Functional ER alpha transcriptional regulatory network for cell cycle in an ER(+) breast cancer subgroup
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE17040 | GEO | 2009/07/24
SECONDARY ACCESSION(S): PRJNA117841
REPOSITORIES: GEO
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 primordial actions of the estrogen receptor alpha (ER) in controlling breast cancer cells proliferation rate are particularly documented. However, reintroducing ER into ER-negative cells does not reprogram their transcriptome towards an estrogen-sensitive growth phenotype. Member of the Forkhead (FKH) family of transcription factors, FOXA1 has been characterized to be essential for the appropriate binding of ER onto chromatin in MCF-7 cells. FOXA1 pioneering actions involve modulations of histone post-translational modifications (HPTMs) and local depletion in methylated CpGs. Using MDA-MB231 cells which are ER and FOXA1 negative, we aimed at determining whether the introduction of ER and FOXA1 would be sufficient to restore an estrogen-sensitive growth and to coincidently reprogram chromatin. We used ChIP-seq experiments to map ER and FOXA1 binding sites (BSs) and to profile H3K4me2 and H3K27ac marks, and surprisingly observed that FOXA1 had rather a global negative impact on ER actions, associated with an inhibition of growth and a reorientation of the transcriptome of the cells towards cell death. We demonstrate that the re-introduction of FOXA1 in these cells actually competes for the binding and pioneering actions of FOXA2, another FKH protein, on a number of ER BSs. As demonstrated for its alter ego FOXA1 in MCF-7 cells, abrogating FOXA2 expression drastically diminished ER binding onto its cognate sites, associated with a local loss of HPTMs for active chromatin.
2022-12-11 | GSE55680 | GEO
Project description:The primordial actions of the estrogen receptor alpha (ER) in controlling breast cancer cells proliferation rate are particularly documented. However, reintroducing ER into ER-negative cells does not reprogram their transcriptome towards an estrogen-sensitive growth phenotype. Member of the Forkhead (FKH) family of transcription factors, FOXA1 has been characterized to be essential for the appropriate binding of ER onto chromatin in MCF-7 cells. FOXA1 pioneering actions involve modulations of histone post-translational modifications (HPTMs) and local depletion in methylated CpGs. Using MDA-MB231 cells which are ER and FOXA1 negative, we aimed at determining whether the introduction of ER and FOXA1 would be sufficient to restore an estrogen-sensitive growth and to coincidently reprogram chromatin. We used ChIP-seq experiments to map ER and FOXA1 binding sites (BSs) and to profile H3K4me2 and H3K27ac marks, and surprisingly observed that FOXA1 had rather a global negative impact on ER actions, associated with an inhibition of growth and a reorientation of the transcriptome of the cells towards cell death. We demonstrate that the re-introduction of FOXA1 in these cells actually competes for the binding and pioneering actions of FOXA2, another FKH protein, on a number of ER BSs. As demonstrated for its alter ego FOXA1 in MCF-7 cells, abrogating FOXA2 expression drastically diminished ER binding onto its cognate sites, associated with a local loss of HPTMs for active chromatin.
2022-12-11 | GSE55740 | GEO
Project description:Estrogen is proven to promote the malignant behaviors of many cancers via its receptors. Estrogen receptor alfa 36(ER-α36) is a newly identified isoform of estrogen receptor alfa （ERα）, which is different from the 66 kDa estrogen receptor alpha (ER-α66).However, the role of ER-α36 in regulating the effects of estrogen and its potential impact on human cervical cancer is poorly understood. In this study, we found that ER-α36 was over-expressed in cervical cancer tissues and elevated ER-α36 expression was associated with poor prognosis in cervical cancer patients. High expression of ER-α36 promotes the proliferation, invasion and metastasis of cervical cancer cells mediated by estrogen, while silencing ER-α36 had the opposite effects. Further research showed that high mobility group A2 (HMGA2) identified as a down-target of ER-α36 in cervical cancer cells. The oncogenic effect of ER-α36 was attenuated after HMGA2 knockdown. In conclusion, high expression of ER-α36 was correlated with a poor prognosis and metastasis in cervical cancer by regulating HMGA2.ER-α36 might serve as a prognostic biomarker and a target for cervical cancer treatment.
