Distinct bronchial microbiome precedes clinical diagnosis of lung cancer

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.

Automated summary

Resident microbial populations have been found in solid tumors of different origins. By analyzing the airway microbiome of nearly 400 patients, it is possible to detect bacterial shifts that occur in the pre-malignant lung in non-cancerous airway liquid biopsies. Using a microbial-based classifier, it is possible to predict the occurrence of lung cancer in patients without clinical signs of cancer.