DNA methylation analysis of the SDC2, SEPT9 and VIM genes in fecal DNA for colorectal cancer diagnosis.

BACKGROUND: Colorectal cancer is one of the most common cancers worldwide. DNA methylation sites may serve as a new gene signature for colorectal cancer diagnosis. The search for representative DNA methylation sites is urgently needed. This study aimed to systematically identify a methylation gene panel for colorectal cancer diagnosis via tissue and fecal samples. METHODS: A total of 181 fecal and 50 tumor tissue samples were collected. They were obtained from 83 colorectal cancer patients and 98 healthy subjects. These samples were evaluated for DNA methylation of 9 target genes via quantitative bisulfite next-generation sequencing. We employed the rank-sum test to screen the colorectal cancer-specific methylation sites in the tissue and fecal cohorts. A data model was subsequently constructed and validated via the dedicated validation dataset. RESULTS: Compared with the fecal and negative control samples, the colorectal cancer tissue samples presented significantly higher methylation rates for all the selected gene sites. The methylation rates of the tissue and preoperative fecal samples showed the same high and low rates at the same sites. After screening, a panel of 29 loci in the SDC2, SEPT9, and VIM genes proved to be reliable biomarkers for colorectal cancer diagnosis in fecal samples. Logistic regression models were then constructed and validated using this panel. The sensitivity of the model was 91.43% (95% CI = [89.69, 93.17]), the specificity was 100% (95% CI = [100,100]), and the AUC value is 99.31% (95% CI = [99,99.62]). The diagnostic accuracy of the model for stage I and stage II colorectal cancer was 100% (11/11) and 91.3% (21/23), respectively. Overall, this study confirms that the gene locus panel and the model can be used to diagnose colorectal cancer effectively through feces. CONCLUSIONS: Our study identified a set of key methylation sites for colorectal cancer diagnosis from fecal samples, highlighting the importance of using tissue and fecal samples to accurately assess DNA methylation levels to screen for methylation sites, and developing an effective diagnostic model for colorectal cancer.

MethylGenotyper: Accurate Estimation of SNP Genotypes and Genetic Relatedness from DNA Methylation Data.

Epigenome-wide association studies (EWAS) are susceptible to widespread confounding caused by population structure and genetic relatedness. Nevertheless, kinship estimation is challenging in EWAS without genotyping data. Here, we proposed MethylGenotyper, a method that for the first time enables accurate genotyping at thousands of single nucleotide polymorphisms (SNPs) directly from commercial DNA methylation microarrays. We modeled the intensities of methylation probes near SNPs with a mixture of three beta distributions corresponding to different genotypes and estimated parameters with an expectation-maximization algorithm. We conducted extensive simulations to demonstrate the performance of the method. When applying MethylGenotyper to the Infinium EPIC array data of 4662 Chinese samples, we obtained genotypes at 4319 SNPs with a concordance rate of 98.26%, enabling the identification of 255 pairs of close relatedness. Furthermore, we showed that MethylGenotyper allows for the estimation of both population structure and cryptic relatedness among 702 Australians of diverse ancestry. We also implemented MethylGenotyper in a publicly available R package (https://github.com/Yi-Jiang/MethylGenotyper) to facilitate future large-scale EWAS.

Variation within the non-coding genome influences genetic and epigenetic regulation of the human leukocyte antigen genes.

Variation within the non-coding genome may influence the regulation and expression of important genes involved in immune control such as the human leukocyte antigen (HLA) system. Class I and Class II HLA molecules are essential for peptide presentation which is required for T lymphocyte activation. Single nucleotide polymorphisms within non-coding regions of HLA Class I and Class II genes may influence the expression of these genes by affecting the binding of transcription factors and chromatin modeling molecules. Furthermore, an interplay between genetic and epigenetic factors may also influence HLA expression. Epigenetic factors such as DNA methylation and non-coding RNA, regulate gene expression without changing the DNA sequence. However, genetic variation may promote or allow genes to escape regulation by epigenetic factors, resulting in altered expression. The HLA system is central to most diseases, therefore, understanding the role of genetics and epigenetics on HLA regulation will tremendously impact healthcare. The knowledge gained from these studies may lead to novel and cost-effective diagnostic approaches and therapeutic interventions. This review discusses the role of non-coding variants on HLA regulation. Furthermore, we discuss the interplay between genetic and epigenetic factors on the regulation of HLA by evaluating literature based on polymorphisms within DNA methylation and miRNA regulatory sites within class I and Class II HLA genes. We also provide insight into the importance of the HLA non-coding genome on disease, discuss ethnic-specific differences across the HLA region and provide guidelines for future HLA studies.

