Stable Methylation Research Articles

Mathematical model of RNA-directed DNA methylation predicts tuning of negative feedback required for stable maintenance.

RNA-directed DNA methylation (RdDM) is a plant-specific de novo methylation pathway that is responsible for maintenance of asymmetric methylation (CHH, H = A, T or G) in euchromatin. Loci with CHH methylation produce 24 nucleotide (nt) short interfering (si) RNAs. These siRNAs direct additional CHH methylation to the locus, maintaining methylation states through DNA replication. To understand the necessary conditions to produce stable methylation, we developed a stochastic mathematical model of RdDM. The model describes DNA target search by siRNAs derived from CHH methylated loci bound by an Argonaute. Methylation reinforcement occurs either throughout the cell cycle (steady) or immediately following replication (bursty). We compare initial and final methylation distributions to determine simulation conditions that produce stable methylation. We apply this method to the low CHH methylation case. The resulting model predicts that siRNA production must be linearly proportional to methylation levels, that bursty reinforcement is more stable and that slightly higher levels of siRNA production are required for searching DNA, compared to RNA. Unlike CG methylation, which typically exhibits bi-modality with loci having either 100% or 0% methylation, CHH methylation exists across a range. Our model predicts that careful tuning of the negative feedback in the system is required to enable stable maintenance.

An epigenetic editor targeting human PCSK9 efficiently and durably lowers Low Density Lipoprotein Cholesterol (LDL-C) in non-human primates

Abstract Background Reducing the risk of atherosclerotic cardiovascular disease is dependent on both the magnitude and cumulative duration of LDL-C lowering. However, in clinical practice achieving treatment goals is often hampered by low adherence to standard of care. Although PCSK9 inhibitors represent an effective option for LDL-C lowering, they require chronic life-long treatment. Epigenetic editing is a new therapeutic approach designed to durably silence genes by leveraging nature’s endogenous cellular mechanism for gene regulation via CpG methylation without the inherent genotoxic risks of genome editing approaches that nick or cut the DNA. We are developing a PCSK9 epigenetic editor (PCSK9-EE) to durably silence PCSK9, with the promise of lifelong reduction in LDL-C. Methods Here, we describe the development of an epigenetic editor targeting human PCSK9. This epigenetic editor consists of a DNA targeting component fused to a transcriptional repressor domain and a DNA methyltransferase domain. PCSK9-EE was first screened and evaluated for specificity and efficacy in primary human hepatocytes (PHH). In vivo efficacy and durability were then evaluated in a transgenic mouse carrying the human PCSK9 genomic locus (hPCSK9-Tg mouse) and non-human primates (NHP). Results Our initial screen of PCSK9-EEs identified several hits that efficiently suppressed secreted PCSK9 levels in immortalized liver cells. We confirmed that our top PCSK9-EE candidates robustly decreased PCSK9 secretion in PHH and were found to be highly specific at targeting PCSK9 as assessed by RNA-seq, methylation array, and whole-genome methylation sequencing. To examine in vivo activity, we treated hPCSK9-Tg mice with a single administration of a lipid nanoparticle delivering mRNA encoding our PCSK9-EE and observed >97% reduction in liver PCSK9 mRNA, and >98% reduction in plasma PCSK9 for the duration of the study (one year). We then delivered PCSK9-EE in NHP and observed a robust reduction in plasma PCSK9 with a concomitant reduction in LDL-C. These effects were found to be durable for at least 6 months following a single administration of PCSK9-EE in NHP. To establish a mechanistic relationship between PCSK9-EE’s molecular action and durable PCSK9 silencing, we performed serial liver biopsies in each NHP approximately 2 months apart. Robust CpG methylation at the PCSK9 genomic locus was observed in the first liver biopsy and was comparable to that observed in the second liver biopsy suggesting that PCSK9-EE induced stable CpG methylation in NHP livers. Conclusions We believe PCSK9-EE may offer an effective, safe, and durable approach to suppress hepatic PCSK9 expression and achieve long-lasting reduction in LDL-C. Furthermore, epigenetic editing may hold promise for one-and-done approaches for the treatment of atherosclerotic cardiovascular disease without cutting, nicking, or altering the DNA sequence.

