Grant: Doctoral Research Award: Canada Graduate Scholarships

Bladder cancer that has spread to other organs (i.e. metastasized) is an aggressive, deadly disease. In recent years, new treatments have been developed that greatly benefit select patients. However these treatments have toxic side effects, and many tumours do not respond. Being able to predict which tumours will respond to a given treatment would help clinicians choose therapies that are most likely to benefit their patients. In bladder cancer that is confined to the bladder, research shows that the biological features of a patient's tumour determine whether a patient will respond to a given treatment. However, the biology of metastatic disease is greatly understudied. A potential solution to this problem lies in the blood. When cancer cells die, they release fragments of DNA into the bloodstream. This DNA (referred to as circulating tumour DNA or ctDNA) captures the biological features of the tumour. In my project, I will use ctDNA and tumour tissue samples from patients with aggressive bladder cancer to characterize the biological features of the disease. I will then train machine learning models incorporating these features to predict whether or not patients will respond to a treatment. Once validated, these models will help clinicians choose personalized, effective therapies for their patients, which will help them live longer, healthier lives.