Translational Oncology (Apr 2017)

Differential Expression of Circular RNAs in Glioblastoma Multiforme and Its Correlation with Prognosis

  • Junle Zhu,
  • Jingliang Ye,
  • Lei Zhang,
  • Lili Xia,
  • Hongkang Hu,
  • Heng Jiang,
  • Zhiping Wan,
  • Fei Sheng,
  • Yan Ma,
  • Wen Li,
  • Jun Qian,
  • Chun Luo

DOI
https://doi.org/10.1016/j.tranon.2016.12.006
Journal volume & issue
Vol. 10, no. 2
pp. 271 – 279

Abstract

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OBJECTIVE: The present study aimed to explore the expression profiles of circular RNAs (circRNAs) in glioblastoma multiforme (GBM) in an attempt to identify potential core genes in the pathogenesis of this tumor. METHODS: Differentially expressed circRNAs were screened between tumor tissues from five GBM patients and five normal brain samples using Illumina Hiseq. Bioinformatics analysis was used to analyze their potential function. CircBRAF was further detected in different WHO grades glioma tissues and normal brain tissues. Kaplan-Meier curves and multivariate Cox's analysis were used to analyze the association between circBRAF expression level and prognosis of glioma patients. RESULTS: A total of 1411 differentially expressed circRNAs were identified in GBM patients including 206 upregulated circRNAs and 1205 downregulated circRNAs. Differential expression of circRNAs was closely associated with the biological process and molecular function. The downregulated circRNAs were mainly associated with ErbB and Neurotrophin signaling pathways. Moreover, the expression level of circBRAF in normal brain tissues was significantly higher than that in glioma tissues (P < .001). CircBRAF was significantly lower in glioma patients with high pathological grade (WHO III & IV) than those with low grade (WHO I & II) (P < .001). Cox analysis revealed that high circBRAF expression was an independent biomarker for predicting good progression-free survival and overall survival in glioma patients (HR = 0.413, 95% CI 0.201-0.849; HR = 0.299, 95% CI 0.135-0.661; respectively). CONCLUSION: The present study identified a profile of dysregulated circRNAs in GBM. Bioinformatics analysis showed that dysregulated circRNAs might be associated with tumorigenesis and development of GBM. In addition, circBRAF could severe as a biomarker for predicting pathological grade and prognosis in glioma patients.