Ontology highlight
ABSTRACT:
PROVIDER: PRJNA328906 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR3883934.fastq.gz | Fastqsanger.gz | |||
| SRR3883935.fastq.gz | Fastqsanger.gz | |||
| SRR3883936.fastq.gz | Fastqsanger.gz | |||
| SRR3883937.fastq.gz | Fastqsanger.gz | |||
| SRR3883938_1.fastq.gz | Fastqsanger.gz |
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Project description:The Estrogen Receptor alpha (ERα) controls key cellular functions in hormone responsive breast cancer by assembling in large functional multiprotein complexes. ERα ligands are classified as agonists and antagonist, according to the response they elicit, thus the molecular characterization of the of ERα nuclear iteractome composition following estrogen and antiestrogen stimulation whose is needed to understand their effects on estrogen target tissues, in particular breast cancer. To this aim interaction proteomics coupled to mass spectrometry (MS) was applied to map the ERα nuclear interacting partners in MCF7 breast cancer cell nuclei following estrogen and antiestrogen stimuli.
2020-09-02 | PXD018709 | Pride
Project description:Estrogen regulates diverse physiological effects and drives breast tumor progression by directly activating the estrogen receptor α (ERα). However, due to the stochastic nature of gene transcription and the resulting heterogeneous cellular responses, it is important to investigate estrogen-stimulated gene expression profiles at the single-cell level in order to fully understand how ERα regulates transcription in breast cancer cells. In this study, we performed single-cell transcriptome analysis on ERα-positive breast cancer cell lines following 17β-estradiol stimulation. We sequenced a total of 177 single-cell transcriptomes and observed robust gene expression diversity between individual cells.
2018-11-20 | GSE119455 | GEO
Project description:Estrogen regulates diverse physiological effects and drives breast tumor progression by directly activating the estrogen receptor α (ERα). However, due to the stochastic nature of gene transcription and the resulting heterogeneous cellular responses, it is important to investigate estrogen-stimulated gene expression profiles at the single-cell level in order to fully understand how ERα regulates transcription in breast cancer cells. In this study, we performed single-cell transcriptome analysis on ERα-positive breast cancer cell lines following 17β-estradiol stimulation. We sequenced a total of 177 single-cell transcriptomes and observed robust gene expression diversity between individual cells.
2018-11-20 | GSE107863 | GEO
Project description:Estrogen regulates diverse physiological effects and drives breast tumor progression by directly activating the estrogen receptor α (ERα). However, due to the stochastic nature of gene transcription and the resulting heterogeneous cellular responses, it is important to investigate estrogen-stimulated gene expression profiles at the single-cell level in order to fully understand how ERα regulates transcription in breast cancer cells. In this study, we performed single-cell transcriptome analysis on ERα-positive breast cancer cell lines following 17β-estradiol stimulation. We sequenced a total of 177 single-cell transcriptomes and observed robust gene expression diversity between individual cells.
2018-11-20 | GSE107858 | GEO
Project description:Estrogen Receptor (ESR1) drives growth in the majority of human breast cancers by binding to regulatory elements and inducing transcription events that promote tumor growth. Differences in enhancer occupancy by ESR1, contribute to the diverse expression profiles and clinical outcome observed in breast cancer patients. GATA3 is an ESR1 co-operating transcription factor mutated in breast tumors, however its genomic properties are not fully defined. In order to investigate the composition of enhancers involved in estrogen-induced transcription and the potential role of GATA3, we performed extensive ChIP-sequencing in unstimulated breast cancer cells and following estrogen treatment. We find that GATA3 is pivotal in mediating enhancer accessibility at regulatory regions involved in ESR1-mediated transcription. GATA3 silencing resulted in a global redistribution of co-factors and active histone marks prior to estrogen stimulation. These global genomic changes altered the ESR1 binding profile that subsequently occurred following estrogen, with events exhibiting both loss and gain in binding affinity, implying a GATA3 mediated re-distribution of ESR1 binding. The GATA3-mediated re-distributed ESR1 profile correlated with changes in gene expression, suggestive of its functionality. Chromatin loops at the TFF locus involving ESR1 bound enhancers occurred independently of ESR1 when GATA3 was silenced, indicating that GATA3, when present on the chromatin, may serve as a licensing factor for estrogen- ESR1 mediated interactions between cis-regulatory elements. Together these experiments suggest that GATA3 directly impacts ESR1 enhancer accessibility and may potentially explain the contribution of mutant-GATA3 in the heterogeneity of ESR1+ breast cancer. GATA and ER binding studied by chromatin immunoprecipitation in breast cancer cell lines, with and without estrogen stimulation and by knocking down GATA
2012-11-26 | E-GEOD-40129 | biostudies-arrayexpress
Project description:The transcription factor GATA3 is a favorable prognostic indicator in estrogen receptor-M-NM-1 (ERM-NM-1)-positive breast tumors in which it participates with ERa and FOXA1 in a complex transcriptional regulatory program driving tumor growth. Paradoxically, GATA3 mutations are frequent in breast cancer and have been classified as drivers. To elucidate the contribution(s) of GATA3 alterations to oncogenesis, we studied two breast cancer cell lines, MCF7, which carries a heterozygous frameshift mutation in the second zinc finger of GATA3, and T47D, wild-type at this locus. Heterozygosity for the truncating mutation conferred protection from regulated turnover of GATA3, ERa and FOXA1 following estrogen stimulation. Thus, mutant GATA3 uncouples protein-level regulation of master regulatory transcription factors from hormone action. Consistent with increased protein stability, ChIP-seq profiling identified stronger accumulation of GATA3 in cells bearing the mutation, albeit with a similar distribution across the genome. We propose that this specific, cancer-derived mutation in GATA3 deregulates physiologic protein turnover, stabilizes GATA3 binding across the genome and modulates the response of mammary epithelial cells to hormone signaling, thus conferring a selective growth advantage. Genome-wide mapping of GATA3 in two cell lines. There were two biological replicates and unchipped (input) DNA was used as reference.
