Browse
Submit Data
Databases
API
Help

Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Histone H3 Lysine4 Acetylation-Methylation Dynamics Define Breast Cancer Subtypes [ChIP-seq]

ABSTRACT: The molecular signature at histone H3K4 involved in epigenetic regulation of normal (MCF10A) and transformed (MCF7, MDA-MB-231) breast cells using ChIP-Seq technology. This study examines the dynamic distribution of H3K4me3 and H3K4ac histone modification associated with active chromatin to provide an understanding of the changes in epigenetic regulation associated with the unique breast cancer subtypes. H3K4me3 and H3K4ac histone modification study in normal (MCF10A) and transformed (MCF7, MDA-MB-231) breast cells using ChIP-Seq technology

ORGANISM(S): Homo sapiens

SUBMITTER: Joe Boyd

PROVIDER: E-GEOD-69377 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Json Xml

Publications

Histone H3 lysine 4 acetylation and methylation dynamics define breast cancer subtypes.

Messier Terri L TL Gordon Jonathan A R JA Boyd Joseph R JR Tye Coralee E CE Browne Gillian G Stein Janet L JL Lian Jane B JB Stein Gary S GS

Oncotarget 20160201 5

The onset and progression of breast cancer are linked to genetic and epigenetic changes that alter the normal programming of cells. Epigenetic modifications of DNA and histones contribute to chromatin structure that result in the activation or repression of gene expression. Several epigenetic pathways have been shown to be highly deregulated in cancer cells. Targeting specific histone modifications represents a viable strategy to prevent oncogenic transformation, tumor growth or metastasis. Meth ...[more]

PMID: 26783963

Similar Datasets

Bivalency - Histone H3 Lysine4 and Histone H3 Lysine27 Methylation Dynamics

Project description:The molecular signature at histone H3K4me3 and H3K27me3 involved in epigenetic regulation of normal (MCF10A) and transformed (MCF7, MDA-MB-231) breast cells using ChIP-Seq technology. This study examines the dynamic distribution of H3K4me3, associated with active chromatin, and H3K27me3, associated with repressed chromatin, histone modifications to provide an understanding of the changes in epigenetic regulation associated with the unique breast cancer subtypes. histone H3K4me3 and H3K27me3 ChIP-seq normal (MCF10A) and transformed (MCF7, MDA-MB-231) breast cells Please note that the 'H3K4me3' and 'input' data are duplicated records of the samples represented in GSE69377 for the convenient retrieval of the complete raw data from SRA.

2016-03-24 | E-GEOD-77772 | biostudies-arrayexpress

Histone H3 lysine 4 acetylation-methylation dynamics define breast cancer subtypes [RNA-seq]

Project description:The onset and progression of breast cancer are linked to genetic and epigenetic changes that alter the normal programming of cells. Epigenetic modifications of DNA and histones contribute to chromatin structure that results in the activation or repression of gene expression. Several epigenetic pathways have been shown to be highly deregulated in cancer cells. Targeting specific histone modifications represents a viable strategy to prevent oncogenic transformation, tumor growth or metastasis. Methylation of histone H3 lysine 4 has been extensively studied and shown to mark genes for expression; however this residue can also be acetylated and the specific function of this alteration is less well known. To define the relative roles of histone H3 methylation (H3K4me3) and acetylation (H3K4ac) in breast cancer, we determined genomic regions enriched for both marks in normal-like (MCF10A), transformed (MCF7) and metastatic (MDA-MB-231) cells using a genome-wide ChIP-Seq approach. Our data revealed a genome-wide gain of H3K4ac associated with both early and late breast cancer cell phenotypes, while gain of H3K4me3 was predominantly associated with late stage cancer cells. Enrichment of H3K4ac was overrepresented at promoters of genes associated with cancer-related phenotypic traits, such as estrogen response and epithelial-to-mesenchymal transition pathways. Our findings highlight an important role for H3K4ac in predicting epigenetic changes associated with early stages of transformation. In addition, our data provide a valuable resource for understanding epigenetic signatures that correlate with known breast cancer-associated oncogenic pathways. RNA-Seq of cell lines MCF10A, MCF7 and MDA-MB-231.

2016-02-10 | E-GEOD-75168 | biostudies-arrayexpress

Differential Gene Expression between MCF10A and MCF7 cells

Project description:These RNA-seq data were generated to correlate with genomic interaction data in a related Hi-C analysis. MCF10A is a normal-like mammary epithelial cell line and MCF7 is a transformed estrogen responsive breast cancer cell line derived from a metastatic site; both are commonly used in models of breast cancer progression. Analysis revealed a set of genes related to repression of WNT signalling that were both up-regulated in MCF7 and located in genomic regions that had transitioned from closed to open structure in MCF7. RNA-seq of MCF10A and MCF7 cells. 3 replicates each. Sequencing was strand-specific and conducted on ribo-depleted RNA.

2015-09-02 | E-GEOD-71862 | biostudies-arrayexpress

Histone H3 Lysine4 Acetylation-Methylation Dynamics Define Breast Cancer Subtypes [ChIP-seq]

Project description:The molecular signature at histone H3K4 involved in epigenetic regulation of normal (MCF10A) and transformed (MCF7, MDA-MB-231) breast cells using ChIP-Seq technology. This study examines the dynamic distribution of H3K4me3 and H3K4ac histone modification associated with active chromatin to provide an understanding of the changes in epigenetic regulation associated with the unique breast cancer subtypes.

