Prediction of lung cancer using novel biomarkers based on microbiome profiling of bronchoalveolar lavage fluid

Sci Rep. 2024 Jan 19;14(1):1691. doi: 10.1038/s41598-024-52296-w.

Abstract

There is an unmet need for biomarkers for the diagnosis of lung cancer and decision criteria for lung biopsy. We comparatively investigated the lung microbiomes of patients with lung cancer and benign lung diseases. Patients who underwent bronchoscopy at Chungnam National University Hospital between June 2021 and June 2022 were enrolled. Bronchoalveolar lavage fluid (BALF) was collected from 24 patients each with lung cancer and benign lung diseases. The samples were analyzed using 16S rRNA-based metagenomic sequencing. We found that alpha diversity and the beta diversity distribution (P = 0.001) differed significantly between patients with benign lung diseases and those with lung cancer. Firmicutes was the most abundant phylum in patients with lung cancer (33.39% ± 17.439), whereas Bacteroidota was the most abundant phylum in patients with benign lung disease (31.132% ± 22.505), respectively. In differential abundance analysis, the most differentially abundant microbiota taxon was unclassified_SAR202_clade, belonging to the phylum Chloroflexi. The established prediction model distinguished patients with benign lung disease from those with lung cancer with a high accuracy (micro area under the curve [AUC] = 0.98 and macro AUC = 0.99). The BALF microbiome may be a novel biomarker for the detection of lung cancer.

MeSH terms

  • Biomarkers
  • Bronchoalveolar Lavage Fluid
  • Humans
  • Lung / pathology
  • Lung Diseases*
  • Lung Neoplasms* / diagnosis
  • Lung Neoplasms* / pathology
  • Microbiota* / genetics
  • RNA, Ribosomal, 16S / genetics

Substances

  • RNA, Ribosomal, 16S
  • Biomarkers