Open Access

Identification of potential key genes associated with glioblastoma based on the gene expression profile

  • Authors:
    • Lijuan Bo
    • Bo Wei
    • Chaohui Li
    • Zhanfeng Wang
    • Zheng Gao
    • Zhuang Miao
  • View Affiliations

  • Published online on: June 22, 2017     https://doi.org/10.3892/ol.2017.6460
  • Pages: 2045-2052
  • Copyright: © Bo et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

Gliomas are serious primary brain tumors. The aim of the present study was to identify potential key genes associated with the progression of gliomas. The GSE31262 gene expression profile data, which included 9 glioblastoma stem cells (GSCs) samples and 5 neural stem cell samples from adult humans, were downloaded from Gene Expression Omnibus (GEO) database. limma package was used to identify differentially expressed genes (DEGs). Based on STRING database and Pearson Correlation Coefficient (PCC), a co‑expression network was constructed to comprehensively understand the interactions between DEGs, and function analysis of genes in the network was conducted. Furthermore, the DEGs that were associated with prognosis were analyzed. A total of 431 DEGs were identified, including 98 upregulated DEGs and 333 downregulated DEGs. Genes including PDZ binding kinase, topoisomerase (DNA) II α (TOP2A), cyclin dependent kinase (CDK) 1, cell division cycle 6 and NIMA related kinase 2 had a relatively high degree in the co‑expression network. A set of genes including cyclin D1, CDK1 and CDK2 were significantly enriched in the cell cycle and p53 signaling pathway. Additionally, 69 DEGs were identified as genes involved in glioblastoma prognosis, such as CDK2 and TOP2A. The genes that had a higher degree and were associated with cell cycle and p53 signaling pathway may play pivotal roles in the progress of glioblastoma.
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August-2017
Volume 14 Issue 2

Print ISSN: 1792-1074
Online ISSN:1792-1082

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Copy and paste a formatted citation
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Spandidos Publications style
Bo L, Wei B, Li C, Wang Z, Gao Z and Miao Z: Identification of potential key genes associated with glioblastoma based on the gene expression profile. Oncol Lett 14: 2045-2052, 2017
APA
Bo, L., Wei, B., Li, C., Wang, Z., Gao, Z., & Miao, Z. (2017). Identification of potential key genes associated with glioblastoma based on the gene expression profile. Oncology Letters, 14, 2045-2052. https://doi.org/10.3892/ol.2017.6460
MLA
Bo, L., Wei, B., Li, C., Wang, Z., Gao, Z., Miao, Z."Identification of potential key genes associated with glioblastoma based on the gene expression profile". Oncology Letters 14.2 (2017): 2045-2052.
Chicago
Bo, L., Wei, B., Li, C., Wang, Z., Gao, Z., Miao, Z."Identification of potential key genes associated with glioblastoma based on the gene expression profile". Oncology Letters 14, no. 2 (2017): 2045-2052. https://doi.org/10.3892/ol.2017.6460