Grant: Project Grant

Lung cancer is the leading cause of cancer-related death in Canada and around the world. More people die from lung cancer than breast, colon and prostate cancer combined. If detected at an early stage, surgery offers a chance for cure. However, many patients recur after surgery and require additional treatment. There is currently no clinical guidelines to determine who requires additional therapy. This proposal aims to use artificial intelligence to predict which patients will likely relapse. This will not only inform which patients require more treatment but save those who do not require additional treatment form unnecessary side effects. It will also save the health care system the cost of treating patients that are unlikely to benefit. Our team will also deploy sophisticated imaging technologies to provide single-cell resolution data of patient tumors before treatment with immunotherapy. These data will resolve the topography of cellular neighbourhoods present within the tumor immune microenvironment (TIME). Understanding the TIME of lung cancer is vital to understanding how immunotherapy works. As a result, we will further our understanding of why some patients have dramatic responses to immunotherapy and why others do not. These efforts will not only allow us to improve the ideal adjudication of immunotherapy to patients with earlystage operable disease but also inform on treatment of patients with advanced lung cancer.