Characteristics of gut and lung microbiota in patients with lung masses and their relationship with clinical featuresOriginal paper
Karen Pendergrass is a microbiome researcher specializing in microbiome-targeted interventions (MBTIs). She systematically analyzes scientific literature to identify microbial patterns, develop hypotheses, and validate interventions. As the founder of the Microbiome Signatures Database, she bridges microbiome research with clinical practice. In 2012, based on her own investigative research, she became the first documented case of FMT for Celiac Disease, four years before the first published case study.
Read MoreWhat was studied?
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.
Who was studied?
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.
What were the most important findings?
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).
What are the greatest implications of this study?
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.