DNA motifs associated with aberrant CpG island methylation

Genome-wide screening and functional validation of methylation barriers near promoters

CpG islands near promoters are normally unmethylated despite being surrounded by densely methylated regions. Aberrant hypermethylation of these CpG islands has been associated with the development of various human diseases. Although local genetic elements have been speculated to play a role in protecting promoters from methylation, only a limited number of methylation barriers have been identified. In this study, we conducted an integrated computational and experimental investigation of colorectal cancer methylomes. Our study revealed 610 genes with disrupted methylation barriers. Genomic sequences of these barriers shared a common 41-bp sequence motif (MB-41) that displayed homology to the chicken HS4 methylation barrier. Using the CDKN2A (P16) tumor suppressor gene promoter, we validated the protective function of MB-41 and showed that loss of such protection led to aberrant hypermethylation. Our findings highlight a novel sequence signature of cis-acting methylation barriers in the human genome that safeguard promoters from silencing.

CMIC: predicting DNA methylation inheritance of CpG islands with embedding vectors of variable-length k-mers

Background

Epigenetic modifications established in mammalian gametes are largely reprogrammed during early development, however, are partly inherited by the embryo to support its development. In this study, we examine CpG island (CGI) sequences to predict whether a mouse blastocyst CGI inherits oocyte-derived DNA methylation from the maternal genome. Recurrent neural networks (RNNs), including that based on gated recurrent units (GRUs), have recently been employed for variable-length inputs in classification and regression analyses. One advantage of this strategy is the ability of RNNs to automatically learn latent features embedded in inputs by learning their model parameters. However, the available CGI dataset applied for the prediction of oocyte-derived DNA methylation inheritance are not large enough to train the neural networks.

Results

We propose a GRU-based model called CMIC (CGI Methylation Inheritance Classifier) to augment CGI sequence by converting it into variable-length k-mers, where the length k is randomly selected from the range \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$k_{\min }$$\end{document}kmin to \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$k_{\max }$$\end{document}kmax, N times, which were then used as neural network input. N was set to 1000 in the default setting. In addition, we proposed a new embedding vector generator for k-mers called splitDNA2vec. The randomness of this procedure was higher than the previous work, dna2vec.

Conclusions

We found that CMIC can predict the inheritance of oocyte-derived DNA methylation at CGIs in the maternal genome of blastocysts with a high F-measure (0.93). We also show that the F-measure can be improved by increasing the parameter N, that is, the number of sequences of variable-length k-mers derived from a single CGI sequence. This implies the effectiveness of augmenting input data by converting a DNA sequence to N sequences of variable-length k-mers. This approach can be applied to different DNA sequence classification and regression analyses, particularly those involving a small amount of data.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04916-3.

An Unbiased Predictive Model to Detect DNA Methylation Propensity of CpG Islands in the Human Genome

Background:

Epigenetic repression mechanisms play an important role in gene regulation, specifically in cancer development. In many cases, a CpG island’s (CGI) susceptibility or resistance to methylation is shown to be contributed by local DNA sequence features.

Objective:

To develop unbiased machine learning models–individually and combined for different biological features–that predict the methylation propensity of a CGI.

Methods:

We developed our model consisting of CGI sequence features on a dataset of 75 sequences (28 prone, 47 resistant) representing a genome-wide methylation structure. We tested our model on two independent datasets that are chromosome (132 sequences) and disease (70 sequences) specific.

Results:

We provided improvements in prediction accuracy over previous models. Our results indicate that combined features better predict the methylation propensity of a CGI (area under the curve (AUC) ~0.81). Our global methylation classifier performs well on independent datasets reaching an AUC of ~0.82 for the complete model and an AUC of ~0.88 for the model using select sequences that better represent their classes in the training set. We report certain de novo motifs and transcription factor binding site (TFBS) motifs that are consistently better in separating prone and resistant CGIs.

Conclusion:

Predictive models for the methylation propensity of CGIs lead to a better understanding of disease mechanisms and can be used to classify genes based on their tendency to contain methylation prone CGIs, which may lead to preventative treatment strategies. MATLAB® and Python™ scripts used for model building, prediction, and downstream analyses are available at https://github.com/dicleyalcin/methylProp_predictor.

Impacts of Epigenetic Processes on the Health and Productivity of Livestock

The dynamic changes in the epigenome resulting from the intricate interactions of genetic and environmental factors play crucial roles in individual growth and development. Numerous studies in plants, rodents, and humans have provided evidence of the regulatory roles of epigenetic processes in health and disease. There is increasing pressure to increase livestock production in light of increasing food needs of an expanding human population and environment challenges, but there is limited related epigenetic data on livestock to complement genomic information and support advances in improvement breeding and health management. This review examines the recent discoveries on epigenetic processes due to DNA methylation, histone modification, and chromatin remodeling and their impacts on health and production traits in farm animals, including bovine, swine, sheep, goat, and poultry species. Most of the reports focused on epigenome profiling at the genome-wide or specific genic regions in response to developmental processes, environmental stressors, nutrition, and disease pathogens. The bulk of available data mainly characterized the epigenetic markers in tissues/organs or in relation to traits and detection of epigenetic regulatory mechanisms underlying livestock phenotype diversity. However, available data is inadequate to support gainful exploitation of epigenetic processes for improved animal health and productivity management. Increased research effort, which is vital to elucidate how epigenetic mechanisms affect the health and productivity of livestock, is currently limited due to several factors including lack of adequate analytical tools. In this review, we (1) summarize available evidence of the impacts of epigenetic processes on livestock production and health traits, (2) discuss the application of epigenetics data in livestock production, and (3) present gaps in livestock epigenetics research. Knowledge of the epigenetic factors influencing livestock health and productivity is vital for the management and improvement of livestock productivity.

Ultra performance liquid chromatography-tandem mass spectrometry assay for the quantification of RNA and DNA methylation

Previous studies have reported that nucleic acid methylation is a critical element in cardiovascular disease, and most studies mainly focused on sequencing and biochemical research. Here we developed an Ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/ MS) method for the quantification analysis of the dissociative epigenetic modified nucleosides (5mdC, 5mrC, m⁶A) in Myocardial Infarction (MI) SD rats from different periods (1 week, 4 weeks, 8 weeks) after the surgery. The samples for analysis were obtained from heart tissue and blood of the rats. All the quantification results are compared with the sham-operated group. Total RNA and DNA were isolated by enzymatic hydrolytic methods before the UPLC-MS/MS analysis. The statistical analysis demonstrates the dynamic changes of modified nucleosides in MI rats, and it showed good specificity, accuracy, stability and less samples were needed in the method. In this paper, we discovered that the concentration of 5mdC, 5mrC, m⁶A from heart tissue significantly increased at 8 weeks after the surgery. Furthermore, UPLC-MS/MS helps us observe the similar change of the concentration of those 3 methylated biomarkers in peripheral blood after 8 weeks. The result shows that the dynamic process of those 3 methylated biomarkers in peripheral blood is related to the content of methylated biomarkers from the heart tissue. Based on the scientific evidence available, we proved that the methylation of genetic materials in peripheral blood is similar to myocardial infarction tissue. The relation between them indicates that peripheral blood could be a promising alternative to the heart tissue which monitor the level of methylation and MI diagnosis-aided.

