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

Abstract (Expand)

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.

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

Date Published: 12th Jun 2018

Publication Type: Not specified

Human Diseases: glioblastoma multiforme

Dysregulated Signal Propagation in a MYC-associated Boolean Gene Network in B-cell Lymphoma
MMML-MYC-SYS

Abstract (Expand)

By the modern molecular biological approaches that exploit the availability of high quality gene expression data, it is made clear that flexible and robust responses of cellular programs are encoded … in the relations between gene expression values. These relations naturally define a network where they stand for edges between the nodes that stand for the genes. The wiring of these networks often found to be dysregulated in cancer. Different system biological approaches that rely on correlations, differential equations and logical analysis are used to probe these relations in gene expression data especially. In our work we investigated selected biological functions in aggressive germinal center B-cell lymphoma in terms of a logical analysis of gene-regulation in Boolean space and a signal propagation algorithm considering network topology based on gene expression data. We especially aimed at studying the activity of the MYC gene as a key player. It is shown that the functional output of a gene network is affected by the states of the genes and also by the wirings between them. Our results support the key function of MYC in lymphoma biology. In addition, we showed that genes can alter functional output of the network by alternative mechanisms like reducing the variance in propagating signal and locking it to a certain level.

Authors: V. Cakir, H. Loeffler-Wirth, A. Arakelyan, H. Binder

Date Published: 17th May 2017

Publication Type: Not specified

Human Diseases: B-cell lymphoma

Function Shapes Content: DNA-Methylation Marker Genes and their Impact for Molecular Mechanisms of Glioma
GGN - German Glioma Network

Abstract (Expand)

Glioma is a clinically and biologically diverse disease. It challenges diagnosis and prognosis due to its molecular heterogeneity and diverse regimes of biological dysfunctions which are driven by … genetic and epigenetic mechanisms. We discover the functional impact of sets of DNA methylation marker genes in the context of brain cancer subtypes as an exemplary approach how bioinformatics and particularly machine learning using self organizing maps (SOM) complements modern high-throughput genomic technologies. DNA methylation changes in gliomas comprise both, hyper- and hypomethylation in a subtype specific fashion. We compared pediatric (2 subtypes) and adult (4) glioblastoma and non-neoplastic brain. The functional impact of differential methylation marker sets is discovered in terms of gene set analysis which comprises a large collection of markers related to biological processes, literature data on gliomas and also chromatin states of the healthy brain. DNA methylation signature genes from alternative studies well agree with our signatures. SOM mapping of gene sets robustly identifies similarities between different marker sets even under conditions of noisy compositions. Mapping of previous sets of glioma markers reveals high redundancy and mixtures of subtypes in the reference cohorts. Consideration of the regulatory level of DNA methylation is inevitable for understanding cancer genesis and progression. It provides suited markers for diagnosis of glioma subtypes and disentangles tumor heterogeneity.

Authors: E. Willscher, H. Loffler-Wirth, H. Binder, Lydia Hopp

Date Published: 2015

Publication Type: Not specified

Human Diseases: brain glioma

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