A comparison of the microbiome composition in lower respiratory tract at different sites in early lung cancer patients.

Abstract

Lung microbiome dysbiosis has been associated with lung carcinogenesis. However, the differences in the microbiome composition at different lung sites of lung cancer patients remain little understood. Studying the whole lung microbiome in cancer patients could provide new insights for interpreting the complex interplay between the microbiome and lung cancer and finding new targets for more effective therapies and preventive measures. A total of 16 patients with non-small cell lung cancer (NSCLC) were recruited for this study. Samples were obtained from four sites, including lung tumor tissues (TT), para-tumor tissues (PT), distal normal lung tissues (DN), and bronchial tissues (BT). The DNA was isolated from the tissues, and the V3-V4 regions were amplified. Sequencing libraries were generated and sequenced on an Illumina NovaSeq6000 platform. The richness and evenness of the microbiome were generally consistent among the TT, PT, DN, and BT groups in lung cancer patients. Principal coordinate analysis (PCoA) and nonmetric multidimensional scaling (NMDS) based on Bray-Curtis, weighted and unweighted UniFrac distance showed no distinct separation trend among the four groups. Proteobacteria, Firmicutes, Bacteroidota, and Desulfobacterota were the most common phyla in all four groups, while TT showed the highest abundance of Proteobacteria and the lowest abundance of Firmicutes. At the genus level, Rubellimicrobium and Fictibacillus were higher in the TT group. In the predicted functional analysis by PICRUSt, there were no specifically discrepant pathways among the four groups. In addition, an inverse relationship between body mass index (BMI) and alpha diversity was observed in this study. A non-significant result was obtained from the microbiome diversity comparison between different tissues. However, we demonstrated that lung tumors were enriched with specific bacterial species, which might contribute to tumorigenesis. Moreover, we found an inverse relationship between BMI and alpha diversity in these tissues, providing a new clue for deciphering the mechanisms of lung carcinogenesis.