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The Impact of Phenotypic Switching on Glioblastoma Growth and Invasion

Philip Gerlee (Institutionen för medicin, avdelningen för molekylär och klinisk medicin ; Institutionen för matematiska vetenskaper, matematik) ; Sven Nelander
PLoS Computational Biology (1553-7358). Vol. 8 (2012), 6,
[Artikel, refereegranskad vetenskaplig]

The brain tumour glioblastoma is characterised by diffuse and infiltrative growth into surrounding brain tissue. At the macroscopic level, the progression speed of a glioblastoma tumour is determined by two key factors: the cell proliferation rate and the cell migration speed. At the microscopic level, however, proliferation and migration appear to be mutually exclusive phenotypes, as indicated by recent in vivo imaging data. Here, we develop a mathematical model to analyse how the phenotypic switching between proliferative and migratory states of individual cells affects the macroscopic growth of the tumour. For this, we propose an individual-based stochastic model in which glioblastoma cells are either in a proliferative state, where they are stationary and divide, or in motile state in which they are subject to random motion. From the model we derive a continuum approximation in the form of two coupled reaction-diffusion equations, which exhibit travelling wave solutions whose speed of invasion depends on the model parameters. We propose a simple analytical method to predict progression rate from the cell-specific parameters and demonstrate that optimal glioblastoma growth depends on a non-trivial trade-off between the phenotypic switching rates. By linking cellular properties to an in vivo outcome, the model should be applicable to designing relevant cell screens for glioblastoma and cytometry-based patient prognostics.

Nyckelord: glioma-cell migration, mathematical-model, in-vivo, angiogenesis, chemotherapy, synthase, cancer, tumors, genes

Denna post skapades 2012-08-01. Senast ändrad 2016-06-30.
CPL Pubid: 160863


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Institutioner (Chalmers)

Institutionen för medicin, avdelningen för molekylär och klinisk medicin (GU)
Institutionen för matematiska vetenskaper, matematik (2005-2016)


Cell- och molekylärbiologi

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