Identification of DNA methylation biomarkers from Infinium arrays

Homeobox and Polycomb target gene methylation in human solid tumors

DNA methylation is an epigenetic mark that plays an important role in defining cancer phenotypes, with global hypomethylation and focal hypermethylation at CpG islands observed in tumors. These methylation marks can also be used to define tumor types and provide an avenue for biomarker identification. The homeobox gene class is one that has potential for this use, as well as other genes that are Polycomb Repressive Complex 2 targets. To begin to unravel this relationship, we performed a pan-cancer DNA methylation analysis using sixteen Illumina HM450k array datasets from TCGA, delving into cancer-specific qualities and commonalities between tumor types with a focus on homeobox genes. Our comparisons of tumor to normal samples suggest that homeobox genes commonly harbor significant hypermethylated differentially methylated regions. We identified two homeobox genes, HOXA3 and HOXD10, that are hypermethylated in all 16 cancer types. Furthermore, we identified several potential homeobox gene biomarkers from our analysis that are uniquely methylated in only one tumor type and that could be used as screening tools in the future. Overall, our study demonstrates unique patterns of DNA methylation in multiple tumor types and expands on the interplay between the homeobox gene class and oncogenesis.

Whole-genome methylation profiling reveals regions associated with painful temporomandibular disorders and active recovery processes

ABSTRACT

Temporomandibular disorders (TMDs), collectively representing one of the most common chronic pain conditions, have a substantial genetic component, but genetic variation alone has not fully explained the heritability of TMD risk. Reasoning that the unexplained heritability may be because of DNA methylation, an epigenetic phenomenon, we measured genome-wide DNA methylation using the Illumina MethylationEPIC platform with blood samples from participants in the Orofacial Pain: Prospective Evaluation and Risk Assessment (OPPERA) study. Associations with chronic TMD used methylation data from 496 chronic painful TMD cases and 452 TMD-free controls. Changes in methylation between enrollment and a 6-month follow-up visit were determined for a separate sample of 62 people with recent-onset painful TMD. More than 750,000 individual CpG sites were examined for association with chronic painful TMD. Six differentially methylated regions were significantly ( P < 5 × 10 -8 ) associated with chronic painful TMD, including loci near genes involved in the regulation of inflammatory and neuronal response. A majority of loci were similarly differentially methylated in acute TMD consistent with observed transience or persistence of symptoms at follow-up. Functional characterization of the identified regions found relationships between methylation at these loci and nearby genetic variation contributing to chronic painful TMD and with gene expression of proximal genes. These findings reveal epigenetic contributions to chronic painful TMD through methylation of the genes FMOD , PM20D1 , ZNF718 , ZFP57 , and RNF39 , following the development of acute painful TMD. Epigenetic regulation of these genes likely contributes to the trajectory of transcriptional events in affected tissues leading to resolution or chronicity of pain.

Sex-specific DNA methylation in saliva from the multi-ethnic Future of Families and Child Wellbeing Study

The prevalence and severity of many diseases differs by sex, potentially due to sex-specific patterns in DNA methylation. Autosomal sex-specific differences in DNA methylation have been observed in cord blood and placental tissue but are not well studied in saliva or in diverse populations. We sought to characterize sex-specific DNA methylation on autosomal chromosomes in saliva samples from children in the Future of Families and Child Wellbeing Study, a multi-ethnic prospective birth cohort containing an oversampling of Black, Hispanic and low-income families. DNA methylation from saliva samples was analysed on 796 children (50.6% male) at both ages 9 and 15 with DNA methylation measured using the Illumina HumanMethylation 450k array. An epigenome-wide association analysis of the age 9 samples identified 8,430 sex-differentiated autosomal DNA methylation sites (P < 2.4 × 10-7), of which 76.2% had higher DNA methylation in female children. The strongest sex-difference was in the cg26921482 probe, in the AMDHD2 gene, with 30.6% higher DNA methylation in female compared to male children (P < 1 × 10-300). Treating the age 15 samples as an internal replication set, we observed highly consistent results between the ages 9 and 15 measurements, indicating stable and replicable sex-differentiation. Further, we directly compared our results to previously published DNA methylation sex differences in both cord blood and saliva and again found strong consistency. Our findings support widespread and robust sex-differential DNA methylation across age, human tissues, and populations. These findings help inform our understanding of potential biological processes contributing to sex differences in human physiology and disease.

Beadchip technology to detect DNA methylation in mouse faithfully recapitulates whole-genome bisulfite sequencing

Aim: To facilitate wide-scale implementation of Illumina Mouse Methylation BeadChip (MMB) technology, array-based measurement of cytosine methylation was compared with the gold-standard assessment of DNA methylation by whole-genome bisulfite sequencing (WGBS). Methods: DNA methylation across two mouse strains (C57B6 and C3H) and both sexes was assessed using the MMB and compared with previously existing deep-coverage WGBS of mice of the same strain and sex. Results & conclusion: The findings demonstrated that 93.3-99.2% of sites had similar measurements of methylation across technologies and that differentially methylated cytosines and regions identified by each technology overlap and enrich for similar biological functions, suggesting that the MMB faithfully recapitulates the findings of WGBS.

In silico study of cancer stage-specific DNA methylation pattern in White breast cancer patients based on TCGA dataset

BACKGROUND

Breast cancer is one of the most common types of cancer among women. As current breast cancer treatments are still ineffective, we assess the methylation pattern of White breast cancer patients across cancer stage based on The Cancer Genome Atlas (TCGA) dataset. Significant hypermethylation and hypomethylation can regulate the gene expression, thus becoming potential biomarkers in breast cancer tumorigenesis.

