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Integrated analysis of DNA methylation profiles and gene expression profiles to identify genes associated with pilocytic astrocytomas
The present study performed an integral analysis of the gene expression and DNA methylation profile of pilocytic astrocytomas (PAs). Weighted gene co-expression network analysis (WGCNA) was also performed to examine and identify the genes correlated to PAs, to identify candidate therapeutic targets...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
D.A. Spandidos
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4805069/ https://www.ncbi.nlm.nih.gov/pubmed/26934913 http://dx.doi.org/10.3892/mmr.2016.4943 |
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author | ZHOU, RUIGANG MAN, YIGANG |
author_facet | ZHOU, RUIGANG MAN, YIGANG |
author_sort | ZHOU, RUIGANG |
collection | PubMed |
description | The present study performed an integral analysis of the gene expression and DNA methylation profile of pilocytic astrocytomas (PAs). Weighted gene co-expression network analysis (WGCNA) was also performed to examine and identify the genes correlated to PAs, to identify candidate therapeutic targets for the treatment of PAs. The DNA methylation profile and gene expression profile were downloaded from the Gene Expression Omnibus database. Following screening of the differentially expressed genes (DEGs) and differentially methylated regions (DMRs), respectively, integrated analysis of the DEGs and DMRs was performed to detect their correlation. Subsequently, the WGCNA algorithm was applied to identify the significant modules and construct the co-expression network associated with PAs. Furthermore, Gene Ontology enrichment analysis of the associated genes was performed using the Database for Annotation, Visualization and Integrated Discovery. A total number of 2,259 DEGs and 235 DMRs were screened out. Integrated analysis revealed that 30 DEGs were DMRs with prominent negative correlation (cor=−0.82; P=0.02). Based on the DEGs, the gene co-expression network was constructed, and nine network modules associated with PAs were identified. The functional analysis results showed that genes relevant to PAs were closely associated with cell differentiation modulation. The screened PA-associated genes were significantly different at the expression and methylation levels. These genes may be used as reliable candidate target genes for the treatment of PAs. |
format | Online Article Text |
id | pubmed-4805069 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | D.A. Spandidos |
record_format | MEDLINE/PubMed |
spelling | pubmed-48050692016-04-04 Integrated analysis of DNA methylation profiles and gene expression profiles to identify genes associated with pilocytic astrocytomas ZHOU, RUIGANG MAN, YIGANG Mol Med Rep Articles The present study performed an integral analysis of the gene expression and DNA methylation profile of pilocytic astrocytomas (PAs). Weighted gene co-expression network analysis (WGCNA) was also performed to examine and identify the genes correlated to PAs, to identify candidate therapeutic targets for the treatment of PAs. The DNA methylation profile and gene expression profile were downloaded from the Gene Expression Omnibus database. Following screening of the differentially expressed genes (DEGs) and differentially methylated regions (DMRs), respectively, integrated analysis of the DEGs and DMRs was performed to detect their correlation. Subsequently, the WGCNA algorithm was applied to identify the significant modules and construct the co-expression network associated with PAs. Furthermore, Gene Ontology enrichment analysis of the associated genes was performed using the Database for Annotation, Visualization and Integrated Discovery. A total number of 2,259 DEGs and 235 DMRs were screened out. Integrated analysis revealed that 30 DEGs were DMRs with prominent negative correlation (cor=−0.82; P=0.02). Based on the DEGs, the gene co-expression network was constructed, and nine network modules associated with PAs were identified. The functional analysis results showed that genes relevant to PAs were closely associated with cell differentiation modulation. The screened PA-associated genes were significantly different at the expression and methylation levels. These genes may be used as reliable candidate target genes for the treatment of PAs. D.A. Spandidos 2016-04 2016-02-29 /pmc/articles/PMC4805069/ /pubmed/26934913 http://dx.doi.org/10.3892/mmr.2016.4943 Text en Copyright: © Zhou 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 ZHOU, RUIGANG MAN, YIGANG Integrated analysis of DNA methylation profiles and gene expression profiles to identify genes associated with pilocytic astrocytomas |
title | Integrated analysis of DNA methylation profiles and gene expression profiles to identify genes associated with pilocytic astrocytomas |
title_full | Integrated analysis of DNA methylation profiles and gene expression profiles to identify genes associated with pilocytic astrocytomas |
title_fullStr | Integrated analysis of DNA methylation profiles and gene expression profiles to identify genes associated with pilocytic astrocytomas |
title_full_unstemmed | Integrated analysis of DNA methylation profiles and gene expression profiles to identify genes associated with pilocytic astrocytomas |
title_short | Integrated analysis of DNA methylation profiles and gene expression profiles to identify genes associated with pilocytic astrocytomas |
title_sort | integrated analysis of dna methylation profiles and gene expression profiles to identify genes associated with pilocytic astrocytomas |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4805069/ https://www.ncbi.nlm.nih.gov/pubmed/26934913 http://dx.doi.org/10.3892/mmr.2016.4943 |
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