Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Li, Qiang, Aishwarya, S., Li, Ji-Ping, Pan, Dong-Xiao, Shi, Jia-Pei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
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
_version_ 1784704869298339840
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
work_keys_str_mv AT liqiang geneexpressionprofilingofglioblastomatorecognizepotentialbiomarkercandidates
AT aishwaryas geneexpressionprofilingofglioblastomatorecognizepotentialbiomarkercandidates
AT lijiping geneexpressionprofilingofglioblastomatorecognizepotentialbiomarkercandidates
AT pandongxiao geneexpressionprofilingofglioblastomatorecognizepotentialbiomarkercandidates
AT shijiapei geneexpressionprofilingofglioblastomatorecognizepotentialbiomarkercandidates