DNA Methylation as a Noninvasive Epigenetic Biomarker for the Detection of Cancer

E74-like Factor 5 Promoter Methylation in Circulating Tumor DNA as a Potential Prognostic Marker in Breast Cancer Patients

BACKGROUND

Epigenetic alternations, such as DNA methylation, play a crucial role in breast tumor initiation and progression. The identification of noninvasive prognostic biomarkers has great importance in cancer management. Methylated cell-free DNA (cfDNA), circulating in the blood as a convenient tumor-associated DNA marker, can be used as a minimally invasive cancer biomarker. This study aimed to evaluate the promoter methylation status of E74-like factor 5 (ELF5) tumor suppressor gene in both tumors and plasma cell-free DNA of 80 breast cancer patients, compared with normal controls.

METHODS

Plasma cfDNA concentrations were measured using quantitative real-time PCR, and methylation pattern in the ELF5 gene promoter region was performed using methylation-specific polymerase chain reaction (MS-PCR) technique.

RESULTS

The data revealed a statistically significant increase in cfDNA concentrations in breast cancer patients, particularly in those with higher stages of the disease, triple-negative status, and metastasis (p<0.001). ELF5 promoter region hypermethylation was observed in 70% of breast cancer patients in both plasma cfDNA and tumor tissues. Notably, all patients with lymph node involvement and distant metastatic exhibited promoter hypermethylation in the ELF5 gene.

CONCLUSION

Our findings suggest that ELF5 promoter methylation in circulating DNA could serve as a potential non-invasive prognostic molecular marker in breast cancer patients. However, further studies are warranted to evaluate its diagnostic value.

DNA Methylation Biomarkers as Prediction Tools for Therapeutic Response and Prognosis in Intermediate-Stage Hepatocellular Carcinoma

INTRODUCTION

Alfa-fetoprotein (AFP), as the main serum tumor marker of hepatocellular carcinoma (HCC), is limited in terms of specificity and ability to predict outcomes. This study investigated the clinical utility of DNA methylation biomarkers to predict therapeutic responses and prognosis in intermediate-stage HCC.

METHODS

This study enrolled 72 patients with intermediate-stage HCC who underwent locoregional therapy (LRT) between 2020 and 2021. The immediate therapeutic response and disease status during a two-year follow-up were recorded. Analysis was performed on 10 selected DNA methylation biomarkers via pyrosequencing analysis of plasma collected before and after LRT.

RESULTS

Analysis was performed on 53 patients with complete responses and 19 patients with disease progression after LRT. The mean follow-up duration was 2.4 ± 0.6 years. A methylation prediction model for tumor response (MMTR) and a methylation prediction model for early progression (MMEP) were constructed. The area under the curve (AUC) for sensitivity and specificity of MMTR was 0.79 for complete response and 0.759 for overall survival. The corresponding AUCs for sensitivity and specificity of AFP and protein induced by vitamin K absence-II (PIVKA-II) were 0.717 and 0.708, respectively. Note that the MMTR index was the only significant predictor in multivariate analysis. The AUC for sensitivity and specificity of the MMEP in predicting early progression was 0.79. The corresponding AUCs for sensitivity and specificity of AFP and PIVKA-II were 0.758 and 0.714, respectively. Multivariate analysis revealed that platelet count, beyond up-to-7 criteria, and the MMEP index were strongly correlated with early tumor progression. Combining the indexes and serum markers further improved the predictive accuracy (AUC = 0.922). Multivariate analysis revealed the MMEP index was the only independent risk factor for overall survival.

DISCUSSION/CONCLUSIONS

This study indicates that these methylation markers could potentially outperform current serum markers in terms of accuracy and reliability in assessing treatment response and predicting outcomes. Combining methylation markers and serum markers further improved predictive accuracy, indicating that a multi-marker approach may be more effective in clinical practice. These findings suggest that DNA methylation biomarkers may be a useful tool for managing intermediate-stage HCC patients and guiding personalized treatment, particularly for those who are at high risk for close surveillance or adjuvant treatment after LRT.

The deficiency of 5-methylcytosine (5mC) and its ramification in the occurrence and prognosis of colon cancer

The incidence and mortality of colon cancer are increasing, and effective biomarkers for its diagnosis are limited. 5-methylcytosine (5mC), a vital DNA methylation marker, plays important roles in gene expression, genomic imprinting, and transposon inhibition. This study aimed to identify the predictors of colon cancer prognosis and lay the foundation for research on therapeutic targets by detecting the levels of 5mC, 5-hydroxymethylcytosine (5hmC), 5-formyl cytosine (5fC), and 5-carboxylcytosine (5caC) in colon cancer and adjacent non-tumor tissues. A tissue microarray including 100 colon cancer tissue samples and 60 adjacent non-tumor tissue samples was used. The expression levels of 5mC and its ramifications were assessed by immunohistochemistry. According to the expression levels, patients were divided into moderately positive and strongly positive groups, and the correlation between clinicopathological characteristics and methylation marks was assessed using 2-sided chi-square tests. The prognostic values of 5mC, 5hmC, 5fC, and 5caC were tested using Kaplan-Meier analyses. Compared with adjacent non-tumor tissues, the overall levels of DNA methylation were lower in colon carcinoma lesions. However, the clinical parameters were not significantly associated with these methylation markers, except for 5hmC, which was associated with the age of cancer patients (P value = .043). Kaplan-Meier analysis disclosed that moderate positive group had a significantly shorter disease specific survival than strong positive group for patients with different levels of 5mC (65.2 vs 95.2 months, P = .014) and 5hmC (71.2 vs 97.5 months, P = .045). 5mC and its ramifications (5hmC, 5fC, and 5caC) can serve as biomarkers for colon cancer. 5mC and 5hmC are stable predictors and therapeutic targets in colon cancer. However, further understanding of its function will help to reveal the complex tumorigenic process and identify new therapeutic strategies.

Molecular mechanisms of multi-omic regulation in breast cancer

Breast cancer is a complex disease that is influenced by the concurrent influence of multiple genetic and environmental factors. Recent advances in genomics and other high throughput biomolecular techniques (-omics) have provided numerous insights into the molecular mechanisms underlying breast cancer development and progression. A number of these mechanisms involve multiple layers of regulation. In this review, we summarize the current knowledge on the role of multiple omics in the regulation of breast cancer, including the effects of DNA methylation, non-coding RNA, and other epigenomic changes. We comment on how integrating such diverse mechanisms is envisioned as key to a more comprehensive understanding of breast carcinogenesis and cancer biology with relevance to prognostics, diagnostics and therapeutics. We also discuss the potential clinical implications of these findings and highlight areas for future research. Overall, our understanding of the molecular mechanisms of multi-omic regulation in breast cancer is rapidly increasing and has the potential to inform the development of novel therapeutic approaches for this disease.

Utility of DNA Methylation as a Biomarker in Aging and Alzheimer's Disease

Epigenetic mechanisms such as DNA methylation have been implicated in a number of diseases including cancer, heart disease, autoimmune disorders, and neurodegenerative diseases. While it is recognized that DNA methylation is tissue-specific, a limitation for many studies is the ability to sample the tissue of interest, which is why there is a need for a proxy tissue such as blood, that is reflective of the methylation state of the target tissue. In the last decade, DNA methylation has been utilized in the design of epigenetic clocks, which aim to predict an individual's biological age based on an algorithmically defined set of CpGs. A number of studies have found associations between disease and/or disease risk with increased biological age, adding weight to the theory of increased biological age being linked with disease processes. Hence, this review takes a closer look at the utility of DNA methylation as a biomarker in aging and disease, with a particular focus on Alzheimer's disease.

Impact of mini-driver genes in the prognosis and tumor features of colorectal cancer samples: a novel perspective to support current biomarkers

Background

Colorectal cancer (CRC) is the second leading cause of cancer-related deaths, and its development is associated with the gains and/or losses of genetic material, which leads to the emergence of main driver genes with higher mutational frequency. In addition, there are other genes with mutations that have weak tumor-promoting effects, known as mini-drivers, which could aggravate the development of oncogenesis when they occur together. The aim of our work was to use computer analysis to explore the survival impact, frequency, and incidence of mutations of possible mini-driver genes to be used for the prognosis of CRC.

Methods

We retrieved data from three sources of CRC samples using the cBioPortal platform and analyzed the mutational frequency to exclude genes with driver features and those mutated in less than 5% of the original cohort. We also observed that the mutational profile of these mini-driver candidates is associated with variations in the expression levels. The candidate genes obtained were subjected to Kaplan-Meier curve analysis, making a comparison between mutated and wild-type samples for each gene using a p-value threshold of 0.01.

