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A 4‐gene panel predicting the survival of patients with glioblastoma
Author(s) -
Guo XiaoXia,
Su Jiao,
He XiaoFeng
Publication year - 2019
Publication title -
journal of cellular biochemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.028
H-Index - 165
eISSN - 1097-4644
pISSN - 0730-2312
DOI - 10.1002/jcb.28883
Subject(s) - proportional hazards model , hazard ratio , oncology , univariate , medicine , survival analysis , univariate analysis , confidence interval , multivariate analysis , statistics , multivariate statistics , mathematics
Background To identify independently prognostic gene panel in patients with glioblastoma (GBM). Materials and methods The Cancer Genome Atlas (TCGA)‐GBM was used as a training set and a test set. GSE13041 was used as a validation set. Survival associated differentially expression genes (DEGs), derived between GBM and normal brain tissue, was obtained using univariate Cox proportional hazards regression model and then was included in a least absolute shrinkage and selection operator penalized Cox proportional hazards regression model. Thus, a 4‐gene prognostic panel was developed based on the risk score for each patient in that model. The prognostic role of the 4‐gene panel was validated using univariate and multivariable Cox proportional hazards regression model. Results A total of 686 patients with GBM were included in our study; 724 DEGs was identified, 133 of which was significantly correlated with the overall survival (OS) of patients with GBM. A 4‐gene panel including NMB, RTN1, GPC5, and epithelial membrane protein 3 (EMP3) was developed. Kaplan‐Meier survival analysis suggested that patients in the 4‐gene panel low risk group had significantly better OS than those in the 4‐gene panel high risk group in the training set (hazard ratio [HR] = 0.3826; 95% confidence interval [CI]: 0.2751‐0.532; P < 0.0001), test set (HR = 0.718; 95% CI: 0.5282‐0.9759; P = 0.033) and the independent validation set (HR = 0.6898; 95% CI: 0.4872‐0.9766; P = 0.035). Both univariate and multivariable Cox proportional hazards regression analysis suggested that the 4‐gene panel was independent prognostic factor for GBM in the training set. Conclusion We developed and validated 4‐gene panel that was independently correlated with the survival of patients with GBM.