Open Access

Identification of glioblastoma‑specific prognostic biomarkers via an integrative analysis of DNA methylation and gene expression

  • Authors:
    • Yu Kun Mao
    • Zhi Bo Liu
    • Lin Cai
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  • Published online on: June 11, 2020     https://doi.org/10.3892/ol.2020.11729
  • Pages: 1619-1628
  • Copyright: © Mao et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

Glioblastoma (GBM) is the most aggressive and lethal tumor of the central nervous system. The present study set out to identify reliable prognostic and predictive biomarkers for patients with GBM. RNA‑sequencing data were obtained from The Cancer Genome Atlas database and DNA methylation data were downloaded using the University of California Santa Cruz‑Xena database. The expression and methylation differences between patients with GBM, and survival times <1 and ≥1 year were investigated. A protein‑protein interaction network was constructed and functional enrichment analyses of differentially expressed and methylated genes were performed. Hub genes were identified using the Cytoscape plug‑in cytoHubba software. Survival analysis was performed using the survminer package, in order to determine the prognostic values of the hub genes. The present study identified 71 genes that were hypomethylated and expressed at high levels, and four genes that were hypermethylated and expressed at low levels in GBM. These genes were predominantly enriched in the ‘JAK‑STAT signaling pathway’, ‘transcriptional misregulation in cancer’ and the ‘ECM‑receptor interaction’, which are associated with GBM development. Among the 24 hub genes identified, 15 possessed potential prognostic value. An integrative analysis approach was implemented in order to analyze the association of DNA methylation with changes in gene expression and to assess the association of gene expression changes with GBM survival time. The results of the present study suggest that these 15 CpG‑based genes may be useful and practical tools in predicting the prognosis of patients with GBM. However, future research on gene methylation and/or expression is required in order to develop personalized treatments for patients with GBM.
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August-2020
Volume 20 Issue 2

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

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Spandidos Publications style
Mao YK, Liu ZB and Cai L: Identification of glioblastoma‑specific prognostic biomarkers via an integrative analysis of DNA methylation and gene expression. Oncol Lett 20: 1619-1628, 2020.
APA
Mao, Y.K., Liu, Z.B., & Cai, L. (2020). Identification of glioblastoma‑specific prognostic biomarkers via an integrative analysis of DNA methylation and gene expression. Oncology Letters, 20, 1619-1628. https://doi.org/10.3892/ol.2020.11729
MLA
Mao, Y. K., Liu, Z. B., Cai, L."Identification of glioblastoma‑specific prognostic biomarkers via an integrative analysis of DNA methylation and gene expression". Oncology Letters 20.2 (2020): 1619-1628.
Chicago
Mao, Y. K., Liu, Z. B., Cai, L."Identification of glioblastoma‑specific prognostic biomarkers via an integrative analysis of DNA methylation and gene expression". Oncology Letters 20, no. 2 (2020): 1619-1628. https://doi.org/10.3892/ol.2020.11729