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A robust two‐gene signature for glioblastoma survival prediction
Author(s) -
Pan Yuhualei,
Zhang JianHua,
Zhao Lianhe,
Guo JinCheng,
Wang Song,
Zhao Yushang,
Tao Shaoxin,
Wang Huan,
Zhu YanBing
Publication year - 2020
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.29653
Subject(s) - proportional hazards model , gene signature , log rank test , oncology , survival analysis , confidence interval , medicine , microarray analysis techniques , glioma , biology , gene , gene expression , cancer research , genetics
Glioblastoma multiforme (GBM) is a highly malignant brain tumor. We explored the prognostic gene signature in 443 GBM samples by systematic bioinformatics analysis, using GSE16011 with microarray expression and corresponding clinical data from Gene Expression Omnibus as the training set. Meanwhile, patients from The Chinese Glioma Genome Atlas database (CGGA) were used as the test set and The Cancer Genome Atlas database (TCGA) as the validation set. Through Cox regression analysis, Kaplan‐Meier analysis, t‐distributed Stochastic Neighbor Embedding algorithm, clustering, and receiver operating characteristic analysis, a two‐gene signature (GRIA2 and RYR3) associated with survival was selected in the GSE16011 dataset. The GRIA2‐RYR3 signature divided patients into two risk groups with significantly different survival in the GSE16011 dataset (median: 0.72, 95% confidence interval [CI]: 0.64‐0.98, vs median: 0.98, 95% CI: 0.65‐1.61 years, logrank test P < .001), the CGGA dataset (median: 0.84, 95% CI: 0.70‐1.18, vs median: 1.21, 95% CI: 0.95‐2.94 years, logrank test P = .0017), and the TCGA dataset (median: 1.03, 95% CI: 0.86‐1.24, vs median: 1.23, 95% CI: 1.04‐1.85 years, logrank test P = .0064), validating the predictive value of the signature. And the survival predictive potency of the signature was independent from clinicopathological prognostic features in multivariable Cox analysis. We found that after transfection of U87 cells with small interfering RNA, GRIA2 and RYR3 influenced the biological behaviors of proliferation, migration, and invasion of glioblastoma cells. In conclusion, the two‐gene signature was a robust prognostic model to predict GBM survival.