Data Management And Sharing System of China National Clinical Research Center for Neurological Diseases
Bioinformatic analysis of gene expression and methylation regulation in glioblastoma.
First author：Wang Wen
Corresponding author：Zhao Jizong
essential_information
2018-02-01
Published articles
Background And Purpose
Method
To screen the differentially expressed genes affected by DNA methylation modification and further investigate their prognostic values for GBMs. We included The Cancer Genome Atlas (TCGA) RNA sequencing (676) and DNA methylation (Illumina Human Methylation 450K; 657) databases to detect the gene expression and methylation profiles. Chinese Glioma Genome Atlas (CGGA) RNA sequencing database and TCGA DNA methylation (Illumina Human Methylation 27K; 283) was included for validation. Gene expression and DNA methylation statues were identified using principal components analysis (PCA). A total of 3365 differentially expressed genes were identified.
Conclusion
Our results showed that the eight-gene signature has independently prognostic value for GBM patients.
Main results
Among them, 2940 genes showed low methylation and high expression, while 425 genes showed high methylation and low expression in GBMs. An eight-gene (C9orf64, OSMR, MDK, MARVELD1, PTRF, MYD88, BIRC3, RPP25) signature was established to divide GBM patients into two groups based on the cut-off point (27.24). The high risk group had shorter overall survival (OS) than low risk group (median OS 15.77 vs. 10.61 months; P = 0.0002). Moreover, the different clinical and molecular features were shown between two groups. These findings could be validated in additional datasets. The differentially expressed genes affected by DNA methylation modification were detected.