• Medicine · Jan 2022

    Bioinformatics analysis and experimental verification of five metabolism-related lncRNAs as prognostic models for hepatocellular carcinoma.

    • Wei Wang, Zhenfeng Deng, Zongrui Jin, Guolin Wu, Jilong Wang, Hai Zhu, Banghao Xu, Zhang Wen, and Ya Guo.
    • Department of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.
    • Medicine (Baltimore). 2022 Jan 28; 101 (4): e28694e28694.

    BackgroundThe number of patients with hepatocellular carcinoma (HCC) is showing a growing trend all over the world. The metabolic microenvironment has been shown to play a key role in the pathogenesis of HCC in recent studies. The expression of metabolites and metabolic processes in tumor cells can be regulated by gene regulation mediated by long non-coding RNAs (lncRNAs), the abnormal expression of which is closely related to tumor occurrence and metastasis. However, the fundamental mechanism of applying metabolism-related lncRNAs to predicting HCC is still unclear.MethodsWith the complete RNA sequence data and clinical data obtained from The Cancer Genome Atlas database and metabolism-related genes downloaded from the Kyoto Encyclopedia of Genes and Genomes database, with false discovery rate < 0.001, log fold change > 1.5 selected as the screening criteria for lncRNA, the relationship between the expression level of metabolism-related LncRNAs (MRLs) and the overall survival rate was determined by the Univariate Cox regression analyses with the establishment of the metabolic prognosis model by the application of Multivariate Cox regression analyses, revealing the different biological processes and signaling pathways in both high-risk groups and low-risk groups by Gene Ontology, Kyoto Encyclopedia of Genes and Genomes enrichment analysis, and gene set enrichment analysis, leading the expression of lncRNA to be assessed by the reverse transcription-polymerase chain reaction results.ResultsThe overall survival rate of HCC patients is significantly correlated with signature of 5-MRLs. The prognosis characteristics of lncRNA reveal the relatively high death rate of patients in the high-risk groups, with the predicted signals by functional and pathway enrichment analysis related to biosynthesis, metabolic process, and metabolic pathway, with the prognostic characteristics of 5-MRLs by the combined analysis showing that it is an independent factor of HCC superior to the traditional clinical indicators in predicting the prognosis. A trend of high-expression was shown in MRLs in tumors by reverse transcription-polymerase chain reaction.ConclusionThe new 5-MRLs as potential biomarkers provide more powerful prognostic information for HCC patients. In the future clinical treatment of HCC, it will provide doctors with more methods.Copyright © 2022 the Author(s). Published by Wolters Kluwer Health, Inc.

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