RESUMO
Resident microbial populations have been detected across solid tumors of diverse origins. Sequencing of the airway microbiota represents an opportunity for establishing a novel omics approach to early detection of lung cancer, as well as risk prediction of cancer development. We hypothesize that bacterial shifts in the pre-malignant lung may be detected in non-cancerous airway liquid biopsies collected during bronchoscopy. We analyzed the airway microbiome profile of near 400 patients: epithelial brushing samples from those with lung cancer, those who developed an incident cancer, and those who do not develop cancer after 10-year follow-up. Using linear discriminate analysis, we define and validate a microbial-based classifier that is able to predict incident cancer in patients before diagnosis with no clinical signs of cancer. Our results demonstrate the potential of using lung microbiome profiling as a method for early detection of lung cancer.