Molecular mechanisms underlying gliomas and glioblastoma pathogenesis revealed by bioinformatics analysis of microarray data
- PMID: 28952134
- DOI: 10.1007/s12032-017-1043-x
Molecular mechanisms underlying gliomas and glioblastoma pathogenesis revealed by bioinformatics analysis of microarray data
Abstract
The aim of this study was to identify key genes associated with gliomas and glioblastoma and to explore the related signaling pathways. Gene expression profiles of three glioma stem cell line samples, three normal astrocyte samples, three astrocyte overexpressing 4 iPSC-inducing and oncogenic factors (myc(T58A), OCT-4, p53DD, and H-Ras(G12V)) samples, three astrocyte overexpressing 7 iPSC-inducing and oncogenic factors (OCT4, H-Ras(G12V), myc(T58A), p53DD, cyclin D1, CDK4(RC24) and hTERT) samples and three glioblastoma cell line samples were downloaded from the ArrayExpress database (accession: E-MTAB-4771). The differentially expressed genes (DEGs) in gliomas and glioblastoma were identified using FDR and t tests, and protein-protein interaction (PPI) networks for these DEGs were constructed using the protein interaction network analysis. The GeneTrail2 1.5 tool was used to identify potentially enriched biological processes among the DEGs using gene ontology (GO) terms and to identify the related pathways using the Kyoto Encyclopedia of Genes and Genomes, Reactome and WikiPathways pathway database. In addition, crucial modules of the constructed PPI networks were identified using the PEWCC1 plug-in, and their topological properties were analyzed using NetworkAnalyzer, both available from Cytoscape. We also constructed microRNA-target gene regulatory network and transcription factor-target gene regulatory network for these DEGs were constructed using the miRNet and binding and expression target analysis. We identified 200 genes that could potentially be involved in the gliomas and glioblastoma. Among them, bioinformatics analysis identified 137 up-regulated and 63 down-regulated DEGs in gliomas and glioblastoma. The significant enriched pathway (PI3K-Akt) for up-regulated genes such as COL4A1, COL4A2, EGFR, FGFR1, LAPR6, MYC, PDGFA, SPP1 were selected as well as significant GO term (ear development) for up-regulated genes such as CELSR1, CHRNA9, DDR1, FGFR1, GLI2, LGR5, SOX2, TSHR were selected, while the significant enriched pathway (amebiasis) for down-regulated gene such as COL3A1, COL5A2, LAMA2 were selected as well as significant GO term (RNA polymerase II core promoter proximal region sequence-specific binding (5) such as MEIS2, MEOX2, NR2E1, PITX2, TFAP2B, ZFPM2 were selected. Importantly, MYC and SOX2 were hub proteins in the up-regulated PPI network, while MET and CDKN2A were hub proteins in the down-regulated PPI network. After network module analysis, MYC, FGFR1 and HOXA10 were selected as the up-regulated coexpressed genes in the gliomas and glioblastoma, while SH3GL3 and SNRPN were selected as the down-regulated coexpressed genes in the gliomas and glioblastoma. MicroRNA hsa-mir-22-3p had a regulatory effect on the most up DEGs, including VSNL1, while hsa-mir-103a-3p had a regulatory effect on the most down DEGs, including DAPK1. Transcription factor EZH2 had a regulatory effect on the both up and down DEGs, including CD9, CHI3L1, MEIS2 and NR2E1. The DEGs, such as MYC, FGFR1, CDKN2A, HOXA10 and MET, may be used for targeted diagnosis and treatment of gliomas and glioblastoma.
Keywords: DEGs; Glioblastoma; Gliomas; MicroRNA; Protein–protein interaction network; Transcription factors.
Similar articles
-
Identification of differentially expressed genes regulated by molecular signature in breast cancer-associated fibroblasts by bioinformatics analysis.Arch Gynecol Obstet. 2018 Jan;297(1):161-183. doi: 10.1007/s00404-017-4562-y. Epub 2017 Oct 23. Arch Gynecol Obstet. 2018. PMID: 29063236
-
Bioinformatics analyses of significant genes, related pathways and candidate prognostic biomarkers in glioblastoma.Mol Med Rep. 2018 Nov;18(5):4185-4196. doi: 10.3892/mmr.2018.9411. Epub 2018 Aug 21. Mol Med Rep. 2018. PMID: 30132538 Free PMC article.
-
The identification of key genes and pathways in hepatocellular carcinoma by bioinformatics analysis of high-throughput data.Med Oncol. 2017 Jun;34(6):101. doi: 10.1007/s12032-017-0963-9. Epub 2017 Apr 21. Med Oncol. 2017. PMID: 28432618 Free PMC article.
-
Gene Prioritization and Network Topology Analysis of Targeted Genes for Acquired Taxane Resistance by Meta-Analysis.Crit Rev Eukaryot Gene Expr. 2019;29(6):581-597. doi: 10.1615/CritRevEukaryotGeneExpr.2019026317. Crit Rev Eukaryot Gene Expr. 2019. PMID: 32422012 Review.
-
Bioinformatics Genes and Pathway Analysis for Chronic Neuropathic Pain after Spinal Cord Injury.Biomed Res Int. 2017;2017:6423021. doi: 10.1155/2017/6423021. Epub 2017 Oct 15. Biomed Res Int. 2017. PMID: 29164149 Free PMC article. Review.
Cited by
-
The impact of MEIS1 TALE homeodomain transcription factor knockdown on glioma stem cell growth.Anim Cells Syst (Seoul). 2024 Mar 13;28(1):93-109. doi: 10.1080/19768354.2024.2327340. eCollection 2024. Anim Cells Syst (Seoul). 2024. PMID: 38487309 Free PMC article.
-
Chromatin and Cancer: Implications of Disrupted Chromatin Organization in Tumorigenesis and Its Diversification.Cancers (Basel). 2023 Jan 11;15(2):466. doi: 10.3390/cancers15020466. Cancers (Basel). 2023. PMID: 36672415 Free PMC article. Review.
-
The Mysterious Universe of the TSH Receptor.Front Endocrinol (Lausanne). 2022 Jul 12;13:944715. doi: 10.3389/fendo.2022.944715. eCollection 2022. Front Endocrinol (Lausanne). 2022. PMID: 35903283 Free PMC article. Review.
-
A Novel Multi-Omics Analysis Model for Diagnosis and Survival Prediction of Lower-Grade Glioma Patients.Front Oncol. 2022 May 12;12:729002. doi: 10.3389/fonc.2022.729002. eCollection 2022. Front Oncol. 2022. PMID: 35646656 Free PMC article.
-
Downregulation of MEIS1 mediated by ELFN1-AS1/EZH2/DNMT3a axis promotes tumorigenesis and oxaliplatin resistance in colorectal cancer.Signal Transduct Target Ther. 2022 Mar 30;7(1):87. doi: 10.1038/s41392-022-00902-6. Signal Transduct Target Ther. 2022. PMID: 35351858 Free PMC article.
References
MeSH terms
Substances
LinkOut - more resources
Full Text Sources
Other Literature Sources
Medical
Research Materials
Miscellaneous
