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Identification of Potential Biomarkers in Glioblastoma through Bioinformatic Analysis and Evaluating Their Prognostic Value
Joint Authors
Zhou, Yangmei
Yang, Li
Zhang, Xiaoxi
Chen, Rui
Chen, Xiuqiong
Tang, Wenhua
Zhang, Mengxian
Source
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-04-15
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
Glioblastoma is a common malignant tumor in the central nervous system with an extremely poor outcome; understanding the mechanisms of glioblastoma at the molecular level is essential for clinical treatment.
In the present study, we used bioinformatics analysis to identify potential biomarkers associated with prognosis in glioblastoma and elucidate the underlying mechanisms.
The result revealed that 552 common genes were differentially expressed between glioblastoma and normal tissues based on TCGA, GSE4290, and GSE 50161 datasets.
Gene Oncology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment and protein-protein interaction (PPI) network were carried out to gain insight into the actions of differentially expressed genes (DEGs).
As a result, 20 genes (CALB1, CDC20, CDCA8, CDK1, CEP55, DLGAP5, KIF20A, KIF4A, NDC80, PBK, RRM2, SYN1, SYP, SYT1, TPX2, TTK, VEGFA, BDNF, GNG3, and TOP2A) were found as hub genes via CytoHubba in Cytoscape and functioned mainly by participating in cell cycle and p53 signaling pathway; among them, RRM2 and CEP55 were considered to have relationship with the prognosis of glioblastoma, especially RRM2.
High expression of RRM2 was consistent with shorter overall survival time.
In conclusion, our study displayed the bioinformatic analysis methods in screening potential oncogenes in glioblastoma and underlying mechanisms.
What is more is that we successfully identified RRM2 as a novel biomarker linked with prognosis, which might be expected to be a promising target for the therapy of glioblastoma.
American Psychological Association (APA)
Zhou, Yangmei& Yang, Li& Zhang, Xiaoxi& Chen, Rui& Chen, Xiuqiong& Tang, Wenhua…[et al.]. 2019. Identification of Potential Biomarkers in Glioblastoma through Bioinformatic Analysis and Evaluating Their Prognostic Value. BioMed Research International،Vol. 2019, no. 2019, pp.1-13.
https://search.emarefa.net/detail/BIM-1126847
Modern Language Association (MLA)
Zhou, Yangmei…[et al.]. Identification of Potential Biomarkers in Glioblastoma through Bioinformatic Analysis and Evaluating Their Prognostic Value. BioMed Research International No. 2019 (2019), pp.1-13.
https://search.emarefa.net/detail/BIM-1126847
American Medical Association (AMA)
Zhou, Yangmei& Yang, Li& Zhang, Xiaoxi& Chen, Rui& Chen, Xiuqiong& Tang, Wenhua…[et al.]. Identification of Potential Biomarkers in Glioblastoma through Bioinformatic Analysis and Evaluating Their Prognostic Value. BioMed Research International. 2019. Vol. 2019, no. 2019, pp.1-13.
https://search.emarefa.net/detail/BIM-1126847
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1126847