DNA methylation signatures of prenatal socioeconomic position associated with 36-month language outcomes.

BACKGROUND: Socioeconomic position (SEP), which reflects one's position in society and access to resources, is strongly tied to neurodevelopment and is associated with epigenetic changes. AIM: This study examined whether DNA methylation signatures of prenatal SEP, measured in birth samples, are associated with child neurodevelopmental outcomes at 36 months of age. METHODS: Prenatal SEP DNA methylation scores were derived using 97 placenta and 127 cord blood biospecimens in the Early Autism Risk Longitudinal Investigation cohort. Participants completed the Mullen Scales of Early Learning (MSEL) and Vineland Adaptive Behavior Scales (VABS) at 36 months of age. Generalized regression analyses, adjusting for maternal age and race, were performed to test the association between SEP methylation score, for each birth biospecimen type, and MSEL and VABS scores. RESULTS: Significant associations were observed between placenta SEP methylation score and MSEL Expressive Language outcomes (beta = -2.7, p = 0.046, 95 % CI [- 5.43, -0.05]) and Receptive Language outcomes (beta = -2.5, p = 0.037, 95 % CI [-4.82, -0.16]). In cord blood, methylation-SEP scores were significantly associated with Receptive Language outcomes (beta = -2.0, p = 0.037, 95 % CI [-3.85, -0.12]). No significant associations were observed with VABS scores. CONCLUSION: Our results confirm associations between prenatal SEP and early childhood language development using a novel empiric DNA methylation measure of exposure.

Effect of body mass index on semen quality, sperm chromatin integrity and sperm DNA methylation.

Obesity represents a growing problem due to its impacts on human health and reproduction. In this study, we analysed semen quality, sperm DNA integrity and gene-specific CpG methylation in 116 healthy men from normal population. The men were divided into three groups according to their body mass index (BMI), and their ejaculates were analysed using standard methods, sperm chromatin structure assay (SCSA), methylation next generation sequencing (NGS) and amplicon sequencing. The sperm methylation NGS revealed six significantly differentially methylated regions (DMRs). Using subsequent targeted amplicon sequencing in 116 men, two of the DMRs were proved as differentially methylated in sperm of men with normal BMI vs. BMI ≥ 25. The DMRs were located in the EPHA8 and ANKRD11 gene. Also, we detected a significant decline in the EPHA8, ANKRD11 and CFAP46 gene methylation in association with increasing BMI values. The genes EPHA8 and ANKRD11 are involved in the nervous system and brain development; the CFAP46 gene plays a role in a flagellar assembly and is associated with sperm motility. Significantly lower rates of motile and progressive motile sperm were observed in men with BMI ≥ 30. Our results show that excess body weight can modify CpG methylation of specific genes, affect sperm motility, and compromise sperm chromatin integrity. These factors can stand behind the observed reduced fertility in men with obesity. The methylation changes might be transmitted to their offspring through sperm, and become a basis for possible developmental and reproductive issues in the next generation.

ERBB2 is a potential diagnostic and prognostic biomarker in renal clear cell carcinoma.

