A DNA methylation fingerprint of 1628 human samples

Plasma DNA tissue mapping by genome-wide methylation sequencing for noninvasive prenatal, cancer, and transplantation assessments

Plasma consists of DNA released from multiple tissues within the body. Using genome-wide bisulfite sequencing of plasma DNA and deconvolution of the sequencing data with reference to methylation profiles of different tissues, we developed a general approach for studying the major tissue contributors to the circulating DNA pool. We tested this method in pregnant women, patients with hepatocellular carcinoma, and subjects following bone marrow and liver transplantation. In most subjects, white blood cells were the predominant contributors to the circulating DNA pool. The placental contributions in the plasma of pregnant women correlated with the proportional contributions as revealed by fetal-specific genetic markers. The graft-derived contributions to the plasma in the transplant recipients correlated with those determined using donor-specific genetic markers. Patients with hepatocellular carcinoma showed elevated plasma DNA contributions from the liver, which correlated with measurements made using tumor-associated copy number aberrations. In hepatocellular carcinoma patients and in pregnant women exhibiting copy number aberrations in plasma, comparison of methylation deconvolution results using genomic regions with different copy number status pinpointed the tissue type responsible for the aberrations. In a pregnant woman diagnosed as having follicular lymphoma during pregnancy, methylation deconvolution indicated a grossly elevated contribution from B cells into the plasma DNA pool and localized B cells as the origin of the copy number aberrations observed in plasma. This method may serve as a powerful tool for assessing a wide range of physiological and pathological conditions based on the identification of perturbed proportional contributions of different tissues into plasma.

The potential of DNA modifications as biomarkers and therapeutic targets in oncology

Knowledge of epigenetic alterations in cancer is rapidly increasing due to the development of genome-wide techniques for their identification. DNA methylation is the best understood epigenetic adaptation and disease-specific aberrant DNA methylation is a well-recognized hallmark of cancer. Recently, novel modifications, including 5-hydroxymethylation have been described, adding a new layer of complexity to understanding the epigenetic machinery and their role in cancer. There have been significant advances in techniques for the discovery and validation of DNA methylation- and hydroxymethylation-based biomarkers, each with its own advantages and limitations. With the advent of new profiling technologies, the ever-growing list of genes that show epigenetic alterations, particularly DNA methylation, emphasizes the role of these changes for early detection, diagnosis, prognosis, and prediction of response to therapies. While there are yet many challenges to the effective implementation of DNA-methylation/hydroxymethylation-based biomarkers and epigenetic therapeutics, the field is moving closer to the goal of defining personalized medicine.

Concordance of Hypermethylated DNA and the Tumor Markers CA 15-3, CEA, and TPA in Serum during Monitoring of Patients with Advanced Breast Cancer

The serological protein tumor markers CA 15-3, CEA, and TPA are frequently used to monitor tumor burden among metastatic breast cancer patients. Breast cancer is associated with global DNA hypomethylation and hypermethylation of some promoter regions. No monitoring study has yet investigated the interrelationship between protein tumor markers, the global DNA hypomethylation, and hypermethylated genes in serum from patients with advanced disease. Twenty-nine patients with histologically proven advanced breast cancer received first-line chemotherapy with epirubicin. Samples were collected prior to each treatment and prospectively analyzed for CA 15-3, CEA, and TPA. The same samples were retrospectively analyzed for the concentration of hypermethylated RASSF1A and for global DNA hypomethylation using LINE-1. Among patients with elevated concentrations of the protein markers, concordance could be observed between serial changes of the hypermethylated RASSF1A gene and the protein markers. Among patients with lower concentrations, RASSF1A could only be detected periodically. There was discordance between changes of the hypomethylated LINE-1 as compared to the protein markers. Circulating hypermethylated RASSF1A and protein markers may have similar kinetics during monitoring of tumor burden. Further investigations are needed to determine whether any of the hypermethylated DNA genes may provide predictive information during monitoring.

EGFR promoter exhibits dynamic histone modifications and binding of ASH2L and P300 in human germinal matrix and gliomas

Several signaling pathways important for the proliferation and growth of brain cells are pathologically dysregulated in gliomas, including the epidermal growth factor receptor (EGFR). Expression of EGFR is high in neural progenitors during development and in gliomas but decreases significantly in most adult brain regions. Here we show that EGFR expression is maintained in the astrocyte ribbon of the adult human subventricular zone. The transcriptional regulation of EGFR expression is poorly understood. To investigate the role of epigenetics on EGFR regulation in the contexts of neural development and gliomagenesis, we measured levels of DNA methylation and histone H3 modifications at the EGFR promoter in human brain tissues, glioma specimens, and EGFR-expressing neural cells, acutely isolated from their native niche. While DNA was constitutively hypomethylated in non-neoplastic and glioma samples, regardless of their EGFR-expression status, the activating histone modifications H3K27ac and H3K4me3 were enriched only when EGFR is highly expressed (developing germinal matrix and gliomas). Conversely, repressive H3K27me3 marks predominated in adult white matter where EGFR is repressed. Furthermore, the histone methyltransferase core enzyme ASH2L was bound at EGFR in the germinal matrix and in gliomas where levels of H3K4me3 are high, and the histone acetyltransferase P300 was bound in samples with H3K27ac enrichment. Our studies use human cells and tissues undisturbed by cell-culture artifact, and point to an important, locus-specific role for chromatin remodeling in EGFR expression in human neural development that may be dysregulated during gliomagenesis, unraveling potential novel targets for future drug therapy.

Deconstruction of DNA methylation patterns during myogenesis reveals specific epigenetic events in the establishment of the skeletal muscle lineage

The progressive restriction of differentiation potential from pluripotent embryonic stem cells (ESCs) to tissue-specific stem cells involves widespread epigenetic reprogramming, including modulation of DNA methylation patterns. Skeletal muscle stem cells are required for the growth, maintenance, and regeneration of skeletal muscle. To investigate the contribution of DNA methylation to the establishment of the myogenic program, we analyzed ESCs, skeletal muscle stem cells in proliferating (myoblasts) and differentiating conditions (myotubes), and mature myofibers. About 1.000 differentially methylated regions were identified during muscle-lineage determination and terminal differentiation, mainly located in gene bodies and intergenic regions. As a whole, myogenic stem cells showed a gain of DNA methylation, while muscle differentiation was accompanied by loss of DNA methylation in CpG-poor regions. Notably, the hypomethylated regions in myogenic stem cells were neighbored by enhancer-type chromatin, suggesting the involvement of DNA methylation in the regulation of cell-type specific enhancers. Interestingly, we demonstrated the hypomethylation of the muscle cell-identity Myf5 super-enhancer only in muscle cells. Furthermore, we observed that upstream stimulatory factor 1 binding to Myf5 super-enhancer occurs upon DNA demethylation in myogenic stem cells. Taken altogether, we characterized the unique DNA methylation signature of skeletal muscle stem cells and highlighted the importance of DNA methylation-mediated regulation of cell identity Myf5 super-enhancer during cellular differentiation.