METHODS

DNA methylation data was downloaded using TCGA Assembler 2 based on race-specific metadata of TCGA - Breast Invasive Carcinoma (TCGA-BRCA) project from Genomic Data Commons (GDC) Data Portal. After the data was divided into each cancer stage, duplicated data of each patient was removed using OMICSBind, while differentially-expressed probes were identified using edgeR. The resulting probes were validated based on correlation and regression analysis with the gene expression, ANOVA between cancer stages, ROC curve per stage, as well as databases.

RESULTS

Based on the White dataset, we found 66 significant hypermethylated genes with logFC > 1.8 between Stage I-III. From this number, three epigenetic-regulated, stage-specific genes are proposed to be the detection biomarkers of breast cancer due to significant aberrant gene expression and/or low mutation ratio among breast cancer patients: ABCC9 (Stage III), SHISA3 (Stage II), and POU4F1 (Stage I-II).

CONCLUSIONS

Our study shows that ABCC9, SHISA3, and POU4F1 are potential stage-specific detection biomarkers of breast cancer for White individuals, whereas their roles in other races need to be studied further.

Discrimination between human populations using a small number of differentially methylated CpG sites: a preliminary study using lymphoblastoid cell lines and peripheral blood samples of European and Chinese origin

Background

Epigenetics is one of the factors shaping natural variability observed among human populations. A small proportion of heritable inter-population differences are observed in the context of both the genome-wide methylation level and the methylation status of individual CpG sites. It has been demonstrated that a limited number of carefully selected differentially methylated sites may allow discrimination between main human populations. However, most of the few published results have been performed exclusively on B-lymphocyte cell lines.

Results

The goal of our study was to identify a set of CpG sites sufficient to discriminate between populations of European and Chinese ancestry based on the difference in the DNA methylation profile not only in cell lines but also in primary cell samples. The preliminary selection of CpG sites differentially methylated in these two populations (pop-CpGs) was based on the analysis of two groups of commercially available ethnically-specific B-lymphocyte cell lines, performed using Illumina Infinium Human Methylation 450 BeadChip Array. A subset of 10 pop-CpGs characterized by the best differentiating criteria (|Mdiff| > 1, q < 0.05; lack of the confounding genomic features), and 10 additional CpGs in their immediate vicinity, were further tested using pyrosequencing technology in both B-lymphocyte cell lines and in the primary samples of the peripheral blood representing two analyzed populations. To assess the population-discriminating potential of the selected set of CpGs (further referred to as “composite pop (CEU-CHB)-CpG marker”), three classification methods were applied. The predictive ability of the composite 8-site pop (CEU-CHB)-CpG marker was assessed using 10-fold cross-validation method on two independent sets of samples.

Conclusions

Our results showed that less than 10 pop-CpG sites may distinguish populations of European and Chinese ancestry; importantly, this small composite pop-CpG marker performs well in both lymphoblastoid cell lines and in non-homogenous blood samples regardless of a gender.

Bioinformatics Tools and Resources for Cancer Immunotherapy Study

In recent years, cancer immunotherapy has emerged as a highly promising approach to treat patients with cancer, as the patient's own immune system is harnessed to attack cancer cells. However, the application of these approaches is still limited to a minority of patients with cancer and it is difficult to predict which patients will derive the greatest clinical benefit.One of the challenges faced by the biomedical community in the search of more effective biomarkers is the fact that translational research efforts involve collecting and accessing data at many different levels: from the type of material examined (e.g., cell line, animal models, clinical samples) to multiple data type (e.g., pharmacodynamic markers, genetic sequencing data) to the scale of a study (e.g., small preclinical study, moderate retrospective study on stored specimen sets, clinical trials with large cohorts).This chapter reviews several publicly available bioinformatics tools and data resources for high throughput molecular analyses applied to a range of data types, including those generated from microarray, whole-exome sequencing (WES), RNA-seq, DNA copy number, and DNA methylation assays, that are extensively used for integrative multidimensional data analysis and visualization.

DNA epigenetic signature predictive of benefit from neoadjuvant chemotherapy in oesophageal adenocarcinoma: results from the MRC OE02 trial

BACKGROUND

DNA methylation signatures describing distinct histological subtypes of oesophageal cancer have been reported. We studied DNA methylation in samples from the MRC OE02 phase III trial, which randomised patients with resectable oesophageal cancer to surgery alone (S) or neoadjuvant chemotherapy followed by surgery (CS).

AIM

The aim of the study was to identify epigenetic signatures predictive of chemotherapy benefit in patients with oesophageal adenocarcinoma (OAC) from the OE02 trial and validate the findings in an independent cohort.

METHODS

DNA methylation was analysed using the Illumina GoldenGate platform on surgically resected OAC specimens from patients in the OE02 trial. Cox proportional hazard analysis was performed to select probes predictive of survival in the CS arm. Non-negative matrix factorisation was used to perform clustering and delineate DNA methylation signatures. The findings were validated in an independent cohort of patients with gastroesophageal adenocarcinoma treated with neoadjuvant chemotherapy.

