Identification and functional analysis of lactic acid metabolism-related differentially expressed genes in hepatocellular carcinoma

Background: Hepatocellular carcinoma (HCC) is a malignant tumor with high morbidity and mortality rate that seriously threatens human health. We aimed to investigate the expression, prognostic value, and immune cell infiltration of lactic acid metabolism-related genes (LAMRGs) in HCC using bioinformatics. Methods: The HCC database (The Cancer Genome Atlas-Liver Hepatocellular Carcinoma) was downloaded from the Cancer Genome Atlas (TCGA). Differentially expressed genes (DEGs) between normal and tumor groups were identified. The LAMRGs were obtained from literature and GeneCards and MSigDB databases. Lactic acid metabolism-related differentially expressed genes (LAMRDEGs) in HCC were screened from the DEGs and LAMRGs. Functional enrichment analyses of the screened LAMRDEGs were further conducted using Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, and Gene Set Enrichment Analysis (GSEA). The genes were used in multivariate Cox regression and least absolute shrinkage and selection operator (LASSO) analyses to construct a prognostic model. Then, a protein-protein interaction network was constructed using STRING and CTD databases. Furthermore, the CIBERSORTx online database was used to assess the relationship between immune cell infiltration and hub genes. Results: Twenty-eight lactic acid metabolism-related differentially expressed genes (LAMRDEGs) were identified. The GO and KEGG analyses showed that the LAMRDEGs were related to the prognosis of HCC. The GSEA indicated that the LAMRDEGs were significantly enriched in tumor related pathways. In the multivariate Cox regression analysis, 14 key genes (E2F1, SERPINE1, GYS2, SPP1, PCK1, CCNB1, CYP2C9, IGFBP3, KDM8, RCAN1, ALPL, FBP1, NQO1, and LCAT) were found to be independent prognostic factors of HCC. Finally, the LASSO and Cox regression analyses showed that six key genes (SERPINE1, SPP1, CCNB1, CYP2C9, NQO1, and LCAT) were associated with HCC prognosis. Moreover, the correlation analyses revealed that the expression of the six key genes were associated with immune infiltrates of HCC. Conclusion: The LAMRDEGs can predict the prognosis and may be associated with immune cells infiltration in patients with HCC. These genes might be the promising biomarkers for the prognosis and treatment of HCC.