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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Journal of Cellular ...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Journal of Cellular Biochemistry
Article . 2020 . Peer-reviewed
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A robust two‐gene signature for glioblastoma survival prediction

Authors: Yuhualei Pan; Jian‐Hua Zhang; Lianhe Zhao; Jin‐Cheng Guo; Song Wang; Yushang Zhao; Shaoxin Tao; +2 Authors

A robust two‐gene signature for glioblastoma survival prediction

Abstract

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.

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Keywords

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

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    influence
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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).
BIP!Citations provided by BIP!
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.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
9
Top 10%
Average
Top 10%
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