Identification of methylation haplotype blocks aids in deconvolution of heterogeneous tissue samples and tumor tissue-of-origin mapping from plasma DNA

Bioinformatics Analysis for Cell-Free Tumor DNA Sequencing Data

As a major biomarker of liquid biopsy, cell-free tumor DNA (ctDNA), which can be extracted from blood, urine, or other circulating liquids, is able to provide comprehensive genetic information of tumor and better overcome the tumor heterogeneity problem comparing to tissue biopsy. Developed in recent years, next-generation sequencing (NGS) is a widely used technology for analyzing ctDNA. Although the technologies of processing ctDNA samples are mature, the task to detect low mutated allele frequency (MAF) variations from noisy sequencing data remains challenging. In this chapter, the authors will first explain the difficulties of analyzing ctDNA sequencing data, review related technologies, and then present some novel bioinformatics methods for analyzing ctDNA NGS data in better ways.

From Genotype to Phenotype: Through Chromatin

Advances in sequencing technologies have enabled the exploration of the genetic basis for several clinical disorders by allowing identification of causal mutations in rare genetic diseases. Sequencing technology has also facilitated genome-wide association studies to gather single nucleotide polymorphisms in common diseases including cancer and diabetes. Sequencing has therefore become common in the clinic for both prognostics and diagnostics. The success in follow-up steps, i.e., mapping mutations to causal genes and therapeutic targets to further the development of novel therapies, has nevertheless been very limited. This is because most mutations associated with diseases lie in inter-genic regions including the so-called regulatory genome. Additionally, no genetic causes are apparent for many diseases including neurodegenerative disorders. A complementary approach is therefore gaining interest, namely to focus on epigenetic control of the disease to generate more complete functional genomic maps. To this end, several recent studies have generated large-scale epigenetic datasets in a disease context to form a link between genotype and phenotype. We focus DNA methylation and important histone marks, where recent advances have been made thanks to technology improvements, cost effectiveness, and large meta-scale epigenome consortia efforts. We summarize recent studies unravelling the mechanistic understanding of epigenetic processes in disease development and progression. Moreover, we show how methodology advancements enable causal relationships to be established, and we pinpoint the most important issues to be addressed by future research.

Epigenetic Biomarkers in Cell-Free DNA and Applications in Liquid Biopsy

Cell-free circulating DNA (cfDNA) in plasma has gained global interest as a diagnostic material for noninvasive prenatal testing and cancer diagnosis, or the so-called “liquid biopsy”. Recent studies have discovered a great number of valuable genetic and epigenetic biomarkers for cfDNA-based liquid biopsy. Considering that the genetic biomarkers, e.g., somatic mutations, usually vary from case to case in most cancer patients, epigenetic biomarkers that are generalizable across various samples thus possess certain advantages. In this study, we reviewed the most recent studies and advances on utilizing epigenetic biomarkers for liquid biopsies. We first reviewed more traditional methods of using tissue/cancer-specific DNA methylation biomarkers and digital PCR or sequencing technologies for cancer diagnosis, as well as tumor origin determination. In the second part, we discussed the emerging novel approaches for exploring the biological basis and clinical applications of cfDNA fragmentation patterns. We further provided our comments and points of view on the future directions on epigenetic biomarker development for cfDNA-based liquid biopsies.

Molecular characterisation and liquid biomarkers in Carcinoma of Unknown Primary (CUP): taking the 'U' out of 'CUP'

Cancers of Unknown Primary (CUP) comprise a heterogeneous clinical entity of confirmed metastatic cancer where the primary site of origin is undetectable. It has a poor prognosis with limited treatment options. CUP is historically under-researched; however, understanding its biology has the potential to not only improve treatment and survival by implementation of biomarkers for patient management, but also to greatly contribute to our understanding of carcinogenesis and metastasis across all cancer types. Here we review the current advances in CUP research and explore the debated hypotheses underlying its biology. The evolution of molecular profiling and tissue-of-origin classifiers have the potential to transform the diagnosis, classification and therapeutic management of patients with CUP but robust evidence to support widespread use is lacking. Precision medicine has transformed treatment strategy in known tumour types; in CUP, however, there remains a clinical need for a better understanding of molecular characteristics to establish the potential role of novel or existing therapeutics. The emergence of liquid biopsies as a source of predictive and prognostic biomarkers within known tumour types is gaining rapid ground and this review explores the potential utility of liquid biopsies in CUP.

Analysis of genome-wide in cell free DNA methylation: progress and prospect

In this work, we focus on the detection methods of cfDNA methylation based on NGS and the latest progress.

Distal regulatory elements identified by methylation and hydroxymethylation haplotype blocks from mouse brain

Background

5-Hydroxymethylcytosine (5hmC) is an oxidation product of 5-methylcytosine (5mC), and adjacent CpG sites in mammalian genome can be co-methylated and co-hydroxymethylated due to the processivity of DNMT and TET enzymes.

Results

We applied TAB-seq and oxBS-seq to selectively detect 5hmC and 5mC at base resolution in the mouse cortex, olfactory bulb and cerebellum tissues. We found that majority of the called 5hmC CpG sites frequently have 5mC modification simultaneously and are enriched in gene body regions of neuron development-related genes in brain tissues. Strikingly, by a systematic search of regions that show highly coordinated methylation and hydroxymethylation (MHBs and hMHBs), we found that MHBs significantly overlapped with hMHBs in gene body regions. Moreover, using a metric called methylation haplotype load, we defined a subset of 1361 tissue-specific MHBs and 3818 shared MHBs. Shared MHBs with low MHL correspond with developmental enhancers, and tissue-specific MHBs resemble the regulatory elements for tissue identity.

Conclusions

Our results provide new insights into the role of coordinately oxidized 5mC to 5hmC as distal regulatory elements may involve in regulating tissue identity.

Electronic supplementary material

The online version of this article (10.1186/s13072-018-0248-3) contains supplementary material, which is available to authorized users.

Epigenetically reprogrammed methylation landscape drives the DNA self-assembly and serves as a universal cancer biomarker

Epigenetic reprogramming in cancer genomes creates a distinct methylation landscape encompassing clustered methylation at regulatory regions separated by large intergenic tracks of hypomethylated regions. This methylation landscape that we referred to as Methylscape is displayed by most cancer types, thus may serve as a universal cancer biomarker. To-date most research has focused on the biological consequences of DNA Methylscape changes whereas its impact on DNA physicochemical properties remains unexplored. Herein, we examine the effect of levels and genomic distribution of methylcytosines on the physicochemical properties of DNA to detect the Methylscape biomarker. We find that DNA polymeric behaviour is strongly affected by differential patterning of methylcytosine, leading to fundamental differences in DNA solvation and DNA-gold affinity between cancerous and normal genomes. We exploit these Methylscape differences to develop simple, highly sensitive and selective electrochemical or colorimetric one-step assays for the detection of cancer. These assays are quick, i.e., analysis time ≤10 minutes, and require minimal sample preparation and small DNA input.

DNA methylation is an epigenetic modification that control genetic programs. Here, the authors found that the methylation landscape influences the physicochemical properties of DNA and that it can serve as a universal cancer biomarker, and developed a one-step assay for the detection of cancer DNA.

Comprehensive human cell-type methylation atlas reveals origins of circulating cell-free DNA in health and disease

Methylation patterns of circulating cell-free DNA (cfDNA) contain rich information about recent cell death events in the body. Here, we present an approach for unbiased determination of the tissue origins of cfDNA, using a reference methylation atlas of 25 human tissues and cell types. The method is validated using in silico simulations as well as in vitro mixes of DNA from different tissue sources at known proportions. We show that plasma cfDNA of healthy donors originates from white blood cells (55%), erythrocyte progenitors (30%), vascular endothelial cells (10%) and hepatocytes (1%). Deconvolution of cfDNA from patients reveals tissue contributions that agree with clinical findings in sepsis, islet transplantation, cancer of the colon, lung, breast and prostate, and cancer of unknown primary. We propose a procedure which can be easily adapted to study the cellular contributors to cfDNA in many settings, opening a broad window into healthy and pathologic human tissue dynamics.

The methylation status of circulating cell-free DNA (cfDNA) can be informative about recent cell death events. Here the authors present an approach to determine the tissue origins of cfDNA, using a reference methylation atlas of 25 human tissues and cell types, and find that cfDNA from patients reveals tissue contributions that agree with clinical findings.

The 150 most important questions in cancer research and clinical oncology series: questions 94-101 : Edited by Cancer Communications

Since the beginning of 2017, Cancer Communications (former title: Chinese Journal of Cancer) has published a series of important questions regarding cancer research and clinical oncology, to provide an enhanced stimulus for cancer research, and to accelerate collaborations between institutions and investigators. In this edition, the following 8 valuable questions are presented. Question 94. The origin of tumors: time for a new paradigm? Question 95. How can we accelerate the identification of biomarkers for the early detection of pancreatic ductal adenocarcinoma? Question 96. Can we improve the treatment outcomes of metastatic pancreatic ductal adenocarcinoma through precision medicine guided by a combination of the genetic and proteomic information of the tumor? Question 97. What are the parameters that determine a competent immune system that gives a complete response to cancers after immune induction? Question 98. Is high local concentration of metformin essential for its anti-cancer activity? Question 99. How can we monitor the emergence of cancer cells anywhere in the body through plasma testing? Question 100. Can phytochemicals be more specific and efficient at targeting P-glycoproteins to overcome multi-drug resistance in cancer cells? Question 101. Is cell migration a selectable trait in the natural evolution of carcinoma?

New insights into structural features and optimal detection of circulating tumor DNA determined by single-strand DNA analysis

Circulating cell-free DNA (cfDNA) has received increasing interest as an apparent breakthrough approach in diagnostics, personalized medicine, and tumor biology. However, the structural features of cfDNA are poorly characterized. Specifically, the literature has discrepancies with regards to cfDNA size profile. We performed a blinded study of the distribution of cfDNA fragment sizes in cancer patient plasma (n = 11), by various ultra-deep-sequencing approaches and quantitative PCR (Q-PCR). Whole-genome sequencing of single-stranded DNA library preparation (SSP-S) revealed that nearly half of the total cfDNA fragment number are below 120 nucleotides, which are not readily detectable by standard double-stranded DNA library preparation (DSP) protocols. Fractional size distribution of cancer patient circulating DNA was very similar using both SSP-S-based or Q-PCR-based methods also revealing that high molecular weight (over 350 bp) cfDNA is a minor component (~2%). These extra small detected cfDNA fragments may mostly result from nicks occurring in blood circulation in one or both DNA strands, which are subsequently revealed through the denaturation step of the SSP and Q-PCR procedures. Detailed analysis of the data suggested that most of the detectable cfDNA in blood has a nucleosome footprint (∼10-bp periodicity repeats). The nucleosome is thus the most stabilizing structure of DNA in the circulation. cfDNA molecules, which are initially packed in chromatin, are released from cells and are then dynamically degraded in blood both within and between nucleosomes or transcription factor-associated subcomplexes. While this study provides new insights into cfDNA size profiles harmonizing sequencing and Q-PCR findings, our data validate the use of a specific Q-PCR method and SSP-S for obtaining an optimal qualitative and quantitative analytical signal.

Circulating tumor DNA: clinical roles in diffuse large B cell lymphoma

Diffuse large B cell lymphoma (DLBCL), the most common non-Hodgkin lymphoma (NHL), is a clinically and molecularly heterogeneous malignant lymphoproliferative disease. In the era of personalized medicine, genetic information is critical to early diagnosis, aiding risk stratification, directing therapeutic option, and monitoring disease relapse. However, lacking a circulating disease with most DLBCL cases hampers the acquisition of tumor genomic landscapes and disease dynamics. Circulating tumor DNA (ctDNA) is a novel noninvasive, real-time, and tumor-specific biomarker, reliably reflecting the comprehensive tumor genetic profiles, thus holds great promise in individualized medicine, including precise diagnosis and prognosis, response monitoring, and relapse detection of DLBCL. Here, we reviewed the recent advances of ctDNA in DLBCL and discussed its clinical values at different time points during the disease courses by comparing with the current routine methods in clinical practice. Collectively, we anticipated that ctDNA will ultimately be integrated into the management of DLBCL to facilitate precision medicine.

A similar effect of P16 hydroxymethylation and true-methylation on the prediction of malignant transformation of oral epithelial dysplasia: observation from a prospective study

Background

Total P16 methylation (P16M), including P16 hydroxymethylation (P16H) and true-P16M, correlates with malignant transformation of oral epithelial dysplasia (OED). Both true-P16M and P16H are early events in carcinogenesis. The aim of this study is to prospectively determine if discrimination of true-P16M from P16H is necessary for prediction of cancer development from OEDs.

Methods

Patients (n = 265) with mild or moderate OED were recruited into the double blind two-center cohort. Total-P16M and P16H were analyzed using the 115-bp MethyLight, TET-assisted bisulfite (TAB) methylation-specific PCR (MSP), and TAB-sequencing. Total-P16M-positive and P16H-negative samples were defined as true-P16M-positive. Progression of OEDs was monitored for a minimum 24 months follow-up period.

Results

P16H was detected in 23 of 73 (31.5%) total-P16M-positive OEDs. Follow-up information was obtained from 247 patients with an ultimate compliance rate of 93.2%. OED-derived squamous cell carcinomas were observed in 13.0% (32/247) patients during follow-up (median, 41.0 months). The cancer progression rate for total-P16M-positive patients was significantly increased when compared to total-P16M-negative patients [23.3% vs 8.6%; adjusted odds ratio = 2.67 (95% CI: 1.19–5.99)]. However, the cancer progression rates were similar between P16H- and true-P16M-positive OEDs [26.1% (6/23) vs 22.0% (11/50); odds ratio = 0.80 (95% CI: 0.22–2.92)]. The cancer-free survival was also similar for these patients.

Conclusion

P16H and true-P16M are similar biomarkers for determining malignant potential of OEDs. Discrimination of P16H from true-P16M, at least in OED, may be not necessary in clinical applications.

Trial registration

This study is registered prospectively in the U.S. National Institutes of Health Clinical Trials Protocol Registration System (trial number NCT02967120, available at https://ClinicalTrials.gov/ct2/show/NCT02967120).

Electronic supplementary material

The online version of this article (10.1186/s12885-018-4787-6) contains supplementary material, which is available to authorized users.

CancerDetector: ultrasensitive and non-invasive cancer detection at the resolution of individual reads using cell-free DNA methylation sequencing data

The detection of tumor-derived cell-free DNA in plasma is one of the most promising directions in cancer diagnosis. The major challenge in such an approach is how to identify the tiny amount of tumor DNAs out of total cell-free DNAs in blood. Here we propose an ultrasensitive cancer detection method, termed 'CancerDetector', using the DNA methylation profiles of cell-free DNAs. The key of our method is to probabilistically model the joint methylation states of multiple adjacent CpG sites on an individual sequencing read, in order to exploit the pervasive nature of DNA methylation for signal amplification. Therefore, CancerDetector can sensitively identify a trace amount of tumor cfDNAs in plasma, at the level of individual reads. We evaluated CancerDetector on the simulated data, and showed a high concordance of the predicted and true tumor fraction. Testing CancerDetector on real plasma data demonstrated its high sensitivity and specificity in detecting tumor cfDNAs. In addition, the predicted tumor fraction showed great consistency with tumor size and survival outcome. Note that all of those testing were performed on sequencing data at low to medium coverage (1× to 10×). Therefore, CancerDetector holds the great potential to detect cancer early and cost-effectively.

Principles of DNA methylation and their implications for biology and medicine

DNA methylation represents an annotation system for marking the genetic text, thus providing instruction as to how and when to read the information and control transcription. Unlike sequence information, which is inherited, methylation patterns are established in a programmed process that continues throughout development, thus setting up stable gene expression profiles. This DNA methylation paradigm is a key player in medicine. Some changes in methylation closely correlate with age providing a marker for biological ageing, and these same sites could also play a part in cancer. The genome continues to undergo programmed variation in methylation after birth in response to environmental inputs, serving as a memory device that could affect ageing and predisposition to various metabolic, autoimmune, and neurological diseases. Taking advantage of tissue-specific differences, methylation can be used to detect cell death and thereby monitor many common diseases with a simple cell-free circulating-DNA blood test.

The Clinical Landscape of Circulating Tumor DNA in Gastrointestinal Malignancies

Technologies for genomic analyses have revealed more details in cancer biology and have changed standard treatments for cancer, including the introduction of targeted gene-specific therapy. Currently, liquid biopsies are increasingly being utilized in clinical trials and research settings to analyze circulating tumor DNA (ctDNA) from peripheral blood. Several studies have shown the potential of ctDNA in the screening, prognostication, molecular profiling, and monitoring of gastrointestinal malignancies. Although limitations continue to exist in the use of ctDNA, such as method standardization, the sensitivity, concordance with tumor tissue, and regulatory issues, this field offers promising benefits for cancer treatment. A deeper understanding of tumor biology via ctDNA analyses and ctDNA-guided clinical trials will lead to the increasing use of ctDNA in clinical practice in the near future; this development will result in the improvement of outcomes among patients with gastrointestinal malignancies.

Establishment of environmentally sensitive DNA methylation states in the very early human embryo

The molecular mechanisms responsible for the developmental origins of later disease are currently unknown. We previously demonstrated that women's periconceptional nutrition predicts their offspring's DNA methylation at metastable epialleles (MEs). We present a genome-wide screen yielding 687 MEs and track their trajectories across nine developmental stages in human in vitro fertilization embryos. MEs exhibit highly unusual methylation dynamics across the implantation-gastrulation transition, producing a large excess of intermediate methylation states, suggesting the potential for differential programming in response to external signals. Using a natural experiment in rural Gambia, we show that genomic regions sensitive to season of conception are highly enriched for MEs and show similar atypical methylation patterns. MEs are enriched for proximal enhancers and transcription start sites and are influenced by genotype. Together, these observations position MEs as distinctive epigenomic features programmed in the early embryo, sensitive to genetic and periconceptional environment, and with the potential to influence phenotype.

