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Bioinformatics identification of crucial genes and pathways associated with hepatocellular carcinoma
Hepatocellular carcinoma (HCC) is a major cause of cancer-related death worldwide. Up to date, HCC pathogenesis has not been fully understood. The aim of the present study was to identify crucial genes and pathways associated with HCC by bioinformatics methods. The differentially expressed genes (DE...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Portland Press Ltd.
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6239270/ https://www.ncbi.nlm.nih.gov/pubmed/30341252 http://dx.doi.org/10.1042/BSR20181441 |
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author | Gao, Xueren Wang, Xixi Zhang, Shulong |
author_facet | Gao, Xueren Wang, Xixi Zhang, Shulong |
author_sort | Gao, Xueren |
collection | PubMed |
description | Hepatocellular carcinoma (HCC) is a major cause of cancer-related death worldwide. Up to date, HCC pathogenesis has not been fully understood. The aim of the present study was to identify crucial genes and pathways associated with HCC by bioinformatics methods. The differentially expressed genes (DEGs) between 14 HCC tissues and corresponding non-cancerous tissues were identified using limma package. Gene Ontology (GO) and KEGG pathway enrichment analysis of DEGs were performed by clusterProfiler package. The protein–protein interaction (PPI) network of DEGs was constructed and visualized by STRING database and Cytoscape software, respectively. The crucial genes in PPI network were identified using a Cytoscape plugin, CytoNCA. Furthermore, the effect of the expression level of the crucial genes on HCC patient survival was analyzed by an interactive web-portal, UALCAN. A total of 870 DEGs including 237 up-regulated and 633 down-regulated genes were identified in HCC tissues. KEGG pathway analysis revealed that DEGs were mainly enriched in complement and coagulation cascades pathway, chemical carcinogenesis pathway, retinol metabolism pathway, fatty acid degradation pathway, and valine, leucine and isoleucine degradation pathway. PPI network analysis showed that CDK1, CCNB1, CCNB2, MAD2L1, ACACB, IGF1, TOP2A, and EHHADH were crucial genes. Survival analysis suggested that the high expression of CDK1, CCNB1, CCNB2, MAD2L1, and TOP2A significantly decreased the survival probability of HCC patients. In conclusion, the identification of the above crucial genes and pathways will not only contribute to elucidating the pathogenesis of HCC, but also provide prognostic markers and therapeutic targets for HCC. |
format | Online Article Text |
id | pubmed-6239270 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Portland Press Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-62392702018-11-28 Bioinformatics identification of crucial genes and pathways associated with hepatocellular carcinoma Gao, Xueren Wang, Xixi Zhang, Shulong Biosci Rep Research Articles Hepatocellular carcinoma (HCC) is a major cause of cancer-related death worldwide. Up to date, HCC pathogenesis has not been fully understood. The aim of the present study was to identify crucial genes and pathways associated with HCC by bioinformatics methods. The differentially expressed genes (DEGs) between 14 HCC tissues and corresponding non-cancerous tissues were identified using limma package. Gene Ontology (GO) and KEGG pathway enrichment analysis of DEGs were performed by clusterProfiler package. The protein–protein interaction (PPI) network of DEGs was constructed and visualized by STRING database and Cytoscape software, respectively. The crucial genes in PPI network were identified using a Cytoscape plugin, CytoNCA. Furthermore, the effect of the expression level of the crucial genes on HCC patient survival was analyzed by an interactive web-portal, UALCAN. A total of 870 DEGs including 237 up-regulated and 633 down-regulated genes were identified in HCC tissues. KEGG pathway analysis revealed that DEGs were mainly enriched in complement and coagulation cascades pathway, chemical carcinogenesis pathway, retinol metabolism pathway, fatty acid degradation pathway, and valine, leucine and isoleucine degradation pathway. PPI network analysis showed that CDK1, CCNB1, CCNB2, MAD2L1, ACACB, IGF1, TOP2A, and EHHADH were crucial genes. Survival analysis suggested that the high expression of CDK1, CCNB1, CCNB2, MAD2L1, and TOP2A significantly decreased the survival probability of HCC patients. In conclusion, the identification of the above crucial genes and pathways will not only contribute to elucidating the pathogenesis of HCC, but also provide prognostic markers and therapeutic targets for HCC. Portland Press Ltd. 2018-11-09 /pmc/articles/PMC6239270/ /pubmed/30341252 http://dx.doi.org/10.1042/BSR20181441 Text en © 2018 The Author(s). http://creativecommons.org/licenses/by/4.0/This is an open access article published by Portland Press Limited on behalf of the Biochemical Society and distributed under the Creative Commons Attribution License 4.0 (CC BY) (http://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Research Articles Gao, Xueren Wang, Xixi Zhang, Shulong Bioinformatics identification of crucial genes and pathways associated with hepatocellular carcinoma |
title | Bioinformatics identification of crucial genes and pathways associated with hepatocellular carcinoma |
title_full | Bioinformatics identification of crucial genes and pathways associated with hepatocellular carcinoma |
title_fullStr | Bioinformatics identification of crucial genes and pathways associated with hepatocellular carcinoma |
title_full_unstemmed | Bioinformatics identification of crucial genes and pathways associated with hepatocellular carcinoma |
title_short | Bioinformatics identification of crucial genes and pathways associated with hepatocellular carcinoma |
title_sort | bioinformatics identification of crucial genes and pathways associated with hepatocellular carcinoma |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6239270/ https://www.ncbi.nlm.nih.gov/pubmed/30341252 http://dx.doi.org/10.1042/BSR20181441 |
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