Identification of key methylation differentially expressed genes in posterior fossa ependymoma based on epigenomic and transcriptome analysis
| Autor: | Xiaosheng He, Huijun Chen, Guanyi Wang, Yibin Jia, Yuqing Ye, Enming Kang, Jiayou Wang |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Epigenomics
0301 basic medicine Ependymoma Posterior fossa ependymoma Computational biology Biology Methylation General Biochemistry Genetics and Molecular Biology Transcriptome Phosphatidylinositol 3-Kinases Epigenome 03 medical and health sciences 0302 clinical medicine medicine Humans KEGG Child WGCNA Microarray analysis techniques Research Gene Expression Profiling Membrane raft Differential genes General Medicine medicine.disease 030104 developmental biology 030220 oncology & carcinogenesis Medicine Extracellular matrix organization |
| Zdroj: | Journal of Translational Medicine, Vol 19, Iss 1, Pp 1-14 (2021) Journal of Translational Medicine |
| ISSN: | 1479-5876 |
| DOI: | 10.1186/s12967-021-02834-1 |
| Popis: | Background Posterior fossa ependymoma (EPN-PF) can be classified into Group A posterior fossa ependymoma (EPN-PFA) and Group B posterior fossa ependymoma (EPN-PFB) according to DNA CpG island methylation profile status and gene expression. EPN-PFA usually occurs in children younger than 5 years and has a poor prognosis. Methods Using epigenome and transcriptome microarray data, a multi-component weighted gene co-expression network analysis (WGCNA) was used to systematically identify the hub genes of EPN-PF. We downloaded two microarray datasets (GSE66354 and GSE114523) from the Gene Expression Omnibus (GEO) database. The Limma R package was used to identify differentially expressed genes (DEGs), and ChAMP R was used to analyze the differential methylation genes (DMGs) between EPN-PFA and EPN-PFB. GO and KEGG enrichment analyses were performed using the Metascape database. Results GO analysis showed that enriched genes were significantly enriched in the extracellular matrix organization, adaptive immune response, membrane raft, focal adhesion, NF-kappa B pathway, and axon guidance, as suggested by KEGG analysis. Through WGCNA, we found that MEblue had a significant correlation with EPN-PF (R = 0.69, P = 1 × 10–08) and selected the 180 hub genes in the blue module. By comparing the DEGs, DMGs, and hub genes in the co-expression network, we identified five hypermethylated, lower expressed genes in EPN-PFA (ATP4B, CCDC151, DMKN, SCN4B, and TUBA4B), and three of them were confirmed by IHC. Conclusion ssGSEA and GSVA analysis indicated that these five hub genes could lead to poor prognosis by inducing hypoxia, PI3K-Akt-mTOR, and TNFα-NFKB pathways. Further study of these dysmethylated hub genes in EPN-PF and the pathways they participate in may provides new ideas for EPN-PF treatment. |
| Databáze: | OpenAIRE |
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