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Updated: Mar 19, 2026

Characterization of Functionally Associated miRNAs in Glioblastoma and their Engineering into Artificial Clusters for Gene Therapy
Published on: October 4, 2019
Identification of key genes in glioblastoma-associated stromal cells using bioinformatics analysis
Chengyong Chen1, Chong Sun2, Dong Tang1
1Department of Neurosurgery, The Fifth People's Hospital of Jinan, Jinan, Shandong 250022, P.R. China.
Abstract:
The aim of the present study was to identify key genes and pathways in glioblastoma-associated stromal cells (GASCs) using bioinformatics. The expression profile of microarray GSE24100 was obtained from the Gene Expression Omnibus database, which included the expression profile of 4 GASC samples and 3 control stromal cell samples. Differentially expressed genes (DEGs) were identified using limma software in R language, and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis of DEGs were performed using the Database for Annotation, Visualization and Integrated Discovery software. In addition, a protein-protein interaction (PPI) network was constructed. Subsequently, a sub-network was constructed to obtain additional information on genes identified in the PPI network using CFinder software. In total, 502 DEGs were identified in GASCs, including 331 upregulated genes and 171 downregulated genes. Cyclin-dependent kinase 1 (CDK1), cyclin A2, mitotic checkpoint serine/threonine kinase (BUB1), cell division cycle 20 (CDC20), polo-like kinase 1 (PLK1), and transcription factor breast cancer 1, early onset (BRCA1) were identified from the PPI network, and sub-networks revealed these genes as hub genes that were involved in significant pathways, including mitotic, cell cycle and p53 signaling pathways. In conclusion, CDK1, BUB1, CDC20, PLK1 and BRCA1 may be key genes that are involved in significant pathways associated with glioblastoma. This information may lead to the identification of the mechanism of glioblastoma tumorigenesis.
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