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Mining the glioma susceptibility genes in children from gene expression profiles and a methylation database
Glioma is the most common type of primary brain tumor, which is associated with a poor prognosis due to its aggressive growth behavior and highly invasive nature. Research regarding glioma pathogenesis is expected to provide novel methods of adjuvant therapy for the treatment of glioma. The use of b...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
D.A. Spandidos
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5587983/ https://www.ncbi.nlm.nih.gov/pubmed/28927102 http://dx.doi.org/10.3892/ol.2017.6579 |
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author | Xi, Yongqiang Tang, Wanzhong Yang, Song Li, Maolei He, Yuchao Fu, Xianhua |
author_facet | Xi, Yongqiang Tang, Wanzhong Yang, Song Li, Maolei He, Yuchao Fu, Xianhua |
author_sort | Xi, Yongqiang |
collection | PubMed |
description | Glioma is the most common type of primary brain tumor, which is associated with a poor prognosis due to its aggressive growth behavior and highly invasive nature. Research regarding glioma pathogenesis is expected to provide novel methods of adjuvant therapy for the treatment of glioma. The use of bioinformatics to identify candidate genes is commonly used to understand the genetic basis of disease. The present study used bioinformatics to mine the disease-related genes using gene expression profiles (GSE50021) and dual-channel DNA methylation data (GSE50022). The results identified 17 methylation sites located on 33 transcription factor binding sites, which may be responsible for downregulation of 17 target genes. glutamate metabotropic receptor 2 was one of the 17 downregulated target genes. Furthermore, inositol-trisphosphate 3-kinase A (ITPKA) was revealed to be the gene most associated with the risk of glioma in children. The protein coded by the ITPKA gene appeared in all risk sub-pathways, thus suggesting that ITPKA was the gene most associated with the risk of glioma, and inositol phosphate metabolism may be a key pathway associated with glioma in children. The identification of specific genes helps to determine the pathogenesis and possible therapeutic targets for the treatment of glioma in children. |
format | Online Article Text |
id | pubmed-5587983 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | D.A. Spandidos |
record_format | MEDLINE/PubMed |
spelling | pubmed-55879832017-09-18 Mining the glioma susceptibility genes in children from gene expression profiles and a methylation database Xi, Yongqiang Tang, Wanzhong Yang, Song Li, Maolei He, Yuchao Fu, Xianhua Oncol Lett Articles Glioma is the most common type of primary brain tumor, which is associated with a poor prognosis due to its aggressive growth behavior and highly invasive nature. Research regarding glioma pathogenesis is expected to provide novel methods of adjuvant therapy for the treatment of glioma. The use of bioinformatics to identify candidate genes is commonly used to understand the genetic basis of disease. The present study used bioinformatics to mine the disease-related genes using gene expression profiles (GSE50021) and dual-channel DNA methylation data (GSE50022). The results identified 17 methylation sites located on 33 transcription factor binding sites, which may be responsible for downregulation of 17 target genes. glutamate metabotropic receptor 2 was one of the 17 downregulated target genes. Furthermore, inositol-trisphosphate 3-kinase A (ITPKA) was revealed to be the gene most associated with the risk of glioma in children. The protein coded by the ITPKA gene appeared in all risk sub-pathways, thus suggesting that ITPKA was the gene most associated with the risk of glioma, and inositol phosphate metabolism may be a key pathway associated with glioma in children. The identification of specific genes helps to determine the pathogenesis and possible therapeutic targets for the treatment of glioma in children. D.A. Spandidos 2017-09 2017-07-15 /pmc/articles/PMC5587983/ /pubmed/28927102 http://dx.doi.org/10.3892/ol.2017.6579 Text en Copyright: © Xi 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 Xi, Yongqiang Tang, Wanzhong Yang, Song Li, Maolei He, Yuchao Fu, Xianhua Mining the glioma susceptibility genes in children from gene expression profiles and a methylation database |
title | Mining the glioma susceptibility genes in children from gene expression profiles and a methylation database |
title_full | Mining the glioma susceptibility genes in children from gene expression profiles and a methylation database |
title_fullStr | Mining the glioma susceptibility genes in children from gene expression profiles and a methylation database |
title_full_unstemmed | Mining the glioma susceptibility genes in children from gene expression profiles and a methylation database |
title_short | Mining the glioma susceptibility genes in children from gene expression profiles and a methylation database |
title_sort | mining the glioma susceptibility genes in children from gene expression profiles and a methylation database |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5587983/ https://www.ncbi.nlm.nih.gov/pubmed/28927102 http://dx.doi.org/10.3892/ol.2017.6579 |
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