Molecular Signatures of Regression of the Canine Transmissible Venereal Tumor.

The canine transmissible venereal tumor (CTVT) is a clonally transmissible cancer that regresses spontaneously or after treatment with vincristine, but we know little about the regression mechanisms. We performed global transcriptional, methylation, and functional pathway analyses on serial biopsies of vincristine-treated CTVTs and found that regression occurs in sequential steps; activation of the innate immune system and host epithelial tissue remodeling followed by immune infiltration of the tumor, arrest in the cell cycle, and repair of tissue damage. We identified CCL5 as a possible driver of CTVT regression. Changes in gene expression are associated with methylation changes at specific intragenic sites. Our results underscore the critical role of host innate immunity in triggering cancer regression.

Molecular dissection of colorectal cancer in pre-clinical models identifies biomarkers predicting sensitivity to EGFR inhibitors.

Colorectal carcinoma represents a heterogeneous entity, with only a fraction of the tumours responding to available therapies, requiring a better molecular understanding of the disease in precision oncology. To address this challenge, the OncoTrack consortium recruited 106 CRC patients (stages I-IV) and developed a pre-clinical platform generating a compendium of drug sensitivity data totalling >4,000 assays testing 16 clinical drugs on patient-derived in vivo and in vitro models. This large biobank of 106 tumours, 35 organoids and 59 xenografts, with extensive omics data comparing donor tumours and derived models provides a resource for advancing our understanding of CRC. Models recapitulate many of the genetic and transcriptomic features of the donors, but defined less complex molecular sub-groups because of the loss of human stroma. Linking molecular profiles with drug sensitivity patterns identifies novel biomarkers, including a signature outperforming RAS/RAF mutations in predicting sensitivity to the EGFR inhibitor cetuximab.

Nano-MeDIP-seq Methylome Analysis Using Low DNA Concentrations.

DNA methylation is an epigenetic mark that is indispensable for mammalian development and occurs at cytosine residues throughout the genome (the "methylome"). Approximately 70 % of all CpG dinucleotides are affected by DNA methylation, which serve to "lock in" chromatin states and thus transcriptional programs. The systemic and pervasive occurrence of DNA methylation throughout the genome defines cellular identity and therefore requires genome-wide assays to fully appreciate and discern differential patterns of methylation that influence aspects of phenotypic plasticity including susceptibility to common complex disease.One method that permits methylome analysis is methylated DNA immunoprecipitation (MeDIP) combined with next-generation sequencing (MeDIP-seq). MeDIP uses an antibody raised against 5-methylcytosine to capture methylated fragments of DNA, which are subsequently sequenced to envisage the methylome landscape. The advantageous cost versus coverage balance of MeDIP-seq has made it the method of choice to replace or complement array-based methods for population epigenetic studies. Here we detail nano-MeDIP-seq, which allows methylome analysis using nanogram quantities of starting material.

eFORGE: A Tool for Identifying Cell Type-Specific Signal in Epigenomic Data.

Epigenome-wide association studies (EWAS) provide an alternative approach for studying human disease through consideration of non-genetic variants such as altered DNA methylation. To advance the complex interpretation of EWAS, we developed eFORGE (http://eforge.cs.ucl.ac.uk/), a new standalone and web-based tool for the analysis and interpretation of EWAS data. eFORGE determines the cell type-specific regulatory component of a set of EWAS-identified differentially methylated positions. This is achieved by detecting enrichment of overlap with DNase I hypersensitive sites across 454 samples (tissues, primary cell types, and cell lines) from the ENCODE, Roadmap Epigenomics, and BLUEPRINT projects. Application of eFORGE to 20 publicly available EWAS datasets identified disease-relevant cell types for several common diseases, a stem cell-like signature in cancer, and demonstrated the ability to detect cell-composition effects for EWAS performed on heterogeneous tissues. Our approach bridges the gap between large-scale epigenomics data and EWAS-derived target selection to yield insight into disease etiology.