Methylation patterns at the adjacent CpG sites within enhancers are a part of cell identity

BackgroundIt is generally accepted that methylation status of CpG sites spaced up to 50 bp apart is correlated, and accumulation of locally disordered methylation at adjacent CpG sites is involved in neoplastic transformation, acting in similar way as stochastic accumulation of mutations.ResultsWe used EPIC microarray data from 596 samples, representing 12 healthy tissue and cell types, as well as 572 blood cancer specimens to analyze methylation status of adjacent CpG sites across human genome, and subsequently validated our findings with NGS and Sanger sequencing. Our analysis showed that there is a subset of the adjacent CpG sites in human genome, with cytosine at one CpG site methylated and the other devoid of methyl group. These loci map to enhancers that are targeted by families of transcription factors involved in cell differentiation. Moreover, our results suggest that the methylation at these loci differ between alleles within a cell, what allows for remarkable level of heterogeneity of methylation patterns. However, different types of specialized cells acquire only one specific and stable pattern of methylation at each of these loci and that pattern is to a large extent lost during neoplastic transformation.ConclusionsWe identified a substantial number of adjacent CpG loci in human genome that display remarkably stable and cell type specific methylation pattern. The methylation pattern at these loci appears to reflect different methylation of alleles in cells. Furthermore, we showed that changes of methylation status at those loci are likely to be involved in regulation of the activity of enhancers and contribute to neoplastic transformation.

A high-throughput droplet digital PCR system aiming eight DNA methylation targets for age prediction

The droplet digital Polymerase Chain Reaction (ddPCR) has garnered recognition for its distinctive attribute of absolute quantification. And it has found practical utility in age prediction through DNA methylation profiles. However, a prevalent limitation in current ddPCR methodologies is the restricted capacity to detect only two targets concurrently in most instruments, leading to high costs, sample wastage, and labor-intensive procedures. To address the limitations, a novel high-throughput ddPCR system allowing for the simultaneous detection of eight targets was developed. Through the implementation of a new 8-plex ddPCR assay, coupled with comprehensive linear regression analyses involving primers and probes ratios, diverse inputs of single CpG sites with distinct primers and probes, and varying plex assay configurations, stable DNA methylation values for four CpGs and stable measurement precisions for distinct multiplex systems were consistently observed. These findings pave the way for advancing the field of chemistry science by enabling more efficient and cost-effective methods. Furthermore, the comparative validation of ddPCR and SNaPshot demonstrated a remarkable concordance in results, and the system also displayed well in the field of various aspects, including species specificity, DNA input, and aged samples. In this study, the recommended input of bisulfite-converted DNA was determined to be 10-50ng due to the double-positive droplets. Notably, the Pearson correlation coefficient squared values of four CpGs were 0.4878 (ASPA), 0.4832 (IGSF1), 0.6881 (COL1A1), and 0.6475 (MEIS1-AS3). And the testing set exhibited a mean absolute error of 4.5923 years, indicating the robustness and accuracy of the age-predictive model.

StableDNAm: towards a stable and efficient model for predicting DNA methylation based on adaptive feature correction learning

BackgroundDNA methylation, instrumental in numerous life processes, underscores the paramount importance of its accurate prediction. Recent studies suggest that deep learning, due to its capacity to extract profound insights, provides a more precise DNA methylation prediction. However, issues related to the stability and generalization performance of these models persist.ResultsIn this study, we introduce an efficient and stable DNA methylation prediction model. This model incorporates a feature fusion approach, adaptive feature correction technology, and a contrastive learning strategy. The proposed model presents several advantages. First, DNA sequences are encoded at four levels to comprehensively capture intricate information across multi-scale and low-span features. Second, we design a sequence-specific feature correction module that adaptively adjusts the weights of sequence features. This improvement enhances the model’s stability and scalability, or its generality. Third, our contrastive learning strategy mitigates the instability issues resulting from sparse data. To validate our model, we conducted multiple sets of experiments on commonly used datasets, demonstrating the model’s robustness and stability. Simultaneously, we amalgamate various datasets into a single, unified dataset. The experimental outcomes from this combined dataset substantiate the model’s robust adaptability.ConclusionsOur research findings affirm that the StableDNAm model is a general, stable, and effective instrument for DNA methylation prediction. It holds substantial promise for providing invaluable assistance in future methylation-related research and analyses.

