A five-miRNA signature with prognostic and predictive value for MGMT promoter-methylated glioblastoma patients
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Wen Cheng1, Xiufang Ren2, Jinquan Cai3, Chuanbao Zhang4,5, Mingyang Li4,5, Kuanyu Wang6, Yang Liu1, Sheng Han1 and Anhua Wu1
1 Department of Neurosurgery, The First Hospital of China Medical University, Shenyang, China
2 Department of Pathology, Shengjing Hospital of China Medical University, Shenyang, China
3 Department of Neurosurgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
4 Beijing Neurosurgical Institute, Beijing, China
5 Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
6 Department of Neurosurgery, The First Affiliated Hospital of Dalian Medical University, Dalian, China
Anhua Wu, email:
Keywords: glioblastoma, MGMT promoter methylation, miRNA, prognosis, predictive model
Received: May 02, 2015 Accepted: July 11, 2015 Published: July 22, 2015
Although O(6)-methylguanine DNA methyltransferase (MGMT) promoter methylation status is an important marker for glioblastoma multiforme (GBM), there is considerable variability in the clinical outcome of patients with similar methylation profiles. The present study aimed to refine the prognostic and predictive value of MGMT promoter status in GBM by identifying a micro (mi)RNA risk signature. Data from The Cancer Genome Atlas was used for this study, with MGMT promoter-methylated samples randomly divided into training and internal validation sets. Data from The Chinese Glioma Genome Atlas was used for independent validation. A five miRNA-based risk signature was established for MGMT promoter-methylated GBM to distinguish cases as high- or low-risk with distinct prognoses, which was confirmed using internal and external validation sets. Importantly, the prognostic value of the signature was significant in different cohorts stratified by clinicopathologic factors and alkylating chemotherapy, and a multivariate Cox analysis found it to be an independent prognostic marker along with age and chemotherapy. Based on these three factors, we developed a quantitative model with greater accuracy for predicting the 1-year survival of patients with MGMT promoter-methylated GBM. These results indicate that the five-miRNA signature is an independent risk predictor for GBM with MGMT promoter methylation and can be used to identify patients at high risk of unfavorable outcome and resistant to alkylating chemotherapy, underscoring its potential for personalized GBM management.
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