NEUROLOGY / RESEARCH PAPER
An immune-related long non-coding RNA signature predicts prognosis in glioblastoma patients
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1 |
Department of Neurosurgery, Jiangxi Provincial People’s Hospital Affiliated to Nanchang University, Nanchang 330006, Jiangxi Provincial, China., China |
2 |
Department of Neurosurgery, Jinan City People's Hospital, Jinan 271100, Shandong Provincial, China., China |
3 |
Department of Neurosurgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, No.324, Jingwu Road, Jinan 250000, Shandong Provincial, China., China |
CORRESPONDING AUTHOR
Peng Qiu
Department of Neurosurgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, No.324, Jingwu Road, Jinan 250000, Shandong Provincial, China., China
Submission date: 2021-04-24
Final revision date: 2021-07-01
Acceptance date: 2021-07-21
Online publication date: 2021-07-27
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ABSTRACT
Introduction:
This study aimed to explore the prognostic value of immune-related long non-coding RNAs (lncRNAs) in glioblastoma (GBM).
Material and methods:
Expression and clinical data were acquired, including GSE111260 dataset: 67 GBM and 3 normal brain samples; GSE103227 dataset: 5 GBM and 5 normal brain samples; and TCGA data: 187 GBM samples. Immune-related genes were retrieved from ImmPort database. Immune-related differentially expressed genes (DEGs) and lncRNAs were screened. Prognostic lncRNAs were then screened to establish prognostic risk score model. Survival analysis and differential expression analysis were performed in high- vs. low-risk groups, followed by protein-protein interaction network and lncRNA-mRNA co-expression network.
Results:
A total of 251 immune-related DEGs were screened. After correlation analysis, 387 immune-related lncRNAs that co-expressed with 140 immune-related DEGs were screened. Univariate analysis identified 18 lncRNAs that were significantly associated with prognosis. The prognostic risk score could be able to stratify GBM patients into high- and low-risk groups, and patients with high risk scores displayed worse outcomes than those with low risk scores in both training set and validation set. A total of 272 genes had abnormal expression between high- and low-risk groups. Of which, 22 genes were immune-related, such as SNAP25, SNAP91, SNCB, and RAB3A. These genes were mainly enriched in synaptic vesicle cycle/exocytosis and insulin secretion. The co-expression network contained 22 genes and 11 lncRNAs, and lncRNA LINC01574 co-expressed with the great number of mRNAs.
Conclusions:
We identified 18 immune-related prognostic lncRNAs, and the established lncRNAs-based prognostic risk model could stratify GBM patients into different risks.