2016-02-10 | GSE69377 | GEO

Bivalency - Histone H3 Lysine4 and Histone H3 Lysine27 Methylation Dynamics

2016-03-24 | GSE77772 | GEO

Phosphoproteomic analysis of breast cancer-derived extracellular vesicles reveals disease-specific phosphorylated enzymes

Project description:Small membrane-derived extracellular vesicles have been proposed to participate in several cancer diseases, including breast cancer. We performed phosphoproteomic analysis of breast cancer-derived small extracellular vesicles (sEVs) to provide insight into the molecular and cellular regulatory mechanisms important for breast cancer tumor progression and metastasis. We examined 3 cell lines as models for breast cancer: MCF10A (non-metastatic), MCF7 (estrogen and progesterone receptor positive, metastatic) and MDA-MB-231 (triple-negative, highly metastatic). To obtain a comprehensive overview of the sEV phosphoproteme derived from each cell line, an effective enrichment phosphopeptide techniques with IMAC and TiO2, followed by LC-MS/MS was achieved. In total, 2003 phosphopeptides on which 207, 854 and 1335 have been identified in MCF10A, MCF7 and MDA-MB-231cell lines, respectively. These phosphorylation sites were mapped to 855 distinct proteins, covering a wide range of functions. These proteins are associated with larger number of diseases and the most common diseases are related to cancer. Among the phosphoproteins identified, we validated four enzymes associated to cancer and present only in sEVs isolated from MCF7 and MDA-MB-231 cell lines: ATP citrate lyase (ACLY), phosphofructokinase-M (PFKM), Sirtuin-1 (SIRT1) and Sirtuin-6 (SIRT6). With the exception of PFKM, the specific activity of these enzymes was significantly higher in MDA-MB-231 when compared with MCF10A-derived sEVs. This study demonstrates that sEVs contain functional metabolic enzymes that could be further explored for their potential in early BC diagnostic and therapeutic applications.

2022-02-28 | PXD030424 | Pride

Lysine acetolome of breast cancer-derived small extracellular vesicles reveals specific acetylation pattern for metabolic enzymes

Project description:Cancer-derived small extracellular vesicles have been proposed as promising potential biomarkers for diagnosis and prognosis of breast cancer (BC). We performed a proteomic study of lysine acetylation of breast cancer-derived small extracellular vesicles (sEVs) to understand the potential role of the aberrant acetylated proteins in the metastasis and progression of BC. Three cell lines were used as models for this study: MCF10A (non-metastatic), MCF7 (estrogen and progesterone receptor positive, metastatic) and MDA-MB-231 (triple-negative, highly metastatic). For a com-prehensive protein acetylation analysis of the sEVs derived from each cell line, acetylated peptides were enriched using the anti-acetyl-lysine antibody, followed by LC-MS/MS analysis. In total, 118 lysine acetylated peptides of which 22, 58 and 82 have been identified in MCF10A, MCF7 and MDA-MB-231 cell lines, respectively. These acetylated peptides were mapped to 60 distinct pro-teins and mainly identified proteins involved in metabolic pathways. Among those identified acetylated proteins presented in cancer-derived sEVs (MCF7, MDA-MB-231) are proteins associ-ated with glycolysis pathway, annexins and histones. Five enzymes from the glycolytic pathway, present only in sEVs isolated from cancer-derived sEVs cell lines, were validated. These include aldolase (ALDOA), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), phosphoglycerate kinase (PGK 1), enolase (ENO) and pyruvate kinase M1/2 (PKM). For three of these enzymes, ALDOA, PGK 1 and ENO, the specific enzymatic activity was significantly higher in MDA-MB-231 when compared with MCF10A-derived sEVs. This study reveals that sEVs contain acetylated glycolytic metabolic enzymes that could be interesting potential candidates for early BC diagnostics.

2023-07-20 | PXD040413 | Pride

tsRNA microarray of parental normal-like and breast cancer cell lines and with inhibited or induced RUNX1 expression

Project description:The expression levels of tRNA-derived small RNA, known as tsRNA, were interrogated in the following parental cell lines: MCF10A normal-like mammary epithelial cell, MCF7, MCF10AT1, MCF10CA1a, and MDA-MB-231 breast cancer cells. In addition, tsRNA expression was determined after shRNA-inhibition of RUNX1 in MCF10A cells or RUNX1 induction in MCF10CA1a cells.

2020-01-01 | GSE142382 | GEO

RNA-seq of cancer-associated fibroblasts (CAF) treated with PBS or extracellular vesicles (EV) from MCF10A or MDA-MB-231 cells

Project description:To identify gene expression changes associated with treatment of EV that carry high levels of miR-105 (from MDA-MB-231 and MCF10A/miR-105 cells) in human breast tumor derived CAF, we analyzed RNA isolated from PBS- or EV-treated CAF. Gene expression in CAF treated with EV from MDA-MB-231 or MCF10A/miR-105 cells was compared to cells treated with PBS or EV from MCF10A cells, both of which served as controls in this experiment.

2018-02-11 | GSE106503 | GEO

MicroRNAome of highly metastatic and non-metastatic human breast cell lines

Project description:MicroRNAs are noncoding, endogenous small RNAs that regulate target genes by cleavage of the targeted mRNA or translational repression. We investigated the microRNAome using 2-color microarrays in a highly invasive human breast cancer cell line, MDA-MB-231 (sub line 4175) and a non-invasive breast epithelial cell line, MCF10A. We found 13 miRNAs that were up-regulated and 9 were down-regulated significantly in 4175 cells (p <0.05, fold change >2) compared with MCF10A cells. We compared the highly metastatic human breast cell lines MDA-MB-231 (4175 subline) with non-metastatic MCF10A cell lines. Two 4175 sublines and two MCF10A cell lines, independently grown and harvested. Dye swap was performed.

2010-05-15 | E-GEOD-17350 | biostudies-arrayexpress

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data