Monitoring liver damage using hepatocyte-specific methylation markers in cell-free circulating DNA

Liver damage is typically inferred from serum measurements of cytoplasmic liver enzymes. DNA molecules released from dying hepatocytes are an alternative biomarker, unexplored so far, potentially allowing for quantitative assessment of liver cell death. Here we describe a method for detecting acute hepatocyte death, based on quantification of circulating, cell-free DNA (cfDNA) fragments carrying hepatocyte-specific methylation patterns. We identified 3 genomic loci that are unmethylated specifically in hepatocytes, and used bisulfite conversion, PCR, and massively parallel sequencing to quantify the concentration of hepatocyte-derived DNA in mixed samples. Healthy donors had, on average, 30 hepatocyte genomes/ml plasma, reflective of basal cell turnover in the liver. We identified elevations of hepatocyte cfDNA in patients shortly after liver transplantation, during acute rejection of an established liver transplant, and also in healthy individuals after partial hepatectomy. Furthermore, patients with sepsis had high levels of hepatocyte cfDNA, which correlated with levels of liver enzymes aspartate aminotransferase (AST) and alanine aminotransferase (ALT). Duchenne muscular dystrophy patients, in which elevated AST and ALT derive from damaged muscle rather than liver, did not have elevated hepatocyte cfDNA. We conclude that measurements of hepatocyte-derived cfDNA can provide specific and sensitive information on hepatocyte death, for monitoring human liver dynamics, disease, and toxicity.

Liver- and Colon-Specific DNA Methylation Markers in Plasma for Investigation of Colorectal Cancers with or without Liver Metastases

BACKGROUND

Measurement of DNA derived from different tissues in the circulating DNA pool can provide important information regarding the presence of many pathological conditions. However, existing methods involving genome-wide bisulfite sequencing are relatively expensive and may present challenges for large-scale analysis.

METHODS

Through identifying differentially methylated regions in the liver and colon compared with other tissues, we identified 2 markers and developed corresponding droplet digital PCR assays. Plasma concentrations of liver-derived and colon-derived DNA were measured for 13 liver transplant recipients, 40 liver cancer patients, and 62 colorectal cancer (CRC) patients (27 with and 35 without liver metastases).

RESULTS

In liver transplant recipients, the fractional concentration of liver-derived DNA measured using the liver-specific methylation marker and donor-specific alleles showed good correlation (Pearson R = 0.99). In liver cancer patients, the concentration of liver-derived DNA correlated positively with the maximal dimension of the tumor (Spearman R = 0.74). In CRC patients with and without liver metastasis, the plasma concentrations of colon-derived DNA (median, 138 copies/mL and 4 copies/mL, respectively) were increased compared with the 30 healthy controls (26 had undetectable concentrations). The absolute concentration of liver-derived DNA provided a better differentiation between CRC patients with and without liver metastasis compared with the fractional concentration (area under ROC curve, 0.85 vs 0.75).

CONCLUSIONS

Quantitative analysis of plasma DNA with tissue-specific methylation patterns using droplet digital PCR is applicable for the investigation of cancers and assessing organ transplantation. This approach is useful for differentiating patients with and without metastases to other organs.

Targeted methylation sequencing of plasma cell-free DNA for cancer detection and classification

Background

Targeted methylation sequencing of plasma cell-free DNA (cfDNA) has a potential to expand liquid biopsies to patients with tumors without detectable oncogenic alterations, which can be potentially useful in early diagnosis.

Patients and methods

We developed a comprehensive methylation sequencing assay targeting 9223 CpG sites consistently hypermethylated according to The Cancer Genome Atlas. Next, we carried out a clinical validation of our method using plasma cfDNA samples from 78 patients with advanced colorectal cancer, non-small-cell lung cancer (NSCLC), breast cancer or melanoma and compared results with patients' outcomes.

Results

Median methylation scores in plasma cfDNA samples from patients on therapy were lower than from patients off therapy (4.74 versus 85.29; P = 0.001). Of 68 plasma samples from patients off therapy, methylation scores detected the presence of cancer in 57 (83.8%), and methylation-based signatures accurately classified the underlying cancer type in 45 (78.9%) of these. Methylation scores were most accurate in detecting colorectal cancer (96.3%), followed by breast cancer (91.7%), melanoma (81.8%) and NSCLC (61.1%), and most accurate in classifying the underlying cancer type in colorectal cancer (88.5%), followed by NSCLC (81.8%), breast cancer (72.7%) and melanoma (55.6%). Low methylation scores versus high were associated with longer survival (10.4 versus 4.4 months, P < 0.001) and longer time-to-treatment failure (2.8 versus 1.6 months, P = 0.016).

Conclusions

Comprehensive targeted methylation sequencing of 9223 CpG sites in plasma cfDNA from patients with common advanced cancers detects the presence of cancer and underlying cancer type with high accuracy. Methylation scores in plasma cfDNA correspond with treatment outcomes.

An optimized library for reference-based deconvolution of whole-blood biospecimens assayed using the Illumina HumanMethylationEPIC BeadArray

Genome-wide methylation arrays are powerful tools for assessing cell composition of complex mixtures. We compare three approaches to select reference libraries for deconvoluting neutrophil, monocyte, B-lymphocyte, natural killer, and CD4+ and CD8+ T-cell fractions based on blood-derived DNA methylation signatures assayed using the Illumina HumanMethylationEPIC array. The IDOL algorithm identifies a library of 450 CpGs, resulting in an average R2 = 99.2 across cell types when applied to EPIC methylation data collected on artificial mixtures constructed from the above cell types. Of the 450 CpGs, 69% are unique to EPIC. This library has the potential to reduce unintended technical differences across array platforms.

BoostMe accurately predicts DNA methylation values in whole-genome bisulfite sequencing of multiple human tissues

Background

Bisulfite sequencing is widely employed to study the role of DNA methylation in disease; however, the data suffer from biases due to coverage depth variability. Imputation of methylation values at low-coverage sites may mitigate these biases while also identifying important genomic features associated with predictive power.

