Tumour class prediction and discovery by microarray-based DNA methylation analysis

Deep learning-based classifier for carcinoma of unknown primary using methylation quantitative trait loci

Cancer of unknown primary (CUP) constitutes between 2% and 5% of human malignancies and is among the most common causes of cancer death in the United States. Brain metastases are often the first clinical presentation of CUP; despite extensive pathological and imaging studies, 20%-45% of CUP are never assigned a primary site. DNA methylation array profiling is a reliable method for tumor classification but tumor-type-specific classifier development requires many reference samples. This is difficult to accomplish for CUP as many cases are never assigned a specific diagnosis. Recent studies identified subsets of methylation quantitative trait loci (mQTLs) unique to specific organs, which could help increase classifier accuracy while requiring fewer samples. We performed a retrospective genome-wide methylation analysis of 759 carcinoma samples from formalin-fixed paraffin-embedded tissue samples using Illumina EPIC array. Utilizing mQTL specific for breast, lung, ovarian/gynecologic, colon, kidney, or testis (BLOCKT) (185k total probes), we developed a deep learning-based methylation classifier that achieved 93.12% average accuracy and 93.04% average F1-score across a 10-fold validation for BLOCKT organs. Our findings indicate that our organ-based DNA methylation classifier can assist pathologists in identifying the site of origin, providing oncologists insight on a diagnosis to administer appropriate therapy, improving patient outcomes.

Hypermethylated ITGA8 Facilitate Bladder Cancer Cell Proliferation and Metastasis

DNA methylation plays a vital role during the development of tumorigenesis. The purpose of this study is to identify candidate DNA methylation drivers during progression of bladder cancer (BLCA). The methylation spectrum in bladder cancer tissues was detected by CHARM analysis, and methylated ITGA8 was selected for further study due to its low expression. Methylation levels in BLCA tissues and cells were detected with methylated-specific PCR (MSP), while mRNA expression and methylation of ITGA8 were detected by qRT-PCR and MSP. After treatment with 5-Aza-dC (DNA methylation inhibitor), the proliferation, migration, and invasion abilities of BLCA cells were determined by MTT, wound healing, and transwell assays, respectively. Flow cytometric analysis was performed to evaluate any variance in the cell cycle. In addition, the effect of demethylated ITGA8 on BLCA tumor growth was verified with an in vivo xenograft tumor model. Based on the methylation profiling of BLCA, ITGA8 was identified to be hypermethylated. ITGA8 methylation levels in BLCA tissues and cells were upregulated, and 5-Aza-dC significantly suppressed ITGA8 methylation levels and increased ITGA8 mRNA expression. Furthermore, after treatment with 5-Aza-dC, the propagation, migration, and invasiveness of the cancer cells were inhibited, and more cancer cells were arrested at the G0/G1 phase. In vivo assays further demonstrated that 5-Aza-dC could impede BLCA tumor growth by repressing methylation levels of ITGA8 and increasing ITGA8 mRNA expression. Hypermethylated ITGA8 facilitated BLCA progression, and 5-Aza-dC treatment inhibited BLCA cell propagation and metastasis by decreasing methylation levels of ITGA8 and inducing cell cycle arrest.

Methylation specific enzyme-linked oligonucleotide assays (MS-ELONA) for ultrasensitive DNA methylation analysis

Methylation of the promoter region of cancer related genes plays a crucial role in the occurrence and development of cancer, and the degree of methylation has great potential for the early cancer diagnosis. At present, the technology used to quantify DNA methylation is mainly based on the DNA sequencing which are time-consuming and high-cost in the relating application. We have developed an ultrasensitive method of methylation specific enzyme-linked oligonucleotide assays (MS-ELONA) to detect and quantify the level of DNA methylation. We could detect as little as 2 pg of methylated DNA in the 100000-fold excess of unmethylated genes, and discriminate prostate cancer from benign prostatic hyperplasia (BPH) and control with serum samples. We also demonstrate the reversibility of DNA methylation modification by treatment with demethylation drugs. With 16-channel electrochemical work station, our research reveals a simple and inexpensive method to quantify the methylation level of specially appointed genes, and have the potential to be applied in the clinical research.

Epigenetic Alterations and Inflammation as Emerging Use for the Advancement of Treatment in Non-Small Cell Lung Cancer

Lung cancer remains one of the most common malignancies in the world. Nowadays, the most common lung cancer is non-small cell lung cancer (NSCLC), namely, adenocarcinoma, squamous cell carcinoma, and large cell lung carcinoma. Epigenetic alterations that refer to DNA methylation, histone modifications, and noncoding RNA expression, are now suggested to drive the genesis and development of NSCLC. Additionally, inflammation-related tumorigenesis also plays a vital role in cancer research and efforts have been attempted to reverse such condition. During the occurrence and development of inflammatory diseases, the immune component of inflammation may cause epigenetic changes, but it is not always certain whether the immune component itself or the stimulated host cells cause epigenetic changes. Moreover, the links between epigenetic alterations and cancer-related inflammation and their influences on the human cancer are not clear so far. Therefore, the connection between epigenetic drivers, inflammation, and NSCLC will be summarized. Investigation on such topic is most likely to shed light on the molecular and immunological mechanisms of epigenetic and inflammatory factors and promote the application of epigenetics in the innovative diagnostic and therapeutic strategies for NSCLC.