Renal clear cell carcinoma (ccRCC) is a common parenchymal tumor of the kidney, and the discovery of biomarkers for early and effective diagnosis of ccRCC can improve the early diagnosis of patients and thus improve long-term survival. Erb-b2 receptor tyrosine kinase 2 (ERBB2) mediates the processes of cell proliferation, differentiation, and apoptosis inhibition. The purpose of this study was to investigate the diagnostic and prognostic role of ERBB2 in ccRCC. We analyzed the expression levels of ERBB2 in various cancers from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. RNA-seq data were analyzed using R packages to identify differentially expressed genes between the high and low ERBB2 expression groups in the TCGA-KIRC dataset. Spearman correlation analysis was performed to determine the correlation between ERBB2 expression and immune cell infiltration, immune checkpoint expression, and PTEN expression. DNA methylation changes and genetic alterations in ERBB2 were assessed using the MethSurv and cBioPortal databases. Logistic regression analysis was performed to determine the correlation between ERBB2 expression and the clinicopathological characteristics of ccRCC patients. The diagnostic and prognostic value of ERBB2 was assessed using Kaplan‒Meier (K‒M) survival curves, diagnostic ROC curves, time-dependent ROC curves, nomogram models, and Cox regression models. The expression level of ERBB2 is lower in tumor tissues of ccRCC patients than in the corresponding control tissues. Differentially expressed genes associated with ERBB2 were significantly enriched in the pathways "BMP2WNT4FOXO1 pathway in primary endometrial stromal cell differentiation" and "AMAN pathway". In ccRCC tissues, ERBB2 expression levels were associated with immune cell infiltration, immune checkpoints, and PTEN. The DNA methylation status of 10 CpG islands in the ERBB2 gene was associated with the prognosis of ccRCC. ERBB2 expression levels in ccRCC tissues were associated with race, sex, T stage, M stage, histological grade, and pathological stage. Cox regression analysis showed that ERBB2 was a potential independent predictor of overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) in ccRCC patients. ROC curve analysis showed that the expression level of ERBB2 could accurately distinguish between ccRCC tissue and adjacent normal renal tissue. Our study showed that ERBB2 expression in ccRCC tissues can be of clinical importance as a potential diagnostic and prognostic biomarker.

Expression, DNA methylation pattern and transcription factor EPB41L3 in gastric cancer: a study of 262 cases.

PURPOSE: DNA methylation prominently inactivates tumor suppressor genes and facilitates oncogenesis. Previously, we delineated a chromosome 18 deletion encompassing the erythrocyte membrane protein band 4.1-like 3 (EPB41L3) gene, a progenitor for the tumor suppressor that is differentially expressed in adenocarcinoma of the lung-1 (DAL-1) in gastric cancer (GC). METHODS: Our current investigation aimed to elucidate EPB41L3 expression and methylation in GC, identify regulatory transcription factors, and identify affected downstream pathways. Immunohistochemistry demonstrated that DAL-1 expression is markedly reduced in GC tissues, with its downregulation serving as an independent prognostic marker. RESULTS: High-throughput bisulfite sequencing of 70 GC patient tissue pairs revealed that higher methylation of non-CpGs in the EPB41L3 promoter was correlated with more malignant tumor progression and higher-grade tissue classification. Such hypermethylation was shown to diminish DAL-1 expression, thus contributing to the malignancy of GC phenotypes. The DNA methyltransferase inhibitor 5-aza-2'-deoxycytidine (5-aza-CdR) was found to partially restore DAL-1 expression. Moreover, direct binding of the transcription factor CDC5L to the upstream region of the EPB41L3 promoter was identified via chromosome immunoprecipitation (ChIP)-qPCR and luciferase reporter assays. Immunohistochemistry confirmed the positive correlation between CDC5L and DAL-1 protein levels. Subsequent RNA-seq analysis revealed that DAL-1 significantly influences the extracellular matrix and space-related pathways. GC cell RNA-seq post-5-Aza-CdR treatment and single-cell RNA-seq data of GC tissues confirmed the upregulation of AREG and COL17A1, pivotal tumor suppressors, in response to EPB41L3 demethylation or overexpression in GC epithelial cells. CONCLUSION: In conclusion, this study elucidates the association between non-CpG methylation of EPB41L3 and GC progression and identifies the key transcription factors and downstream molecules involved. These findings enhance our understanding of the role of EPB41L3 in gastric cancer and provide a solid theoretical foundation for future research and potential clinical applications.

The EPB41L3 gene, frequently exhibiting haplotype deletions and reduced expression in gastric cancer tissues, points to its potential role as a tumor suppressor. However, tumor suppressor genes are not only influenced by genomic deletions but also by their methylation status. Our study highlights the significantly lower expression of EPB41L3 in gastric cancer compared to adjacent non-cancerous tissues across 262 patients. We also discovered that elevated non-CpG island methylation of EPB41L3 correlates strongly with tumor malignancy progression, based on the analysis of 70 paired gastric cancer samples. Moreover, we identified CDC5L as a crucial transcription factor interacting with the EPB41L3 promoter. Integrative analyses of transcriptomic and single-cell sequencing data further revealed that AREG and COL17A1 are key downstream molecules regulated by DAL-1, with their expression tightly controlled by EPB41L3 methylation and expression levels. These insights enhance our understanding of EPB41L3's role in gastric cancer and could open new avenues for targeted therapies.