Polycomb repressive complex 2 epigenomic signature defines age-associated hypermethylation and gene expression changes

Although age-associated gene expression and methylation changes have been reported throughout the literature, the unifying epigenomic principles of aging remain poorly understood. Recent explosion in availability and resolution of functional/regulatory genome annotation data (epigenomic data), such as that provided by the ENCODE and Roadmap Epigenomics projects, provides an opportunity for the identification of epigenomic mechanisms potentially altered by age-associated differentially methylated regions (aDMRs) and regulatory signatures in the promoters of age-associated genes (aGENs). In this study we found that aDMRs and aGENs identified in multiple independent studies share a common Polycomb Repressive Complex 2 signature marked by EZH2, SUZ12, CTCF binding sites, repressive H3K27me3, and activating H3K4me1 histone modification marks, and a "poised promoter" chromatin state. This signature is depleted in RNA Polymerase II-associated transcription factor binding sites, activating H3K79me2, H3K36me3, H3K27ac marks, and an "active promoter" chromatin state. The PRC2 signature was shown to be generally stable across cell types. When considering the directionality of methylation changes, we found the PRC2 signature to be associated with aDMRs hypermethylated with age, while hypomethylated aDMRs were associated with enhancers. In contrast, aGENs were associated with the PRC2 signature independently of the directionality of gene expression changes. In this study we demonstrate that the PRC2 signature is the common epigenomic context of genomic regions associated with hypermethylation and gene expression changes in aging.

A comparison of genome-wide DNA methylation patterns between different vascular tissues from patients with coronary heart disease

Epigenetic mechanisms of gene regulation in context of cardiovascular diseases are of considerable interest. So far, our current knowledge of the DNA methylation profiles for atherosclerosis affected and healthy human vascular tissues is still limited. Using the Illumina Infinium Human Methylation27 BeadChip, we performed a genome-wide analysis of DNA methylation in right coronary artery in the area of advanced atherosclerotic plaques, atherosclerotic-resistant internal mammary arteries, and great saphenous veins obtained from same patients with coronary heart disease. The resulting DNA methylation patterns were markedly different between all the vascular tissues. The genes hypomethylated in athero-prone arteries to compare with atherosclerotic-resistant arteries were predominately involved in regulation of inflammation and immune processes, as well as development. The great saphenous veins exhibited an increase of the DNA methylation age in comparison to the internal mammary arteries. Gene ontology analysis for genes harboring hypermethylated CpG-sites in veins revealed the enrichment for biological processes associated with the development. Four CpG-sites located within the MIR10B gene sequence and about 1 kb upstream of the HOXD4 gene were also confirmed as hypomethylated in the independent dataset of the right coronary arteries in the area of advanced atherosclerotic plaques in comparison with the other vascular tissues. The DNA methylation differences observed in vascular tissues of patients with coronary heart disease can provide new insights into the mechanisms underlying the development of pathology and explanation for the difference in graft patency after coronary artery bypass grafting surgery.

Deregulation of DNMT1, DNMT3B and miR-29s in Burkitt lymphoma suggests novel contribution for disease pathogenesis

Methylation of CpG islands in promoter gene regions is frequently observed in lymphomas. DNA methylation is established by DNA methyltransferases (DNMTs). DNMT1 maintains methylation patterns, while DNMT3A and DNMT3B are critical for de novo DNA methylation. Little is known about the expression of DNMTs in lymphomas. DNMT3A and 3B genes can be regulated post-transcriptionally by miR-29 family. Here, we demonstrated for the first time the overexpression of DNMT1 and DNMT3B in Burkitt lymphoma (BL) tumor samples (69% and 86%, respectively). Specifically, the treatment of two BL cell lines with the DNMT inhibitor 5-aza-dC decreased DNMT1 and DNMT3B protein levels and inhibited cell growth. Additionally, miR-29a, miR-29b and miR-29c levels were significantly decreased in the BL tumor samples. Besides, the ectopic expression of miR-29a, miR-29b and miR-29c reduced the DNMT3B expression and miR-29a and miR-29b lead to increase of p16(INK4a) mRNA expression. Altogether, our data suggest that deregulation of DNMT1, DNMT3B and miR29 may be involved in BL pathogenesis.

Pharmacological methyl group donors block skeletal metastasis in vitro and in vivo

BACKGROUND AND PURPOSE

DNA hypomethylation was previously implicated in metastasis. In the present study, we examined whether methyl supplementation with the universal methyl donor S-adenosylmethionine (SAM) inhibits prostate cancer associated skeletal metastasis.

EXPERIMENTAL APPROACH

Highly invasive human prostate cancer cells PC-3 and DU-145 were treated with vehicle alone, S-adenosylhomocysteine (SAH) or SAM and their effects on tumour cell proliferation, invasion, migration and colony formation were monitored. For in vivo studies, control (SAH) and SAM-treated PC-3 cells were injected into the tibia of Fox chase SCID mice and skeletal lesions were determined by X-ray and μCT. To understand possible mechanisms involved, we delineated the effect of SAM on the genome-wide methylation profile of PC-3 cells.

KEY RESULTS

Treatment with SAM resulted in a dose-dependent inhibition of tumour cell proliferation, invasion, cell migration, colony formation and cell cycle characteristics. Animals injected with 250 μM SAM-treated cells developed significantly smaller skeletal lesions, which were associated with increases in bone volume to tumour volume ratio and connectivity density as well as decreased trabecular spacing. Genome-wide methylation analysis showed differential methylation in several key signalling pathways implicated in prostate cancer including the signal transducer and activator of transcription 3 (STAT3) pathway. A selective STAT3 inhibitor decreased tumour cell invasion, effects which were less pronounced as compared with SAM.

CONCLUSIONS AND IMPLICATIONS

These studies provide a possible mechanism for the role of DNA demethylation in the development of skeletal metastasis and a rationale for the use of hypermethylation pharmacological agents to impede the development and progression of skeletal metastasis.

Aberrant DNA methylation patterns of spermatozoa in men with unexplained infertility

STUDY QUESTION

Are there DNA methylation alterations in sperm that could explain the reduced biological fertility of male partners from couples with unexplained infertility?

SUMMARY ANSWER

DNA methylation patterns, not only at specific loci but also at Alu Yb8 repetitive sequences, are altered in infertile individuals compared with fertile controls.

WHAT IS KNOWN ALREADY

Aberrant DNA methylation of sperm has been associated with human male infertility in patients demonstrating either deficiencies in the process of spermatogenesis or low semen quality.

STUDY DESIGN, SIZE, DURATION

Case and control prospective study. This study compares 46 sperm samples obtained from 17 normospermic fertile men and 29 normospermic infertile patients.

