Abstract

BackgroundGlioma is the most common form of primary malignant intracranial tumor.MethodsIn the current study, miRNA matrix were obtained from the Chinese Glioma Genome Atlas (CGGA), and then univariate Cox regression analysis and Lasso regression analysis were utilized to select candidate miRNAs and multivariate Cox regression analysis was applied to establish a miRNA signature for predicting overall survival (OS) of glioma. The signature was assessed with the area under the curve (AUC) of the receiver operating characteristic curve (ROC) and validated by data from Gene Expression Omnibus (GEO).ResultsEight miRNAs (miR-1246, miR-148a, miR-150, miR-196a, miR-338-3p, miR-342-5p, miR-548h and miR-645) were included in the miRNA signature. The AUC of ROC analysis for 1- and 3-year OS in the CGGA dataset was 0.747 and 0.905, respectively. In the GEO dataset, The AUC for 1- and 3-year was 0.736 and 0.809, respectively. The AUC in both the CGGA and GEO datasets was similar to that based on WHO 2007 classification (0.736 and 0.799) and WHO 2016 classification (0.663 and 0.807). Additionally, Kaplan–Meier plot revealed that high-risk score patients had a poorer clinical outcome. Multivariate Cox regression analysis suggested that the miRNA signature was an independent prognosis-related factor [HR: 6.579, 95% CI [1.227−35.268], p = 0.028].ConclusionOn the whole, in the present study, based on eight miRNAs, a novel prognostic signature was developed for predicting the 1- and 3- year survival rate in glioma. The results may be conducive to predict the precise prognosis of glioma and to elucidate the underlying molecular mechanisms. However, further experimental researches of miRNAs are needed to validate the findings of this study.

Highlights

  • Glioma is the most prevalent malignant and most aggressive brain tumor (Alexander & Cloughesy, 2017; Molinaro et al, 2019)

  • 690 miRNAs were selected in the Chinese Glioma Genome Atlas (CGGA) dataset, and they were further analyzed by Lasso regression analysis, which screened out 19 miRNAs (Fig. 1A)

  • The results indicated that the prognosis of high-risk patients was worse than that of low-risk patients (P < 0.001, Fig. 4A)

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Summary

Introduction

Glioma is the most prevalent malignant and most aggressive brain tumor (Alexander & Cloughesy, 2017; Molinaro et al, 2019). Identification of an 8-miRNA signature as a potential prognostic biomarker for glioma. The overall survival rate of glioma is very low, especially the most common subtype: glioblastoma, which 5-year relative survival probability is only limited to 5.1% and median lifespan is only 14.6 months (Bray et al, 2018; Ferlay et al, 2019). Theerefore, there is an urgent need to explore more accurate tumor-specific biomarkers for glioma in order further develop novel diagnostic signatures and guide clinical treatment. The AUC of ROC analysis for 1- and 3-year OS in the CGGA dataset was 0.747 and 0.905, respectively. In the GEO dataset, The AUC for 1- and 3-year was 0.736 and 0.809, respectively. In the present study, based on eight miRNAs, a novel prognostic signature was developed for predicting the 1- and 3- year survival rate in glioma. Further experimental researches of miRNAs are needed to validate the findings of this study

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