Speaker
Description
Glioblastoma is a highly aggressive primary brain tumour characterised by rapid growth and diffuse infiltration into surrounding tissue, making complete surgical removal and effective treatment extremely challenging. An important feature of glioblastoma is the behaviour of tumour cells at the invasive margin, which drives the disease progression, highlighting the need for mathematical models to understand the motility of these cells. The Proliferation-Invasion-Recruitment (PIR) partial differential equation (PDE) model was previously developed to model an experimental system in which virally transduced Platelet-Derived Growth Factor (PDGF) expressing glial progenitor cells produce PDGF, and therefore promote migration and proliferation of both transduced and already present non-transduced cells. Here, we develop an individual-based model for transduced and non-transduced glial cell migration and proliferation coupled to a PDE for PDGF dynamics. We use the model, along with experimental cell-tracking data, to explore the dynamics of chemotaxis, random motility and tissue-dependent migration of both transduced and non-transduced cells in response to the emergent PDGF gradients and grey-white matter tissue distribution. Overall, these models help explain how cell migration, PDGF driven recruitment, and tissue dependent migration may contribute to glioblastoma progression.