PARTICIPANTS/MATERIALS, SETTING, METHODS

Illumina Infinium HD Human Methylation 450K arrays were used to identify genomic regions showing differences in sperm DNA methylation patterns between five fertile and seven infertile individuals. Additionally, global DNA methylation of sperm was measured using the Methylamp Global DNA Methylation Quantification Ultra kit (Epigentek) in 14 samples, and DNA methylation at several repetitive sequences (LINE-1, Alu Yb8, NBL2, D4Z4) measured by bisulfite pyrosequencing in 44 sperm samples. A sperm-specific DNA methylation pattern was obtained by comparing the sperm methylomes with the DNA methylomes of differentiated somatic cells using data obtained from methylation arrays (Illumina 450 K) of blood, neural and glial cells deposited in public databases.

MAIN RESULTS AND THE ROLE OF CHANCE

In this study we conduct, for the first time, a genome-wide study to identify alterations of sperm DNA methylation in individuals with unexplained infertility that may account for the differences in their biological fertility compared with fertile individuals. We have identified 2752 CpGs showing aberrant DNA methylation patterns, and more importantly, these differentially methylated CpGs were significantly associated with CpG sites which are specifically methylated in sperm when compared with somatic cells. We also found statistically significant (P < 0.001) associations between DNA hypomethylation and regions corresponding to those which, in somatic cells, are enriched in the repressive histone mark H3K9me3, and between DNA hypermethylation and regions enriched in H3K4me1 and CTCF, suggesting that the relationship between chromatin context and aberrant DNA methylation of sperm in infertile men could be locus-dependent. Finally, we also show that DNA methylation patterns, not only at specific loci but also at several repetitive sequences (LINE-1, Alu Yb8, NBL2, D4Z4), were lower in sperm than in somatic cells. Interestingly, sperm samples at Alu Yb8 repetitive sequences of infertile patients showed significantly lower DNA methylation levels than controls.

LIMITATIONS, REASONS FOR CAUTION

Our results are descriptive and further studies would be needed to elucidate the functional effects of aberrant DNA methylation on male fertility.

WIDER IMPLICATIONS OF THE FINDINGS

Overall, our data suggest that aberrant sperm DNA methylation might contribute to fertility impairment in couples with unexplained infertility and they provide a promising basis for future research.

STUDY FUNDING/COMPETING INTERESTS

This work has been financially supported by Fundación Cientifica de la AECC (to R.G.U.); IUOPA (to G.F.B.); FICYT (to E.G.T.); the Spanish National Research Council (CSIC; 200820I172 to M.F.F.); Fundación Ramón Areces (to M.F.F); the Plan Nacional de I+D+I 2008-2011/2013-2016/FEDER (PI11/01728 to AF.F., PI12/01080 to M.F.F. and PI12/00361 to S.L.); the PN de I+D+I 2008-20011 and the Generalitat de Catalunya (2009SGR01490). A.F.F. is sponsored by ISCIII-Subdirección General de Evaluación y Fomento de la Investigación (CP11/00131). S.L. is sponsored by the Researchers Stabilization Program from the Spanish National Health System (CES09/020). The IUOPA is supported by the Obra Social Cajastur, Spain.

DNA methylation dynamics in muscle development and disease

DNA methylation is an essential epigenetic modification for mammalian development and is crucial for the establishment and maintenance of cellular identity. Traditionally, DNA methylation has been considered as a permanent repressive epigenetic mark. However, the application of genome-wide approaches has allowed the analysis of DNA methylation in different genomic contexts revealing a more dynamic regulation than originally thought, since active DNA methylation and demethylation occur during cellular differentiation and tissue specification. Satellite cells are the primary stem cells in adult skeletal muscle and are responsible for postnatal muscle growth, hypertrophy, and muscle regeneration. This review outlines the published data regarding DNA methylation changes along the skeletal muscle program, in both physiological and pathological conditions, to better understand the epigenetic mechanisms that control myogenesis.

Discordance of DNA methylation variance between two accessible human tissues

Population epigenetic studies have been seeking to identify differences in DNA methylation between specific exposures, demographic factors, or diseases in accessible tissues, but relatively little is known about how inter-individual variability differs between these tissues. This study presents an analysis of DNA methylation differences between matched peripheral blood mononuclear cells (PMBCs) and buccal epithelial cells (BECs), the two most accessible tissues for population studies, in 998 promoter-located CpG sites. Specifically we compared probe-wise DNA methylation variance, and how this variance related to demographic factors across the two tissues. PBMCs had overall higher DNA methylation than BECs, and the two tissues tended to differ most at genomic regions of low CpG density. Furthermore, although both tissues showed appreciable probe-wise variability, the specific regions and magnitude of variability differed strongly between tissues. Lastly, through exploratory association analysis, we found indication of differential association of BEC and PBMC with demographic variables. The work presented here offers insight into variability of DNA methylation between individuals and across tissues and helps guide decisions on the suitability of buccal epithelial or peripheral mononuclear cells for the biological questions explored by epigenetic studies in human populations.

Pancancer analysis of DNA methylation-driven genes using MethylMix

Aberrant DNA methylation is an important mechanism that contributes to oncogenesis. Yet, few algorithms exist that exploit this vast dataset to identify hypo- and hypermethylated genes in cancer. We developed a novel computational algorithm called MethylMix to identify differentially methylated genes that are also predictive of transcription. We apply MethylMix to 12 individual cancer sites, and additionally combine all cancer sites in a pancancer analysis. We discover pancancer hypo- and hypermethylated genes and identify novel methylation-driven subgroups with clinical implications. MethylMix analysis on combined cancer sites reveals 10 pancancer clusters reflecting new similarities across malignantly transformed tissues.

De novo identification of differentially methylated regions in the human genome

Background

The identification and characterisation of differentially methylated regions (DMRs) between phenotypes in the human genome is of prime interest in epigenetics. We present a novel method, DMRcate, that fits replicated methylation measurements from the Illumina HM450K BeadChip (or 450K array) spatially across the genome using a Gaussian kernel. DMRcate identifies and ranks the most differentially methylated regions across the genome based on tunable kernel smoothing of the differential methylation (DM) signal. The method is agnostic to both genomic annotation and local change in the direction of the DM signal, removes the bias incurred from irregularly spaced methylation sites, and assigns significance to each DMR called via comparison to a null model.

Results

We show that, for both simulated and real data, the predictive performance of DMRcate is superior to those of Bumphunter and Probe Lasso, and commensurate with that of comb-p. For the real data, we validate all array-derived DMRs from the candidate methods on a suite of DMRs derived from whole-genome bisulfite sequencing called from the same DNA samples, using two separate phenotype comparisons.

Conclusions

The agglomeration of genomically localised individual methylation sites into discrete DMRs is currently best served by a combination of DM-signal smoothing and subsequent threshold specification. The findings also suggest the design of the 450K array shows preference for CpG sites that are more likely to be differentially methylated, but its overall coverage does not adequately reflect the depth and complexity of methylation signatures afforded by sequencing.

For the convenience of the research community we have created a user-friendly R software package called DMRcate, downloadable from Bioconductor and compatible with existing preprocessing packages, which allows others to apply the same DMR-finding method on 450K array data.