2014-04-01 | E-GEOD-51274 | biostudies-arrayexpress
Project description:Androgen receptor (AR) is expressed in 60-70% of breast cancers independent of estrogen receptor (ER) expression, however its function in breast cancer is largely unknown. Our study identified the high level of AR in ERâ??/HER2+ breast tumors and andorgen and AR greatly stimulated growth of MDA-MB-453 breast cancer cells. To define the genome-wide AR binding sites, we performed AR ChIP-seq using MDA-MB-453 breast cancer cells followig stimulation of DHT. We also identified FOXA1 is a crucial AR cofactor in MDA-MB-453 cells and the FOXA cistrome showed signaficant overlap with AR at both early and late time points of DHT stimulation. AR ChIP was performed in MDA-MB-453 breast cancer cells following 5a-dihydrotestosterone (DHT) stimulation for 4h and 16h respectively. FOXA1 ChIP-seq was performed after 4h DHT stimulation in MDA-MB-453 cells.
2011-07-11 | E-GEOD-28788 | biostudies-arrayexpress
Project description:Estrogen receptors play critical roles in both the normal physiological, and disease states of numerous tissues, including breast and uterus. Estrogen receptor alpha (ER) can activate or repress the expression of target genes upon estrogen stimulation. In order to better understand the transcriptional network of ER in breast and uterus, we generated genome wide maps ofM-BM- ER binding sites (ERBS) and gene expression profiles in breast cancer cells (MCF7 and T47D) and uterine cancer cells (ECC1 and Ishikawa) through ChIP-Seq and microarray techniques. Surprisingly, we identified large scale differences in the numbers of ERBS between these cell lines when treated with E2 (17-M-NM-2 estradiol). Besides identification of common and unique ERBS between breast and uterine cancer cell types., our data also suggest that both cell types could recruit a large set of common co-operating transcription factors (Co-TFs) and a few unique Co-TFs as well. Besides the genes that are commonly regulatedM-BM- between the different cell lines, there are a number of genes that are differentially regulated in different cell types. Gene pathway analyses of E2 target genes suggest that ER regulates many biological pathways and processes in both tissue-type dependent and independent manners. Our results showed that cell lines derived from same tissue display a greater similarity for both profiles of ERBS and gene expression, and that the differential profiles of ER and preferential recruitment of some Co-TFs are the main determinants for the differential regulation of E2 signaling in breast and uterine cancer cells. In order to explore common and distinctive features of ERM-NM-1 (estrogen receptor alpha) binding profiles between breast and uterus, we generated eight ChIP-Seq libraries for the four cell lines (MCF7, T47D, ECC1 and Ishikawa) under two different treatments (E2, ethanol). In addition, we generated four control libraries for the four cell lines. For all treatment libraries, we generated about 7-12 million unique tags each. ER antibody catalog number is (Santa Cruz,sc-543).
2011-01-05 | E-GEOD-23893 | biostudies-arrayexpress
Project description:Mufudza2012 - Estrogen effect on the dynamics
of breast cancer
This deterministic model shows the
dynamics of breast cancer with immune response. The effects of
estrogen are incorporated to study its effects as a risk factor for
the disease.
This model is described in the article:
Assessing the effects of
estrogen on the dynamics of breast cancer.
Mufudza C, Sorofa W, Chiyaka
ET.
Comput Math Methods Med 2012; 2012:
473572
Abstract:
Worldwide, breast cancer has become the second most common
cancer in women. The disease has currently been named the most
deadly cancer in women but little is known on what causes the
disease. We present the effects of estrogen as a risk factor on
the dynamics of breast cancer. We develop a deterministic
mathematical model showing general dynamics of breast cancer
with immune response. This is a four-population model that
includes tumor cells, host cells, immune cells, and estrogen.
The effects of estrogen are then incorporated in the model. The
results show that the presence of extra estrogen increases the
risk of developing breast cancer.
This model is hosted on
BioModels Database
and identified by:
BIOMD0000000642.
To cite BioModels Database, please use:
BioModels Database:
An enhanced, curated and annotated resource for published
quantitative kinetic models.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to
the public domain worldwide. Please refer to
CC0
Public Domain Dedication for more information.
2024-09-02 | BIOMD0000000642 | BioModels
Project description:In order to study transcriptional heterogeneity in response to hormone stimulation in breast cancer, we performed high-throughput single-cell RNA sequencing (scRNA-seq) on 3 breast cancer cell lines that differ in their nuclear receptor expression levels. MCF-7, T-47D and ZR-75-1 cell lines were treated with estrogen and progesterone alone or in combination and collected at different time points. Hash-tagging antibodies were used to identify samples.
2022-09-08 | GSE154873 | GEO