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Integrated mRNAseq and microRNAseq data analysis for grade III gliomas
The World Health Organization classification distinguishes four grades for gliomas. Grade III gliomas, which are brain malignant brain tumors with variable biological behavior and propensity, have been not widely investigated. The objective of the present study was to identify specific gene modules...
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/PMC5865882/ https://www.ncbi.nlm.nih.gov/pubmed/28944855 http://dx.doi.org/10.3892/mmr.2017.7545 |
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author | Dai, Junqiang Bing, Zhitong Zhang, Yinian Li, Qiao Niu, Liang Liang, Wentao Yuan, Guoqiang Duan, Lei Yin, Hang Pan, Yawen |
author_facet | Dai, Junqiang Bing, Zhitong Zhang, Yinian Li, Qiao Niu, Liang Liang, Wentao Yuan, Guoqiang Duan, Lei Yin, Hang Pan, Yawen |
author_sort | Dai, Junqiang |
collection | PubMed |
description | The World Health Organization classification distinguishes four grades for gliomas. Grade III gliomas, which are brain malignant brain tumors with variable biological behavior and propensity, have been not widely investigated. The objective of the present study was to identify specific gene modules and valuable hubs associated with gliomagenesis and molecular signatures to assist in determining grade III glioma prognosis. mRNAseq and micro (mi)RNAseq data were used to construct a co-expression network of gliomas using weight gene co-expression network analysis, and revealed the prognostic molecular signature of grade III gliomas. The differently expressed miRNAs and mRNAs were identified. A total of 37 mRNAs and 10 miRNAs were identified, which were closely associated with the survival rates of patients with grade III glioma. To further understand the tumorigenesis, Cytoscape software was used to construct a network containing these differently expressed molecules. The result suggested that both the downregulated genes and upregulated genes are vital in the process of glioma deterioration, and certain genes are closely associated with clinical prognosis. |
format | Online Article Text |
id | pubmed-5865882 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | D.A. Spandidos |
record_format | MEDLINE/PubMed |
spelling | pubmed-58658822018-03-27 Integrated mRNAseq and microRNAseq data analysis for grade III gliomas Dai, Junqiang Bing, Zhitong Zhang, Yinian Li, Qiao Niu, Liang Liang, Wentao Yuan, Guoqiang Duan, Lei Yin, Hang Pan, Yawen Mol Med Rep Articles The World Health Organization classification distinguishes four grades for gliomas. Grade III gliomas, which are brain malignant brain tumors with variable biological behavior and propensity, have been not widely investigated. The objective of the present study was to identify specific gene modules and valuable hubs associated with gliomagenesis and molecular signatures to assist in determining grade III glioma prognosis. mRNAseq and micro (mi)RNAseq data were used to construct a co-expression network of gliomas using weight gene co-expression network analysis, and revealed the prognostic molecular signature of grade III gliomas. The differently expressed miRNAs and mRNAs were identified. A total of 37 mRNAs and 10 miRNAs were identified, which were closely associated with the survival rates of patients with grade III glioma. To further understand the tumorigenesis, Cytoscape software was used to construct a network containing these differently expressed molecules. The result suggested that both the downregulated genes and upregulated genes are vital in the process of glioma deterioration, and certain genes are closely associated with clinical prognosis. D.A. Spandidos 2017-11 2017-09-20 /pmc/articles/PMC5865882/ /pubmed/28944855 http://dx.doi.org/10.3892/mmr.2017.7545 Text en Copyright: © Dai 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 Dai, Junqiang Bing, Zhitong Zhang, Yinian Li, Qiao Niu, Liang Liang, Wentao Yuan, Guoqiang Duan, Lei Yin, Hang Pan, Yawen Integrated mRNAseq and microRNAseq data analysis for grade III gliomas |
title | Integrated mRNAseq and microRNAseq data analysis for grade III gliomas |
title_full | Integrated mRNAseq and microRNAseq data analysis for grade III gliomas |
title_fullStr | Integrated mRNAseq and microRNAseq data analysis for grade III gliomas |
title_full_unstemmed | Integrated mRNAseq and microRNAseq data analysis for grade III gliomas |
title_short | Integrated mRNAseq and microRNAseq data analysis for grade III gliomas |
title_sort | integrated mrnaseq and micrornaseq data analysis for grade iii gliomas |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5865882/ https://www.ncbi.nlm.nih.gov/pubmed/28944855 http://dx.doi.org/10.3892/mmr.2017.7545 |
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