A prognostic signature based on three non‐coding RNA s for prediction of the overall survival of glioma patients

• Published in: FEBS open bio 2019-04, Vol.9 (4), p.682-692
• Main Authors: Xian, Junmin, Zhang, Quanzhong, Guo, Xiwen, Liang, Xiankun, Liu, Xinhua, Feng, Yugong
• Format: Article
• Language: English
• ISSN: 2211-5463; 2211-5463
• DOI: 10.1002/2211-5463.12602

Recent studies have identified certain non‐coding RNA s (nc RNA s) as biomarkers of disease progression. Glioma is the most common primary intracranial cancer, with high mortality. Here, we developed a prognostic signature for prediction of overall survival (OS) of glioma patients by analyzing nc RNA expression profiles. We downloaded gene expression profiles of glioma patients along with their clinical information from the Gene Expression Omnibus and extracted nc RNA expression profiles via a microarray annotation file. Correlations between nc RNA s and glioma patients’ OS were first evaluated through univariate Cox regression analysis and a permutation test, followed by random survival forest analysis for further screening of valuable nc RNA signatures. Prognostic signatures could be established as a risk score formula by including nc RNA signature expression values weighted by their estimated regression coefficients. Patients could be divided into high risk and low risk subgroups by using the median risk score as cutoff. As a result, glioma patients with a high risk score tended to have shorter OS than those with low risk scores, which was confirmed by analyzing another set of glioma patients in an independent dataset. Additionally, gene set enrichment analysis showed significant enrichment of cancer development‐related biological processes and pathways. Our study may provide further insights into the evaluation of glioma patients’ prognosis.