An epigenetic human cytomegalovirus infection score predicts viremia risk in seropositive lung transplant recipients.

Cytomegalovirus (CMV) infection and reactivation in solid organ transplant (SOT) recipients increases the risk of viremia, graft failure and death. Clinical studies of CMV serostatus indicate that donor positive recipient negative (D+/R-) patients have greater viremia risk than D-/R-. The majority of patients are R+ having intermediate serologic risk. To characterize the long-term impact of CMV infection and assess viremia risk, we sought to measure the effects of CMV on the recipient immune epigenome. Specifically, we profiled DNA methylation in 156 individuals before lung or kidney transplant. We found that the methylome of CMV positive SOT recipients is hyper-methylated at loci associated with neural development and Polycomb group (PcG) protein binding, and hypo-methylated at regions critical for the maturation of lymphocytes. In addition, we developed a machine learning-based model to predict the recipient CMV serostatus after correcting for cell type composition and ancestry. This CMV episcore measured at baseline in R+ individual stratifies viremia risk accurately in the lung transplant cohort, and along with serostatus the CMV episcore could be a potential biomarker for identifying R+ patients at high viremia risk.

Circulating tumor DNA predicts recurrence and survival in patients with resectable gastric and gastroesophageal junction cancer.

BACKGROUND: Gastric and gastroesophageal junction (GEJ) cancer represents a significant global health challenge, with high recurrence rates and poor survival outcomes. This study investigates circulating tumor DNA (ctDNA) as a biomarker for assessing recurrence risk in patients with resectable gastric and GEJ adenocarcinomas (AC). METHODS: Patients with resectable gastric and GEJ AC, undergoing perioperative chemotherapy and surgery, were prospectively enrolled. Serial plasma samples were collected at baseline, after one cycle of chemotherapy, after preoperative chemotherapy, and after surgery. ctDNA was assessed by a ddPCR test (TriMeth), which targets the gastrointestinal cancer-specific methylation patterns of the genes C9orf50, KCNQ5, and CLIP4. RESULTS: ctDNA analysis was performed on 229 plasma samples from 86 patients. At baseline, ctDNA was detected in 56% of patients, which decreased to 37% following one cycle of chemotherapy, 25% after preoperative chemotherapy and 15% after surgical resection. The presence of ctDNA after one cycle of chemotherapy was associated with reduced recurrence-free survival (RFS) (HR = 2.54, 95% confidence interval (CI) 1.33-4.85, p = 0.005) and overall survival (OS) (HR = 2.23, 95% CI 1.07-4.62, p = 0.032). Similarly, ctDNA after surgery was associated with significantly shorter RFS (HR = 6.22, 95% CI 2.39-16.2, p < 0.001) and OS (HR = 6.37, 95% CI 2.10-19.3, p = 0.001). Multivariable regression analysis confirmed ctDNA after surgery as an independent prognostic factor (p < 0.001). CONCLUSION: ctDNA analysis has the potential to identify patients at elevated risk of recurrence, thus providing personalized treatment strategies for patients with resectable gastric and GEJ cancer. Further validation in larger cohorts and ctDNA-guided interventions are needed for future clinical use.

DNA methylation of serotonin genes as predictive biomarkers of antidepressant treatment response.

Selective serotonin reuptake inhibitors (SSRI) are frequently ineffective in treating depressive episodes and biomarkers are needed to optimize antidepressant treatment outcomes. DNA methylation levels of serotonin transporter (SLC6A4) and tryptophan hydroxylase 2 genes (TPH2) have been suggested to predict antidepressant clinical outcomes but their applicability remains uncertain. In this study, we: 1) evaluated SLC6A4/TPH2 methylation biomarker potential for predicting clinical outcomes after escitalopram treatment; 2) evaluated whether changes in SLC6A4/TPH2 methylation are informative of treatment mechanisms. We used a cohort of 90 unmedicated patients with major depressive disorder that were part of a 12-week open-label longitudinal trial and compared our observations with previous findings. Depressive symptoms were measured at baseline and after 8 and 12 weeks of treatment using the Hamilton Depression Rating Scale (HAMD6/17). We found an association between baseline TPH2 methylation and both clinical response (ß:3.43; p = 0.01; 95 % CI:[0.80; 6.06]) and change in depressive symptoms after 8 weeks (ß:-45.44; p = 0.01; 95 %CI:[- -78.58; -12.30]). However, we found no evidence for predictive value of any gene (TPH2 AUC: 0.74 95 % CI:[0.42;0.79]; SLC6A4: AUC: 0.61; 95 % CI: [0.48-0.78]). Methylation levels changed at the trend level for CpG sites of SLC6A4 and TPH2 over the course of 12 weeks of treatment. In addition, similar to previous observations, we found a trend for an association between methylation of SLC6A4 CpG2 (chr17:30,236,083) and HAMD17 change after 12 weeks. Our findings suggest that although TPH2 and SLC6A4 methylation may be informative of antidepressant treatment outcome, they are unlikely to prove useful as clinical predictor tools.

