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Mining the glioma susceptibility genes in children from gene expression profiles and a methylation database

  • Authors:
    • Yongqiang Xi
    • Wanzhong Tang
    • Song Yang
    • Maolei Li
    • Yuchao He
    • Xianhua Fu
  • View Affiliations / Copyright

    Affiliations: Department of Neurosurgery, The Third People's Hospital of Chengyang, Qingdao, Shandong 266100, P.R. China, Department of Neurosurgery, Affiliated Hospital of Medical College of Qingdao University, Qingdao, Shandong 266100, P.R. China, Department of Neurosurgery, Suqian First Hospital, Suqian, Jiangsu 223800, P.R. China, Department of Neurosurgery, People's Hospital of Chengyang, Qingdao, Shandong 266100, P.R. China
    Copyright: © Xi et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
  • Pages: 3473-3479
    |
    Published online on: July 15, 2017
       https://doi.org/10.3892/ol.2017.6579
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Abstract

Glioma is the most common type of primary brain tumor, which is associated with a poor prognosis due to its aggressive growth behavior and highly invasive nature. Research regarding glioma pathogenesis is expected to provide novel methods of adjuvant therapy for the treatment of glioma. The use of bioinformatics to identify candidate genes is commonly used to understand the genetic basis of disease. The present study used bioinformatics to mine the disease‑related genes using gene expression profiles (GSE50021) and dual‑channel DNA methylation data (GSE50022). The results identified 17 methylation sites located on 33 transcription factor binding sites, which may be responsible for downregulation of 17 target genes. glutamate metabotropic receptor 2 was one of the 17 downregulated target genes. Furthermore, inositol-trisphosphate 3-kinase A (ITPKA) was revealed to be the gene most associated with the risk of glioma in children. The protein coded by the ITPKA gene appeared in all risk sub‑pathways, thus suggesting that ITPKA was the gene most associated with the risk of glioma, and inositol phosphate metabolism may be a key pathway associated with glioma in children. The identification of specific genes helps to determine the pathogenesis and possible therapeutic targets for the treatment of glioma in children.
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Copy and paste a formatted citation
Spandidos Publications style
Xi Y, Tang W, Yang S, Li M, He Y and Fu X: Mining the glioma susceptibility genes in children from gene expression profiles and a methylation database. Oncol Lett 14: 3473-3479, 2017.
APA
Xi, Y., Tang, W., Yang, S., Li, M., He, Y., & Fu, X. (2017). Mining the glioma susceptibility genes in children from gene expression profiles and a methylation database. Oncology Letters, 14, 3473-3479. https://doi.org/10.3892/ol.2017.6579
MLA
Xi, Y., Tang, W., Yang, S., Li, M., He, Y., Fu, X."Mining the glioma susceptibility genes in children from gene expression profiles and a methylation database". Oncology Letters 14.3 (2017): 3473-3479.
Chicago
Xi, Y., Tang, W., Yang, S., Li, M., He, Y., Fu, X."Mining the glioma susceptibility genes in children from gene expression profiles and a methylation database". Oncology Letters 14, no. 3 (2017): 3473-3479. https://doi.org/10.3892/ol.2017.6579
Copy and paste a formatted citation
x
Spandidos Publications style
Xi Y, Tang W, Yang S, Li M, He Y and Fu X: Mining the glioma susceptibility genes in children from gene expression profiles and a methylation database. Oncol Lett 14: 3473-3479, 2017.
APA
Xi, Y., Tang, W., Yang, S., Li, M., He, Y., & Fu, X. (2017). Mining the glioma susceptibility genes in children from gene expression profiles and a methylation database. Oncology Letters, 14, 3473-3479. https://doi.org/10.3892/ol.2017.6579
MLA
Xi, Y., Tang, W., Yang, S., Li, M., He, Y., Fu, X."Mining the glioma susceptibility genes in children from gene expression profiles and a methylation database". Oncology Letters 14.3 (2017): 3473-3479.
Chicago
Xi, Y., Tang, W., Yang, S., Li, M., He, Y., Fu, X."Mining the glioma susceptibility genes in children from gene expression profiles and a methylation database". Oncology Letters 14, no. 3 (2017): 3473-3479. https://doi.org/10.3892/ol.2017.6579
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