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Identification of potential therapeutic targets for gliomas by bioinformatics analysis

  • Authors:
    • Ke Ma
    • Zhihua Cheng
    • Liqun Sun
    • Haibo Li
  • View Affiliations / Copyright

    Affiliations: Department of Paediatric Emergency, The First Hospital of Jilin University, Changchun, Jilin 130021, P.R. China, Department of Vascular Surgery, The First Hospital of Jilin University, Changchun, Jilin 130021, P.R. China
    Copyright: © Ma et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
  • Pages: 5203-5210
    |
    Published online on: August 28, 2017
       https://doi.org/10.3892/ol.2017.6850
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Abstract

Gliomas are primary tumors that originate in the brain or spinal cord and develop from supportive glial cells. The present study aimed to identify potential candidate molecular markers for the treatment of gliomas, and to explore the underlying mechanisms of this disease. The gene expression profile data GSE50021, which consisted of 10 specimens of normal brain tissues and 35 specimens of glioma tissues, was downloaded from Gene Expression Omnibus (GEO). The methylation microarray data GSE50022, consisting of 28 glioma specimens, was also downloaded from GEO. Differentially expressed genes (DEGs) between patients with glioma and normal individuals were identified, and key methylation sites were screened. Transcriptional regulatory networks were constructed, and target genes were selected. Survival analysis of key methylation sites and risk analysis of sub‑pathways were performed, from which key genes and pathways were selected. A total of 79 DEGs and 179 key methylation sites were identified, of which 20 target genes and 36 transcription factors were included in the transcriptional regulatory network. Glutamate metabotropic receptor 2 (GRM2) was regulated by 8 transcription factors. Inositol‑trisphosphate 3‑kinase A (ITPKA) was a significantly enriched DEG, associated with the inositol phosphate metabolism pathway, Survival analysis revealed that the survival time of patients with lower methylation levels in cg00157228 was longer than patients with higher methylation levels. ITPKA was the closest located gene to cg00157228. In conclusion, GRM2 and enriched ITPKA, associated with the inositol phosphate metabolism pathway, may be key mechanisms in the development and progression of gliomas. Furthermore, the present study provided evidence for an additional mechanism of methylation‑induced gliomas, in which methylation results in the dysregulation of specific transcripts. The results of the present study may provide a research direction for studying the mechanisms underlying the development and progression of gliomas.
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Copy and paste a formatted citation
Spandidos Publications style
Ma K, Cheng Z, Sun L and Li H: Identification of potential therapeutic targets for gliomas by bioinformatics analysis. Oncol Lett 14: 5203-5210, 2017.
APA
Ma, K., Cheng, Z., Sun, L., & Li, H. (2017). Identification of potential therapeutic targets for gliomas by bioinformatics analysis. Oncology Letters, 14, 5203-5210. https://doi.org/10.3892/ol.2017.6850
MLA
Ma, K., Cheng, Z., Sun, L., Li, H."Identification of potential therapeutic targets for gliomas by bioinformatics analysis". Oncology Letters 14.5 (2017): 5203-5210.
Chicago
Ma, K., Cheng, Z., Sun, L., Li, H."Identification of potential therapeutic targets for gliomas by bioinformatics analysis". Oncology Letters 14, no. 5 (2017): 5203-5210. https://doi.org/10.3892/ol.2017.6850
Copy and paste a formatted citation
x
Spandidos Publications style
Ma K, Cheng Z, Sun L and Li H: Identification of potential therapeutic targets for gliomas by bioinformatics analysis. Oncol Lett 14: 5203-5210, 2017.
APA
Ma, K., Cheng, Z., Sun, L., & Li, H. (2017). Identification of potential therapeutic targets for gliomas by bioinformatics analysis. Oncology Letters, 14, 5203-5210. https://doi.org/10.3892/ol.2017.6850
MLA
Ma, K., Cheng, Z., Sun, L., Li, H."Identification of potential therapeutic targets for gliomas by bioinformatics analysis". Oncology Letters 14.5 (2017): 5203-5210.
Chicago
Ma, K., Cheng, Z., Sun, L., Li, H."Identification of potential therapeutic targets for gliomas by bioinformatics analysis". Oncology Letters 14, no. 5 (2017): 5203-5210. https://doi.org/10.3892/ol.2017.6850
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