BMC Microbiology (Aug 2023)

Microbiota profiles in the saliva, cancerous tissues and its companion paracancerous tissues among Chinese patients with lung cancer

  • Yuhan Zhou,
  • Hongfen Zeng,
  • Kai Liu,
  • Hui Pan,
  • Baohui Wang,
  • Minghua Zhu,
  • Jiawei Wang,
  • Haoyi Wang,
  • Hongwei Chen,
  • Dan Shen,
  • Yue Wang,
  • Zhaonan Yu

DOI
https://doi.org/10.1186/s12866-023-02882-1
Journal volume & issue
Vol. 23, no. 1
pp. 1 – 8

Abstract

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Abstract Background Despite the growing interest in the impact of the gut microbiome on cancer, the relationship between the lung microbiome and lung cancer has received limited investigation. Additionally, the composition of the oral microbiome was found to differ from that of individuals with lung cancer, indicating that these microorganisms may serve as potential biomarkers for the detection of lung cancer. Methods Forty-three Chinese lung cancer patients were enrolled in the current retrospective study and 16 S rRNA sequencing was performed on saliva, cancerous tissue (CT) and paracancerous tissue (PT) samples. Results Diversity and species richness were significantly different between the oral and lung microbiota. Lung microbiota were largely composed of the phyla Proteobacteria, Firmicutes, Bacteroidetes and Actinobacteria. The relative abundance of Promicromonosporacea and Chloroflexi increased in CT, while Enterococcaceae and Enterococcus were enriched in PT (p<0.05). A cancer-related microbiota model was constructed and produced an area under the curve of 0.74 in the training set, indicating discrimination between subjects with and without cancer. Conclusions Characterization of microbiota in saliva, CT and PT from Chinese lung cancer patients revealed little difference between CT and PT, indicating that the tumor and its microenvironment might influence the local microbiome. A model to distinguish between CT and PT was constructed, which has the potential to enhance our comprehension of the involvement of microbiota in the pathogenesis of lung cancer and identify novel therapeutic targets.

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