Electronic supplementary material

The online version of this article (doi:10.1186/1756-8935-8-6) contains supplementary material, which is available to authorized users.

Predicting genome-wide DNA methylation using methylation marks, genomic position, and DNA regulatory elements

BACKGROUND

Recent assays for individual-specific genome-wide DNA methylation profiles have enabled epigenome-wide association studies to identify specific CpG sites associated with a phenotype. Computational prediction of CpG site-specific methylation levels is critical to enable genome-wide analyses, but current approaches tackle average methylation within a locus and are often limited to specific genomic regions.

RESULTS

We characterize genome-wide DNA methylation patterns, and show that correlation among CpG sites decays rapidly, making predictions solely based on neighboring sites challenging. We built a random forest classifier to predict methylation levels at CpG site resolution using features including neighboring CpG site methylation levels and genomic distance, co-localization with coding regions, CpG islands (CGIs), and regulatory elements from the ENCODE project. Our approach achieves 92% prediction accuracy of genome-wide methylation levels at single-CpG-site precision. The accuracy increases to 98% when restricted to CpG sites within CGIs and is robust across platform and cell-type heterogeneity. Our classifier outperforms other types of classifiers and identifies features that contribute to prediction accuracy: neighboring CpG site methylation, CGIs, co-localized DNase I hypersensitive sites, transcription factor binding sites, and histone modifications were found to be most predictive of methylation levels.

CONCLUSIONS

Our observations of DNA methylation patterns led us to develop a classifier to predict DNA methylation levels at CpG site resolution with high accuracy. Furthermore, our method identified genomic features that interact with DNA methylation, suggesting mechanisms involved in DNA methylation modification and regulation, and linking diverse epigenetic processes.

Epigenetics of aging

The aging phenotype is the result of a complex interaction between genetic, epigenetic and environmental factors, and it is among the most complex phenotypes studied to date. Evidence suggests that epigenetic factors, including DNA methylation, histone modifications and microRNA expression, may affect the aging process and may be one of the central mechanisms by which aging predisposes to many age-related diseases. The total number of altered methylation sites increases with increasing age, such that they could serve as a biomarker for chronological age. This chapter summarizes the mechanisms by which these epigenetic factors contribute to aging and how they may affect the complex physiology of aging, lifespan and age-associated diseases.

H3K4me1 marks DNA regions hypomethylated during aging in human stem and differentiated cells

In differentiated cells, aging is associated with hypermethylation of DNA regions enriched in repressive histone post-translational modifications. However, the chromatin marks associated with changes in DNA methylation in adult stem cells during lifetime are still largely unknown. Here, DNA methylation profiling of mesenchymal stem cells (MSCs) obtained from individuals aged 2 to 92 yr identified 18,735 hypermethylated and 45,407 hypomethylated CpG sites associated with aging. As in differentiated cells, hypermethylated sequences were enriched in chromatin repressive marks. Most importantly, hypomethylated CpG sites were strongly enriched in the active chromatin mark H3K4me1 in stem and differentiated cells, suggesting this is a cell type-independent chromatin signature of DNA hypomethylation during aging. Analysis of scedasticity showed that interindividual variability of DNA methylation increased during aging in MSCs and differentiated cells, providing a new avenue for the identification of DNA methylation changes over time. DNA methylation profiling of genetically identical individuals showed that both the tendency of DNA methylation changes and scedasticity depended on nongenetic as well as genetic factors. Our results indicate that the dynamics of DNA methylation during aging depend on a complex mixture of factors that include the DNA sequence, cell type, and chromatin context involved and that, depending on the locus, the changes can be modulated by genetic and/or external factors.

Prenatal arsenic exposure and the epigenome: identifying sites of 5-methylcytosine alterations that predict functional changes in gene expression in newborn cord blood and subsequent birth outcomes

Prenatal exposure to inorganic arsenic (iAs) is detrimental to the health of newborns and increases the risk of disease development later in life. Here we examined a subset of newborn cord blood leukocyte samples collected from subjects enrolled in the Biomarkers of Exposure to ARsenic (BEAR) pregnancy cohort in Gómez Palacio, Mexico, who were exposed to a range of drinking water arsenic concentrations (0.456-236 µg/l). Changes in iAs-associated DNA 5-methylcytosine methylation were assessed across 424,935 CpG sites representing 18,761 genes and compared with corresponding mRNA expression levels and birth outcomes. In the context of arsenic exposure, a total of 2919 genes were identified with iAs-associated differences in DNA methylation. Site-specific analyses identified DNA methylation changes that were most predictive of gene expression levels where CpG methylation within CpG islands positioned within the first exon, the 5' untranslated region and 200 bp upstream of the transcription start site yielded the most significant association with gene expression levels. A set of 16 genes was identified with correlated iAs-associated changes in DNA methylation and mRNA expression and all were highly enriched for binding sites of the early growth response (EGR) and CCCTC-binding factor (CTCF) transcription factors. Furthermore, DNA methylation levels of 7 of these genes were associated with differences in birth outcomes including gestational age and head circumference.These data highlight the complex interplay between DNA methylation, functional changes in gene expression and health outcomes and underscore the need for functional analyses coupled to epigenetic assessments.

Genome-wide DNA methylation analysis of lung carcinoma reveals one neuroendocrine and four adenocarcinoma epitypes associated with patient outcome

PURPOSE

Lung cancer is the worldwide leading cause of death from cancer. DNA methylation in gene promoter regions is a major mechanism of gene expression regulation that may promote tumorigenesis. However, whether clinically relevant subgroups based on DNA methylation patterns exist in lung cancer remains unclear.

EXPERIMENTAL DESIGN

Whole-genome DNA methylation analysis using 450K Illumina BeadArrays was performed on 12 normal lung tissues and 124 tumors, including 83 adenocarcinomas, 23 squamous cell carcinomas (SqCC), 1 adenosquamous cancer, 5 large cell carcinomas, 9 large cell neuroendocrine carcinomas (LCNEC), and 3 small-cell carcinomas (SCLC). Unsupervised bootstrap clustering was performed to identify DNA methylation subgroups, which were validated in 695 adenocarcinomas and 122 SqCCs. Subgroups were characterized by clinicopathologic factors, whole-exome sequencing data, and gene expression profiles.

RESULTS

Unsupervised analysis identified five DNA methylation subgroups (epitypes). One epitype was distinctly associated with neuroendocrine tumors (LCNEC and SCLC). For adenocarcinoma, remaining four epitypes were associated with unsupervised and supervised gene expression phenotypes, and differences in molecular features, including global hypomethylation, promoter hypermethylation, genomic instability, expression of proliferation-associated genes, and mutations in KRAS, TP53, KEAP1, SMARCA4, and STK11. Furthermore, these epitypes were associated with clinicopathologic features such as smoking history and patient outcome.