Global DNA methylation profile at LINE-1 repeats and promoter methylation of genes involved in DNA damage response and repair pathways in human peripheral blood mononuclear cells in response to γ-radiation

DNA methylation is an epigenetic mechanism, which plays an important role in gene regulation. The present study evaluated DNA methylation profile of LINE1 repeats and promoter methylation of DNA damage response (DDR) and DNA repair (DR) genes (PARP1, ATM, BRCA1, MLH1, XPC, RAD23B, APC, TNFα, DNMT3A, MRE11A, MGMT, CDKN2A, MTHFR) in human peripheral blood mononuclear cells (PBMCs) of healthy donors in response to γ-radiation. Methylation level was correlated with gene expression profile of selected DDR and DR genes (APC, MLH1, PARP1, MRE11A, TNFα, MGMT) to understand their role in gene regulation. Blood samples were collected from 15 random healthy donors, PBMCs were isolated, exposed to 0.1 Gy (low) and 2.0 Gy (high) doses of γ-radiation and proliferated for 48 h and 72 h. Genomic DNA and total RNA were isolated from irradiated PBMCs along with un-irradiated control. Methylation profile was determined from bisulphite converted DNA and amplified by methylation sensitive high resolution melting (MS-HRM) method. Total RNA was converted to cDNA and relative expression was analysed using real time quantitative-PCR. Our results revealed that at 0.1 Gy, MRE11A and TNFα showed significant (P < 0.05) increase in methylation at 72 h. At 2.0 Gy, significant increase (P < 0.05) in methylation profile was observed at LINE1, MRE11A, PARP1, BRCA1, DNMT3A and RAD23B at 48 h and 72 h. PARP1 showed significant positive correlation of methylation status with gene expression. In conclusion, low and high doses of γ-radiation have significant influence on DNA methylation status of LINE1, DDR and DR genes suggesting their potential role as epigenetic signatures in human PBMCs, which can be further explored in human populations.

Current Insights and Advancements in Head and Neck Cancer: Emerging Biomarkers and Therapeutics with Cues from Single Cell and 3D Model Omics Profiling

Head and neck cancer (HNC) is among the ten leading malignancies worldwide, with India solely contributing one-third of global oral cancer cases. The current focus of all cutting-edge strategies against this global malignancy are directed towards the heterogeneous tumor microenvironment that obstructs most treatment blueprints. Subsequent to the portrayal of established information, the review details the application of single cell technology, organoids and spheroid technology in relevance to head and neck cancer and the tumor microenvironment acknowledging the resistance pattern of the heterogeneous cell population in HNC. Bioinformatic tools are used for study of differentially expressed genes and further omics data analysis. However, these tools have several challenges and limitations when analyzing single-cell gene expression data that are discussed briefly. The review further examines the omics of HNC, through comprehensive analyses of genomics, transcriptomics, proteomics, metabolomics, and epigenomics profiles. Patterns of alterations vary between patients, thus heterogeneity and molecular alterations between patients have driven the clinical significance of molecular targeted therapies. The analyses of potential molecular targets in HNC are discussed with connotation to the alteration of key pathways in HNC followed by a comprehensive study of protein kinases as novel drug targets including its ATPase and additional binding pockets, non-catalytic domains and single residues. We herein review, the therapeutic agents targeting the potential biomarkers in light of new molecular targeted therapies. In the final analysis, this review suggests that the development of improved target-specific personalized therapies can combat HNC's global plight.

DNA methylation methods: Global DNA methylation and methylomic analyses

DNA methylation provides a pivotal layer of epigenetic regulation in eukaryotes that has significant involvement for numerous biological processes in health and disease. The function of methylation of cytosine bases in DNA was originally proposed as a "silencing" epigenetic marker and focused on promoter regions of genes for decades. Improved technologies and accumulating studies have been extending our understanding of the roles of DNA methylation to various genomic contexts including gene bodies, repeat sequences and transcriptional start sites. The demand for comprehensively describing DNA methylation patterns spawns a diversity of DNA methylation profiling technologies that target its genomic distribution. These approaches have enabled the measurement of cytosine methylation from specific loci at restricted regions to single-base-pair resolution on a genome-scale level. In this review, we discuss the different DNA methylation analysis technologies primarily based on the initial treatments of DNA samples: bisulfite conversion, endonuclease digestion and affinity enrichment, involving methodology evolution, principles, applications, and their relative merits. This review may offer referable information for the selection of various platforms for genome-wide analysis of DNA methylation.

Current status of development of methylation biomarkers for in vitro diagnostic IVD applications

A significant volume of research clearly shows that disease-related methylation changes can be used as biomarkers at all stages of clinical disease management, including risk assessment and predisposition screening through early diagnostics to personalization of patient care and monitoring of the relapse and chronic disease. Thus disease-related methylation changes are an attractive source of the biomarkers that can have significant impact on precision medicine. However, the translation of the research findings in methylation biomarkers field to clinical practice is at the very least not satisfactory. That is mainly because the evidence generated in research studies indicating the utility of the disease-related methylation change to predict clinical outcome is in majority of the cases not sufficient to postulate the diagnostic use of the biomarker. The research studies need to be followed by well-designed and systematic investigations of clinical utility of the biomarker that produce data of sufficient quality to meet regulatory approval for the test to be used to make clinically valid decision. In this review, we describe methylation-based IVD tests currently approved for IVD use or at the advanced stages of the development for the diagnostic use. For each of those tests, we analyze the technologies that the test utilizes for methylation detection as well as describe the types of the clinical studies that were performed to show clinical validity of the test and warrant regulatory approval. The examples reviewed here should help with planning of clinical investigations and delivery of the clinical evidence required for the regulatory approval of potential methylation biomarker based IVD tests.

The 100 Most Cited Papers About Cancer Epigenetics

Introduction

Although bibliometric analyses have been performed in the past on cancer and genomics, little is known about the most frequently cited articles specifically related to cancer epigenetics. Therefore, the purpose of this study is to use citation count to identify those papers in the scientific literature that have made key contributions in the field of cancer epigenetics and identify key driving forces behind future investigations.

Materials and methods

The Thomas Reuters Web of Science services was queried for the years 1980-2018 without language restrictions. Articles were sorted in descending order of the number of times they were cited in the Web of Science database by other studies, and all titles and abstracts were screened to identify the research areas of the top 100 articles. The number of citations per year was calculated.

