Speaker
Description
Glioblastoma (GBM) is a highly invasive brain tumour with a 5-year survival rate below 5%. The first step of treatment for GBM is surgery with the goal of removing the entire visible tumour. However, even when all the visible tumour is removed, it almost always recurs leading to the cancer’s poor prognosis. Margins between tumour tissue and healthy tissue can appear unclear during surgery. To aid in identification of tumour tissue 5-ALA is consumed prior to surgery. This leads tumour cells to accumulate protoporphyrin IX (PpIX) causing tumour tissue to fluoresce under UV light during surgery improving identification and the extent of resection during surgery.
5-ALA is converted to PpIX in cells as part of the heme biosynthesis pathway. However, the biological reason for the accumulation of PpIX in tumour cells and not healthy cells is unclear. To better understand this behaviour, we develop and analyse a mathematical model of a simplified heme biosynthesis pathway consisting of a system of ODEs. A key part of the analysis of this model is parameter sensitivity and identifiability to allow us to consider model fits to data and compare the fits for different cell type. We then compare this model to data in the literature and use RNA sequencing data to understand the relationship between the parameters and gene expression in fluorescent and non-fluorescent GBM tissue. This model can then be combined with a model of tumour growth to predict 5-ALA induced fluorescence in a tumour.