Rapid genome-wide profiling of DNA methylation and genetic variation using guide positioning sequencing (GPS).

Whole-genome bisulfite sequencing (WGBS) has been extensively utilized for DNA methylation profiling over the past decade. However, it has shown limitations in terms of high costs and inefficiencies. The productivity and accuracy of DNA methylation detection rely critically on the optimization of methodologies and the continuous refinements of related sequencing platforms. Here, we describe a detailed protocol of guide positioning sequencing (GPS), a bisulfite-based, location-specific sequencing technology designed for comprehensive DNA methylation characterization across the genome. The fundamental principle of GPS lies in the substitution of dCTP with 5-methyl-dCTP (5 mC) at the 3'-end of DNA fragments by T4 DNA polymerase, which protects cytosines from bisulfite conversion to preserve the integrity of the base composition. This alteration allows the 3'-end to independently facilitate genetic variation profiling and guides the 5'-end, enriched with methylation information, to align more rapidly to the reference genome. Hence, GPS enables the concurrent detection of both genetic and epigenetic variations. Additionally, we provide an accessible description of the data processing, specifically involving certain software and scripts. Overall, the entire GPS procedure can be completed within a maximum of 15 days, starting with a low initial DNA input of 100-500 ng, followed by 4-5 days for library construction, 8-10 days for high-throughput sequencing (HTS) and data analysis, which can greatly facilitate the promotion and application of DNA methylation detection, especially for the rapid clinical diagnosis of diverse disease pathologies associated with concurrent genetic and epigenetic variations.

Sarcoma diagnosis by DNA methylation classifier: A systematic review, current status and future prospects.

Sarcomas, a diverse group of malignant tumors originating from connective tissues, present substantial diagnostic challenges due to their histological heterogeneity. Traditional diagnostic methods include histomorphology along with immunohistochemistry is necessary for primary evaluation. Fluorescence in situ hybridization (FISH) is a supplementary tool that helps with additional findings. However it is very difficult sometimes to accurately classify sarcoma subtypes despite all these tools. Recent advancements in DNA methylation profiling have emerged as a promising approach to enhance the precision of sarcoma diagnosis. This paper delves into the role of DNA methylation classifiers in diagnosing sarcomas, emphasizing their potential to improve diagnostic accuracy, inform treatment decisions, and ultimately enhance patient outcomes.

MethylSeqLogo: DNA methylation smart sequence logos.

BACKGROUND: Some transcription factors, MYC for example, bind sites of potentially methylated DNA. This may increase binding specificity as such sites are (1) highly under-represented in the genome, and (2) offer additional, tissue specific information in the form of hypo- or hyper-methylation. Fortunately, bisulfite sequencing data can be used to investigate this phenomenon. METHOD: We developed MethylSeqLogo, an extension of sequence logos which includes new elements to indicate DNA methylation and under-represented dimers in each position of a set binding sites. Our method displays information from both DNA strands, and takes into account the sequence context (CpG or other) and genome region (promoter versus whole genome) appropriate to properly assess the expected background dimer frequency and level of methylation. MethylSeqLogo preserves sequence logo semantics-the relative height of nucleotides within a column represents their proportion in the binding sites, while the absolute height of each column represents information (relative entropy) and the height of all columns added together represents total information RESULTS: We present figures illustrating the utility of using MethylSeqLogo to summarize data from several CpG binding transcription factors. The logos show that unmethylated CpG binding sites are a feature of transcription factors such as MYC and ZBTB33, while some other CpG binding transcription factors, such as CEBPB, appear methylation neutral. CONCLUSIONS: Our software enables users to explore bisulfite and ChIP sequencing data sets-and in the process obtain publication quality figures.

