
doi: 10.1002/jcb.29653
pmid: 31960992
AbstractGlioblastoma 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.
Adult, Aged, 80 and over, Male, Models, Statistical, Brain Neoplasms, Genome, Human, Gene Expression Profiling, Kaplan-Meier Estimate, Middle Aged, Gene Expression Regulation, Neoplastic, Cell Movement, Cell Line, Tumor, Cluster Analysis, Humans, Female, Neoplasm Invasiveness, Glioblastoma, Algorithms, Aged, Cell Proliferation
Adult, Aged, 80 and over, Male, Models, Statistical, Brain Neoplasms, Genome, Human, Gene Expression Profiling, Kaplan-Meier Estimate, Middle Aged, Gene Expression Regulation, Neoplastic, Cell Movement, Cell Line, Tumor, Cluster Analysis, Humans, Female, Neoplasm Invasiveness, Glioblastoma, Algorithms, Aged, Cell Proliferation
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 9 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
