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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...

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Autores principales: Xi, Yongqiang, Tang, Wanzhong, Yang, Song, Li, Maolei, He, Yuchao, Fu, Xianhua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: D.A. Spandidos 2017
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.
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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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