Non-CG DNA methylation is a biomarker for assessing endodermal differentiation capacity in pluripotent stem cells.

Non-CG methylation is an unexplored epigenetic hallmark of pluripotent stem cells. Here we report that a reduction in non-CG methylation is associated with impaired differentiation capacity into endodermal lineages. Genome-wide analysis of 2,670 non-CG sites in a discovery cohort of 25 phenotyped human induced pluripotent stem cell (hiPSC) lines revealed unidirectional loss (Δß=13%, P<7.4 × 10(-4)) of non-CG methylation that correctly identifies endodermal differentiation capacity in 23 out of 25 (92%) hiPSC lines. Translation into a simplified assay of only nine non-CG sites maintains predictive power in the discovery cohort (Δß=23%, P<9.1 × 10(-6)) and correctly identifies endodermal differentiation capacity in nine out of ten pluripotent stem cell lines in an independent replication cohort consisting of hiPSCs reprogrammed from different cell types and different delivery systems, as well as human embryonic stem cell (hESC) lines. This finding infers non-CG methylation at these sites as a biomarker when assessing endodermal differentiation capacity as a readout.

Comparative methylome analysis identifies new tumour subtypes and biomarkers for transformation of nephrogenic rests into Wilms tumour.

BACKGROUND: Wilms tumours (WTs) are characterised by several hallmarks that suggest epimutations such as aberrant DNA methylation are involved in tumour progression: loss of imprinting at 11p15, lack of recurrent mutations and formation of nephrogenic rests (NRs), which are lesions of retained undifferentiated embryonic tissue that can give rise to WTs. METHODS: To identify such epimutations, we performed a comprehensive methylome analysis on 20 matched trios of micro-dissected WTs, NRs and surrounding normal kidneys (NKs) using Illumina Infinium HumanMethylation450 Bead Chips and functionally validated findings using RNA sequencing. RESULTS: Comparison of NRs with NK revealed prominent tissue biomarkers: 629 differentially methylated regions, of which 55% were hypermethylated and enriched for domains that are bivalent in embryonic stem cells and for genes expressed during development (P = 2.49 × 10(-5)). Comparison of WTs with NRs revealed two WT subgroups; group-2 WTs and NRs were epigenetically indistinguishable whereas group-1 WTs showed an increase in methylation variability, hypomethylation of renal development genes, hypermethylation and relative loss of expression of cell adhesion genes and known and potential new WT tumour suppressor genes (CASP8, H19, MIR195, RB1 and TSPAN32) and was strongly associated with bilateral disease (P = 0.032). Comparison of WTs and NRs to embryonic kidney highlighted the significance of polycomb target methylation in Wilms tumourigenesis. CONCLUSIONS: Methylation levels vary during cancer evolution. We have described biomarkers related to WT evolution from its precursor NRs which may be useful to differentiate between these tissues for patients with bilateral disease.

Probe Lasso: a novel method to rope in differentially methylated regions with 450K DNA methylation data.

The speed and resolution at which we can scour the genome for DNA methylation changes has improved immeasurably in the last 10years and the advent of the Illumina 450K BeadChip has made epigenome-wide association studies (EWAS) a reality. The resulting datasets are conveniently formatted to allow easy alignment of significant hits to genes and genetic features, however; methods that parse significant hits into discreet differentially methylated regions (DMRs) remain a challenge to implement. In this paper we present details of a novel DMR caller, the Probe Lasso: a flexible window based approach that gathers neighbouring significant-signals to define clear DMR boundaries for subsequent in-depth analysis. The method is implemented in the R package ChAMP (Morris et al., 2014) and returns sets of DMRs according to user-tuned levels of probe filtering (e.g., inclusion of sex chromosomes, polymorphisms) and probe-lasso size distribution. Using a sub-sample of colon cancer- and healthy colon-samples from TCGA we show that Probe Lasso shifts DMR calling away from just probe-dense regions, and calls a range of DMR sizes ranging from tens-of-bases to tens-of-kilobases in scale. Moreover, using TCGA data we show that Probe Lasso leverages more information from the array and highlights a potential role of hypomethylated transcription factor binding motifs not discoverable using a basic, fixed-window approach.