Results

After gene filtering by mutational frequency, we obtained 159 genes of which 60 were associated with a high accumulation of total somatic mutations with Log₂ (fold change) > 2 and p values < 10^-5. In addition, these genes were enriched to oncogenic pathways such as epithelium-mesenchymal transition, hsa-miR-218-5p downregulation, and extracellular matrix organization. Our analysis identified five genes with possible implications as mini-drivers: DOCK3, FN1, PAPPA2, DNAH11, and FBN2. Furthermore, we evaluated a combined classification where CRC patients with at least one mutation in any of these genes were separated from the main cohort obtaining a p-value < 0.001 in the evaluation of CRC prognosis.

Conclusion

Our study suggests that the identification and incorporation of mini-driver genes in addition to known driver genes could enhance the accuracy of prognostic biomarkers for CRC.

Multi-omic integration via similarity network fusion to detect molecular subtypes of ageing

Molecular subtyping of brain tissue provides insights into the heterogeneity of common neurodegenerative conditions, such as Alzheimer's disease. However, existing subtyping studies have mostly focused on single data modalities and only those individuals with severe cognitive impairment. To address these gaps, we applied similarity network fusion, a method capable of integrating multiple high-dimensional multi-omic data modalities simultaneously, to an elderly sample spanning the full spectrum of cognitive ageing trajectories. We analyzed human frontal cortex brain samples characterized by five omic modalities: bulk RNA sequencing (18 629 genes), DNA methylation (53 932 CpG sites), histone acetylation (26 384 peaks), proteomics (7737 proteins) and metabolomics (654 metabolites). Similarity network fusion followed by spectral clustering was used for subtype detection, and subtype numbers were determined by Eigen-gap and rotation cost statistics. Normalized mutual information determined the relative contribution of each modality to the fused network. Subtypes were characterized by associations with 13 age-related neuropathologies and cognitive decline. Fusion of all five data modalities (n = 111) yielded two subtypes (n S1 = 53, n S2 = 58), which were nominally associated with diffuse amyloid plaques; however, this effect was not significant after correction for multiple testing. Histone acetylation (normalized mutual information = 0.38), DNA methylation (normalized mutual information = 0.18) and RNA abundance (normalized mutual information = 0.15) contributed most strongly to this network. Secondary analysis integrating only these three modalities in a larger subsample (n = 513) indicated support for both three- and five-subtype solutions, which had significant overlap, but showed varying degrees of internal stability and external validity. One subtype showed marked cognitive decline, which remained significant even after correcting for tests across both three- and five-subtype solutions (p Bonf = 5.9 × 10-3). Comparison to single-modality subtypes demonstrated that the three-modal subtypes were able to uniquely capture cognitive variability. Comprehensive sensitivity analyses explored influences of sample size and cluster number parameters. We identified highly integrative molecular subtypes of ageing derived from multiple high dimensional, multi-omic data modalities simultaneously. Fusing RNA abundance, DNA methylation, and histone acetylation measures generated subtypes that were associated with cognitive decline. This work highlights the potential value and challenges of multi-omic integration in unsupervised subtyping of post-mortem brain.

Rapid detection of cancer DNA in human blood using cysteamine-capped AuNPs and a machine learning-enabled smartphone

DNA methylation occurs when a methyl group is added to a cytosine (C) residue's fifth carbon atom, forming 5-methylcytosine (5-mC). Cancer genomes have a distinct methylation landscape (Methylscape), which could be used as a universal cancer biomarker. This study developed a simple, low-cost, and straightforward Methylscape sensing platform using cysteamine-decorated gold nanoparticles (Cyst/AuNPs), in which the sensing principle is based on methylation-dependent DNA solvation. Normal and cancer DNAs have distinct methylation profiles; thus, they can be distinguished by observing the dispersion of Cyst/AuNPs adsorbed on these DNA aggregates in MgCl2 solution. After optimising the MgCl2, Cyst/AuNPs, DNA concentration, and incubation time, the optimised conditions were used for leukemia screening, by comparing the relative absorbance (ΔA 650/525). Following the DNA extraction from actual blood samples, this sensor demonstrated effective leukemia screening in 15 minutes with high sensitivity, achieving 95.3% accuracy based on the measurement by an optical spectrophotometer. To further develop for practical realisation, a smartphone assisted by machine learning was used to screen cancer patients, achieving 90.0% accuracy in leukemia screening. This sensing platform can be applied not only for leukemia screening but also for other cancers associated with epigenetic modification.

Methylation biomarkers for early cancer detection and diagnosis: Current and future perspectives

The increase in recent scientific studies on cancer biomarkers has brought great new insights into the field. Moreover, novel technological breakthroughs such as long read sequencing and microarrays have enabled high throughput profiling of many biomarkers, while advances in bioinformatic tools have made the possibility of developing highly reliable and accurate biomarkers a reality. These changes triggered renewed interest in biomarker research and provided tremendous opportunities for enhancing cancer management and improving early disease detection. DNA methylation alterations are known to accompany and contribute to carcinogenesis, making them promising biomarkers for cancer, namely due to their stability, frequency and accessibility in bodily fluids. The advent of newer minimally invasive experimental methods such as liquid biopsies provide the perfect setting for methylation-based biomarker development and application. Despite their huge potential, accurate and robust biomarkers for the conclusive diagnosis of most cancer types are still not routinely used, hence a strong need for sustained research in this field is still needed. This review provides a brief exposition of current methylation biomarkers for cancer diagnosis and early detection, including markers already in clinical use as well as various upcoming ones. It also outlines how recent big data and novel technologies will revolutionise the next generation of cancer tests in supplementing or replacing currently existing invasive techniques.

Longitudinal change in blood DNA epigenetic signature after smoking cessation

Cigarette smoking is associated with epigenetic changes that may be reversible following smoking cessation. Whole blood DNA methylation was evaluated in Framingham Heart Study Offspring (n = 169) and Third Generation (n = 30) cohort participants at two study visits 6 years apart and in Atherosclerosis Risk in Communities (ARIC) study (n = 222) participants at two study visits 20 years apart. Changes in DNA methylation (delta β values) at 483,565 cytosine-phosphate-guanine (CpG) sites and differentially methylated regions (DMRs) were compared between participants who were current, former, or never smokers at both visits (current-current, former-former, never-never, respectively), versus those who quit in the interim (current-former). Interim quitters had more hypermethylation at four CpGs annotated to AHRR, one CpG annotated to F2RL3, and one intergenic CpG (cg21566642) compared with current-current smokers (FDR < 0.02 for all), and two significant DMRs were identified. While there were no significant differentially methylated CpGs in the comparison of interim quitters and former-former smokers, 106 DMRs overlapping with small nucleolar RNA were identified. As compared with all non-smokers, current-current smokers additionally had more hypermethylation at two CpG sites annotated to HIVEP3 and TMEM126A, respectively, and another intergenic CpG (cg14339116). Gene transcripts associated with smoking cessation were implicated in immune responses, cell homoeostasis, and apoptosis. Smoking cessation is associated with early reversion of blood DNA methylation changes at CpG sites annotated to AHRR and F2RL3 towards those of never smokers. Associated gene expression suggests a role of longitudinal smoking-related DNA methylation changes in immune response processes.

Potential methylation-regulated genes and pathways in hepatocellular neoplasm, not otherwise specified

Background and Aims

The molecular basis of hepatocellular neoplasm, not otherwise specified (HCN-NOS) is unknown. We aimed to identify gene expression patterns, potential methylation-regulated genes and pathways that characterize the tumor, and its possible relationship to hepatoblastoma and hepatocellular carcinoma (HCC).

Approach & Results

Parallel genome-wide profiling of gene expression (RNAseq) and DNA methylation (EPIC850) was performed on 4 pairs of pre-treatment HCN-NOS tumors and adjacent non-tumor controls. 2530 significantly differentially expressed genes (DEGs) were identified between tumors and controls. Many of these DEGs were associated with hepatoblastoma and/or HCC. Analysis Match in Ingenuity Pathway Analysis determined that the gene expression profile of HCN-NOS was unique but significantly similar to that of both hepatoblastoma and HCC. A total of 27,195 CpG sites (CpGs) were significantly differentially methylated (DM) between tumors and controls, with a global hypomethylation pattern and predominant CpG island hypermethylation in promotor regions. Aberrant DNA methylation predominated in Developmental Process and Molecular Function Regulator pathways. Embryonic stem cell pathways were significantly enriched. In total, 1055 aberrantly methylated (at CpGs) and differentially expressed genes were identified, including 25 upstream regulators and sixty-one potential CpG island methylation-regulated genes. Eight methylation-regulated genes (TCF3, MYBL2, SRC, HMGA2, PPARGC1A, SLC22A1, COL2A1 and MYCN) had highly consistent gene expression patterns and prognostic value in patients with HCC, based on comparison to publicly available datasets.

