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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...

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Autores principales: Li, Chunguang, Luo, Liangtao, Wei, Sheng, Wang, Xiongbiao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals LLC 2017
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.
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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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