Metabolic Reprogramming and Its Relationship to Survival in Hepatocellular Carcinoma

Abstract

Hepatocarcinogenesis is frequently accompanied by substantial metabolic reprogramming to maximize the growth and proliferation of cancer cells. In this study, we carried out a comprehensive study of metabolomics and lipidomics profiles combined with gene expression analysis to characterize the metabolic reprogramming in hepatocellular carcinoma (HCC). Compared with adjacent noncancerous liver tissue, the enhanced aerobic glycolysis and de novo lipogenesis (DNL) and the repressed urea cycle were underscored in HCC tissue. Furthermore, multiscale embedded correlation analysis was performed to construct differential correlation networks and reveal pathologically relevant molecule modules. The obtained hub nodes were further screened according to the maximum biochemical diversity and the least intraclass correlation. Finally, a panel of ornithine, FFA 18:1, PC O-32:1 and TG (18:1_17:1_18:2) was generated to achieve the prognostic risk stratification of HCC patients (p < 0.001 by log-rank test). Altogether, our findings suggest that the metabolic dysfunctions of HCC detected via metabolomics and lipidomics would contribute to a better understanding of clinical relevance of hepatic metabolic reprogramming and provide potential sources for the identification of therapeutic targets and the discovery of biomarkers.

Keywords

• metabolomics
• lipidomics
• metabolic reprogramming
• hepatocellular carcinoma
• prognosis