Integrative analysis of the characteristic of lipid metabolism-related genes for the prognostic prediction of hepatocellular carcinoma

Abstract

Background Dysregulation of lipid metabolism has been implicated in the progression of hepatocellular carcinoma (HCC). We therefore investigated the molecular characteristics of lipid-metabolism-related genes for the prognostic prediction of HCC. Methods Multi-dimensional bioinformatics analysis was conducted to comprehensively analyzed the lipid metabolism-related genes (IMRG) and construct the prognostic prediction signature. Results A total of 770 HCC patients and their corresponding 776 IMRGs were downloaded from three databases. The HCC patients were classified into 2 molecular clusters, which were associated with overall survival, clinical characteristics, and immune cells. The biological function of the differentially expressed IMRGs in the 2 clusters showed that the genes were associated with tumor-related metabolism pathways. A 6 IMRGs signature (6-IS), including FMO3, SLC11A1, RNF10, KCNH2, ME1, and ZIC2 were established for HCC prognostic prediction, which was found to be an independent prognostic factor. Performance of the 6-IS prognostic signature was verified in a validation set and compared with an external data set. Results revealed that the 6-IS signature could effectively predict the prognosis of patients with HCC. Conclusion This study provides new insights into the role of IMRG in the pathogenesis of HCC and presents a novel signature 6-IS to predict the prognosis of HCC.