Effects of HIST1H2ac knockdown on the DNA methylation landscape of breast cancer cell line MCF-7
Ontology highlight
ABSTRACT:
INSTRUMENT(S): Illumina HiSeq 2000
ORGANISM(S): Homo sapiens
SUBMITTER: Ming-Ta Hsu
PROVIDER: E-MTAB-3320 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
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Project description:To improve our understanding of the effect of differential methylation on gene expression between normal and tumor breast cells, we employed high-throughput sequencing technology to determine and compare CpG methylation of normal breast and four breast tumor genomes at single-base resolution. By comparing the methylation profiles between normal and tumor, we identified large hypomethylated zones in associated with large tissue-specific genes and gene deserts. We identified small hypomethylated regions in the methylomes and termed these sites as unmethylated islands (UMI). The UMI are highly correlated with positive regulatory chromatin marks and exhibit differential methylation mainly at the island shores. Our analysis showed there is a complex relationship between genome-wide promoter differential methylation and gene expression. Four other data sets from this study were also deposited at ArrayExpress under accession numbers E-MTAB-1935, E-MTAB-1952, E-MTAB-1958 and E-MTAB-1961.
2015-02-25 | E-MTAB-2014 | biostudies-arrayexpress
Project description:The goal of this study is to identify the DNA methylation changes caused by exposure of to the DNMT inhibitor 5-aza-2â-deoxycytidine (5Aza) and HDAC inhibitor Trichostatin A (TSA). We performed whole-genome bisulfite sequencing of the drug-treated MCF7 breast cancer cell lines and compare their DNA methylation profile with the untreated MCF7 (see E-MTAB-2014). While MCF7 treated with both drugs experienced global loss of DNA methylation, the 5Aza induced stronger demethylation than TSA.
2016-06-30 | E-MTAB-3785 | biostudies-arrayexpress
Project description:This study was undertaken to identify novel tumour suppressor genes in lung adenocarcinoma. EYA4, located at 6q23.2 was identified as a frequently lost and hypermethylated gene in the analyzed samples. EYA4 is underexpressed in addition to being deleted and hypermethylated. Control of EYA4 expression by DNA methylation was assessed using 5'-azacytidine. The role of EYA4 in apoptosis was assessed using a stable knock down of the gene which was assessed for apoptotis using FACS and qPCR. Methylation profiling: 30 adenocarcinoma samples and 30 patient-matched non-malignant lung samples are included. Non-malignant samples were used as references to identify hypermethylated probes. For each normal/tumor pair, the sample numbers are paired but offset by one with the tumor being the lower of the two numbers. For example, 85040001 is the adenocarcinoma tumor profile that pairs with non-malignant 85040002. Genome variation (aCGH) profiling: 30 adenocarcinoma gene dosage profiles are included. Values presented are log2 ratios of Cy3(sample)/Cy5(diploid reference)
2014-02-25 | E-GEOD-19034 | biostudies-arrayexpress
Project description:A Cartes d'Identite des Tumeurs (CIT) project from the french Ligue Nationale Contre le Cancer (http://cit.ligue-cancer.net) | Transcriptome analysis led to the unsupervised classification of carcinomas in two groups, associated with different outcomes {de Reynies, 2009 ; Giordano, 2009}. Subsequently, we have shown that unsupervised clustering further classified the tumors of the poor prognosis group in three different subgroups, two of them harbouring a cardinal molecular alteration {Ragazzon, 2010}. One is associated with p53 inactivation, the second with ?-catenin activation. No molecular defect has been identified in the third group so far. The aim is to describe the genome-wide methylome of adrenocortical tumors, and to assess the link with previously established molecular classifications. Experimental design: Genome-wide methylation patterns of 84 adenomas and 51 carcinomas were obtained with the Infinium HumanMethylation27 beadchip (Illumina). | Submitter : Olivia Barreau <olivia.barreau@inserm.fr> | Project leader : Jerome Bertherat <jerome.bertherat@inserm.fr>
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2014-01-06 | E-GEOD-44806 | biostudies-arrayexpress
Project description:Extensive changes in DNA methylation are common in cancer and may contribute to oncogenesis through transcriptional silencing of tumor suppressor genes. Genome-scale studies have yielded important insights into these changes, but have focused on CpG islands or gene promoters. We used whole-genome bisulfite sequencing (Bisulfite-Seq) to comprehensively profile a primary human colorectal tumor and adjacent-normal colon tissue at single-basepair resolution. Regions of focal hypermethylation in the tumor were located primarily at CpG islands and were concentrated within regions of long-range (>100 kb) hypomethylation. These hypomethylated domains covered nearly half the genome and coincided with late replication and attachment to the nuclear lamina in human cell lines. The confluence of hypermethylation and hypomethylation within these domains was confirmed in 25 diverse colorectal tumors with matched adjacent tissue. We propose that widespread DNA methylation changes in cancer are linked to silencing programs orchestrated by the 3D organization of chromatin within the nucleus. dbGAP study: phs000385 Primary tissue samples sequenced using 76-bp bisulfite sequencing (WGBS or Methyl-seq) using the Illumina GAII platform. Two independent libraries were constructed for each sample, and these libraries were combined into a single data file for each sample.
