Gao H, Zhao H, Xiang W. Expression level of human miR-34a correlates with glioma grade and prognosis.
J Neurooncol 2013;
113:221-8. [PMID:
23529798 DOI:
10.1007/s11060-013-1119-1]
[Citation(s) in RCA: 45] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2012] [Accepted: 03/16/2013] [Indexed: 12/11/2022]
Abstract
The aim of this study is to investigate the expression level of microRNA-34a (miR-34a) in glioma patients and its significance for predicting the prognosis of glioma. In this study, we examined the expression of miR-34a in glioma tissues of various World Health Organization (WHO) grades and explored the association between miR-34a expression and clinical and pathological parameters of glioma patients. We found that the tissues from high-grade gliomas (grade III and IV) had much lower miR-34a expression compared to normal brain tissues. The results of a 72-month follow-up in 146 glioma patients further demonstrated that miR-34a expression levels positively correlated with tumor WHO grades. Additionally, in the patients with grade III and IV gliomas, lower miR-34a expression correlated with worse progression-free survival and overall survival. Univariate and multivariate analysis revealed that miR-34a was an independent prognostic indicator for glioma. Additionally, we explored the correlation between miR-34a expression and p53 status and Bcl-2 expression in grade III and IV glioma tissues. Wild-type p53 tumors displayed significantly higher miR-34a expression level than mutant p53 tumors. In addition, glioma tissues with high miR-34a expression had dramatically lower Bcl-2 expression levels than tissues with low miR-34a expression. These findings indicate the role of miR-34a in tumor progression may be closely associated with p53 mutation and inversely correlated to Bcl-2 expression. In conclusion, our work presents comprehensive evidence for miR-34a expression as a novel and potentially useful signature for predicting prognosis of glioma.
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