Frontiers in Bioengineering and Biotechnology (Aug 2022)

The microbiome of lower respiratory tract and tumor tissue in lung cancer manifested as radiological ground-glass opacity

  • Zhigang Wu,
  • Jie Tang,
  • Runzhou Zhuang,
  • Di Meng,
  • Lichen Zhang,
  • Chen Gu,
  • Xiao Teng,
  • Ziyue Zhu,
  • Jiacong Liu,
  • Jinghua Pang,
  • Jian Hu,
  • Xiayi Lv

DOI
https://doi.org/10.3389/fbioe.2022.892613
Journal volume & issue
Vol. 10

Abstract

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Recent studies have confirmed the existence of microbiota in the lungs. The relationship between lung ground-glass opacity (GGO) and microbiota in the lung microenvironment is not clear. In this study, we investigated the microbial composition and diversity in bronchoalveolar lavage fluid (BALF) of diseased lung segments and paired contralateral healthy lung segments from 11 GGO patients. Furthermore, lung GGO and paired normal tissues of 26 GGO patients were explored whether there are microbial characteristics related to GGO. Compared with the control group, the community richness of GGO tissue and BALF of GGO lung segment (α-diversity) and overall microbiome difference (β-diversity) had no significant difference. The microbiome composition of BALF of GGO segments is distinct from that of paired healthy lung segments [genus (Rothia), order (Lachnospiraceae), family (Lachnospiraceae), genus (Lachnospiraceae_NK4A136_group, Faecalibacterium), and species (Faecalibacterium prausnitzii, Bacteroides uniforms)]. GGO tissue and adjacent lung tissue had more significant differences at the levels of class, order, family, genus, and species level, and most of them are enriched in normal lung tissue. The area under the curve (AUC) using 10 genera-based biomarkers to predict GGO was 91.05% (95% CI: 81.93–100%). In conclusion, this study demonstrates there are significant differences in the lower respiratory tract and lung microbiome between GGO and the non-malignant control group through the BALF and lung tissues. Furthermore, some potential bacterial biomarkers showed good performance to predict GGO.

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