CONCLUSIONS

Our findings highlight one neuroendocrine and four adenocarcinoma epitypes associated with molecular and clinicopathologic characteristics, including patient outcome. This study demonstrates the possibility to further subgroup lung cancer, and more specifically adenocarcinomas, based on epigenetic/molecular classification that could lead to more accurate tumor classification, prognostication, and tailored patient therapy.

DiffVar: a new method for detecting differential variability with application to methylation in cancer and aging

Methylation of DNA is known to be essential to development and dramatically altered in cancers. The Illumina HumanMethylation450 BeadChip has been used extensively as a cost-effective way to profile nearly half a million CpG sites across the human genome. Here we present DiffVar, a novel method to test for differential variability between sample groups. DiffVar employs an empirical Bayes model framework that can take into account any experimental design and is robust to outliers. We applied DiffVar to several datasets from The Cancer Genome Atlas, as well as an aging dataset. DiffVar is available in the missMethyl Bioconductor R package.

Senescent cells: SASPected drivers of age-related pathologies

The progression of physiological ageing is driven by intracellular aberrations including telomere attrition, genomic instability, epigenetic alterations and loss of proteostasis. These in turn damage cells and compromise their functionality. Cellular senescence, a stable irreversible cell-cycle arrest, is elicited in damaged cells and prevents their propagation in the organism. Under normal conditions, senescent cells recruit the immune system which facilitates their removal from tissues. Nevertheless, during ageing, tissue-residing senescent cells tend to accumulate, and might negatively impact their microenvironment via profound secretory phenotype with pro-inflammatory characteristics, termed senescence-associated secretory phenotype (SASP). Indeed, senescent cells are mostly abundant at sites of age-related pathologies, including degenerative disorders and malignancies. Interestingly, studies on progeroid mice indicate that selective elimination of senescent cells can delay age-related deterioration. This suggests that chronic inflammation induced by senescent cells might be a main driver of these pathologies. Importantly, senescent cells accumulate as a result of deficient immune surveillance, and their removal is increased upon the use of immune stimulatory agents. Insights into mechanisms of senescence surveillance could be combined with current approaches for cancer immunotherapy to propose new preventive and therapeutic strategies for age-related diseases.

Diverse epigenetic mechanisms of human disease

Epigenetic control of gene expression programs is essential for normal organismal development and cellular function. Abrogation of epigenetic regulation is seen in many human diseases, including cancer and neuropsychiatric disorders, where it can affect disease etiology and progression. Abnormal epigenetic profiles can serve as biomarkers of disease states and predictors of disease outcomes. Therefore, epigenetics is a key area of clinical investigation in diagnosis, prognosis, and treatment. In this review, we give an overarching view of epigenetic mechanisms of human disease. Genetic mutations in genes that encode chromatin regulators can cause monogenic disease or are incriminated in polygenic, multifactorial diseases. Environmental stresses can also impact directly on chromatin regulation, and these changes can increase the risk of, or directly cause, disease. Finally, emerging evidence suggests that exposure to environmental stresses in older generations may predispose subsequent generations to disease in a manner that involves the transgenerational inheritance of epigenetic information.

DNA methylation, microRNAs, and their crosstalk as potential biomarkers in hepatocellular carcinoma

Epigenetic alterations have been identified as a major characteristic in human cancers. Advances in the field of epigenetics have contributed significantly in refining our knowledge of molecular mechanisms underlying malignant transformation. DNA methylation and microRNA expression are epigenetic mechanisms that are widely altered in human cancers including hepatocellular carcinoma (HCC), the third leading cause of cancer related mortality worldwide. Both DNA methylation and microRNA expression patterns are regulated in developmental stage specific-, cell type specific- and tissue-specific manner. The aberrations are inferred in the maintenance of cancer stem cells and in clonal cell evolution during carcinogenesis. The availability of genome-wide technologies for DNA methylation and microRNA profiling has revolutionized the field of epigenetics and led to the discovery of a number of epigenetically silenced microRNAs in cancerous cells and primary tissues. Dysregulation of these microRNAs affects several key signalling pathways in hepatocarcinogenesis suggesting that modulation of DNA methylation and/or microRNA expression can serve as new therapeutic targets for HCC. Accumulative evidence shows that aberrant DNA methylation of certain microRNA genes is an event specifically found in HCC which correlates with unfavorable outcomes. Therefore, it can potentially serve as a biomarker for detection as well as for prognosis, monitoring and predicting therapeutic responses in HCC.

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.

A novel method for identification and quantification of consistently differentially methylated regions

Advances in biotechnology have resulted in large-scale studies of DNA methylation. A differentially methylated region (DMR) is a genomic region with multiple adjacent CpG sites that exhibit different methylation statuses among multiple samples. Many so-called “supervised” methods have been established to identify DMRs between two or more comparison groups. Methods for the identification of DMRs without reference to phenotypic information are, however, less well studied. An alternative “unsupervised” approach was proposed, in which DMRs in studied samples were identified with consideration of nature dependence structure of methylation measurements between neighboring probes from tiling arrays. Through simulation study, we investigated effects of dependencies between neighboring probes on determining DMRs where a lot of spurious signals would be produced if the methylation data were analyzed independently of the probe. In contrast, our newly proposed method could successfully correct for this effect with a well-controlled false positive rate and a comparable sensitivity. By applying to two real datasets, we demonstrated that our method could provide a global picture of methylation variation in studied samples. R source codes to implement the proposed method were freely available at http://www.csjfann.ibms.sinica.edu.tw/eag/programlist/ICDMR/ICDMR.html.

Jumping on the Train of Personalized Medicine: A Primer for Non- Geneticist Clinicians: Part 3. Clinical Applications in the Personalized Medicine Area

The rapid decline of sequencing costs brings hope that personal genome sequencing will become a common feature of medical practice. This series of three reviews aim to help non-geneticist clinicians to jump into the fast-moving field of personalized genetic medicine. In the first two articles, we covered the fundamental concepts of molecular genetics and the methodologies used in genetic epidemiology. In this third article, we discuss the evolution of personalized medicine and illustrate the most recent success in the fields of Mendelian and complex human diseases. We also address the challenges that currently limit the use of personalized medicine to its full potential.

DNA methylome profiling of human tissues identifies global and tissue-specific methylation patterns

Background

DNA epigenetic modifications, such as methylation, are important regulators of tissue differentiation, contributing to processes of both development and cancer. Profiling the tissue-specific DNA methylome patterns will provide novel insights into normal and pathogenic mechanisms, as well as help in future epigenetic therapies. In this study, 17 somatic tissues from four autopsied humans were subjected to functional genome analysis using the Illumina Infinium HumanMethylation450 BeadChip, covering 486 428 CpG sites.