A Bayesian Framework for Inferring the Influence of Sequence Context on Point Mutations

The probability of point mutations is expected to be highly influenced by the flanking nucleotides that surround them, known as the sequence context. This phenomenon may be mainly attributed to the enzyme that modifies or mutates the genetic material, because most enzymes tend to have specific sequence contexts that dictate their activity. Here, we develop a statistical model that allows for the detection and evaluation of the effects of different sequence contexts on mutation rates from deep population sequencing data. This task is computationally challenging, as the complexity of the model increases exponentially as the context size increases. We established our novel Bayesian method based on sparse model selection methods, with the leading assumption that the number of actual sequence contexts that directly influence mutation rates is minuscule compared with the number of possible sequence contexts. We show that our method is highly accurate on simulated data using pentanucleotide contexts, even when accounting for noisy data. We next analyze empirical population sequencing data from polioviruses and HIV-1 and detect a significant enrichment in sequence contexts associated with deamination by the cellular deaminases ADAR 1/2 and APOBEC3G, respectively. In the current era, where next-generation sequencing data are highly abundant, our approach can be used on any population sequencing data to reveal context-dependent base alterations and may assist in the discovery of novel mutable sites or editing sites.

DNA sequence context as a marker of CpG methylation instability in normal and cancer tissues

DNA methylation alterations are related to multiple molecular mechanisms. The DNA context of CpG sites plays a crucial role in the maintenance and stability of methylation patterns. The quantitative relationship between DNA composition and DNA methylation has been studied in normal as well as pathological conditions, showing that DNA methylation status is highly dependent on the local sequence context. In this work, we describe this relationship by analyzing the DNA sequence context associated to methylation profiles in both physiological and pathological conditions. In particular, we used DNA motifs to describe methylation stability patterns in normal tissues and aberrant methylation events in cancer lesions. In this manuscript, we show how different groups of DNA sequences can be related to specific epigenetic events, across normal and cancer tissues, and provide a thorough structural and functional characterization of these sequences.

MeinteR: A framework to prioritize DNA methylation aberrations based on conformational and cis-regulatory element enrichment

DNA methylation studies have been reformed with the advent of single-base resolution arrays and bisulfite sequencing methods, enabling deeper investigation of methylation-mediated mechanisms. In addition to these advancements, numerous bioinformatics tools address important computational challenges, covering DNA methylation calling up to multi-modal interpretative analyses. However, contrary to the analytical frameworks that detect driver mutational signatures, the identification of putatively actionable epigenetic events remains an unmet need. The present work describes a novel computational framework, called MeinteR, that prioritizes critical DNA methylation events based on the following hypothesis: critical aberrations of DNA methylation more likely occur on a genomic substrate that is enriched in cis-acting regulatory elements with distinct structural characteristics, rather than in genomic “deserts”. In this context, the framework incorporates functional cis-elements, e.g. transcription factor binding sites, tentative splice sites, as well as conformational features, such as G-quadruplexes and palindromes, to identify critical epigenetic aberrations with potential implications on transcriptional regulation. The evaluation on multiple, public cancer datasets revealed significant associations between the highest-ranking loci with gene expression and known driver genes, enabling for the first time the computational identification of high impact epigenetic changes based on high-throughput DNA methylation data.

EAT-Rice: A predictive model for flanking gene expression of T-DNA insertion activation-tagged rice mutants by machine learning approaches

T-DNA activation-tagging technology is widely used to study rice gene functions. When T-DNA inserts into genome, the flanking gene expression may be altered using CaMV 35S enhancer, but the affected genes still need to be validated by biological experiment. We have developed the EAT-Rice platform to predict the flanking gene expression of T-DNA insertion site in rice mutants. The three kinds of DNA sequences including UPS1K, DISTANCE, and MIDDLE were retrieved to encode and build a forecast model of two-layer machine learning. In the first-layer models, the features nucleotide context (N-gram), cis-regulatory elements (Motif), nucleotide physicochemical properties (NPC), and CG-island (CGI) were used to build SVM models by analysing the concealed information embedded within the three kinds of sequences. Logistic regression was used to estimate the probability of gene activation which as feature-encoding weighting within first-layer model. In the second-layer models, the NaiveBayesUpdateable algorithm was used to integrate these first layer-models, and the system performance was 88.33% on 5-fold cross-validation, and 79.17% on independent-testing finally. In the three kinds of sequences, the model constructed by Middle had the best contribution to the system for identifying the activated genes. The EAT-Rice system provided better performance and gene expression prediction at further distances when compared to the TRIM database. An online server based on EAT-rice is available at http://predictor.nchu.edu.tw/EAT-Rice.

Enhanced sensitivity of CpG island search and primer design based on predicted CpG island position

DNA methylation has important biological roles, such as gene expression regulation, as well as practical applications in forensics, such as in body fluid identification and age estimation. DNA methylation often occurs in the CpG site, and methylation within the CpG islands affects various cellular functions and is related to tissue-specific identification. Several programs have been developed to identify CpG islands; however, the size, location, and number of predicted CpG islands are not identical due to different search algorithms. In addition, they only provide structural information for predicted CpG islands without experimental information, such as primer design. We developed an analysis pipeline package, CpGPNP, to integrate CpG island prediction and primer design. CpGPNP predicts CpG islands more accurately and sensitively than other programs, and designs primers easily based on the predicted CpG island locations. The primer design function included standard, bisulfite, and methylation-specific PCR to identify the methylation of particular CpG sites. In this study, we performed CpG island prediction on all chromosomes and compared CpG island search performance of CpGPNP with other CpG island prediction programs. In addition, we compared the position of primers designed for a specific region within the predicted CpG island using other bisulfite PCR primer programs. The primers designed by CpGPNP were used to experimentally verify the amplification of the target region of markers for body fluid identification and age estimation. CpGPNP is freely available at http://forensicdna.kr/cpgpnp/.

Genome wide classification and characterisation of CpG sites in cancer and normal cells

This study identifies common methylation patterns across different cancer types in an effort to identify common molecular events in diverse types of cancer cells and provides evidence for the sequence surrounding a CpG to influence its susceptibility to aberrant methylation. CpG sites throughout the genome were divided into four classes: sites that either become hypo or hyper-methylated in a variety cancers using all the freely available microarray data (HypoCancer and HyperCancer classes) and those found in a constant hypo (Never methylated class) or hyper-methylated (Always methylated class) state in both normal and cancer cells. Our data shows that most CpG sites included in the HumanMethylation450K microarray remain unmethylated in normal and cancerous cells; however, certain sites in all the cancers investigated become specifically modified. More detailed analysis of the sites revealed that majority of those in the never methylated class were in CpG islands whereas those in the HyperCancer class were mostly associated with miRNA coding regions. The sites in the Hypermethylated class are associated with genes involved in initiating or maintaining the cancerous state, being enriched for processes involved in apoptosis, and with transcription factors predicted to bind to these genes linked to apoptosis and tumourgenesis (notably including E2F). Further we show that more LINE elements are associated with the HypoCancer class and more Alu repeats are associated with the HyperCancer class. Motifs that classify the classes were identified to distinguish them based on the surrounding DNA sequence alone, and for the identification of DNA sequences that could render sites more prone to aberrant methylation in cancer cells. This provides evidence that the sequence surrounding a CpG site has an influence on whether a site is hypo or hyper methylated.

