A 4‐gene panel predicting the survival of patients with glioblastoma

Abstract

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.

Development of a Prognostic Five-Gene Signature with Radiotherapy Guidance Significance for Diffuse Lower-Grade Glioma Patients Based on Large-Scale Sequencing Data

“…Epithelial membrane protein 3(EMP3) is considered to be a tumor suppressor, but this article found that this gene is a prognostic risk gene for LGG. Similar to our results, Haiwei Wang et al also found that EMP3 was associated with the worse prognosis of LGG patients [23] and Xiao-Xia Guo et al discovered EMP3 was also a risk gene in the process of developing a prognostic 4-gene panel for glioblastoma patients [24]. WEE1 G2 checkpoint kinase(WEE1) is reported to be an oncogenic nuclear kinase and a regulator of the G2 checkpoint.…”

Prognosis Analysis and Validation of m6A Signature and Tumor Immune Microenvironment in Glioma

“…Ma et al have demonstrated that EMP3 -mediated miR-663a inhibits the gallbladder cancer progression via the MAPK/ERK pathway ( 63 ). Recently, the bioinformatics analysis also found that EMP3 was one of the validated gene panel independently and was correlated with the GBM survival ( 64 , 65 ). Another bioinformatics analysis though significant analysis of microarray (SAM) identified that EMP3 could be used to estimate glioma patient prognosis ( 66 ).…”

Systematic identification of lncRNA-based prognostic biomarkers for glioblastoma

“…The AUC of our model in 3 years was 0.85, the highest was 0.93, the smallest AUC was 0.75 such as Figure 11A, and the highest AUC of 8 immune gene signature (Cheng et al) was 0.64 such as Figure 11B [32]. The highest AUC of 4 gene panel of Guo et al was 0.79 (Figure 11C) [33]. On the other hand, comparing the C-index of the three models, our model has the highest C-index, 0.66, and our model is better than the other two models in all aspects.…”