Conclusions

HCN-NOS has a unique, stem-cell like gene expression and DNA methylation profile related to both hepatoblastoma and HCC but distinct therefrom. Further, 8 methylation-regulated genes associated with prognosis in HCC were identified.

Germline Abnormalities in DNA Methylation and Histone Modification and Associated Cancer Risk

PURPOSE OF REVIEW

Somatic mutations in DNA methyltransferases and other DNA methylation associated genes have been found in a wide variety of cancers. Germline mutations in these genes have been associated with several rare hereditary disorders. Among the described germline/congenital disorders, neurological dysfunction and/or growth abnormalities appear to be a common phenotype. Here, we outline known germline abnormalities and examine the cancer risks associated with these mutations.

RECENT FINDINGS

The increased use and availability of sequencing techniques in the clinical setting has expanded the identification of germline abnormalities involving DNA methylation machinery. This has provided additional cases to study these rare hereditary disorders and their predisposition to cancer. Studying these syndromes may offer an opportunity to better understand the contribution of these genes in cancer development.

Discovering the key genes and important DNA methylation regions in breast cancer

BACKGROUND

Breast cancer is the malignant tumor with the highest incidence in women. DNA methylation has an important effect on breast cancer, but the effect of abnormal DNA methylation on gene expression in breast cancer is still unclear. Therefore, it is very important to find therapeutic targets related to DNA methylation.

RESULTS

In this work, we calculated the DNA methylation distribution and gene expression level in cancer and para-cancerous tissues for breast cancer samples. We found that DNA methylation in key regions is closely related to gene expression by analyzing the relationship between the distribution characteristics of DNA methylation in different regions and the change of gene expression level. Finally, the 18 key genes (17 tumor suppressor genes and 1 oncogene) related to prognosis were confirmed by the survival analysis of clinical data. Some important DNA methylation regions in these genes that result in breast cancer were found.

CONCLUSIONS

We believe that 17 TSGs and 1 oncogene may be breast cancer biomarkers regulated by DNA methylation in key regions. These results will help to explore DNA methylation biomarkers as potential therapeutic targets for breast cancer.

Genome-wide DNA methylation profiling and identification of potential pan-cancer and tumor-specific biomarkers

DNA methylation alterations have already been linked to cancer, and their usefulness for therapy and diagnosis has encouraged research into the human epigenome. Several biomarker studies have focused on identifying cancer types individually, yet common cancer and multi-cancer markers are still underexplored. We used The Cancer Genome Atlas (TCGA) to investigate genome-wide methylation profiles of 14 different cancer types and developed a three-step computational approach to select candidate biomarker CpG sites. In total, 1,991 pan-cancer and between 75 and 1,803 cancer-specific differentially methylated CpG sites were discovered. Differentially methylated blocks and regions were also discovered for the first time on such a large-scale. Through a three-step computational approach, a combination of four pan-cancer CpG markers was identified from these sites and externally validated (AUC = 0.90), maintaining comparable performance across tumor stages. Additionally, 20 tumor-specific CpG markers were identified and made up the final type-specific prediction model, which could accurately differentiate tumor types (AUC = 0.87-0.99). Our study highlights the power of the methylome as a rich source of cancer biomarkers, and the signatures we identified provide a new resource for understanding cancer mechanisms on the wider genomic scale with strong applicability in the context of new minimally invasive cancer detection assays.

BCurve: Bayesian Curve Credible Bands Approach for the Detection of Differentially Methylated Regions

High-throughput assays have been developed to measure DNA methylation, among which bisulfite-based sequencing (BS-seq) and microarray technologies are the most popular for genome-wide profiling. A major goal in DNA methylation analysis is the detection of differentially methylated genomic regions under two different conditions. To accomplish this, many state-of-the-art methods have been proposed in the past few years; only a handful of these methods are capable of analyzing both types of data (BS-seq and microarray), though. On the other hand, covariates, such as sex and age, are known to be potentially influential on DNA methylation; and thus, it would be important to adjust for their effects on differential methylation analysis. In this chapter, we describe a Bayesian curve credible bands approach and the accompanying software, BCurve, for detecting differentially methylated regions for data generated from either microarray or BS-Seq. The unified theme underlying the analysis of these two different types of data is the model that accounts for correlation between DNA methylation in nearby sites, covariates, and between-sample variability. The BCurve R software package also provides tools for simulating both microarray and BS-seq data, which can be useful for facilitating comparisons of methods given the known "gold standard" in the simulated data. We provide detailed description of the main functions in BCurve and demonstrate the utility of the package for analyzing data from both platforms using simulated data from the functions provided in the package. Analyses of two real datasets, one from BS-seq and one from microarray, are also furnished to further illustrate the capability of BCurve.

Aspects of the Epigenetic Regulation of EMT Related to Cancer Metastasis

Epithelial to mesenchymal transition (EMT) occurs during the pathological process associated with tumor progression and is considered to influence and promote the metastatic cascade. Characterized by loss of cell adhesion and apex base polarity, EMT enhances cell motility and metastasis. The key markers of the epithelial to mesenchymal transition are proteins characteristic of the epithelial phenotype, e.g., E-cadherin, cytokeratins, occludin, or desmoplakin, the concentration and activity of which are reduced during this process. On the other hand, as a result of acquiring the characteristics of mesenchymal cells, an increased amount of N-cadherin, vimentin, fibronectin, or vitronectin is observed. Importantly, epithelial cells undergo partial EMT where some of the cells show both epithelial and mesenchymal characteristics. The significant influence of epigenetic regulatory mechanisms is observed in the gene expression involved in EMT. Among the epigenetic modifications accompanying incorrect genetic reprogramming in cancer are changes in the level of DNA methylation within the CpG islands and posttranslational covalent changes of histone proteins. All observed modifications, which are stable but reversible changes, affect the level of gene expression leading to the development and progression of the disease, and consequently affect the uncontrolled growth of the population of cancer cells.

Application of droplet digital polymerase chain reaction of plasma methylated septin 9 on detection and early monitoring of colorectal cancer

Methylated septin 9 (SEPT9) has been approved for non-invasive screening of colorectal cancer (CRC), but data on monitoring of CRC is sparse. Droplet digital polymerase chain reaction (ddPCR), with higher detection precision and simpler quantification than conventional PCR, has not been applied in SEPT9 detection. We explored the role of SEPT9 ddPCR for CRC detection and to measure serial SEPT9 levels in blood samples of CRC patients before and 3-month after surgery. SEPT9 methylated ratio, methylated abundance, and CEA levels were all higher in CRC patients than normal controls (all P < 0.05). The area under the curve (AUC) for methylated ratio and abundance to detect CRC was 0.707 and 0.710, respectively. There was an increasing trend for SEPT9 methylated abundance from proximal to distal cancers (P = 0.017). At 3-month after surgery, both methylated abundance and ratio decreased (P = 0.005 and 0.053, respectively), especially methylated abundance in stage III and distal cancer (both P < 0.01). We have developed a ddPCR platform for the quantitative detection of plasma SEPT9 in CRC patients. SEPT9 methylated abundance had an early post-operative decline, which may be useful in monitoring of treatment response.

Epithelial to Mesenchymal Transition: A Challenging Playground for Translational Research. Current Models and Focus on TWIST1 Relevance and Gastrointestinal Cancers

Resembling the development of cancer by multistep carcinogenesis, the evolution towards metastasis involves several passages, from local invasion and intravasation, encompassing surviving anoikis into the circulation, landing at distant sites and therein establishing colonization, possibly followed by the outgrowth of macroscopic lesions. Within this cascade, epithelial to mesenchymal transition (EMT) works as a pleiotropic program enabling cancer cells to overcome local, systemic, and distant barriers against diffusion by replacing traits and functions of the epithelial signature with mesenchymal-like ones. Along the transition, a full-blown mesenchymal phenotype may not be accomplished. Rather, the plasticity of the program and its dependency on heterotopic signals implies a pendulum with oscillations towards its reversal, that is mesenchymal to epithelial transition. Cells in intermixed E⇔M states can also display stemness, enabling their replication together with the epithelial reversion next to successful distant colonization. If we aim to include the EMT among the hallmarks of cancer that could modify clinical practice, the gap between the results pursued in basic research by animal models and those achieved in translational research by surrogate biomarkers needs to be filled. We review the knowledge on EMT, derived from models and mechanistic studies as well as from translational studies, with an emphasis on gastrointestinal cancers (GI).

