Vestibular Schwannoma Clinical Phenotypes Are Associated with Differential Methylation Patterns

2020 ◽  
Author(s):  
Avital Perry ◽  
Christopher S. Graffeo ◽  
Lucas P. Carlstrom ◽  
Amanda Munoz Casabella ◽  
Matthew L. Carlson ◽  
...  
Keyword(s):  
Vestibular Schwannoma ◽  
Differential Methylation ◽  
Clinical Phenotypes ◽  
Methylation Patterns

Genome-Wide DNA Methylation Analysis Shows Enrichment of Differential Methylation in “Open Seas” and Enhancers and Reveals Hypomethylation in DNMT3A Mutated Cytogenetically Normal AML (CN-AML)

Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 653-653 ◽  
Author(s):  
Ying Qu ◽  
Andreas Lennartsson ◽  
Verena I. Gaidzik ◽  
Stefan Deneberg ◽  
Sofia Bengtzén ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Cpg Island ◽  
Cpg Islands ◽  
Differential Methylation ◽  
Methylation Analysis ◽  
Cpg Sites ◽  
Genome Wide ◽  
Genomic Regions ◽  
Methylation Patterns

Abstract Abstract 653 DNA methylation is involved in multiple biologic processes including normal cell differentiation and tumorigenesis. In AML, methylation patterns have been shown to differ significantly from normal hematopoietic cells. Most studies of DNA methylation in AML have previously focused on CpG islands within the promoter of genes, representing only a very small proportion of the DNA methylome. In this study, we performed genome-wide methylation analysis of 62 AML patients with CN-AML and CD34 positive cells from healthy controls by Illumina HumanMethylation450K Array covering 450.000 CpG sites in CpG islands as well as genomic regions far from CpG islands. Differentially methylated CpG sites (DMS) between CN-AML and normal hematopoietic cells were calculated and the most significant enrichment of DMS was found in regions more than 4kb from CpG Islands, in the so called open sea where hypomethylation was the dominant form of aberrant methylation. In contrast, CpG islands were not enriched for DMS and DMS in CpG islands were dominated by hypermethylation. DMS successively further away from CpG islands in CpG island shores (up to 2kb from CpG Island) and shelves (from 2kb to 4kb from Island) showed increasing degree of hypomethylation in AML cells. Among regions defined by their relation to gene structures, CpG dinucleotide located in theoretic enhancers were found to be the most enriched for DMS (Chi χ2<0.0001) with the majority of DMS showing decreased methylation compared to CD34 normal controls. To address the relation to gene expression, GEP (gene expression profiling) by microarray was carried out on 32 of the CN-AML patients. Totally, 339723 CpG sites covering 18879 genes were addressed on both platforms. CpG methylation in CpG islands showed the most pronounced anti-correlation (spearman ρ =-0.4145) with gene expression level, followed by CpG island shores (mean spearman rho for both sides' shore ρ=-0.2350). As transcription factors (TFs) have shown to be crucial for AML development, we especially studied differential methylation of an unbiased selection of 1638 TFs. The most enriched differential methylation between CN-AML and normal CD34 positive cells were found in TFs known to be involved in hematopoiesis and with Wilms tumor protein-1 (WT1), activator protein 1 (AP-1) and runt-related transcription factor 1 (RUNX1) being the most differentially methylated TFs. The differential methylation in WT 1 and RUNX1 was located in intragenic regions which were confirmed by pyro-sequencing. AML cases were characterized with respect to mutations in FLT3, NPM1, IDH1, IDH2 and DNMT3A. Correlation analysis between genome wide methylation patterns and mutational status showed statistically significant hypomethylation of CpG Island (p<0.0001) and to a lesser extent CpG island shores (p<0.001) and the presence of DNMT3A mutations. This links DNMT3A mutations for the first time to a hypomethylated phenotype. Further analyses correlating methylation patterns to other clinical data such as clinical outcome are ongoing. In conclusion, our study revealed that non-CpG island regions and in particular enhancers are the most aberrantly methylated genomic regions in AML and that WT 1 and RUNX1 are the most differentially methylated TFs. Furthermore, our data suggests a hypomethylated phenotype in DNMT3A mutated AML. Disclosures: No relevant conflicts of interest to declare.

