Abstract
BACKGROUND: Gliomas are the most lethal type of primary brain tumor in adult. Long noncoding RNAs (lncRNAs), which are involved in the progression of various cancers, may offer a potential gene therapy target in glioma. METHODS AND FINDINGS: We first classified gliomas into three molecular subtypes (namely LncR1, LncR2 and LncR3) in Rembrandt dataset using consensus clustering. Survival analysis indicated that LncR3 had the best prognosis, while the LncR1 subtype showed the poorest overall survival rate. The results were further validated in an independent glioma dataset GSE16011. Additionally, we collected and merged data of the two databases (Rembrandt and GSE16011 dataset) and analyzed prognosis of each subtype in WHO II, III and IV gliomas. The similar results were obtained. Gene Set Variation Analysis (GSVA) demonstrated that LncR1 subtype enriched cultured astroglia's gene signature, while LncR2 subtype was characterized by neuronal gene signature. Oligodendrocytic was rich in LncR3. In addition, IDH1 mutation and 1p/19q LOH were found rich with LncR3, and EGFR amplification showed high percentage in LncR1 in GSE16011 dataset. CONCLUSIONS: We report a novel molecular classification of glioma based on lncRNA expression profiles and believe that it would provide a potential platform for future studies on gene treatment for glioma and lead to more individualized therapies to improve survival rates.