Genome-wide DNA methylation and their transgenerational pattern differ in Arabidopsis thaliana populations originated along the elevation of West Himalaya.

Methylation at 5' cytosine of DNA molecule is an important epigenetic mark. It is known to play critical role in adaptation of organisms under different biotic and abiotic stressors via modulating gene expression and/or chromatin architecture. Plant populations evolved under variable climatic conditions may have evolved different epigenetic marks including DNA methylation. Here we, describe the genome-wide DNA methylation pattern under native field, F1 and F6 generation followed by their association with phenotypes, climate and global gene expression in the three Arabidopsis thaliana populations originated at different elevation ranges of Indian West Himalaya. We show that the global methyl cytosine (mC) content is more or less similar in the three populations but differ in their distribution across genome. There was an increase in differential methylation between the populations as elevation increased. The methylation divergence was the highest between the low and the high elevation populations. The high elevation populations were hypo-methylated than the low elevation population. The methylation in the genes was associated with population specific phenotypes and climate of the region. The genes which were differentially methylated as well as differentially expressed between the low and high elevation populations were mostly related to abiotic stresses. When grown under controlled condition, there was gain of differential methylation over native condition and the maximum percent changes was observed in CHH-sequence context. Further ~ 99.8% methylated cytosines were stably passed on from F1 to F6 generation. Overall, our data suggest that high elevation population is epigenetically more plastic under changing environmental condition.Background Arabidopsis thaliana is the model plant species and has been extensively studied to understand plants life processes. There are numerous reports on its origin, demography, evolution, epigenomes and adaptation etc. however, Indian populations of Arabidopsis thaliana evolved along wide elevation ranging from ~ 700 m amsl to ~ 3400 m amsl not explored yet. Here we, describe the genome-wide DNA methylation pattern under native field, F1 and F6 generation followed by their association with phenotypes, climate and global gene expression in the three Arabidopsis thaliana populations originated at different elevation ranges of Indian West Himalaya.Results In our study we found that total mCs percent was more or less similar in the three populations but differ in their distribution across genome. The proportion of CG-mCs was the highest, followed by CHH-mCs and CHG-mCs in all the three populations. Under native field condition the methylation divergence was more prominent between low and high elevation populations and the high elevation populations were hypo-methylated than the low elevation population. The methylation in the genes was linked to population-specific phenotypes and the regional climate. The genes that showed differential methylation and expression between low and high elevation populations were primarily associated with abiotic stress responses. When grown under controlled condition, there was gain of differential methylation compared to the native condition and the maximum percent changes was observed in CHH-sequence context. Further 99.8% methylated cytosines were stably passed on from F1 to F6 generation.Conclusions The populations of A. thaliana adapted at different climatic conditions were significantly differentially methylated both under native and controlled condition. However, the magnitude and extent of gain or loss of methylation were most significant between the low and the high elevation populations. Overall, our data suggest that high elevation population is epigenetically more plastic under changing environmental condition.

PathMethy: an interpretable AI framework for cancer origin tracing based on DNA methylation.

Despite advanced diagnostics, 3%-5% of cases remain classified as cancer of unknown primary (CUP). DNA methylation, an important epigenetic feature, is essential for determining the origin of metastatic tumors. We presented PathMethy, a novel Transformer model integrated with functional categories and crosstalk of pathways, to accurately trace the origin of tumors in CUP samples based on DNA methylation. PathMethy outperformed seven competing methods in F1-score across nine cancer datasets and predicted accurately the molecular subtypes within nine primary tumor types. It not only excelled at tracing the origins of both primary and metastatic tumors but also demonstrated a high degree of agreement with previously diagnosed sites in cases of CUP. PathMethy provided biological insights by highlighting key pathways, functional categories, and their interactions. Using functional categories of pathways, we gained a global understanding of biological processes. For broader access, a user-friendly web server for researchers and clinicians is available at https://cup.pathmethy.com.

Uterine mesenchymal tumours harboring the KAT6B/A::KANSL1 gene fusion represent a distinct type of uterine sarcoma based on DNA methylation profiles.