Epigenetic Deregulation In Relapsed Acute Myeloid Leukemia

Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 2499-2499 ◽  
Author(s):  
Francine E. Garrett-Bakelman ◽  
Sheng Li ◽  
Todd Hricik ◽  
Stephen S. Chung ◽  
Haim Bar ◽  
...  
Keyword(s):  
Myeloid Leukemia ◽  
Cytosine Methylation ◽  
Somatic Mutations ◽  
Cpg Islands ◽  
Differential Methylation ◽  
Exome Capture ◽  
Gene Promoters ◽  
Disease Relapse ◽  
Methylation Patterns ◽  
Epigenetic Plasticity

Abstract Treatment failure in Acute Myeloid Leukemia (AML) is attributed in many cases to relapsed disease. Relapsed AML is a fundamental clinical challenge since most patients have poor clinical outcomes. The exact biological basis of AML relapse remains unclear. Genetic clonal evolution is widely believed to underlie the emergence of chemotherapy resistant clones. However, only limited, predominantly non-overlapping, somatic mutations and copy number aberrations were found to occur upon AML relapse. Furthermore, in a subset of cases, no relapse specific somatic mutations or copy number aberrations were identified. This suggests a role for other mechanisms in relapsed AML. We hypothesize that epigenetic plasticity and deregulation contributes to the pathogenesis of relapse in AML. To explore this notion, we performed a genome scale epigenetic and genetic analysis of thirty-nine paired diagnosis and relapsed AML human patient samples using exome capture, RNA-seq and ERRBS for DNA methylation sequencing. Exome capture was performed on each patient’s germline DNA as well. Exome capture revealed only a limited number of known recurrent somatic mutations acquired upon disease relapse, in agreement with previous reports. In contrast, upon disease relapse we identified thousands of statistically significant changes in cytosine methylation patterns. Globally, the majority of patients (85%) displayed striking predominance of DNA hypermethylation (p= 1.00433e-05, binomial test for equality of proportions) upon disease relapse. Notably a smaller set of patients displayed the opposite epigenetic phenotype with prominent loss of cytosine methylation. While differential methylation in the hypermethylated group of patients localized predominantly to CpG islands, the majority of differential methylation in the hypomethylated group localized to regions lacking both CpG islands and shores. In spite of these two distinct overall cytosine methylation patterns, the majority of differentially methylated cytosines are located in intergenic regions in all cases, and a subset of promoters were hypermethylated in almost all patients at relapse. A pathway analysis indicated that the commonly hypermethylated gene promoters at relapse are involved in the Hedghog, Wnt and calcium signaling pathways (p<0.05, modified Fisher Exact test). Integration of these findings with mutational and transcriptional profiles is underway. In order to determine whether epigenetic events linked to AML relapse could be modeled experimentally we performed a pilot study of a human AML xenograft in immunocompromised mice. Engrafted mice were treated with Ara-C at a clinically relevant dose (60mg/Kg; n=2) or vehicle alone (n=3) for five consecutive days. Human AML cells were collected at various timepoints including 28 days after Ara-C treatment where the AML had frankly relapsed in mice. Cytosine methylation profiles obtained through ERRBS revealed predominantly hypermethylated cytosines when compared to the xenotransplanted diagnostic sample (72% hypermethylated versus 28% hypomethylated). Remarkably, there was a strong overlap with gene promoters that are also aberrantly methylated in relapsed AML patients (p<0.01, hypergeometric test), including members of the Wnt signaling pathway. We conclude that there are epigenetically distinct forms of relapsed AML. Nonetheless, there is convergent epigenetic regulation of specific gene pathways that may contribute to relapsed AML pathogenesis and xenotransplanted AML mice can serve as experimental models for further study. Finally, the genomic distribution of reprogrammed methylation suggests a role for epigenetic plasticity at distal regulatory elements. Whereas it remains unclear whether these changes represent clonal selection, their extensive and dynamic range suggest that exposure to chemotherapy may alter the fidelity of mechanisms that control cytosine methylation distribution thus permitting widespread and distant epigenetic reprogramming and contributing to disease relapse. Disclosures: No relevant conflicts of interest to declare.

