Chromatin state annotation using combinations of chromatin modification patterns has emerged as a powerful approach for discovering regulatory regions and their cell type specific activity patterns, and for interpreting disease-association studies1-5. However, the computational challenge of learning chromatin state models from large numbers of chromatin modification datasets in multiple cell types still requires extensive bioinformatics expertise making it inaccessible to the wider scientific community. To address this challenge, we have developed ChromHMM, an automated computational system for learning chromatin states, characterizing their biological functions and correlations with large-scale functional datasets, and visualizing the resulting genome-wide maps of chromatin state annotations.

ChromHMM: automating chromatin-state discovery and characterization

Next-generation sequencing has revealed that more than 50% of human cancers harbour mutations in enzymes that are involved in chromatin organization. Tumour cells not only are activated by genetic and epigenetic alterations, but also routinely use epigenetic processes to ensure their escape from chemotherapy and host immune surveillance. Hence, a growing emphasis of recent drug discovery efforts has been on targeting the epigenome, including DNA methylation and histone modifications, with several new drugs being tested and some already approved by the US Food and Drug Administration (FDA). The future will see the increasing success of combining epigenetic drugs with other therapies. As epigenetic drugs target the epigenome as a whole, these true 'genomic medicines' lessen the need for precision approaches to individualized therapies.

Targeting the cancer epigenome for therapy

The detection of differentially methylated regions (DMRs) is a necessary prerequisite for characterizing different epigenetic states. We present a novel program, metilene, to identify DMRs within whole-genome and targeted data with unrivaled specificity and sensitivity. A binary segmentation algorithm combined with a two-dimensional statistical test allows the detection of DMRs in large methylation experiments with multiple groups of samples in minutes rather than days using off-the-shelf hardware. metilene outperforms other state-of-the-art tools for low coverage data and can estimate missing data. Hence, metilene is a versatile tool to study the effect of epigenetic modifications in differentiation/development, tumorigenesis, and systems biology on a global, genome-wide level. Whether in the framework of international consortia with dozens of samples per group, or even without biological replicates, it produces highly significant and reliable results.

/pdf/metilene-fast-and-sensitive-calling-of-differentially-3987bddagn.pdf

metilene: fast and sensitive calling of differentially methylated regions from bisulfite sequencing data

In cost-utility analysis, the numbers of quality-adjusted life years (QALYs) gained are aggregated according to the sum-ranking (or QALY maximisation) rule. This requires that the social value from health improvements is a simple product of gains in quality of life, length of life and the number of persons treated. The results from a systematic review of the literature suggest that QALY maximisation is descriptively flawed. Rather than being linear in quality and length of life, it would seem that social value diminishes in marginal increments of both. And rather than being neutral to the characteristics of people other than their propensity to generate QALYs, the social value of a health improvement seems to be higher if the person has worse lifetime health prospects and higher if that person has dependents. In addition, there is a desire to reduce inequalities in health. However, there are some uncertainties surrounding the results, particularly in relation to what might be affecting the responses, and there is the need for more studies of the general public that attempt to highlight the relative importance of various key factors.

/pdf/qaly-maximisation-and-people-s-preferences-a-methodological-4w4uxdjg5h.pdf

QALY maximisation and people's preferences: a methodological review of the literature.

Charting differences between tumors and normal tissue is a mainstay of cancer research. However, clonal tumor expansion from complex normal tissue architectures potentially obscures cancer-specific events, including divergent epigenetic patterns. Using whole-genome bisulfite sequencing of normal B cell subsets, we observed broad epigenetic programming of selective transcription factor binding sites coincident with the degree of B cell maturation. By comparing normal B cells to malignant B cells from 268 patients with chronic lymphocytic leukemia (CLL), we showed that tumors derive largely from a continuum of maturation states reflected in normal developmental stages. Epigenetic maturation in CLL was associated with an indolent gene expression pattern and increasingly favorable clinical outcomes. We further uncovered that most previously reported tumor-specific methylation events are normally present in non-malignant B cells. Instead, we identified a potential pathogenic role for transcription factor dysregulation in CLL, where excess programming by EGR and NFAT with reduced EBF and AP-1 programming imbalances the normal B cell epigenetic program.

DNA methylation dynamics during B cell maturation underlie a continuum of disease phenotypes in chronic lymphocytic leukemia

Although Burkitt lymphomas and follicular lymphomas both have features of germinal center B cells, they are biologically and clinically quite distinct. Here we performed whole-genome bisulfite, genome and transcriptome sequencing in 13 IG-MYC translocation-positive Burkitt lymphoma, nine BCL2 translocation-positive follicular lymphoma and four normal germinal center B cell samples. Comparison of Burkitt and follicular lymphoma samples showed differential methylation of intragenic regions that strongly correlated with expression of associated genes, for example, genes active in germinal center dark-zone and light-zone B cells. Integrative pathway analyses of regions differentially methylated in Burkitt and follicular lymphomas implicated DNA methylation as cooperating with somatic mutation of sphingosine phosphate signaling, as well as the TCF3-ID3 and SWI/SNF complexes, in a large fraction of Burkitt lymphomas. Taken together, our results demonstrate a tight connection between somatic mutation, DNA methylation and transcriptional control in key B cell pathways deregulated differentially in Burkitt lymphoma and other germinal center B cell lymphomas.

/pdf/dna-methylome-analysis-in-burkitt-and-follicular-lymphomas-235uw0vavb.pdf

DNA methylome analysis in Burkitt and follicular lymphomas identifies differentially methylated regions linked to somatic mutation and transcriptional control

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DNA methylome analysis in Burkitt and follicular lymphomas identifies differentially methylated regions linked to somatic mutation and transcriptional control