Methylome analysis identifies a Wilms tumor epigenetic biomarker detectable in blood.

BACKGROUND: Wilms tumor is the most common pediatric renal malignancy and there is a clinical need for a molecular biomarker to assess treatment response and predict relapse. The known mutated genes in this tumor type show low mutation frequencies, whereas aberrant methylation at 11p15 is by far the most common aberration. We therefore analyzed the epigenome, rather than the genome, to identify ubiquitous tumor-specific biomarkers. RESULTS: Methylome analysis of matched normal kidney and Wilms tumor identifies 309 preliminary methylation variable positions which we translate into three differentially methylated regions (DMR) for use as tumor-specific biomarkers. Using two novel algorithms we show that these three DMRs are not confounded by cell type composition. We further show that these DMRs are not methylated in embryonic blastema but are intermediately methylated in Wilms tumor precursor lesions. We validate the biomarker DMRs using two independent sample sets of normal kidney and Wilms tumor and seven Wilms tumor histological subtypes, achieving 100% and 98% correct classification, respectively. As proof-of-principle for clinical utility, we successfully use biomarker DMR-2 in a pilot analysis of cell-free circulating DNA to monitor tumor response during treatment in ten patients. CONCLUSIONS: These findings define the most common methylated regions in Wilms tumor known to date which are not associated with their embryonic origin or precursor stage. We show that this tumor-specific methylated DNA is released into the blood circulation where it can be detected non-invasively showing potential for clinical utility.

Genome-wide age-related changes in DNA methylation and gene expression in human PBMCs.

Aging is a progressive process that results in the accumulation of intra- and extracellular alterations that in turn contribute to a reduction in health. Age-related changes in DNA methylation have been reported before and may be responsible for aging-induced changes in gene expression, although a causal relationship has yet to be shown. Using genome-wide assays, we analyzed age-induced changes in DNA methylation and their effect on gene expression with and without transient induction with the synthetic transcription modulating agent WY14,643. To demonstrate feasibility of the approach, we isolated peripheral blood mononucleated cells (PBMCs) from five young and five old healthy male volunteers and cultured them with or without WY14,643. Infinium 450K BeadChip and Affymetrix Human Gene 1.1 ST expression array analysis revealed significant differential methylation of at least 5 % (ΔYO > 5 %) at 10,625 CpG sites between young and old subjects, but only a subset of the associated genes were also differentially expressed. Age-related differential methylation of previously reported epigenetic biomarkers of aging including ELOVL2, FHL2, PENK, and KLF14 was confirmed in our study, but these genes did not display an age-related change in gene expression in PBMCs. Bioinformatic analysis revealed that differentially methylated genes that lack an age-related expression change predominantly represent genes involved in carcinogenesis and developmental processes, and expression of most of these genes were silenced in PBMCs. No changes in DNA methylation were found in genes displaying transiently induced changes in gene expression. In conclusion, aging-induced differential methylation often targets developmental genes and occurs mostly without change in gene expression.

Human-specific epigenetic variation in the immunological Leukotriene B4 Receptor (LTB4R/BLT1) implicated in common inflammatory diseases.