Uterine mesenchymal tumours harboring KAT6B/A::KANSL1 gene fusions typically exhibit histological and immunophenotypic overlap with endometrial stromal and smooth muscle tumours. To date it remains uncertain whether such neoplasms should be regarded as variants of smooth muscle or endometrial stromal neoplasm, or if they constitute a distinct tumour type. In this study we investigated DNA methylation patterns and copy number variations (CNVs) in a series of uterine tumours harboring KAT6B/A::KANSL1 gene fusions in comparison to other mesenchymal neoplasms of the gynecological tract. Unsupervised hierarchical clustering and t-SNE analysis of DNA methylation data (Illumina EPIC array) identified a distinct cluster for 8/13 KAT6B/A::KANSL1 tumours (herein referred to as core cluster). The other 5 tumours (herein referred to as outliers) did not assign to the core cluster but clustered near various other tumour types. CNV analysis did not identify significant alterations in the core cluster. In contrast, various alterations, including deletions at the CDKN2A/B and NF1 loci were identified in the outlier group. Analysis of the DNA methylation clusters in relation to histological features revealed that while tumours in the core KAT6B/A::KANSL1 cluster were histologically bland, outlier tumours frequently exhibited "high-grade" histologic features in the form of significant nuclear atypia, increased mitotic activity and necrosis. Three of the five patients with outlier tumours died from their disease while clinical follow-up in the remaining two patients was limited (less than 12 months). In comparison, none of the 7 out of 8 patients with tumors in the core KAT6B/A::KANSL1 sarcoma cluster, where follow-up was available, died from disease. Furthermore, only 1 out of 7 patients recurred (mean follow-up of 30 months). In conclusion, KAT6B/A::KANSL1 uterine sarcoma is a molecularly unique type of uterine tumour that should be recognized as a distinct entity. These tumors typically exhibit low-grade histologic features but are occasionally morphologically high-grade; the latter have a DNA methylation profile different from the typical low-grade neoplasms and may be associated with aggressive behaviour.

DNA demethylation triggers cell free DNA release in colorectal cancer cells.

BACKGROUND: Liquid biopsy based on cell-free DNA (cfDNA) analysis holds significant promise as a minimally invasive approach for the diagnosis, genotyping, and monitoring of solid malignancies. Human tumors release cfDNA in the bloodstream through a combination of events, including cell death, active and passive release. However, the precise mechanisms leading to cfDNA shedding remain to be characterized. Addressing this question in patients is confounded by several factors, such as tumor burden extent, anatomical and vasculature barriers, and release of nucleic acids from normal cells. In this work, we exploited cancer models to dissect basic mechanisms of DNA release. METHODS: We measured cell loss ratio, doubling time, and cfDNA release in the supernatant of a colorectal cancer (CRC) cell line collection (N = 76) representative of the molecular subtypes previously identified in cancer patients. Association analyses between quantitative parameters of cfDNA release, cell proliferation, and molecular features were evaluated. Functional experiments were performed to test the impact of modulating DNA methylation on cfDNA release. RESULTS: Higher levels of supernatant cfDNA were significantly associated with slower cell cycling and increased cell death. In addition, a higher cfDNA shedding was found in non-CpG Island Methylator Phenotype (CIMP) models. These results indicate a positive correlation between lower methylation and increased cfDNA levels. To explore this further, we exploited methylation microarrays to identify a subset of probes significantly associated with cfDNA shedding and derive a methylation signature capable of discriminating high from low cfDNA releasers. We applied this signature to an independent set of 176 CRC cell lines and patient derived organoids to select 14 models predicted to be low or high releasers. The methylation profile successfully predicted the amount of cfDNA released in the supernatant. At the functional level, genetic ablation of DNA methyl-transferases increased chromatin accessibility and DNA fragmentation, leading to increased cfDNA release in isogenic CRC cell lines. Furthermore, in vitro treatment of five low releaser CRC cells with a demethylating agent was able to induce a significant increase in cfDNA shedding. CONCLUSIONS: Methylation status of cancer cell lines contributes to the variability of cfDNA shedding in vitro. Changes in methylation pattern are associated with cfDNA release levels and might be exploited to increase sensitivity of liquid biopsy assays.

Applicability of epigenetic age models to next-generation methylation arrays.

