Identification of Potential Hub Genes Associated with the Pathogenesis and Prognosis of Hepatocellular Carcinoma Via Integrated Bioinformatics Analysis

Overview

Journal J Int Med Res

Publisher Sage Publications

Specialty General Medicine

Date 2020 Jul 30

PMID 32722976

Citations 11

Authors

Ziqi Meng

Jiarui Wu

Xinkui Liu

Wei Zhou

Mengwei Ni

Shuyu Liu

Siyu Guo

Shanshan Jia

Jingyuan Zhang

Affiliations

Soon will be listed here.

Abstract

Objective: The objective was to identify potential hub genes associated with the pathogenesis and prognosis of hepatocellular carcinoma (HCC).

Methods: Gene expression profile datasets were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) between HCC and normal samples were identified via an integrated analysis. A protein-protein interaction network was constructed and analyzed using the STRING database and Cytoscape software, and enrichment analyses were carried out through DAVID. Gene Expression Profiling Interactive Analysis and Kaplan-Meier plotter were used to determine expression and prognostic values of hub genes.

Results: We identified 11 hub genes (, , , , , , , , , , and ) that might be closely related to the pathogenesis and prognosis of HCC. Enrichment analyses indicated that the DEGs were significantly enriched in metabolism-associated pathways, and hub genes and module 1 were highly associated with cell cycle pathway.

Conclusions: In this study, we identified key genes of HCC, which indicated directions for further research into diagnostic and prognostic biomarkers that could facilitate targeted molecular therapy for HCC.

Citing Articles

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Spatial and Single-Cell Transcriptomics Reveals the Regional Division of the Spatial Structure of MASH Fibrosis.

Li J, Yang L, Xiao M, Li N, Huang X, Ye L Liver Int. 2024; 45(4):e16125.

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The role of Aurora kinase A in hepatocellular carcinoma: Unveiling the intriguing functions of a key but still underexplored factor in liver cancer.

Grisetti L, Garcia C, Saponaro A, Tiribelli C, Pascut D Cell Prolif. 2024; 57(8):e13641.

PMID: 38590119 PMC: 11294426. DOI: 10.1111/cpr.13641.

Differentially expressed discriminative genes and significant meta-hub genes based key genes identification for hepatocellular carcinoma using statistical machine learning.

Hasan M, Maniruzzaman M, Shin J Sci Rep. 2023; 13(1):3771.

PMID: 36882493 PMC: 9992474. DOI: 10.1038/s41598-023-30851-1.

Comparative RNA-Sequencing Analysis Reveals High Complexity and Heterogeneity of Transcriptomic and Immune Profiles in Hepatocellular Carcinoma Tumors of Viral (HBV, HCV) and Non-Viral Etiology.

Paslaru L, Bindea G, Nastase A, Sorop A, Zimbru C, Herlea V Medicina (Kaunas). 2022; 58(12).

PMID: 36557005 PMC: 9785216. DOI: 10.3390/medicina58121803.

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