2011-09-26 | E-GEOD-32399 | biostudies-arrayexpress
Project description:The samples were collected from the participants of the Finnish Diabetes Prediction and Prevention (DIPP) Study, born between 1995 and 2006. DIPP is a prospective follow-up cohort of children with a moderate or high risk of type 1 diabetes, based on the HLA-DR-DQ genotype. Islet cell autoantibodies (ICA, GADA, IAA, IA2A and ZnT8A) were measured 1 - 4 times per year until age 15 or year 2018. The aim was to study associations between perinatal DNA methylation marks and later progression to type 1 diabetes. Case individuals who became persistently positive for at least two biochemical autoantibodies (GADA, IAA, IA2A or ZnT8A) and/or were diagnosed with type 1 diabetes during the follow-up were compared to the control individuals who remained autoantibody-negative throughout the follow-up. These data were also used in the development of data analysis methodology in bisulfite sequencing studies. To protect the privacy of the study participants, the sequence read data are not publicly available. However, the processed data can be downloaded here. These include two count matrices: \\"methylated_reads\\" and \\"total_reads\\". The matrix \\"methylated_reads\\" contains methylated read counts at each high-coverage CpG site (altogether approximately 2.5 million rows) at each of the 173 samples (173 columns), and the matrix \\"total_reads\\" contains the corresponding total read counts (coverage). Please notice that the methylated read counts are read counts, not percentages. Methylation proportions can be calculated as methylated_reads/total_reads. The row names are the genomic locations of these CpG sites in hg19 (GRCh37) coordinates (1,2). For privacy reasons, all potential SNPs were excluded from these publicly available count matrices. Specifically, we removed all common (minor allele frequency > 1 %) human SNPs, as listed in dbSNP (3). We also removed all SNPs that were detected in one or more samples even with \\"low\\" evidence by BS-SNPer, which is a software for detecting SNPs from bisulfite sequencing data (4). Altogether 204443 out of 2752981 rows were removed from the original coverage-filtered count matrices that were analyzed in the present study. Description of the sample attributes: Individual: The individual-specific identifiers, such as “Subject1”. Since each sample is from a different individual, these correspond to the sample identifiers (Subject1 == Sample 1 etc.) Experimental Group: The variable of interest (called \\"class\\" in the associated publications) with three possible values: 1) case, 2) control and 3) NA (neither case nor control). 1) Case: became persistently positive for at least two biochemical autoantibodies (GADA, IAA, IA2A or ZnT8A) and/or diagnosed with type 1 diabetes during the follow-up. 2) Control: remained autoantibody-negative throughout the follow-up. 3) NA: The remaining 51 individuals with a missing value (“NA”) did not qualify as cases or controls, since they were either persistently positive for only 1 biochemical autoantibody or transiently positive for one or more autoantibodies. We excluded these 51 individuals from the case-control-comparison but included them in the comparison between the sexes. Library preparation batch: The sequencing libraries were prepared in 7 batches. The names of the batches do not have any special meaning. That is, \\"1A\\" is not necessarily more similar to \\"1B\\" than it is to \\"3B\\". We treated this as a categorical technical variable with 7 categories. PC1 and PC2: Projections of the sample-specific methylation proportion vectors on the first two orthonormal principal components. The principal component analysis (PCA) was performed on the original coverage-filtered methylation