Combined SOM-portrayal of gene expression and DNA methylation landscapes disentangles modes of epigenetic regulation in glioblastoma.

Abstract:

AIM: We present here a novel method that enables unraveling the interplay between gene expression and DNA methylation in complex diseases such as cancer. MATERIALS & METHODS: The method is based on self-organizing maps and allows for analysis of data landscapes from 'governed by methylation' to 'governed by expression'. RESULTS: We identified regulatory modules of coexpressed and comethylated genes in high-grade gliomas: two modes are governed by genes hypermethylated and underexpressed in IDH-mutated cases, while two other modes reflect immune and stromal signatures in the classical and mesenchymal subtypes. A fifth mode with proneural characteristics comprises genes of repressed and poised chromatin states active in healthy brain. Two additional modes enrich genes either in active or repressed chromatin states. CONCLUSION: The method disentangles the interplay between gene expression and methylation. It has the potential to integrate also mutation and copy number data and to apply to large sample cohorts.

PubMed ID: 29888966

Projects: GGN - German Glioma Network

Publication type: Not specified

Journal: Epigenomics

Human Diseases: Glioblastoma multiforme

Citation: Epigenomics. 2018 Jun;10(6):745-764. doi: 10.2217/epi-2017-0140. Epub 2018 Jun 11.

Date Published: 12th Jun 2018

Registered Mode: by PubMed ID

Authors: L. Hopp, H. Loffler-Wirth, J. Galle, H. Binder

Help
Activity

Views: 2720

Created: 25th Oct 2019 at 13:07

Last updated: 7th Dec 2021 at 17:58

help Attributions

None

Related items

Powered by
(v.1.13.0-master)
Copyright © 2008 - 2021 The University of Manchester and HITS gGmbH
Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig

By continuing to use this site you agree to the use of cookies