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Screening and Identification of Potential Biomarkers in Hepatitis B Virus-Related Hepatocellular Carcinoma by Bioinformatics Analysis
Hepatocellular carcinoma (HCC) is one of the most lethal cancers globally. Hepatitis B virus (HBV) infection might cause chronic hepatitis and cirrhosis, leading to HCC. To screen prognostic genes and therapeutic targets for HCC by bioinformatics analysis and determine the mechanisms underlying HBV-...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2020
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7556301/ https://www.ncbi.nlm.nih.gov/pubmed/33193629 http://dx.doi.org/10.3389/fgene.2020.555537 |
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author | Zeng, Xian-Chang Zhang, Lu Liao, Wen-Jun Ao, Lu Lin, Ze-Man Kang, Wen Chen, Wan-Nan Lin, Xu |
author_facet | Zeng, Xian-Chang Zhang, Lu Liao, Wen-Jun Ao, Lu Lin, Ze-Man Kang, Wen Chen, Wan-Nan Lin, Xu |
author_sort | Zeng, Xian-Chang |
collection | PubMed |
description | Hepatocellular carcinoma (HCC) is one of the most lethal cancers globally. Hepatitis B virus (HBV) infection might cause chronic hepatitis and cirrhosis, leading to HCC. To screen prognostic genes and therapeutic targets for HCC by bioinformatics analysis and determine the mechanisms underlying HBV-related HCC, three high-throughput RNA-seq based raw datasets, namely GSE25599, GSE77509, and GSE94660, were obtained from the Gene Expression Omnibus database, and one RNA-seq raw dataset was acquired from The Cancer Genome Atlas (TCGA). Overall, 103 genes were up-regulated and 127 were down-regulated. A protein–protein interaction (PPI) network was established using Cytoscape software, and 12 pivotal genes were selected as hub genes. The 230 differentially expressed genes and 12 hub genes were subjected to functional and pathway enrichment analyses, and the results suggested that cell cycle, nuclear division, mitotic nuclear division, oocyte meiosis, retinol metabolism, and p53 signaling-related pathways play important roles in HBV-related HCC progression. Further, among the 12 hub genes, kinesin family member 11 (KIF11), TPX2 microtubule nucleation factor (TPX2), kinesin family member 20A (KIF20A), and cyclin B2 (CCNB2) were identified as independent prognostic genes by survival analysis and univariate and multivariate Cox regression analysis. These four genes showed higher expression levels in HCC than in normal tissue samples, as identified upon analyses with Oncomine. In addition, in comparison with normal tissues, the expression levels of KIF11, TPX2, KIF20A, and CCNB2 were higher in HBV-related HCC than in HCV-related HCC tissues. In conclusion, our results suggest that KIF11, TPX2, KIF20A, and CCNB2 might be involved in the carcinogenesis and development of HBV-related HCC. They can thus be used as independent prognostic genes and novel biomarkers for the diagnosis of HBV-related HCC and development of pertinent therapeutic strategies. |
format | Online Article Text |
id | pubmed-7556301 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-75563012020-11-13 Screening and Identification of Potential Biomarkers in Hepatitis B Virus-Related Hepatocellular Carcinoma by Bioinformatics Analysis Zeng, Xian-Chang Zhang, Lu Liao, Wen-Jun Ao, Lu Lin, Ze-Man Kang, Wen Chen, Wan-Nan Lin, Xu Front Genet Genetics Hepatocellular carcinoma (HCC) is one of the most lethal cancers globally. Hepatitis B virus (HBV) infection might cause chronic hepatitis and cirrhosis, leading to HCC. To screen prognostic genes and therapeutic targets for HCC by bioinformatics analysis and determine the mechanisms underlying HBV-related HCC, three high-throughput RNA-seq based raw datasets, namely GSE25599, GSE77509, and GSE94660, were obtained from the Gene Expression Omnibus database, and one RNA-seq raw dataset was acquired from The Cancer Genome Atlas (TCGA). Overall, 103 genes were up-regulated and 127 were down-regulated. A protein–protein interaction (PPI) network was established using Cytoscape software, and 12 pivotal genes were selected as hub genes. The 230 differentially expressed genes and 12 hub genes were subjected to functional and pathway enrichment analyses, and the results suggested that cell cycle, nuclear division, mitotic nuclear division, oocyte meiosis, retinol metabolism, and p53 signaling-related pathways play important roles in HBV-related HCC progression. Further, among the 12 hub genes, kinesin family member 11 (KIF11), TPX2 microtubule nucleation factor (TPX2), kinesin family member 20A (KIF20A), and cyclin B2 (CCNB2) were identified as independent prognostic genes by survival analysis and univariate and multivariate Cox regression analysis. These four genes showed higher expression levels in HCC than in normal tissue samples, as identified upon analyses with Oncomine. In addition, in comparison with normal tissues, the expression levels of KIF11, TPX2, KIF20A, and CCNB2 were higher in HBV-related HCC than in HCV-related HCC tissues. In conclusion, our results suggest that KIF11, TPX2, KIF20A, and CCNB2 might be involved in the carcinogenesis and development of HBV-related HCC. They can thus be used as independent prognostic genes and novel biomarkers for the diagnosis of HBV-related HCC and development of pertinent therapeutic strategies. Frontiers Media S.A. 2020-09-30 /pmc/articles/PMC7556301/ /pubmed/33193629 http://dx.doi.org/10.3389/fgene.2020.555537 Text en Copyright © 2020 Zeng, Zhang, Liao, Ao, Lin, Kang, Chen and Lin. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Zeng, Xian-Chang Zhang, Lu Liao, Wen-Jun Ao, Lu Lin, Ze-Man Kang, Wen Chen, Wan-Nan Lin, Xu Screening and Identification of Potential Biomarkers in Hepatitis B Virus-Related Hepatocellular Carcinoma by Bioinformatics Analysis |
title | Screening and Identification of Potential Biomarkers in Hepatitis B Virus-Related Hepatocellular Carcinoma by Bioinformatics Analysis |
title_full | Screening and Identification of Potential Biomarkers in Hepatitis B Virus-Related Hepatocellular Carcinoma by Bioinformatics Analysis |
title_fullStr | Screening and Identification of Potential Biomarkers in Hepatitis B Virus-Related Hepatocellular Carcinoma by Bioinformatics Analysis |
title_full_unstemmed | Screening and Identification of Potential Biomarkers in Hepatitis B Virus-Related Hepatocellular Carcinoma by Bioinformatics Analysis |
title_short | Screening and Identification of Potential Biomarkers in Hepatitis B Virus-Related Hepatocellular Carcinoma by Bioinformatics Analysis |
title_sort | screening and identification of potential biomarkers in hepatitis b virus-related hepatocellular carcinoma by bioinformatics analysis |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7556301/ https://www.ncbi.nlm.nih.gov/pubmed/33193629 http://dx.doi.org/10.3389/fgene.2020.555537 |
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