Genome-Wide Methylation Analysis of Patients with Diffuse Large B Cell Lymphoma Treated on the UK NCRI R-CHOP 14 Vs 21 Trial

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 1747-1747
Author(s):  
Andrea Kühnl ◽  
Ridwan Shaikh ◽  
David Cunningham ◽  
Sharon L Barrans ◽  
Cathy H Burton ◽  
...  
Keyword(s):  
Research Funding ◽  
Cpg Islands ◽  
Prospective Trial ◽  
B Cell Lymphoma ◽  
Differential Methylation ◽  
Cell Of Origin ◽  
Promoter Regions ◽  
Epigenetic Modifiers ◽  
The Uk ◽  
Methylation Patterns

Abstract Background: Epigenetic alterations are a hallmark of diffuse large B cell lymphoma (DLBCL). A high degree of methylation disruption and intra-tumor methylation heterogeneity have been linked to poor outcome in DLBCL. However, high-coverage methylation data within prospective trial cohorts are warranted to characterize clinically relevant methylation subgroups of DLBCL. Here, we investigate the methylome of DLBCL cases from a large multicentre Phase III trial and its interaction with clinical and molecular characteristics. Methods: DNA methylation was assessed with the Illumina Infinium 450k array in archived FFPE samples of 127 newly diagnosed DLBCL patients treated with R-CHOP chemotherapy on the UK NCRI R-CHOP14v21 trial. Status of BCL2-, BCL6-, and MYC-rearrangements and amplifications was available for 111 cases. Cell-of-origin classification was available for all cases, both according to the IHC Hans algorithm and the microarray-based classification tool using Illumina DASL technology (Barrans, Br J Haematol 2012). In addition, microarray data was used to extract mean expression values of the epigenetic modifiers EZH2, MLL2, CREBBP, EP300, DNMT3A, IDH1/2 and TET2 and patients in the lowest and highest expression quartiles were compared. Analyses were performed in R 3.2.3 using the RnBeads package. Differential methylation was analyzed on region level (tiling, genes, promoters, CpG islands). P values were adjusted for multiple testing using the false discovery rate method. Results: After normalization and quality control 425,623 probes were included in the analysis. Median methylation levels of probes showed a bimodal distribution (unmethylated/methylated) across samples, with CpG islands and shores being mainly unmethylated, and CpG shelves and open seas being predominantly methylated. No significant association of clinical prognostic factors (age, LDH level, extranodal involvement, stage, WHO performance status) and methylation could be observed. We did not find significant differential methylation between patients who relapsed after R-CHOP therapy and those who did not. However, more detailed outcome analyses using Cox regression models for progression- and overall survival on single-site level will be provided at the meeting. There was no evidence for a difference in methylation with regards to rearrangements or amplifications of MYC or BCL6, nor with presence of double-hit abnormalities. Interestingly, cases with BCL2 rearrangement showed differential methylation of 39 promoter regions compared to cases without this abnormality (all adj. P<0.05). A strong impact on methylation patterns was seen with regards to microarray-based cell-of-origin categories (but not according to the IHC classifier). GCB vs. ABC cases showed global hypermethylation, predominantly affecting CpG islands and shores. 388 promoter regions were differentially methylated between GCB and ABC subtypes, corresponding to 226 annotated genes or miRNAs, the majority (93%) being hypermethylated in GCB cases. Differentially methylated promoter regions in GCB lymphomas were enriched for signal transduction and cell-cell communication pathway genes (adj. P<0.05) and included EZH2 target genes such as CDKN1A and SOX9. mRNA expression levels of epigenetic modifiers was not associated with significant differences in methylation, apart from DNMT3A expression. Patients with high vs. low DNMT3Aexpression showed differential methylation of 3300 promoters, which were significantly enriched for KRAS-associated genes (P=3.68E-12), cancer pathway genes (e.g. Wnt-, FGF- and hedgehog signalling; P=1.45E-08), as well as cytokine signalling genes (P=1.96E-09). Data on recurrent somatic mutations of epigenetic modifiers and correlation of methylation and mRNA expression will be provided at the meeting. Conclusions: The cell-of-origin as well as expression levels of DNMT3A are main drivers of methylation variability in DLBCL, whereas other molecular features like MYC seem to have little impact on methylation patterns. This comprehensive dataset of genome-wide methylation profiles from a prospective trial cohort provides important information for identifying biologically and clinically relevant epigenetic subgroups of DLBCL. Disclosures Cunningham: Amgen: Research Funding; Astra-Zeneca: Research Funding; Bayer: Research Funding; Celgene: Research Funding; Merrimack: Research Funding; Medimmune: Research Funding.

