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.
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.
Entities:
Keywords:
cancer heterogeneity; gene regulation; integrative bioinformatics; machine learning; molecular subtypes; transcriptome and methylome
Authors: H Binder; E Willscher; H Loeffler-Wirth; L Hopp; D T W Jones; S M Pfister; M Kreuz; D Gramatzki; E Fortenbacher; B Hentschel; M Tatagiba; U Herrlinger; H Vatter; J Matschke; M Westphal; D Krex; G Schackert; J C Tonn; U Schlegel; H-J Steiger; W Wick; R G Weber; M Weller; M Loeffler Journal: Acta Neuropathol Commun Date: 2019-04-25 Impact factor: 7.801
Authors: Henry Loeffler-Wirth; Michael Rade; Arsen Arakelyan; Markus Kreuz; Markus Loeffler; Ulrike Koehl; Kristin Reiche; Hans Binder Journal: Front Immunol Date: 2022-09-28 Impact factor: 8.786