Results

We identified the 100 most-cited articles on cancer epigenetics, which collectively had been cited 147,083 times at the time of this writing. The top-cited article was cited 7,124 times, with an average of 375 citations per year since publication. In the period 1980-2018, the most prolific years were the years 2006 and 2010, producing nine articles, respectively. Twenty-eight unique journals contributed to the 100 articles, with the Nature journal contributing most of the articles (n=22). The most common country of article origin was the United States of America (n=78), followed by Germany (n=4), Switzerland (n=4), Japan (n=3), Spain (n=2), and United Kingdom (n=2).

Conclusions

In this study, the 100 most-cited articles in cancer epigenetics were examined, and the contributions from various authors, specialties, and countries were identified. Cancer epigenetics is a rapidly growing scientific field impacting translational research in cancer screening, diagnosis, classification, prognosis, and targeted treatments. Recognition of important historical contributions to this field may guide future investigations.

Machine learning and clinical epigenetics: a review of challenges for diagnosis and classification

BACKGROUND

Machine learning is a sub-field of artificial intelligence, which utilises large data sets to make predictions for future events. Although most algorithms used in machine learning were developed as far back as the 1950s, the advent of big data in combination with dramatically increased computing power has spurred renewed interest in this technology over the last two decades.

MAIN BODY

Within the medical field, machine learning is promising in the development of assistive clinical tools for detection of e.g. cancers and prediction of disease. Recent advances in deep learning technologies, a sub-discipline of machine learning that requires less user input but more data and processing power, has provided even greater promise in assisting physicians to achieve accurate diagnoses. Within the fields of genetics and its sub-field epigenetics, both prime examples of complex data, machine learning methods are on the rise, as the field of personalised medicine is aiming for treatment of the individual based on their genetic and epigenetic profiles.

CONCLUSION

We now have an ever-growing number of reported epigenetic alterations in disease, and this offers a chance to increase sensitivity and specificity of future diagnostics and therapies. Currently, there are limited studies using machine learning applied to epigenetics. They pertain to a wide variety of disease states and have used mostly supervised machine learning methods.

Genome-Wide Methylation Profiling in Canine Mammary Tumor Reveals miRNA Candidates Associated with Human Breast Cancer

Genome-wide methylation profiling is used in breast cancer (BC) studies, because DNA methylation is a crucial epigenetic regulator of gene expression, involved in many diseases including BC. We investigated genome-wide methylation profiles in both canine mammary tumor (CMT) tissues and peripheral blood mononuclear cells (PBMCs) using reduced representation bisulfite sequencing (RRBS) and found unique CMT-enriched methylation signatures. A total of 2.2-4.2 million cytosine-phosphate-guanine (CpG) sites were analyzed in both CMT tissues and PBMCs, which included 40,000 and 28,000 differentially methylated regions (DMRs) associated with 341 and 247 promoters of differentially methylated genes (DMGs) in CMT tissues and PBMCs, respectively. Genes related to apoptosis and ion transmembrane transport were hypermethylated, but cell proliferation and oncogene were hypomethylated in tumor tissues. Gene ontology analysis using DMGs in PBMCs revealed significant methylation changes in the subset of immune cells and host defense system-related genes, especially chemokine signaling pathway-related genes. Moreover, a number of CMT tissue-enriched DMRs were identified from the promoter regions of various microRNAs (miRNAs), including cfa-mir-96 and cfa-mir-149, which were reported as cancer-associated miRNAs in humans. We also identified novel miRNAs associated with CMT which can be candidates for new miRNAs associated with human BC. This study may provide new insight for a better understanding of aberrant methylation associated with both human BC and CMT, as well as possible targets for methylation-based BC diagnostic markers.

Identifying Methylation Pattern and Genes Associated with Breast Cancer Subtypes

Breast cancer is regarded worldwide as a severe human disease. Various genetic variations, including hereditary and somatic mutations, contribute to the initiation and progression of this disease. The diagnostic parameters of breast cancer are not limited to the conventional protein content and can include newly discovered genetic variants and even genetic modification patterns such as methylation and microRNA. In addition, breast cancer detection extends to detailed breast cancer stratifications to provide subtype-specific indications for further personalized treatment. One genome-wide expression–methylation quantitative trait loci analysis confirmed that different breast cancer subtypes have various methylation patterns. However, recognizing clinically applied (methylation) biomarkers is difficult due to the large number of differentially methylated genes. In this study, we attempted to re-screen a small group of functional biomarkers for the identification and distinction of different breast cancer subtypes with advanced machine learning methods. The findings may contribute to biomarker identification for different breast cancer subtypes and provide a new perspective for differential pathogenesis in breast cancer subtypes.

Lung Cancer Screening and Epigenetics in African Americans: The Role of the Socioecological Framework

Lung cancer is the leading cause of cancer morbidity and mortality in the U.S. and racial/ethnic minorities carry the greatest burden of lung cancer disparities with African Americans (AAs) impacted disproportionately. Inequities in lung cancer health disparities are often associated with multiple bio-behavioral and socio-cultural factors among racial/ethnic minorities. Epigenetic research has advanced the understanding of the intersectionality between biological and socio-cultural factors in lung cancer disparities among AAs. However, gaps exist in the engagement of diverse populations in epigenetic lung cancer research, which poses a challenge in ensuring the generalizability and implementation of epigenetic research in populations that carry an unequal cancer burden. Grounding epigenetic lung cancer research within a socio-ecological framework may prove promising in implementing a multi-level approach to community engagement, screening, navigation, and research participation among AAs. The University of Illinois Cancer Center (UI Cancer Center) is employing an evidence–based (EB) model of community/patient engagement utilizing the socio-ecological model (SEM) to develop a culturally sensitive epigenetic lung cancer research program that addresses multiple factors that impact lung cancer outcomes in AAs. By implementing epigenetic research within a group of Federally Qualified Health Centers (FQHCs) guided by the SEM, the UI Cancer Center is proposing a new pathway in mitigating lung cancer disparities in underserved communities. At the individual level, the framework examines tobacco use among patients at FQHCs (the organizational level) and also tailors epigenetic research to explore innovative biomarkers in high risk populations. Interpersonal interventions use Patient Navigators to support navigation to EB tobacco cessation resources and lung cancer screening. Community level support within the SEM is developed by ongoing partnerships with local and national partners such as the American Lung Association (ALA) and the American Cancer Society (ACS). Lastly, at the policy level, the UI Cancer Center acknowledges the role of policy implications in lung cancer screening and advocates for policies and screening recommendations that examine the current guidelines from the United States Preventive Services Task Force (USPTF).

