Construction of a gene-metabolite-microbiome regulatory network reveals novel therapeutic targets in bladder cancer through multi-omics analysis.

BACKGROUND

Bladder cancer (BLCA) is a prevalent malignancy with substantial consequences for patient health. This study aimed to elucidate the underlying mechanisms of BLCA through integrated multi-omics analysis.

METHODS

Tumor and adjacent tissues from BLCA patients underwent transcriptomic, whole-exome sequencing, metabolomic, and intratumoral microbiome analyses. These data were integrated with public datasets to identify key genes, metabolites, and microorganisms. Molecular subtypes were defined by key gene expression and compared for pathways, immune profiles, mutations, immunotherapy response, and drug sensitivity. Prognostic relevance was validated in external cohorts. Single-cell sequencing was applied to reveal cellular localization of key genes.

RESULTS

Three key genes (), 90 metabolites, and two microbes () were identified. Key genes negatively correlated with metabolites but not with microbes. BLCA samples were classified into two molecular clusters with distinct ECM organization, metabolic features, immune checkpoint expression, and therapeutic sensitivity. NCAM1 correlated positively with γδ T cells and negatively with M0 macrophages. Single-cell analysis revealed nine major cell types, with fibroblasts displaying the highest expression of key genes, particularly elevated in specific fibroblast subtypes. Drug prediction and docking identified candidate compounds targeting these genes with stable binding potential.

CONCLUSION

This comprehensive multi-omics analysis links key genes, metabolites, and microbes to BLCA pathogenesis. Fibroblasts emerge as central regulators, while identified gene-metabolite interactions and microbial associations provide novel insights into tumor heterogeneity. These findings highlight potential biomarkers and therapeutic targets to support precision treatment in BLCA.