Epigenetics in head and neck cancer

Epigenetics refers to the study of heritable changes in gene expression that occur without a change in DNA sequence. Research has shown that epigenetic mechanisms provide an "extra" layer of transcriptional control that regulates how genes are expressed. These mechanisms are critical components in the normal development and growth of cells. Epigenetic abnormalities have been found to be causative factors in cancer, genetic disorders, and pediatric syndromes. Head and neck cancers are a group of malignancies with diverse biological behaviors and a strong, well-established association with environmental effects. Although the hunt for genetic alterations in head and neck cancer has continued in the past two decades, with unequivocal proof of a genetic role in multistage head and neck carcinogenesis, epigenetic alteration in association with promoter CpG islands hypermethylation has emerged in the past few years as one of the most active areas of cancer research. Silencing of the genes by hypermethylation or induction of oncogenes by promoter hypomethylation is a frequent mechanism in head and neck cancer and achieves increasing diagnostic and therapeutic importance. In this context it is important for clinicians to understand the principles of epigenetic mechanisms and how these principles relate to human health and disease. It is important to address the use of epigenetic pathways in new approaches to molecular diagnosis and novel targeted treatments across the clinical spectrum.

Direct observation of preferential processing of clustered abasic DNA damages with APE1 in TATA box and CpG island by reaction kinetics and fluorescence dynamics

Sequences like the core element of TATA box and CpG island are frequently encountered in the genome and related to transcription. The fate of repair of clustered abasic sites in such sequences of genomic importance is largely unknown. This prompted us to investigate the sequence dependence of cleavage efficiency of APE1 enzyme at abasic sites within the core sequences of TATA box and CpG island using fluorescence dynamics and reaction kinetics. Simultaneous molecular dynamics study through steady state and time resolved fluorescence spectroscopy using unique ethidium bromide dye release assay confirmed an elevated amount of abasic site cleavage of the TATA box sequence as compared to the core CpG island. Reaction kinetics showed that catalytic efficiency of APE1 for abasic site cleavage of core CpG island sequence was ∼4 times lower as compared to that of the TATA box. Higher value of Km was obtained from the core CpG island sequence than the TATA box sequence. This suggests a greater binding effect of APE1 enzyme on TATA sequence that signifies a prominent role of the sequence context of the DNA substrate. Evidently, a faster response from APE1 was obtained for clustered abasic damage repair of TATA box core sequences than CpG island consensus sequences. The neighboring bases of the abasic sites in the complementary DNA strand were found to have significant contribution in addition to the flanking bases in modulating APE1 activity. The repair refractivity of the bistranded clustered abasic sites arise from the slow processing of the second abasic site, consequently resulting in decreased overall production of potentially lethal double strand breaks.

Identification of genomic features in environmentally induced epigenetic transgenerational inherited sperm epimutations

A variety of environmental toxicants have been shown to induce the epigenetic transgenerational inheritance of disease and phenotypic variation. The process involves exposure of a gestating female and the developing fetus to environmental factors that promote permanent alterations in the epigenetic programming of the germline. The molecular aspects of the phenomenon involve epigenetic modifications (epimutations) in the germline (e.g. sperm) that are transmitted to subsequent generations. The current study integrates previously described experimental epigenomic transgenerational data and web-based bioinformatic analyses to identify genomic features associated with these transgenerationally transmitted epimutations. A previously identified genomic feature associated with these epimutations is a low CpG density (<12/100bp). The current observations suggest the transgenerational differential DNA methylation regions (DMR) in sperm contain unique consensus DNA sequence motifs, zinc finger motifs and G-quadruplex sequences. Interaction of molecular factors with these sequences could alter chromatin structure and accessibility of proteins with DNA methyltransferases to alter de novo DNA methylation patterns. G-quadruplex regions can promote the opening of the chromatin that may influence the action of DNA methyltransferases, or factors interacting with them, for the establishment of epigenetic marks. Zinc finger binding factors can also promote this chromatin remodeling and influence the expression of non-coding RNA. The current study identified genomic features associated with sperm epimutations that may explain in part how these sites become susceptible for transgenerational programming.

Variants of a Thermus aquaticus DNA polymerase with increased selectivity for applications in allele- and methylation-specific amplification

The selectivity of DNA polymerases is crucial for many applications. For example, high discrimination between the extension of matched versus mismatched primer termini is desired for the detection of a single nucleotide variation at a particular locus within the genome. Here we describe the generation of thermostable mutants of the large fragment of Thermus aquaticus DNA polymerase (KlenTaq) with increased mismatch extension selectivity. In contrast to previously reported much less active KlenTaq mutants with mismatch discrimination abilities, many of the herein discovered mutants show conserved wild-type-like high activities. We demonstrate for one mutant containing the single amino acid exchange R660V the suitability for application in allele-specific amplifications directly from whole blood without prior sample purification. Also the suitability of the mutant for methylation specific amplification in the diagnostics of 5-methyl cytosines is demonstrated. Furthermore, the identified mutant supersedes other commercially available enzymes in human leukocyte antigen (HLA) analysis by sequence-specific primed polymerase chain reactions (PCRs).

Comparative (computational) analysis of the DNA methylation status of trinucleotide repeat expansion diseases

Previous studies have examined DNA methylation in different trinucleotide repeat diseases. We have combined this data and used a pattern searching algorithm to identify motifs in the DNA surrounding aberrantly methylated CpGs found in the DNA of patients with one of the three trinucleotide repeat (TNR) expansion diseases: fragile X syndrome (FRAXA), myotonic dystrophy type I (DM1), or Friedreich's ataxia (FRDA). We examined sequences surrounding both the variably methylated (VM) CpGs, which are hypermethylated in patients compared with unaffected controls, and the nonvariably methylated CpGs which remain either always methylated (AM) or never methylated (NM) in both patients and controls. Using the J48 algorithm of WEKA analysis, we identified that two patterns are all that is necessary to classify our three regions CCGG∗ which is found in VM and not in AM regions and AATT∗ which distinguished between NM and VM + AM using proportional frequency. Furthermore, comparing our software with MEME software, we have demonstrated that our software identifies more patterns than MEME in these short DNA sequences. Thus, we present evidence that the DNA sequence surrounding CpG can influence its susceptibility to be de novo methylated in a disease state associated with a trinucleotide repeat.

GC skew at the 5' and 3' ends of human genes links R-loop formation to epigenetic regulation and transcription termination

Strand asymmetry in the distribution of guanines and cytosines, measured by GC skew, predisposes DNA sequences toward R-loop formation upon transcription. Previous work revealed that GC skew and R-loop formation associate with a core set of unmethylated CpG island (CGI) promoters in the human genome. Here, we show that GC skew can distinguish four classes of promoters, including three types of CGI promoters, each associated with unique epigenetic and gene ontology signatures. In particular, we identify a strong and a weak class of CGI promoters and show that these loci are enriched in distinct chromosomal territories reflecting the intrinsic strength of their protection against DNA methylation. Interestingly, we show that strong CGI promoters are depleted from the X chromosome while weak CGIs are enriched, a property consistent with the acquisition of DNA methylation during dosage compensation. Furthermore, we identify a third class of CGI promoters based on its unique GC skew profile and show that this gene set is enriched for Polycomb group targets. Lastly, we show that nearly 2000 genes harbor GC skew at their 3′ ends and that these genes are preferentially located in gene-dense regions and tend to be closely arranged. Genomic profiling of R-loops accordingly showed that a large proportion of genes with terminal GC skew form R-loops at their 3′ ends, consistent with a role for these structures in permitting efficient transcription termination. Altogether, we show that GC skew and R-loop formation offer significant insights into the epigenetic regulation, genomic organization, and function of human genes.