BACKGROUND: Common human diseases are caused by the complex interplay of genetic susceptibility as well as environmental factors. Due to the environment's influence on the epigenome, and therefore genome function, as well as conversely the genome's facilitative effect on the epigenome, analysis of this level of regulation may increase our knowledge of disease pathogenesis. METHODS: In order to identify human-specific epigenetic influences, we have performed a novel genome-wide DNA methylation analysis comparing human, chimpanzee and rhesus macaque. RESULTS: We have identified that the immunological Leukotriene B4 receptor (LTB4R, BLT1 receptor) is the most epigenetically divergent human gene in peripheral blood in comparison with other primates. This difference is due to the co-ordinated active state of human-specific hypomethylation in the promoter and human-specific increased gene body methylation. This gene is significant in innate immunity and the LTB4/LTB4R pathway is involved in the pathogenesis of the spectrum of human inflammatory diseases. This finding was confirmed by additional neutrophil-only DNA methylome and lymphoblastoid H3K4me3 chromatin comparative data. Additionally we show through functional analysis that this receptor has increased expression and a higher response to the LTB4 ligand in human versus rhesus macaque peripheral blood mononuclear cells. Genome-wide we also find human species-specific differentially methylated regions (human s-DMRs) are more prevalent in CpG island shores than within the islands themselves, and within the latter are associated with the CTCF motif. CONCLUSIONS: This result further emphasises the exclusive nature of the human immunological system, its divergent adaptation even from very closely related primates, and the power of comparative epigenomics to identify and understand human uniqueness.

Assessment of RainDrop BS-seq as a method for large-scale, targeted bisulfite sequencing.

We present a systematic assessment of RainDrop BS-seq, a novel method for large-scale, targeted bisulfite sequencing using microdroplet-based PCR amplification coupled with next-generation sequencing. We compared DNA methylation levels at 498 target loci (1001 PCR amplicons) in human whole blood, osteosarcoma cells and an archived tumor tissue sample. We assessed the ability of RainDrop BS-seq to accurately measure DNA methylation over a range of DNA quantities (from 10 to 1500 ng), both with and without whole-genome amplification (WGA) following bisulfite conversion. DNA methylation profiles generated using at least 100 ng correlated well (median R = 0.92) with those generated on Illumina Infinium HumanMethylation450 BeadChips, currently the platform of choice for epigenome-wide association studies (EWAS). WGA allowed for testing of samples with a starting DNA amount of 10 and 50 ng, although a reduced correlation was observed (median R = 0.79). We conclude that RainDrop BS-seq is suitable for measuring DNA methylation levels using nanogram quantities of DNA, and can be used to study candidate epigenetic biomarker loci in an accurate and high-throughput manner, paving the way for its application to routine clinical diagnostics.

ChAMP: 450k Chip Analysis Methylation Pipeline.

UNLABELLED: The Illumina Infinium HumanMethylation450 BeadChip is a new platform for high-throughput DNA methylation analysis. Several methods for normalization and processing of these data have been published recently. Here we present an integrated analysis pipeline offering a choice of the most popular normalization methods while also introducing new methods for calling differentially methylated regions and detecting copy number aberrations. AVAILABILITY AND IMPLEMENTATION: ChAMP is implemented as a Bioconductor package in R. The package and the vignette can be downloaded at bioconductor.org

Assessment of patient-derived tumour xenografts (PDXs) as a discovery tool for cancer epigenomics.

BACKGROUND: The use of tumour xenografts is a well-established research tool in cancer genomics but has not yet been comprehensively evaluated for cancer epigenomics. METHODS: In this study, we assessed the suitability of patient-derived tumour xenografts (PDXs) for methylome analysis using Infinium 450 K Beadchips and MeDIP-seq. RESULTS: Controlled for confounding host (mouse) sequences, comparison of primary PDXs and matching patient tumours in a rare (osteosarcoma) and common (colon) cancer revealed that an average 2.7% of the assayed CpG sites undergo major (Δß ≥ 0.51) methylation changes in a cancer-specific manner as a result of the xenografting procedure. No significant subsequent methylation changes were observed after a second round of xenografting between primary and secondary PDXs. Based on computational simulation using publically available methylation data, we additionally show that future studies comparing two groups of PDXs should use 15 or more samples in each group to minimise the impact of xenografting-associated changes in methylation on comparison results. CONCLUSIONS: Our results from rare and common cancers indicate that PDXs are a suitable discovery tool for cancer epigenomics and we provide guidance on how to overcome the observed limitations.

Integrated virus-host methylome analysis in head and neck squamous cell carcinoma.

