Comparative analysis of human oral microbiota associated with cancer development in participants of the Canadian Partnership for Tomorrow’s Health (CanPath) Project

Principal Investigator: Dr. Morgan Langille

Affiliation: Dalhousie University

Start Year: 2020

Investigators: Dr. Vanessa DeClercq, Dr. Morgan Langille, Dr. Johan Van Limbergen, Jacob Nearing

Microbes are small organisms such as bacteria that can live within and on the human body. These groups of microbes have been shown to play important roles in maintaining human health. Some microbes that can inhabit the body can cause disruptions that contribute to the development of chronic diseases such as cancer. One area these microbes reside is within the human oral cavity where they have been linked with certain types of cancer. However, there is currently a lack of studies that have examined the community of oral microbes in a large group of individuals that have gone on to develop cancer. Identifying microbes that are predictive of future cancer development could aid in the discovery of new risk factors for cancer development. To address this, we will study the role of oral microbes in the development of specific types of cancer using a large Canadian cohort known as the Canadian Partnership for Tomorrow’s Health (CanPath). At baseline, before cancer development, participants donated saliva samples and provided detailed information about their health status, physical measures, and lifestyle choices. Since then a subset of these individuals have developed some form of cancer. With the oral saliva sample, we can use DNA sequencing approaches along with machine learning and statistical models to study the microbes that reside within our bodies. By comparing samples from individuals that have developed cancer to healthy controls, we will attempt to detect unique microbial features that are associated to the development of certain types of cancer. The results of this study will provide important information about the usefulness of accessing oral microbes as possible way to forecast individuals at a higher risk of developing cancer.