Functional implications of aging-related lncRNAs for predicting prognosis and immune status in glioma patients

This study is aimed to establish a new glioma prognosis model by integrating the aging-related lncRNA expression profiles and clinical parameters of glioma patients enrolled in the Chinese Glioma Genome Atlas and The Cancer Genome Atlas. The aging-related lncRNAs were explored using Pearson correlation analysis (|R|> 0.6, P < 0.001), and the prognostic signature in glioma patients was screened using univariate cox regression and least absolute shrinkage/selection operator regression. Based on the fifteen lncRNAs screened out, we divided the glioma patients into three subtypes, and developed a prognostic model. Kaplan-Meier survival curve analysis showed that low-risk patients survived longer time than high-risk patients. Principal component analysis indicated that the signature of aging-related lncRNAs was clearly distinct between the high- and low-risk groups. We also found the fifteen lncRNAs were closely correlated with 119 genes by establishing a co-expression network. Kyoto Encyclopedia of Genes and Genomes analysis displayed that the high- and low-risk groups were enriched in different functions and pathways. Different missense mutations were observed in the two groups, and the most frequent variant types were single nucleotide polymorphism. This study demonstrates that the novel aging-related lncRNAs signature has an important prognosis prediction ability and may contribute to individualized treatment for glioma.