Project description:To improve our understanding of the relationships between methylation and expression we profiled mRNA expression and single-base resolution methylation levels for two breast cancer cell lines, MCF7 and T47D. Expression was profiled using RNA-seq. Methylation was assayed using Methyl-MAPS, which uses methylation-sensitive and -dependent restriction enzyme digests followed by high-throughput sequencing to identify methylation levels at individual CpGs (Edwards et al. 2010, Genome Research). DNA Methylation was assayed for two breast cancer cell lines using Methyl-MAPS.
Project description:To evaluate the methylation profiles of breast cell lines, we performed methylation profiling of 55 well-characterized breast cancer cell lines on the Illumina HumanMethylation27 (HM27) platform and made use of publicly available methylation profiles of primary breast tumors for comparison. The available annotation for each cell line includes estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) status, as well as the tumor type, and the age of each patient. Additionally, recent publications have described genome-wide mRNA expression profiles for most of these lines, and samples were classified on the basis of the expression profile into Basal A (BaA), Basal B/Claudin Low (BaB/CLDNlow) and Luminal (Lu) subtypes. Finally, GI50 has been calculated for these cell lines for 77 approved therapeutic agents. We find that the DNA methylation profiles of breast cancer cell lines largely retain the features that characterize primary tumors, although there are crucial differences as well. We assayed DNA methylation in 55 breast cancer cell lines. DNA extracted from breast cell lines was bisulfite treated and hybridized to Illumina HM27 arrays.
Project description:Aberrant DNA methylation is frequently observed in cancer. The aim of the study was to determine how is DNA methylation of miRNA genes changed in breast cancer cell lines an breast tumor specimens. Breast cancer cell lines vs. HMEC. Breast tumor tissue specimens vs. non-tumor tissue specimens. Biological replicates: 12 breast tumor specimens, 5 breast non-tumor specimens, 7 breast cancer cell lines, 3 HMEC genotypes, 3 HMF genotypes. Immunoprecipitation using anti-Methylcytosine (5MeC) antibody.
Project description:10 Breast cancer cell lines profiled on the Affymetrix U133 Plus 2.0 platform used in conjunction with matched DNA copy number and DNA methylation data for integrative analysis. In total, 10 samples were used. The MCF10A profile used as normal was obtained from GSM254525 and the remaining 2 cell lines were obtained from caBIG. Full RMA normalized expression profile is attached.
Project description:We used microarrays to detail the global programme of gene expression for MCF-7 and MDA-MB-231 and revealed the correlation between the methylation state of various genomic components and gene expression level. The expression analyses of the two breast cancer cell lines are a part of the whole study. The summary of our study is as follows: We establish a technique, called modified methylation-specific digital karyotyping (MMSDK) based on methylation-specific digital karyotyping (MSDK) with a novel sequencing approach. Briefly, after a tandem digestion of genomic DNA with a methylation-sensitive mapping enzyme and a fragmenting enzyme, short sequence tags are obtained. These tags are amplified, followed by direct, massively parallel sequencing (Solexa 1G Genome Analyzer). This method allows high-throughput and low-cost genome-wide DNA methylation mapping. We applied this method to investigate global DNA methylation profiles for widely used breast cancer cell lines, MCF-7 and MDA-MB-231, which are representatives for luminal-like and mesenchymal-like cancer types, respectively. By comparison, a highly similar overall DNA methylation pattern was revealed for the two cell lines. However a cohort of individual genomic loci with significantly different DNA methylation profile between two cell lines was identified. Furthermore, we revealed a genome-wide significant correlation between gene expression and the methylation status of gene promoters with CpG islands (CGIs) in the two cancer cell lines, and a correlation of gene expression and the methylation status of promoters without CGIs in MCF-7 cells. Experiment Overall Design: Breast cancer cell lines, MCF-7 and MDA-MB-231, were selected for the study of the impact of DNA methylation on gene expression regulation. Total RNA extraction was performed for both cell lines and hybridization was carried out using Affymetrix microarrays. We developed a modified methylation-specific digital karyotyping (MSDK) to obtain DNA methylation profiling genome wide. Then, we combined the analysis of DNA methylation data and gene expression data to reveal a correlation between epigenetic and transcriptional features genome wide.
Project description:Aberrant DNA methylation is frequently observed in cancer. The aim of the study was to determine how is DNA methylation of miRNA genes changed in breast cancer cell lines an breast tumor specimens.
Project description:To evaluate the methylation profiles of breast cell lines, we performed methylation profiling of 55 well-characterized breast cancer cell lines on the Illumina HumanMethylation27 (HM27) platform and made use of publicly available methylation profiles of primary breast tumors for comparison. The available annotation for each cell line includes estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) status, as well as the tumor type, and the age of each patient. Additionally, recent publications have described genome-wide mRNA expression profiles for most of these lines, and samples were classified on the basis of the expression profile into Basal A (BaA), Basal B/Claudin Low (BaB/CLDNlow) and Luminal (Lu) subtypes. Finally, GI50 has been calculated for these cell lines for 77 approved therapeutic agents. We find that the DNA methylation profiles of breast cancer cell lines largely retain the features that characterize primary tumors, although there are crucial differences as well.
Project description:We used deep sequencinge technology to profile the transcriptome, gene copy number, and CpG island methylation status simultaneously in eight commonly used breast cell lines to develop a model for how these genomic features are integrated in estrogen receptor positive (ER+) and negative breast cancer. Total mRNA sequence, gene copy number, and genomic CpG island methylation were carried out using the Illumina Genome Analyzer. Sequences were mapped to the human genome to obtain digitized gene expression data, DNA copy number in reference to the non-tumor cell line (MCF10A), and methylation status of 21,570 CpG islands to identify differentially expressed genes that were correlated with methylation or copy number changes. These were evaluated in a dataset from 129 primary breast tumors. Gene expression in cell lines was dominated by ER-associated genes. ER+ and ER- cell lines formed two distinct, stable clusters, and 1,873 genes were differentially expressed in the two groups. Part of chromosome 8 was deleted in all ER- cells and part of chromosome 17 amplified in all ER+ cells. These loci encoded 30 genes that were overexpressed in ER+ cells; 9 of these genes were overexpressed in ER+ tumors. We identified 149 differentially expressed genes that exhibited differential methylation of one or more CpG islands within 5kb of the 5' end of the gene and for which mRNA abundance was inversely correlated with CpG island methylation status. In primary tumors we identified 84 genes that appear to be robust components of the methylation signature that we identified in ER+ cell lines. Our analyses reveal a global pattern of differential CpG island methylation that contributes to the transcriptome landscape of ER+ and ER- breast cancer cells and tumors. The role of gene amplification/deletion appears to more modest, although several potentially significant genes appear to be regulated by copy number aberrations. 8 commonly used breast cancer cell lines were sequenced for mRNA expression, CpG methylation and DNA copy number