Results

Only 2% of the CpGs analyzed are hypermethylated in all 17 tissue specimens; these permanently methylated CpG sites are located predominantly in gene-body regions. In contrast, 15% of the CpGs are hypomethylated in all specimens and are primarily located in regions proximal to transcription start sites. A vast number of tissue-specific differentially methylated regions are identified and considered likely mediators of tissue-specific gene regulatory mechanisms since the hypomethylated regions are closely related to known functions of the corresponding tissue. Finally, a clear inverse correlation is observed between promoter methylation within CpG islands and gene expression data obtained from publicly available databases.

Conclusions

This genome-wide methylation profiling study identified tissue-specific differentially methylated regions in 17 human somatic tissues. Many of the genes corresponding to these differentially methylated regions contribute to tissue-specific functions. Future studies may use these data as a reference to identify markers of perturbed differentiation and disease-related pathogenic mechanisms.

Genome-wide DNA methylation changes with age in disease-free human skeletal muscle

A decline in skeletal muscle mass and function with aging is well recognized, but remains poorly characterized at the molecular level. Here, we report for the first time a genome-wide study of DNA methylation dynamics in skeletal muscle of healthy male individuals during normal human aging. We predominantly observed hypermethylation throughout the genome within the aged group as compared to the young subjects. Differentially methylated CpG (dmCpG) nucleotides tend to arise intragenically and are underrepresented in promoters and are overrepresented in the middle and 3′ end of genes. The intragenic methylation changes are overrepresented in genes that guide the formation of the junction of the motor neuron and myofibers. We report a low level of correlation of gene expression from previous studies of aged muscle with our current analysis of DNA methylation status. For those genes that had both changes in methylation and gene expression with age, we observed a reverse correlation, with the exception of intragenic hypermethylated genes that were correlated with an increased gene expression. We suggest that a minimal number of dmCpG sites or select sites are required to be altered in order to correlate with gene expression changes. Finally, we identified 500 dmCpG sites that perform well in discriminating young from old samples. Our findings highlight epigenetic links between aging postmitotic skeletal muscle and DNA methylation.

Next-generation technologies and data analytical approaches for epigenomics

Epigenetics refers to the collection of heritable features that modulate the genome-environment interaction without being encoded in the actual DNA sequence. While being mitotically and sometimes even meiotically transmitted, epigenetic traits often demonstrate extensive flexibility. This allows cells to acquire diverse gene expression patterns during differentiation, but also to adapt to a changing environment. However, epigenetic alterations are not always beneficial to the organism, as they are, for example, frequently identified in human diseases such as cancer. Accurate and cost-efficient genome-scale profiling of epigenetic features is thus of major importance to pinpoint these "epimutations," for example, to monitor the epigenetic impact of environmental exposure. Over the last decade, the field of epigenetics has been revolutionized by several innovative "epigenomics" technologies exactly addressing this need. In this review, we discuss and compare widely used next-generation methods to assess DNA methylation and hydroxymethylation, noncoding RNA expression, histone modifications, and nucleosome positioning. Although recent methods are typically based on "second-generation" sequencing, we also pay attention to still commonly used array- and PCR-based methods, and look forward to the additional advantages of single-molecule sequencing. As the current bottleneck in epigenomics research is the analysis rather than generation of data, the basic difficulties and problem-solving strategies regarding data preprocessing and statistical analysis are introduced for the different technologies. Finally, we also consider the complications associated with epigenomic studies of species with yet unsequenced genomes and possible solutions.

Methylated DNA for monitoring tumor growth and regression: how do we get there?

A wide range of protein cancer biomarkers is currently recommended in international guidelines for monitoring the growth and regression of solid tumors. However, a number of these markers are also present in low concentrations in blood obtained from healthy individuals and from patients with benign diseases. In contrast, evidence has accumulated that suggests that modified methylated DNA is strongly related to the cancer phenotype. The modifications found in modified methylated DNA include a global loss of methylation in the genomes of the tumor cells as well as focal hypermethylation of gene promoters. Because tumor cells naturally secrete DNA and upon cell death leak DNA, modified methylated DNA can be detected in blood, urine, sputum and other body fluids. At present international guidelines do not include recommendations for monitoring modified methylated DNA. The low level of evidence can partly be explained by incomplete collection of serial blood samples, by analytical challenges, and by lack of knowledge of how monitoring studies should be designed and how serial marker data obtained from individual patients should be interpreted. Here, we review the clinical validity and utility of methylated DNA for monitoring the activity of malignant disease.

The de novo DNA methyltransferase DNMT3A in development and cancer

DNA methylation, one of the best-characterized epigenetic modifications, plays essential roles in development, aging and diseases. The de novo DNA methyltransferase DNMT3A is responsible for the establishment of de novo genomic DNA methylation patterns and, as such, involved in normal development as well as in many diseases including cancer. In recent years, our understanding of this important protein has made significant progress, which was facilitated by stunning development in the analysis of the DNA methylome of multiple organs and cell types. In this review, recent developments in the characterization of DNMT3A were discussed with special emphasis on the roles of DNMT3A in development and cancer.

First Barcelona Conference on Epigenetics and Cancer

The Barcelona Conference on Epigenetics and Cancer (BCEC) entitled “Challenges, opportunities and perspectives” took place November 21–22, 2013 in Barcelona. The 2013 BCEC is the first edition of a series of annual conferences jointly organized by five leading research centers in Barcelona. These centers are the Institute of Predictive and Personalized Medicine of Cancer (IMPPC), the Biomedical Campus Bellvitge with its Program of Epigenetics and Cancer Biology (PEBC), the Centre for Genomic Regulation (CRG), the Institute for Biomedical Research (IRB), and the Molecular Biology Institute of Barcelona (IBMB). Manuel Perucho and Marcus Buschbeck from the Institute of Predictive and Personalized Medicine of Cancer put together the scientific program of the first conference broadly covering all aspects of epigenetic research ranging from fundamental molecular research to drug and biomarker development and clinical application. In one and a half days, 23 talks and 50 posters were presented to a completely booked out audience counting 270 participants.

DNA methylation profiling of well-differentiated thyroid cancer uncovers markers of recurrence free survival

Thyroid cancer is a heterogeneous disease with several subtypes characterized by cytological, histological and genetic alterations, but the involvement of epigenetics is not well understood. Here, we investigated the role of aberrant DNA methylation in the development of well-differentiated thyroid tumors. We performed genome-wide DNA methylation profiling in the largest well-differentiated thyroid tumor series reported to date, comprising 83 primary tumors as well as 8 samples of adjacent normal tissue. The epigenetic profiles were closely related to not only tumor histology but also the underlying driver mutation; we found that follicular tumors had higher levels of methylation, which seemed to accumulate in a progressive manner along the tumorigenic process from adenomas to carcinomas. Furthermore, tumors harboring a BRAF or RAS mutation had a larger number of hypo- or hypermethylation events, respectively. The aberrant methylation of several candidate genes potentially related to thyroid carcinogenesis was validated in an independent series of 52 samples. Furthermore, through the integration of methylation and transcriptional expression data, we identified genes whose expression is associated with the methylation status of their promoters. Finally, by integrating clinical follow-up information with methylation levels we propose etoposide-induced 2.4 and Wilms tumor 1 as novel prognostic markers related to recurrence-free survival. This comprehensive study provides insights into the role of DNA methylation in well-differentiated thyroid cancer development and identifies novel markers associated with recurrence-free survival.

