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Characterization of microbiome in bronchoalveolar lavage fluid of patients with lung cancer comparing with benign mass like lesions
Cited 194 time in
Web of Science
Cited 212 time in Scopus
- Authors
- Issue Date
- 2016-12
- Publisher
- Elsevier BV
- Citation
- Lung Cancer, Vol.102, pp.89-95
- Abstract
- Objectives: Disruption in the stability of respiratory microbiota is known to be associated with many chronic respiratory diseases. However, only few studies have examined microbiomes in lung cancer. Therefore, we characterized and compared the microbiomes of patients with lung cancer and those with benign mass-like lesions. Materials and methods: Bronchoalveolar fluid was collected prospectively to evaluate lung masses in patients who had undergone bronchoscopies from May to September 2015. Twenty-eight patients (20 male, 8 female) were enrolled: 20 diagnosed with lung cancer and 8 diagnosed with benign diseases. Samples were analysed by 165 rRNA-based next-generation sequencing. Results: The participants' mean age was 64 +/- 11 years. Bacterial operational taxonomic units were classified into 26 phyla, 44 classes, 81 orders, 153 families, 288 genera, and 797 species. The relative abundance of two phyla (Firmicutes and TM7) was significantly increased in patients with lung cancer (p = 0.037 and 0.035, respectively). Furthermore, two genera (Veillonella and Megasphaera) were relatively more abundant in lung cancer patients (p = 0.003 and 0.022, respectively). The area under the curve of a combination of these two genera used to predict lung cancer was 0.888 (sensitivity = 95.0%, specificity = 75.0% and sensitivity 70.0%, specificity = 100.0%; p = 0.002). Conclusion: The results indicate that differences exist in the bacterial communities of patients with lung cancer and those with benign mass-like lesions. The genera Veillonella and Megasphaera showed the potential to serve as biomarkers to predict lung cancer. Thus, the lung microbiota may change the environment in patients with lung cancer. (C) 2016 Elsevier Ireland Ltd. All rights reserved.
- ISSN
- 0169-5002
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