Dataset Information

Expression data from breast cancer cell lines (MCF-7 and MDA-MB-231)

ABSTRACT: 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. Keywords: genetic modification

ORGANISM(S): Homo sapiens

PROVIDER: GSE12199 | GEO | 2008/07/22

SECONDARY ACCESSION(S): PRJNA113423

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

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:Purpose: Development of resistance to tamoxifen is an important clinical issue in the treatment of patients with breast cancer. Tamoxifen resistance may be the result of the acquisition of epigenetic regulation such as DNA methylation within breast cancer cells resulting in changed mRNA expression of genes being pivotal for estrogen dependent growth. Alternatively, tamoxifen resistance may be due to selection of preexisting resistant cells, which may exhibit cancer stem-like characteristics or a combination of the two mechanisms. Methods: To evaluate the contribution of these possible mechanisms to tamoxifen resistance, we applied modified DNA methylation-specific digital karyotyping (MMSDK) and digital gene expression (DGE) in combination with massively parallel sequencing to analyze a well-established tamoxifen resistant cell line model: MCF-7/S0.5 (tamoxifen sensitive parental cell line) and 4 high-dosage tamoxifen selected resistant offspring sublines (MCF-7/TAMR-1, MCF-7/TAMR-4, MCF-7/TAMR-7 and MCF-7/TAMR-8). MMSDK uses BssHII as mapping enzyme (DNA methylation sensitive enzyme). Both MMSDK and DGE use NlaIII and MmeI to produce 20-21 bp tag. The indexed single-end sequencing was performed by Illumina HiSeq 2000 in BGI-Shenzhen. A dynamic programming algorithm-FASTX-Toolkit implemented in Perl was used to trim the adaptor sequence. The trimmed tags were subjected to quality filtering, so that only tags with sequencing quality higher than 30 for more than 80% of the nucleotides were used for subsequent analysis. For MMSDK tag mapping, we generated a simulated reference library, i.e., BssHII reference library, by in silico enzyme digestion of the human genome (hg19, UCSC) regardless of the methylation state. This library was used as reference for subsequent mapping of the tags in the MMSDK analysis. In the DGE analysis, refMrna (hg19, UCSC) was used as reference for mapping cDNA tags. Subsequently, the Burrows–Wheeler Aligner (BWA) procedure for aligning the MMSDK and DGE tags to the simulated BssHII reference library and refMrna reference library, respectively, was applied. Results: MMSDK libraries using BssHII/NlaIII were generated from the parental tamoxifen sensitive subline MCF-7/S0.5 and the 4 TAMR cell lines: TAMR-1, TAMR-4, TAMR-7 and TAMR-8. The 5 indexed MMSDK libraries were sequenced in one lane and 1.38 Gb clean tag data for all 5 cell lines were obtained, with an average sequencing amount of ~270 Mb per library. On average, 59.5 % of the tags with mapping quality ≥ 20 were mapped back to the simulated BssHII/NlaIII reference library. DGE libraries were also generated from MCF-7/S0.5 and the 4 TAMR cell lines. The 5 indexed DGE libraries were sequenced in one lane and obtained 1.71 Gb clean tag data for all 5 cell lines with an average sequencing amount of ~340 Mb per library. On average, 40.8 % with mapping quality ≥ 20 were mapped back to the simulated NlaIII human transcriptome (refMrna reference library). Our present study demonstrates large differences in global gene expression and DNA methylation profiles between parental tamoxifen-sensitive cell line and 4 high-dosage tamoxifen treatment selected resistant sublines. The tamoxifen resistant cell lines exhibited globally higher methylation level than the parental cell line and an inverse relationship between gene expression and DNA methylation in the promoter regions were noticed. High expression of SOX2 and alterations of other SOX gene family members, E2F gene family members and RB-related pocket protein genes as well as highlighted stem cell pathways imply that cancer initiating cells/stem cells are involved in the resistance to tamoxifen.