Results

Here we describe BoostMe, a method for imputing low-quality DNA methylation estimates within whole-genome bisulfite sequencing (WGBS) data. BoostMe uses a gradient boosting algorithm, XGBoost, and leverages information from multiple samples for prediction. We find that BoostMe outperforms existing algorithms in speed and accuracy when applied to WGBS of human tissues. Furthermore, we show that imputation improves concordance between WGBS and the MethylationEPIC array at low WGBS depth, suggesting improved WGBS accuracy after imputation.

Conclusions

Our findings support the use of BoostMe as a preprocessing step for WGBS analysis.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4766-y) contains supplementary material, which is available to authorized users.

Epigenetics and Precision Oncology

Epigenetic alterations such as DNA methylation defects and aberrant covalent histone modifications occur within all cancers and are selected for throughout the natural history of tumor formation, with changes being detectable in early onset, progression, and ultimately recurrence and metastasis. The ascertainment and use of these marks to identify at-risk patient populations, refine diagnostic criteria, and provide prognostic and predictive factors to guide treatment decisions are of growing clinical relevance. Furthermore, the targetable nature of epigenetic modifications provides a unique opportunity to alter treatment paradigms and provide new therapeutic options for patients whose malignancies possess these aberrant epigenetic modifications, paving the way for new and personalized medicine. DNA methylation has proven to be of significant clinical utility for its stability and relative ease of testing. The intent of this review is to elaborate upon well-supported examples of epigenetic precision medicine and how the field is moving forward, primarily in the context of aberrant DNA methylation.

DNA Methylation Patterns in Normal Tissue Correlate more Strongly with Breast Cancer Status than Copy-Number Variants

Normal tissue at risk of neoplastic transformation is characterized by somatic mutations, copy-number variation and DNA methylation changes. It is unclear however, which type of alteration may be more informative of cancer risk. We analyzed genome-wide DNA methylation and copy-number calls from the same DNA assay in a cohort of healthy breast samples and age-matched normal samples collected adjacent to breast cancer. Using statistical methods to adjust for cell type heterogeneity, we show that DNA methylation changes can discriminate normal-adjacent from normal samples better than somatic copy-number variants. We validate this important finding in an independent dataset. These results suggest that DNA methylation alterations in the normal cell of origin may offer better cancer risk prediction and early detection markers than copy-number changes.

Enrichment of methylated molecules using enhanced-ice-co-amplification at lower denaturation temperature-PCR (E-ice-COLD-PCR) for the sensitive detection of disease-related hypermethylation

AIM

The detection of specific DNA methylation patterns bears great promise as biomarker for personalized management of cancer patients. Co-amplification at lower denaturation temperature-PCR (COLD-PCR) assays are sensitive methods, but have previously only been able to analyze loss of DNA methylation.

MATERIALS & METHODS

Enhanced (E)-ice-COLD-PCR reactions starting from 2 ng of bisulfite-converted DNA were developed to analyze methylation patterns in two promoters with locked nucleic acid (LNA) probes blocking amplification of unmethylated CpGs. The enrichment of methylated molecules was compared to quantitative (q)PCR and quantified using serial dilutions.

RESULTS

E-ice-COLD-PCR allowed the multiplexed enrichment and quantification of methylated DNA. Assays were validated in primary breast cancer specimens and circulating cell-free DNA from cancer patients.

CONCLUSION

E-ice-COLD-PCR could prove a useful tool in the context of DNA methylation analysis for personalized medicine.

Non-invasive detection of human cardiomyocyte death using methylation patterns of circulating DNA

Detection of cardiomyocyte death is crucial for the diagnosis and treatment of heart disease. Here we use comparative methylome analysis to identify genomic loci that are unmethylated specifically in cardiomyocytes, and develop these as biomarkers to quantify cardiomyocyte DNA in circulating cell-free DNA (cfDNA) derived from dying cells. Plasma of healthy individuals contains essentially no cardiomyocyte cfDNA, consistent with minimal cardiac turnover. Patients with acute ST-elevation myocardial infarction show a robust cardiac cfDNA signal that correlates with levels of troponin and creatine phosphokinase (CPK), including the expected elevation-decay dynamics following coronary angioplasty. Patients with sepsis have high cardiac cfDNA concentrations that strongly predict mortality, suggesting a major role of cardiomyocyte death in mortality from sepsis. A cfDNA biomarker for cardiomyocyte death may find utility in diagnosis and monitoring of cardiac pathologies and in the study of normal human cardiac physiology and development.

The detection of cardiomyocyte death is a critical aspect in the diagnosis and monitoring of heart diseases. Here the authors show that cardiomyocyte-specific methylation patterns of circulating cell-free DNA may serve as a biomarker of cardiac cell death in infarcted and septic patients.

An epigenomic approach to identifying differential overlapping and cis-acting lncRNAs in cisplatin-resistant cancer cells

Long noncoding RNAs (lncRNAs) are critical regulators of cell biology whose alteration can lead to the development of diseases such as cancer. The potential role of lncRNAs and their epigenetic regulation in response to platinum treatment are largely unknown. We analyzed four paired cisplatin-sensitive/resistant non-small cell lung cancer and ovarian cancer cell lines. The epigenetic landscape of overlapping and cis-acting lncRNAs was determined by combining human microarray data on 30,586 lncRNAs and 20,109 protein coding mRNAs with whole-genome bisulfite sequencing. Selected candidate lncRNAs were further characterized by PCR, gene-ontology analysis, and targeted bisulfite sequencing. Differential expression in response to therapy was observed more frequently in cis-acting than in overlapping lncRNAs (78% vs. 22%, fold change ≥1.5), while significantly altered methylation profiles were more commonly associated with overlapping lncRNAs (29% vs. 8%; P value <0.001). Moreover, overlapping lncRNAs contain more CpG islands (CGIs) (25% vs. 17%) and the majority of CGI-containing overlapping lncRNAs share these CGIs with their associated coding genes (84%). The differences in expression between sensitive and resistant cell lines were replicated in 87% of the selected candidates (P<0.05), while our bioinformatics approach identifying differential methylation was confirmed in all of the selected lncRNAs (100%). Five lncRNAs under epigenetic regulation appear to be involved in cisplatin resistance (AC091814.2, AC141928.1, RP11-65J3.1-002, BX641110, and AF198444). These novel findings provide new insights into epigenetic mechanisms and acquired resistance to cisplatin that highlight specific lncRNAs, some with unknown function, that may signal strategies in epigenetic therapies.