New insights into the (epi)genetics of twinning.

Spontaneous dizygotic (DZ) twins, i.e. twins conceived without the use of ARTs, run in families and their prevalence varies widely around the globe. In contrast, monozygotic (MZ) twins occur at a constant rate across time and geographical regions and, with some rare exceptions, do not cluster in families. The leading hypothesis for MZ twins, which arise when a zygote splits during preimplantation stages of development, is random occurrence. We have found the first series of genes underlying the liability of being the mother of DZ twins and have shown that being an MZ twin is strongly associated with a stable DNA methylation signature in child and adult somatic tissues. Because identical twins keep this molecular signature across the lifespan, this discovery opens up completely new possibilities for the retrospective diagnosis of whether a person is an MZ twin whose co-twin may have vanished in the early stages of pregnancy. Here, we summarize the gene finding results for mothers of DZ twins based on genetic association studies followed by meta-analysis, and further present the striking epigenetic results for MZ twins.

DNA Methylation Instability: A Novel Biomarker for Aging, Clonality, and Cancer

Background: Clonal hematopoiesis (CH) is an age-related condition defined by the over-representation of blood cells derived from a single clone. CH has been associated with an increased risk of leukemia development, adverse cardiovascular events, and all-cause mortality. There has been great emphasis on investigating CH at the genomic level, yet the epigenetic factors that regulate the development and progression of pre-malignant clones haven't been extensively studied. Methods: Here, we develop a novel framework that employs DNA methylation (DNA-M) to detect abnormal clonal expansion of hematopoietic cells. DNA-M profiles of >1500 blood samples from healthy, young persons (age = 18) were interrogated to identify CpG sites with highly consistent methylation levels across individuals. DNA methylation instability (DMI), which we define as deviation in methylation levels at the identified stable methylation sites (SMSs), was evaluated in diverse healthy and cancer cohorts to investigate how epigenetic mechanisms may affect cellular functions resulting in clonality. Results: Characterization of SMSs. SMSs were found to be predominantly unmethylated and significantly enriched within CpG islands (OR: 13.8, p < 2 x 10 -16) and gene promoter regions (OR: 4.8, p < 2 x 10 -16). A gene ontology enrichment analysis implicated the corresponding genes in vital cellular processes such as DNA repair, damage response, and cell cycle checkpoints (p < 0.002). Consistently low methylation levels at SMSs were observed across major blood cell types. Moreover, analysis of a methylome cell atlas derived from whole genome bisulphite sequencing (WGBS) of 40 healthy human tissues revealed that SMSs remain stably unmethylated in the vast majority of tissues, suggesting broad and strict regulation at those sites. DMI in overt blood cancers. Interrogation of SMS methylation levels across diverse control and cancer datasets revealed significantly higher destabilization in cancer samples (Fig. 1, p < 2 x 10 -16). Moreover, longitudinal profiling of bone marrow samples from AML patients (n = 4, four time points each) indicated that DMI levels follow the clonal burden patterns expected during treatment. Analysis of serial dilutions of AML cell lines in cord blood further corroborated the link between DMI levels and malignant cell fractions (p < 2 x 10 -16). DMI in non-cancer cohorts. Given the link between DMI and clonality, we measured DMI in blood samples of three independent aging cohorts of individuals without a malignancy (n = 1751, age 14-101) and observed a positive correlation with age (r = 0.25, 0.38, 0.4; p < 7 x 10 -11). These results are in accordance with the increasing incidence of CH with age and suggest that DMI, much like genomic mutations, may causally precede the development and progression of various age-related diseases. CH has previously been associated with adverse cardiovascular outcomes. In a competing risk analysis of 64 cardiogenic shock patients (CH+ = 31, CH- = 33), DMI was better able to stratify patients into risk groups than genomics-based CH detection (Kaplan-Meier analysis, CH: p = 0.46, DMI: p = 0.01). These results indicate that DMI is significantly associated with mortality in high-risk patients. DMI and gene regulation. WGBS of AML and healthy control samples revealed that significantly destabilized SMSs in AML (p < 7 x 10 -6) near transcriptional start sites reflect broader hypermethylation of promoter regions. Transcriptome profiling of age-stratified controls (n = 755) and AML samples (n = 151) confirmed a gradual decrease in expression for many of the implicated genes. Notably, genes known to suppress cell proliferation and promote apoptosis such as BASP1 were implicated (Fig. 2, r = -0.20, p < 2 x 10 -16), as well as novel genes that have not previously been associated with age-related gene silencing and leukemia development. These findings further emphasize that DMI reflects a gradual process that precedes disease. Conclusion: Our results suggest that the development of clonality is not merely a genomic phenomenon and that the gradual silencing of specific genes via DMI in their promoter regions may result in positive selection and clonal dominance. This work has significant implications for elucidating the molecular mechanisms underlying age-related diseases, early detection of cancer, and the development of novel biomarkers and therapeutic strategies against hematologic malignancies.

