Identification and Validation of Key Genes in Hepatocellular Carcinoma by Bioinformatics Analysis

Hepatocellular carcinoma (HCC) is the most frequent primary liver cancer and has poor outcomes. However, the potential molecular biological process underpinning the occurrence and development of HCC is still largely unknown. The purpose of this study was to identify the core genes related to HCC and...

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Main Authors: Jia Wang, Rui Peng, Zheng Zhang, Yixi Zhang, Yuke Dai, Yan Sun
Format: Article
Language:English
Published: Hindawi Limited 2021-01-01
Series:BioMed Research International
Online Access:http://dx.doi.org/10.1155/2021/6662114
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spelling doaj-3de4795f14a14a9f892cfd2061bd358b2021-03-08T02:01:45ZengHindawi LimitedBioMed Research International2314-61412021-01-01202110.1155/2021/6662114Identification and Validation of Key Genes in Hepatocellular Carcinoma by Bioinformatics AnalysisJia Wang0Rui Peng1Zheng Zhang2Yixi Zhang3Yuke Dai4Yan Sun5Department of Molecular Medicine and Cancer Research CenterDepartment of BioinformaticsDepartment of Molecular Medicine and Cancer Research CenterDepartment of Molecular Medicine and Cancer Research CenterDepartment of Molecular Medicine and Cancer Research CenterDepartment of Molecular Medicine and Cancer Research CenterHepatocellular carcinoma (HCC) is the most frequent primary liver cancer and has poor outcomes. However, the potential molecular biological process underpinning the occurrence and development of HCC is still largely unknown. The purpose of this study was to identify the core genes related to HCC and explore their potential molecular events using bioinformatics methods. HCC-related expression profiles GSE25097 and GSE84005 were selected from the Gene Expression Omnibus (GEO) database, and the differentially expressed genes (DEGs) between 306 HCC tissues and 281 corresponding noncancerous tissues were identified using GEO2R online tools. The protein-protein interaction network (PPIN) was constructed and visualized using the STRING database. Gene Ontology (GO) and KEGG pathway enrichment analyses of the DEGs were carried out using DAVID 6.8 and KOBAS 3.0. Additionally, module analysis and centrality parameter analysis were performed by Cytoscape. The expression differences of key genes in normal hepatocyte cells and HCC cells were verified by quantitative real-time fluorescence polymerase chain reaction (qRT-PCR). Additionally, survival analysis of key genes was performed by GEPIA. Our results showed that a total of 291 DEGs were identified including 99 upregulated genes and 192 downregulated genes. Our results showed that the PPIN of HCC was made up of 287 nodes and 2527 edges. GO analysis showed that these genes were mainly enriched in the molecular function of protein binding. Additionally, KEGG pathway analysis also revealed that DEGs were mainly involved in the metabolic, cell cycle, and chemical carcinogenesis pathways. Interestingly, a significant module with high centrality features including 10 key genes was found. Among these, CDK1, NDC80, HMMR, CDKN3, and PTTG1, which were only upregulated in HCC patients, have attracted much attention. Furthermore, qRT-PCR also confirmed the upregulation of these five key genes in the normal human hepatocyte cell line (HL-7702) and HCC cell lines (SMMC-7721, MHCC-97L, and MHCC-97H); patients with upregulated expression of these five key genes had significantly poorer survival and prognosis. CDK1, NDC80, HMMR, CDKN3, and PTTG1 can be used as molecular markers for HCC. This finding provides potential strategies for clinical diagnosis, accurate treatment, and prognosis analysis of liver cancer.http://dx.doi.org/10.1155/2021/6662114
collection DOAJ
language English
format Article
sources DOAJ
author Jia Wang
Rui Peng
Zheng Zhang
Yixi Zhang
Yuke Dai
Yan Sun
spellingShingle Jia Wang
Rui Peng
Zheng Zhang
Yixi Zhang
Yuke Dai
Yan Sun
Identification and Validation of Key Genes in Hepatocellular Carcinoma by Bioinformatics Analysis
BioMed Research International
author_facet Jia Wang
Rui Peng
Zheng Zhang
Yixi Zhang
Yuke Dai
Yan Sun
author_sort Jia Wang
title Identification and Validation of Key Genes in Hepatocellular Carcinoma by Bioinformatics Analysis
title_short Identification and Validation of Key Genes in Hepatocellular Carcinoma by Bioinformatics Analysis
title_full Identification and Validation of Key Genes in Hepatocellular Carcinoma by Bioinformatics Analysis
title_fullStr Identification and Validation of Key Genes in Hepatocellular Carcinoma by Bioinformatics Analysis
title_full_unstemmed Identification and Validation of Key Genes in Hepatocellular Carcinoma by Bioinformatics Analysis
title_sort identification and validation of key genes in hepatocellular carcinoma by bioinformatics analysis
publisher Hindawi Limited
series BioMed Research International
issn 2314-6141
publishDate 2021-01-01
description Hepatocellular carcinoma (HCC) is the most frequent primary liver cancer and has poor outcomes. However, the potential molecular biological process underpinning the occurrence and development of HCC is still largely unknown. The purpose of this study was to identify the core genes related to HCC and explore their potential molecular events using bioinformatics methods. HCC-related expression profiles GSE25097 and GSE84005 were selected from the Gene Expression Omnibus (GEO) database, and the differentially expressed genes (DEGs) between 306 HCC tissues and 281 corresponding noncancerous tissues were identified using GEO2R online tools. The protein-protein interaction network (PPIN) was constructed and visualized using the STRING database. Gene Ontology (GO) and KEGG pathway enrichment analyses of the DEGs were carried out using DAVID 6.8 and KOBAS 3.0. Additionally, module analysis and centrality parameter analysis were performed by Cytoscape. The expression differences of key genes in normal hepatocyte cells and HCC cells were verified by quantitative real-time fluorescence polymerase chain reaction (qRT-PCR). Additionally, survival analysis of key genes was performed by GEPIA. Our results showed that a total of 291 DEGs were identified including 99 upregulated genes and 192 downregulated genes. Our results showed that the PPIN of HCC was made up of 287 nodes and 2527 edges. GO analysis showed that these genes were mainly enriched in the molecular function of protein binding. Additionally, KEGG pathway analysis also revealed that DEGs were mainly involved in the metabolic, cell cycle, and chemical carcinogenesis pathways. Interestingly, a significant module with high centrality features including 10 key genes was found. Among these, CDK1, NDC80, HMMR, CDKN3, and PTTG1, which were only upregulated in HCC patients, have attracted much attention. Furthermore, qRT-PCR also confirmed the upregulation of these five key genes in the normal human hepatocyte cell line (HL-7702) and HCC cell lines (SMMC-7721, MHCC-97L, and MHCC-97H); patients with upregulated expression of these five key genes had significantly poorer survival and prognosis. CDK1, NDC80, HMMR, CDKN3, and PTTG1 can be used as molecular markers for HCC. This finding provides potential strategies for clinical diagnosis, accurate treatment, and prognosis analysis of liver cancer.
url http://dx.doi.org/10.1155/2021/6662114
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