Journal Article

Characteristics of gut and lung microbiota in patients with lung masses and their relationship with clinical features

Xu, Nuo, Zhou, Jian, Shen, Jiacheng, Hu, Jie, Song, Yuanlin, Yang, Yanping, Tong, Lin, Ye, Maosong, Zhao, Xing, Wei, Sulan, Wu, Shengdi

2025

Overview

Objectives The exploration of how dysbiosis relates to lung masses is still nascent, with few studies focusing on the microbial characteristics across various sites. Therefore, we categorized the microbiota into feces and bronchoalveolar fluid (BALF) groups to compare microbial characteristics between benign and malignant masses, analyze their clinical correlations, and develop predictive models for lung cancer. Methods A total of 238 fecal samples and 34 BALF samples were collected from patients with benign and malignant masses and then analyzed by 16 SrRNA. We explored the distinct composition of the gut and lung microbiota and their associations with clinical features. The diagnostic models were constructed using microbial features identified through two approaches: random forest algorithm with five-fold cross-validation and comparative analysis of significantly differential taxa. The performance evaluation was subsequently conducted using receiver operating characteristic (ROC) analysis. Results There was no significant difference in α-and β-diversity between feces and BALF groups. The relative abundance of Lachnospiraceae_NK4A136_group ( P  = 0.003232) and Erysipelotrichaceae_UCG-003 ( P  = 0.01316) in feces group and Proteobacteria ( P  = 0.03654) in BALF group were significantly increased in lung cancer patients. We also found Bacteroides ( P  = 0.01458) was abundant in NSCLC than those of SCLC in feces group, while the BALF group was dominated by norank_c_Cyanobacteria ( P  = 0.03384). Smoking history appeared to be related to the distribution of microbiota, with enrichment of Parabacteroides ( P  = 0.02054) in feces and Prevotella_1 ( P  = 0.03286) in BALF. Furthermore, the patients with Sellimonas ( P  = 0.04148) in feces and Alloprevotella ( P  = 0.04283) in BALF seemed to have better response to chemotherapy combined with immunotherapy. For differentiating benign and malignant masses, the combination of Megasphaera and norank_p__Saccharibacteria in BALF demonstrated superior predictive performance, with an AUC reaching 0.8 (95% CI 0.59-1). Conclusion The microbiota composition significantly differed between benign and malignant masses in both fecal and BALF groups, with minimal evidence supporting microbial migration between these two sites. Our findings suggest that BALF microbiota may serve as a more reliable biomarker for lung masses classification, offering valuable insights for early diagnosis and clinical decision-making.

• Publisher: BioMed Central,BioMed Central Ltd,Springer Nature B.V,BMC
• Subject: Adult / Aged / Bacteria - classification / Bacteria - genetics / Bacteria - isolation & purification / Benign / Biological Microscopy / Biomarkers / Biomedical and Life Sciences / Bronchoalveolar Lavage Fluid - microbiology / Bronchoscopy / Bronchus / Care and treatment / Cell differentiation / Chemotherapy / Chronic obstructive pulmonary disease / Clinical features / Comparative analysis / Composition / Cyanobacteria / Decision making / Decision trees / Diagnosis / Dysbacteriosis / Dysbiosis - microbiology / Feces / Feces - microbiology / Female / Gastrointestinal Microbiome / Gut microbiota / Health aspects / Humans / Immunotherapy / Lavage / Life Sciences / Lung - microbiology / Lung - pathology / Lung cancer / Lung masses / Lung microbiota / Lung Neoplasms - diagnosis / Lung Neoplasms - microbiology / Lung Neoplasms - pathology / Male / Metabolism / Microbiology / Microbiota / Microbiota (Symbiotic organisms) / Microorganisms / Middle Aged / Mycology / Non-small cell lung carcinoma / Parasitology / Patient outcomes / Performance evaluation / Prediction models / Relative abundance / Risk factors / ROC Curve / Tumors / Virology