The Impact of Phenotypic Switching on Glioblastoma Growth and Invasion

Recently we had a paper accepted in PLoS Computational Biology, which introduces and analyses an individual-based model of glioblastoma (brain tumour) growth. From the author summary: In this work, we develop a spatial mathematical model in order to analyse the growth behavior of the brain tumour glioblastoma. Tumours of this type have a diffuse boundary, with considerable local invasion of surrounding brain tissue, making surgery difficult. At the cellular level, the progression of a glioblastoma is known to depend on the balance between cell division (proliferation) and cell movement (migration). Based on recent evidence, our model assumes that each cell in a glioblastoma tumour resides in either of two mutually exclusive states: proliferating or migrating. From a probabilistic model of switching between these two phenotypes, we go on to derive equations that link cellular phenotypes to disease progression. The model has several possible applications. For instance, it could be used to predict the rate of disease progression in an individual patient, and to improve screening methods. And here's the first figure which describes the stochastic switching of cell phenotypes.