DNA methylation, transcriptome and genetic copy number signatures of diffuse cerebral WHO grade II/III gliomas resolve cancer heterogeneity and development.

BACKGROUND: Diffuse lower WHO grade II and III gliomas (LGG) are slowly progressing brain tumors, many of which eventually transform into a more aggressive type. LGG is characterized by widespread genetic and transcriptional heterogeneity, yet little is known about the heterogeneity of the DNA methylome, its function in tumor biology, coupling with the transcriptome and tumor microenvironment and its possible impact for tumor development. METHODS: We here present novel DNA methylation data of an LGG-cohort collected in the German Glioma Network containing about 85% isocitrate dehydrogenase (IDH) mutated tumors and performed a combined bioinformatics analysis using patient-matched genome and transcriptome data. RESULTS: Stratification of LGG based on gene expression and DNA-methylation provided four consensus subtypes. We characterized them in terms of genetic alterations, functional context, cellular composition, tumor microenvironment and their possible impact for treatment resistance and prognosis. Glioma with astrocytoma-resembling phenotypes constitute the largest fraction of nearly 60%. They revealed largest diversity and were divided into four expression and three methylation groups which only partly match each other thus reflecting largely decoupled expression and methylation patterns. We identified a novel G-protein coupled receptor and a cancer-related 'keratinization' methylation signature in in addition to the glioma-CpG island methylator phenotype (G-CIMP) signature. These different signatures overlap and combine in various ways giving rise to diverse methylation and expression patterns that shape the glioma phenotypes. The decrease of global methylation in astrocytoma-like LGG associates with higher WHO grade, age at diagnosis and inferior prognosis. We found analogies between astrocytoma-like LGG with grade IV IDH-wild type tumors regarding possible worsening of treatment resistance along a proneural-to-mesenchymal axis. Using gene signature-based inference we elucidated the impact of cellular composition of the tumors including immune cell bystanders such as macrophages. CONCLUSIONS: Genomic, epigenomic and transcriptomic factors act in concert but partly also in a decoupled fashion what underpins the need for integrative, multidimensional stratification of LGG by combining these data on gene and cellular levels to delineate mechanisms of gene (de-)regulation and to enable better patient stratification and individualization of treatment.

[Gene expression analyses and their possible clinical benefit in head and neck cancer]. / Genexpressionsanalysen und ihrmöglicher klinischer Nutzen inder Betrachtung der Kopf-Hals-Karzinome

Systems biology approaches for mutational (exome analysis and targeted sequencing) and gene expression analysis (transcriptome-wide gene expression profiling) represent a new and growing scientific field in head and neck oncology. In addition to medical biological expertise, bioinformatic assistance is increasingly required. For squamous cell head and neck cancer (HNSCC), the recent molecular genetic single-gene and signal pathway observations represent basic research. Important aspects of this have now been significantly enhanced by systems biology approaches, which have grown into relevant areas of translational clinical research. It is now known that HPV16 is associated with genetic alterations at various locations, but also that it functionally affects genes not altered in their base sequence at the level of methylation. In transcriptome analyses, various consortia found matching clusters of gene expression and HPV16 association with the spectrum of somatic mutations. The differential methylation of gene promoters discovered in HPV16-driven HNSCC proved predictive for survival­even in HNSCC patients without HPV detection. The authors present an overview of some translationally relevant findings and venture an outlook on possible future clinical developments.

Genomic and epigenomic co-evolution in follicular lymphomas.

Follicular lymphoma (FL) with a t(14;18) is a B-cell neoplasm clinically characterized by multiple recurrencies. In order to investigate the clonal evolution of this lymphoma, we studied paired primary and relapse tumor samples from 33 patients with recurrent non-transformed t(14;18)-positive FL. We reconstructed phylogenetic trees of the evolution by taking advantage of the activation-induced cytidine deaminase (AID)-mediated somatic hypermutation (SHM) active in the germinal center reaction using sequences of the clonal VHDHJH rearrangements of the immunoglobulin heavy chain (IGH) locus. Mutational analysis of the IGH locus showed evidence for ongoing somatic mutation and for counter-selection of mutations affecting the BCR conformation during tumor evolution. We further followed evolutionary divergence by targeted sequencing of gene loci affected by aberrant SHM as well as of known driver genes of lymphomagenesis, and by array-based genome-wide chromosomal imbalance and DNA methylation analysis. We observed a wide spectrum of evolutionary patterns ranging from almost no evolution to divergent evolution within recurrent non-transformed t(14;18) FL. Remarkably, we observed a correlation of the magnitude of evolutionary divergence across all genetic and epigenetic levels suggesting co-evolution. The distribution of coding mutations in driver genes and the correlation with SHM suggest CREBBP and AID to be potential modifiers of genetic and epigenetic co-evolution in FL.

