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Comprehensive Analysis of Gene Expression Changes and Validation in Hepatocellular Carcinoma

Authors Zhang H, Liu R, Sun L, Guo W, Ji X, Hu X

Received 27 November 2020

Accepted for publication 3 February 2021

Published 15 February 2021 Volume 2021:14 Pages 1021—1031

DOI https://doi.org/10.2147/OTT.S294500

Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 3

Editor who approved publication: Dr Federico Perche


Hao Zhang,1 Renzheng Liu,1 Lin Sun,2 Weidong Guo,1 Xiaoyue Ji,3 Xiao Hu1

1Department of Hepatobiliary Pancreatic Surgery, The Affiliated Hospital of Qingdao University, Qingdao, Shandong, People’s Republic of China; 2Department of ICU, The Affiliated Hospital of Qingdao University, Qingdao, Shandong, People’s Republic of China; 3Department of Ophthalmology, The Affiliated Hospital of Qingdao University, Qingdao, Shandong, People’s Republic of China

Correspondence: Xiao Hu
Department of Hepatobiliary Pancreatic Surgery, The Affiliated Hospital of Qingdao University, 16 Jiangsu Road, Qingdao, Shandong, People’s Republic of China
Tel +86 18661808808
Email 8371270@qq.com

Aim: This study aimed to analyze the involvement of hub genes in hepatocellular carcinoma.
Methods: Four series were used in this study: GSE45267, GSE84402, and GSE101685 from GPL570 platform in the Gene Expression Omnibus and the other from The Cancer Genome Atlas. The gene audition was completed using R software and Venn diagrams. The outcome, Gene Ontology enrichment, and Kyoto Encyclopedia of Genes and Genomes preliminary analyses of differentially expressed genes were performed using the R software. A string image was obtained using the Search Tool for the Retrieval of Interacting Genes. The protein–protein interaction network was examined using Cytoscape software. The corrplot package was used to analyze the correlation of genes. Human Protein Atlas was used to confirm the protein levels. Univariate Cox regression was used to analyze whether these genes were related to survival. UALCAN was used to confirm the effect of these genes on patient survival.
Results: A total of 107 differentially expressed genes from 491 patients with hepatocellular carcinoma and 119 normal individuals were selected in this study. Cytoscape revealed 25 central nodes from the 107 genes. CCNB1, CDK1, CCNA2, PTTG1, and CDC20 were selected based on the cell cycle pathway. A significant correlation was found among the 6 DEGs. The transcription levels and protein levels of these genes were verified in cells and human tissue samples. The overall survival for these genes was analyzed using univariate Cox regression and UALCAN.
Conclusion: CCNB1, CDK1, CDC20, PTTG1, CCNA2, and TTK were overexpressed and correlated in hepatocellular carcinoma cells and tumors. The results might help explore the prognosis and diagnostic markers of HCC.

Keywords: cell cycle, differentially expressed genes network analysis, hepatocellular carcinoma, oncogene, prognosis analysis

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