-localized biopsy techniques allow multiple biopsies to be taken during surgery and provide information that identifies regions where particular sub-populations occur within an individual GBM, thus providing insight into their regional genetic variability. These sub-populations may also interact with one another in a competitive or cooperative manner; it is important to ascertain the nature of these interactions, as they may have implications for responses to targeted therapies.

Citation

Morris, B., Curtin, L., Hawkins-Daarud, A., Hubbard, M. E., Rahman, R., Smith, S. J., …Owen, M. R. (2020). Identifying the spatial and temporal dynamics of molecularly-distinct glioblastoma sub-populations. Mathematical Biosciences and Engineering, 17(5), 4905-4941. https://doi.org/10.3934/mbe.2020267

Journal Article Type Article
Acceptance Date Jul 2, 2020
Online Publication Date Jul 16, 2020
Publication Date Jul 16, 2020
Deposit Date Jul 2, 2020
Publicly Available Date Mar 28, 2024
Journal Mathematical Biosciences and Engineering
Print ISSN 1547-1063
Publisher American Institute of Mathematical Sciences (AIMS)
Peer Reviewed Peer Reviewed
Volume 17
Issue 5
Pages 4905-4941
DOI https://doi.org/10.3934/mbe.2020267
Keywords glioblastoma; EGFR; PDGFRA; interactions; mathematical oncology
Public URL https://nottingham-repository.worktribe.com/output/4745017
Publisher URL http://www.aimspress.com/article/10.3934/mbe.2020267

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