One in six cancers worldwide is caused by infection and human papillomavirus (HPV) is one of the main culprits. To better understand the dynamics of HPV integration and its effect on both the viral and host methylomes, we conducted whole-genome DNA methylation analysis using MeDIP-seq of HPV+ and HPV- head and neck squamous cell carcinoma (HNSCC). We determined the viral subtype to be HPV-16 in all cases and show that HPV-16 integrates into the host genome at multiple random sites and that this process predominantly involves the transcriptional repressor gene (E2) in the viral genome. Comparative analysis identified 453 (FDR ≤ 0.01) differentially methylated regions (DMRs) in the HPV+ host methylome. Bioinformatics characterization of these DMRs confirmed the previously reported cadherin genes to be affected but also revealed new targets for HPV-mediated methylation changes at regions not covered by array-based platforms, including the recently identified super-enhancers.

Human-specific CpG "beacons" identify loci associated with human-specific traits and disease.

Regulatory change has long been hypothesized to drive the delineation of the human phenotype from other closely related primates. Here we provide evidence that CpG dinucleotides play a special role in this process. CpGs enable epigenome variability via DNA methylation, and this epigenetic mark functions as a regulatory mechanism. Therefore, species-specific CpGs may influence species-specific regulation. We report non-polymorphic species-specific CpG dinucleotides (termed "CpG beacons") as a distinct genomic feature associated with CpG island (CGI) evolution, human traits and disease. Using an inter-primate comparison, we identified 21 extreme CpG beacon clusters (≥ 20/kb peaks, empirical p < 1.0 × 10(-3)) in humans, which include associations with four monogenic developmental and neurological disease related genes (Benjamini-Hochberg corrected p = 6.03 × 10(-3)). We also demonstrate that beacon-mediated CpG density gain in CGIs correlates with reduced methylation in these species in orthologous CGIs over time, via human, chimpanzee and macaque MeDIP-seq. Therefore mapping into both the genomic and epigenomic space the identified CpG beacon clusters define points of intersection where a substantial two-way interaction between genetic sequence and epigenetic state has occurred. Taken together, our data support a model for CpG beacons to contribute to CGI evolution from genesis to tissue-specific to constitutively active CGIs.

Methylome analysis using MeDIP-seq with low DNA concentrations.

DNA methylation is an epigenetic mark that has a crucial role in many biological processes. To understand the functional consequences of DNA methylation on phenotypic plasticity, a genome-wide analysis should be embraced. This in turn requires a technique that balances accuracy, genome coverage, resolution and cost, yet is low in DNA input in order to minimize the drain on precious samples. Methylated DNA immunoprecipitation-sequencing (MeDIP-seq) fulfils these criteria, combining MeDIP with massively parallel DNA sequencing. Here we report an improved protocol using 100-fold less genomic DNA than that commonly used. We show comparable results for specificity (>97%) and enrichment (>100-fold) over a wide range of DNA concentrations (5,000-50 ng) and demonstrate the utility of the protocol for the generation of methylomes from rare bone marrow cells using 160-300 ng of starting DNA. The protocol described here, i.e., DNA extraction to generation of MeDIP-seq library, can be completed within 3-5 d.

Whole genome DNA methylation analysis based on high throughput sequencing technology.

There are numerous approaches to decipher a whole genome DNA methylation profile ("methylome"), each varying in cost, throughput and resolution. The gold standard of these methods, whole genome bisulfite-sequencing (BS-seq), involves treatment of DNA with sodium bisulfite combined with subsequent high throughput sequencing. Using BS-seq, we generated a single-base-resolution methylome in human peripheral blood mononuclear cells (in press). This BS-seq map was then used as the reference methylome to compare two alternative sequencing-based methylome assays (performed on the same donor of PBMCs): methylated DNA immunoprecipitation (MeDIP-seq) and methyl-binding protein (MBD-seq). In our analysis, we found that MeDIP-seq and MBD-seq are complementary strategies, with MeDIP-seq more sensitive to highly methylated, high-CpG densities and MDB-seq more sensitive to highly methylated, moderate-CpG densities. Taking into account the size of a mammalian genome and the current expense of sequencing, we feel 3gigabases (Gbp) 45bp paired-end MeDIP-seq or MBD-seq uniquely mapped reads is the minimum requirement and cost-effective strategy for methylome pattern analysis.

