The poor prognosis for lung cancer (LC) patients is typically associated with a late stage of disease at the time of diagnosis, highlighting the need for effective methods for early detection. Recently, it has been demonstrated that low-dose computed tomography (LDCT) screening of patients at high-risk of developing LC reduces mortality by 20%; however, issues remain, including determining what to do when LDCT screens detect lung masses that may or may not be cancerous. Currently, surgical resection is the only proven treatment option for these patients and there is an urgent need for efficient, non-invasive treatment strategies to resolve suspicious lung nodules detected through LDCT screening to improve patient outcomes. The immune system provides a key line of defense against LC development; however, as investigation in patients is difficult, the specific immune cells that respond and how cancers evade destruction by these cells remain unknown. Here, we aim to perform the first comprehensive assessment of the immune response to LC using mice genetically engineered to develop lung tumours. These "model" systems will allow us to identify the immune components necessary to prevent nodules from becoming tumours and determine the way cancers circumvent this process. Furthermore, we will confirm our findings from mice in human patient samples using unique resources and methodologies, develop new compounds to help identify lung nodules most likely to develop into LC, and determine if modulating the immune response prevents LC progression. It is our hope that this work will enable the design of effective treatment strategies that bolster immune system recognition of cancer cells in patients undergoing LDCT screening, preventing their development into more advanced tumours without the need for surgery. If successful, this will lead to the optimization of LC screening through more effective management of patients, ultimately improving the survival rates of this disease.