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Identification of key genes in glioblastoma-associated stromal cells using bioinformatics analysis

  • Authors:
    • Chengyong Chen
    • Chong Sun
    • Dong Tang
    • Guangcheng Yang
    • Xuanjun Zhou
    • Donghai Wang
  • View Affiliations / Copyright

    Affiliations: Department of Neurosurgery, The Fifth People's Hospital of Jinan, Jinan, Shandong 250022, P.R. China, Department of Neurosurgery, People's Hospital of Huantai, Zibo, Shandong 256400, P.R. China, Department of Neurosurgery, Qilu Hospital of Shandong University, Jinan, Shandong 250012, P.R. China
    Copyright: © Chen et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
  • Pages: 3999-4007
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    Published online on: May 5, 2016
       https://doi.org/10.3892/ol.2016.4526
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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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Copy and paste a formatted citation
Spandidos Publications style
Chen C, Sun C, Tang D, Yang G, Zhou X and Wang D: Identification of key genes in glioblastoma-associated stromal cells using bioinformatics analysis. Oncol Lett 11: 3999-4007, 2016.
APA
Chen, C., Sun, C., Tang, D., Yang, G., Zhou, X., & Wang, D. (2016). Identification of key genes in glioblastoma-associated stromal cells using bioinformatics analysis. Oncology Letters, 11, 3999-4007. https://doi.org/10.3892/ol.2016.4526
MLA
Chen, C., Sun, C., Tang, D., Yang, G., Zhou, X., Wang, D."Identification of key genes in glioblastoma-associated stromal cells using bioinformatics analysis". Oncology Letters 11.6 (2016): 3999-4007.
Chicago
Chen, C., Sun, C., Tang, D., Yang, G., Zhou, X., Wang, D."Identification of key genes in glioblastoma-associated stromal cells using bioinformatics analysis". Oncology Letters 11, no. 6 (2016): 3999-4007. https://doi.org/10.3892/ol.2016.4526
Copy and paste a formatted citation
x
Spandidos Publications style
Chen C, Sun C, Tang D, Yang G, Zhou X and Wang D: Identification of key genes in glioblastoma-associated stromal cells using bioinformatics analysis. Oncol Lett 11: 3999-4007, 2016.
APA
Chen, C., Sun, C., Tang, D., Yang, G., Zhou, X., & Wang, D. (2016). Identification of key genes in glioblastoma-associated stromal cells using bioinformatics analysis. Oncology Letters, 11, 3999-4007. https://doi.org/10.3892/ol.2016.4526
MLA
Chen, C., Sun, C., Tang, D., Yang, G., Zhou, X., Wang, D."Identification of key genes in glioblastoma-associated stromal cells using bioinformatics analysis". Oncology Letters 11.6 (2016): 3999-4007.
Chicago
Chen, C., Sun, C., Tang, D., Yang, G., Zhou, X., Wang, D."Identification of key genes in glioblastoma-associated stromal cells using bioinformatics analysis". Oncology Letters 11, no. 6 (2016): 3999-4007. https://doi.org/10.3892/ol.2016.4526
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