scholarly journals Gut Microbiota as an Epigenetic Regulator: Pilot Study Based on Whole-Genome Methylation Analysis

mBio ◽  
2014 ◽  
Vol 5 (6) ◽  
Author(s):  
Himanshu Kumar ◽  
Riikka Lund ◽  
Asta Laiho ◽  
Krista Lundelin ◽  
Ruth E. Ley ◽  
...  
Keyword(s):  
Lipid Metabolism ◽  
Gut Microbiota ◽  
Pregnant Women ◽  
Methylation Status ◽  
Differential Methylation ◽  
Gene Promoters ◽  
Dominant Group ◽  
Bacterial Phyla ◽  
Genome Methylation ◽  
Methylation Patterns

ABSTRACT The core human gut microbiota contributes to the developmental origin of diseases by modifying metabolic pathways. To evaluate the predominant microbiota as an epigenetic modifier, we classified 8 pregnant women into two groups based on their dominant microbiota, i.e., Bacteroidetes, Firmicutes, and Proteobacteria. Deep sequencing of DNA methylomes revealed a clear association between bacterial predominance and epigenetic profiles. The genes with differentially methylated promoters in the group in which Firmicutes was dominant were linked to risk of disease, predominantly to cardiovascular disease and specifically to lipid metabolism, obesity, and the inflammatory response. This is one of the first studies that highlights the association of the predominant bacterial phyla in the gut with methylation patterns. Further longitudinal and in-depth studies targeting individual microbial species or metabolites are recommended to give us a deeper insight into the molecular mechanism of such epigenetic modifications. IMPORTANCE Epigenetics encompasses genomic modifications that are due to environmental factors and do not affect the nucleotide sequence. The gut microbiota has an important role in human metabolism and could be a significant environmental factor affecting our epigenome. To investigate the association of gut microbiota with epigenetic changes, we assessed pregnant women and selected the participants based on their predominant gut microbiota for a study on their postpartum methylation profile. Intriguingly, we found that blood DNA methylation patterns were associated with gut microbiota profiles. The gut microbiota profiles, with either Firmicutes or Bacteroidetes as a dominant group, correlated with differential methylation status of gene promoters functionally associated with cardiovascular diseases. Furthermore, differential methylation of gene promoters linked to lipid metabolism and obesity was observed. For the first time, we report here a position of the predominant gut microbiota in epigenetic profiling, suggesting one potential mechanism in obesity with comorbidities, if proven in further in-depth studies.

scholarly journals An analytical pipeline for DNA Methylation Array Biomarker Studies

2021 ◽  
Author(s):  
Jennifer Lu ◽  
Darren Korbie ◽  
Matt Trau
Keyword(s):  
Dna Methylation ◽  
Feature Selection ◽  
Differential Methylation ◽  
The Cancer Genome Atlas ◽  
Methylation Array ◽  
Epigenetic Biomarkers ◽  
Cancer Genome Atlas ◽  
Dna Methylation Array ◽  
Methylation Patterns ◽  
Selection Of

DNA methylation is one of the most commonly studied epigenetic biomarkers, due to its role in disease and development. The Illumina Infinium methylation arrays still remains the most common method to interrogate methylation across the human genome, due to its capabilities of screening over 480, 000 loci simultaneously. As such, initiatives such as The Cancer Genome Atlas (TCGA) have utilized this technology to examine the methylation profile of over 20,000 cancer samples. There is a growing body of methods for pre-processing, normalisation and analysis of array-based DNA methylation data. However, the shape and sampling distribution of probe-wise methylation that could influence the way data should be examined was rarely discussed. Therefore, this article introduces a pipeline that predicts the shape and distribution of normalised methylation patterns prior to selection of the most optimal inferential statistics screen for differential methylation. Additionally, we put forward an alternative pipeline, which employed feature selection, and demonstrate its ability to select for biomarkers with outstanding differences in methylation, which does not require the predetermination of the shape or distribution of the data of interest. Availability: The Distribution test and the feature selection pipelines are available for download at: https://github.com/uqjlu8/DistributionTest Keywords: DNA methylation, Biomarkers, Cancers, Data Distribution, TCGA, 450K

scholarly journals Differential DNA methylation patterns of homeobox genes in proximal and distal colon epithelial cells

2016 ◽  
Vol 48 (4) ◽  
pp. 257-273 ◽  
Author(s):  
Alan Barnicle ◽  
Cathal Seoighe ◽  
Aaron Golden ◽  
John M. Greally ◽  
Laurence J. Egan
Keyword(s):  
Colorectal Cancer ◽  
Dna Methylation ◽  
Epithelial Cells ◽  
Distal Colon ◽  
Human Colon ◽  
Differential Methylation ◽  
Cell Type ◽  
Cell Type Specific ◽  
Inflammatory Bowel ◽  
Methylation Patterns

Region and cell-type specific differences in the molecular make up of colon epithelial cells have been reported. Those differences may underlie the region-specific characteristics of common colon epithelial diseases such as colorectal cancer and inflammatory bowel disease. DNA methylation is a cell-type specific epigenetic mark, essential for transcriptional regulation, silencing of repetitive DNA and genomic imprinting. Little is known about any region-specific variations in methylation patterns in human colon epithelial cells. Using purified epithelial cells and whole biopsies ( n = 19) from human subjects, we generated epigenome-wide DNA methylation data (using the HELP-tagging assay), comparing the methylation signatures of the proximal and distal colon. We identified a total of 125 differentially methylated sites (DMS) mapping to transcription start sites of protein-coding genes, most notably several members of the homeobox ( HOX) family of genes. Patterns of differential methylation were validated with MassArray EpiTYPER. We also examined DNA methylation in whole biopsies, applying a computational technique to deconvolve variation in methylation within cell types and variation in cell-type composition across biopsies. Including inferred epithelial proportions as a covariate in differential methylation analysis applied to the whole biopsies resulted in greater overlap with the results obtained from purified epithelial cells compared with when the covariate was not included. Results obtained from both approaches highlight region-specific methylation patterns of HOX genes in colonic epithelium. Regional variation in methylation patterns has implications for the study of diseases that exhibit regional expression patterns in the human colon, such as inflammatory bowel disease and colorectal cancer.

scholarly journals Hemimethylation of CpG dyads is characteristic of secondary DMRs associated with imprinted loci and correlates with 5-hydroxymethylcytosine at paternally methylated sequences

2019 ◽  
Vol 12 (1) ◽  
Author(s):  
Julianna Nechin ◽  
Emma Tunstall ◽  
Naideline Raymond ◽  
Nicole Hamagami ◽  
Chris Pathmanabhan ◽  
...  
Keyword(s):  
Methylation Status ◽  
Differential Methylation ◽  
Imprinted Genes ◽  
Differentially Methylated Regions ◽  
High Incidence ◽  
Sequence Elements ◽  
Parent Of Origin ◽  
Methylation Patterns ◽  
Post Implantation ◽  
Control Regions