RESULTS

A total of 229 patients with OAC were analysed from the OE02 trial (118 in the CS arm and 111 in the S arm). There was no difference in DNA methylation status between the CS and S arms. A metagene signature was created by dichotomising samples into two clusters. In cluster 1, patients in the CS arm had significant overall survival (OS) benefit (median OS CS: 931 days vs. S: 536 days [HR: 1.54, P = 0.031]). In cluster 2, patients in the CS arm had similar (or worse) OS compared with patients in the S arm (CS: 348 days vs. S: 472 days [HR: 0.70, P = 0.1], and test of interaction was significant (p = 0.005). In the validation cohort (n = 13), there was no difference in DNA methylation status in paired pre- and post-treatment samples. When the epigenetic signature was applied, cluster 1 samples had better OS (median OS, cluster 1: 1174 days vs. cluster 2: 392 days, HR: 3.47, p = 0.059) CONCLUSIONS: This is the first and largest study of DNA methylation in patients with OAC uniformly treated in a randomised phase III trial. We identified an epigenetic signature that may serve as a predictive biomarker for chemotherapy benefit in OAC.

First evidence of association between past environmental exposure to dioxin and DNA methylation of CYP1A1 and IGF2 genes in present day Vietnamese population

During the Vietnam War, the United States military sprayed over 74 million litres of Agent Orange (AO) to destroy forest cover as a counterinsurgency tactic in Vietnam, Laos and Cambodia. The main ingredient was contaminated by 2,3,7,8-tetrachlorodibenzo-paradioxin (TCDD). DNA methylation (DNAm) differences are potential biomarker of environmental toxicants exposure. The aim of this study was to perform a preliminary investigation of the DNAm levels from peripheral blood of the present-day Vietnamese population, including individuals whose parents, according to historical data, were exposed to AO/TCDD during the war. 94 individuals from heavily sprayed areas (cases) and 94 individuals from non-sprayed areas (controls) were studied, and historical data on alleged exposure of parents collected. 94 cases were analysed considering those whose father/parents participated in the war (N = 29) and considering the place of residence of both parents (64 living in sprayed areas versus 30 in non-contaminated areas). DNAm levels in CYP1A1 and IGF2 genes were measured (MALDI-TOF technology). The analyses showed that: 1) one CpG site in the CYP1A1 and one in the IGF2 gene showed significant differences in DNAm levels between cases and controls; 2) the CYP1A1 region resulted to be hypomethylated (in 9 out of 16 sites/units; p-val<0.01) in 29 individuals whose father/parents participated in the war in the spray zones; 3) we showed that the place of residence of both parents influenced methylation levels of the CYP1A1 and IGF2 genes (p-val<0.05). In conclusion this study indicates that past environmental exposure to dioxin (AO/TCDD) shapes the DNAm profile of CYP1A1 and that the place of living for parents in former spray zones influences DNAm of CYP1A1 and IGF2 genes. These results open the way to new applications of DNAm as potential biomarker(s) of past human exposure to dioxin.

Differences in DNA methylation profiles by histologic subtype of paediatric germ cell tumours: a report from the Children's Oncology Group

Background

Abnormal DNA methylation may be important in germ cell tumour (GCT) aetiology, as germ cells undergo complete epigenetic reprogramming during development. GCTs show differences in global and promoter methylation patterns by histologic subtype. We conducted an epigenome-wide study to identify methylation differences by GCT histology.

Methods

Using the Illumina HumanMethylation450K array we measured methylation in 154 paediatric GCTs (21 germinomas/seminomas/dysgerminoma, 70 yolk sac tumours [YST], 9 teratomas, and 54 mixed histology tumours). We identified differentially methylated regions (DMRs) between GCT histologies by comparing methylation beta values.

Results

We identified 8,481 DMRs (FWER < 0.05). Unsupervised hierarchical clustering of individual probes within DMRs resulted in four high level clusters closely corresponding to tumour histology. Clusters corresponding to age, location, sex and FFPE status were not observed within these DMRs. Germinomas displayed lower levels of methylation across the DMRs relative to the other histologic subtypes. Pathway analysis on the top 10% of genes with differential methylation in germinomas/seminomas/dysgerminoma compared to YST suggested angiogenesis and immune cell-related pathways displayed decreased methylation in germinomas/seminomas/dysgerminoma relative to YST.

Conclusions

Paediatric GCT histologies have differential methylation patterns. The genes that are differentially methylated may provide insights into GCT aetiology including the timing of GCT initiation.

EBV Associated Breast Cancer Whole Methylome Analysis Reveals Viral and Developmental Enriched Pathways

Background: Breast cancer (BC) ranks among the most common cancers in Sudan and worldwide with hefty toll on female health and human resources. Recent studies have uncovered a common BC signature characterized by low frequency of oncogenic mutations and high frequency of epigenetic silencing of major BC tumor suppressor genes. Therefore, we conducted a pilot genome-wide methylome study to characterize aberrant DNA methylation in breast cancer.

Results: Differential methylation analysis between primary tumor samples and normal samples from healthy adjacent tissues yielded 20,188 differentially methylated positions (DMPs), which is further divided into 13,633 hypermethylated sites corresponding to 5339 genes and 6,555 hypomethylated sites corresponding to 2811 genes. Moreover, bioinformatics analysis revealed epigenetic dysregulation of major developmental pathways including hippo signaling pathway. We also uncovered many clues to a possible role for EBV infection in BC.

Conclusion: Our results clearly show the utility of epigenetic assays in interrogating breast cancer tumorigenesis, and pinpointing specific developmental and viral pathways dysregulation that might serve as potential biomarkers or targets for therapeutic interventions.