Chromosomal imbalances and partial uniparental disomies in primary central nervous system lymphoma.

To determine the pattern of genetic alterations in primary central nervous system lymphomas (PCNSL), 19 PCNSL were studied by high-density single-nucleotide polymorphism arrays. Recurrent losses involved 6p21.32, 6q21, 8q12-12.2, 9p21.3, 3p14.2, 4q35.2, 10q23.21 and 12p13.2, whereas gains involved 18q21-23, 19q13.31, 19q13.43 and the entire chromosomes X and 12. Partial uniparental disomies (pUPDs) were identified in 6p and 9p21.3. These genomic alterations affected the HLA locus, the CDKN2A/p16, CDKN2B/p15 and MTAP, as well as the PRDM1, FAS, MALT1, and BCL2 genes. Increased methylation values of the CDKN2A/p16 promoter region were detected in 75% (6/8) PCNSL. Gene expression profiling showed 4/21 (20%) minimal common regions of imbalances to be associated with a differential mRNA expression affecting the FAS, STAT6, CD27, ARHGEF6 and SEPT6 genes. Collectively, this study unraveled novel genomic imbalances and pUPD with a high resolution in PCNSL and identified target genes of potential relevance in the pathogenesis of this lymphoma entity.

Measurement of the proton asymmetry parameter in neutron beta decay.

The proton asymmetry parameter C in neutron decay describes the angular correlation between neutron spin and proton momentum. In this Letter, the first measurement of this quantity is presented. The result C= -0.2377(26) agrees with the standard model expectation. The coefficient C provides an additional parameter for new and improved standard model tests.

Development and implementation of an analysis tool for array-based comparative genomic hybridization.

OBJECTIVES: Array-comparative genomic hybridization (aCGH) is a high-throughput method to detect and map copy number aberrations in the genome. Multi-step analysis of high-dimensional data requires an integrated suite of bioinformatic tools. In this paper we detail an analysis pipeline for array CGH data. METHODS: We developed an analysis tool for array CGH data which supports single and multi-chip analyses as well as combined analyses with paired mRNA gene expression data. The functions supporting relevant steps of analysis were implemented using the open source software R and combined as package aCGHPipeline. Analysis methods were illustrated using 189 CGH arrays of aggressive B-cell lymphomas. RESULTS: The package covers data input, quality control, normalization, segmentation and classification. For multi-chip analysis aCGHPipeline offers an algorithm for automatic delineation of recurrent regions. This task was performed manually up to now. The package also supports combined analysis with mRNA gene expression data. Outputs consist of HTML documents to facilitate communication with clinical partners. CONCLUSIONS: The R package aCGHPipeline supports basic tasks of single and multi-chip analysis of array CGH data.

Measurement of the neutrino asymmetry parameter B in neutron decay.

A new measurement of the neutrino asymmetry parameter B in neutron decay, the angular correlation between neutron spin and antineutrino momentum, is presented. The result, B=0.9802(50), confirms earlier measurements but features considerably smaller corrections. It agrees with the standard model expectation and permits updated tests on "new physics" in neutron decay.

The Beta-, Neutrino- and Proton-Asymmetry in Neutron ß-Decay.

This article describes measurements of angular-correlation coefficients in the decay of free neutrons with the superconducting spectrometer PERKEO II. A method for measuring the ß-asymmetry coefficient A is presented, as well as a new method for determining the neutrino-asymmetry coefficient B, which allows a value for the proton-asymmetry coefficient C to be obtained for the first time. An ongoing experiment is trying to improve the accuracy of these quantities.