Epigenetic regulation of gene expression in cancer: techniques, resources and analysis

Cancer is a complex disease, driven by aberrant activity in numerous signaling pathways in even individual malignant cells. Epigenetic changes are critical mediators of these functional changes that drive and maintain the malignant phenotype. Changes in DNA methylation, histone acetylation and methylation, noncoding RNAs, posttranslational modifications are all epigenetic drivers in cancer, independent of changes in the DNA sequence. These epigenetic alterations were once thought to be crucial only for the malignant phenotype maintenance. Now, epigenetic alterations are also recognized as critical for disrupting essential pathways that protect the cells from uncontrolled growth, longer survival and establishment in distant sites from the original tissue. In this review, we focus on DNA methylation and chromatin structure in cancer. The precise functional role of these alterations is an area of active research using emerging high-throughput approaches and bioinformatics analysis tools. Therefore, this review also describes these high-throughput measurement technologies, public domain databases for high-throughput epigenetic data in tumors and model systems and bioinformatics algorithms for their analysis. Advances in bioinformatics data that combine these epigenetic data with genomics data are essential to infer the function of specific epigenetic alterations in cancer. These integrative algorithms are also a focus of this review. Future studies using these emerging technologies will elucidate how alterations in the cancer epigenome cooperate with genetic aberrations during tumor initiation and progression. This deeper understanding is essential to future studies with epigenetics biomarkers and precision medicine using emerging epigenetic therapies.

Targeting DNA Hypomethylation in Malignancy by Epigenetic Therapies

DNA methylation is a chemically reversible epigenetic modification that regulates the chromatin structure and gene expression, and thereby takes part in various cellular processes like embryogenesis, genomic imprinting, X-chromosome inactivation, and genome stability. Alterations in the normal methylation levels of DNA may contribute to the development of pathological conditions like cancer. Even though both hypo- and hypermethylation-mediated abnormalities are prevalent in the cancer genome, the field of cancer epigenetics has been more focused on targeting hypermethylation. As a result, DNA hypomethylation-mediated abnormalities remained relatively less explored, and currently, there are no approved drugs that can be clinically used to target hypomethylation. Understanding the precise role of DNA hypomethylation is not only crucial from a mechanistic point of view but also for the development of pharmacological agents that can reverse the hypomethylated state of the DNA. This chapter focuses on the causes and impact of DNA hypomethylation in the development of cancer and describes the possible ways to pharmacologically target it, especially by using a naturally occurring physiologic agent S-adenosylmethionine (SAM).

Machine learning selected smoking-associated DNA methylation signatures that predict HIV prognosis and mortality

Background

The effects of tobacco smoking on epigenome-wide methylation signatures in white blood cells (WBCs) collected from persons living with HIV may have important implications for their immune-related outcomes, including frailty and mortality. The application of a machine learning approach to the analysis of CpG methylation in the epigenome enables the selection of phenotypically relevant features from high-dimensional data. Using this approach, we now report that a set of smoking-associated DNA-methylated CpGs predicts HIV prognosis and mortality in an HIV-positive veteran population.

Results

We first identified 137 epigenome-wide significant CpGs for smoking in WBCs from 1137 HIV-positive individuals (p < 1.70E−07). To examine whether smoking-associated CpGs were predictive of HIV frailty and mortality, we applied ensemble-based machine learning to build a model in a training sample employing 408,583 CpGs. A set of 698 CpGs was selected and predictive of high HIV frailty in a testing sample [(area under curve (AUC) = 0.73, 95%CI 0.63~0.83)] and was replicated in an independent sample [(AUC = 0.78, 95%CI 0.73~0.83)]. We further found an association of a DNA methylation index constructed from the 698 CpGs that were associated with a 5-year survival rate [HR = 1.46; 95%CI 1.06~2.02, p = 0.02]. Interestingly, the 698 CpGs located on 445 genes were enriched on the integrin signaling pathway (p = 9.55E−05, false discovery rate = 0.036), which is responsible for the regulation of the cell cycle, differentiation, and adhesion.

Conclusion

We demonstrated that smoking-associated DNA methylation features in white blood cells predict HIV infection-related clinical outcomes in a population living with HIV.

Electronic supplementary material

The online version of this article (10.1186/s13148-018-0591-z) contains supplementary material, which is available to authorized users.

Epigenetic alterations to Polycomb targets precede malignant transition in a mouse model of breast cancer

Malignant breast cancer remains a major health threat to women of all ages worldwide and epigenetic variations on DNA methylation have been widely reported in cancers of different types. We profiled DNA methylation with ERRBS (Enhanced Reduced Representation Bisulfite Sequencing) across four main stages of tumor progression in the MMTV-PyMT mouse model (hyperplasia, adenoma/mammary intraepithelial neoplasia, early carcinoma and late carcinoma), during which malignant transition occurs. We identified a large number of differentially methylated cytosines (DMCs) in tumors relative to age-matched normal mammary glands from FVB mice. Despite similarities, the methylation differences of the premalignant stages were distinct from the malignant ones. Many differentially methylated loci were preserved from the first to the last stage throughout tumor progression. Genes affected by methylation gains were enriched in Polycomb repressive complex 2 (PRC2) targets, which may present biomarkers for early diagnosis and targets for treatment.

