Identification of Prognostic Genes Associated with Expression Differentiation During Metabolism Process in Hepatocellular Carcinoma (HCC)

Abstract

Background: Metabolic disorders have attracted more and more attention from scientists in the research of various tumors, especially in hepatocellular carcinoma (HCC). The purpose of this study is to assess the prognostic significance of metabolism in HCC.Methods: The expression profile of metabolism-related gene (MRGs) were extracted from the cancer genome atlas (TCGA) database of 349 HCC-surviving patients. Subsequently, A series of biomedical computational algorithms were used to identify seven-MRGs signature as a prognostic model. GSEA analysis indicated the function and pathway enrichment of these MRGs. Then, drug sensitivity analysis found the hub gene, which tested by IHC staining.Results: 420 differential MRGs and 116 differential transcription factor (TFs) expression were extracted from HCC patients based on TCGA database. Metabolic disturbance might be involved in the development of HCC by GO and KEGG enrichment analyses. LASSO regression analysis constructed seven-MRGs signature (DHDH, ENO1, G6PD, LPCAT1, PDE6D, PIGU and PPAT), which were used to predict the prognosis of HCC patients. Further GSEA analysis found the function and pathway enrichment of these seven MRGs. Then, drug sensitivity analysis indicated G6PD might play a key role in the prognosis of HCC by chemoresistance. Finally, we used IHC staining to demonstrate the relationship of G6PD expression and clinical parameter in HCC patients.Conclusion: This study provides a potential clue for predicting the prognosis of HCC patients and further studies on HCC metabolism.