Responders to low-dose ATG induce CD4+ T cell exhaustion in type 1 diabetes.

BACKGROUNDLow-dose anti-thymocyte globulin (ATG) transiently preserves C-peptide and lowers HbA1c in individuals with recent-onset type 1 diabetes (T1D); however, the mechanisms of action and features of the response remain unclear. Here, we characterized the post hoc immunological outcomes of ATG administration and their potential use as biomarkers of metabolic response to therapy (i.e., improved preservation of endogenous insulin production).METHODSWe assessed gene and protein expression, targeted gene methylation, and cytokine concentrations in peripheral blood following treatment with ATG (n = 29), ATG plus granulocyte colony-stimulating factor (ATG/G-CSF, n = 28), or placebo (n = 31).RESULTSTreatment with low-dose ATG preserved regulatory T cells (Tregs), as measured by stable methylation of FOXP3 Treg-specific demethylation region (TSDR) and increased proportions of CD4+FOXP3+ Tregs (P < 0.001) identified by flow cytometry. While treatment effects were consistent across participants, not all maintained C-peptide. Responders exhibited a transient rise in IL-6, IP-10, and TNF-α (P < 0.05 for all) 2 weeks after treatment and a durable CD4+ exhaustion phenotype (increased PD-1+KLRG1+CD57- on CD4+ T cells [P = 0.011] and PD1+CD4+ Temra MFI [P < 0.001] at 12 weeks, following ATG and ATG/G-CSF, respectively). ATG nonresponders displayed higher proportions of senescent T cells (at baseline and after treatment) and increased methylation of EOMES (i.e., less expression of this exhaustion marker).CONCLUSIONAltogether in these exploratory analyses, Th1 inflammation-associated serum and CD4+ exhaustion transcript and cellular phenotyping profiles may be useful for identifying signatures of clinical response to ATG in T1D.TRIAL REGISTRATIONClinicalTrials.gov NCT02215200.FUNDINGThe Leona M. and Harry B. Helmsley Charitable Trust (2019PG-T1D011), the NIH (R01 DK106191 Supplement, K08 DK128628), NIH TrialNet (U01 DK085461), and the NIH NIAID (P01 AI042288).

The role of demethylase AlkB homologs in cancer.

The AlkB family (ALKBH1-8 and FTO), a member of the Fe (II)- and α-ketoglutarate-dependent dioxygenase superfamily, has shown the ability to catalyze the demethylation of a variety of substrates, including DNA, RNA, and histones. Methylation is one of the natural organisms' most prevalent forms of epigenetic modifications. Methylation and demethylation processes on genetic material regulate gene transcription and expression. A wide variety of enzymes are involved in these processes. The methylation levels of DNA, RNA, and histones are highly conserved. Stable methylation levels at different stages can coordinate the regulation of gene expression, DNA repair, and DNA replication. Dynamic methylation changes are essential for the abilities of cell growth, differentiation, and division. In some malignancies, the methylation of DNA, RNA, and histones is frequently altered. To date, nine AlkB homologs as demethylases have been identified in numerous cancers' biological processes. In this review, we summarize the latest advances in the research of the structures, enzymatic activities, and substrates of the AlkB homologs and the role of these nine homologs as demethylases in cancer genesis, progression, metastasis, and invasion. We provide some new directions for the AlkB homologs in cancer research. In addition, the AlkB family is expected to be a new target for tumor diagnosis and treatment.

