4.6 Article

An Immune-Related Six-lncRNA Signature to Improve Prognosis Prediction of Glioblastoma Multiforme

期刊

MOLECULAR NEUROBIOLOGY
卷 55, 期 5, 页码 3684-3697

出版社

HUMANA PRESS INC
DOI: 10.1007/s12035-017-0572-9

关键词

Long non-coding RNAs; Glioblastoma multiforme; Signature; Prognosis; Immune

资金

  1. National Natural Science Foundation of China [61602134]
  2. Postdoctoral scientific research developmental fund of Heilongjiang Province [LBH-Q16172]

向作者/读者索取更多资源

Recent studies have demonstrated the utility and superiority of long non-coding RNAs (lncRNAs) as novel biomarkers for cancer diagnosis, prognosis, and therapy. In the present study, the prognostic value of lncRNAs in glioblastoma multiforme was systematically investigated by performing a genome-wide analysis of lncRNA expression profiles in 419 glioblastoma patients from The Cancer Genome Atlas (TCGA) project. Using survival analysis and Cox regression model, we identified a set of six lncRNAs (AC005013.5, UBE2R2-AS1, ENTPD1-AS1, RP11-89C21.2, AC073115.6, and XLOC_004803) demonstrating an ability to stratify patients into high- and low-risk groups with significantly different survival (median 0.899 vs. 1.611 years, p = 3.87e-09, log-rank test) in the training cohort. The six-lncRNA signature was successfully validated on independent test cohort of 219 patients with glioblastoma, and it revealed superior performance for risk stratification with respect to existing lncRNA-related signatures. Multivariate Cox and stratification analysis indicated that the six-lncRNA signature was an independent prognostic factor after adjusting for other clinical covariates. Further in silico functional analysis suggested that the six-lncRNA signature may be involved in the immune-related biological processes and pathways which are very well known in the context of glioblastoma tumorigenesis. The identified lncRNA signature had important clinical implication for improving outcome prediction and guiding the tailored therapy for glioblastoma patients with further prospective validation.

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