Responders and non-responders to influenza vaccination: A DNA methylation approach on blood cells

Several evidences indicate that aging negatively affects the effectiveness of influenza vaccination. Although it is well established that immunosenescence has an important role in vaccination response, the molecular pathways underlying this process are largely unknown. Given the importance of epigenetic remodeling in aging, here we analyzed the relationship between responsiveness to influenza vaccination and DNA methylation profiles in healthy subjects of different ages. Peripheral blood mononuclear cells were collected from 44 subjects (age range: 19-90 years old) immediately before influenza vaccination. Subjects were subsequently classified as responders or non-responders according to hemagglutination inhibition assay 4-6 weeks after the vaccination. Baseline whole genome DNA methylation in peripheral blood mononuclear cells was analyzed using the Illumina® Infinium 450 k microarray. Differential methylation analysis between the two groups (responders and non-responders) was performed through an analysis of variance, correcting for age, sex and batch. We identified 83 CpG sites having a nominal p-value <.001 and absolute difference in DNA methylation of at least 0.05 between the two groups. For some CpG sites, we observed age-dependent decrease or increase in methylation, which in some cases was specific for the responders and non-responders groups. Finally, we divided the cohort in two subgroups including younger (age < 50) and older (age ≥ 50) subjects and compared DNA methylation between responders and non-responders, correcting for sex and batch in each subgroup. We identified 142 differentially methylated CpG sites in the young subgroup and 305 in the old subgroup, suggesting a larger epigenetic remodeling at older ages. Interestingly, some of the differentially methylated probes mapped in genes involved in immunosenescence (CD40) and in innate immunity responses (CXCL16, ULK1, BCL11B, BTC). In conclusion, the analysis of epigenetic landscape can shed light on the biological basis of vaccine responsiveness during aging, possibly providing new appropriate biomarkers of this process.

Promoter methylation of DNA damage repair (DDR) genes in human tumor entities: RBBP8/CtIP is almost exclusively methylated in bladder cancer

Background

Genome-wide studies identified pan-cancer genes and shared biological networks affected by epigenetic dysregulation among diverse tumor entities. Here, we systematically screened for hypermethylation of DNA damage repair (DDR) genes in a comprehensive candidate-approach and exemplarily identify and validate candidate DDR genes as targets of epigenetic inactivation unique to bladder cancer (BLCA), which may serve as non-invasive biomarkers.

Methods

Genome-wide DNA methylation datasets (2755 CpG probes of n = 7819 tumor and n = 659 normal samples) of the TCGA network covering 32 tumor entities were analyzed in silico for 177 DDR genes. Genes of interest were defined as differentially methylated between normal and cancerous tissues proximal to transcription start sites. The lead candidate gene was validated by methylation-specific PCR (MSP) and/or bisulfite-pyrosequencing in different human cell lines (n = 36), in primary BLCA tissues (n = 43), and in voided urine samples (n = 74) of BLCA patients. Urines from healthy donors and patients with urological benign and malignant diseases were included as controls (n = 78). mRNA expression was determined using qRT-PCR in vitro before (n = 5) and after decitabine treatment (n = 2). Protein expression was assessed by immunohistochemistry (n = 42). R 3.2.0. was used for statistical data acquisition and SPSS 21.0 for statistical analysis.

Results

Overall, 39 DDR genes were hypermethylated in human cancers. Most exclusively and frequently methylated (37%) in primary BLCA was RBBP8, encoding endonuclease CtIP. RBBP8 hypermethylation predicted longer overall survival (OS) and was found in 2/4 bladder cancer cell lines but not in any of 33 cancer cell lines from entities with another origin like prostate. RBBP8 methylation was inversely correlated with RBBP8 mRNA and nuclear protein expression while RBBP8 was re-expressed after in vitro demethylation. RBBP8 methylation was associated with histological grade in primary BLCA and urine samples. RBBP8 methylation was detectable in urine samples of bladder cancer patients achieving a sensitivity of 52%, at 91% specificity.

Conclusions

RBBP8 was identified as almost exclusively hypermethylated in BLCA. RBBP8/CtIP has a proven role in homologous recombination-mediated DNA double-strand break repair known to sensitize cancer cells for PARP1 inhibitors. Since RBBP8 methylation was detectable in urines, it may be a complementary marker of high specificity in urine for BLCA detection.

HumanMethylation450K Array-Identified Biomarkers Predict Tumour Recurrence/Progression at Initial Diagnosis of High-risk Non-muscle Invasive Bladder Cancer

Background:

High-risk non-muscle invasive bladder cancer (HR-NMIBC) is a clinically unpredictable disease. Despite clinical risk estimation tools, many patients are undertreated with intra-vesical therapies alone, whereas others may be over-treated with early radical surgery. Molecular biomarkers, particularly DNA methylation, have been reported as predictive of tumour/patient outcomes in numerous solid organ and haematologic malignancies; however, there are few reports in HR-NMIBC and none using genome-wide array assessment. We therefore sought to identify novel DNA methylation markers of HR-NMIBC clinical outcomes that might predict tumour behaviour at initial diagnosis and help guide patient management.

Patients and methods:

A total of 21 primary initial diagnosis HR-NMIBC tumours were analysed by Illumina HumanMethylation450 BeadChip arrays and subsequently bisulphite Pyrosequencing. In all, 7 had not recurred at 1 year after resection and 14 had recurred and/or progressed despite intra-vesical BCG. A further independent cohort of 32 HR-NMIBC tumours (17 no recurrence and 15 recurrence and/or progression despite BCG) were also assessed by bisulphite Pyrosequencing.

