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pmid:34350240
Identification of an IFN-β-associated gene signature for the prediction of overall survival among glioblastoma patients.
Lijing Cheng · Meiling Yuan · Shu Li · Zhiying Lian · Junjing Chen · Weibiao Lin · Jianbo Zhang · Shupeng Zhong
Annals of translational medicine · 2021 doi:10.21037/atm-21-1986
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Complete file
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While the introduction of β-interferon (IFN-β) regimen in the treatment of gliomas has significantly improved the outcome of patients; The mechanism by which IFN-β induces increased TMZ sensitivity has not been described. Therefore, the main objective of the study was to elucidate the molecular mechanisms responsible for the beneficial effect of IFNβ in GBM.\nMETHODS: Messenger RNA expression profiles and clinicopathological data were downloaded from The Cancer Genome Atlas (TCGA) GBM and GSE83300 dataset from the Gene Expression Omnibus. Univariate Cox regression analysis and lasso Cox regression model established a novel 4-gene IFN-β signature (peroxiredoxin 1, Sec61 subunit beta, X-ray repair cross-complementing 5, and Bcl-2-like protein 2) for GBM prognosis prediction. Further, GBM samples (n=50) and normal brain tissues (n=50) were then used for real-time polymerase chain reaction experiments. Gene set enrichment analysis (GSEA) was performed to further understand the underlying molecular mechanisms. Pearson correlation was applied to calculate the correlation between the long non-coding RNAs (lncRNAs) and IFN-β-associated genes. An lncRNA with a correlation coefficient |R2|>0.3 and P<0.05 was considered to be an IFN-β-associated lncRNA.\nRESULTS: Patients in the high-risk group had significantly poorer survival than patients in the low-risk group. The signature was found to be an independent prognostic factor for GBM survival. Furthermore, GSEA revealed several significantly enriched pathways, which might help explain the underlying mechanisms. Our study identified a novel robust 4-gene IFN-β signature for GBM prognosis prediction. The signature might contain potential biomarkers for metabolic therapy and treatment response prediction for GBM patients.\nCONCLUSIONS: In the present study, we established a novel IFN-β-associated gene signature to predict the overall survival of GBM patients, which may help in clinical decision making for individual treatment.", "claims": [{"id": "claim-method", "statement": "The limma package was used to screen the differentially expressed genes of interest with R software version 4.0.2. The expression pattern of the 120 IFN-β-associated genes was then investigated in TCGA.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34350240", "locator": "sections[4] \"Identification of differentially expressed genes in TCGA GBM\" paragraph 2", "quote": "The limma package was used to screen the differentially expressed genes of interest with R software version 4.0.2. 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