2021-04-23 | GSE173120 | GEO
Project description:A variety of high-throughput techniques are now available for constructing comprehensive gene regulatory networks in systems biology. In this study, we report a new statistical approach for facilitating in silico inference of regulatory network structure. The new measure of association, coefficient of intrinsic dependence (CID), is model-free and can be applied to both continuous and categorical distributions. When given two variables X and Y, CID answers whether Y is dependent on X by examining the conditional distribution of Y given X. In this paper, we apply CID to analyze the regulatory relationships between transcription factors (TFs) (X) and their downstream genes (Y) based on clinical data. More specifically, we use estrogen receptor alpha (ERalpha) as the variable X, and the analyses are based on 48 clinical breast cancer gene expression arrays (48A). RESULTS: The analytical utility of CID was evaluated in comparison with four commonly used statistical methods, Galton-Pearson's correlation coefficient (GPCC), Student's t-test (STT), coefficient of determination (CoD), and mutual information (MI). When being compared to GPCC, CoD, and MI, CID reveals its preferential ability to discover the regulatory association where distribution of the mRNA expression levels on X and Y does not fit linear models. On the other hand, when CID is used to measure the association of a continuous variable (Y) against a discrete variable (X), it shows similar performance as compared to STT, and appears to outperform CoD and MI. In addition, this study established a two-layer transcriptional regulatory network to exemplify the usage of CID, in combination with GPCC, in deciphering gene networks based on gene expression profiles from patient arrays. CONCLUSION: CID is shown to provide useful information for identifying associations between genes and transcription factors of interest in patient arrays. When coupled with the relationships detected by GPCC, the association predicted by CID are applicable to the construction of transcriptional regulatory networks. This study shows how information from different data sources and learning algorithms can be integrated to investigate whether relevant regulatory mechanisms identified in cell models can also be partially re-identified in clinical samples of breast cancers. AVAILABILITY: the implementation of CID in R codes can be freely downloaded from (http://homepage.ntu.edu.tw/~lyliu/BC/). Experiment Overall Design: Total 48 clinical arrays (48A) used in this study can be found in GSE9309. We designed the experiments using a given breast cancer population with clear status of estrogen receptor alpha (ER), which were confirmed by immunochemical staining (If ³10% immunopositive stain is found at tumor section, we designate it as ER(+). Otherwise, it is ER(-). ) in this study. 48A consist of 36A with positive in ER status and of 12A with negative in ER status.
2009-07-19 | E-GEOD-17041 | biostudies-arrayexpress
Project description:We performed chromatin immunoprecipitation (ChIP) with overnight with antibodies against the C-terminus (HC-20, from Santa Cruz Biotechnology, Europe) or the N-terminus (anti-Estrogen Receptor 18-32, from SigmaAldrich, Italy) of human ER-alpha with or without estrogen treatment for 45 minutes on TAP-ER-beta cells, and the immunoprecipitated DNA was sequenced with the Illumina/Solexa Genome Analyzer. (Note: Raw data files not provided by submitter)
2010-12-01 | E-MTAB-345 | biostudies-arrayexpress
Project description:Background: We have established a statistical approach on building a transcriptional regulatory network in silico at a global transcriptome scale. Here, we characterize clinical relevant gene activities regulated by a transcription factor-estrogen-related receptor gamma (ESRRG) via such approach. Methods: We measured gene expression relationship between ESRRG and its target gene via univariate coefficient of intrinsic dependence and Galton Pearson’s correlation coefficient. A few more bioinformatics tools were used for further investigation on ESRRG. Results: ESRRG is a negative determinant of lymphovascular invasion, lymph nodal category, stage, histological grade, nuclear pleomorphism and tubule formation in ER(+) infiltrating ductal carcinoma of breast. Interestingly, ESRRG was the only one in the final intersection of Venn Diagram analyses for determinants of those clinical indices. We established an ESRRG core network consisting of 118 probes. Both MYB and ARNT2 were up-regulated by ESRRG and in two ESRRG subnetworks (29 probes, 89 probes), respectively. We observed genes for tumor suppressive activities and responsiveness to anticancer treatments within ESRRG core network and a conserved protective role of ESRRG. Conclusions: ESRRG is a tumor suppressor typically for ER(+) breast cancer and up-regulates tumor suppressor genes mostly within ERα transcriptional regulatory network. An ESRRG core network reveals ESRRG to be a favorable marker and MYB to be the main partner for its cancer protective role during early tumor promotion. But, ARNT2 is an additional partner of ESRRG during early tumor progression. Impact: A core ESRRG transcriptional regulatory network indicates the major clinical impact of ESRRG. 181 surgical specimens of primary infiltrating ductal carcinoma (IDC) were obtained from patients who underwent surgery at National Taiwan University Hospital (NTUH) between 1998 and 2007. They include 90 ER(+) IDCs and 91 ER(-) IDCs. Tissue samples were excised, snap frozen in liquid nitrogen, and stored at -80℃. Breast cancer samples containing relatively pure cancer as defined by greater than 50% tumor cells per high-power field examined in an adjacent section of tumor sample were for this study (Lien HC, et al. Oncogene 2007; 26: 7859-71). Twenty five non-tumor samples were surgically taken from breast cancer patients in 181 IDC patients to generate 25 gene expression profiles as a control in this study. All patients had given informed consent according to the guidelines approved by the Institutional Review Board at NTUH. The matrix file linked to the bottom of this Series includes reanalyzed data from the 119 Samples of this Series and 87 Samples from Series GSE9309 and GSE17040.
