Effect of differential hypoxia-related gene expression on glioblastoma

• Published in: Journal of international medical research Vol. 49; no. 5; p. 3000605211013774
• Main Authors: Lin, Chao-Qun, Chen, Lu-Kui
• Format: Journal Article
• Language: English
• Published: London, England SAGE Publications 01.05.2021; Sage Publications Ltd; SAGE Publishing
• Subjects: Brain cancer; Gene expression; Hypoxia; Medical prognosis; Nomograms; Retrospective Clinical Research Report; prognostic; hypoxia; nomogram; the Cancer Genome Atlas; Glioblastoma; risk scoring model
• ISSN: 0300-0605; 1473-2300
• DOI: 10.1177/03000605211013774

Objective Glioblastoma (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. Method Gene 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. Result Fourteen 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. Conclusion We determined a reliable hypoxia-related gene risk scoring model for predicting the prognosis of patients with GB.