Emerging Single-Cell Technological Approaches to Investigate Chromatin Dynamics and Centromere Regulation in Human Health and Disease

Epigenetic regulators play a crucial role in establishing and maintaining gene expression states. To date, the main efforts to study cellular heterogeneity have focused on elucidating the variable nature of the chromatin landscape. Specific chromatin organisation is fundamental for normal organogenesis and developmental homeostasis and can be affected by different environmental factors. The latter can lead to detrimental alterations in gene transcription, as well as pathological conditions such as cancer. Epigenetic marks regulate the transcriptional output of cells. Centromeres are chromosome structures that are epigenetically regulated and are crucial for accurate segregation. The advent of single-cell epigenetic profiling has provided finer analytical resolution, exposing the intrinsic peculiarities of different cells within an apparently homogenous population. In this review, we discuss recent advances in methodologies applied to epigenetics, such as CUT&RUN and CUT&TAG. Then, we compare standard and emerging single-cell techniques and their relevance for investigating human diseases. Finally, we describe emerging methodologies that investigate centromeric chromatin specification and neocentromere formation.

Detection of Cell Types Contributing to Cancer From Circulating, Cell-Free Methylated DNA

Detection of cellular changes in tissue biopsies has been the basis for cancer diagnostics. However, tissue biopsies are invasive and limited by inaccuracies due to sampling locations, restricted sampling frequency, and poor representation of tissue heterogeneity. Liquid biopsies are emerging as a complementary approach to traditional tissue biopsies to detect dynamic changes in specific cell populations. Cell-free DNA (cfDNA) fragments released into the circulation from dying cells can be traced back to the tissues and cell types they originated from using DNA methylation, an epigenetic regulatory mechanism that is highly cell-type specific. Decoding changes in the cellular origins of cfDNA over time can reveal altered host tissue homeostasis due to local cancer invasion and metastatic spread to distant organs as well as treatment responses. In addition to host-derived cfDNA, changes in cancer cells can be detected from cell-free, circulating tumor DNA (ctDNA) by monitoring DNA mutations carried by cancer cells. Here, we will discuss computational approaches to identify and validate robust biomarkers of changed tissue homeostasis using cell-free, methylated DNA in the circulation. We highlight studies performing genome-wide profiling of cfDNA methylation and those that combine genetic and epigenetic markers to further identify cell-type specific signatures. Finally, we discuss opportunities and current limitations of these approaches for implementation in clinical oncology.

Development of a liquid biopsy based purely quantitative digital droplet PCR assay for detection of MLH1 promoter methylation in colorectal cancer patients

Background

MutL Homolog 1 (MLH1) promotor methylation is associated with microsatellite instability high colorectal cancer (CRC). The strong correlation between methylation status and cancer development and progression has led to a growing interest in the use of methylation markers in circulating tumor DNA (ctDNA) for early cancer detection and longitudinal monitoring. As cancer-specific DNA methylation changes in body fluids are limited, it is particularly challenging to develop clinically applicable liquid biopsy methodologies with high sensitivity and specificity. The purpose of this study was to develop a fit-for-purpose methylation sensitive restriction enzyme (MSRE) based digital droplet PCR (ddPCR) assay to examine MLH1 promoter methylation in ctDNA in advanced CRC.

Methods

Primers and probes were designed to amplify CpG sites of the MLH1 promoter. Methylated and unmethylated control genomic DNA were sheared to mimic ctDNA and subjected to MSRE HpaII digestion. Plasma samples from 20 healthy donors and 28 CRC patients were analyzed with the optimized MSRE procedure using ddPCR.

Results

Using methylated and unmethylated controls, we optimized the conditions for HpaII enzyme digestion to ensure complete digestion and avoid false positives. Based on the results from the ddPCR assay using 1 ng circulating cell-free DNA (cfDNA) input from healthy donors or CRC samples, ROC curves were generated with an area under the curve (AUC) value of 0.965 (95% CI: 0.94, 0.99). The statistically optimal assay sensitivity and specificity was achieved when 8 positive droplets were used as acceptance criteria (78% sensitivity and 100% specificity, 95% CI: 0.45, 0.95). A tiered-based cutoff (20, 50, 80% percentile based) was applied to distinguish CRC samples with different methylation level.

Conclusions

Our study demonstrated that the liquid biopsy assay for MLH1 promoter methylation detection using purely quantitative ddPCR is a simple and highly sensitive procedure that provides reliable methylation detection in ctDNA. The MSRE ddPCR approach can also be applied to other genes of interest where methylation patterns could reveal clinically relevant information for future clinical biomarker and/or companion diagnostic development.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08497-x.

Detection and relevance of epigenetic markers on ctDNA: recent advances and future outlook

Liquid biopsy, a minimally invasive approach, is a highly powerful clinical tool for the real-time follow-up of cancer and overcomes many limitations of tissue biopsies. Epigenetic alterations have a high potential to provide a valuable source of innovative biomarkers for cancer, owing to their stability, frequency, and noninvasive accessibility in bodily fluids. Numerous DNA methylation markers are now tested in circulating tumor DNA (ctDNA) as potential biomarkers, in various types of cancer. DNA methylation in combination with liquid biopsy is very powerful in identifying circulating epigenetic biomarkers of clinical importance. Blood-based epigenetic biomarkers have a high potential for early detection of cancer since DNA methylation in plasma can be detected early during cancer pathogenesis. In this review, we summarize the latest findings on DNA methylation markers in ctDNA for early detection, prognosis, minimal residual disease, risk of relapse, treatment selection, and resistance, for breast, prostate, lung, and colorectal cancer.

Epigenomic and Metabolomic Integration Reveals Dynamic Metabolic Regulation in Bladder Cancer

Bladder cancer (BC) represents a clinical, social, and economic challenge due to tumor-intrinsic characteristics, limitations of diagnostic techniques and a lack of personalized treatments. In the last decade, the use of liquid biopsy has grown as a non-invasive approach to characterize tumors. Moreover, the emergence of omics has increased our knowledge of cancer biology and identified critical BC biomarkers. The rewiring between epigenetics and metabolism has been closely linked to tumor phenotype. Chromatin remodelers interact with each other to control gene silencing in BC, but also with stress-inducible factors or oncogenic signaling cascades to regulate metabolic reprogramming towards glycolysis, the pentose phosphate pathway, and lipogenesis. Concurrently, one-carbon metabolism supplies methyl groups to histone and DNA methyltransferases, leading to the hypermethylation and silencing of suppressor genes in BC. Conversely, α-KG and acetyl-CoA enhance the activity of histone demethylases and acetyl transferases, increasing gene expression, while succinate and fumarate have an inhibitory role. This review is the first to analyze the interplay between epigenome, metabolome and cell signaling pathways in BC, and shows how their regulation contributes to tumor development and progression. Moreover, it summarizes non-invasive biomarkers that could be applied in clinical practice to improve diagnosis, monitoring, prognosis and the therapeutic options in BC.

The MAL Protein, an Integral Component of Specialized Membranes, in Normal Cells and Cancer

The MAL gene encodes a 17-kDa protein containing four putative transmembrane segments whose expression is restricted to human T cells, polarized epithelial cells and myelin-forming cells. The MAL protein has two unusual biochemical features. First, it has lipid-like properties that qualify it as a member of the group of proteolipid proteins. Second, it partitions selectively into detergent-insoluble membranes, which are known to be enriched in condensed cell membranes, consistent with MAL being distributed in highly ordered membranes in the cell. Since its original description more than thirty years ago, a large body of evidence has accumulated supporting a role of MAL in specialized membranes in all the cell types in which it is expressed. Here, we review the structure, expression and biochemical characteristics of MAL, and discuss the association of MAL with raft membranes and the function of MAL in polarized epithelial cells, T lymphocytes, and myelin-forming cells. The evidence that MAL is a putative receptor of the epsilon toxin of Clostridium perfringens, the expression of MAL in lymphomas, the hypermethylation of the MAL gene and subsequent loss of MAL expression in carcinomas are also presented. We propose a model of MAL as the organizer of specialized condensed membranes to make them functional, discuss the role of MAL as a tumor suppressor in carcinomas, consider its potential use as a cancer biomarker, and summarize the directions for future research.

Plasma cell free DNA methylation markers for hepatocellular carcinoma surveillance in patients with cirrhosis: a case control study

BACKGROUND

Hepatocellular carcinoma (HCC) is the leading cause of death in patients with cirrhosis, primarily due to failed early detection. HCC screening is recommended among individuals with cirrhosis using biannual abdominal ultrasound, for earlier tumor detection, administration of curative treatment, and improved survival. Surveillance by imaging with or without biomarkers such as alpha-fetoprotein (AFP) remains suboptimal for early stage HCC detection. Here we report on the development and assessment of methylation biomarkers from liquid biopsies for HCC surveillance in cirrhotic patients.

