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Identification of potential therapeutic targets for gliomas by bioinformatics analysis
Gliomas are primary tumors that originate in the brain or spinal cord and develop from supportive glial cells. The present study aimed to identify potential candidate molecular markers for the treatment of gliomas, and to explore the underlying mechanisms of this disease. The gene expression profile...
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/PMC5652254/ https://www.ncbi.nlm.nih.gov/pubmed/29113156 http://dx.doi.org/10.3892/ol.2017.6850 |
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author | Ma, Ke Cheng, Zhihua Sun, Liqun Li, Haibo |
author_facet | Ma, Ke Cheng, Zhihua Sun, Liqun Li, Haibo |
author_sort | Ma, Ke |
collection | PubMed |
description | Gliomas are primary tumors that originate in the brain or spinal cord and develop from supportive glial cells. The present study aimed to identify potential candidate molecular markers for the treatment of gliomas, and to explore the underlying mechanisms of this disease. The gene expression profile data GSE50021, which consisted of 10 specimens of normal brain tissues and 35 specimens of glioma tissues, was downloaded from Gene Expression Omnibus (GEO). The methylation microarray data GSE50022, consisting of 28 glioma specimens, was also downloaded from GEO. Differentially expressed genes (DEGs) between patients with glioma and normal individuals were identified, and key methylation sites were screened. Transcriptional regulatory networks were constructed, and target genes were selected. Survival analysis of key methylation sites and risk analysis of sub-pathways were performed, from which key genes and pathways were selected. A total of 79 DEGs and 179 key methylation sites were identified, of which 20 target genes and 36 transcription factors were included in the transcriptional regulatory network. Glutamate metabotropic receptor 2 (GRM2) was regulated by 8 transcription factors. Inositol-trisphosphate 3-kinase A (ITPKA) was a significantly enriched DEG, associated with the inositol phosphate metabolism pathway, Survival analysis revealed that the survival time of patients with lower methylation levels in cg00157228 was longer than patients with higher methylation levels. ITPKA was the closest located gene to cg00157228. In conclusion, GRM2 and enriched ITPKA, associated with the inositol phosphate metabolism pathway, may be key mechanisms in the development and progression of gliomas. Furthermore, the present study provided evidence for an additional mechanism of methylation-induced gliomas, in which methylation results in the dysregulation of specific transcripts. The results of the present study may provide a research direction for studying the mechanisms underlying the development and progression of gliomas. |
format | Online Article Text |
id | pubmed-5652254 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | D.A. Spandidos |
record_format | MEDLINE/PubMed |
spelling | pubmed-56522542017-11-06 Identification of potential therapeutic targets for gliomas by bioinformatics analysis Ma, Ke Cheng, Zhihua Sun, Liqun Li, Haibo Oncol Lett Articles Gliomas are primary tumors that originate in the brain or spinal cord and develop from supportive glial cells. The present study aimed to identify potential candidate molecular markers for the treatment of gliomas, and to explore the underlying mechanisms of this disease. The gene expression profile data GSE50021, which consisted of 10 specimens of normal brain tissues and 35 specimens of glioma tissues, was downloaded from Gene Expression Omnibus (GEO). The methylation microarray data GSE50022, consisting of 28 glioma specimens, was also downloaded from GEO. Differentially expressed genes (DEGs) between patients with glioma and normal individuals were identified, and key methylation sites were screened. Transcriptional regulatory networks were constructed, and target genes were selected. Survival analysis of key methylation sites and risk analysis of sub-pathways were performed, from which key genes and pathways were selected. A total of 79 DEGs and 179 key methylation sites were identified, of which 20 target genes and 36 transcription factors were included in the transcriptional regulatory network. Glutamate metabotropic receptor 2 (GRM2) was regulated by 8 transcription factors. Inositol-trisphosphate 3-kinase A (ITPKA) was a significantly enriched DEG, associated with the inositol phosphate metabolism pathway, Survival analysis revealed that the survival time of patients with lower methylation levels in cg00157228 was longer than patients with higher methylation levels. ITPKA was the closest located gene to cg00157228. In conclusion, GRM2 and enriched ITPKA, associated with the inositol phosphate metabolism pathway, may be key mechanisms in the development and progression of gliomas. Furthermore, the present study provided evidence for an additional mechanism of methylation-induced gliomas, in which methylation results in the dysregulation of specific transcripts. The results of the present study may provide a research direction for studying the mechanisms underlying the development and progression of gliomas. D.A. Spandidos 2017-11 2017-08-28 /pmc/articles/PMC5652254/ /pubmed/29113156 http://dx.doi.org/10.3892/ol.2017.6850 Text en Copyright: © Ma 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 Ma, Ke Cheng, Zhihua Sun, Liqun Li, Haibo Identification of potential therapeutic targets for gliomas by bioinformatics analysis |
title | Identification of potential therapeutic targets for gliomas by bioinformatics analysis |
title_full | Identification of potential therapeutic targets for gliomas by bioinformatics analysis |
title_fullStr | Identification of potential therapeutic targets for gliomas by bioinformatics analysis |
title_full_unstemmed | Identification of potential therapeutic targets for gliomas by bioinformatics analysis |
title_short | Identification of potential therapeutic targets for gliomas by bioinformatics analysis |
title_sort | identification of potential therapeutic targets for gliomas by bioinformatics analysis |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5652254/ https://www.ncbi.nlm.nih.gov/pubmed/29113156 http://dx.doi.org/10.3892/ol.2017.6850 |
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