识别介导肥胖与肝细胞癌关联的核心基因：基于线粒体代谢和免疫通路的生物信息学研究

Obesity is strongly associated with hepatocellular carcinoma (HCC), yet the molecular mechanisms linking them remain unclear. This study aimed to identify mitochondrial metabolism-related genes bridging obesity and HCC and to investigate their role in regulating the metabolic-immune microenvironment.

Public transcriptomic datasets from obesity (derived from peripheral blood mononuclear cells) and HCC (derived from liver tissue) cohorts were integrated. A multi-step bioinformatic pipeline combining differential expression analysis (DEA), weighted gene co-expression network analysis (WGCNA), and machine learning (ML) algorithms was applied to identify and validate hub genes. Associations with the tumor immune microenvironment were assessed using ssGSEA and correlation analyses.

27 core genes were identified, significantly enriched in lipid metabolism and immune response pathways. Among these, ML highlighted ACAA1 and ADI1 as downregulated candidate genes. While discovery datasets showed high diagnostic potential, ADI1 exhibited more variable performance in obesity external validation compared to the robust consistency of ACAA1. Downregulation of both genes correlated with effector T/NK cell lipid-mediated functional exhaustion and disrupted networks of immune checkpoints and chemokines, reflecting an immunosuppressive microenvironment.

ACAA1 and potentially ADI1 are downregulated candidate genes linking obesity to HCC. Their suppression likely drives obesity-related HCC progression by coupling mitochondrial metabolic reprogramming with immunosuppressive tumor microenvironment remodeling, representing potential therapeutic targets.