Prediction of Epigenetic Target Sites by Using Genomic DNA Sequence

Epigenetic regulation provides an extra layer of gene control in addition to the genomic sequence and is critical for the maintenance of cell-type specific gene expression programs. Significant changes of epigenetic patterns have been linked to developmental stages, environmental exposure, ageing, and diet. However, the regulatory mechanisms for epigenetic recruitment, maintenance, and switch are still poorly understood. Computational biology provides tools to deeply uncover hidden connections and these tools have played a major role in shaping the current understanding of gene regulation, but its application in epigenetics is still in the infancy. This chapter reviews some recent developments of computational approaches to predict epigenetic target sites.

3-D DNA methylation phenotypes correlate with cytotoxicity levels in prostate and liver cancer cell models

Background

The spatial organization of the genome is being evaluated as a novel indicator of toxicity in conjunction with drug-induced global DNA hypomethylation and concurrent chromatin reorganization. 3D quantitative DNA methylation imaging (3D-qDMI) was applied as a cell-by-cell high-throughput approach to investigate this matter by assessing genome topology through represented immunofluorescent nuclear distribution patterns of 5-methylcytosine (MeC) and global DNA (4,6-diamidino-2-phenylindole = DAPI) in labeled nuclei.

Methods

Differential progression of global DNA hypomethylation was studied by comparatively dosing zebularine (ZEB) and 5-azacytidine (AZA). Treated and untreated (control) human prostate and liver cancer cells were subjected to confocal scanning microscopy and dedicated 3D image analysis for the following features: differential nuclear MeC/DAPI load and codistribution patterns, cell similarity based on these patterns, and corresponding differences in the topology of low-intensity MeC (LIM) and low in intensity DAPI (LID) sites.

Results

Both agents generated a high fraction of similar MeC phenotypes across applied concentrations. ZEB exerted similar effects at 10–100-fold higher drug concentrations than its AZA analogue: concentration-dependent progression of global cytosine demethylation, validated by measuring differential MeC levels in repeat sequences using MethyLight, and the concurrent increase in nuclear LIM densities correlated with cellular growth reduction and cytotoxicity.

Conclusions

3D-qDMI demonstrated the capability of quantitating dose-dependent drug-induced spatial progression of DNA demethylation in cell nuclei, independent from interphase cell-cycle stages and in conjunction with cytotoxicity. The results support the notion of DNA methylation topology being considered as a potential indicator of causal impacts on chromatin distribution with a conceivable application in epigenetic drug toxicology.

The landscape of DNA repeat elements in human heart failure

BACKGROUND

The epigenomes of healthy and diseased human hearts were recently examined by genome-wide DNA methylation profiling. Repetitive elements, heavily methylated in post-natal tissue, have variable methylation profiles in cancer but methylation of repetitive elements in the heart has never been examined.

RESULTS

We analyzed repetitive elements from all repeat families in human myocardial samples, and found that satellite repeat elements were significantly hypomethylated in end-stage cardiomyopathic hearts relative to healthy normal controls. Satellite repeat elements are almost always centromeric or juxtacentromeric, and their overexpression correlates with disease aggressiveness in cancer. Similarly, we found that hypomethylation of satellite repeat elements correlated with up to 27-fold upregulation of the corresponding transcripts in end-stage cardiomyopathic hearts. No other repeat family exhibited differential methylation between healthy and cardiomyopathic hearts, with the exception of the Alu element SINE1/7SL, for which a modestly consistent trend of increased methylation was observed.

CONCLUSIONS

Satellite repeat element transcripts, a form of non-coding RNA, have putative functions in maintaining genomic stability and chromosomal integrity. Further studies will be needed to establish the functional significance of these non-coding RNAs in the context of heart failure.

SINE retrotransposons cause epigenetic reprogramming of adjacent gene promoters

Almost half of the human genome and as much as 40% of the mouse genome is composed of repetitive DNA sequences. The majority of these repeats are retrotransposons of the SINE and LINE families, and such repeats are generally repressed by epigenetic mechanisms. It has been proposed that these elements can act as methylation centers from which DNA methylation spreads into gene promoters in cancer. Contradictory to a methylation center function, we have found that retrotransposons are enriched near promoter CpG islands that stay methylation-free in cancer. Clearly, it is important to determine which influence, if any, these repetitive elements have on nearby gene promoters. Using an in vitro system, we confirm here that SINE B1 elements can influence the activity of downstream gene promoters, with acquisition of DNA methylation and loss of activating histone marks, thus resulting in a repressed state. SINE sequences themselves did not immediately acquire DNA methylation but were marked by H3K9me2 and H3K27me3. Moreover, our bisulfite sequencing data did not support that gain of DNA methylation in gene promoters occurred by methylation spreading from SINE B1 repeats. Genome-wide analysis of SINE repeats distribution showed that their enrichment is directly correlated with the presence of USF1, USF2, and CTCF binding, proteins with insulator function. In summary, our work supports the concept that SINE repeats interfere negatively with gene expression and that their presence near gene promoters is counter-selected, except when the promoter is protected by an insulator element.

Gene silencing of EREG mediated by DNA methylation and histone modification in human gastric cancers

Epiregulin (EREG) induces cell growth by binding to the epidermal growth factor receptor (EGFR). Expression of EREG affects sensitivity to cetuximab a chimeric monoclonal antibody that inhibits the EGFR signaling pathway. The mechanism through which EREG is regulated is largely unknown, but a methyl-array study previously performed by our group revealed that EREG is methylated in gastric cancer cells. In this study, we found that EREG gene expression was low in 7 out of 11 gastric cancer cells and this downregulation was mediated by aberrant CpG methylation of the EREG promoter. Treatment with 5-aza-CdR restored EREG expression and demethylated CpG sites in the EREG promoter. Compared with DNA methyltransferase 1 (DNMT1), knock-down of DNA methyltransferase 3b (DNMT3b) significantly increased the expression of EREG and led to the demethylation of specific CpG sites in the EREG promoter, suggesting that DNMT3b primarily regulates CpG methylation and silencing of the EREG gene. EREG methylation was observed in 30% (4/13) of human primary gastric tumor tissues we evaluated. In addition to DNA methylation, results from a chromatin immunoprecipitation assay demonstrated that transcriptional levels of EREG were associated with the enrichment of active histone marks (H3K4me3 and AcH3) and of a repressive mark (H3K27me2). Treatment with 5-aza-CdR dynamically increased the low occupancy of H3K4me3 and AcH3, while decreasing the high enrichment of H3K27me2, indicating that dynamic histone modifications contribute to EREG regulation in addition to DNA methylation. Finally, the combination of 5-aza-CdR and cetuximab exerted a synergistic anti-proliferative effect on gastric cancer cells. Taken together, the results of our study showed for the first time that EREG is epigenetically silenced in gastric cancer cells by aberrant DNA methylation and histone modification.

Environmental epigenetics: prospects for studying epigenetic mediation of exposure-response relationships

Changes in epigenetic marks such as DNA methylation and histone acetylation are associated with a broad range of disease traits, including cancer, asthma, metabolic disorders, and various reproductive conditions. It seems plausible that changes in epigenetic state may be induced by environmental exposures such as malnutrition, tobacco smoke, air pollutants, metals, organic chemicals, other sources of oxidative stress, and the microbiome, particularly if the exposure occurs during key periods of development. Thus, epigenetic changes could represent an important pathway by which environmental factors influence disease risks, both within individuals and across generations. We discuss some of the challenges in studying epigenetic mediation of pathogenesis and describe some unique opportunities for exploring these phenomena.

A novel k-mer mixture logistic regression for methylation susceptibility modeling of CpG dinucleotides in human gene promoters

Background

DNA methylation is essential for normal development and differentiation and plays a crucial role in the development of nearly all types of cancer. Aberrant DNA methylation patterns, including genome-wide hypomethylation and region-specific hypermethylation, are frequently observed and contribute to the malignant phenotype. A number of studies have recently identified distinct features of genomic sequences that can be used for modeling specific DNA sequences that may be susceptible to aberrant CpG methylation in both cancer and normal cells. Although it is now possible, using next generation sequencing technologies, to assess human methylomes at base resolution, no reports currently exist on modeling cell type-specific DNA methylation susceptibility. Thus, we conducted a comprehensive modeling study of cell type-specific DNA methylation susceptibility at three different resolutions: CpG dinucleotides, CpG segments, and individual gene promoter regions.

Results

Using a k-mer mixture logistic regression model, we effectively modeled DNA methylation susceptibility across five different cell types. Further, at the segment level, we achieved up to 0.75 in AUC prediction accuracy in a 10-fold cross validation study using a mixture of k-mers.

Conclusions

The significance of these results is three fold: 1) this is the first report to indicate that CpG methylation susceptible "segments" exist; 2) our model demonstrates the significance of certain k-mers for the mixture model, potentially highlighting DNA sequence features (k-mers) of differentially methylated, promoter CpG island sequences across different tissue types; 3) as only 3 or 4 bp patterns had previously been used for modeling DNA methylation susceptibility, ours is the first demonstration that 6-mer modeling can be performed without loss of accuracy.

Linking genome to epigenome

Recent epigenomic studies have identified significant differences between developmental stages and cell types. While the importance of epigenetic regulation has been increasingly recognized, it remains unclear how the global epigenetic patterns are established and maintained. Here I review a number of recent studies with the emphasis on the role of the genomic sequence in shaping the epigenetic landscape. These studies strongly suggest that the sequence information is important not just for controlling target specificity but for orchestrating the diversity of epigenetic patterns among different cell types. The epigenome is maintained by the complex network of a large number of interactions. Integrative approaches are needed to gain insights into these networks.

Epigenetics and colorectal cancer

Colorectal cancer (CRC) is a leading cause of cancer deaths worldwide. It results from an accumulation of genetic and epigenetic changes in colon epithelial cells, which transforms them into adenocarcinomas. Over the past decade, major advances have been made in understanding cancer epigenetics, particularly regarding aberrant DNA methylation. Assessment of the colon cancer epigenome has revealed that virtually all CRCs have aberrantly methylated genes and that the average CRC methylome has hundreds to thousands of abnormally methylated genes. As with gene mutations in the cancer genome, a subset of these methylated genes, called driver genes, is presumed to have a functional role in CRC. The assessment of methylated genes in CRCs has also revealed a unique molecular subgroup of CRCs called CpG island methylator phenotype (CIMP) cancers; these tumors have a particularly high frequency of methylated genes. These advances in our understanding of aberrant methylation in CRC have led to epigenetic alterations being developed as clinical biomarkers for diagnostic, prognostic and therapeutic applications. Progress in this field suggests that these epigenetic alterations will be commonly used in the near future to direct the prevention and treatment of CRC.

Analysis of promoter CpG island hypermethylation in cancer: location, location, location!

The genetic and epigenetic alterations that underlie cancer pathogenesis are rapidly being identified. This provides novel insights in tumor biology as well as in potential cancer biomarkers. The somatic mutations in cancer genes that have been implemented in clinical practice are well defined and very specific. For epigenetic alterations, and more specifically aberrant methylation of promoter CpG islands, evidence is emerging that these markers could be used for the early detection of cancer as well as prediction of prognosis and response to therapy. However, the exact location of biologically and clinically relevant hypermethylation has not been identified for the majority of methylation markers. The most widely used approaches to analyze DNA methylation are based on primer- and probe-based assays that provide information for a limited number of CpG dinucleotides and thus for only part of the information available in a given CpG island. Validation of the current data and implementation of hypermethylation markers in clinical practice require a more comprehensive and critical evaluation of DNA methylation and limitations of the techniques currently used in methylation marker research. Here, we discuss the emerging evidence on the importance of the location of CpG dinucleotide hypermethylation in relation to gene expression and associations with clinicopathologic characteristics in cancer.

Reconstructing the ancestral germ line methylation state of young repeats

One of the key objectives of comparative genomics is the characterization of the forces that shape genomes over the course of evolution. In the last decades, evidence has been accumulated that for vertebrate genomes also epigenetic modifications have to be considered in this context. Especially, the elevated mutation frequency of 5-methylcytosine (5mC) is assumed to facilitate the depletion of CpG dinucleotides in species that exhibit global DNA methylation. For instance, the underrepresentation of CpG dinucleotides in many mammalian genomes is attributed to this effect, which is only neutralized in so-called CpG islands (CGIs) that are preferentially unmethylated and thus partially protected from rapid CpG decay. For primate-specific CpG-rich transposable elements from the ALU family, it is unclear whether their elevated CpG frequency is caused by their small age or by the absence of DNA methylation. In consequence, these elements are often misclassified in CGI annotations. We present a method for the estimation of germ line methylation from pairwise ancestral-descendant alignments. The approach is validated in a simulation study and tested on DNA repeats from the AluSx family. We conclude that a predicted unmethylated state in the germ line is highly correlated with epigenetic activity of the respective genomic region. Thus, CpG-rich repeats can be facilitated as in silico probes for the epigenetic potential of their genomic neighborhood.

Genome architecture marked by retrotransposons modulates predisposition to DNA methylation in cancer

Epigenetic silencing plays an important role in cancer development. An attractive hypothesis is that local DNA features may participate in differential predisposition to gene hypermethylation. We found that, compared with methylation-resistant genes, methylation-prone genes have a lower frequency of SINE and LINE retrotransposons near their transcription start site. In several large testing sets, this distribution was highly predictive of promoter methylation. Genome-wide analysis showed that 22% of human genes were predicted to be methylation-prone in cancer; these tended to be genes that are down-regulated in cancer and that function in developmental processes. Moreover, retrotransposon distribution marks a larger fraction of methylation-prone genes compared to Polycomb group protein (PcG) marking in embryonic stem cells; indeed, PcG marking and our predictive model based on retrotransposon frequency appear to be correlated but also complementary. In summary, our data indicate that retrotransposon elements, which are widespread in our genome, are strongly associated with gene promoter DNA methylation in cancer and may in fact play a role in influencing epigenetic regulation in normal and abnormal physiological states.

Epigenetic transgenerational actions of vinclozolin on promoter regions of the sperm epigenome

Previous observations have demonstrated that embryonic exposure to the endocrine disruptor vinclozolin during gonadal sex determination promotes transgenerational adult onset disease such as male infertility, kidney disease, prostate disease, immune abnormalities and tumor development. The current study investigates genome-wide promoter DNA methylation alterations in the sperm of F3 generation rats whose F0 generation mother was exposed to vinclozolin. A methylated DNA immunoprecipitation with methyl-cytosine antibody followed by a promoter tilling microarray (MeDIP-Chip) procedure was used to identify 52 different regions with statistically significant altered methylation in the sperm promoter epigenome. Mass spectrometry bisulfite analysis was used to map the CpG DNA methylation and 16 differential DNA methylation regions were confirmed, while the remainder could not be analyzed due to bisulfite technical limitations. Analysis of these validated regions identified a consensus DNA sequence (motif) that associated with 75% of the promoters. Interestingly, only 16.8% of a random set of 125 promoters contained this motif. One candidate promoter (Fam111a) was found to be due to a copy number variation (CNV) and not a methylation change, suggesting initial alterations in the germline epigenome may promote genetic abnormalities such as induced CNV in later generations. This study identifies differential DNA methylation sites in promoter regions three generations after the initial exposure and identifies common genome features present in these regions. In addition to primary epimutations, a potential indirect genetic abnormality was identified, and both are postulated to be involved in the epigenetic transgenerational inheritance observed. This study confirms that an environmental agent has the ability to induce epigenetic transgenerational changes in the sperm epigenome.

Guanine quadruplex DNA structure restricts methylation of CpG dinucleotides genome-wide

Cytosine methylation in mammals is important for epigenetic control of the transcriptome. Although altered methylation is frequently encountered in disease situations, particularly cancer, the relationship between genome-wide methylation and DNA structure is poorly understood. It is now evident that alternative DNA forms are functionally relevant in replication, recombination and transcription. Herein, we researched the role of alternative DNA structure in cytosine methylation using quadruplex DNA as a case study. Our findings from analysis of 2.1 million CpGs in humans, across 12 tissues from the Human Epigenome Project (HEP), revealed a striking correlation within each tissue: CpGs with low methylation were enriched (P = 5.24E(-20)) whereas CpGs with high methylation were relatively depleted (P = 9.28E(-15)), within quadruplex-forming regions. This was further substantiated on considering 1.07E(8) methylcytosines from genome-wide sequencing within embryonic stem cells and differentiated fibroblasts. To further test the predictions we experimentally determined methylation in >600,000 CpGs across 18 individuals using bisulfite mapping and found significantly low methylation of CpGs within quadruplex-forming regions (P = 1.36E(-08)). Together, these suggest the role of guanine-quadruplexes in CpG methylation and directly impact our understanding of the inter-relationship between DNA conformation and global cytosine methylation.

Estrogen-mediated epigenetic repression of large chromosomal regions through DNA looping

The current concept of epigenetic repression is based on one repressor unit corresponding to one silent gene. This notion, however, cannot adequately explain concurrent silencing of multiple loci observed in large chromosome regions. The long-range epigenetic silencing (LRES) can be a frequent occurrence throughout the human genome. To comprehensively characterize the influence of estrogen signaling on LRES, we analyzed transcriptome, methylome, and estrogen receptor alpha (ESR1)-binding datasets from normal breast epithelia and breast cancer cells. This "omics" approach uncovered 11 large repressive zones (range, 0.35 approximately 5.98 megabases), including a 14-gene cluster located on 16p11.2. In normal cells, estrogen signaling induced transient formation of multiple DNA loops in the 16p11.2 region by bringing 14 distant loci to focal ESR1-docking sites for coordinate repression. However, the plasticity of this free DNA movement was reduced in breast cancer cells. Together with the acquisition of DNA methylation and repressive chromatin modifications at the 16p11.2 loci, an inflexible DNA scaffold may be a novel determinant used by breast cancer cells to reinforce estrogen-mediated repression.

HOXB13, a target of DNMT3B, is methylated at an upstream CpG island, and functions as a tumor suppressor in primary colorectal tumors

BACKGROUND

A hallmark of cancer cells is hypermethylation of CpG islands (CGIs), which probably arises from upregulation of one or more DNA methyltransferases. The purpose of this study was to identify the targets of DNMT3B, an essential DNA methyltransferase in mammals, in colon cancer.

METHODOLOGY/PRINCIPAL FINDINGS

Chromatin immunoprecipitation with DNMT3B specific antibody followed by CGI microarray identified genes with or without CGIs, repeat elements and genomic contigs in RKO cells. ChIP-Chop analysis showed that the majority of the target genes including P16, DCC, DISC1, SLIT1, CAVEOLIN1, GNA11, TBX5, TBX18, HOXB13 and some histone variants, that harbor CGI in their promoters, were methylated in multiple colon cancer cell lines but not in normal colon epithelial cells. Further, these genes were reactivated in RKO cells after treatment with 5-aza-2'-deoxycytidine, a DNA hypomethylating agent. COBRA showed that the CGIs encompassing the promoter and/or coding region of DCC, TBX5, TBX18, SLIT1 were methylated in primary colorectal tumors but not in matching normal colon tissues whereas GNA11 was methylated in both. MassARRAY analysis demonstrated that the CGI located approximately 4.5 kb upstream of HOXB13 +1 site was tumor-specifically hypermethylated in primary colorectal cancers and cancer cell lines. HOXB13 upstream CGI was partially hypomethylated in DNMT1(-/-) HCT cells but was almost methylation free in cells lacking both DNMT1 and DNMT3B. Analysis of tumor suppressor properties of two aberrantly methylated transcription factors, HOXB13 and TBX18, revealed that both inhibited growth and clonogenic survival of colon cancer cells in vitro, but only HOXB13 abolished tumor growth in nude mice.

CONCLUSIONS/SIGNIFICANCE

This is the first report that identifies several important tumor suppressors and transcription factors as direct DNMT3B targets in colon cancer and as potential biomarkers for this cancer. Further, this study shows that methylation at an upstream CGI of HOXB13 is unique to colon cancer.

Breast cancer epigenetics: from DNA methylation to microRNAs

Both appropriate DNA methylation and histone modifications play a crucial role in the maintenance of normal cell function and cellular identity. In cancerous cells these "epigenetic belts" become massively perturbed, leading to significant changes in expression profiles which confer advantage to the development of a malignant phenotype. DNA (cytosine-5)-methyltransferase 1 (Dnmt1), Dnmt3a and Dnmt3b are the enzymes responsible for setting up and maintaining DNA methylation patterns in eukaryotic cells. Intriguingly, DNMTs were found to be overexpressed in cancerous cells, which is believed to partly explain the hypermethylation phenomenon commonly observed in tumors. However, several lines of evidence indicate that further layers of gene regulation are critical coordinators of DNMT expression, catalytic activity and target specificity. Splice variants of DNMT transcripts have been detected which seem to modulate methyltransferase activity. Also, the DNMT mRNA 3'UTR as well as the coding sequence harbors multiple binding sites for trans-acting factors guiding post-transcriptional regulation and transcript stabilization. Moreover, microRNAs targeting DNMT transcripts have recently been discovered in normal cells, yet expression of these microRNAs was found to be diminished in breast cancer tissues. In this review we summarize the current knowledge on mechanisms which potentially lead to the establishment of a DNA hypermethylome in cancer cells.