Results:

Array analyses identified 206 CpG loci that segregated non-recurrent HR-NMIBC tumours from clinically more aggressive recurrence/progression tumours. Hypermethylation of CpG cg11850659 and hypomethylation of CpG cg01149192 in combination predicted HR-NMIBC recurrence and/or progression within 1 year of diagnosis with 83% sensitivity, 79% specificity, and 83% positive and 79% negative predictive values.

Conclusions:

This is the first genome-wide DNA methylation analysis of a unique HR-NMIBC tumour cohort encompassing known 1-year clinical outcomes. Our analyses identified potential novel epigenetic markers that could help guide individual patient management in this clinically unpredictable disease.

Whole genome DNA methylation profiling of oral cancer in ethnic population of Meghalaya, North East India reveals novel genes

Oral Squamous Cell Carcinoma (OSCC) is a serious and one of the most common and highly aggressive malignancies. Epigenetic factors such as DNA methylation have been known to be implicated in a number of cancer etiologies. The main objective of this study was to investigate physiognomies of Promoter DNA methylation patterns associated with oral cancer epigenome with special reference to the ethnic population of Meghalaya, North East India. The present study identifies 27,205 CpG sites and 3811 regions that are differentially methylated in oral cancer when compared to matched normal. 45 genes were found to be differentially methylated within the promoter region, of which 38 were hypermethylated and 7 hypomethylated. 14 of the hypermethylated genes were found to be similar to that of the TCGA-HNSCC study some of which are TSGs and few novel genes which may serve as candidate methylation biomarkers for OSCC in this poorly characterized ethnic group.

Circulating cell-free DNA-based epigenetic assay can detect early breast cancer

Background

Circulating cell-free DNA (cfDNA) has recently been recognized as a resource for biomarkers of cancer progression, treatment response, and drug resistance. However, few have demonstrated the usefulness of cfDNA for early detection of cancer. Although aberrant DNA methylation in cfDNA has been reported for more than a decade, its diagnostic accuracy remains unsatisfactory for cancer screening. Thus, the aim of the present study was to develop a highly sensitive cfDNA-based system for detection of primary breast cancer (BC) using epigenetic biomarkers and digital PCR technology.

Methods

Array-based genome-wide DNA methylation analysis was performed using 56 microdissected breast tissue specimens, 34 cell lines, and 29 blood samples from healthy volunteers (HVs). Epigenetic markers for BC detection were selected, and a droplet digital methylation-specific PCR (ddMSP) panel with the selected markers was established. The detection model was constructed by support vector machine and evaluated using cfDNA samples.

Results

The methylation array analysis identified 12 novel epigenetic markers (JAK3, RASGRF1, CPXM1, SHF, DNM3, CAV2, HOXA10, B3GNT5, ST3GAL6, DACH1, P2RX3, and chr8:23572595) for detecting BC. We also selected four internal control markers (CREM, GLYATL3, ELMOD3, and KLF9) that were identified as infrequently altered genes using a public database. A ddMSP panel using these 16 markers was developed and detection models were constructed with a training dataset containing cfDNA samples from 80 HVs and 87 cancer patients. The best detection model adopted four methylation markers (RASGRF1, CPXM1, HOXA10, and DACH1) and two parameters (cfDNA concentration and the mean of 12 methylation markers), and, and was validated in an independent dataset of 53 HVs and 58 BC patients. The area under the receiver operating characteristic curve for cancer-normal discrimination was 0.916 and 0.876 in the training and validation dataset, respectively. The sensitivity and the specificity of the model was 0.862 (stages 0-I 0.846, IIA 0.862, IIB-III 0.818, metastatic BC 0.935) and 0.827, respectively.

Conclusion

Our epigenetic-marker-based system distinguished BC patients from HVs with high accuracy. As detection of early BC using this system was comparable with that of mammography screening, this system would be beneficial as an optional method of screening for BC.

Electronic supplementary material

The online version of this article (doi:10.1186/s13058-016-0788-z) contains supplementary material, which is available to authorized users.

Epigenetic Variability across Human Populations: A Focus on DNA Methylation Profiles of the KRTCAP3, MAD1L1 and BRSK2 Genes

Natural epigenetic diversity has been suggested as a key mechanism in microevolutionary processes due to its capability to create phenotypic variability within individuals and populations. It constitutes an important reservoir of variation potentially useful for rapid adaptation in response to environmental stimuli. The analysis of population epigenetic structure represents a possible tool to study human adaptation and to identify external factors that are able to naturally shape human DNA methylation variability. The aim of this study is to investigate the dynamics that create epigenetic diversity between and within different human groups. To this end, we first used publicly available epigenome-wide data to explore population-specific DNA methylation changes that occur at macro-geographic scales. Results from this analysis suggest that nutrients, UVA exposure and pathogens load might represent the main environmental factors able to shape DNA methylation profiles. Then, we evaluated DNA methylation of candidate genes (KRTCAP3, MAD1L1, and BRSK2), emerged from the previous analysis, in individuals belonging to different populations from Morocco, Nigeria, Philippines, China, and Italy, but living in the same Italian city. DNA methylation of the BRSK2 gene is significantly different between Moroccans and Nigerians (pairwise t-test: CpG 6 P-value = 5.2*10 (-) (3); CpG 9 P-value = 2.6*10 (-) (3); CpG 10 P-value = 3.1*10 (-) (3); CpG 11 P-value = 2.8*10 (-) (3)). Comprehensively, these results suggest that DNA methylation diversity is a source of variability in human groups at macro and microgeographical scales and that population demographic and adaptive histories, as well as the individual ancestry, actually influence DNA methylation profiles.

seqlm: an MDL based method for identifying differentially methylated regions in high density methylation array data

MOTIVATION

One of the main goals of large scale methylation studies is to detect differentially methylated loci. One way is to approach this problem sitewise, i.e. to find differentially methylated positions (DMPs). However, it has been shown that methylation is regulated in longer genomic regions. So it is more desirable to identify differentially methylated regions (DMRs) instead of DMPs. The new high coverage arrays, like Illuminas 450k platform, make it possible at a reasonable cost. Few tools exist for DMR identification from this type of data, but there is no standard approach.

