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There were 2 million new cases of lung cancer worldwide in 2018. Annually, over 2,500 Albertans are diagnosed with lung cancer and 2,100 patients died each year from the malignancy. While lunch cancer can arise from occupational exposures and radon, most (85-90%) of lung cancer is related to tobacco use. With a net survival rate of 17%, lung cancer by far is the most common cause of cancer deaths in Alberta. Therefore, Dr. Wang and his team felt that a lung cancer screening program for tobacco smokers would potentially reduce the number of late diagnoses, leading to earlier cure and fewer deaths. Ìý

Successful lung cancer screening requires a process that will accurately detect the majority of lung cancers while minimizing harm to the vast majority of individuals without lung cancer who receive screening. Moreover, a screening program like this must be cost-effective for the health system. Ìý

To improve the selection of high-risk smokers, Dr. Wang and his team will combine predictive risk models with biomarkers, something that has rarely been explored to date. Using machine learning approaches, they have already developed a set of genomic biomarkers that can significantly improve the selection of smokers for targeted lung cancer screening by incorporating these biomarkers with the current risk models. In this project, the team will validate the genomic biomarkers in several independent cohorts by conducting whole-exome sequencing of several thousands of tobacco smokers. Ìý

Funding source: Albert Innovates Cancer Screening Research and Innovation Opportunity II Ìý