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Screening seven hub genes associated with prognosis and immune infiltration in glioblastoma
Glioblastoma (GBM) is the most common and deadly primary brain tumor in adults. Diagnostic and therapeutic challenges have been raised because of poor prognosis. Gene expression profiles of GBM and normal brain tissue samples from GSE68848, GSE16011, GSE7696, and The Cancer Genome Atlas (TCGA) were...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9412194/ https://www.ncbi.nlm.nih.gov/pubmed/36035134 http://dx.doi.org/10.3389/fgene.2022.924802 |
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author | Zhang, Yesen Fan, Huasheng Zou, Chun Wei, Feng Sun, Jiwei Shang, Yuchun Chen, Liechun Wang, Xiangyu Hu, Beiquan |
author_facet | Zhang, Yesen Fan, Huasheng Zou, Chun Wei, Feng Sun, Jiwei Shang, Yuchun Chen, Liechun Wang, Xiangyu Hu, Beiquan |
author_sort | Zhang, Yesen |
collection | PubMed |
description | Glioblastoma (GBM) is the most common and deadly primary brain tumor in adults. Diagnostic and therapeutic challenges have been raised because of poor prognosis. Gene expression profiles of GBM and normal brain tissue samples from GSE68848, GSE16011, GSE7696, and The Cancer Genome Atlas (TCGA) were downloaded. We identified differentially expressed genes (DEGs) by differential expression analysis and obtained 3,800 intersected DEGs from all datasets. Enrichment analysis revealed that the intersected DEGs were involved in the MAPK and cAMP signaling pathways. We identified seven different modules and 2,856 module genes based on the co-expression analysis. Module genes were used to perform Cox and Kaplan-Meier analysis in TCGA to obtain 91 prognosis-related genes. Subsequently, we constructed a random survival forest model and a multivariate Cox model to identify seven hub genes (KDELR2, DLEU1, PTPRN, SRBD1, CRNDE, HPCAL1, and POLR1E). The seven hub genes were subjected to the risk score and survival analyses. Among these, CRNDE may be a key gene in GBM. A network of prognosis-related genes and the top three differentially expressed microRNAs with the largest fold-change was constructed. Moreover, we found a high infiltration of plasmacytoid dendritic cells and T helper 17 cells in GBM. In conclusion, the seven hub genes were speculated to be potential prognostic biomarkers for guiding immunotherapy and may have significant implications for the diagnosis and treatment of GBM. |
format | Online Article Text |
id | pubmed-9412194 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-94121942022-08-27 Screening seven hub genes associated with prognosis and immune infiltration in glioblastoma Zhang, Yesen Fan, Huasheng Zou, Chun Wei, Feng Sun, Jiwei Shang, Yuchun Chen, Liechun Wang, Xiangyu Hu, Beiquan Front Genet Genetics Glioblastoma (GBM) is the most common and deadly primary brain tumor in adults. Diagnostic and therapeutic challenges have been raised because of poor prognosis. Gene expression profiles of GBM and normal brain tissue samples from GSE68848, GSE16011, GSE7696, and The Cancer Genome Atlas (TCGA) were downloaded. We identified differentially expressed genes (DEGs) by differential expression analysis and obtained 3,800 intersected DEGs from all datasets. Enrichment analysis revealed that the intersected DEGs were involved in the MAPK and cAMP signaling pathways. We identified seven different modules and 2,856 module genes based on the co-expression analysis. Module genes were used to perform Cox and Kaplan-Meier analysis in TCGA to obtain 91 prognosis-related genes. Subsequently, we constructed a random survival forest model and a multivariate Cox model to identify seven hub genes (KDELR2, DLEU1, PTPRN, SRBD1, CRNDE, HPCAL1, and POLR1E). The seven hub genes were subjected to the risk score and survival analyses. Among these, CRNDE may be a key gene in GBM. A network of prognosis-related genes and the top three differentially expressed microRNAs with the largest fold-change was constructed. Moreover, we found a high infiltration of plasmacytoid dendritic cells and T helper 17 cells in GBM. In conclusion, the seven hub genes were speculated to be potential prognostic biomarkers for guiding immunotherapy and may have significant implications for the diagnosis and treatment of GBM. Frontiers Media S.A. 2022-08-12 /pmc/articles/PMC9412194/ /pubmed/36035134 http://dx.doi.org/10.3389/fgene.2022.924802 Text en Copyright © 2022 Zhang, Fan, Zou, Wei, Sun, Shang, Chen, Wang and Hu. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Zhang, Yesen Fan, Huasheng Zou, Chun Wei, Feng Sun, Jiwei Shang, Yuchun Chen, Liechun Wang, Xiangyu Hu, Beiquan Screening seven hub genes associated with prognosis and immune infiltration in glioblastoma |
title | Screening seven hub genes associated with prognosis and immune infiltration in glioblastoma |
title_full | Screening seven hub genes associated with prognosis and immune infiltration in glioblastoma |
title_fullStr | Screening seven hub genes associated with prognosis and immune infiltration in glioblastoma |
title_full_unstemmed | Screening seven hub genes associated with prognosis and immune infiltration in glioblastoma |
title_short | Screening seven hub genes associated with prognosis and immune infiltration in glioblastoma |
title_sort | screening seven hub genes associated with prognosis and immune infiltration in glioblastoma |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9412194/ https://www.ncbi.nlm.nih.gov/pubmed/36035134 http://dx.doi.org/10.3389/fgene.2022.924802 |
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