RESULTS

We propose a novel method for DMR identification that detects the region boundaries according to the minimum description length (MDL) principle, essentially solving the problem of model selection. The significance of the regions is established using linear mixed models. Using both simulated and large publicly available methylation datasets, we compare seqlm performance to alternative approaches. We demonstrate that it is both more sensitive and specific than competing methods. This is achieved with minimal parameter tuning and, surprisingly, quickest running time of all the tried methods. Finally, we show that the regional differential methylation patterns identified on sparse array data are confirmed by higher resolution sequencing approaches.

AVAILABILITY AND IMPLEMENTATION

The methods have been implemented in R package seqlm that is available through Github: https://github.com/raivokolde/seqlm

CONTACT

rkolde@gmail.com

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Quantitative genome-wide methylation analysis of high-grade non-muscle invasive bladder cancer

High-grade non-muscle invasive bladder cancer (HG-NMIBC) is a clinically unpredictable disease with greater risks of recurrence and progression relative to their low-intermediate-grade counterparts. The molecular events, including those affecting the epigenome, that characterize this disease entity in the context of tumor development, recurrence, and progression, are incompletely understood. We therefore interrogated genome-wide DNA methylation using HumanMethylation450 BeadChip arrays in 21 primary HG-NMIBC tumors relative to normal bladder controls. Using strict inclusion-exclusion criteria we identified 1,057 hypermethylated CpGs within gene promoter-associated CpG islands, representing 256 genes. We validated the array data by bisulphite pyrosequencing and examined 25 array-identified candidate genes in an independent cohort of 30 HG-NMIBC and 18 low-intermediate-grade NMIBC. These analyses revealed significantly higher methylation frequencies in high-grade tumors relative to low-intermediate-grade tumors for the ATP5G2, IRX1 and VAX2 genes (P<0.05), and similarly significant increases in mean levels of methylation in high-grade tumors for the ATP5G2, VAX2, INSRR, PRDM14, VSX1, TFAP2b, PRRX1, and HIST1H4F genes (P<0.05). Although inappropriate promoter methylation was not invariantly associated with reduced transcript expression, a significant association was apparent for the ARHGEF4, PON3, STAT5a, and VAX2 gene transcripts (P<0.05). Herein, we present the first genome-wide DNA methylation analysis in a unique HG-NMIBC cohort, showing extensive and discrete methylation changes relative to normal bladder and low-intermediate-grade tumors. The genes we identified hold significant potential as targets for novel therapeutic intervention either alone, or in combination, with more conventional therapeutic options in the treatment of this clinically unpredictable disease.

Integrating genetics and epigenetics in breast cancer: biological insights, experimental, computational methods and therapeutic potential

BACKGROUND

Development of human cancer can proceed through the accumulation of different genetic changes affecting the structure and function of the genome. Combined analyses of molecular data at multiple levels, such as DNA copy-number alteration, mRNA and miRNA expression, can clarify biological functions and pathways deregulated in cancer. The integrative methods that are used to investigate these data involve different fields, including biology, bioinformatics, and statistics.

RESULTS

These methodologies are presented in this review, and their implementation in breast cancer is discussed with a focus on integration strategies. We report current applications, recent studies and interesting results leading to the identification of candidate biomarkers for diagnosis, prognosis, and therapy in breast cancer by using both individual and combined analyses.

CONCLUSION

This review presents a state of art of the role of different technologies in breast cancer based on the integration of genetics and epigenetics, and shares some issues related to the new opportunities and challenges offered by the application of such integrative approaches.

Early life lead exposure causes gender-specific changes in the DNA methylation profile of DNA extracted from dried blood spots

AIMS

In this paper, we tested the hypothesis that early life lead (Pb) exposure associated DNA methylation (5 mC) changes are dependent on the sex of the child and can serve as biomarkers for Pb exposure.

METHODS

In this pilot study, we measured the 5mC profiles of DNA extracted from dried blood spots (DBS) in a cohort of 43 children (25 males and 18 females; ages from 3 months to 5 years) from Detroit. Result & Discussion: We found that the effect of Pb-exposure on the 5-mC profiles can be separated into three subtypes: affected methylation loci which are conserved irrespective of the sex of the child (conserved); affected methylation loci unique to males (male-specific); and affected methylation loci unique to females (female-specific).

Methylation of the FGFR2 gene is associated with high birth weight centile in humans

AIMS

This study examined links between DNA methylation and birth weight centile (BWC), and explored the impact of genetic variation.

MATERIALS & METHODS

Using HumanMethylation450 arrays, we examined candidate gene-associated CpGs in cord blood from newborns with low (<15th centile), medium (40-60th centile) and high (>85th centile) BWC (n = 12). Candidates were examined in an investigation cohort (n = 110) using pyrosequencing and genotyping for putative methylation-associated polymorphisms performed using standard PCR.

