EXPERIMENTAL RESEARCH
An immune-related long non-coding RNA signature predicts prognosis in glioblastoma patients
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1
Nanchang University, Nanchang 330031, Jiangxi, China
2
Department of Neurosurgery, Jiangxi provincial People’s Hospital,The First Affiliated Hospital of Nanchang Medical College, Nanchang 330006, Jiangxi, China
3
Department of Neurosurgery, Department of Neurosurgery, People’s Hospital Affiliated to Shandong First Medical University, Jinan271100, Shandong, China
4
Department of Neurosurgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong Provincial, China
Submission date: 2021-04-24
Final revision date: 2021-07-01
Acceptance date: 2021-07-21
Online publication date: 2021-07-27
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
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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 the GSE111260 dataset: 67 GBM and 3 normal brain samples; the GSE103227 dataset: 5 GBM and 5 normal brain samples; and TCGA data: 187 GBM samples. Immune-related genes were retrieved from the ImmPort database. Immune-related differentially expressed genes (DEGs) and lncRNAs were screened. Prognostic lncRNAs were then screened to establish a prognostic risk score model. Survival analysis and differential expression analysis were performed in high- vs. low-risk groups, followed by the protein-protein interaction network and the 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 was 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 the training set and the validation set. A total of 272 genes had abnormal expression between high- and low-risk groups. Of these, 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 lncRNA-based prognostic risk model could stratify GBM patients into different risk levels.