Abstract
BACKGROUND: Brain metastasis is a common and severe complication in non-small cell lung cancer (NSCLC) patients, significantly affecting prognosis. However, the role of gut microbiota and its metabolites in NSCLC brain metastasis remains poorly understood. This study aims to explore the relationship between gut microbiota, metabolites, and the development of brain metastasis in NSCLC. METHODS: We conducted an integrative analysis combining metagenomics and non-targeted metabolomics on baseline fecal samples from NSCLC patients with brain metastasis (n = 18) and those without distant metastasis (n = 12). Gut microbiota composition and metabolite profiles were detected and analyzed, and statistical methods, including machine learning models, were applied to identify differences and potential biomarkers. RESULTS: Significant differences in gut microbiota composition were found between the two groups, with higher microbial diversity observed in patients with brain metastasis. Specific genera, such as Paenibacillus, Fournierella, and Adlercreutzia, were enriched in the brain metastasis group. Metabolomic analysis revealed altered levels of short-chain fatty acids and other metabolites associated with immune modulation and vascular permeability, including angiotensin (1-7). These changes were linked to the metastatic process and may influence brain metastasis development. Furthermore, machine learning models identified key biomarkers, such as Raoultibacter, Mobilibacterium, and N-acetyl-L-glutamic acid, which could serve as valuable indicators for brain metastasis. CONCLUSIONS: Our findings suggest that gut microbiota dysbiosis and its metabolic products may contribute to the development of brain metastasis in NSCLC. The identification of microbiota-derived biomarkers holds potential for early detection and therapeutic intervention in NSCLC brain metastasis.