BACKGROUND: Emerging evidence has suggested that dysbiosis of the lung microbiota may be associated with the development of lung diseases. However, the interplay between the lung microbiome and lung cancer remains unclear. The aim of the present study was to evaluate and compare differences in taxonomic and derived functional profiles in the lung microbiota between lung cancer and benign pulmonary diseases. METHODS: Bronchoalveolar lavage fluid (BALF) samples were collected from 32 patients with lung cancer and 22 patients with benign pulmonary diseases, and further analyzed by 16S rRNA amplicon sequencing. The obtained sequence data were deeply analyzed by bioinformatics methods. RESULTS: A significant differentiation trend was observed between the lung cancer and control groups based on principal coordinate analysis (PCoA), while richness and evenness in the lung microbiome of lung cancer patients generally resembled those of patients with benign pulmonary diseases. Phylum and six genera (c: and ) were enriched in the lung cancer group compared with the control group (adjust P<0.05). The area under the curve (AUC) combining the microbiome with clinical tumor markers to predict lung cancer was 84.52% (95% CI: 74.06-94.97%). In addition, predicted KEGG pathways showed that the functional differences in metabolic pathways of microbiome varied with groups. CONCLUSIONS: The results indicated that differences existed in the lung microbiome of patients with lung cancer and those with benign pulmonary diseases, and some certain bacteria may have potential to predict lung cancer, though future larger-sample studies are required to validate this supposition.