METHODS

DNA methylation markers including the HCCBloodTest (Epigenomics AG) and a DNA-methylation panel established by next generation sequencing (NGS) were assessed using a training/testing design. The NGS panel algorithm was established in a training study (41 HCC patients; 46 cirrhotic non-HCC controls). For testing, plasma samples were obtained from cirrhotic patients (Child class A or B) with (60) or without (103) early stage HCC (BCLC stage 0, A, B). The assays were then tested using blinded sample sets and analyzed by preset algorithms.

RESULTS

The HCCBloodTest and the NGS panel exhibited 76.7% and 57% sensitivities at 64.1% and 97% specificity, respectively. In a post-hoc analysis, a combination of the NGS panel with AFP (20 ng/mL) achieved 68% sensitivity at 97% specificity (AUC = 0.9).

CONCLUSIONS

Methylation biomarkers in cell free plasma DNA provide a new alternative for HCC surveillance. Multiomic panels comprising DNA methylation markers with other biological markers, such as AFP, provide an option to further increase the overall clinical performance of surveillance via minimally invasive blood samples.

TRIAL REGISTRATION

Test set study-ClinicalTrials.gov (NCT03804593) January 11, 2019, retrospectively registered.

Emerging noninvasive methylation biomarkers of cancer prognosis and drug response prediction

Cancer is the second leading cause of death worldwide being responsible for 9.6 million deaths in 2018. Epigenetic alterations are key in directing the aberrant expression of tumor-associated genes that drive cellular malignant transformation and cancer progression. Among epigenetic alterations, DNA methylation is the most deeply studied one in relation to environmental exposure. Tissue biopsies have traditionally been the main procedure by which a small sample of body tissue is excised to confirm cancer diagnosis or to indicate the primary site when cancer has spread. In contrast, the analysis of circulating tumor-derived material, or tumor circulome, by means of liquid biopsy of peripheral blood, urine, saliva or sputum is a noninvasive, fast and reproducible alternative to tissue biopsy. Recently, the assessment of epigenetic alterations such as DNA methylation and hydroxymethylation in circulating free DNA has been proved possible. These marks can be associated to prognosis and response to a variety of treatments including chemotherapy, hormonotherapy or immunotherapy. Epigenetic biomarkers may offer some advantages over RNA or genetic biomarkers given their stability in bodily fluids and their high tissue-specificity. While many challenges are still ahead, the unique advantages of these types of biomarkers is urging the scientific community to persevere in their clinical validation and integration into reliable prediction models. This review aims at recapitulating the emerging noninvasive DNA methylated biomarkers of importance for prediction of prognosis and drug response in cancer.

High Expression of CLEC11A Predicts Favorable Prognosis in Acute Myeloid Leukemia

Background

Acute myeloid leukemia (AML) is a heterogeneous disease of the hematopoietic system, for which identification of novel molecular markers is potentially important for clinical prognosis and is an urgent need for treatment optimization.

Methods

We selected C-type lectin domain family 11, member A (CLEC11A) for study via several public databases, comparing expression among a variety of tumors and normal samples as well as different organs and tissues. To investigated the relationship between CLEC11A expression and clinical characteristics, we derived an AML cohort from The Cancer Genome Atlas (TCGA); we also investigated the Bloodspot and HemaExplorer databases. The Kaplan-Meier method and log-rank test were used to evaluate the associations between CLEC11A mRNA expression, as well as DNA methylation, and overall survival (OS), event-free survival (EFS), and relapse-free survival (RFS). DNA methylation levels of CLEC11A from our own 28 de novo AML patients were assessed and related to chemotherapeutic outcomes. Bioinformatics analysis of CLEC11A was carried out using public databases.

Results

Multiple public databases revealed that CLEC11A expression was higher in leukemia. The TCGA data revealed that high CLEC11A expression was linked with favorable prognosis (OS p-value = 2e-04; EFS p-value = 6e-04), which was validated in GSE6891 (OS p-value = 0; EFS p-value = 0; RFS p-value = 2e-03). Methylation of CLEC11A was negatively associated with CLEC11A expression, and high CLEC11A methylation level group was linked to poorer prognosis (OS p-value = 1e-02; EFS p-value = 2e-02). Meanwhile, CLEC11A hypermethylation was associated with poor induction remission rate and dismal survival. Bioinformatic analysis also showed that CLEC11A was an up-regulated gene in leukemogenesis.

Conclusion

CLEC11A may be used as a prognostic biomarker, and could do benefit for AML patients by providing precise treatment indications, and its unique gene pattern should aid in further understanding the heterogeneous AML mechanisms.

Multi-Omics Data Analysis of Gene Expressions and Alterations, Cancer-Associated Fibroblast and Immune Infiltrations, Reveals the Onco-Immune Prognostic Relevance of STAT3/CDK2/4/6 in Human Malignancies

Simple Summary

Signal transducer and activator of transcription 3 (STAT3)/Cyclin-dependent kinases are multifunctional proteins that play instrumental roles in carcinogenesis. However, the genetic alterations of the STAT3/CDK2/4/6 signaling axis and its role in predicting immune infiltration and immunotherapeutic response remain unclear. Here, we used in silico analyses of multi-Omics data to map out the role of epigenetic and genetic alterations of STAT3/CDK2/4/6 in tumor immune infiltrations, immunotherapy response, and prognosis of cancer patients. Our study collectively suggested that STAT3/CDK2/4/6 are important onco-immune signatures that contribute to tumor immune invasion, poor prognoses, and immune therapy failure. Our finding may be clinically useful in designing therapeutic strategies, prognosis assessment, and follow-up management in patients receiving immunotherapy in multiple cancers.

Abstract

Signal transducer and activator of transcription 3 (STAT3)/Cyclin-dependent kinases are multifunctional proteins that play an important implicative role in cancer initiations, progression, drug resistance, and metastasis, and has been extensively explored in cancer therapy. However, the genetic alterations of STAT3/CDK2/4/6 and its role in predicting immune infiltration and immunotherapeutic response are yet to be well exploited. In this study, we use in silico methods to analyze differential expression, prognostic value, genetic and epigenetic alterations, association with tumor-infiltrating immune cells, and cancer-associated fibroblast (CAF) infiltrations of STAT3/CDK2/4/6 in multiple cancer types. Our results revealed that the expression of STAT3/CDK2/4/6 was altered in various cancers and is associated with poor overall and disease-free survival of the cohorts. Moreover, genetic alterations in STAT3/CDK2/4/6 co-occurred with a number of other genetic alterations and are associated with poorer prognoses of the cohorts. The protein-protein interaction (PPI) network analysis suggests CDK2/4/6/STAT3 may directly interact with factors that promote tumorigenesis and immune response. We found that STAT3/CDK2/4/6 expressions were associated with infiltrations of CAF and the various immune cells in multiple cancers and it’s associated with poor response to immunotherapy. Collectively, our study suggested that STAT3/CDK2/4/6 are important onco-immune signatures that play central roles in tumor immune invasion, poor prognoses and, immune therapy response. Findings from the present study may therefore be clinically useful in prognosis assessment and follow-up management of immunotherapy.

Ultra-Low DNA Input into Whole Genome Methylation Assays and Detection of Oncogenic Methylation and Copy Number Variants in Circulating Tumour DNA

Abnormal CpG methylation in cancer is ubiquitous and generally detected in tumour specimens using a variety of techniques at a resolution encompassing single CpG loci to genome wide coverage. Analysis of samples with very low DNA inputs, such as formalin fixed (FFPE) biopsy specimens from clinical trials or circulating tumour DNA is challenging at the genome-wide level because of lack of available input. We present the results of low input experiments into the Illumina Infinium HD methylation assay on FFPE specimens and ctDNA samples.

METHODS

For all experiments, the Infinium HD assay for methylation was used. In total, forty-eight FFPE specimens were used at varying concentrations (lowest input 50 ng); eighteen blood derived specimens (lowest input 10 ng) and six matched ctDNA input (lowest input 10 ng)/fresh tumour specimens (lowest input 250 ng) were processed. Downstream analysis was performed in R/Bioconductor for quality control metrics and differential methylation analysis as well as copy number calls.