AutoMeDIP-seq: a high-throughput, whole genome, DNA methylation assay.

DNA methylation is an epigenetic mark linking DNA sequence and transcription regulation, and therefore plays an important role in phenotypic plasticity. The ideal whole genome methylation (methylome) assay should be accurate, affordable, high-throughput and agnostic with respect to genomic features. To this end, the methylated DNA immunoprecipitation (MeDIP) assay provides a good balance of these criteria. In this Methods paper, we present AutoMeDIP-seq, a technique that combines an automated MeDIP protocol with library preparation steps for subsequent second-generation sequencing. We assessed recovery of DNA sequences covering a range of CpG densities using in vitro methylated λ-DNA fragments (and their unmethylated counterparts) spiked-in against a background of human genomic DNA. We show that AutoMeDIP is more reliable than manual protocols, shows a linear recovery profile of fragments related to CpG density (R(2)=0.86), and that it is highly specific (>99%). AutoMeDIP-seq offers a competitive approach to high-throughput methylome analysis of medium to large cohorts.

A three-stage genome-wide association study of general cognitive ability: hunting the small effects.

Childhood general cognitive ability (g) is important for a wide range of outcomes in later life, from school achievement to occupational success and life expectancy. Large-scale association studies will be essential in the quest to identify variants that make up the substantial genetic component implicated by quantitative genetic studies. We conducted a three-stage genome-wide association study for general cognitive ability using over 350,000 single nucleotide polymorphisms (SNPs) in the quantitative extremes of a population sample of 7,900 7-year-old children from the UK Twins Early Development Study. Using two DNA pooling stages to enrich true positives, each of around 1,000 children selected from the extremes of the distribution, and a third individual genotyping stage of over 3,000 children to test for quantitative associations across the normal range, we aimed to home in on genes of small effect. Genome-wide results suggested that our approach was successful in enriching true associations and 28 SNPs were taken forward to individual genotyping in an unselected population sample. However, although we found an enrichment of low P values and identified nine SNPs nominally associated with g (P < 0.05) that show interesting characteristics for follow-up, further replication will be necessary to meet rigorous standards of association. These replications may take advantage of SNP sets to overcome limitations of statistical power. Despite our large sample size and three-stage design, the genes associated with childhood g remain tantalizingly beyond our current reach, providing further evidence for the small effect sizes of individual loci. Larger samples, denser arrays and multiple replications will be necessary in the hunt for the genetic variants that influence human cognitive ability.

A genome-wide association study of social and non-social autistic-like traits in the general population using pooled DNA, 500 K SNP microarrays and both community and diagnosed autism replication samples.

Two separate genome-wide association studies were conducted to identify single nucleotide polymorphisms (SNPs) associated with social and nonsocial autistic-like traits. We predicted that we would find SNPs associated with social and non-social autistic-like traits and that different SNPs would be associated with social and nonsocial. In Stage 1, each study screened for allele frequency differences in approximately 430,000 autosomal SNPs using pooled DNA on microarrays in high-scoring versus low-scoring boys from a general population sample (N = approximately 400/group). In Stage 2, 22 and 20 SNPs in the social and non-social studies, respectively, were tested for QTL association by individually genotyping an independent community sample of 1,400 boys. One SNP (rs11894053) was nominally associated (P < .05, uncorrected for multiple testing) with social autistic-like traits. When the sample was increased by adding females, 2 additional SNPs were nominally significant (P < .05). These 3 SNPs, however, showed no significant association in transmission disequilibrium analyses of diagnosed ASD families.