The value of cell-free DNA for molecular pathology

Over the past decade, advances in molecular biology and genomics techniques have revolutionized the diagnosis and treatment of cancer. The technological advances in tissue profiling have also been applied to the study of cell-free nucleic acids, an area of increasing interest for molecular pathology. Cell-free nucleic acids are released from tumour cells into the surrounding body fluids and can be assayed non-invasively. The repertoire of genomic alterations in circulating tumour DNA (ctDNA) is reflective of both primary tumours and distant metastatic sites, and ctDNA can be sampled multiple times, thereby overcoming the limitations of the analysis of single biopsies. Furthermore, ctDNA can be sampled regularly to monitor response to treatment, to define the evolution of the tumour genome, and to assess the acquisition of resistance and minimal residual disease. Recently, clinical ctDNA assays have been approved for guidance of therapy, which is an exciting first step in translating cell-free nucleic acid research tests into clinical use for oncology. In this review, we discuss the advantages of cell-free nucleic acids as analytes in different body fluids, including blood plasma, urine, and cerebrospinal fluid, and their clinical applications in solid tumours and haematological malignancies. We will also discuss practical considerations for clinical deployment, such as preanalytical factors and regulatory requirements. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Liquid biopsies: DNA methylation analyses in circulating cell-free DNA

Analysis of patient's materials like cells or nucleic acids obtained in a minimally invasive or noninvasive manner through the sampling of blood or other body fluids serves as liquid biopsies, which has huge potential for numerous diagnostic applications. Circulating cell-free DNA (cfDNA) is explored as a prognostic or predictive marker of liquid biopsies with the improvements in genomic and molecular methods. DNA methylation is an important epigenetic marker known to affect gene expression. cfDNA methylation detection is a very promising approach as abnormal distribution of DNA methylation is one of the hallmarks of many cancers and methylation changes occur early during carcinogenesis. This review summarizes the various investigational applications of cfDNA methylation and its oxidized derivatives as biomarkers for cancer diagnosis, prenatal diagnosis and organ transplantation monitoring. The review also provides a brief overview of the technologies for cfDNA methylation analysis based on next generation sequencing.

DNA methylation in human diseases

Even though the importance of epigenetics was first recognized in light of its role in tissue development, an increasing amount of evidence has shown that it also plays an important role in the development and progression of many common diseases. We discuss some recent findings on one representative epigenetic modification, DNA methylation, in some common diseases. While many new risk factors have been identified through the population-based epigenetic epidemiologic studies on the role of epigenetics in common diseases, this relatively new field still faces many unique challenges. Here, we describe those promises and unique challenges of epigenetic epidemiological studies and propose some potential solutions.

Cell-type-specific brain methylomes profiled via ultralow-input microfluidics

Methylomic analyses typically require substantial amounts of DNA, thus hindering studies involving scarce samples. Here, we show that microfluidic diffusion-based reduced representative bisulfite sequencing (MID-RRBS) permits high-quality methylomic profiling with nanogram-to-single-cell quantities of starting DNA. We used the microfluidic device, which allows for efficient bisulfite conversion with high DNA recovery, to analyse genome-wide DNA methylation in cell nuclei isolated from mouse brains and sorted into NeuN+ (primarily neuronal) and NeuN- (primarily glial) fractions, and to establish cell-type-specific methylomes. Genome-wide methylation and methylation in low-CpG-density promoter regions showed distinct patterns for NeuN+ and NeuN- fractions from the mouse cerebellum. The identification of substantial variations in the methylomic landscapes of the NeuN+ fraction of the frontal cortex of mice chronically treated with an atypical antipsychotic drug suggests that this technology can be broadly used for cell-type-specific drug profiling and for the study of drug-methylome interactions.

Molecular roles and function of circular RNAs in eukaryotic cells

Protein-coding and noncoding genes in eukaryotes are typically expressed as linear messenger RNAs, with exons arranged colinearly to their genomic order. Recent advances in sequencing and in mapping RNA reads to reference genomes have revealed that thousands of genes express also covalently closed circular RNAs. Many of these circRNAs are stable and contain exons, but are not translated into proteins. Here, we review the emerging understanding that both, circRNAs produced by co- and posttranscriptional head-to-tail "backsplicing" of a downstream splice donor to a more upstream splice acceptor, as well as circRNAs generated from intronic lariats during colinear splicing, may exhibit physiologically relevant regulatory functions in eukaryotes. We describe how circRNAs impact gene expression of their host gene locus by affecting transcriptional initiation and elongation or splicing, and how they partake in controlling the function of other molecules, for example by interacting with microRNAs and proteins. We conclude with an outlook how circRNA dysregulation affects disease, and how the stability of circRNAs might be exploited in biomedical applications.

Developing DNA methylation-based diagnostic biomarkers

An emerging paradigm shift for disease diagnosis is to rely on molecular characterization beyond traditional clinical and symptom-based examinations. Although genetic alterations and transcription signature were first introduced as potential biomarkers, clinical implementations of these markers are limited due to low reproducibility and accuracy. Instead, epigenetic changes are considered as an alternative approach to disease diagnosis. Complex epigenetic regulation is required for normal biological functions and it has been shown that distinctive epigenetic disruptions could contribute to disease pathogenesis. Disease-specific epigenetic changes, especially DNA methylation, have been observed, suggesting its potential as disease biomarkers for diagnosis. In addition to specificity, the feasibility of detecting disease-associated methylation marks in the biological specimens collected noninvasively, such as blood samples, has driven the clinical studies to validate disease-specific DNA methylation changes as a diagnostic biomarker. Here, we highlight the advantages of DNA methylation signature for diagnosis in different diseases and discuss the statistical and technical challenges to be overcome before clinical implementation.

