A Novel Six-mRNA Signature Predicts Survival of Patients With Glioblastoma Multiforme - Liu, Zhentao; Zhang, Hao; Hu, Hongkang; Cai, Zheng; Lu, Chengyin; Liang, Qiang; Qian, Jun; Wang, Chunhui; Jiang, Lei (Frontiers in Genetics, 2021)
Glioblastoma multiform (GBM) is a devastating brain tumor and displays divergent clinical outcomes due to its high degree of heterogeneity. Reliable prognostic biomarkers are urgently needed for improving risk stratification and survival prediction. In this study, we analyzed genome-wide mRNA profiles in GBM patients derived from The Cancer Genome Atlas to identify mRNA-based signatures for GBM prognosis with survival analysis. Univariate cox regression model was used to evaluate the relationship between the expression of mRNA and the prognosis of glioblastomas. We established a risk score model that consisted of six mRNA (AACS, STEAP1, STEAP2, G6PC3, FKBP9, LOXL1) by Lasso regression method. The 6-mRNA-signature could divide patients into high- and low-risk group with significantly different survival rates in train and test sets. Multivariate Cox’s regression analysis confirmed that it was an independent prognostic factor in GBM patients and it has a superior predictive power as compared with age, IDH mutation status, MGMT and G-CIMP methylation status. By combining this signature and clinical risk factors, a nomogram can be established to predict 1 -, 2-and 3-year OS in GBM patients with relatively high accuracy.