ArticleThe Journal of international medical research2021
Effect of differential hypoxia-related gene expression on glioblastoma.
Article in The Journal of international medical research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 11 citations in OpenAlex.
- The neglected burden of chronic hypoxia on the resistance of glioblastoma multiforme to first-line therapies.BMC biology · 2024Review
- Histone acetylation risk model predicts prognosis and guides therapy selection in glioblastoma: implications for chemotherapy and anti-CTLA-4 immunotherapy.BMC immunology · 2024Article
- Cuproptosis in glioblastoma: unveiling a novel prognostic model and therapeutic potential.Frontiers in oncology · 2024Article
- Deciphering glycosylation-driven prognostic insights and therapeutic prospects in glioblastoma through a comprehensive regulatory model.Frontiers in oncology · 2024Article
- Engineered Extracellular Vesicles for Drug Delivery in Therapy of Stroke.Pharmaceutics · 2023Review
Corrections and comments
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Authors and funding
2 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveGlioblastoma (GB) is a refractory malignancy with a high rate of recurrence and treatment resistance. Hypoxia-related genes are promising prognostic indicators for GB, so we herein developed a reliable hypoxia-related gene risk scoring model to predict the prognosis of patients with GB.
methodGene expression profiles and corresponding clinicopathological features of patients with GB were obtained from the Cancer Genome Atlas (TCGA; n = 160) and Gene Expression Omnibus (GEO) GSE7696 (n = 80) databases. Univariate and multivariate Cox regression analyses of differentially expressed hypoxia-related genes were performed using R 3.5.1 software.
resultFourteen prognosis-related genes were identified and used to construct a risk signature. Patients with high-risk scores had significantly lower overall survival (OS) than those with low-risk scores. The median risk score was used as a critical value and for OS prediction in an independent external verification GSE7696 cohort. Risk score was not significantly affected by clinical-related factors. We also developed a prediction nomogram based on the TCGA training set to predict survival rates, and included six independent prognostic parameters in the TCGA prediction model.
conclusionWe determined a reliable hypoxia-related gene risk scoring model for predicting the prognosis of patients with GB.
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