Gut Clostridium aminophilum as a protective microbe in never-smoker lung cancer: insights from metagenomics and machine learning
Jiandong Zhang, Leping Fang, Chunbo Ma, Zixuan Hu, Chunyi Chen, Ting Zhu, Junlei Ying, Wentao Zhu, Gang Huang, Jiangwei Ni, Chu Zhang, Guangmao YuABSTRACT
Lung cancer in never-smoking patients (LCINS) has gradually gained attention in recent years, and emerging evidence points to a potential role of the gut microbiota in LCINS by modulating host immunity and metabolism. In this study, metagenomics was performed on stool samples from 24 LCINS patients and 18 healthy individuals. LCINS patients exhibited reduced microbial richness in α-diversity compared with healthy controls, and differences in principal component distribution were observed. Pathway enrichment analyses revealed that LPS biosynthesis capacity was significantly increased, whereas the fatty acid biosynthesis pathway was significantly decreased in LCINS. A total of 317 differentially abundant species were identified, including 29 assigned to the module most strongly associated with LCINS based on weighted gene co-expression network (WGCNA). Then, 36 machine learning–based diagnostic models were constructed based on these 29 species, with the glmBoost + Ridge model showing the best performance for LCINS discrimination (AUC = 0.855). SHAP (SHapley Additive exPlanations) identified
IMPORTANCE
Lung cancer remains the leading cause of cancer incidence and mortality worldwide, and the proportion of lung cancer in patients who have never smoked (LCINS) has been steadily increasing. However, the potential role of the gut microbiota in this disease has not been fully explored. In this study, we characterized the gut microbial spectrum of LCINS patients using metagenomic sequencing and developed a lung cancer predictive model with translational potential. Importantly, we identified a beneficial bacterium,