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Identification of key genes and pathways in hepatocellular carcinoma: A preliminary bioinformatics analysis

BACKGROUND: Hepatocellular carcinoma (HCC) is one of the most prevalent cancers worldwide. However, the precise mechanisms of the development and progression of HCC remain unclear. The present study attempted to identify and functionally analyze the differentially expressed genes between HCC and cir...

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Autores principales: Wu, Min, Liu, Zhaobo, Zhang, Aiying, Li, Ning
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer Health 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6380748/
https://www.ncbi.nlm.nih.gov/pubmed/30702595
http://dx.doi.org/10.1097/MD.0000000000014287
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author Wu, Min
Liu, Zhaobo
Zhang, Aiying
Li, Ning
author_facet Wu, Min
Liu, Zhaobo
Zhang, Aiying
Li, Ning
author_sort Wu, Min
collection PubMed
description BACKGROUND: Hepatocellular carcinoma (HCC) is one of the most prevalent cancers worldwide. However, the precise mechanisms of the development and progression of HCC remain unclear. The present study attempted to identify and functionally analyze the differentially expressed genes between HCC and cirrhotic tissues by using comprehensive bioinformatics analyses. METHODS: The GSE63898 gene expression profile was downloaded from the Gene Expression Omnibus (GEO) and analyzed using the online tool GEO2R to identify differentially expressed genes (DEGs). Gene ontology (GO) functional analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the DEGs were performed in DAVID. The STRING database was used to evaluate the interactions of DEGs and to construct a protein-protein interaction (PPI) network using Cytoscape software. Hub genes were selected using the cytoHubba plugin and were validated with the cBioPortal database. RESULTS: A total of 301 DEGs were identified between HCC and cirrhotic tissues. The GO analysis results showed that these DEGs were significantly enriched in certain biological processes including negative regulation of growth and cell chemotaxis. Several significant pathways, including the p53 signaling pathway, were identified as being closely associated with these DEGs. The top 12 hub genes were screened and included TTK, NCAPG, TOP2A, CCNB1, CDK1, PRC1, RRM2, UBE2C, ZWINT, CDKN3, AURKA, and RACGAP1. The cBioPortal analysis found that alterations in hub genes could result in significantly reduced disease-free survival in HCC. CONCLUSION: The present study identified a series of key genes and pathways that may be involved in the tumorigenicity and progression of HCC, providing a new understanding of the underlying molecular mechanisms of carcinogenesis in HCC.
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spelling pubmed-63807482019-03-04 Identification of key genes and pathways in hepatocellular carcinoma: A preliminary bioinformatics analysis Wu, Min Liu, Zhaobo Zhang, Aiying Li, Ning Medicine (Baltimore) Research Article BACKGROUND: Hepatocellular carcinoma (HCC) is one of the most prevalent cancers worldwide. However, the precise mechanisms of the development and progression of HCC remain unclear. The present study attempted to identify and functionally analyze the differentially expressed genes between HCC and cirrhotic tissues by using comprehensive bioinformatics analyses. METHODS: The GSE63898 gene expression profile was downloaded from the Gene Expression Omnibus (GEO) and analyzed using the online tool GEO2R to identify differentially expressed genes (DEGs). Gene ontology (GO) functional analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the DEGs were performed in DAVID. The STRING database was used to evaluate the interactions of DEGs and to construct a protein-protein interaction (PPI) network using Cytoscape software. Hub genes were selected using the cytoHubba plugin and were validated with the cBioPortal database. RESULTS: A total of 301 DEGs were identified between HCC and cirrhotic tissues. The GO analysis results showed that these DEGs were significantly enriched in certain biological processes including negative regulation of growth and cell chemotaxis. Several significant pathways, including the p53 signaling pathway, were identified as being closely associated with these DEGs. The top 12 hub genes were screened and included TTK, NCAPG, TOP2A, CCNB1, CDK1, PRC1, RRM2, UBE2C, ZWINT, CDKN3, AURKA, and RACGAP1. The cBioPortal analysis found that alterations in hub genes could result in significantly reduced disease-free survival in HCC. CONCLUSION: The present study identified a series of key genes and pathways that may be involved in the tumorigenicity and progression of HCC, providing a new understanding of the underlying molecular mechanisms of carcinogenesis in HCC. Wolters Kluwer Health 2019-02-01 /pmc/articles/PMC6380748/ /pubmed/30702595 http://dx.doi.org/10.1097/MD.0000000000014287 Text en Copyright © 2019 the Author(s). Published by Wolters Kluwer Health, Inc. http://creativecommons.org/licenses/by-nc-nd/4.0 This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc-nd/4.0
spellingShingle Research Article
Wu, Min
Liu, Zhaobo
Zhang, Aiying
Li, Ning
Identification of key genes and pathways in hepatocellular carcinoma: A preliminary bioinformatics analysis
title Identification of key genes and pathways in hepatocellular carcinoma: A preliminary bioinformatics analysis
title_full Identification of key genes and pathways in hepatocellular carcinoma: A preliminary bioinformatics analysis
title_fullStr Identification of key genes and pathways in hepatocellular carcinoma: A preliminary bioinformatics analysis
title_full_unstemmed Identification of key genes and pathways in hepatocellular carcinoma: A preliminary bioinformatics analysis
title_short Identification of key genes and pathways in hepatocellular carcinoma: A preliminary bioinformatics analysis
title_sort identification of key genes and pathways in hepatocellular carcinoma: a preliminary bioinformatics analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6380748/
https://www.ncbi.nlm.nih.gov/pubmed/30702595
http://dx.doi.org/10.1097/MD.0000000000014287
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