RESULTS

Correlation coefficients for CpG methylation were high at the probe level averaged R2 = 0.99 for blood derived samples and R2 > 0.96 for the FFPE samples. When matched ctDNA/fresh tumour samples were compared, R2 > 0.91 between the two. Results of differential methylation analysis did not vary significantly by DNA input in either the blood or FFPE groups. There were differences seen in the ctDNA group as compared to their paired tumour sample, possibly because of enrichment for tumour material without contaminating normal. Copy number variants observed in the tumour were generally also seen in the paired ctDNA sample with good concordance via DQ plot.

CONCLUSIONS

The Illumina Infinium HD methylation assay can robustly detect methylation across a range of sample types, including ctDNA, down to an input of 10 ng. It can also reliably detect oncogenic methylation changes and copy number variants in ctDNA. These findings demonstrate that these samples can now be accessed by methylation array technology, allowing analysis of these important sample types.

A multi-scale integrated analysis identifies KRT8 as a pan-cancer early biomarker

An early biomarker would transform our ability to screen and treat patients with cancer. The large amount of multi-scale molecular data in public repositories from various cancers provide unprecedented opportunities to find such a biomarker. However, despite identification of numerous molecular biomarkers using these public data, fewer than 1% have proven robust enough to translate into clinical practice. One of the most important factors affecting the successful translation to clinical practice is lack of real-world patient population heterogeneity in the discovery process. Almost all biomarker studies analyze only a single cohort of patients with the same cancer using a single modality. Recent studies in other diseases have demonstrated the advantage of leveraging biological and technical heterogeneity across multiple independent cohorts to identify robust disease biomarkers. Here we analyzed 17149 samples from patients with one of 23 cancers that were profiled using either DNA methylation, bulk and single-cell gene expression, or protein expression in tumor and serum. First, we analyzed DNA methylation profiles of 9855 samples across 23 cancers from The Cancer Genome Atlas (TCGA). We then examined the gene expression profile of the most significantly hypomethylated gene, KRT8, in 6781 samples from 57 independent microarray datasets from NCBI GEO. KRT8 was significantly over-expressed across cancers except colon cancer (summary effect size=1.05; p < 0.0001). Further, single-cell RNAseq analysis of 7447 single cells from lung tumors showed that genes that significantly correlated with KRT8 (p < 0.05) were involved in p53-related pathways. Immunohistochemistry in tumor biopsies from 294 patients with lung cancer showed that high protein expression of KRT8 is a prognostic marker of poor survival (HR = 1.73, p = 0.01). Finally, detectable KRT8 in serum as measured by ELISA distinguished patients with pancreatic cancer from healthy controls with an AUROC=0.94. In summary, our analysis demonstrates that KRT8 is (1) differentially expressed in several cancers across all molecular modalities and (2) may be useful as a biomarker to identify patients that should be further tested for cancer.

Plasma GBP2 promoter methylation is associated with advanced stages in breast cancer

Blood methylated cell-free DNA (cfDNA) as a minimally invasive cancer biomarker has great importance in cancer management. Guanylate binding protein 2 (GBP2) has been considered as a possible controlling factor in tumor development. GBP2 gene expression and its promoter methylation status in both plasma cfDNA and tumor tissues of ductal carcinoma breast cancer patients were analyzed using SYBR green comparative Real-Time RT-PCR and, Methyl-specific PCR techniques, respectively in order to find a possible cancer-related marker. The results revealed that GBP2 gene expression and promoter methylation were inversely associated. GBP2 was down-regulated in tumors with emphasis on triple negative status, nodal involvement and higher cancer stages (p<0.0001). GBP2 promoter methylation on both cfDNA and tumor tissues were positively correlated and was detected in about 88% of breast cancer patients mostly in (Lymph node positive) LN+ and higher stages. Data provided shreds of evidence that GBP2 promoter methylation in circulating DNA may be considered as a possible effective non-invasive molecular marker in poor prognostic breast cancer patients with the evidence of its relation to disease stage and lymph node metastasis. However further studies need to evaluate the involvement of GBP2 promoter methylation in progression-free survival or overall survival of the patients.

Whole Genome DNA Methylation and Gene Expression Profiling of Oropharyngeal Cancer Patients in North-Eastern India: Identification of Epigenetically Altered Gene Expression Reveals Potential Biomarkers

Oropharyngeal cancer is a subtype of head and neck squamous cell carcinoma that is associated with unique risk exposures like consumption of smokeless tobacco and areca nut and is highly prevalent in the northeastern region of India, especially Meghalaya. However, the underlying epigenetic and transcriptomic changes in this cancer type is yet to be delineated. We have undertaken a study on genome wide somatic alterations in the DNA methylation and transcriptome in oropharyngeal cancer patients from this region using genome wide techniques in paired tumors and adjacent normal tissues. By using integrative approaches, we have identified 194 epigenetically silenced and 241 epigenetically overexpressed genes in the tumor tissue of these patients. Pathways that are significantly enriched by these genes include the pathways of immune systems, such as the interleukin signaling pathways and Toll-like receptor signaling pathway. Also, osteoclast differentiation pathway was found to be epigenetically upregulated. The pathways enriched by the epigenetically downregulated genes were found to be predominantly those involved in xenobiotic metabolism and keratinization. Two major transcription factors - SPI1 and RUNX1 were identified as epigenetically dysregulated, which further modulates 129 downstream genes. Comparison of our observations with the head and neck cancer data from TCGA revealed distinct DNA methylation and gene expression landscapes which might be specific for oropharyngeal cancer. HPV DNA sequences were not detected in any of the tumor samples in RNA-Seq data. The results obtained in this study might provide improved understanding of the disease.

Hypermethylated promoters of genes UNC5D and KCNA1 as potential novel diagnostic biomarkers in colorectal cancer

Aim: Identification of aberrant hypermethylation in promoter regions of candidate genes to discover potential biomarkers for colorectal cancer. Materials & Methods: Genes BMP2, IRF4, KCNA1, LRRC7, NRG3, SLC27A6 and UNC5D were pre-selected in a bioinformatics study for their hypermethylation status in colorectal cancer. Methylation analysis was performed on 202 cancer tissue specimens to validate candidate genes. Results: Genes KCNA1 and UNC5D displayed methylation in 95.3 and 99.7% of The Cancer Genome Atlas dataset samples and in 96 and 98% of our experimentally tested samples, respectively. Conclusion: KCNA1 and UNC5D promoter hypermethylation holds diagnostic biomarker potential in patients with early colorectal cancer.

DNA methylation markers for endometrial cancer detection in minimally invasive samples: a systematic review

Aim: DNA methylation testing for endometrial cancer detection in minimally invasive specimens is a promising tool to improve screening and diagnostic procedures. Available literature was systematically reviewed to assess the potential of this approach and define methylation markers deserving further development. Methods: A systematic search up to March 31 2020 was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Results: 15 methylation markers with an area under the curve value of ≥ 0.80 for endometrial cancer detection in cytological specimens were selected from nine studies. Conclusion: Detection of methylation markers in cytological samples indicate the feasibility of minimally invasive testing methods, potentially guiding diagnosis and detection of endometrial cancer in high-risk women and in cancer screening programs.

DNA methylation biomarkers of future health outcomes in children

Biomarkers which predict future health outcomes are key to the goals of precision health. Such biomarkers do not have to be involved in the causal pathway of a disease, and their performance is best assessed using statistical tests of clinical performance and evaluation of net health impact. DNA methylation is the most commonly studied epigenetic process and represents a potential biomarker of future health outcomes. We review 25 studies in non-oncological paediatric conditions where DNA methylation biomarkers of future health outcomes are assessed. Whilst a number of positive findings have been described, the body of evidence is severely limited by issues with outcome measures, tissue-specific samples, accounting for sample cell type heterogeneity, lack of appropriate statistical testing, small effect sizes, limited validation, and no assessment of net health impact. Future studies should concentrate on careful study design to overcome these issues, and integration of DNA methylation data with other 'omic', clinical, and environmental data to generate the most clinically useful biomarkers of paediatric disease.

CD40 DNA hypermethylation in primary gastric tumors; as a novel diagnostic biomarker

AIMS

Gastric cancer (GC) remains one of the deadliest malignancies worldwide due to its poor prognosis. DNA methylation changes, as an early event during tumor progression, constitute attractive markers for cancer diagnostics. In the current study, CD40 DNA methylation was investigated in GC as a novel epigenetic biomarker.

MAIN METHODS

We first analyzed DNA methylation microarrays from the Gene Expression Omnibus database on GC samples to evaluate the potential diagnostic value of CD40 methylation. Moreover, using q-MSP, in a set of internal samples including GC primary tumors and adjacent normal specimens, CD40 DNA methylation levels were determined. The Cancer Genome Atlas (TCGA) data on GC was also analyzed for further validation.

