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Identification of hub genes related to prognosis in glioma
Glioma, a common malignant tumor of the central nervous system, has high invasiveness. The objective of the present study was to identify genes playing an important role in the development of glioma and to reveal their potential research value. Conjoint analysis on the GSE16011 dataset in the Gene E...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Portland Press Ltd.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7253401/ https://www.ncbi.nlm.nih.gov/pubmed/32406502 http://dx.doi.org/10.1042/BSR20193377 |
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author | Zhang, Delong Zhao, Jinxia Han, Chengzheng Liu, Xiaocen Liu, Jun Yang, Hui |
author_facet | Zhang, Delong Zhao, Jinxia Han, Chengzheng Liu, Xiaocen Liu, Jun Yang, Hui |
author_sort | Zhang, Delong |
collection | PubMed |
description | Glioma, a common malignant tumor of the central nervous system, has high invasiveness. The objective of the present study was to identify genes playing an important role in the development of glioma and to reveal their potential research value. Conjoint analysis on the GSE16011 dataset in the Gene Expression Omnibus (GEO) database and the ‘Messenger RNA Expression Microarray of Diffuse Gliomas and Controls’ dataset and ‘RNA sequencing of Diffuse Gliomas’ dataset in the Chinese Glioma Genome Atlas (CGGA) database is carried out in the study. The weighted correlation network analysis (WGCNA) was used to carry out co-expression analysis on the GSE16011. Finally, 24 genes significantly related to grade and prognosis were obtained. In addition, there is no report about CACNG2, JPH3, TUBB6 (tubulin β 6 class V), NRSN1, FAM19A2, NALCN, CDH18, GNAL on glioma. |
format | Online Article Text |
id | pubmed-7253401 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Portland Press Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-72534012020-06-08 Identification of hub genes related to prognosis in glioma Zhang, Delong Zhao, Jinxia Han, Chengzheng Liu, Xiaocen Liu, Jun Yang, Hui Biosci Rep Bioinformatics Glioma, a common malignant tumor of the central nervous system, has high invasiveness. The objective of the present study was to identify genes playing an important role in the development of glioma and to reveal their potential research value. Conjoint analysis on the GSE16011 dataset in the Gene Expression Omnibus (GEO) database and the ‘Messenger RNA Expression Microarray of Diffuse Gliomas and Controls’ dataset and ‘RNA sequencing of Diffuse Gliomas’ dataset in the Chinese Glioma Genome Atlas (CGGA) database is carried out in the study. The weighted correlation network analysis (WGCNA) was used to carry out co-expression analysis on the GSE16011. Finally, 24 genes significantly related to grade and prognosis were obtained. In addition, there is no report about CACNG2, JPH3, TUBB6 (tubulin β 6 class V), NRSN1, FAM19A2, NALCN, CDH18, GNAL on glioma. Portland Press Ltd. 2020-05-27 /pmc/articles/PMC7253401/ /pubmed/32406502 http://dx.doi.org/10.1042/BSR20193377 Text en © 2020 The Author(s). https://creativecommons.org/licenses/by/4.0/ This is an open access article published by Portland Press Limited on behalf of the Biochemical Society and distributed under the Creative Commons Attribution License 4.0 (CC BY). |
spellingShingle | Bioinformatics Zhang, Delong Zhao, Jinxia Han, Chengzheng Liu, Xiaocen Liu, Jun Yang, Hui Identification of hub genes related to prognosis in glioma |
title | Identification of hub genes related to prognosis in glioma |
title_full | Identification of hub genes related to prognosis in glioma |
title_fullStr | Identification of hub genes related to prognosis in glioma |
title_full_unstemmed | Identification of hub genes related to prognosis in glioma |
title_short | Identification of hub genes related to prognosis in glioma |
title_sort | identification of hub genes related to prognosis in glioma |
topic | Bioinformatics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7253401/ https://www.ncbi.nlm.nih.gov/pubmed/32406502 http://dx.doi.org/10.1042/BSR20193377 |
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