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J R Soc Interface. 2017 Nov;14(136). pii: 20170490. doi: 10.1098/rsif.2017.0490.

The biology and mathematical modelling of glioma invasion: a review.

Author information

1
Department of Systems Immunology and Braunschweig Integrated Centre of Systems Biology, Helmholtz Centre for Infection Research, Braunschweig, Germany.
2
Centre for Information Services and High Performance Computing, Technische Universität Dresden, Germany.
3
Institute for Medical Informatics and Biometry, Technische Universität Dresden, Germany.
4
National Center for Tumor Diseases (NCT), Dresden, Germany.
5
Institute for Clinical Genetics, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, Germany.
6
German Cancer Consortium (DKTK), partner site, Dresden, Germany.
7
German Cancer Research Center (DKFZ), Heidelberg, Germany.
8
Precision Neurotherapeutics Innovation Program, Mayo Clinic, Phoenix, AZ, USA.
9
Centre for Information Services and High Performance Computing, Technische Universität Dresden, Germany andreas.deutsch@tu-dresden.de.

Abstract

Adult gliomas are aggressive brain tumours associated with low patient survival rates and limited life expectancy. The most important hallmark of this type of tumour is its invasive behaviour, characterized by a markedly phenotypic plasticity, infiltrative tumour morphologies and the ability of malignant progression from low- to high-grade tumour types. Indeed, the widespread infiltration of healthy brain tissue by glioma cells is largely responsible for poor prognosis and the difficulty of finding curative therapies. Meanwhile, mathematical models have been established to analyse potential mechanisms of glioma invasion. In this review, we start with a brief introduction to current biological knowledge about glioma invasion, and then critically review and highlight future challenges for mathematical models of glioma invasion.

KEYWORDS:

cell phenotypic plasticity; glioma invasion; infiltrative tumour morphology; malignant progression; mathematical modelling

PMID:
29118112
PMCID:
PMC5721156
DOI:
10.1098/rsif.2017.0490
[Indexed for MEDLINE]
Free PMC Article

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