Epigenetic regulation of gene expression in cancer: techniques, resources and analysis

Cancer is a complex disease, driven by aberrant activity in numerous signaling pathways in even individual malignant cells. Epigenetic changes are critical mediators of these functional changes that drive and maintain the malignant phenotype. Changes in DNA methylation, histone acetylation and methylation, noncoding RNAs, posttranslational modifications are all epigenetic drivers in cancer, independent of changes in the DNA sequence. These epigenetic alterations were once thought to be crucial only for the malignant phenotype maintenance. Now, epigenetic alterations are also recognized as critical for disrupting essential pathways that protect the cells from uncontrolled growth, longer survival and establishment in distant sites from the original tissue. In this review, we focus on DNA methylation and chromatin structure in cancer. The precise functional role of these alterations is an area of active research using emerging high-throughput approaches and bioinformatics analysis tools. Therefore, this review also describes these high-throughput measurement technologies, public domain databases for high-throughput epigenetic data in tumors and model systems and bioinformatics algorithms for their analysis. Advances in bioinformatics data that combine these epigenetic data with genomics data are essential to infer the function of specific epigenetic alterations in cancer. These integrative algorithms are also a focus of this review. Future studies using these emerging technologies will elucidate how alterations in the cancer epigenome cooperate with genetic aberrations during tumor initiation and progression. This deeper understanding is essential to future studies with epigenetics biomarkers and precision medicine using emerging epigenetic therapies.

Detection of methylation on dsDNA using nanopores in a MoS2 membrane

Methylation at the 5-carbon position of the cytosine nucleotide base in DNA has been shown to be a reliable diagnostic biomarker for carcinogenesis. Early detection of methylation and intervention could drastically increase the effectiveness of therapy and reduce the cancer mortality rate. Current methods for detecting methylation involve bisulfite genomic sequencing, which are cumbersome and demand a large sample size of bodily fluids to yield accurate results. Hence, more efficient and cost effective methods are desired. Based on our previous work, we present a novel nanopore-based assay using a nanopore in a MoS₂ membrane, and the methyl-binding protein (MBP), MBD1x, to detect methylation on dsDNA. We show that the dsDNA translocation was effectively slowed down using an asymmetric concentration of buffer and explore the possibility of profiling the position of methylcytosines on the DNA strands as they translocate through the 2D membrane. Our findings advance us one step closer towards the possible use of nanopore sensing technology in medical applications such as cancer detection.

Identification of Biomarkers for Predicting Lymph Node Metastasis of Stomach Cancer Using Clinical DNA Methylation Data

Background

Lymph node (LN) metastasis was an independent risk factor for stomach cancer recurrence, and the presence of LN metastasis has great influence on the overall survival of stomach cancer patients. Thus, accurate prediction of the presence of lymph node metastasis can provide guarantee of credible prognosis evaluation of stomach cancer patients. Recently, increasing evidence demonstrated that the aberrant DNA methylation first appears before symptoms of the disease become clinically apparent.

Objective

Selecting key biomarkers for LN metastasis presence prediction for stomach cancer using clinical DNA methylation based on a machine learning method.

Methods

To reduce the overfitting risk of prediction task, we applied a three-step feature selection method according to the property of DNA methylation data.

Results

The feature selection procedure extracted several cancer-related and lymph node metastasis-related genes, such as TP73, PDX1, FUT8, HOXD1, NMT1, and SEMA3E. The prediction performance was evaluated on the public DNA methylation dataset. The results showed that the three-step feature procedure can largely improve the prediction performance and implied the reliability of the biomarkers selected.

Conclusions

With the selected biomarkers, the prediction method can achieve higher accuracy in detecting LN metastasis and the results also proved the reliability of the selected biomarkers indirectly.

Machine learning for epigenetics and future medical applications

Understanding epigenetic processes holds immense promise for medical applications. Advances in Machine Learning (ML) are critical to realize this promise. Previous studies used epigenetic data sets associated with the germline transmission of epigenetic transgenerational inheritance of disease and novel ML approaches to predict genome-wide locations of critical epimutations. A combination of Active Learning (ACL) and Imbalanced Class Learning (ICL) was used to address past problems with ML to develop a more efficient feature selection process and address the imbalance problem in all genomic data sets. The power of this novel ML approach and our ability to predict epigenetic phenomena and associated disease is suggested. The current approach requires extensive computation of features over the genome. A promising new approach is to introduce Deep Learning (DL) for the generation and simultaneous computation of novel genomic features tuned to the classification task. This approach can be used with any genomic or biological data set applied to medicine. The application of molecular epigenetic data in advanced machine learning analysis to medicine is the focus of this review.

DNA methylation patterns as noninvasive biomarkers and targets of epigenetic therapies in colorectal cancer

Aberrant DNA methylation is frequently detected in gastrointestinal tumors, and can therefore potentially be used to screen, diagnose, prognosticate, and predict colorectal cancers (CRCs). Although colonoscopic screening remains the gold standard for CRC screening, this procedure is invasive, expensive, and suffers from poor patient compliance. Methylated DNA is an attractive choice for a biomarker substrate because CRCs harbor hundreds of aberrantly methylated genes. Furthermore, abundance in extracellular environments and resistance to degradation and enrichment in serum, stool, and other noninvasive bodily fluids, allows quantitative measurements of methylated DNA biomarkers. This article describes the most important studies that investigated the efficacy of serum- or stool-derived methylated DNA as population-based screening biomarkers in CRC, details several mechanisms and factors that control DNA methylation, describes a better use of prevailing technologies that discover novel DNA methylation biomarkers, and illustrates the diversity of demethylating agents and their applicability toward clinical impact.

Methods for genome-wide DNA methylation analysis in human cancer

Aberrant DNA methylation is considered to be one of the most common hallmarks of cancer. Several recent advances in assessing the DNA methylome provide great promise for deciphering the cancer-specific DNA methylation patterns. Herein, we present the current key technologies used to detect high-throughput genome-wide DNA methylation, and the available cancer-associated methylation databases. Additionally, we focus on the computational methods for preprocessing, analyzing and interpreting the cancer methylome data. It not only discusses the challenges of the differentially methylated region calling and the prediction model construction but also highlights the biomarker investigation for cancer diagnosis, prognosis and response to treatment. Finally, some emerging challenges in the computational analysis of cancer methylome data are summarized.