Project description:Purpose: Development of resistance to tamoxifen is an important clinical issue in the treatment of patients with breast cancer. Tamoxifen resistance may be the result of the acquisition of epigenetic regulation such as DNA methylation within breast cancer cells resulting in changed mRNA expression of genes being pivotal for estrogen dependent growth. Alternatively, tamoxifen resistance may be due to selection of preexisting resistant cells, which may exhibit cancer stem-like characteristics or a combination of the two mechanisms. Methods: To evaluate the contribution of these possible mechanisms to tamoxifen resistance, we applied modified DNA methylation-specific digital karyotyping (MMSDK) and digital gene expression (DGE) in combination with massively parallel sequencing to analyze a well-established tamoxifen resistant cell line model: MCF-7/S0.5 (tamoxifen sensitive parental cell line) and 4 high-dosage tamoxifen selected resistant offspring sublines (MCF-7/TAMR-1, MCF-7/TAMR-4, MCF-7/TAMR-7 and MCF-7/TAMR-8). MMSDK uses BssHII as mapping enzyme (DNA methylation sensitive enzyme). Both MMSDK and DGE use NlaIII and MmeI to produce 20-21 bp tag. The indexed single-end sequencing was performed by Illumina HiSeq 2000 in BGI-Shenzhen. A dynamic programming algorithm-FASTX-Toolkit implemented in Perl was used to trim the adaptor sequence. The trimmed tags were subjected to quality filtering, so that only tags with sequencing quality higher than 30 for more than 80% of the nucleotides were used for subsequent analysis. For MMSDK tag mapping, we generated a simulated reference library, i.e., BssHII reference library, by in silico enzyme digestion of the human genome (hg19, UCSC) regardless of the methylation state. This library was used as reference for subsequent mapping of the tags in the MMSDK analysis. In the DGE analysis, refMrna (hg19, UCSC) was used as reference for mapping cDNA tags. Subsequently, the BurrowsM-bM-^@M-^SWheeler Aligner (BWA) procedure for aligning the MMSDK and DGE tags to the simulated BssHII reference library and refMrna reference library, respectively, was applied. Results: MMSDK libraries using BssHII/NlaIII were generated from the parental tamoxifen sensitive subline MCF-7/S0.5 and the 4 TAMR cell lines: TAMR-1, TAMR-4, TAMR-7 and TAMR-8. The 5 indexed MMSDK libraries were sequenced in one lane and 1.38 Gb clean tag data for all 5 cell lines were obtained, with an average sequencing amount of ~270 Mb per library. On average, 59.5 % of the tags with mapping quality M-bM-^IM-% 20 were mapped back to the simulated BssHII/NlaIII reference library. DGE libraries were also generated from MCF-7/S0.5 and the 4 TAMR cell lines. The 5 indexed DGE libraries were sequenced in one lane and obtained 1.71 Gb clean tag data for all 5 cell lines with an average sequencing amount of ~340 Mb per library. On average, 40.8 % with mapping quality M-bM-^IM-% 20 were mapped back to the simulated NlaIII human transcriptome (refMrna reference library). Our present study demonstrates large differences in global gene expression and DNA methylation profiles between parental tamoxifen-sensitive cell line and 4 high-dosage tamoxifen treatment selected resistant sublines. The tamoxifen resistant cell lines exhibited globally higher methylation level than the parental cell line and an inverse relationship between gene expression and DNA methylation in the promoter regions were noticed. High expression of SOX2 and alterations of other SOX gene family members, E2F gene family members and RB-related pocket protein genes as well as highlighted stem cell pathways imply that cancer initiating cells/stem cells are involved in the resistance to tamoxifen. DNA methylation and mRNA expression profiles from tamoxifen sensitive parental cell line MCF-7/S0.5 and 4 high dosage of tamoxifen selected resistant offspring sublines (MCF-7/TAMR-1, MCF-7/TAMR-4, MCF-7/TAMR-7 and MCF-7/TAMR-8) were analyzed by MMSDK and DGE methods, respectively, in combination of massively parallel sequencing, using Illumina HiSeq 2000

Project description:Probing epigenetic features on long molecules of DNA has tremendous potential to advance our understanding of the phased epigenome. In this study, we evaluate CpG methylation and chromatin accessibility simultaneously on long strands of DNA using GpC methyltransferase to exogenously label open chromatin, coupled with nanopore sequencing technology. We performed nanopore sequencing of Nucleosome Occupancy and Methylome (nanoNOMe) on four human cell lines (GM12878, MCF-10A, MCF-7, MDA-MB-231), and demonstrate the ability to directly measure methylation and chromatin accessibility in genomic features such as structural variations and repetitive elements. The long single-molecule resolution allows footprinting of protein and nucleosome binding and determining the combinatorial promoter epigenetic state on individual molecules. Long-read sequencing makes it possible to robustly assign reads to haplotypes, enabling allele-specific epigenetic analysis across the genome. We use existing SNV data on GM12878 to present the first fully phased human Probing epigenetic features on long molecules of DNA has tremendous potential to advance our understanding of the phased epigenome. We evaluate CpG methylation and chromatin accessibility simultaneously on long strands of DNA using GpC methyltransferase to exogenously label open chromatin, coupled with nanopore sequencing technology. We performed nanopore sequencing of Nucleosome Occupancy and Methylome (nanoNOMe) on four human cell lines (GM12878, MCF-10A, MCF-7, MDA-MB-231), and demonstrate the ability to directly measure methylation and chromatin accessibility in genomic features such as structural variations and repetitive elements. The long single-molecule resolution allows footprinting of protein and nucleosome binding and determining the combinatorial promoter epigenetic state on individual molecules. Long-read sequencing makes it possible to robustly assign reads to haplotypes, enabling allele-specific epigenetic analysis across the genome. We use existing SNV data on GM12878 to present the first fully phased human epigenome, consisting of chromosome-level allele-specific profiles of CpG methylation and chromatin accessibility.mosome-level allele-specific profiles of CpG methylation and chromatin accessibility.

Dataset Information

Expression data from breast cancer cell lines (MCF-7 and MDA-MB-231)

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets