Ontology highlight
ABSTRACT:
OTHER RELATED OMICS DATASETS IN: PXD002104
PROVIDER: PRJNA282502 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:To better characterize group IE like human breast cancer based on the gene profiles of estrogen actions through estrogen receptor alpha (ER alpha), we identified an ER alpha transcriptional regulatory network for cell cycle in silico. We used two datasets from cell line (Data 1) and clinical samples (Data 2), respectively. Analyses on Data 1 via trajectory clustering and Pathway-Express confirmed the significant estrogen effect on up-regulating cell cycle activities. The gene expression relationships between ER alpha and cell cycle genes were re-identified in Data 2 by three statistical methods – Galton-Pearson’s correlation coefficient, Student’s t-test and the coefficient of intrinsic dependence. They were mostly (56.09%)(46/82) re-confirmed by literature search. E2F1 was found to be the major ER alpha target in regulating cell cycle gene expressions (83.72%)(36/43) via suppressive mode. However, enhanced cell cycle progression via up-regulating some cell cycle genes was predicted in silico possibly involving E2F2, in part. Both tumorigenic and tumor suppressing activities indicated by this network were predicted. This network clearly provides a robust way for uncovering estrogen actions in an ER(+) subtype specific manner. Experiment Overall Design: Two clinical datasets were used in this study. One, the 37 clinical arrays (abbreviated as 37A) consist of 26 A for patients positive in estrogen receptor alpha (ER) and in progesterone receptor (PR) immunohistochemical stain (IHC) and 11A for patients negative in ER IHC. This dataset was designated as Data 2. The 31 clinical arrays (31A) consist of 20A for patients positive in ER status but negative in PR status and 11A which are the same as in 37A. This dataset was used for data comparison. All the signals from the mRNA profile of each sample in the experiments were normalized using the internal control RNA- Stratagene's human common reference RNA via statistical method 'rank consistant lowess. Finally, those ratios were transformed by Log2.
2009-08-14 | E-GEOD-17040 | biostudies-arrayexpress
Project description:The estrogen receptor alpha (ERa) drives the growth of two-thirds of all breast cancers. Endocrine therapy impinges on estrogen-induced ERa activation to block tumor growth. However, half of ERa-positive breast cancers are tolerant or acquire endocrine therapy resistance. Here we demonstrate that breast cancer cells undergo genome-wide reprogramming of their chromatin landscape, defined by epigenomic maps and chromatin openness, as they acquire resistance to endocrine therapy. This reveals a role for the Notch pathway while excluding classical ERa signaling. In agreement, blocking Notch signaling, using gamma-secretase inhibitors, or targeting its downstream gene PBX1 abrogates growth of endocrine therapy-resistant breast cancer cells. Moreover Notch signaling through PBX1 directs a transcriptional program predictive of tumor outcome and endocrine therapy response. Comparing histone modifications (H3K4me2 and H3K36me3), chromatin openness (FAIRE) and PBX1 binding between endocrine therapy sensitive MCF7 and resistant MCF7-LTED cells.
2013-05-01 | E-GEOD-37323 | biostudies-arrayexpress
Project description:Breast cancer (BC) is the second most common type of cancer in women and one of the leading causes of cancer-related deaths worldwide. BC classification is based on the detection of three main histological markers: estrogen receptor alpha (ERα), progesterone receptor (PR) and the amplification of epidermal growth factor receptor 2 (HER2/neu). A specific BC subtype, named triple-negative BC (TNBC), lacks the aforementioned markers but a fraction of them express the estrogen receptor beta (ERβ). To investigate the functional role of ERβ in these tumors, interaction proteomics coupled to mass spectrometry (MS) was applied to deeply characterize the nuclear interactors partners in MDA-MD-468 and HCC1806 TNBC cells.
2019-12-03 | PXD014468 | Pride
Project description:Estrogen and progesterone are important regulators of human endometrial differentiation. These steroid hormones act, at least in part, through their nucelar receptors. Role of estrogen receptor alpha (ESR1) during human endometrial differentiation is still unclear. We used microarray analysis to detail the gene expression regulated by ESR1 during differentiation of human endometrial stromal cells.
2016-12-22 | GSE73550 | GEO
Project description:The initiation of breast cancer is associated with increased expression of tumor-promoting estrogen receptor α (ERα) protein and decreased expression of tumor-suppressive ERβ protein. However, the mechanism underlying this process is unknown. Here we show that Pescadillo/PES1, an estrogen-inducible protein that is over-expressed in breast cancer, can regulate the balance between ERα and ERβ. PES1 enhances transcriptional activity of ERα and reduces that of ERβ, and modulates many estrogen-responsive genes. Consistent with this regulation of ERα and ERβ transcriptional activity, PES1 increases the stability of the ERα protein and decreases that of ERβ through the ubiquitin-proteasome pathway, mediated by the carboxyl terminus of Hsc70-interacting protein (CHIP). Moreover, PES1 can transform normal human mammary epithelial cells and is required for estrogen-induced breast tumor growth in nude mice. Further analysis of clinical samples showed that expression of PES1 correlates positively with ERα expression and negatively with ERβ expression, and predicts good clinical outcome in breast cancer. Our data demonstrate that PES1 contributes to breast tumor growth through regulating the balance between ERα and ERβ and may be a better target for the development of drugs that selectively regulate ERα and ERβ activities.