Nanopore-based assay for detection of methylation in double-stranded DNA fragments

DNA methylation is an epigenetic modification of DNA in which methyl groups are added at the 5-carbon position of cytosine. Aberrant DNA methylation, which has been associated with carcinogenesis, can be assessed in various biological fluids and potentially can be used as markers for detection of cancer. Analytically sensitive and specific assays for methylation targeting low-abundance and fragmented DNA are needed for optimal clinical diagnosis and prognosis. We present a nanopore-based direct methylation detection assay that circumvents bisulfite conversion and polymerase chain reaction amplification. Building on our prior work, we used methyl-binding proteins (MBPs), which selectively label the methylated DNA. The nanopore-based assay selectively detects methylated DNA/MBP complexes through a 19 nm nanopore with significantly deeper and prolonged nanopore ionic current blocking, while unmethylated DNA molecules were not detectable due to their smaller diameter. Discrimination of hypermethylated and unmethylated DNA on 90, 60, and 30 bp DNA fragments was demonstrated using sub-10 nm nanopores. Hypermethylated DNA fragments fully bound with MBPs are differentiated from unmethylated DNA at 2.1- to 6.5-fold current blockades and 4.5- to 23.3-fold transport durations. Furthermore, these nanopore assays can detect the CpG dyad in DNA fragments and could someday profile the position of methylated CpG sites on DNA fragments.

Interdependency between genetic and epigenetic regulatory defects in cancer

Epigenetic regulation is understood as heritable changes in gene expression and genome function that can occur without affecting the DNA sequence. In its in vivo context DNA is coupled to a group of small basic proteins that together with the DNA form the chromatin. The organization and regulation of the chromatin alliance with multiple nuclear functions are inconceivable without genetic information. With the advance on the understanding of the chromatin organization of the eukaryotic genome, it has been clear that not only genetics but also epigenetics influence both normal human biology and diseases. As a consequence, the basic concepts and mechanisms of cancer need to be readdressed and viewed not only locally but also at the whole genome scale or even, in the three-dimensional context of the cell nucleus space. Such a vision has a larger impact than has been previously predicted, since phenomena like aging, senescence, the entail of nutrition, stem cell biology, and cancer are orchestrated by epigenetic and genetic processes. Here I describe the relevance and central role of genetic and epigenetic defects in cancer.

Designing DNA interstrand lock for locus-specific methylation detection in a nanopore

DNA methylation is an important epigenetic regulation of gene transcription. Locus-specific DNA methylation can be used as biomarkers in various diseases including cancer. Many methods have been developed for genome-wide methylation analysis, but molecular diagnotics needs simple tools to determine methylation states at individual CpG sites in a gene fragment. In this report, we utilized the nanopore single-molecule sensor to investigate a base-pair specific metal ion/nucleic acids interaction, and explored its potential application in locus-specific DNA methylation analysis. We identified that divalent Mercury ion (Hg²⁺) can selectively bind a uracil-thymine mismatch (U-T) in a dsDNA. The Hg²⁺ binding creates a reversible interstrand lock, called MercuLock, which enhances the hybridization strength by two orders of magnitude. Such MercuLock cannot be formed in a 5-methylcytosine-thymine mismatch (mC-T). By nanopore detection of dsDNA stability, single bases of uracil and 5-methylcytosine can be distinguished. Since uracil is converted from cytosine by bisulfite treatment, cytosine and 5′-methylcytosine can be discriminated. We have demonstrated the methylation analysis of multiple CpGs in a p16 gene CpG island. This single-molecule assay may have potential in detection of epigenetic cancer biomarkers in biofluids, with an ultimate goal for early diagnosis of cancer.

Review of processing and analysis methods for DNA methylation array data

The promise of epigenome-wide association studies and cancer-specific somatic DNA methylation changes in improving our understanding of cancer, coupled with the decreasing cost and increasing coverage of DNA methylation microarrays, has brought about a surge in the use of these technologies. Here, we aim to provide both a review of issues encountered in the processing and analysis of array-based DNA methylation data and a summary of the advantages of recent approaches proposed for handling those issues, focusing on approaches publicly available in open-source environments such as R and Bioconductor. We hope that the processing tools and analysis flowchart described herein will facilitate researchers to effectively use these powerful DNA methylation array-based platforms, thereby advancing our understanding of human health and disease.

Toxicogenomic approaches for understanding molecular mechanisms of heavy metal mutagenicity and carcinogenicity

Heavy metals that are harmful to humans include arsenic, cadmium, chromium, lead, mercury, and nickel. Some metals or their related compounds may even cause cancer. However, the mechanism underlying heavy metal-induced cancer remains unclear. Increasing data show a link between heavy metal exposure and aberrant changes in both genetic and epigenetic factors via non-targeted multiple toxicogenomic technologies of the transcriptome, proteome, metabolome, and epigenome. These modifications due to heavy metal exposure might provide a better understanding of environmental disorders. Such informative changes following heavy metal exposure might also be useful for screening of biomarker-monitored exposure to environmental pollutants and/or predicting the risk of disease. We summarize advances in high-throughput toxicogenomic-based technologies and studies related to exposure to individual heavy metal and/or mixtures and propose the underlying mechanism of action and toxicant signatures. Integrative multi-level expression analysis of the toxicity of heavy metals via system toxicology-based methodologies combined with statistical and computational tools might clarify the biological pathways involved in carcinogenic processes. Although standard in vitro and in vivo endpoint testing of mutagenicity and carcinogenicity are considered a complementary approach linked to disease, we also suggest that further evaluation of prominent biomarkers reflecting effects, responses, and disease susceptibility might be diagnostic. Furthermore, we discuss challenges in toxicogenomic applications for toxicological studies of metal mixtures and epidemiological research. Taken together, this review presents toxicogenomic data that will be useful for improvement of the knowledge of carcinogenesis and the development of better strategies for health risk assessment.