OP03 Highly stable epigenome-wide peripheral blood DNA methylation signatures accurately predict endoscopic response to adalimumab, vedolizumab and ustekinumab in Crohn’s disease patients: The EPIC-CD study

Abstract Background Despite the proven efficacy of biological treatments in Crohn’s disease (CD), many patients fail to respond or lose response over time. Therefore, predictive biomarkers for treatment efficacy would be of extreme value. Previous epigenome-wide association studies associated differential DNA methylation with CD-specific phenotypes, suggesting a potential use in classification and prediction of response to treatment. Methods We prospectively collected and measured longitudinal peripheral blood DNA methylation profiles of 184 adult CD patients prior to (T1) and after a median of 28 weeks (T2) following biological treatment with Adalimumab (ADA), Vedolizumab (VEDO) or Ustekinumab (USTE) in a discovery (n=88) and independently collected internal validation cohort (n=96) using the Illumina EPIC BeadChip array. Response (R) was defined as the combination of endoscopic response (≥50% reduction in SES-CD score) and steroid-free clinical response (≥3 point drop in HBI or HBI ≤4 AND no systemic steroids) and/or biochemical response (≥50% reduction in C-reactive protein (CRP) and fecal calprotectin or a CRP ≤5 g/mL and fecal calprotectin ≤250 µg/g). Biomarker identification and classification analyses were performed using stability selection gradient boosting on samples taken at T1 whereas samples taken at T2 and intraclass correlation (ICC) data were used to assess long-term stability of our identified CpG loci1. Results A total of 58 ADA-patients (NR=29, NNR=29), 64 VEDO-patients (NR=36, NNR=28) and 62 USTE-patients (NR=30, NNR=32) were included. Prior to treatment, at T1, we identified distinct panels of 100 ADA-, 22 VEDO- and 68 USTE-associated CpG loci that, in combination, predict clinical- and endoscopic response with high accuracy (AUC ADA=0.73, VEDO=0.89 and USTE=0.94) upon validation. Notably, for these CpG loci, methylation levels did not significantly differ between T1 and T2, implicating stability during both induction and maintenance treatment, irrespective of inflammatory status and therapeutic intervention. In addition, the majority of these CpG loci (&amp;gt;60%) demonstrated long-term hyper stability (ICC-values ≥0.90). Furthermore, genes annotated to the CpGs of interest suggest drug specific involvement in TNF-signaling, endothelial cell-cell adhesion, integrin dependent T-cell homing, the innate immune system and Th17/Treg differentiation, corroborating to the mode of action of each drug. Conclusion Here, we report on 3 validated panels of highly stable, epigenetic biomarkers that predict clinical and endoscopic response in CD patients treated with ADA, VEDO or USTE. Additional external- and clinical validation as part of EPIC-CD and the OMICROHN clinical trial are currently ongoing.

Risperidone response in patients with schizophrenia drives DNA methylation changes in immune and neuronal systems.

Background: The choice of efficient antipsychotic therapy for schizophrenia relies on a time-consuming trial-and-error approach, whereas the social and economic burdens of the disease call for faster alternatives. Material & methods: In a search for predictive biomarkers of antipsychotic response, blood methylomes of 28 patients were analyzed before and 4weeks into risperidone therapy. Results: Several CpGs exhibiting response-specific temporal dynamics were identified in otherwise temporally stable methylomes and noticeable global response-related differences wereobserved between good and bad responders. These were associated with genes involved in immunity, neurotransmission and neuronal development. Polymorphisms in many of these genes were previously linked with schizophrenia etiology and antipsychotic response. Conclusion: Antipsychotic response seems to be shaped by both stable and medication-induced methylation differences.

DamID-seq: A Genome-WideDNA Methylation Method that Captures Both Transient and Stable TF-DNA Interactions in Plant Cells.

