Data Management And Sharing System of China National Clinical Research Center for Neurological Diseases
Identification of IDH-mutant gliomas by a prognostic signature according to gene expression profiling
First author：Wang Qiangwei,Wang Zhiliang
Corresponding author：Wang Zheng,You Gan,Jiang Tao
essential_information
- Person in charge：Wang Qiangwei,Wang Zhiliang
- Data Sources： OTHERS
- Number of papers：OTHERS20190623
- Published time：2018-08-15
2018-08-15
Published articles
Journal：Aging
Publication type: Research Paper
IF(IF): 5.515
PMID: 30115812 Link To Pubmed Full text Download
Background And Purpose
Method
In total, 167 gliomas from Chinese Glioma Genome Atlas (CGGA) dataset were included for discovery. The Cancer Genome Atlas (TCGA) dataset was used for validation. R language was the main software environment for our statistical operation and graphics.
Conclusion
We have identified a seven-gene signature that can provide a more accurate predictor of 3 years and 5 years for patients with IDH-mutant glioma. Moreover, the signature may potentially help neurosurgeons with the clinical personalized management of gliomas.
Main results
We applied the Time-Dependent ROC Curve (timeROC) method to estimate the gene prediction accuracy of 3 years and 5 years in two datasets. Seven genes were selected for further analysis (AUC ≥ 0.7 in two datasets). A seven-gene enrichment score was established to predict the overall survival of 3 years and 5 years for IDH- mutant glioma patients. Moreover, the seven-gene signature was an independent prognostic indicator for patients with IDH-mutant glioma. Gene Ontology (GO) Analysis of associated genes revealed signature-related biological process of cell cycle and division.