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Screening and identification of key biomarkers in hepatocellular carcinoma: Evidence from bioinformatic analysis

Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide. Intense efforts have been made to elucidate the pathogeny, but the molecular mechanisms of HCC are still not well understood. To identify the candidate genes in the carcinogenesis and progression of HCC, microarray datasets...

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Autores principales: Li, Lin, Lei, Qingsong, Zhang, Shujun, Kong, Lingna, Qin, Bo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: D.A. Spandidos 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5780015/
https://www.ncbi.nlm.nih.gov/pubmed/28901457
http://dx.doi.org/10.3892/or.2017.5946
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author Li, Lin
Lei, Qingsong
Zhang, Shujun
Kong, Lingna
Qin, Bo
author_facet Li, Lin
Lei, Qingsong
Zhang, Shujun
Kong, Lingna
Qin, Bo
author_sort Li, Lin
collection PubMed
description Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide. Intense efforts have been made to elucidate the pathogeny, but the molecular mechanisms of HCC are still not well understood. To identify the candidate genes in the carcinogenesis and progression of HCC, microarray datasets GSE19665, GSE33006 and GSE41804 were downloaded from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified, and function enrichment analyses were performed. The protein-protein interaction network (PPI) was constructed and the module analysis was performed using STRING and Cytoscape. A total of 273 DEGs were identified, consisting of 189 downregulated genes and 84 upregulated genes. The enriched functions and pathways of the DEGs include protein activation cascade, complement activation, carbohydrate binding, complement and coagulation cascades, mitotic cell cycle and oocyte meiosis. Sixteen hub genes were identified and biological process analysis revealed that these genes were mainly enriched in cell division, cell cycle and nuclear division. Survival analysis showed that BUB1, CDC20, KIF20A, RACGAP1 and CEP55 may be involved in the carcinogenesis, invasion or recurrence of HCC. In conclusion, DEGs and hub genes identified in the present study help us understand the molecular mechanisms underlying the carcinogenesis and progression of HCC, and provide candidate targets for diagnosis and treatment of HCC.
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spelling pubmed-57800152018-02-12 Screening and identification of key biomarkers in hepatocellular carcinoma: Evidence from bioinformatic analysis Li, Lin Lei, Qingsong Zhang, Shujun Kong, Lingna Qin, Bo Oncol Rep Articles Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide. Intense efforts have been made to elucidate the pathogeny, but the molecular mechanisms of HCC are still not well understood. To identify the candidate genes in the carcinogenesis and progression of HCC, microarray datasets GSE19665, GSE33006 and GSE41804 were downloaded from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified, and function enrichment analyses were performed. The protein-protein interaction network (PPI) was constructed and the module analysis was performed using STRING and Cytoscape. A total of 273 DEGs were identified, consisting of 189 downregulated genes and 84 upregulated genes. The enriched functions and pathways of the DEGs include protein activation cascade, complement activation, carbohydrate binding, complement and coagulation cascades, mitotic cell cycle and oocyte meiosis. Sixteen hub genes were identified and biological process analysis revealed that these genes were mainly enriched in cell division, cell cycle and nuclear division. Survival analysis showed that BUB1, CDC20, KIF20A, RACGAP1 and CEP55 may be involved in the carcinogenesis, invasion or recurrence of HCC. In conclusion, DEGs and hub genes identified in the present study help us understand the molecular mechanisms underlying the carcinogenesis and progression of HCC, and provide candidate targets for diagnosis and treatment of HCC. D.A. Spandidos 2017-11 2017-09-07 /pmc/articles/PMC5780015/ /pubmed/28901457 http://dx.doi.org/10.3892/or.2017.5946 Text en Copyright: © Li et al. This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
spellingShingle Articles
Li, Lin
Lei, Qingsong
Zhang, Shujun
Kong, Lingna
Qin, Bo
Screening and identification of key biomarkers in hepatocellular carcinoma: Evidence from bioinformatic analysis
title Screening and identification of key biomarkers in hepatocellular carcinoma: Evidence from bioinformatic analysis
title_full Screening and identification of key biomarkers in hepatocellular carcinoma: Evidence from bioinformatic analysis
title_fullStr Screening and identification of key biomarkers in hepatocellular carcinoma: Evidence from bioinformatic analysis
title_full_unstemmed Screening and identification of key biomarkers in hepatocellular carcinoma: Evidence from bioinformatic analysis
title_short Screening and identification of key biomarkers in hepatocellular carcinoma: Evidence from bioinformatic analysis
title_sort screening and identification of key biomarkers in hepatocellular carcinoma: evidence from bioinformatic analysis
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5780015/
https://www.ncbi.nlm.nih.gov/pubmed/28901457
http://dx.doi.org/10.3892/or.2017.5946
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