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Identification of key differentially expressed genes associated with non-small cell lung cancer by bioinformatics analyses
Increasing evidence has indicated that the abnormal expressions of certain genes serve important roles in tumorigenesis, progression and metastasis. The aim of the present study was to explore the key differentially expressed genes (DEGs) between non-small cell lung cancer (NSCLC) and matched normal...
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/PMC5928621/ https://www.ncbi.nlm.nih.gov/pubmed/29532892 http://dx.doi.org/10.3892/mmr.2018.8726 |
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author | Xiao, Yubo Feng, Min Ran, Haiying Han, Xiao Li, Xuegang |
author_facet | Xiao, Yubo Feng, Min Ran, Haiying Han, Xiao Li, Xuegang |
author_sort | Xiao, Yubo |
collection | PubMed |
description | Increasing evidence has indicated that the abnormal expressions of certain genes serve important roles in tumorigenesis, progression and metastasis. The aim of the present study was to explore the key differentially expressed genes (DEGs) between non-small cell lung cancer (NSCLC) and matched normal lung tissues by analyzing 4 different mRNA microarray datasets downloaded from the Gene Expression Omnibus (GEO) database. In improving the reliability of the bioinformatics analysis, the DEGs in each dataset that met the cut-off criteria (adjust P-value <0.05 and |log(2)fold-change (FC)|>1) were intersected with each other, from which 195 were identified (consisting of 57 upregulated and 138 downregulated DEGs). The GO analysis results revealed that the upregulated DEGs were significantly enriched in various biological processes (BP), including cell cycle, mitosis and cell proliferation while the downregulated DEGs were significantly enriched in angiogenesis and response to drug and cell adhesion. The hub genes, including CCNB1, CCNA2, CEP55, PBK and HMMR, were identified based on the protein-protein interaction (PPI) network. The Kaplan-Meier survival analysis indicated that the high expression level of each of these hub genes correlates with poorer overall survival in all patients with NSCLC, which indicates that they may serve important roles in the progression of NSCLC. In conclusion, the DEGs and hub genes identified in the present study may contribute to the comprehensive understanding of the molecular mechanisms of NSCLC and may be used as diagnostic and prognostic biomarkers as well as molecular targets for the treatment of NSCLC. |
format | Online Article Text |
id | pubmed-5928621 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | D.A. Spandidos |
record_format | MEDLINE/PubMed |
spelling | pubmed-59286212018-05-07 Identification of key differentially expressed genes associated with non-small cell lung cancer by bioinformatics analyses Xiao, Yubo Feng, Min Ran, Haiying Han, Xiao Li, Xuegang Mol Med Rep Articles Increasing evidence has indicated that the abnormal expressions of certain genes serve important roles in tumorigenesis, progression and metastasis. The aim of the present study was to explore the key differentially expressed genes (DEGs) between non-small cell lung cancer (NSCLC) and matched normal lung tissues by analyzing 4 different mRNA microarray datasets downloaded from the Gene Expression Omnibus (GEO) database. In improving the reliability of the bioinformatics analysis, the DEGs in each dataset that met the cut-off criteria (adjust P-value <0.05 and |log(2)fold-change (FC)|>1) were intersected with each other, from which 195 were identified (consisting of 57 upregulated and 138 downregulated DEGs). The GO analysis results revealed that the upregulated DEGs were significantly enriched in various biological processes (BP), including cell cycle, mitosis and cell proliferation while the downregulated DEGs were significantly enriched in angiogenesis and response to drug and cell adhesion. The hub genes, including CCNB1, CCNA2, CEP55, PBK and HMMR, were identified based on the protein-protein interaction (PPI) network. The Kaplan-Meier survival analysis indicated that the high expression level of each of these hub genes correlates with poorer overall survival in all patients with NSCLC, which indicates that they may serve important roles in the progression of NSCLC. In conclusion, the DEGs and hub genes identified in the present study may contribute to the comprehensive understanding of the molecular mechanisms of NSCLC and may be used as diagnostic and prognostic biomarkers as well as molecular targets for the treatment of NSCLC. D.A. Spandidos 2018-05 2018-03-09 /pmc/articles/PMC5928621/ /pubmed/29532892 http://dx.doi.org/10.3892/mmr.2018.8726 Text en Copyright: © Xiao 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 Xiao, Yubo Feng, Min Ran, Haiying Han, Xiao Li, Xuegang Identification of key differentially expressed genes associated with non-small cell lung cancer by bioinformatics analyses |
title | Identification of key differentially expressed genes associated with non-small cell lung cancer by bioinformatics analyses |
title_full | Identification of key differentially expressed genes associated with non-small cell lung cancer by bioinformatics analyses |
title_fullStr | Identification of key differentially expressed genes associated with non-small cell lung cancer by bioinformatics analyses |
title_full_unstemmed | Identification of key differentially expressed genes associated with non-small cell lung cancer by bioinformatics analyses |
title_short | Identification of key differentially expressed genes associated with non-small cell lung cancer by bioinformatics analyses |
title_sort | identification of key differentially expressed genes associated with non-small cell lung cancer by bioinformatics analyses |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5928621/ https://www.ncbi.nlm.nih.gov/pubmed/29532892 http://dx.doi.org/10.3892/mmr.2018.8726 |
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