RESULTS

Array analysis identified 314 candidate genes associated with BWC extremes, four of which showed ≥ 4 BWC-linked CpGs. Of these, PM20D1 and MI886 suggested genetically determined methylation levels. However, methylation at three CpGs in FGFR2 remained significantly associated with high BWC (p = 0.004-0.027).

CONCLUSION

We identified a novel biologically plausible candidate (FGFR2) for with BWC that merits further study.

A meta-analysis on age-associated changes in blood DNA methylation: results from an original analysis pipeline for Infinium 450k data

Aging is characterized by a profound remodeling of the epigenetic architecture in terms of DNA methylation patterns. To date the most effective tool to study genome wide DNA methylation changes is Infinium HumanMethylation450 BeadChip (Infinium 450k). Despite the wealth of tools for Infinium 450k analysis, the identification of the most biologically relevant DNA methylation changes is still challenging. Here we propose an analytical pipeline to select differentially methylated regions (DMRs), tailored on microarray architecture, which is highly effective in highlighting biologically relevant results. The pipeline groups microarray probes on the basis of their localization respect to CpG islands and genic sequences and, depending on probes density, identifies DMRs through a single-probe or a region-centric approach that considers the concomitant variation of multiple adjacent CpG probes. We successfully applied this analytical pipeline on 3 independent Infinium 450k datasets that investigated age-associated changes in blood DNA methylation. We provide a consensus list of genes that systematically vary in DNA methylation levels from 0 to 100 years and that have a potentially relevant role in the aging process.

DNA methylation profiling of synovial fluid FLS in rheumatoid arthritis reveals changes common with tissue-derived FLS

Aim: Alterations in DNA methylation contribute to the abnormal phenotype of fibroblast-like synoviocytes (FLS) from patients with rheumatoid arthritis (RA). We profiled genome-wide DNA methylation in these cells from synovial fluid, a more readily accessible source of disease-associated cells. Patients & methods: Genome-wide DNA methylation was interrogated in fluid-derived FLS from five RA and six osteoarthritis patients using Human Methylation 450 Bead Chip and bisulfite pyrosequencing. Results: Array analysis identified 328 CpGs, representing 195 genes, that were differentially methylated between RA and osteoarthritis fluid-derived FLS. Comparison with the genes identified in two independent studies of tissue-derived FLS revealed 73 genes in common (˜40%), of which 22 shared identity with both studies. Pyrosequencing confirmed altered methylation of these genes. Conclusion: Synovial fluid-derived RA FLS show methylation changes common with tissue-derived FLS, supporting the use of fluid-derived FLS for future investigations.

Analysis pipelines and packages for Infinium HumanMethylation450 BeadChip (450k) data

The Illumina HumanMethylation450 BeadChip has become a popular platform for interrogating DNA methylation in epigenome-wide association studies (EWAS) and related projects as well as resource efforts such as the International Cancer Genome Consortium (ICGC) and the International Human Epigenome Consortium (IHEC). This has resulted in an exponential increase of 450k data in recent years and triggered the development of numerous integrated analysis pipelines and stand-alone packages. This review will introduce and discuss the currently most popular pipelines and packages and is particularly aimed at new 450k users.

Genome-wide DNA methylation profiling in rheumatoid arthritis identifies disease-associated methylation changes that are distinct to individual T- and B-lymphocyte populations

Changes to the DNA methylome have been described in patients with rheumatoid arthritis (RA). In previous work, we reported genome-wide methylation differences in T-lymphocyte and B-lymphocyte populations from healthy individuals. Now, using HumanMethylation450 BeadChips to interrogate genome-wide DNA methylation, we have determined disease-associated methylation changes in blood-derived T- and B-lymphocyte populations from 12 female patients with seropositive established RA, relative to 12 matched healthy individuals. Array data were analyzed using NIMBL software and bisulfite pyrosequencing was used to validate array candidates. Genome-wide DNA methylation, determined by analysis of LINE-1 sequences, revealed higher methylation in B-lymphocytes compared with T-lymphocytes (P ≤ 0.01), which is consistent with our findings in healthy individuals. Moreover, loci-specific methylation differences that distinguished T-lymphocytes from B-lymphocytes in healthy individuals were also apparent in RA patients. However, disease-associated methylation differences were also identified in RA. In these cases, we identified 509 and 252 CpGs in RA-derived T- and B-lymphocytes, respectively, that showed significant changes in methylation compared with their cognate healthy counterparts. Moreover, this included a restricted set of 32 CpGs in T-lymphocytes and 20 CpGs in B-lymphocytes (representing 15 and 10 genes, respectively, and including two, MGMT and CCS, that were common to both cell types) that displayed more substantial changes in methylation. These changes, apparent as hyper- or hypo-methylation, were independently confirmed by pyrosequencing analysis. Validation by pyrosequencing also revealed additional sites in some candidate genes that also displayed altered methylation in RA. In this first study of genome-wide DNA methylation in individual T- and B-lymphocyte populations in RA patients, we report disease-associated methylation changes that are distinct to each cell type and which support a role for discrete epigenetic regulation in this disease.

Minfi: a flexible and comprehensive Bioconductor package for the analysis of Infinium DNA methylation microarrays

MOTIVATION

The recently released Infinium HumanMethylation450 array (the '450k' array) provides a high-throughput assay to quantify DNA methylation (DNAm) at ∼450 000 loci across a range of genomic features. Although less comprehensive than high-throughput sequencing-based techniques, this product is more cost-effective and promises to be the most widely used DNAm high-throughput measurement technology over the next several years.