DNA methylation and cancer

Cancer has been considered a genetic disease with a wide array of well-characterized gene mutations and chromosomal abnormalities. Of late, aberrant epigenetic modifications have been elucidated in cancer, and together with genetic alterations, they have been helpful in understanding the complex traits observed in neoplasia. "Cancer Epigenetics" therefore has contributed substantially towards understanding the complexity and diversity of various cancers. However, the positioning of epigenetic events during cancer progression is still not clear, though there are some reports implicating aberrant epigenetic modifications in very early stages of cancer. Amongst the most studied aberrant epigenetic modifications are the DNA methylation differences at the promoter regions of genes affecting their expression. Hypomethylation mediated increased expression of oncogenes and hypermethylation mediated silencing of tumor suppressor genes are well known examples. This chapter also explores the correlation of DNA methylation and demethylation enzymes with cancer.

Epigenetic Regulation in Particulate Matter-Mediated Cardiopulmonary Toxicities: A Systems Biology Perspective

Particulate matter (PM) air pollution exerts significant adverse health effects in global populations, particularly in developing countries with extensive air pollution. Understanding of the mechanisms of PM-induced health effects including the risk for cardiovascular diseases remains limited. In addition to the direct cellular physiological responses such as mitochondrial dysfunction and oxidative stress, PM mediates remarkable dysregulation of gene expression, especially in cardiovascular tissues. The PM-mediated gene dysregulation is likely to be a complex mechanism affected by various genetic and non-genetic factors. Notably, PM is known to alter epigenetic markers (e.g., DNA methylation and histone modifications), which may contribute to air pollution-mediated health consequences including the risk for cardiovascular diseases. Notably, epigenetic changes induced by ambient PM exposure have emerged to play a critical role in gene regulation. Though the underlying mechanism(s) are not completely clear, the available evidence suggests that the modulated activities of DNA methyltransferase (DNMT), histone acetylase (HAT) and histone deacetylase (HDAC) may contribute to the epigenetic changes induced by PM or PM-related chemicals. By employing genome-wide epigenomic and systems biology approaches, PM toxicogenomics could conceivably progress greatly with the potential identification of individual epigenetic loci associated with dysregulated gene expression after PM exposure, as well the interactions between epigenetic pathways and PM. Furthermore, novel therapeutic targets based on epigenetic markers could be identified through future epigenomic studies on PM-mediated cardiopulmonary toxicities. These considerations collectively inform the future population health applications of genomics in developing countries while benefiting global personalized medicine at the same time.

DNA methyltransferase inhibitors in acute myeloid leukemia: discovery, design and first therapeutic experiences

INTRODUCTION

DNA methylation is an epigenetic change mediated by DNA methyltranferases (DNMTs), which are promising epigenetic targets for the treatment of acute myeloid leukemia (AML). This is evidenced by the two DNMT inhibitors (azacitidine and decitabine) approved by the Food and Drug Administration of the United States for the treatment of high-risk myelodysplastic syndromes and the first clinical data available in AML.

AREAS COVERED

This paper reviews data from the international literature regarding the design, sites of impact and pharmacodynamic characteristics of DNMT inhibitors, and their first clinical experiences in AML.

EXPERT OPINION

The strongest advances in epigenetic therapy have been in the treatment of AML. There are now an increasing number of DNMT inhibitors. These agents may be potentially administered at different times of leukemia therapy: before or instead of chemotherapy, as maintenance therapy, prior to allogeneic stem cell transplant (SCT) or after relapse following SCT.

Genome-wide DNA methylation profiling using Infinium® assay

AIMS

Bisulfite sequence analysis of individual CpG sites within genomic DNA is a powerful approach for methylation analysis in the genome. The major limitation of bisulfite-based methods is parallelization. Both array and next-generation sequencing technology are capable of addressing this bottleneck. In this report, we describe the application of Infinium® genotyping technology to analyze bisulfite-converted DNA to simultaneously query the methylation state of over 27,000 CpG sites from promoters of consensus coding sequences (CCDS) genes.

MATERIALS & METHODS

We adapted the Infinium genotyping assay to readout an array of over 27,000 pairs of CpG methylation-specific query probes complementary to bisulfite-converted DNA. Two probes were designed to each CpG site: a 'methylated' and an 'unmethylated' query probe. The probe design assumed that all underlying CpG sites were 'in phase' with the queried CpG site due to their close proximity. Bisulfite conversion was performed with a modified version of the Zymo EZ DNA Methylation™ kit.

RESULTS

We applied this technology to measuring methylation levels across a panel of 14 different human tissues, four Coriell cell lines and six cancer cell lines. We observed that CpG sites within CpG islands (CGIs) were largely unmethylated across all tissues (~80% sites unmethylated, β < 0.2), whereas CpG sites in non-CGIs were moderately to highly methylated (only ~12% sites unmethylated, β < 0.2). Within CGIs, only approximately 3-6% of the loci were highly methylated; in contrast, outside of CGIs approximately 25-40% of loci were highly methylated. Moreover, tissue-specific methylation (variation in methylation across tissues) was much more prevalent in non-CGIs than within CGIs.

CONCLUSION

Our results demonstrate a genome-wide scalable array-based methylation readout platform that is both highly reproducible and quantitative. In the near future, this platform should enable the analysis of hundreds of thousands to millions of CpG sites per sample.

Methods in DNA methylation profiling

Metastable and somatically heritable patterns of DNA methylation provide an important level of genomic regulation. In this article, we review methods for analyzing these genome-wide epigenetic patterns and offer a perspective on the ever-expanding literature, which we hope will be useful for investigators who are new to this area. The historical aspects that we cover will be helpful in interpreting this literature and we hope that our discussion of the newest analytical methods will stimulate future progress. We emphasize that no single approach can provide a complete view of the overall methylome, and that combinations of several modalities applied to the same sample set will give the clearest picture. Given the unexpected epigenomic patterns and new biological principles, as well as new disease markers, that have been uncovered in recent studies, it is likely that important discoveries will continue to be made using genome-wide DNA methylation profiling.

