Grant: Master's Award: Canada Graduate Scholarships

Glioblastoma (GB) is the most common malignant brain tumour. Unfortunately, despite some improvement in the 2-year survival rate, the long term prognosis has not significantly improved for the past 40 years, with 5-year survival rate of around 5% and overall mortality close to 100%. Even with maximal therapy, which includes surgery, radiation, and chemotherapy, the median overall survival is only 12-18 months. Patients who undergo gross total resection and who have tumor-free margins, have delayed time to recurrence and improved overall survival compared to those who undergo subtotal resection or a biopsy. There is specific function to every millimeter of brain and although we can resect some areas of the brain, it comes at cost to the patient. Furthermore, there are highly eloquent regions that cannot be disrupted even if therapeutically beneficial. Therefore, if we could identify which tissue outside of the tumour cavity is at highest risk of recurrence and which areas are low risk for recurrence, we could then provide the benefits of supramarginal resection without the cost of unnecessary brain tissue resection. The goal of this project is to create a tool that allows us to acquire high-density, image-guided biopsies of the tumor cavity following gross total resection of a GB. These biopsies will allow us to describe the biochemical, molecular, and cellular features of the tumour niches that drive GB recurrence. We will then distill the high dimensional descriptive data we acquire into simple, cost-effective assays that allow for maximal resection of high-risk surrounding tissue and preservation of low-risk tissue. If successful, this would set the foundation for a personalized, precision approaches to both GB resection and/or post-operative radiation.