ArticleAnnals of translational medicine2021
Identification of an IFN-β-associated gene signature for the prediction of overall survival among glioblastoma patients.
Article in Annals of translational medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
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11 citing papers in PubMed, 1 synthesis or guideline pooled it, 19 citations in OpenAlex.
- mRNA markers for survival prediction in glioblastoma multiforme patients: a systematic review with bioinformatic analyses.BMC cancer · 2024Pooled it
- Biomarkers for predicting immunotherapy response and resistance in glioblastoma.Frontiers in immunology · 2026Review
- A novel prognostic risk score associated with resistance to docetaxel chemotherapy for predicting biochemical recurrence-free survival in patients with prostate cancer.Discover oncology · 2025Article
- Construction and validation of a lysine beta hydroxybutyrylation related molecular model for predicting biochemical recurrence of prostate cancer.Scientific reports · 2025Article
- Development of a ferroptosis-based molecular markers for predicting RFS in prostate cancer patients.Scientific reports · 2023Article
- A co-formulation of interferons alpha2b and gamma distinctively targets cell cycle in the glioblastoma-derived cell line U-87MG.BMC cancer · 2023Article
- A Liquid-Liquid Phase Separation-Related Index Associate with Biochemical Recurrence and Tumor Immune Environment of Prostate Cancer Patients.International journal of molecular sciences · 2023Article
- Transcription Profile and Pathway Analysis of the Endocannabinoid Receptor Inverse Agonist AM630 in the Core and Infiltrative Boundary of Human Glioblastoma Cells.Molecules (Basel, Switzerland) · 2022Article
- Immune infiltration and a necroptosis-related gene signature for predicting the prognosis of patients with cervical cancer.Frontiers in genetics · 2022Article
- A Novel Ferroptosis-Based Molecular Signature Associated with Biochemical Recurrence-Free Survival and Tumor Immune Microenvironment of Prostate Cancer.Frontiers in cell and developmental biology · 2021Article
- Advancing precision prognostication in neuro-oncology: Machine learning models for data-driven personalized survival predictions in IDH-wildtype glioblastoma.Neuro-oncology advancesArticle
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Authors and funding
8 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundBrain 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.
methodsMessenger 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
resultsPatients 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.
conclusionsIn 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.
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