Capturing the dynamic and transient interactions of a transcription factor (TF) with its genome-wide targets whose regulation leads to plants' adaptation to their changing environment is a major technical challenge. This is a widespread problem with biochemical methods such as chromatin immunoprecipitation-sequencing (ChIP-seq) which are biased towards capturing stable TF-target gene interactions. Herein, we describe how DNA adenine methyltransferase identification and sequencing (DamID-seq) can be used to capture both transient and stable TF-target interactions by DNA methylation. The DamID technique uses a TF protein fusedto a DNA adenine methyltransferase (Dam) from E. coli. When expressed in a plant cell, the Dam-TF fusion protein will methylate adenine (A) bases near the sites of TF-DNA interactions. In this way, DamID results in a permanent, stable DNA methylation mark on TF-targetgene promoters, even if the target gene is only transiently "touched" by the Dam-TF fusion protein. Herewe provide a step-by-step protocol to perform DamID-seq experiments in isolated plant cells for any Dam-TF fusion protein of interest. We also provide information that will enable researchers to analyze DamID-seq data to identify TF-binding sites in the genome. Our protocol includes instructions for vector cloning of the Dam-TF fusion proteins, plant cell protoplast transfections, DamID preps, library preparation, and sequencing data analysis. The protocol outlined in this chapter is performed in Arabidopsis thaliana, however, the DamID-seq workflow developed in this guide is broadly applicable to other plants and organisms.

Predicting methylation class from diffusely infiltrating adult gliomas using multimodality MRI data.

Radiogenomic studies of adult-type diffuse gliomas have used magnetic resonance imaging (MRI) data to infer tumor attributes, including abnormalities such as IDH-mutation status and 1p19q deletion. This approach is effective but does not generalize to tumor types that lack highly recurrent alterations. Tumors have intrinsic DNA methylation patterns and can be grouped into stable methylation classes even when lacking recurrent mutations or copy number changes. The purpose of this study was to prove the principle that a tumor's DNA-methylation class could be used as a predictive feature for radiogenomic modeling. Using a custom DNA methylation-based classification model, molecular classes were assigned to diffuse gliomas in The Cancer Genome Atlas (TCGA) dataset. We then constructed and validated machine learning models to predict a tumor's methylation family or subclass from matched multisequence MRI data using either extracted radiomic features or directly from MRI images. For models using extracted radiomic features, we demonstrated top accuracies above 90% for predicting IDH-glioma and GBM-IDHwt methylation families, IDH-mutant tumor methylation subclasses, or GBM-IDHwt molecular subclasses. Classification models utilizing MRI images directly demonstrated average accuracies of 80.6% for predicting methylation families, compared to 87.2% and 89.0% for differentiating IDH-mutated astrocytomas from oligodendrogliomas and glioblastoma molecular subclasses, respectively. These findings demonstrate that MRI-based machine learning models can effectively predict the methylation class of brain tumors. Given appropriate datasets, this approach could generalize to most brain tumor types, expanding the number and types of tumors that could be used to develop radiomic or radiogenomic models.

DNA methylation in human gastric epithelial cells defines regional identity without restricting lineage plasticity

BackgroundEpigenetic modifications in mammalian DNA are commonly manifested by DNA methylation. In the stomach, altered DNA methylation patterns have been observed following chronic Helicobacter pylori infections and in gastric cancer. In the context of epigenetic regulation, the regional nature of the stomach has been rarely considered in detail.ResultsHere, we establish gastric mucosa derived primary cell cultures as a reliable source of native human epithelium. We describe the DNA methylation landscape across the phenotypically different regions of the healthy human stomach, i.e., antrum, corpus, fundus together with the corresponding transcriptomes. We show that stable regional DNA methylation differences translate to a limited extent into regulation of the transcriptomic phenotype, indicating a largely permissive epigenetic regulation. We identify a small number of transcription factors with novel region-specific activity and likely epigenetic impact in the stomach, including GATA4, IRX5, IRX2, PDX1 and CDX2. Detailed analysis of the Wnt pathway reveals differential regulation along the craniocaudal axis, which involves non-canonical Wnt signaling in determining cell fate in the proximal stomach. By extending our analysis to pre-neoplastic lesions and gastric cancers, we conclude that epigenetic dysregulation characterizes intestinal metaplasia as a founding basis for functional changes in gastric cancer. We present insights into the dynamics of DNA methylation across anatomical regions of the healthy stomach and patterns of its change in disease. Finally, our study provides a well-defined resource of regional stomach transcription and epigenetics.

