Identification of an epithelial-mesenchymal transition related long non-coding RNA (LncRNA) signature in Glioma

Abstract

ABSTRACT Epithelial–mesenchymal transition (EMT)-related long non-coding RNAs (lncRNAs) may be exploited as potential therapeutic targets in gliomas. However, the prognostic value of EMT-related lncRNAs in gliomas is unclear. We obtained lncRNAs from The Cancer Genome Atlas and constructed EMT-related lncRNA co-expression networks to identify EMT-related lncRNAs. The Chinese Glioma Genome Atlas (CGGA) was used for validation. Gene set enrichment and principal component analyses were used for functional annotation. The EMT–lncRNA co-expression networks were constructed. A real-time quantitative polymerase chain reaction assay was performed to validate the bioinformatics results. A nine-EMT-related lncRNAs (HAR1A, LINC00641, LINC00900, MIR210HG, MIR22HG, PVT1, SLC25A21-AS1, SNAI3-AS1, and SNHG18) signature was identified in patients with glioma. Patients in the low-risk group had a longer overall survival (OS) than those in the high-risk group (P < 0.0001). Additionally, patients in the high-risk group showed no deletion of chromosomal arms 1p and/or 19q, isocitrate dehydrogenase wild type, and higher World Health Organization grade. Moreover, the signature was identified as an independent factor and was significantly associated with OS (P = 0.041, hazard ratio = 1.806). These findings were further validated using the CGGA dataset. The low- and high-risk groups showed different EMT statuses based on principal component analysis. To study the regulatory function of lncRNAs, a lncRNA-mediated ceRNA network was constructed, which showed that complex interactions of lncRNA–miRNA–mRNA may be a potential cause of EMT progression in gliomas. This study showed that the nine-EMT-related lncRNA signature has a prognostic value in gliomas.