2012-06-10 | GSE38621 | GEO
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:The estrogen receptor alpha (ERa) drives the growth of two-thirds of all breast cancers. Endocrine therapy impinges on estrogen-induced ERa activation to block tumor growth. However, half of ERa-positive breast cancers are tolerant or acquire endocrine therapy resistance. Here we demonstrate that breast cancer cells undergo genome-wide reprogramming of their chromatin landscape, defined by epigenomic maps and chromatin openness, as they acquire resistance to endocrine therapy. This reveals a role for the Notch pathway while excluding classical ERa signaling. In agreement, blocking Notch signaling, using gamma-secretase inhibitors, or targeting its downstream gene PBX1 abrogates growth of endocrine therapy-resistant breast cancer cells. Moreover Notch signaling through PBX1 directs a transcriptional program predictive of tumor outcome and endocrine therapy response.
2013-05-01 | GSE37323 | GEO
Project description:Expression data from Estrogen Receptor alpha-positive Progesterone Receptor-positive Mammary Tumors in STAT1-/- Mice.
| PRJNA145003 | ENA
Project description:The prognosis of a patient with Estrogen Receptor (ER) and/or Progesterone Receptor (PR)-positive breast cancer is highly variable. Therefore, we developed a gene-expression based outcome predictor for ER+ and/or PR+ (i.e. Luminal) breast cancer patients using biological properties of the tumors. First, we identified estrogen-regulated genes using the ER+ MCF-7 breast cancer cell line treated with estrogen. The estrogen-induced gene set was then used to hierarchically cluster a training set of 65 ER+ and/or PR+ tumors into 2 group, which showed survival differences (p=0.0004). Next, supervised analyses based upon these two groups was performed and identified 822 genes that optimally defined these two groups, with the poor prognosis Group IIE tumors showing a proliferation signature and high expression of anti-apoptosis genes and the good outcome Group IE showing the high expression of estrogen and GATA3-induced genes. Centroids were created for each group and applied to ER+ and/or PR+ tumors from three published datasets. For all datasets, Kaplan-Meier survival analyses showed a statistically significant difference in Relapse-Free Survival (and Overall) between Group IE and IIE tumors. Multivariate Cox analysis of the largest test dataset also showed that this predictor was adding independent information. This study provides new biological information concerning differences within Luminal/ER+ breast cancers and a means of predicting long term outcomes in ER+ and/or PR+ breast cancer patients. Keywords: other
2005-12-01 | GSE2740 | GEO
Project description:High levels of Tissue Inhibitor of Metalloproteinases-1 (TIMP1) are associated with poor prognosis, reduced response to chemotherapy, and, potentially, also poor response to endocrine therapy in breast cancer patients. Our objective was to further investigate the hypothesis that TIMP1 is associated with endocrine sensitivity. We established a panel of 11 MCF-7 subclones with a wide range of TIMP1 mRNA and protein expression levels. Cells with high expression of TIMP1 versus low TIMP1 displayed significantly reduced sensitivity to the antiestrogen fulvestrant (ICI 182,780, Faslodex®), while TIMP1 levels did not influence the sensitivity to 4-hydroxytamoxifen. An inverse correlation between expression of the progesterone receptor and TIMP1 was found, but TIMP1 levels did not correlate with estrogen receptor levels or growth-promoting effects of estrogen (estradiol, E2). Additionally, the effects of fulvestrant, 4-hydroxytamoxifen, or estrogen on estrogen receptor expression were not associated with TIMP1 levels. Gene expression analyses revealed associations between expression of TIMP1 and genes involved in metabolic pathways, epidermal growth factor receptor 1/cancer signaling pathways, and cell cycle. Gene and protein expression analyses showed no general defects in estrogen receptor signaling except from lack of progesterone receptor expression and estrogen inducibility in clones with high TIMP1. The present study suggests a relation between high expression level of TIMP1 and loss of progesterone receptor expression combined with fulvestrant resistance. Our findings in vitro may have clinical implications as the data suggest that high tumor levels of TIMP1 may be a predictive biomarker for reduced response to fulvestrant. Microarray analysis of total RNA from 10 subclones of MCF-7 breast cancer cells with various expression levels of TIMP1.
2013-08-22 | E-GEOD-35535 | biostudies-arrayexpress