A Summary of the Biological Processes, Disease-Associated Changes, and Clinical Applications of DNA Methylation

DNA methylation at cytosines followed by guanines, CpGs, 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 local genomic and higher-order chromatin landscape. DNA methylation is essential for proper mammalian development, crucial for imprinting and plays a role in maintaining genomic stability. 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 life. Changes of DNA methylation levels and patterns have been widely studied in several diseases, especially cancer, where interest has focused on biomarkers for early detection of cancer development, accurate diagnosis, and response to treatment, but have also been shown to occur in many other complex diseases. Recent advances in epigenome engineering technologies allow now for the large-scale assessment of the functional relevance of DNA methylation. As a stable nucleic acid-based modification that is technically easy to handle and which can be analyzed with great reproducibility and accuracy by different laboratories, DNA methylation is a promising biomarker for many applications.

Integration of human pancreatic islet genomic data refines regulatory mechanisms at Type 2 Diabetes susceptibility loci

Human genetic studies have emphasised the dominant contribution of pancreatic islet dysfunction to development of Type 2 Diabetes (T2D). However, limited annotation of the islet epigenome has constrained efforts to define the molecular mechanisms mediating the, largely regulatory, signals revealed by Genome-Wide Association Studies (GWAS). We characterised patterns of chromatin accessibility (ATAC-seq, n = 17) and DNA methylation (whole-genome bisulphite sequencing, n = 10) in human islets, generating high-resolution chromatin state maps through integration with established ChIP-seq marks. We found enrichment of GWAS signals for T2D and fasting glucose was concentrated in subsets of islet enhancers characterised by open chromatin and hypomethylation, with the former annotation predominant. At several loci (including CDC123, ADCY5, KLHDC5) the combination of fine-mapping genetic data and chromatin state enrichment maps, supplemented by allelic imbalance in chromatin accessibility pinpointed likely causal variants. The combination of increasingly-precise genetic and islet epigenomic information accelerates definition of causal mechanisms implicated in T2D pathogenesis.

The potential of circulating tumor DNA methylation analysis for the early detection and management of ovarian cancer

Background

Despite a myriad of attempts in the last three decades to diagnose ovarian cancer (OC) earlier, this clinical aim still remains a significant challenge. Aberrant methylation patterns of linked CpGs analyzed in DNA fragments shed by cancers into the bloodstream (i.e. cell-free DNA) can provide highly specific signals indicating cancer presence.

Methods

We analyzed 699 cancerous and non-cancerous tissues using a methylation array or reduced representation bisulfite sequencing to discover the most specific OC methylation patterns. A three-DNA-methylation-serum-marker panel was developed using targeted ultra-high coverage bisulfite sequencing in 151 women and validated in 250 women with various conditions, particularly in those associated with high CA125 levels (endometriosis and other benign pelvic masses), serial samples from 25 patients undergoing neoadjuvant chemotherapy, and a nested case control study of 172 UKCTOCS control arm participants which included serum samples up to two years before OC diagnosis.

Results

The cell-free DNA amount and average fragment size in the serum samples was up to ten times higher than average published values (based on samples that were immediately processed) due to leakage of DNA from white blood cells owing to delayed time to serum separation. Despite this, the marker panel discriminated high grade serous OC patients from healthy women or patients with a benign pelvic mass with specificity/sensitivity of 90.7% (95% confidence interval [CI] = 84.3–94.8%) and 41.4% (95% CI = 24.1–60.9%), respectively. Levels of all three markers plummeted after exposure to chemotherapy and correctly identified 78% and 86% responders and non-responders (Fisher’s exact test, p = 0.04), respectively, which was superior to a CA125 cut-off of 35 IU/mL (20% and 75%). 57.9% (95% CI 34.0–78.9%) of women who developed OC within two years of sample collection were identified with a specificity of 88.1% (95% CI = 77.3–94.3%). Sensitivity and specificity improved further when specifically analyzing CA125 negative samples only (63.6% and 87.5%, respectively).

Conclusions

Our data suggest that DNA methylation patterns in cell-free DNA have the potential to detect a proportion of OCs up to two years in advance of diagnosis and may potentially guide personalized treatment. The prospective use of novel collection vials, which stabilize blood cells and reduce background DNA contamination in serum/plasma samples, will facilitate clinical implementation of liquid biopsy analyses.

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-017-0500-7) contains supplementary material, which is available to authorized users.

Identification of the functional alteration signatures across different cancer types with support vector machine and feature analysis

Cancers are regarded as malignant proliferations of tumor cells present in many tissues and organs, which can severely curtail the quality of human life. The potential of using plasma DNA for cancer detection has been widely recognized, leading to the need of mapping the tissue-of-origin through the identification of somatic mutations. With cutting-edge technologies, such as next-generation sequencing, numerous somatic mutations have been identified, and the mutation signatures have been uncovered across different cancer types. However, somatic mutations are not independent events in carcinogenesis but exert functional effects. In this study, we applied a pan-cancer analysis to five types of cancers: (I) breast cancer (BRCA), (II) colorectal adenocarcinoma (COADREAD), (III) head and neck squamous cell carcinoma (HNSC), (IV) kidney renal clear cell carcinoma (KIRC), and (V) ovarian cancer (OV). Based on the mutated genes of patients suffering from one of the aforementioned cancer types, patients they were encoded into a large number of numerical values based upon the enrichment theory of gene ontology (GO) terms and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. We analyzed these features with the Monte-Carlo Feature Selection (MCFS) method, followed by the incremental feature selection (IFS) method to identify functional alteration features that could be used to build the support vector machine (SVM)-based classifier for distinguishing the five types of cancers. Our results showed that the optimal classifier with the selected 344 features had the highest Matthews correlation coefficient value of 0.523. Sixteen decision rules produced by the MCFS method can yield an overall accuracy of 0.498 for the classification of the five cancer types. Further analysis indicated that some of these features and rules were supported by previous experiments. This study not only presents a new approach to mapping the tissue-of-origin for cancer detection but also unveils the specific functional alterations of each cancer type, providing insight into cancer-specific functional aberrations as potential therapeutic targets. This article is part of a Special Issue entitled: Accelerating Precision Medicine through Genetic and Genomic Big Data Analysis edited by Yudong Cai & Tao Huang.

