Dr. Scott Brown

Cancer is a disease of the genome, arising from spontaneous changes in the DNA of a single cell. These are mutations, and can be detected by the immune system, allowing specialized white blood cells called T cells to seek out and destroy the mutated cells. Tumours can form when these mutations are not visible to the T cells. Over the past few years there has been a flurry of research on helping the body’s immune system detect these mutated cancer cells in a strategy known as cancer immunotherapy and, in 2013, Science magazine named cancer immunotherapy as the Breakthrough of the Year. Despite some great successes, these therapies are not yet effective in all patients.

My project will use large, public, cancer genome datasets to predict, computationally, the interaction between a tumour and the immune system on a patient by patient level. There is a large but finite set of characteristics that a patient’s immune system can have, which defines the interaction between T cell and tumour. This is one reason why tumours found in different patients will be comprised of dramatically different sets of mutations. Any immunotherapy that will target these unique mutations will need to be personalized for each patient. By extracting the immune characteristics from patient genomes, I will perform computational predictions to determine which mutations are most likely to be detected by that patient’s immune system, indicating the best targets for immunotherapies.

By obtaining a better understanding of the unique interaction between tumours and T cells for any given patient, researchers will be better able to design effective immunotherapies. This could have immediate clinical consequences; improving treatment for the hundreds of thousands of people living with cancer in Canada by reducing the chance of recurrence. It would mark a leap forward in cancer immunotherapy and cancer treatment in general.