RESULTS

Here we describe a suite of computational tools that incorporate state-of-the-art statistical techniques for the analysis of DNAm data. The software is structured to easily adapt to future versions of the technology. We include methods for preprocessing, quality assessment and detection of differentially methylated regions from the kilobase to the megabase scale. We show how our software provides a powerful and flexible development platform for future methods. We also illustrate how our methods empower the technology to make discoveries previously thought to be possible only with sequencing-based methods.

AVAILABILITY AND IMPLEMENTATION

http://bioconductor.org/packages/release/bioc/html/minfi.html.

CONTACT

khansen@jhsph.edu; rafa@jimmy.harvard.edu

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

DNA methylation as a biomarker for preeclampsia

BACKGROUND

Preeclampsia contributes significantly to pregnancy-associated morbidity and mortality as well as future risk of cardiovascular disease in mother and offspring, and preeclampsia in offspring. The lack of reliable methods for early detection limits the opportunities for prevention, diagnosis, and timely treatment.

PURPOSE

The purpose of this study was to explore distinct DNA methylation patterns associated with preeclampsia in both maternal cells and fetal-derived tissue that represent potential biomarkers to predict future preeclampsia and inheritance in children.

METHOD

A convenience sample of nulliparous women (N = 55) in the first trimester of pregnancy was recruited for this prospective study. Genome-wide DNA methylation was quantified in first-trimester maternal peripheral white blood cells and placental chorionic tissue from normotensive women and those with preeclampsia (n = 6/group).

RESULTS

Late-onset preeclampsia developed in 12.7% of women. Significant differences in DNA methylation were identified in 207 individual linked cytosine and guanine (CpG) sites in maternal white blood cells collected in the first trimester (132 sites with gain and 75 sites with loss of methylation), which were common to approximately 75% of the differentially methylated CpG sites identified in chorionic tissue of fetal origin.

CONCLUSION

This study is the first to identify maternal epigenetic targets and common targets in fetal-derived tissue that represent putative biomarkers for early detection and heritable risk of preeclampsia. Findings may pave the way for diagnosis of preeclampsia prior to its clinical presentation and acute damaging effects, and the potential for prevention of the detrimental long-term sequelae.

Epigenome-wide profiling identifies significant differences in DNA methylation between matched-pairs of T- and B-lymphocytes from healthy individuals

Multiple reports now describe changes to the DNA methylome in rheumatoid arthritis and in many cases have analyzed methylation in mixed cell populations from whole blood. However, these approaches may preclude the identification of cell type-specific methylation, which may subsequently bias identification of disease-specific changes. To address this possibility, we conducted genome-wide DNA methylation profiling using HumanMethylation450 BeadChips to identify differences within matched pairs of T-lymphocytes and B-lymphocytes isolated from the peripheral blood of 10 healthy females. Array data were processed and differential methylation identified using NIMBL software. Validation of array data was performed by bisulfite pyrosequencing. Genome-wide DNA methylation was initially determined by analysis of LINE-1 sequences and was higher in B-lymphocytes than matched T-lymphocytes (69.8% vs. 65.2%, P ≤ 0.01). Pairwise analysis identified 679 CpGs, representing 250 genes, which were differentially methylated between T-lymphocytes and B-lymphocytes. The majority of sites (76.6%) were hypermethylated in B-lymphocytes. Pyrosequencing of selected candidates confirmed the array data in all cases. Hierarchical clustering revealed perfect segregation of samples into two distinct clusters based on cell type. Differentially methylated genes showed enrichment for biological functions/pathways associated with leukocytes and T-lymphocytes. Our work for the first time shows that T-lymphocytes and B-lymphocytes possess intrinsic differences in DNA methylation within a restricted set of functionally related genes. These data provide a foundation for investigating DNA methylation in diseases in which these cell types play important and distinct roles.

A comprehensive overview of Infinium HumanMethylation450 data processing

Infinium HumanMethylation450 beadarray is a popular technology to explore DNA methylomes in health and disease, and there is a current explosion in the use of this technique. Despite experience acquired from gene expression microarrays, analyzing Infinium Methylation arrays appeared more complex than initially thought and several difficulties have been encountered, as those arrays display specific features that need to be taken into consideration during data processing. Here, we review several issues that have been highlighted by the scientific community, and we present an overview of the general data processing scheme and an evaluation of the different normalization methods available to date to guide the 450K users in their analysis and data interpretation.

COHCAP: an integrative genomic pipeline for single-nucleotide resolution DNA methylation analysis

COHCAP (City of Hope CpG Island Analysis Pipeline) is an algorithm to analyze single-nucleotide resolution DNA methylation data produced by either an Illumina methylation array or targeted bisulfite sequencing. The goal of the COHCAP algorithm is to identify CpG islands that show a consistent pattern of methylation among CpG sites. COHCAP is currently the only DNA methylation package that provides integration with gene expression data to identify a subset of CpG islands that are most likely to regulate downstream gene expression, and it can generate lists of differentially methylated CpG islands with ∼50% concordance with gene expression from both cell line data and heterogeneous patient data. For example, this article describes known breast cancer biomarkers (such as estrogen receptor) with a negative correlation between DNA methylation and gene expression. COHCAP also provides visualization for quality control metrics, regions of differential methylation and correlation between methylation and gene expression. This software is freely available at https://sourceforge.net/projects/cohcap/.