BACKGROUND: Epigenetic clocks are mathematical models used to estimate epigenetic age based on DNA methylation at specific CpG sites. As new methylation microarrays are developed and older models discontinued, existing epigenetic clocks might become obsolete. Here, we explored the effects of the changes introduced in the new EPICv2 DNA methylation array on existing epigenetic clocks. METHODS: We tested the performance of four epigenetic clocks on the probeset of the EPICv2 array using a dataset of 10,835 samples. We developed a new epigenetic age prediction model compatible across the 450 k, EPICv1, and EPICv2 microarrays and validated it on 2095 samples. We estimated technical noise and intra-subject variation using two datasets with repeated sampling. We used data from (i) cancer survivors who had undergone different therapies, (ii) breast cancer patients and controls, and (iii) an exercise-based interventional study, to test the ability of our model to detect alterations in epigenetic age acceleration in response to theoretically antiaging interventions. RESULTS: The results of the four epiclocks tested are significantly distorted by the EPICv2 probeset, causing an average difference of up to 25 years. Our new model produced highly accurate chronological age predictions, comparable to a state-of-the-art epiclock. The model reported the lowest epigenetic age acceleration in normal populations, as well as the lowest variation across technical replicates and repeated samples from the same subjects. Finally, our model reproduced previous results of increased epigenetic age acceleration in cancer patients and in survivors treated with radiation therapy, and no changes from exercise-based interventions. CONCLUSION: Existing epigenetic clocks require updates for full EPICv2 compatibility. Our new model translates the capabilities of state-of-the-art epigenetic clocks to the EPICv2 platform and is cross-compatible with older microarrays. The characterization of epigenetic age prediction variation provides useful metrics to contextualize the relevance of epigenetic age alterations. The analysis of data from subjects influenced by radiation, cancer, and exercise-based interventions shows that despite being good predictors of chronological age, neither a pathological state like breast cancer, a hazardous environmental factor (radiation), nor exercise (a beneficial intervention) caused significant changes in the values of the "epigenetic age" determined by these first-generation models.

Differences in the DNA methylome of T cells in adults with asthma of varying severity.

BACKGROUND: DNA methylation plays a critical role in asthma development, but differences in DNA methylation among adults with varying asthma severity are less well-defined. OBJECTIVE: To examine how DNA methylomic patterns differ among adults with asthma based on asthma severity and airway inflammation. METHODS: Peripheral blood T cells from 35 adults with asthma in Beijing, China, were serially collected over time (130 samples total) and analyzed for global DNA methylation using the Illumina MethylationEPIC Array. Differential methylation was compared among subjects with varying airway inflammation and severity, as measured by fraction of exhaled nitric oxide, forced expiratory volume in one second (FEV1), and Asthma Control Test (ACT) scores. RESULTS: Significant differences in DNA methylation were noted among subjects with different degrees of airway inflammation and asthma severity. These differences in DNA methylation were annotated to genes that were enriched in pathways related to asthma or T cell function and included gene ontology categories related to MHC class II assembly, T cell activation, interleukin (IL)-1, and IL-12. Genes related to P450 drug metabolism, glutathione metabolism, and developmental pathways were also differentially methylated in comparisons between subjects with high vs low FEV1 and ACT. Notable genes that were differentially methylated based on asthma severity included RUNX3, several members of the HLA family, AGT, PTPRC, PTPRJ, and several genes downstream of the JAK2 and TNF signaling pathway. CONCLUSION: These findings demonstrate how adults with asthma of varying severity possess differences in peripheral blood T cell DNA methylation that contribute to differences in clinical indices of asthma.

Epigenetic Changes in Cerebrospinal Fluid and Blood of People with Neurosyphilis.

Epigenetic changes within immune cells may contribute to neuroinflammation during bacterial infection, but its role in neurosyphilis pathogenesis and response has not yet been established. We longitudinally analyzed DNA methylation and RNA expression changes in cerebrospinal fluid (CSF) cells and peripheral blood mononuclear cells (PBMCs) from 11 participants with laboratory-confirmed NS (CSF VDRL positive) and 11 matched controls with syphilis without NS (non-NS). DNA methylation profiles from CSF and PBMCs of participants with NS significantly differed from those of participants with non-NS. Some genes associated with these differentially methylated sites had corresponding RNA expression changes in the CSF (111/1097, 10.1%), which were enriched in B-cell, cytotoxic-compounds, and insulin-response pathways. Despite antibiotic treatment, approximately 80% of CSF methylation changes persisted; suggesting that epigenetic scars accompanying NS may persistently affect immunity following infection. Future studies must examine whether these sequelae are clinically meaningful.