Variability in DNA methylation defines novel epigenetic subgroups of DLBCL associated with different clinical outcomes

Diffuse large B-cell lymphoma (DLBCL) is the most common aggressive form of non-Hodgkin lymphoma with variable biology and clinical behavior. The current classification does not fully explain the biological and clinical heterogeneity of DLBCLs. In this study, we carried out genomewide DNA methylation profiling of 140 DLBCL samples and 10 normal germinal center B cells using the HpaII tiny fragment enrichment by ligation-mediated polymerase chain reaction assay and hybridization to a custom Roche NimbleGen promoter array. We defined methylation disruption as a main epigenetic event in DLBCLs and designed a method for measuring the methylation variability of individual cases. We then used a novel approach for unsupervised hierarchical clustering based on the extent of DNA methylation variability. This approach identified 6 clusters (A-F). The extent of methylation variability was associated with survival outcomes, with significant differences in overall and progression-free survival. The novel clusters are characterized by disruption of specific biological pathways such as cytokine-mediated signaling, ephrin signaling, and pathways associated with apoptosis and cell-cycle regulation. In a subset of patients, we profiled gene expression and genomic variation to investigate their interplay with methylation changes. This study is the first to identify novel epigenetic clusters of DLBCLs and their aberrantly methylated genes, molecular associations, and survival.

Characterizing multi-omic data in systems biology

In today's biology, studies have shifted to analyzing systems over discrete biochemical reactions and pathways. These studies depend on combining the results from scores of experimental methods that analyze DNA; mRNA; noncoding RNAs, DNA, RNA, and protein interactions; and the nucleotide modifications that form the epigenome into global datasets that represent a diverse array of "omics" data (transcriptional, epigenetic, proteomic, metabolomic). The methods used to collect these data consist of high-throughput data generation platforms that include high-content screening, imaging, flow cytometry, mass spectrometry, and nucleic acid sequencing. Of these, the next-generation DNA sequencing platforms predominate because they provide an inexpensive and scalable way to quickly interrogate the molecular changes at the genetic, epigenetic, and transcriptional level. Furthermore, existing and developing single-molecule sequencing platforms will likely make direct RNA and protein measurements possible, thus increasing the specificity of current assays and making it possible to better characterize "epi-alterations" that occur in the epigenome and epitranscriptome. These diverse data types present us with the largest challenge: how do we develop software systems and algorithms that can integrate these datasets and begin to support a more democratic model where individuals can capture and track their own medical information through biometric devices and personal genome sequencing? Such systems will need to provide the necessary user interactions to work with the trillions of data points needed to make scientific discoveries. Here, we describe novel approaches in the genesis and processing of such data, models to integrate these data, and the increasing ubiquity of self-reporting and self-measured genomics and health data.

Genome-wide age-related DNA methylation changes in blood and other tissues relate to histone modification, expression and cancer

Epigenetic marks are extensively altered in cancer but may also change in normal tissues with age, which is the primary risk factor for most cancers. We conducted an epigenome-wide study to identify age-related methylation sites and examine their relationship to cancer and other underlying epigenetic marks. We analyzed 1006 blood DNA samples of women aged 35-76 years from the Sister Study and found that 7694 (28%) of the 27 578 CpGs assayed were associated with age (false discovery rate, q < 0.05). Using independent data sets, we confirmed 749 'high-confidence' age-related CpG (arCpGs) sites in normal blood. Based on The Cancer Genome Atlas data, we show that these age-related changes are largely concordant in a broad variety of normal tissues and that a significantly higher (71-91%, P < 10(-74)) than expected proportion of increasingly methylated arCpGs (IM-arCpGs) were overmethylated in a wide variety of tumor types. IM-arCpGs sites occurred almost exclusively at CpG islands and were disproportionately marked with the repressive H3K27me3 histone modification (P < 1 × 10(-) (50)). Genes containing these IM-arCpG sites were highly enriched for developmental and signaling pathways (P < 10(-) (10)). Our findings suggest that as cells acquire methylation at age-related sites, they have a lower threshold for malignant transformation that may explain in part the increase in cancer incidence with age.

Epigenetic inactivation of the BRCA1 interactor SRBC and resistance to oxaliplatin in colorectal cancer

Background

A major problem in cancer chemotherapy is the existence of primary resistance and/or the acquisition of secondary resistance. Many cellular defects contribute to chemoresistance, but epigenetic changes can also be a cause.

Methods

A DNA methylation microarray was used to identify epigenetic differences in oxaliplatin-sensitive and -resistant colorectal cancer cells. The candidate gene SRBC was validated by single-locus DNA methylation and expression techniques. Transfection and short hairpin experiments were used to assess oxaliplatin sensitivity. Progression-free survival (PFS) and overall survival (OS) in metastasic colorectal cancer patients were explored with Kaplan–Meier and Cox regression analyses. All statistical tests were two-sided.

Results

We found that oxaliplatin resistance in colorectal cancer cells depends on the DNA methylation–associated inactivation of the BRCA1 interactor SRBC gene. SRBC overexpression or depletion gives rise to sensitivity or resistance to oxaliplatin, respectively. SRBC epigenetic inactivation occurred in primary tumors from a discovery cohort of colorectal cancer patients (29.8%; n = 39 of 131), where it predicted shorter PFS (hazard ratio [HR] = 1.83; 95% confidence interval [CI] = 1.15 to 2.92; log-rank P = .01), particularly in oxaliplatin-treated case subjects for which metastasis surgery was not indicated (HR = 1.96; 95% CI = 1.13 to 3.40; log-rank P = .01). In a validation cohort of unresectable colorectal tumors treated with oxaliplatin (n = 58), SRBC hypermethylation was also associated with shorter PFS (HR = 1.90; 95% CI = 1.01 to 3.60; log-rank P = .045).

Conclusions

These results provide a basis for future clinical studies to validate SRBC hypermethylation as a predictive marker for oxaliplatin resistance in colorectal cancer.

DNA methylation determines nucleosome occupancy in the 5'-CpG islands of tumor suppressor genes

Promoter CpG island hypermethylation of tumor suppressor genes is an epigenetic hallmark of human cancer commonly associated with nucleosome occupancy and the transcriptional silencing of the neighboring gene. Nucleosomes can determine the underlying DNA methylation status. Herein, we show that the opposite is also true: DNA methylation can determine nucleosome positioning. Using a cancer model and digital nucleosome positioning techniques, we demonstrate that the induction of DNA hypomethylation events by genetic (DNMT1/DNMT3B deficient cells) or drug (a DNA demethylating agent) approaches is associated with the eviction of nucleosomes from previously hypermethylated CpG islands of tumor suppressor genes. Most importantly, the establishment of a stable cell line that restores DNMT1/DNMT3B deficiency shows that nucleosomes reoccupy their positions in de novo methylated CpG islands. Finally, we extend these results to the genomic level, combining a DNA methylation microarray and the nucleosome positioning technique. Using this global approach, we observe the dependency of nucleosome occupancy upon the DNA methylation status. Thus, our results suggest that there is a close association between hypermethylated CpG islands and the presence of nucleosomes, such that each of these epigenetic mechanisms can determine the recruitment of the other.