KEY FINDINGS

Our results illustrated significant CD40 hypermethylation in GC samples compared to normal specimens which was significantly correlated with the clinical stage of malignancy. Besides, the high accuracy of CD40 methylation as a diagnostic biomarker in GC was confirmed using the ROC curve analysis with an AUC value of 0.9089. Also, gene set enrichment analysis showed that CD40 is mainly involved in biological processes regulating immune response activation in GC. Further analysis of other prevalent cancer entities in TCGA showed that CD40 hypermethylation is a common event during tumor progression and could be considered as a potential biomarker for the detection of breast, colorectal, and prostate cancers as well.

SIGNIFICANCE

The finding of this study suggests that CD40 methylation as a potential pan biomarker could be a valuable target for liquid biopsy application of human cancers.

Epigenetics in Inflammatory Breast Cancer: Biological Features and Therapeutic Perspectives

Evidence has emerged implicating epigenetic alterations in inflammatory breast cancer (IBC) origin and progression. IBC is a rare and rapidly progressing disease, considered the most aggressive type of breast cancer (BC). At clinical presentation, IBC is characterized by diffuse erythema, skin ridging, dermal lymphatic invasion, and peau d'orange aspect. The widespread distribution of the tumor as emboli throughout the breast and intra- and intertumor heterogeneity is associated with its poor prognosis. In this review, we highlighted studies documenting the essential roles of epigenetic mechanisms in remodeling chromatin and modulating gene expression during mammary gland differentiation and the development of IBC. Compiling evidence has emerged implicating epigenetic changes as a common denominator linking the main risk factors (socioeconomic status, environmental exposure to endocrine disruptors, racial disparities, and obesity) with IBC development. DNA methylation changes and their impact on the diagnosis, prognosis, and treatment of IBC are also described. Recent studies are focusing on the use of histone deacetylase inhibitors as promising epigenetic drugs for treating IBC. All efforts must be undertaken to unravel the epigenetic marks that drive this disease and how this knowledge could impact strategies to reduce the risk of IBC development and progression.

Promoter hypermethylation of cysteine dioxygenase type 1 in patients with non-small cell lung cancer

In the present study, promoter hypermethylation of cysteine dioxygenase type 1 (CDO1) was evaluated in non-small cell lung cancer (NSCLC) tissues to assess the value of CDO1 as a novel biomarker to improve the diagnosis of NSCLC. Tumor tissue samples and corresponding normal lung tissue samples from 42 patients with NSCLC were obtained at the Department of Thoracic Surgery, The Second Xiangya Hospital (Changsha, China). Conventional methylation-specific PCR (cMSP) and methylation-on-beads followed by quantitative methylation-specific PCR (MOB-qMSP) were used to analyze the tumor and normal lung tissue samples. Using these two methods, promoter DNA hypermethylation of the CDO1 gene was detected in 59.4 and 71.0% of tumor tissues of patients with NSCLC and in 9.4 and 0% of normal lung tissue, respectively. Compared with the rate of methylation in the well-differentiated NSCLC tissues (15.4 and 55.6%, respectively), the rate of CDO1 gene promoter methylation was higher in the poorly differentiated tissues (89.5 and 92.3%, respectively). Overall, it was demonstrated that the MOB-qMSP method had a higher positive detection rate for CDO1 hypermethylation compared with the cMSP method. In conclusion, CDO1 gene promoter hypermethylation was more frequently observed in NSCLC tissues compared with in normal lung tissues, and a high methylation frequency of the CDO1 gene in biopsy specimens of NSCLC was associated with the degree of differentiation.

Epigenetics of Circulating Tumor Cells in Breast Cancer

Liquid biopsy based on the analysis of circulating tumor cells (CTCs) has emerged as an important field of research. Molecular characterization of CTCs can provide insights into cancer biology and biomarkers for the clinic, representing a non-invasive powerful tool for monitoring breast cancer metastasis and predict the therapeutic response. Epigenetic mechanisms play a key role in the control of gene expression and their alteration contributes to cancer development and progression. These epigenetic modifications in CTCs have been described mainly related to modifications of the DNA methylation pattern and changes in the expression profile of noncoding RNAs. Here we summarize the recent findings on the epigenetic characterization of CTCs in breast cancer and their clinical value as tumor biomarkers, and discuss challenges and opportunities in this field.

Methylation‑driven genes PMPCAP1, SOWAHC and ZNF454 as potential prognostic biomarkers in lung squamous cell carcinoma

Of the different types of lung cancer, lung squamous cell cancer (LUSC) has the second highest rates of morbidity and mortality, which have been increasing in recent years. Epigenetic abnormalities may serve as potential biomarkers and diagnostic and/or therapeutic targets, which may help to monitor and improve the prognosis of patients with cancer. In the present study, data were obtained from The Cancer Genome Atlas database and survival and joint survival analyses were conducted using the R MethylMix package. Peptidase, mitochondrial processing a subunit pseudogene 1 (PMPCAP1), sosondowah ankyrin repeat domain family member C (SOWAHC) and zinc finger protein (ZNF) 454 were identified as independent prognosis‑related hub methylation‑driven genes (MDGs). Of these three genes, PMPCAP1 and SOWAHC, characterized by hypomethylation and high expression levels, were associated with poor prognosis in patients with LUSC, whilst ZNF454 was associated with an improved prognosis. In addition, pathway enrichment analysis suggested that PMPCAP1, SOWAHC and ZNF454 were primarily involved in gene expression or transcription pathways. Furthermore, 5, 1 and 10 key methylation sites of PMPCAP1, SOWAHC and ZNF454, respectively, were confirmed to be significantly relevant to gene expression, establishing a basis for further investigation into the mechanisms and more precise targets of these 3 genes. In conclusion, the MDGs PMPCAP1, SOWAHC and ZNF454 may be potential prognostic biomarkers of LUSC for guiding diagnosis and therapy options, as well as providing a theoretical basis for further investigation.

Prospects for incorporation of epigenetic biomarkers in human health and environmental risk assessment of chemicals

Epigenetic mechanisms have gained relevance in human health and environmental studies, due to their pivotal role in disease, gene × environment interactions and adaptation to environmental change and/or contamination. Epigenetic mechanisms are highly responsive to external stimuli and a wide range of chemicals has been shown to determine specific epigenetic patterns in several organisms. Furthermore, the mitotic/meiotic inheritance of such epigenetic marks as well as the resulting changes in gene expression and cell/organismal phenotypes has now been demonstrated. Therefore, epigenetic signatures are interesting candidates for linking environmental exposures to disease as well as informing on past exposures to stressors. Accordingly, epigenetic biomarkers could be useful tools in both prospective and retrospective risk assessment but epigenetic endpoints are currently not yet incorporated into risk assessments. Achieving a better understanding on this apparent impasse, as well as identifying routes to promote the application of epigenetic biomarkers within environmental risk assessment frameworks are the objectives of this review. We first compile evidence from human health studies supporting the use of epigenetic exposure-associated changes as reliable biomarkers of exposure. Then, specifically focusing on environmental science, we examine the potential and challenges of developing epigenetic biomarkers for environmental fields, and discuss useful organisms and appropriate sequencing techniques to foster their development in this context. Finally, we discuss the practical incorporation of epigenetic biomarkers in the environmental risk assessment of chemicals, highlighting critical data gaps and making key recommendations for future research within a regulatory context.

Identification of TAF1, SAT1, and ARHGEF9 as DNA methylation biomarkers for hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a major cause of cancer-related deaths worldwide. More than 90% of primary HCC is HCC. Hepatitis C virus (HCV) infection and alcohol consumption have been widely accepted as two major risk factors for developing HCC. Herein, we aimed to identify DNA methylation genes related to both HCV infection and alcohol consumption. In this study, we identified methylation genes that were associated with the risk of HCV infection and alcohol consumption, respectively, by a large-scale bioinformatic analysis. Through PPI network analysis, we revealed the associations between the two types of genes and found six hub genes-TAF1, SAT1, Phospholipase C-beta 2, FGD1, ARHGAP4, and ARHGEF9-that may be associated with both HCV infection and alcohol consumption. Gene Ontology enrichment analysis was used to analyze the function which these genes in the network enriched. Among them, TAF1, SAT1, and ARHGEF9 were methylated genes that have been found to be related to tumor progression in HCC patients. Through independent data sets, we verified the methylation pattern of these six genes in HCC samples that had both HCV infection and alcohol consumption risks. Furthermore, we found that three of the six methylated genes were also associated with the prognosis of HCC patients. To summarize, we identified six hub genes that were associated with both HCV infection and alcohol consumption in the progress of HCC. The six methylation genes that might play an important role in both HCV infection and alcohol consumption would be potential therapy targets for HCC.