Abstract Background In mammals, the regulation of imprinted genes is controlled by differential methylation at imprinting control regions which acquire parent of origin-specific methylation patterns during gametogenesis and retain differences in allelic methylation status throughout fertilization and subsequent somatic cell divisions. In addition, many imprinted genes acquire differential methylation during post-implantation development; these secondary differentially methylated regions appear necessary to maintain the imprinted expression state of individual genes. Despite the requirement for both types of differentially methylated sequence elements to achieve proper expression across imprinting clusters, methylation patterns are more labile at secondary differentially methylated regions. To understand the nature of this variability, we analyzed CpG dyad methylation patterns at both paternally and maternally methylated imprinted loci within multiple imprinting clusters. Results We determined that both paternally and maternally methylated secondary differentially methylated regions associated with imprinted genes display high levels of hemimethylation, 29–49%, in comparison to imprinting control regions which exhibited 8–12% hemimethylation. To explore how hemimethylation could arise, we assessed the differentially methylated regions for the presence of 5-hydroxymethylcytosine which could cause methylation to be lost via either passive and/or active demethylation mechanisms. We found enrichment of 5-hydroxymethylcytosine at paternally methylated secondary differentially methylated regions, but not at the maternally methylated sites we analyzed in this study. Conclusions We found high levels of hemimethylation to be a generalizable characteristic of secondary differentially methylated regions associated with imprinted genes. We propose that 5-hydroxymethylcytosine enrichment may be responsible for the variability in methylation status at paternally methylated secondary differentially methylated regions associated with imprinted genes. We further suggest that the high incidence of hemimethylation at secondary differentially methylated regions must be counteracted by continuous methylation acquisition at these loci.

scholarly journals HMM-Fisher: identifying differential methylation using a hidden Markov model and Fisher’s exact test

2016 ◽  
Vol 15 (1) ◽  
Author(s):  
Shuying Sun ◽  
Xiaoqing Yu
Keyword(s):  
Dna Methylation ◽  
Markov Model ◽  
Hidden Markov Model ◽  
Hidden Markov ◽  
Differential Methylation ◽  
Sequencing Data ◽  
Exact Test ◽  
Fisher's Exact Test ◽  
Fisher’S Exact Test ◽  
Methylation Patterns

AbstractDNA methylation is an epigenetic event that plays an important role in regulating gene expression. It is important to study DNA methylation, especially differential methylation patterns between two groups of samples (e.g. patients vs. normal individuals). With next generation sequencing technologies, it is now possible to identify differential methylation patterns by considering methylation at the single CG site level in an entire genome. However, it is challenging to analyze large and complex NGS data. In order to address this difficult question, we have developed a new statistical method using a hidden Markov model and Fisher’s exact test (HMM-Fisher) to identify differentially methylated cytosines and regions. We first use a hidden Markov chain to model the methylation signals to infer the methylation state as Not methylated (N), Partly methylated (P), and Fully methylated (F) for each individual sample. We then use Fisher’s exact test to identify differentially methylated CG sites. We show the HMM-Fisher method and compare it with commonly cited methods using both simulated data and real sequencing data. The results show that HMM-Fisher outperforms the current available methods to which we have compared. HMM-Fisher is efficient and robust in identifying heterogeneous DM regions.

DNA Methylation in Placentas of Interspecies Mouse Hybrids

Genetics ◽  
2003 ◽  
Vol 165 (1) ◽  
pp. 223-228
Author(s):  
Sabine Schütt ◽  
Andrea R Florl ◽  
Wei Shi ◽  
Myriam Hemberger ◽  
Annie Orth ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Molecular Basis ◽  
Interspecific Hybrids ◽  
Genetic System ◽  
Differential Methylation ◽  
Late Gestation ◽  
Epigenetic Changes ◽  
Repeat Sequences ◽  
Mouse Placenta ◽  
Methylation Patterns

Abstract Interspecific hybridization in the genus Mus results in several hybrid dysgenesis effects, such as male sterility and X-linked placental dysplasia (IHPD). The genetic or molecular basis for the placental phenotypes is at present not clear. However, an extremely complex genetic system that has been hypothesized to be caused by major epigenetic changes on the X chromosome has been shown to be active. We have investigated DNA methylation of several single genes, Atrx, Esx1, Mecp2, Pem, Psx1, Vbp1, Pou3f4, and Cdx2, and, in addition, of LINE-1 and IAP repeat sequences, in placentas and tissues of fetal day 18 mouse interspecific hybrids. Our results show some tendency toward hypomethylation in the late gestation mouse placenta. However, no differential methylation was observed in hyper- and hypoplastic hybrid placentas when compared with normal-sized littermate placentas or intraspecific Mus musculus placentas of the same developmental stage. Thus, our results strongly suggest that generalized changes in methylation patterns do not occur in trophoblast cells of such hybrids.

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