Targeted bisulfite sequencing identified a panel of DNA methylation-based biomarkers for esophageal squamous cell carcinoma (ESCC)

Background

DNA methylation has been implicated as a promising biomarker for precise cancer diagnosis. However, limited DNA methylation-based biomarkers have been described in esophageal squamous cell carcinoma (ESCC).

Methods

A high-throughput DNA methylation dataset (100 samples) of ESCC from The Cancer Genome Atlas (TCGA) project was analyzed and validated along with another independent dataset (12 samples) from the Gene Expression Omnibus (GEO) database. The methylation status of peripheral blood mononuclear cells and peripheral blood leukocytes from healthy controls was also utilized for biomarker selection. The candidate CpG sites as well as their adjacent regions were further validated in 94 pairs of ESCC tumor and adjacent normal tissues from the Chinese Han population using the targeted bisulfite sequencing method. Logistic regression and several machine learning methods were applied for evaluation of the diagnostic ability of our panel.

Results

In the discovery stage, five hyper-methylated CpG sites were selected as candidate biomarkers for further analysis as shown below: cg15830431, P = 2.20 × 10⁻⁴; cg19396867, P = 3.60 × 10⁻⁴; cg20655070, P = 3.60 × 10⁻⁴; cg26671652, P = 5.77 × 10⁻⁴; and cg27062795, P = 3.60 × 10⁻⁴. In the validation stage, the methylation status of both the five CpG sites and their adjacent genomic regions were tested. The diagnostic model based on the combination of these five genomic regions yielded a robust performance (sensitivity = 0.75, specificity = 0.88, AUC = 0.85). Eight statistical models along with five-fold cross-validation were further applied, in which the SVM model reached the best accuracy in both training and test dataset (accuracy = 0.82 and 0.80, respectively). In addition, subgroup analyses revealed a significant difference in diagnostic performance between the alcohol use and non-alcohol use subgroups.

Conclusions

Methylation profiles of the five genomic regions covering cg15830431 (STK3), cg19396867, cg20655070, cg26671652 (ZNF418), and cg27062795 (ZNF542) can be used for effective methylation-based testing for ESCC diagnosis.

Electronic supplementary material

The online version of this article (10.1186/s13148-017-0430-7) contains supplementary material, which is available to authorized users.

Factors involved in cancer metastasis: a better understanding to "seed and soil" hypothesis

Metastasis has intrigued researchers for more than 100 years. Despite the development of technologies and therapeutic strategies, metastasis is still the major cause of cancer-related death until today. The famous "seed and soil" hypothesis is widely cited and accepted, and it still provides significant instructions in cancer research until today. To our knowledge, there are few reviews that comprehensively and correlatively focus on both the seed and soil factors involved in cancer metastasis; moreover, despite the fact that increasingly underlying mechanisms and concepts have been defined recently, previous perspectives are appealing but may be limited. Hence, we reviewed factors involved in cancer metastasis, including both seed and soil factors. By integrating new concepts with the classic hypothesis, we aim to provide a comprehensive understanding of the "seed and soil" hypothesis and to conceptualize the framework for understanding factors involved in cancer metastasis. Based on a dynamic overview of this field, we also discuss potential implications for future research and clinical therapeutic strategies.

Statistical and integrative system-level analysis of DNA methylation data

Epigenetics plays a key role in cellular development and function. Alterations to the epigenome are thought to capture and mediate the effects of genetic and environmental risk factors on complex disease. Currently, DNA methylation is the only epigenetic mark that can be measured reliably and genome-wide in large numbers of samples. This Review discusses some of the key statistical challenges and algorithms associated with drawing inferences from DNA methylation data, including cell-type heterogeneity, feature selection, reverse causation and system-level analyses that require integration with other data types such as gene expression, genotype, transcription factor binding and other epigenetic information.

Circulating tumour DNA methylation markers for diagnosis and prognosis of hepatocellular carcinoma

An effective blood-based method for the diagnosis and prognosis of hepatocellular carcinoma (HCC) has not yet been developed. Circulating tumour DNA (ctDNA) carrying cancer-specific genetic and epigenetic aberrations may enable a noninvasive 'liquid biopsy' for diagnosis and monitoring of cancer. Here, we identified an HCC-specific methylation marker panel by comparing HCC tissue and normal blood leukocytes and showed that methylation profiles of HCC tumour DNA and matched plasma ctDNA are highly correlated. Using cfDNA samples from a large cohort of 1,098 HCC patients and 835 normal controls, we constructed a diagnostic prediction model that showed high diagnostic specificity and sensitivity (P < 0.001) and was highly correlated with tumour burden, treatment response, and stage. Additionally, we constructed a prognostic prediction model that effectively predicted prognosis and survival (P < 0.001). Together, these findings demonstrate in a large clinical cohort the utility of ctDNA methylation markers in the diagnosis, surveillance, and prognosis of HCC.

The emerging roles of NGS-based liquid biopsy in non-small cell lung cancer

The treatment paradigm of non-small cell lung cancer (NSCLC) has evolved into oncogene-directed precision medicine. Identifying actionable genomic alterations is the initial step towards precision medicine. An important scientific progress in molecular profiling of NSCLC over the past decade is the shift from the traditional piecemeal fashion to massively parallel sequencing with the use of next-generation sequencing (NGS). Another technical advance is the development of liquid biopsy with great potential in providing a dynamic and comprehensive genomic profiling of NSCLC in a minimally invasive manner. The integration of NGS with liquid biopsy has been demonstrated to play emerging roles in genomic profiling of NSCLC by increasing evidences. This review summarized the potential applications of NGS-based liquid biopsy in the diagnosis and treatment of NSCLC including identifying actionable genomic alterations, tracking spatiotemporal tumor evolution, dynamically monitoring response and resistance to targeted therapies, and diagnostic value in early-stage NSCLC, and discussed emerging challenges to overcome in order to facilitate clinical translation in future.