Quantitative measurement of genome-wide DNA methylation by a reliable and cost-efficient enzyme-linked immunosorbent assay technique

DNA methylation, the conversion of cytosine to 5-methylcytosine, is an important epigenetic modification involved in gene regulation. DNA methylation is essential for normal development whereas abnormal methylation has been implicated in pathological conditions including cancer. To evaluate the extent and variation of genome-wide DNA methylation and its changes during cellular differentiation and tumorgenesis as well as the interplay with histone modifications, accurate and reproducible quantification of the genomic DNA methylation level is required. These measurements have so far been achieved only by sophisticated and costly techniques. Here we report the generation of an enzyme-linked immunosorbent assay (methDNA-ELISA) for the accurate quantification of global DNA methylation levels. The linear region of this methDNA-ELISA ranges from 1 to 10%, making it highly suitable for the typical ranges from 2 to 6% in mammalian genomes. This method requires 10 ng of isolated DNA per sample, thus permitting investigation with minimal amounts of DNA previously not applicable for global DNA methylation analysis, e.g., clinical biopsies or cells collected by microdissection.

DNA methylation: a timeline of methods and applications

DNA methylation is a biochemical process where a DNA base, usually cytosine, is enzymatically methylated at the 5-carbon position. An epigenetic modification associated with gene regulation, DNA methylation is of paramount importance to biological health and disease. Recently, the quest to unravel the Human Epigenome commenced, calling for a modernization of previous DNA methylation profiling techniques. Here, we describe the major developments in the methodologies used over the past three decades to examine the elusive epigenome (or methylome). The earliest techniques were based on the separation of methylated and unmethylated cytosines via chromatography. The following years would see molecular techniques being employed to indirectly examine DNA methylation levels at both a genome-wide and locus-specific context, notably immunoprecipitation via anti-5'methylcytosine and selective digestion with methylation-sensitive restriction endonucleases. With the advent of sodium bisulfite treatment of DNA, a deamination reaction that converts cytosine to uracil only when unmethylated, the epigenetic modification can now be identified in the same manner as a DNA base-pair change. More recently, these three techniques have been applied to more technically advanced systems such as DNA microarrays and next-generation sequencing platforms, bringing us closer to unveiling a complete human epigenetic profile.

Epigenomic analysis of aberrantly methylated genes in colorectal cancer identifies genes commonly affected by epigenetic alterations

BACKGROUND

Determination of the profile of genes that are commonly methylated aberrantly in colorectal cancer (CRC) will have substantial value for diagnostic and therapeutic applications. However, there is limited knowledge of the DNA methylation pattern in CRC.

MATERIALS AND METHODS

We analyzed the methylation profile of 27,578 CpG sites spanning more than 14,000 genes in CRC and in the adjacent normal mucosa with bead-chip array-based technology.

RESULTS

We identified 621 CpG sites located in promoter regions and CpG islands that were greatly hypermethylated in CRC compared to normal mucosa. The genes on chromosome 18 showed promoter hypermethylation most frequently. According to gene ontology analysis, the most common biologically relevant class of genes affected by methylation was the class associated with the cadherin signaling pathway. Compared to the genome-wide expression array, mRNA expression was more likely to be downregulated in the genes demonstrating promoter hypermethylation, even though this was not statistically significant. We validated ten CpG sites that were hypermethylated (ADHFE1, BOLL, SLC6A15, ADAMTS5, TFPI2, EYA4, NPY, TWIST1, LAMA1, GAS7) and 2 CpG sites showing hypomethylation (MAEL, SFT2D3) in CRC compared to the normal mucosa in the array studies using pyrosequencing. The methylation status measured by pyrosequencing was consistent with the methylation array data.

CONCLUSIONS

Methylation profiling based on bead-chip arrays is an effective method for screening aberrantly methylated genes in CRC. In addition, we identified novel methylated genes that are candidate diagnostic or prognostic markers for CRC.

Profiling epigenetic alterations in disease

Nowadays, epigenetics is one of the fastest growing research areas in biomedicine. Studies have demonstrated that changes in the epigenome are not only common in cancer, but are also involved in the pathogenesis of noncancerous diseases like immunological, cardiovascular, developmental and neurological/psychiatric disorders. At the same time, during the last years, a technological revolution has taken place in the field of epigenomics, which is defined as the study of epigenetic changes throughout the whole genome. Microarray technologies and more recently, the development of next generation sequencing devices are now providing researchers with tools to draw high-resolution maps of DNA methylation and histone modifications in normal tissues and diseases. This chapter will review the currently available high-throughput techniques for studying the epigenome and their applications for characterizing human diseases.

Proteomic investigation of epigenetics in neuropsychiatric disorders: a missing link between genetics and behavior?

Neuropsychiatric disorders affect a large segment of the human population and result in large costs to society. The majority of such disorders have unknown underlying causes. Recent evidence suggests an important role for epigenetic regulation in the emergence of neuropsychiatric disease. Epigenetics may provide a link between genetic and environmental factors and behavior. Epigenetic signaling involves changes on the structure of chromatin; such changes are often triggered and maintained by the post-translational modification of chromatin proteins and/or DNA. Recent proteomic technologies have enabled the study of epigenetic mechanisms in a high-throughput manner. This review will provide an overview of the major epigenetic pathways and modern techniques for their study, before focusing on experimental evidence supporting a strong role for epigenetics in selected psychiatric disorders such as depression, schizophrenia, and drug addiction. These results highlight a great need for the inclusion of the proteomic characterization of epigenetic mechanisms in the study of gene/disease associations in psychiatric disorders.

Profiling DNA methylomes from microarray to genome-scale sequencing

DNA cytosine methylation is a central epigenetic modification which plays critical roles in cellular processes including genome regulation, development and disease. Here, we review current and emerging microarray and next-generation sequencing based technologies that enhance our knowledge of DNA methylation profiling. Each methodology has limitations and their unique applications, and combinations of several modalities may help build the entire methylome. With advances on next-generation sequencing technologies, it is now possible to globally map the DNA cytosine methylation at single-base resolution, providing new insights into the regulation and dynamics of DNA methylation in genomes.