Identification of highly methylated genes across various types of B-cell non-hodgkin lymphoma

Epigenetic alterations of gene expression are important in the development of cancer. In this study, we identified genes which are epigenetically altered in major lymphoma types. We used DNA microarray technology to assess changes in gene expression after treatment of 11 lymphoma cell lines with epigenetic drugs. We identified 233 genes with upregulated expression in treated cell lines and with downregulated expression in B-cell lymphoma patient samples (n = 480) when compared to normal B cells (n = 5). The top 30 genes were further analyzed by methylation specific PCR (MSP) in 18 lymphoma cell lines. Seven of the genes were methylated in more than 70% of the cell lines and were further subjected to quantitative MSP in 37 B-cell lymphoma patient samples (diffuse large B-cell lymphoma (activated B-cell like and germinal center B-cell like subtypes), follicular lymphoma and Burkitt`s lymphoma) and normal B lymphocytes from 10 healthy donors. The promoters of DSP, FZD8, KCNH2, and PPP1R14A were methylated in 28%, 67%, 22%, and 78% of the 36 tumor samples, respectively, but not in control samples. Validation using a second series of healthy donor controls (n = 42; normal B cells, peripheral blood mononuclear cells, bone marrow, tonsils and follicular hyperplasia) and fresh-frozen lymphoma biopsies (n = 25), confirmed the results. The DNA methylation biomarker panel consisting of DSP, FZD8, KCNH2, and PPP1R14A was positive in 89% (54/61) of all lymphomas. Receiver operating characteristic analysis to determine the discriminative power between lymphoma and healthy control samples showed a c-statistic of 0.96, indicating a possible role for the biomarker panel in monitoring of lymphoma patients.

A prognostic DNA methylation signature for stage I non-small-cell lung cancer

PURPOSE

Non-small-cell lung cancer (NSCLC) is a tumor in which only small improvements in clinical outcome have been achieved. The issue is critical for stage I patients for whom there are no available biomarkers that indicate which high-risk patients should receive adjuvant chemotherapy. We aimed to find DNA methylation markers that could be helpful in this regard.

PATIENTS AND METHODS

A DNA methylation microarray that analyzes 450,000 CpG sites was used to study tumoral DNA obtained from 444 patients with NSCLC that included 237 stage I tumors. The prognostic DNA methylation markers were validated by a single-methylation pyrosequencing assay in an independent cohort of 143 patients with stage I NSCLC.

RESULTS

Unsupervised clustering of the 10,000 most variable DNA methylation sites in the discovery cohort identified patients with high-risk stage I NSCLC who had shorter relapse-free survival (RFS; hazard ratio [HR], 2.35; 95% CI, 1.29 to 4.28; P = .004). The study in the validation cohort of the significant methylated sites from the discovery cohort found that hypermethylation of five genes was significantly associated with shorter RFS in stage I NSCLC: HIST1H4F, PCDHGB6, NPBWR1, ALX1, and HOXA9. A signature based on the number of hypermethylated events distinguished patients with high- and low-risk stage I NSCLC (HR, 3.24; 95% CI, 1.61 to 6.54; P = .001).

CONCLUSION

The DNA methylation signature of NSCLC affects the outcome of stage I patients, and it can be practically determined by user-friendly polymerase chain reaction assays. The analysis of the best DNA methylation biomarkers improved prognostic accuracy beyond standard staging.

Evidence of expression variation and allelic imbalance in Crohn's disease susceptibility genes NOD2 and ATG16L1 in human dendritic cells

Human dendritic cells (DCs) play an important role in induction and progression of Crohn's disease (CD). Accumulating evidence suggests that viral infection is required to trigger CD pathogenesis in genetically predisposed individuals. NOD2 and ATG16L1 are among the major CD susceptibility genes implicated in impaired immune response to bacterial infection. In this study, we investigated gene expression and allelic imbalance (AI) of NOD2 and ATG16L1 using common variants in human monocyte-derived DCs. Significant AI was observed in ~40% and ~70% of NOD2 and ATG16L1 heterozygotes, respectively (p<0.05). AI of NOD2 was inversely associated with its expression level (p=0.015). No correlation was detected between gene expression and AI for ATG16L1. When infected with Newcastle Disease Virus (NDV), NOD2 expression in DCs was induced about four-fold (p<0.001), whereas ATG16L1 expression was not affected (p=0.88). In addition, NDV infection tended to lower the variance in AI among DC populations for the NOD2 gene (p=0.05), but not the ATG16L1 gene (p=0.32). Findings of a simulation study, aimed to verify whether the observed variation in gene expression and AI is a result of sample-to-sample variability or experimental measurement error, suggested that NOD2 AI is likely to result from a deterministic event at a single cell level. Overall, our results present initial evidence that AI of the NOD2 and ATG16L1 genes exists in populations of human DCs. In addition, our findings suggest that viral infection may regulate NOD2 expression.

DNA methylation in cancer: a gene silencing mechanism and the clinical potential of its biomarkers

Initiation and progression of human cancer not only depends on genetic alterations but also on epigenetic changes such as DNA methylation and histone modifications. Aberrant DNA hypermethylation in the promoter regions of genes is the most well-defined epigenetic change in tumors and is associated with inappropriate gene silencing. This feature can be utilized to search for tumor-specific DNA methylation biomarkers and to examine candidate DNA biomarkers for clinical use. DNA methylation biomarker is defined as a molecular target that undergoes DNA methylation changes in carcinogenesis. Such a biomarker is useful for early detection of cancer, predicting and/or monitoring the therapeutic response, and detection of recurrent cancer. In this review, we describe the mechanism that establishes and maintains DNA methylation patterns as well as the mechanism of aberrant gene silencing in cancer, and then we introduce methods to isolate the DNA methylation biomarkers. We also summarize the current status of clinical implementation for some of the most widely studied and well-validated DNA methylation biomarkers, including tissue factor pathway inhibitor 2 (TFPI2), septin 9 (SEPT9), glutathione S-transferase pi 1 (GSTP1), and O(6)-methylguanine-DNA methyltransferase (MGMT), and assess the clinical potential of these biomarkers for risk assessment, early diagnosis, prognosis, treatment, and the prevention of cancer. Finally we describe the possible involvement of 5-hydroxymethylcytosine in cancer; this is a recently discovered 5-methylcytosine oxidation derivative and might have a diagnostic potential in certain cancers. Abnormal DNA methylations are leading candidates for the development of specific markers for cancer diagnosis and therapy.