Abstract A011: Epigenetic vulnerabilities in patient-derived colorectal cancer organoids

Abstract Colorectal cancer (CRC) is a major cause of cancer-related deaths worldwide. Here, we established human patient-derived colorectal cancer organoid cultures (PDOs) to decipher the patient-specific DNA methylation profile and drug sensitivity towards 5-aza-2’-deoxycytidine, a DNA methyltransferase inhibitor. Organoid lines (n=15) were generated from adjacent normal mucosa and tumor tissue located in different anatomical sites of the colon and rectum. The derived PDOs were characterized on a histopathological level and reproduced the grade and differentiation capacity of their parental tumors. Additional genotypic profiling of PDOs showed a high degree of similarity to the original patient tumors. However, the stability of the DNA methylation landscape of human cancer organoids remains largely unknown. In genome-wide methylation analysis of long-term organoid cultures (up to 6 months in culture), we observed surprisingly stable methylation signatures that recapitulates the patient’s profile whilst demonstrating the vast intertumoral heterogeneity among patients. Strikingly, we identified a tumor-specific methylation signature that consisted of 39 CpG sites, which were unmethylated in normal epithelial cells but highly (91-96%) methylated in all tumor cells analyzed. This signature allows for the estimation of the percentage of tumor content in resected tissues and might represent potent biomarkers for early CRC diagnostics. Notably, it has been demonstrated that PDOs have the potential to predict clinical outcome and response to chemo- and radiation therapy in patients. Herein, drug screening with 5-aza-2’-deoxycytidine revealed heterogeneous responses and a clustering into drug sensitive, median and resistant organoid lines. ATAC- and RNA-seq analyses identified pathways rendering drug sensitivity and resistance. Our findings highlight the utility of PDOs as an advanced model system to study the role of the epigenome, especially DNA methylation, and its impact on tumor burden and vulnerability towards epigenetic modifiers. Citation Format: Loan Tran, Raheleh Sheibani Tezerji, Carlos Uziel Perez Malla, Anna Malzer, Ajna Logo, Katarina Misura, Theresia Mair, Thomas Dillinger, Madeleine Kuroll, Velina Atanasova, Julijan Kabiljo, Helga Schachner, Katharina Wöran, Judith Stift, Helmut Dolznig, Walter Pulverer, Michael Bergmann, Gerda Egger. Epigenetic vulnerabilities in patient-derived colorectal cancer organoids. [abstract]. In: Proceedings of the AACR Special Conference: Cancer Epigenomics; 2022 Oct 6-8; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2022;82(23 Suppl_2):Abstract nr A011.

Epigenetic Alterations of Repeated Relapses in Patient-matched Childhood Ependymomas

Recurrence is frequent in pediatric ependymoma (EPN). Our longitudinal integrated analysis of 30 patient-matched repeated relapses (3.67 ± 1.76 times) over 13 years (5.8 ± 3.8) reveals stable molecular subtypes (RELA and PFA) and convergent DNA methylation reprogramming during serial relapses accompanied by increased orthotopic patient derived xenograft (PDX) (13/27) formation in the late recurrences. A set of differentially methylated CpGs (DMCs) and DNA methylation regions (DMRs) are found to persist in primary and relapse tumors (potential driver DMCs) and are acquired exclusively in the relapses (potential booster DMCs). Integrating with RNAseq reveals differentially expressed genes regulated by potential driver DMRs (CACNA1H, SLC12A7, RARA in RELA and HSPB8, GMPR, ITGB4 in PFA) and potential booster DMRs (PLEKHG1 in RELA and NOTCH, EPHA2, SUFU, FOXJ1 in PFA tumors). DMCs predicators of relapse are also identified in the primary tumors. This study provides a high-resolution epigenetic roadmap of serial EPN relapses and 13 orthotopic PDX models to facilitate biological and preclinical studies.

Stable methylation loci are associated with systolic blood pressure in a Croatian island population.

Background: The objective was to identify stable and dynamic DNA methylation loci associated with cardiometabolic traits among an adult population from the Croatian island of Hvar. Materials & methods: An epigenome-wide association study was conducted using peripheral blood longitudinally collected at two time points 10years apart via Infinium MethylationEPIC beadarray (n=112). Stable and dynamic loci were identified using linear mixed models. Associations between cardiometabolic traits and loci were assessed using linear models. Results: 22 CpG loci were significantly associated with systolic blood pressure. Twenty were stable and two were dynamic. Conclusion: Multiple genes may be involved in the determination of systolic blood pressure levelvia stable epigenetic programming, potentially established earlier in life.

