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Gene Expression Profiling of Glioblastoma to Recognize Potential Biomarker Candidates
Glioblastoma is an aggressive malignant tumor of the brain and spinal cord. Due to the blood–brain barrier, the accessibility of its treatments still remains significantly challenging. Unfortunately, the recurrence rates of glioblastoma upon surgery are very high too. Hence, understanding the molecu...
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/PMC9091202/ https://www.ncbi.nlm.nih.gov/pubmed/35571016 http://dx.doi.org/10.3389/fgene.2022.832742 |
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author | Li, Qiang Aishwarya, S. Li, Ji-Ping Pan, Dong-Xiao Shi, Jia-Pei |
author_facet | Li, Qiang Aishwarya, S. Li, Ji-Ping Pan, Dong-Xiao Shi, Jia-Pei |
author_sort | Li, Qiang |
collection | PubMed |
description | Glioblastoma is an aggressive malignant tumor of the brain and spinal cord. Due to the blood–brain barrier, the accessibility of its treatments still remains significantly challenging. Unfortunately, the recurrence rates of glioblastoma upon surgery are very high too. Hence, understanding the molecular drivers of disease progression is valuable. In this study, we aimed to investigate the molecular drivers responsible for glioblastoma progression and identify valid biomarkers. Three microarray expression profiles GSE90604, GSE50601, and GSE134470 containing healthy and glioblastoma-affected samples revealed overlapping differentially expressed genes (DEGs). The interrelational pathway enrichment analysis elucidated the halt of cell cycle checkpoints and activation of signaling pathways and led to the identification of 6 predominant hub genes. Validation of hub genes in comparison with The Cancer Genome Atlas datasets identified the potential biomarkers of glioblastoma. The study evaluated two significantly upregulated genes, SPARC (secreted protein acidic and rich in cysteine) and VIM (vimentin) for glioblastoma. The genes CACNA1E (calcium voltage-gated channel subunit alpha1 e), SH3GL2 (SH3 domain-containing GRB2-like 2, endophilin A1), and DDN (dendrin) were identified as under-expressed genes as compared to the normal and pan-cancer tissues along with prominent putative prognostic biomarker potentials. The genes DDN and SH3GL2 were found to be upregulated in the proneural subtype, while CACNA1E in the mesenchymal subtype of glioblastoma exhibits good prognostic potential. The mutational analysis also revealed the benign, possibly, and probably damaging substitution mutations. The correlation between the DEG and survival in glioblastoma was evaluated using the Kaplan–Meier plots, and VIM had a greater life expectancy of 60.25 months. Overall, this study identified key candidate genes that might serve as predictive biomarkers for glioblastoma. |
format | Online Article Text |
id | pubmed-9091202 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-90912022022-05-12 Gene Expression Profiling of Glioblastoma to Recognize Potential Biomarker Candidates Li, Qiang Aishwarya, S. Li, Ji-Ping Pan, Dong-Xiao Shi, Jia-Pei Front Genet Genetics Glioblastoma is an aggressive malignant tumor of the brain and spinal cord. Due to the blood–brain barrier, the accessibility of its treatments still remains significantly challenging. Unfortunately, the recurrence rates of glioblastoma upon surgery are very high too. Hence, understanding the molecular drivers of disease progression is valuable. In this study, we aimed to investigate the molecular drivers responsible for glioblastoma progression and identify valid biomarkers. Three microarray expression profiles GSE90604, GSE50601, and GSE134470 containing healthy and glioblastoma-affected samples revealed overlapping differentially expressed genes (DEGs). The interrelational pathway enrichment analysis elucidated the halt of cell cycle checkpoints and activation of signaling pathways and led to the identification of 6 predominant hub genes. Validation of hub genes in comparison with The Cancer Genome Atlas datasets identified the potential biomarkers of glioblastoma. The study evaluated two significantly upregulated genes, SPARC (secreted protein acidic and rich in cysteine) and VIM (vimentin) for glioblastoma. The genes CACNA1E (calcium voltage-gated channel subunit alpha1 e), SH3GL2 (SH3 domain-containing GRB2-like 2, endophilin A1), and DDN (dendrin) were identified as under-expressed genes as compared to the normal and pan-cancer tissues along with prominent putative prognostic biomarker potentials. The genes DDN and SH3GL2 were found to be upregulated in the proneural subtype, while CACNA1E in the mesenchymal subtype of glioblastoma exhibits good prognostic potential. The mutational analysis also revealed the benign, possibly, and probably damaging substitution mutations. The correlation between the DEG and survival in glioblastoma was evaluated using the Kaplan–Meier plots, and VIM had a greater life expectancy of 60.25 months. Overall, this study identified key candidate genes that might serve as predictive biomarkers for glioblastoma. Frontiers Media S.A. 2022-04-27 /pmc/articles/PMC9091202/ /pubmed/35571016 http://dx.doi.org/10.3389/fgene.2022.832742 Text en Copyright © 2022 Li, Aishwarya, Li, Pan and Shi. 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 Li, Qiang Aishwarya, S. Li, Ji-Ping Pan, Dong-Xiao Shi, Jia-Pei Gene Expression Profiling of Glioblastoma to Recognize Potential Biomarker Candidates |
title | Gene Expression Profiling of Glioblastoma to Recognize Potential Biomarker Candidates |
title_full | Gene Expression Profiling of Glioblastoma to Recognize Potential Biomarker Candidates |
title_fullStr | Gene Expression Profiling of Glioblastoma to Recognize Potential Biomarker Candidates |
title_full_unstemmed | Gene Expression Profiling of Glioblastoma to Recognize Potential Biomarker Candidates |
title_short | Gene Expression Profiling of Glioblastoma to Recognize Potential Biomarker Candidates |
title_sort | gene expression profiling of glioblastoma to recognize potential biomarker candidates |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9091202/ https://www.ncbi.nlm.nih.gov/pubmed/35571016 http://dx.doi.org/10.3389/fgene.2022.832742 |
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