Screening the Significant Hub Genes by Comparing Tumor Cells, Normoxic and Hypoxic Glioblastoma Stem-like Cell Lines Using Co-Expression Analysis in Glioblastoma.
VEGF signaling pathway
biomarker
co-expression
differentially expressed genes
gene ontology pathway enrichment
glioblastoma multiforme
Journal
Genes
ISSN: 2073-4425
Titre abrégé: Genes (Basel)
Pays: Switzerland
ID NLM: 101551097
Informations de publication
Date de publication:
15 03 2022
15 03 2022
Historique:
received:
11
02
2022
revised:
11
03
2022
accepted:
12
03
2022
entrez:
25
3
2022
pubmed:
26
3
2022
medline:
26
4
2022
Statut:
epublish
Résumé
Glioblastoma multiforme (GBM) is categorized by rapid malignant cellular growth in the central nervous system (CNS) tumors. It is one of the most prevailing primary brain tumors, particularly in human male adults. Even though the combination therapy comprises surgery, chemotherapy, and adjuvant therapies, the survival rate is on average 14.6 months. Glioma stem cells (GSCs) have key roles in tumorigenesis, progression, and counteracting chemotherapy and radiotherapy. In our study, firstly, the gene expression dataset GSE45117 was retrieved and differentially expressed genes (DEGs) were spotted. The co-expression network analysis was employed on DEGs to find the significant modules. The most significant module resulting from co-expression analysis was the turquoise module. The turquoise module related to the tumor cells, hypoxia, normoxic treatments of glioblastoma tumor (GBT), and GSCs were screened. Sixty-one common genes in the turquoise module were selected generated through the co-expression analysis and protein-protein interaction (PPI) network. Moreover, the GO and KEGG pathway enrichment results were studied. Twenty common hub genes were screened by the NetworkAnalyst web instrument constructed on the PPI network through the STRING database. After survival analysis via the Kaplan-Meier (KM) plotter from The Cancer Genome Atlas (TCGA) database, we identified the five most significant hub genes strongly related to the progression of GBM. We further observed these five most significant hub genes also up-regulated in another GBM gene expression dataset. The protein-protein interaction (PPI) network of the turquoise module genes was constructed and a KEGG pathway enrichments study of the turquoise module genes was performed. The VEGF signaling pathway was emphasized because of the strong link with GBM. A gene-disease association network was further constructed to demonstrate the information of the progression of GBM and other related brain neoplasms. All hub genes assessed through this study would be potential markers for the prognosis and diagnosis of GBM.
Identifiants
pubmed: 35328072
pii: genes13030518
doi: 10.3390/genes13030518
pmc: PMC8951270
pii:
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Références
BMC Mol Biol. 2009 Mar 03;10:17
pubmed: 19257903
Brain. 2019 Dec 1;142(12):3834-3851
pubmed: 31665239
Int J Clin Exp Pathol. 2015 Jul 01;8(7):7825-37
pubmed: 26339347
Nucleic Acids Res. 2002 Jan 1;30(1):207-10
pubmed: 11752295
Nat Protoc. 2009;4(1):44-57
pubmed: 19131956
Expert Opin Biol Ther. 2008 Apr;8(4):541-53
pubmed: 18352856
Int J Mol Sci. 2022 Feb 04;23(3):
pubmed: 35163706
Nucleic Acids Res. 2014 Jul;42(Web Server issue):W167-74
pubmed: 24861621
Carcinogenesis. 2009 Jan;30(1):20-7
pubmed: 18842679
Cell Tissue Res. 2002 Dec;310(3):257-70
pubmed: 12457224
Bioinformatics. 2005 Aug 15;21(16):3439-40
pubmed: 16082012
Pharmacol Rev. 2018 Jul;70(3):412-445
pubmed: 29669750
Nucleic Acids Res. 2015 Jan;43(Database issue):D447-52
pubmed: 25352553
Cell Death Dis. 2014 Dec 11;5:e1567
pubmed: 25501828
Acta Neuropathol. 2013 Nov;126(5):763-80
pubmed: 24005892
Biochim Biophys Acta. 2015 Jan;1853(1):126-35
pubmed: 25409926
Cancer Res. 2019 Nov 15;79(22):5785-5798
pubmed: 31530567
Philos Trans R Soc Lond B Biol Sci. 2008 Jan 12;363(1489):139-52
pubmed: 17309866
Lab Invest. 2020 Apr;100(4):619-629
pubmed: 31748682
Nature. 2017 Sep 14;549(7671):227-232
pubmed: 28854171
Nucleic Acids Res. 2007 Jul;35(Web Server issue):W169-75
pubmed: 17576678
Int J Mol Sci. 2018 Nov 21;19(11):
pubmed: 30469355
Nucleic Acids Res. 2019 Jul 2;47(W1):W556-W560
pubmed: 31114875
Front Genet. 2016 May 09;7:80
pubmed: 27242890
Br J Pharmacol. 2013 Feb;168(3):591-606
pubmed: 23062197
Neoplasia. 2017 Aug;19(8):649-658
pubmed: 28732212
Cancer Inform. 2008;6:275-92
pubmed: 19259414
Genome Biol. 2018 Mar 16;19(1):35
pubmed: 29548303
Brain Pathol. 2009 Jan;19(1):81-90
pubmed: 18452568
Mol Carcinog. 2016 Mar;55(3):268-79
pubmed: 25620587
Anticancer Res. 2019 Feb;39(2):597-607
pubmed: 30711935
Nucleic Acids Res. 2016 Jan 4;44(D1):D457-62
pubmed: 26476454
Sci Rep. 2019 Feb 26;9(1):2749
pubmed: 30808902
Proc Natl Acad Sci U S A. 1998 Dec 8;95(25):14863-8
pubmed: 9843981
Bioinformatics. 2007 Jul 15;23(14):1846-7
pubmed: 17496320
Database (Oxford). 2015 Apr 15;2015:bav028
pubmed: 25877637
J Clin Oncol. 2011 Dec 1;29(34):4482-90
pubmed: 22025148
Stat Appl Genet Mol Biol. 2005;4:Article17
pubmed: 16646834
Front Oncol. 2021 Mar 17;11:595259
pubmed: 33816228
BMC Bioinformatics. 2008 Dec 29;9:559
pubmed: 19114008
Adv Exp Med Biol. 2020;1240:1-23
pubmed: 32060884
Int J Cancer. 2008 May 15;122(10):2187-98
pubmed: 18092325
Clin J Oncol Nurs. 2016 Oct 1;20(5 Suppl):S2-8
pubmed: 27668386
Nat Methods. 2015 Feb;12(2):115-21
pubmed: 25633503
Lancet Oncol. 2014 Sep;15(10):1100-8
pubmed: 25163906
Am J Pathol. 2010 Sep;177(3):1491-502
pubmed: 20671264