Identification of an IFN-β-associated gene signature for the prediction of overall survival among glioblastoma patients

Abstract

Background: Brain glioblastoma multiforme (GBM) is the most common primary malignant intracranial tumor. The prognosis of this disease is extremely poor. 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.Methods: 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 |R 2 |>0.3 and P<0.05 was considered to be an IFN-β-associated lncRNA.Results: 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.Conclusions: 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.

Transcription Profile and Pathway Analysis of the Endocannabinoid Receptor Inverse Agonist AM630 in the Core and Infiltrative Boundary of Human Glioblastoma Cells

“…In support of our findings, new evidence suggests the involvement of the effector caspases 3 and 9, BAX and the phosphor JNK pathway in the AM630 anti-tumoral actions in glioblastoma [ 55 ]. Our findings regarding the beneficial effects of harnessing the IFN signalling pathway, are supported by recent evidence that identifies an IFN-β-associated gene signature as a marker for the prediction of overall survival among glioblastoma patients [ 56 ]. In tandem with the pathway analysis we performed an investigation of the transcription factors predicted to recapitulate the inhibitory activity of AM630.…”

HeberFERON distinctively targets Cell Cycle in the glioblastoma-derived cell line U-87MG

“…The best known is the methylation status of O(6)-methylguanine-DNA-methyltransferase (MGMT) as a predictor of temozolomide (Hegi et al 2005) and radiation resistance (Rivera et al 2010). Other has described IFNβ or IFNγ associated gene signatures to predict OS, efficacy of immunotherapy and radiotherapy among glioblastoma patients (Cheng et al 2021, Ji et al 2021). Eventually, these genes signatures should be validated in the clinical practice.…”

A co-formulation of Interferons alpha2b and gamma distinctively targets Cell Cycle in the glioblastoma-derived cell line U-87MG

“…The best known molecular biomarker is the methylation status of O(6)-methylguanine-DNA-methyltransferase (MGMT) as a predictor of TMZ [95] and radiation resistance [96]. Other authors have described IFNβ or IFNγ associated gene signatures to predict OS, e cacy of immunotherapy and radiotherapy among glioblastoma patients [97,98].…”