2010-11-04 | E-GEOD-24124 | biostudies-arrayexpress
Project description:Purpose: To perform RNA-Seq expression profiling from Young Women's Breast Cancer FFPE tissues, comparing ER+ Postpartum Brest Cancer to ER+ Nulliparous Breast Cancer Methods: RNA was extracted and isolated from archival Estrogen Receptor Positive primary breast cancer FFPE tissues ( 9 Postpartum, 7 Nulliparous). RNA species selected for inclusion in library utilzing Illumina-Access bead based oligo library preparation representing > 98% of known protein coding genes. Results: We identified gene pathway differences in estrogen receptor signaling, t-cell immunity and cell cycle between nulliparous and postpartum breast cancer cases. Subset analysis also revealed an enrichment in extra-cellular matrix pathway related genes in postpartum compared to nulliparous and luminal A cases.
2021-09-15 | GSE158854 | GEO
Project description:Aminoacyl tRNA synthetases (ARSs) are a class of enzymes with well-conserved housekeeping functions in cellular translation. Recent evidence suggests that ARS genes may participate in a wide array of cellular processes, and may contribute to the pathology of autoimmune disease, cancer, and other diseases. Several studies have suggested a role for the glutamyl prolyl tRNA synthetase (EPRS) in breast cancers, although none has demonstrated any underlying mechanism about how EPRS contributes to carcinogenesis. In this study, we identified EPRS as upregulated in estrogen receptor positive (ER+) human breast tumors in the TCGA and METABRIC cohorts, with copy number gains in nearly 50% of samples in both datasets. EPRS expression is associated with reduced overall survival in patients with ER+ tumors in TCGA and METABRIC datasets. EPRS expression was also associated with reduced distant relapse-free survival in patients treated with adjuvant tamoxifen monotherapy for five years, and EPRS-correlated genes were highly enriched for genes predictive of a poor response to tamoxifen. We demonstrated the necessity of EPRS for proliferation of tamoxifen-resistant ER+ breast cancer, but not ER- breast cancer cells. Transcriptomic profiling showed that EPRS regulated cell cycle and estrogen response genes. Finally, we constructed a causal gene network based on over 2500 ER+ breast tumor samples to build up an EPRS-estrogen signaling pathway. EPRS and its regulated estrogenic gene network may offer a promising alternative approach to target ER+ breast cancers that are refractory to current anti-estrogens.
2016-10-05 | GSE81162 | GEO
Project description:Retinoic acid receptor-alpha (RAR alpha) is a known estrogen target gene in breast cancer cells. The consequence of RAR alpha induction by estrogen was previously unknown. We now show that RAR alpha is required for efficient estrogen receptor-alpha (ER)-mediated transcription and cell proliferation. RAR alpha can interact with ER-binding sites, but this occurs in an ER-dependent manner, providing a novel role for RAR alpha that is independent of its classic role. We show, on a genome-wide scale, that RAR alpha and ER can co-occupy regulatory regions together within the chromatin. This transcriptionally active co-occupancy and dependency occurs when exposed to the predominant breast cancer hormone, estrogen--an interaction that is promoted by the estrogen-ER induction of RAR alpha. These findings implicate RAR alpha as an essential component of the ER complex, potentially by maintaining ER-cofactor interactions, and suggest that different nuclear receptors can cooperate for effective transcriptional activity in breast cancer cells. RAR alpha silenced breast cancer MCF-7 cell lines or control siRNA in the presence of estrogen or a vehicle. MCF-7 cells were hormone-depleted for 3 d and treated with 100 nM estrogen for 12 h. There were three biological replicates for each of the four different groups.
2010-06-16 | E-GEOD-22213 | biostudies-arrayexpress