proportion matrix (methylated/total reads), where missing values at each CpG site were imputed by the median over samples with non-missing values. The original methylation proportion matrix included 2752981 rows, whereas these publicly available matrices include 2548538 rows (all potential SNPs excluded). Hence, PCA on the publicly available data would result in slightly different values for PC1 and PC2. We included these as covariates in the differential methylation analysis to represent technical variation (in addition to the library preparation batches). References 1. Church DM, Schneider VA, Graves T, Auger K, Cunningham F, Bouk N, et al. Modernizing reference genome assemblies. PLoS Biol. 2011 Jul;9(7):e1001091. 2. Genome Reference Consortium. NCBI downloads: https://hgdownload.soe.ucsc.edu/goldenPath/hg19/bigZips/hg19.fa.gz, accessed Feb 10th, 2019 3. NCBI. dbSNP: https://ftp.ncbi.nih.gov/snp/organisms/human_9606_b151_GRCh37p13/VCF/common_all_20180423.vcf.gz, accessed April 29th, 2021 4. Gao S, Zou D, Mao L, Liu H, Song P, Chen Y, et al. BS-SNPer: SNP calling in bisulfite-seq data. Bioinformatics. 2015 Dec 15;31(24):4006–8.
2022-06-06 | E-MTAB-10530 | biostudies-arrayexpress
Project description:Pathologic differentiation of tissue of origin in tumors found in the lung can be challenging, with differentiation of mesothelioma and lung adenocarcinoma emblematic of this problem. Indeed, proper classification is essential for determination of treatment regimen for these diseases, making accurate and early diagnosis critical. Here we investigate the potential of epigenetic profiles of lung adenocarcinoma, mesothelioma, and non-malignant pulmonary tissues (n=285) as differentiation markers in an analysis of DNA methylation at 1413 autosomal CpG loci associated with 773 cancer-related genes. Using an unsupervised recursively-partitioned mixture modeling technique for all samples, the derived methylation profile classes were significantly associated with sample type (P < 0.0001). In a similar analysis restricted to tumors, methylation profile classes significantly predicted tumor type (P < 0.0001). Random forests classification of CpG methylation of tumors - which splits the data into training and test sets - accurately differentiated MPM from lung adenocarcinoma over 99% of the time (P < 0.0001). In a locus-by-locus comparison of CpG methylation between tumor types, 1266 CpG loci had significantly different methylation between tumors following correction for multiple comparisons (Q < 0.05); 61% had higher methylation in adenocarcinoma. Using the CpG loci with significant differential methylation in a pathways analysis revealed significant enrichment of methylated gene-loci in Cell Cycle Regulation, DNA Damage Response, PTEN Signaling, and Apoptosis Signaling pathways in lung adenocarcinoma when compared to mesothelioma. Methylation-profile-based differentiation of lung adenocarcinoma and mesothelioma is highly accurate, informs on the distinct etiologies of these diseases, and holds promise for clinical application. Mesotheliomas (n=158) and grossly non-tumorigenic parietal pleura (n=18) were obtained following surgical resection at Brigham and Womenâ??s Hospital through the International Mesothelioma Program from a pilot study conducted in 2002 (n=70) and an incident case series beginning in 2005 (n=88) with a participation rate of 85%. We used biopsy specimens from patients treated for NSCLC at the Massachusetts General Hospital from 1992 â?? 1996 (18) including lung adenocarcinomas (n=57) and non-malignant pulmonary tissues (n=48) (of which 22 (39%) were taken from the adenocarcinoma patients) (18). Additional normal lung tissues were obtained from the National Disease Research Interchange from donors free of lung malignancy (n=4).
