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Identification of the potential crucial genes in invasive ductal carcinoma using bioinformatics analysis
Invasive ductal carcinoma (IDC) is a common histological type of breast cancer. The aim of this study was to identify the potential crucial genes associated with IDC and to provide valid biological information for further investigations. The gene expression profiles of GSE10780 which contained 42 hi...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Impact Journals LLC
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5805516/ https://www.ncbi.nlm.nih.gov/pubmed/29467930 http://dx.doi.org/10.18632/oncotarget.23239 |
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author | Li, Chunguang Luo, Liangtao Wei, Sheng Wang, Xiongbiao |
author_facet | Li, Chunguang Luo, Liangtao Wei, Sheng Wang, Xiongbiao |
author_sort | Li, Chunguang |
collection | PubMed |
description | Invasive ductal carcinoma (IDC) is a common histological type of breast cancer. The aim of this study was to identify the potential crucial genes associated with IDC and to provide valid biological information for further investigations. The gene expression profiles of GSE10780 which contained 42 histologically normal breast tissues and 143 IDC tissues were downloaded from the GEO database. Functional and pathway enrichment analysis of differentially expressed genes (DEGs) were performed and protein-protein interaction (PPI) network was analyzed using Cytoscape. In total, 999 DEGs were identified, including 667 up-regulated and 332 down-regulated DEGs. Gene ontology analysis demonstrated that most DEGs were significantly enriched in mitotic cell cycle, adhesion and protein binding process. Through PPI network analysis, a significant module was screened out, and the top 10 hub genes, CDK1, CCNB1, CENPE, CENPA, PLK1, CDC20, MAD2L1, HIST1H2BK, KIF2C and CCNA2 were identified from the PPI network. The expression levels of the 10 genes were validated in Oncomine database. KIF2C, MAD2L1 and PLK1 were associated with the overall survival. And we used cBioPortal to explore the genetic alterations of hub genes and potential drugs. In conclusion, the present study identified DEGs between normal and IDC samples, which could improve our understanding of the molecular mechanisms in the development of IDC, and these candidate genes might be used as therapeutic targets for IDC. |
format | Online Article Text |
id | pubmed-5805516 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Impact Journals LLC |
record_format | MEDLINE/PubMed |
spelling | pubmed-58055162018-02-21 Identification of the potential crucial genes in invasive ductal carcinoma using bioinformatics analysis Li, Chunguang Luo, Liangtao Wei, Sheng Wang, Xiongbiao Oncotarget Research Paper Invasive ductal carcinoma (IDC) is a common histological type of breast cancer. The aim of this study was to identify the potential crucial genes associated with IDC and to provide valid biological information for further investigations. The gene expression profiles of GSE10780 which contained 42 histologically normal breast tissues and 143 IDC tissues were downloaded from the GEO database. Functional and pathway enrichment analysis of differentially expressed genes (DEGs) were performed and protein-protein interaction (PPI) network was analyzed using Cytoscape. In total, 999 DEGs were identified, including 667 up-regulated and 332 down-regulated DEGs. Gene ontology analysis demonstrated that most DEGs were significantly enriched in mitotic cell cycle, adhesion and protein binding process. Through PPI network analysis, a significant module was screened out, and the top 10 hub genes, CDK1, CCNB1, CENPE, CENPA, PLK1, CDC20, MAD2L1, HIST1H2BK, KIF2C and CCNA2 were identified from the PPI network. The expression levels of the 10 genes were validated in Oncomine database. KIF2C, MAD2L1 and PLK1 were associated with the overall survival. And we used cBioPortal to explore the genetic alterations of hub genes and potential drugs. In conclusion, the present study identified DEGs between normal and IDC samples, which could improve our understanding of the molecular mechanisms in the development of IDC, and these candidate genes might be used as therapeutic targets for IDC. Impact Journals LLC 2017-12-13 /pmc/articles/PMC5805516/ /pubmed/29467930 http://dx.doi.org/10.18632/oncotarget.23239 Text en Copyright: © 2018 Li et al. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License 3.0 (http://creativecommons.org/licenses/by/3.0/) (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Paper Li, Chunguang Luo, Liangtao Wei, Sheng Wang, Xiongbiao Identification of the potential crucial genes in invasive ductal carcinoma using bioinformatics analysis |
title | Identification of the potential crucial genes in invasive ductal carcinoma using bioinformatics analysis |
title_full | Identification of the potential crucial genes in invasive ductal carcinoma using bioinformatics analysis |
title_fullStr | Identification of the potential crucial genes in invasive ductal carcinoma using bioinformatics analysis |
title_full_unstemmed | Identification of the potential crucial genes in invasive ductal carcinoma using bioinformatics analysis |
title_short | Identification of the potential crucial genes in invasive ductal carcinoma using bioinformatics analysis |
title_sort | identification of the potential crucial genes in invasive ductal carcinoma using bioinformatics analysis |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5805516/ https://www.ncbi.nlm.nih.gov/pubmed/29467930 http://dx.doi.org/10.18632/oncotarget.23239 |
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