DNA methylation: an introduction to the biology and the disease-associated changes of a promising biomarker

DNA methylation occurring on the 5 position of the pyrimidine ring of cytosines in the context of the dinucleotide sequence CpG forms one of the multiple layers of epigenetic mechanisms controlling and modulating gene expression through chromatin structure. It closely interacts with histone modifications and chromatin remodeling complexes to form the genomic chromatin landscape. DNA methylation is essential for proper mammalian development, crucial for imprinting and plays a role in maintaining genomic stability as well as in dosage compensation. DNA methylation patterns are susceptible to change in response to environmental stimuli such as diet or toxins, whereby the epigenome seems to be most vulnerable during early in utero development. Aberrant DNA methylation changes have been detected in several diseases, particularly cancer where genome-wide hypomethylation coincides with genespecific hypermethylation. DNA methylation patterns can be used to detect cancer at very early stages, to classify tumors as well as predict and monitor the response to antineoplastic treatment. As a stable nucleic-acid-based modification with limited dynamic range that is technically easy to handle, DNA methylation is a promising biomarker for many applications.

Consolidation of the cancer genome into domains of repressive chromatin by long-range epigenetic silencing (LRES) reduces transcriptional plasticity

Silencing of individual genes can occur by genetic and epigenetic processes during carcinogenesis, but the underlying mechanisms remain unclear. By creating an integrated prostate cancer epigenome map using tiling arrays, we show that contiguous regions of gene suppression commonly occur through long-range epigenetic silencing (LRES). We identified 47 LRES regions in prostate cancer, typically spanning about 2 Mb and harbouring approximately 12 genes, with a prevalence of tumour suppressor and miRNA genes. Our data reveal that LRES is associated with regional histone deacetylation combined with subdomains of different epigenetic remodelling patterns, which include re-enforcement, gain or exchange of repressive histone, and DNA methylation marks. The transcriptional and epigenetic state of genes in normal prostate epithelial and human embryonic stem cells can play a critical part in defining the mode of cancer-associated epigenetic remodelling. We propose that consolidation or effective reduction of the cancer genome commonly occurs in domains through a combination of LRES and LOH or genomic deletion, resulting in reduced transcriptional plasticity within these regions.

Genome-wide methylation and expression profiling identifies promoter characteristics affecting demethylation-induced gene up-regulation in melanoma

Background

Abberant DNA methylation at CpG dinucleotides represents a common mechanism of transcriptional silencing in cancer. Since CpG methylation is a reversible event, tumor supressor genes that have undergone silencing through this mechanism represent promising targets for epigenetically active anti-cancer therapy. The cytosine analog 5-aza-2'-deoxycytidine (decitabine) induces genomic hypomethylation by inhibiting DNA methyltransferase, and is an example of an epigenetic agent that is thought to act by up-regulating silenced genes.

Methods

It is unclear why decitabine causes some silenced loci to re-express, while others remain inactive. By applying data-mining techniques to large-scale datasets, we attempted to elucidate the qualities of promoter regions that define susceptibility to the drug's action. Our experimental data, derived from melanoma cell strains, consist of genome-wide gene expression data before and after treatment with decitabine, as well as genome-wide data on un-treated promoter methylation status, and validation of specific genes by bisulfite sequencing.

Results

We show that the combination of promoter CpG content and methylation level informs the ability of decitabine treatment to up-regulate gene expression. Promoters with high methylation levels and intermediate CpG content appear most susceptible to up-regulation by decitabine, whereas few of those highly methylated promoters with high CpG content are up-regulated. For promoters with low methylation levels, those with high CpG content are more likely to be up-regulated, whereas those with low CpG content are underrepresented among up-regulated genes.

Conclusions

Clinically, elucidating the patterns of action of decitabine could aid in predicting the likelihood of up-regulating epigenetically silenced tumor suppressor genes and others from pathways involved with tumor biology. As a first step toward an eventual translational application, we build a classifier to predict gene up-regulation based on promoter methylation and CpG content, which achieves a performance of 0.77 AUC.

DNA hypermethylation accompanied by transcriptional repression in follicular lymphoma

High-throughput microarray technologies were used to study DNA methylation accompanied by transcriptional changes in follicular lymphoma (FL). Using Methylated CpG Island Amplification with Microarrays to study CpG Island DNA methylation in FL, we discovered widespread hypermethylation of homeobox genes and previously identified targets of polycomb repressive complex 2 (PRC2) in cell lines and primary tumors, but not in benign follicular hyperplasia (BFH). DNA methylation for HOXA11, HOXD10, HOXB7, HOXC12, PAX6, LHX9, SFMBT2, EN2, and PAX7 was independently validated in the RL cell line and HOXA11, HOXD10, PAX6, and EN2 in primary tumors. Combined Bisulfite Restriction Analysis (COBRA) also established DNA methylation for the previously identified PRC2 targets DCC, DES, GAD2, AQP5, GPR61, GRIA4, GJD2, and AMPH in FL but not in BFH. Gene expression analyses revealed 411 genes that were hypermethylated and transcriptionally repressed in RL, 74% of which were reactivated by the demethylating agent 5-aza-2'-deoxycytidine (5-azaD) plus or minus the histone deacetylase inhibitor trichostatin A (TSA). Forty genes were also downregulated in primary FL. Our results suggest that extensive hypermethylation in promoters of polycomb target genes is a characteristic of FL and that loss of expression of certain SUZ12 target genes could be functionally relevant for lymphomagenesis.

Cancer DNA methylation: molecular mechanisms and clinical implications

DNA methylation plays a crucial role in the regulation of gene expression and chromatin organization within normal eukaryotic cells. In cancer, however, global patterns of DNA methylation are altered with global hypomethylation of repeat-rich intergenic regions and hypermethylation of a subset of CpG-dense gene-associated regions (CpG islands). Extensive research has revealed the cellular machinery that catalyzes DNA methylation, as well as several large protein complexes that mediate the transcriptional repression of hypermethylated genes. However, research is only just beginning to uncover the molecular mechanisms underlying the origins of cancer-specific DNA methylation. Herein, we present several recent advances regarding these mechanisms and discuss the relationship between histone modifications (i.e., H3K4me2/3, H4K16Ac, H3K9me2/3, H3K27me3, H4K20me3), chromatin-modifying enzymes (G9a, EZH2, hMOF, SUV4-20H), and aberrant DNA methylation. Additionally, the role played by inflammation, DNA damage, and miRNAs in the etiology of aberrant DNA methylation is considered. Finally, we discuss the clinical implications of aberrant DNA methylation and the utility of methylated biomarkers in cancer diagnosis and management.

Mining knowledge for the methylation status of CpG islands using alternating decision trees

CpG island (CpGI) methylation is an epigenetic modification that occurs in eukaryotes and is based on the addition of a methyl group to the number 5 carbon of the pyrimidine ring of cytosine. When methylation of a CpGI occurs, the associated gene (if any) is not expressed [1]. Aberrant methylation is thought to be a causative agent in disease [2] and drug sensitivity [3], [4]. In this work, we have predicted the methylation status of CpGIs in human chromosome 21 using sequence patterns. These patterns showed a significantly different distribution between methylated and unmethylated islands in a previous work [5]. Using C4.5 with bagging and cost-sensitive learning, we achieved 85.6% accuracy, 82.8% sensitivity, and 86.4% specificity.We then constructed 1000 alternating decision trees using a bootstrapping method and analyzed the nodes that were conserved between the trees. This allowed us to find specific combinations of sequence patterns that distinguished between methylated and unmethylated CpGIs. Analysis of these characteristics offers certain insight into the conditions that permit or prevent methylation.

