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Identification of key candidate genes and pathways in hepatocellular carcinoma by integrated bioinformatical analysis
Hepatocellular carcinoma (HCC) is one of the most common malignant neoplasms worldwide, however the underlying mechanisms and gene signatures of HCC are unknown. In the present study the profile datasets of four cohorts were integrated to elucidate the pathways and candidate genes of HCC. The expres...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
D.A. Spandidos
2018
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5958738/ https://www.ncbi.nlm.nih.gov/pubmed/29805517 http://dx.doi.org/10.3892/etm.2018.6075 |
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author | Xing, Tonghai Yan, Tingmang Zhou, Qiang |
author_facet | Xing, Tonghai Yan, Tingmang Zhou, Qiang |
author_sort | Xing, Tonghai |
collection | PubMed |
description | Hepatocellular carcinoma (HCC) is one of the most common malignant neoplasms worldwide, however the underlying mechanisms and gene signatures of HCC are unknown. In the present study the profile datasets of four cohorts were integrated to elucidate the pathways and candidate genes of HCC. The expression profiles GSE25097, GSE45267, GSE57957 and GSE62232 were downloaded from the Gene Expression Omnibus database, including 436 HCC and 94 normal liver tissues. A total of 185 differentially expressed genes (DEGs) were identified in HCC, including 92 upregulated genes and 92 downregulated genes. Gene ontology (GO) was performed, which revealed that the upregulated DEGs were primarily enriched in cell division, mitotic nuclear division, mitotic cytokinesis and G1/S transition of the mitotic cell cycle. Pathway enrichment was analyzed based on the Kyoto Encyclopedia of Genes and Genomes database to assess the functional relevance of DEGs. The most significant module was selected from protein-protein interactions and 15 important hub genes were identified. The sub-networks of hub genes were involved in cell division, p53 signaling, and T lymphotropic virus type I infection signaling pathways. In conclusion, the present study revealed that the identified DEG candidate genes may promote the understanding of the cause and molecular mechanisms underlying the development of HCC and that these candidates and signal pathways may be potential targets of clinical therapy for HCC. |
format | Online Article Text |
id | pubmed-5958738 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | D.A. Spandidos |
record_format | MEDLINE/PubMed |
spelling | pubmed-59587382018-05-27 Identification of key candidate genes and pathways in hepatocellular carcinoma by integrated bioinformatical analysis Xing, Tonghai Yan, Tingmang Zhou, Qiang Exp Ther Med Articles Hepatocellular carcinoma (HCC) is one of the most common malignant neoplasms worldwide, however the underlying mechanisms and gene signatures of HCC are unknown. In the present study the profile datasets of four cohorts were integrated to elucidate the pathways and candidate genes of HCC. The expression profiles GSE25097, GSE45267, GSE57957 and GSE62232 were downloaded from the Gene Expression Omnibus database, including 436 HCC and 94 normal liver tissues. A total of 185 differentially expressed genes (DEGs) were identified in HCC, including 92 upregulated genes and 92 downregulated genes. Gene ontology (GO) was performed, which revealed that the upregulated DEGs were primarily enriched in cell division, mitotic nuclear division, mitotic cytokinesis and G1/S transition of the mitotic cell cycle. Pathway enrichment was analyzed based on the Kyoto Encyclopedia of Genes and Genomes database to assess the functional relevance of DEGs. The most significant module was selected from protein-protein interactions and 15 important hub genes were identified. The sub-networks of hub genes were involved in cell division, p53 signaling, and T lymphotropic virus type I infection signaling pathways. In conclusion, the present study revealed that the identified DEG candidate genes may promote the understanding of the cause and molecular mechanisms underlying the development of HCC and that these candidates and signal pathways may be potential targets of clinical therapy for HCC. D.A. Spandidos 2018-06 2018-04-16 /pmc/articles/PMC5958738/ /pubmed/29805517 http://dx.doi.org/10.3892/etm.2018.6075 Text en Copyright: © Xing 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 Xing, Tonghai Yan, Tingmang Zhou, Qiang Identification of key candidate genes and pathways in hepatocellular carcinoma by integrated bioinformatical analysis |
title | Identification of key candidate genes and pathways in hepatocellular carcinoma by integrated bioinformatical analysis |
title_full | Identification of key candidate genes and pathways in hepatocellular carcinoma by integrated bioinformatical analysis |
title_fullStr | Identification of key candidate genes and pathways in hepatocellular carcinoma by integrated bioinformatical analysis |
title_full_unstemmed | Identification of key candidate genes and pathways in hepatocellular carcinoma by integrated bioinformatical analysis |
title_short | Identification of key candidate genes and pathways in hepatocellular carcinoma by integrated bioinformatical analysis |
title_sort | identification of key candidate genes and pathways in hepatocellular carcinoma by integrated bioinformatical analysis |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5958738/ https://www.ncbi.nlm.nih.gov/pubmed/29805517 http://dx.doi.org/10.3892/etm.2018.6075 |
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