Epigenetic Mechanisms in Irritable Bowel Syndrome

Irritable bowel syndrome (IBS) is a brain-gut axis disorder characterized by abdominal pain and altered bowel habits. IBS is a multifactorial, stress-sensitive disorder with evidence for familial clustering attributed to genetic or shared environmental factors. However, there are weak genetic associations reported with IBS and a lack of evidence to suggest that major genetic factor(s) contribute to IBS pathophysiology. Studies on animal models of stress, including early life stress, suggest a role for environmental factors, specifically, stress associated with dysregulation of corticotropin releasing factor and hypothalamus-pituitary-adrenal (HPA) axis pathways in the pathophysiology of IBS. Recent evidence suggests that epigenetic mechanisms, which constitute molecular changes not driven by a change in gene sequence, can mediate environmental effects on central and peripheral function. Epigenetic alterations including DNA methylation changes, histone modifications, and differential expression of non-coding RNAs (microRNA [miRNA] and long non-coding RNA) have been associated with several diseases. The objective of this review is to elucidate the molecular factors in the pathophysiology of IBS with an emphasis on epigenetic mechanisms. Emerging evidence for epigenetic changes in IBS includes changes in DNA methylation in animal models of IBS and patients with IBS, and various miRNAs that have been associated with IBS and endophenotypes, such as increased visceral sensitivity and intestinal permeability. DNA methylation, in particular, is an emerging field in the realm of complex diseases and a promising mechanism which can provide important insights into IBS pathogenesis and identify potential targets for treatment.

A Comprehensive Prognostic and Immune Analysis of SLC41A3 in Pan-Cancer

SLC41A3, as a member of the 41^st family of solute carriers, participates in the transport of magnesium. The role of SLC41A3 in cancer prognosis and immune regulation has rarely been reported. This study was designed to analyze the expression status and prognostic significance of SLC41A3 in pan-cancers. The mRNA expression profiles of SLC41A3 were obtained from The Cancer Genome Atlas (TCGA), the Genotype-Tissue Expression (GTEx), the Broad Institute Cancer Cell Line Encyclopedia (CCLE), and the International Cancer Genome Consortium (ICGC). The Cox regression and Kaplan-Meier analyses were used to evaluate the prognostic value of SLC41A3 in pan-cancer. Furthermore, the correlation between SLC41A3 expression and immune cells infiltration, immune checkpoint, mismatch repair (MMR), DNA methyltransferase (DNMT), tumor mutation burden (TMB), and microsatellite instability (MSI) were calculated using data form TCGA database. The results showed that the expression of SLC41A3 was down-regulated in kidney renal clear cell carcinoma (KIRC), and was associated with poor overall survival and tumor-specific mortality. Whereas, the expression of SLC41A3 was up-regulated in liver hepatocellular carcinoma (LIHC), and the results of Cox regression analysis revealed that SLC41A3 was an independent factor for LIHC prognosis. Meanwhile, a nomogram including SLC41A3 and stage was built and exhibited good predictive power for the overall survival of LIHC patients. Additionally, correlation analysis suggested a significant correlation between SLC41A3 and TMB, MSI, MMR, DNMT, and immune cells infiltration in various cancers. The overall survival and disease-specific survival analysis revealed that the combined SLC41A3 expression and immune cell score, TMB, and MSI were significantly associated with clinical outcomes in ACC, LIHC, and UVM patients. Therefore, we proposed that SLC41A3 may serve as a potential prognostic biomarker for cancer.

Epigenetics Analysis and Integrated Analysis of Multiomics Data, Including Epigenetic Data, Using Artificial Intelligence in the Era of Precision Medicine

To clarify the mechanisms of diseases, such as cancer, studies analyzing genetic mutations have been actively conducted for a long time, and a large number of achievements have already been reported. Indeed, genomic medicine is considered the core discipline of precision medicine, and currently, the clinical application of cutting-edge genomic medicine aimed at improving the prevention, diagnosis and treatment of a wide range of diseases is promoted. However, although the Human Genome Project was completed in 2003 and large-scale genetic analyses have since been accomplished worldwide with the development of next-generation sequencing (NGS), explaining the mechanism of disease onset only using genetic variation has been recognized as difficult. Meanwhile, the importance of epigenetics, which describes inheritance by mechanisms other than the genomic DNA sequence, has recently attracted attention, and, in particular, many studies have reported the involvement of epigenetic deregulation in human cancer. So far, given that genetic and epigenetic studies tend to be accomplished independently, physiological relationships between genetics and epigenetics in diseases remain almost unknown. Since this situation may be a disadvantage to developing precision medicine, the integrated understanding of genetic variation and epigenetic deregulation appears to be now critical. Importantly, the current progress of artificial intelligence (AI) technologies, such as machine learning and deep learning, is remarkable and enables multimodal analyses of big omics data. In this regard, it is important to develop a platform that can conduct multimodal analysis of medical big data using AI as this may accelerate the realization of precision medicine. In this review, we discuss the importance of genome-wide epigenetic and multiomics analyses using AI in the era of precision medicine.

The Gasdermin E Gene Has Potential as a Pan-Cancer Biomarker, While Discriminating between Different Tumor Types

Due to the elevated rates of incidence and mortality of cancer, early and accurate detection is crucial for achieving optimal treatment. Molecular biomarkers remain important screening and detection tools, especially in light of novel blood-based assays. DNA methylation in cancer has been linked to tumorigenesis, but its value as a biomarker has not been fully explored. In this study, we have investigated the methylation patterns of the Gasdermin E gene across 14 different tumor types using The Cancer Genome Atlas (TCGA) methylation data (N = 6502). We were able to identify six CpG sites that could effectively distinguish tumors from normal samples in a pan-cancer setting (AUC = 0.86). This combination of pan-cancer biomarkers was validated in six independent datasets (AUC = 0.84–0.97). Moreover, we tested 74,613 different combinations of six CpG probes, where we identified tumor-specific signatures that could differentiate one tumor type versus all the others (AUC = 0.79–0.98). In all, methylation patterns exhibited great variation between cancer and normal tissues, but were also tumor specific. Our analyses highlight that a Gasdermin E methylation biomarker assay, not only has the potential for being a methylation-specific pan-cancer detection marker, but it also possesses the capacity to discriminate between different types of tumors.

DNA methylation profiles capturing breast cancer heterogeneity

BACKGROUND

As one of the most described epigenetic marks in human cancers, DNA methylation plays essential roles in gene expression regulation and has been implicated in the prognosis and therapeutics of many cancers. We are motivated in this study to explore DNA methylation profiles capturing breast cancer heterogeneity to improve breast cancer prognosis at the epigenetic level.

RESULTS

Through comparisons on differentially methylated CpG sites among breast cancer subtypes followed by a sequential validation and functional studies using computational approaches, we propose 313 CpG, corresponding to 191 genes, whose methylation pattern identifies the triple negative breast cancer subtype, and report cell migration as represented by extracellular matrix organization and cell proliferation as mediated via MAPK and Wnt signalings are the primary factors driving breast cancer subtyping.

CONCLUSIONS

Our study offers novel CpGs and gene methylation patterns with translational potential on triple negative breast cancer prognosis, as well as fresh insights from the epigenetic level on breast cancer heterogeneity.

A three-gene DNA methylation biomarker accurately classifies early stage prostate cancer

BACKGROUND

We identify and validate accurate diagnostic biomarkers for prostate cancer through a systematic evaluation of DNA methylation alterations.

MATERIALS AND METHODS

We assembled three early prostate cancer cohorts (total patients = 699) from which we collected and processed over 1300 prostatectomy tissue samples for DNA extraction. Using real-time methylation-specific PCR, we measured normalized methylation levels at 15 frequently methylated loci. After partitioning sample sets into independent training and validation cohorts, classifiers were developed using logistic regression, analyzed, and validated.

RESULTS

In the training dataset, DNA methylation levels at 7 of 15 genomic loci (glutathione S-transferase Pi 1 [GSTP1], CCDC181, hyaluronan, and proteoglycan link protein 3 [HAPLN3], GSTM2, growth arrest-specific 6 [GAS6], RASSF1, and APC) showed large differences between cancer and benign samples. The best binary classifier was the GAS6/GSTP1/HAPLN3 logistic regression model, with an area under these curves of 0.97, which showed a sensitivity of 94%, and a specificity of 93% after external validation.

CONCLUSION

We created and validated a multigene model for the classification of benign and malignant prostate tissue. With false positive and negative rates below 7%, this three-gene biomarker represents a promising basis for more accurate prostate cancer diagnosis.