Genome-wide epigenetic analysis delineates a biologically distinct immature acute leukemia with myeloid/T-lymphoid features

Acute myeloid leukemia is a heterogeneous disease from the molecular and biologic standpoints, and even patients with a specific gene expression profile may present clinical and molecular heterogeneity. We studied the epigenetic profiles of a cohort of patients who shared a common gene expression profile but differed in that only half of them harbored mutations of the CEBPA locus, whereas the rest presented with silencing of this gene and coexpression of certain T-cell markers. DNA methylation studies revealed that these 2 groups of patients could be readily segregated in an unsupervised fashion based on their DNA methylation profiles alone. Furthermore, CEBPA silencing was associated with the presence of an aberrant DNA hypermethylation signature, which was not present in the CEBPA mutant group. This aberrant hypermethylation occurred more frequently at sites within CpG islands. CEBPA-silenced leukemias also displayed marked hypermethylation compared with normal CD34(+) hematopoietic cells, whereas CEBPA mutant cases showed only mild changes in DNA methylation compared with these normal progenitors. Biologically, CEBPA-silenced leukemias presented with a decreased response to myeloid growth factors in vitro.

DNA methylation: an introduction to the biology and the disease-associated changes of a promising biomarker

DNA methylation occurring on the 5 position of the pyrimidine ring of cytosines in the context of the dinucleotide sequence CpG forms one of the multiple layers of epigenetic mechanisms controlling and modulating gene expression through chromatin structure. It closely interacts with histone modifications and chromatin-remodeling complexes to form the genomic chromatin landscape. DNA methylation is essential for proper mammalian development, crucial for imprinting, and plays a role in maintaining genomic stability as well as in dosage compensation. DNA methylation patterns are susceptible to change in response to environmental stimuli such as diet or toxins whereby the epigenome seems to be most vulnerable during early in utero development. Aberrant DNA methylation changes have been detected in several diseases, particularly cancer where genome-wide hypomethylation coincides with gene-specific hypermethylation. DNA methylation patterns can be used to detect cancer at very early stages, to classify tumors as well as predict and monitor the response to antineoplastic treatment. As a stable nucleic acid-based modification with limited dynamic range that is technically easy to handle, DNA methylation is a promising biomarker for many applications.

Agglomerative epigenetic aberrations are a common event in human breast cancer

Changes in DNA methylation patterns are a common characteristic of cancer cells. Recent studies suggest that DNA methylation affects not only discrete genes, but it can also affect large chromosomal regions, potentially leading to LRES. It is unclear whether such long-range epigenetic events are relatively rare or frequent occurrences in cancer. Here, we use a high-resolution promoter tiling array approach to analyze DNA methylation in breast cancer specimens and normal breast tissue to address this question. We identified 3,506 cancer-specific differentially methylated regions (DMR) in human breast cancer with 2,033 being hypermethylation events and 1,473 hypomethylation events. Most of these DMRs are recurrent in breast cancer; 90% of the identified DMRs occurred in at least 33% of the samples. Interestingly, we found a nonrandom spatial distribution of aberrantly methylated regions across the genome that showed a tendency to concentrate in relatively small genomic regions. Such agglomerates of hypermethylated and hypomethylated DMRs spanned up to several hundred kilobases and were frequently found at gene family clusters. The hypermethylation events usually occurred in the proximity of the transcription start site in CpG island promoters, whereas hypomethylation events were frequently found in regions of segmental duplication. One example of a newly discovered agglomerate of hypermethylated DMRs associated with gene silencing in breast cancer that we examined in greater detail involved the protocadherin gene family clusters on chromosome 5 (PCDHA, PCDHB, and PCDHG). Taken together, our results suggest that agglomerative epigenetic aberrations are frequent events in human breast cancer.

GSTP1 promoter haplotypes affect DNA methylation levels and promoter activity in breast carcinomas

The CpG island spanning the transcription start of the glutathione S-transferase P1 becomes methylated in a variety of human cancers including breast cancer. To study the effect of sequence variation on hypermethylation of the GSTP1 promoter, we analyzed the genetic and epigenetic variability in 90 tumors from patients with locally advanced breast cancer. High-resolution quantitative analysis revealed large variability in the DNA methylation levels. Lack of methylation was more often observed in the basal and normal-like estrogen receptor (ER)-negative tumors, and methylated GSTP1 was associated with better overall survival (P = 0.00063). Studies of the genetic variation identified 14 different haplotypes. The distribution of methylation levels of tumors homozygous for the most frequent haplotype was significantly different from other haplotype combinations (P = 0.011), the difference being more pronounced in ER-positive (P = 0.005) and progesterone receptor-positive (P = 0.008) tumors. Regression modeling identified the ER status and haplotype as the main determinants of DNA methylation variability. We identified a putative c-Myb response element (MRE) that was present in one of two minimal promoter haplotypes. In vitro analysis showed that c-Myb binds to the MRE, but binding was weakened by the two polymorphisms. Transient cotransfections in luminal-type and basal-like breast cancer cell lines confirmed cell-specific differential binding of c-Myb to the polymorphic sites, leading to a change in the expression from the GSTP1 promoter in vivo. GSTP1 expression was moderately but significantly (P = 0.01) reduced after siRNA-mediated knockdown of c-Myb. Our results indicate that haplotype structure of a promoter is important for the extent of DNA methylation.

Stage-specific alterations of DNA methyltransferase expression, DNA hypermethylation, and DNA hypomethylation during prostate cancer progression in the transgenic adenocarcinoma of mouse prostate model

We analyzed DNA methyltransferase (Dnmt) protein expression and DNA methylation patterns during four progressive stages of prostate cancer in the transgenic adenocarcinoma of mouse prostate (TRAMP) model, including prostatic intraepithelial neoplasia, well-differentiated tumors, early poorly differentiated tumors, and late poorly differentiated tumors. Dnmt1, Dnmt3a, and Dnmt3b protein expression were increased in all stages; however, after normalization to cyclin A to account for cell cycle regulation, Dnmt proteins remained overexpressed in prostatic intraepithelial neoplasia and well-differentiated tumors, but not in poorly differentiated tumors. Restriction landmark genomic scanning analysis of locus-specific methylation revealed a high incidence of hypermethylation only in poorly differentiated (early and late) tumors. Several genes identified by restriction landmark genomic scanning showed hypermethylation of downstream regions correlating with mRNA overexpression, including p16INK4a, p19ARF, and Cacna1a. Parallel gene expression and DNA methylation analyses suggests that gene overexpression precedes downstream hypermethylation during prostate tumor progression. In contrast to gene hypermethylation, genomic DNA hypomethylation, including hypomethylation of repetitive elements and loss of genomic 5-methyldeoxycytidine, occurred in both early and late stages of prostate cancer. DNA hypermethylation and DNA hypomethylation did not correlate in TRAMP, and Dnmt protein expression did not correlate with either variable, with the exception of a borderline significant association between Dnmt1 expression and DNA hypermethylation. In summary, our data reveal the relative timing of and relationship between key alterations of the DNA methylation pathway occurring during prostate tumor progression in an in vivo model system.