AUTHOR=Han Xu , Sun Qiang-Guo , Zang Dan , Chen Jun 

TITLE=Comprehensive fecal metagenomic and metabolomic analysis reveals the role of gut microbiota and metabolites in detecting brain metastasis of small cell lung cancer

JOURNAL=Frontiers in Microbiology

VOLUME=Volume 16 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/microbiology/articles/10.3389/fmicb.2025.1673983

DOI=10.3389/fmicb.2025.1673983

ISSN=1664-302X

ABSTRACT=BackgroundBrain metastasis (BM) is a common and highly lethal complication in patients with small cell lung cancer (SCLC). People have paid great attention to exploring the relationship between gut microbiota and the occurrence and development of cancer. This study investigated the relationship between brain metastasis, gut microbiota, and their metabolites in SCLC, providing new insights for the prevention and diagnosis of brain metastasis in SCLC.MethodsBaseline fecal samples were collected from 45 participants, including 15 patients with BM and 30 patients with no distant metastasis who were newly diagnosed with SCLC. The gut microbiota and metabolite levels were analyzed using metagenomics and untargeted metabolomics, and machine learning models were utilized to identify differences and potential biomarkers.ResultsGut microbiota composition varied significantly between the two groups. Genus such as Alistipes and Streptococcus were more abundant in the brain metastasis group, while Bacteroides and Prevotella predominated in patients without distant spread. Metabolomic profiling identified several metabolites inversely associated with brain metastasis, including leukotriene F4, benzoic acid, velnacrine, piperidine, and an unidentified compound labeled C20916. KEGG pathway analysis linked multiple key physiological processes, such as aminobenzoate degradation, carbapenem biosynthesis, toluene degradation, dioxin degradation, and benzoate degradation, underscoring the complex role of gut microbial metabolites in cancer progression. Furthermore, machine learning models identified key biomarkers, including the genus Marvinbryantia and the metabolites benzoic acid, which showed strong discriminatory ability for brain metastasis. After robust validation, the model demonstrated good performance with excellent discriminative power (AUC = 0.80).ConclusionCompared to patients without distant metastasis, SCLC patients with BM exhibit distinctive gut microbial and metabolite profiles. These findings suggest that specific gut microbes and their metabolic products may serve as valuable biomarkers for diagnosing and stratifying treatment in brain metastatic SCLC.