2010-06-25 | E-GEOD-16559 | biostudies-arrayexpress
Project description:Integrated profiling of somatic molecular alterations present in tumors is necessary to further our understanding of the tumorigenic process. We investigated the potential relationships between gene copy number alterations and DNA methylation profiles in a case series of pleural mesotheliomas (n=23). Gene copy number (CN) alterations profiled with 500K SNP arrays and DNA methylation measured at over 750 cancer-related genes with methylation bead-arrays were examined concomitantly. Considering each probed locus, there were no instances of significantly correlated CN alteration and methylation (no loci with Q < 0.05) and averaging loci over their associated genes revealed only two genes with significantly correlated CN and methylation alterations (Q < 0.04). In contrast to the lack of discrete correlations, the overall extent of tumor CN alteration was significantly associated with DNA methylation profile when comparing CN alteration extent among methylation profile classes (P < 0.02), and there was evidence that this association was partially attributable to prevalent allele loss observed at the maintenance DNA methyltransferase DNMT1. Taken together, this work indicates a strong association between global genetic and global epigenetic dysregulation in mesothelioma rather than a discrete, local coordination of gene inactivation, and further highlights the utility and necessity of integrative genomics approaches in cancer biology. Mesotheliomas were obtained following surgical resection at Brigham and Women’s Hospital through the International Mesothelioma Program from a pilot study conducted in 2002 and an incident case series beginning in 2005 as previously described (PMIDs: 19118007 and 19638575). All patients provided informed consent under the approval of the appropriate Institutional Review Boards. Clinical information, including histologic diagnosis was obtained from pathology reports. The study pathologist confirmed the histologic diagnoses and further assessed the percent tumor from resected specimens (mean >60%). DNA extraction and methylation analysis: DNA from fresh frozen tissue and matched whole blood was isolated with QIAamp DNA mini kit (Qiagen, Valencia, CA) following the manufacturer’s protocol. Tumor DNA was modified with sodium bisulfite using the EZ DNA Methylation Kit (Zymo Research, Orange, CA). Illumina GoldenGate® methylation bead arrays interrogated 1505 CpG loci associated with 803 cancer-related genes processed at the UCSF Institute for Human Genetics, Genomics Core Facility using methods described in (28). The GoldenGate methylation data used in the analysis has been previously described (PMIDs: 19118007 and 19638575).
2010-07-01 | E-GEOD-20989 | biostudies-arrayexpress
Project description:DNA methylation is an important epigenetic regulator of gene expression. Recent studies have revealed widespread associations between genetic variation and methylation levels. However, the mechanistic links between genetic variation and methylation remain unclear. To begin addressing this gap, we collected methylation data at ~300,000 loci in lymphoblastoid cell lines (LCLs) from 64 HapMap Yoruba individuals, and genome-wide bisulfite sequence data in ten of these individuals. We identified (at an FDR of 10%) 13,915 *cis* methylation QTLs (meQTLs), i.e., CpG sites in which changes in DNA methylation are associated with genetic variation at proximal loci. We found that meQTLs are frequently associated with changes in methylation at multiple CpGs across regions of up to 3 kb. Interestingly, meQTLs are also frequently associated with variation in other properties of gene regulation, including histone modifications, DNase I accessibility, chromatin accessibility, and expression levels of nearby genes. These observations suggest that genetic variants may lead to coordinated molecular changes in all of these regulatory phenotypes. One plausible driver of coordinated changes in different regulatory mechanisms is variation in transcription factor (TF) binding. Indeed, we found that SNPs that change predicted TF binding affinities are significantly enriched for associations with DNA methylation at nearby CpGs. Whole genomic DNA from 10 Yoruba HapMap individuals and spiked in unmethylated lambda phage DNA was bisuflite converted using the Invitrogen MethylCode Bisulfite Conversion Kit and sequenced using a Illumina HiSeq 2000
2014-05-09 | E-GEOD-57471 | biostudies-arrayexpress