CRISPR/Cas9-mediated epigenetic editing tool: An optimized strategy for targeting de novo DNA methylation with stable status via homology directed repair pathway

With the development of epigenetic engineering tools for manipulating DNA methylation at the desired locus, the stable maintenance of targeted methylation status in edited cells after division poses a major obstacle. Transient methylation levels, along with the reversible inhibition of the desired genes, by some epigenetic editing techniques, limit their further application in functional and therapeutic studies of critical regulators in the cancer epigenome. In this study, we utilized CRISPR/Cas9-mediated the homology-directed repair (HDR) pathway following double-strand breaks (DSBs) information to target de novo methylation of the vital epigenetic biomarker, O6-methylguanine-DNA methyltransferase (MGMT). Based on synthetic single and double stranded methylated repair templates, DNA methylation patterns can be incorporated into the endogenous MGMT gene. In addition, we observed upregulation of DNA methyltransferases (DNMTs) in edited HeLa cells. In particular, we employed an optimized method of using the DNA ligase IV inhibitor SCR7 to markedly enhance the insertion efficiency induced by the long methylated repair template, contributing to the induction of stable methylation alterations through epigenetic recombination after cell division. Additionally, our study confirmed that CRISPR/Cas9-mediated target methylation in a site-specific manner enabled the maintenance of gene silencing in vitro and in vivo. Collectively, we show that a combination of CRISPR/Cas9 components, SCR7 treatment, and the long methylated HDR template can enhance CRISPR/Cas9-directed epigenomic editing efficiency and further induce stable effects on methylation modifications and transcriptional suppression.

Evaluating methylation of human ribosomal DNA at each CpG site reveals its utility for cancer detection using cell-free DNA.

Ribosomal deoxyribonucleic acid (DNA) (rDNA) repeats are tandemly located on five acrocentric chromosomes with up to hundreds of copies in the human genome. DNA methylation, the most well-studied epigenetic mechanism, has been characterized for most genomic regions across various biological contexts. However, rDNA methylation patterns remain largely unexplored due to the repetitive structure. In this study, we designed a specific mapping strategy to investigate rDNA methylation patterns at each CpG site across various physiological and pathological processes. We found that CpG sites on rDNA could be categorized into two types. One is within or adjacent to transcribed regions; the other is distal to transcribed regions. The former shows highly variable methylation levels across samples, while the latter shows stable high methylation levels in normal tissues but severe hypomethylation in tumors. We further showed that rDNA methylation profiles in plasma cell-free DNA could be used as a biomarker for cancer detection. It shows good performances on public datasets, including colorectal cancer [area under the curve (AUC) = 0.85], lung cancer (AUC = 0.84), hepatocellular carcinoma (AUC = 0.91) and in-house generated hepatocellular carcinoma dataset (AUC = 0.96) even at low genome coverage (<1×). Taken together, these findings broaden our understanding of rDNA regulation and suggest the potential utility of rDNA methylation features as disease biomarkers.

Targeted analysis of sugar phosphates from glycolysis pathway by phosphate methylation with liquid chromatography coupled to tandem mass spectrometry

Monitoring the glycolysis pathway remains an analytical challenge as most metabolites involved are sugar phosphates. Structural similarity, instability, high polarity, and rich negative charges of sugar phosphates make LC-MS based analysis challenging. Here, we developed an improved workflow integrating uniformly 13C-labeled yeast metabolite extract, TiO2-based enrichment, differential stable isotope labeling phosphate methylation, porous graphic carbon column, and selected reaction monitoring acquisition. Uniformly 13C labeled yeast metabolite extract was used as internal standards while differential stable isotope labeled sugar phosphates worked as calibrants. The established method was validated in human plasma, platelet and cultured HeLa cells. The limits of quantification ranged between 0.25 and 0.54 pmol on column. The method was adapted and its applicability tested for human platelets in which activation with collagen-related peptide (CRP) clearly showed the upregulation of some SPx metabolites. The results document that this newly established method can be successfully used to monitor glycolysis in different biological samples. As an extension, more phosphorylated and carboxylated metabolites from the central carbon metabolism (pentose phosphate cycle, TCA cycle) were tested as well. This method showed superior performance, especially for multiple phosphorylated and carboxylated metabolites. For quantitative purpose, the concept of SPx in three sets (12C-analytes, U-13C-IS, deuterated calibrants) has the potential to be adapted for more anionic metabolites.