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Integrated mRNAseq and microRNAseq data analysis for grade III gliomas

  • Authors:
    • Junqiang Dai
    • Zhitong Bing
    • Yinian Zhang
    • Qiao Li
    • Liang Niu
    • Wentao Liang
    • Guoqiang Yuan
    • Lei Duan
    • Hang Yin
    • Yawen Pan
  • View Affiliations / Copyright

    Affiliations: Department of Neurosurgery, Lanzhou University Second Hospital, Lanzhou, Gansu 730030, P.R. China, Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou, Gansu 730000, P.R. China, Institute of Neurology, Lanzhou University Second Hospital, Lanzhou, Gansu 730030, P.R. China
    Copyright: © Dai et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
  • Pages: 7468-7478
    |
    Published online on: September 20, 2017
       https://doi.org/10.3892/mmr.2017.7545
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Abstract

The World Health Organization classification distinguishes four grades for gliomas. Grade III gliomas, which are brain malignant brain tumors with variable biological behavior and propensity, have been not widely investigated. The objective of the present study was to identify specific gene modules and valuable hubs associated with gliomagenesis and molecular signatures to assist in determining grade III glioma prognosis. mRNAseq and micro (mi)RNAseq data were used to construct a co‑expression network of gliomas using weight gene co‑expression network analysis, and revealed the prognostic molecular signature of grade III gliomas. The differently expressed miRNAs and mRNAs were identified. A total of 37 mRNAs and 10 miRNAs were identified, which were closely associated with the survival rates of patients with grade III glioma. To further understand the tumorigenesis, Cytoscape software was used to construct a network containing these differently expressed molecules. The result suggested that both the downregulated genes and upregulated genes are vital in the process of glioma deterioration, and certain genes are closely associated with clinical prognosis.
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Copy and paste a formatted citation
Spandidos Publications style
Dai J, Bing Z, Zhang Y, Li Q, Niu L, Liang W, Yuan G, Duan L, Yin H, Pan Y, Pan Y, et al: Integrated mRNAseq and microRNAseq data analysis for grade III gliomas. Mol Med Rep 16: 7468-7478, 2017.
APA
Dai, J., Bing, Z., Zhang, Y., Li, Q., Niu, L., Liang, W. ... Pan, Y. (2017). Integrated mRNAseq and microRNAseq data analysis for grade III gliomas. Molecular Medicine Reports, 16, 7468-7478. https://doi.org/10.3892/mmr.2017.7545
MLA
Dai, J., Bing, Z., Zhang, Y., Li, Q., Niu, L., Liang, W., Yuan, G., Duan, L., Yin, H., Pan, Y."Integrated mRNAseq and microRNAseq data analysis for grade III gliomas". Molecular Medicine Reports 16.5 (2017): 7468-7478.
Chicago
Dai, J., Bing, Z., Zhang, Y., Li, Q., Niu, L., Liang, W., Yuan, G., Duan, L., Yin, H., Pan, Y."Integrated mRNAseq and microRNAseq data analysis for grade III gliomas". Molecular Medicine Reports 16, no. 5 (2017): 7468-7478. https://doi.org/10.3892/mmr.2017.7545
Copy and paste a formatted citation
x
Spandidos Publications style
Dai J, Bing Z, Zhang Y, Li Q, Niu L, Liang W, Yuan G, Duan L, Yin H, Pan Y, Pan Y, et al: Integrated mRNAseq and microRNAseq data analysis for grade III gliomas. Mol Med Rep 16: 7468-7478, 2017.
APA
Dai, J., Bing, Z., Zhang, Y., Li, Q., Niu, L., Liang, W. ... Pan, Y. (2017). Integrated mRNAseq and microRNAseq data analysis for grade III gliomas. Molecular Medicine Reports, 16, 7468-7478. https://doi.org/10.3892/mmr.2017.7545
MLA
Dai, J., Bing, Z., Zhang, Y., Li, Q., Niu, L., Liang, W., Yuan, G., Duan, L., Yin, H., Pan, Y."Integrated mRNAseq and microRNAseq data analysis for grade III gliomas". Molecular Medicine Reports 16.5 (2017): 7468-7478.
Chicago
Dai, J., Bing, Z., Zhang, Y., Li, Q., Niu, L., Liang, W., Yuan, G., Duan, L., Yin, H., Pan, Y."Integrated mRNAseq and microRNAseq data analysis for grade III gliomas". Molecular Medicine Reports 16, no. 5 (2017): 7468-7478. https://doi.org/10.3892/mmr.2017.7545
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