10 research outputs found

    Estradiol-regulated microRNAs control estradiol response in breast cancer cells.

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    Estradiol (E2) regulates gene expression at the transcriptional level by functioning as a ligand for estrogen receptor alpha (ERalpha) and estrogen receptor beta (ERbeta). E2-inducible proteins c-Myc and E2Fs are required for optimal ERalpha activity and secondary estrogen responses, respectively. We show that E2 induces 21 microRNAs and represses seven microRNAs in MCF-7 breast cancer cells; these microRNAs have the potential to control 420 E2-regulated and 757 non-E2-regulated mRNAs at the post-transcriptional level. The serine/threonine kinase, AKT, alters E2-regulated expression of microRNAs. E2 induced the expression of eight Let-7 family members, miR-98 and miR-21 microRNAs; these microRNAs reduced the levels of c-Myc and E2F2 proteins. Dicer, a ribonuclease III enzyme required for microRNA processing, is also an E2-inducible gene. Several E2-regulated microRNA genes are associated with ERalpha-binding sites or located in the intragenic region of estrogen-regulated genes. We propose that the clinical course of ERalpha-positive breast cancers is dependent on the balance between E2-regulated tumor-suppressor microRNAs and oncogenic microRNAs. Additionally, our studies reveal a negative-regulatory loop controlling E2 response through microRNAs as well as differences in E2-induced transcriptome and proteome

    Interplay between estrogen receptor and AKT in estradiol-induced alternative splicing.

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    BACKGROUND: Alternative splicing is critical for generating complex proteomes in response to extracellular signals. Nuclear receptors including estrogen receptor alpha (ERα) and their ligands promote alternative splicing. The endogenous targets of ERα:estradiol (E2)-mediated alternative splicing and the influence of extracellular kinases that phosphorylate ERα on E2-induced splicing are unknown. METHODS: MCF-7 and its anti-estrogen derivatives were used for the majority of the assays. CD44 mini gene was used to measure the effect of E2 and AKT on alternative splicing. ExonHit array analysis was performed to identify E2 and AKT-regulated endogenous alternatively spliced apoptosis-related genes. Quantitative reverse transcription polymerase chain reaction was performed to verify alternative splicing. ERα binding to alternatively spliced genes was verified by chromatin immunoprecipitation assay. Bromodeoxyuridine incorporation-ELISA and Annexin V labeling assays were done to measure cell proliferation and apoptosis, respectively. RESULTS: We identified the targets of E2-induced alternative splicing and deconstructed some of the mechanisms surrounding E2-induced splicing by combining splice array with ERα cistrome and gene expression array. E2-induced alternatively spliced genes fall into at least two subgroups: coupled to E2-regulated transcription and ERα binding to the gene without an effect on rate of transcription. Further, AKT, which phosphorylates both ERα and splicing factors, influenced ERα:E2 dependent splicing in a gene-specific manner. Genes that are alternatively spliced include FAS/CD95, FGFR2, and AXIN-1. E2 increased the expression of FGFR2 C1 isoform but reduced C3 isoform at mRNA level. E2-induced alternative splicing of FAS and FGFR2 in MCF-7 cells correlated with resistance to FAS activation-induced apoptosis and response to keratinocyte growth factor (KGF), respectively. Resistance of MCF-7 breast cancer cells to the anti-estrogen tamoxifen was associated with ERα-dependent overexpression of FGFR2, whereas resistance to fulvestrant was associated with ERα-dependent isoform switching, which correlated with altered response to KGF. CONCLUSION: E2 may partly alter cellular proteome through alternative splicing uncoupled to its effects on transcription initiation and aberration in E2-induced alternative splicing events may influence response to anti-estrogens.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

    Genome-Wide Association Study Identifies Two Novel Regions at 11p15.5-p13 and 1p31 with Major Impact on Acute-Phase Serum Amyloid A

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    Elevated levels of acute-phase serum amyloid A (A-SAA) cause amyloidosis and are a risk factor for atherosclerosis and its clinical complications, type 2 diabetes, as well as various malignancies. To investigate the genetic basis of A-SAA levels, we conducted the first genome-wide association study on baseline A-SAA concentrations in three population-based studies (KORA, TwinsUK, Sorbs) and one prospective case cohort study (LURIC), including a total of 4,212 participants of European descent, and identified two novel genetic susceptibility regions at 11p15.5-p13 and 1p31. The region at 11p15.5-p13 (rs4150642; p = 3.20×10−111) contains serum amyloid A1 (SAA1) and the adjacent general transcription factor 2 H1 (GTF2H1), Hermansky-Pudlak Syndrome 5 (HPS5), lactate dehydrogenase A (LDHA), and lactate dehydrogenase C (LDHC). This region explains 10.84% of the total variation of A-SAA levels in our data, which makes up 18.37% of the total estimated heritability. The second region encloses the leptin receptor (LEPR) gene at 1p31 (rs12753193; p = 1.22×10−11) and has been found to be associated with CRP and fibrinogen in previous studies. Our findings demonstrate a key role of the 11p15.5-p13 region in the regulation of baseline A-SAA levels and provide confirmative evidence of the importance of the 1p31 region for inflammatory processes and the close interplay between A-SAA, leptin, and other acute-phase proteins

    AKT Alters Genome-Wide Estrogen Receptor α Binding and Impacts Estrogen Signaling in Breast Cancer▿ †

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    Estrogen regulates several biological processes through estrogen receptor α (ERα) and ERβ. ERα-estrogen signaling is additionally controlled by extracellular signal activated kinases such as AKT. In this study, we analyzed the effect of AKT on genome-wide ERα binding in MCF-7 breast cancer cells. Parental and AKT-overexpressing cells displayed 4,349 and 4,359 ERα binding sites, respectively, with ∼60% overlap. In both cell types, ∼40% of estrogen-regulated genes associate with ERα binding sites; a similar percentage of estrogen-regulated genes are differentially expressed in two cell types. Based on pathway analysis, these differentially estrogen-regulated genes are linked to transforming growth factor β (TGF-β), NF-κB, and E2F pathways. Consistent with this, the two cell types responded differently to TGF-β treatment: parental cells, but not AKT-overexpressing cells, required estrogen to overcome growth inhibition. Combining the ERα DNA-binding pattern with gene expression data from primary tumors revealed specific effects of AKT on ERα binding and estrogen-regulated expression of genes that define prognostic subgroups and tamoxifen sensitivity of ERα-positive breast cancer. These results suggest a unique role of AKT in modulating estrogen signaling in ERα-positive breast cancers and highlights how extracellular signal activated kinases can change the landscape of transcription factor binding to the genome

    Subcellular Localization of Activated AKT in Estrogen Receptor- and Progesterone Receptor-Expressing Breast Cancers : Potential Clinical Implications

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    Activated v-AKT murine thymoma viral oncogene homolog 1 (AKT)/protein kinase B (PKB) kinase (pAKT) is localized to the plasma membrane, cytoplasm, and/or nucleus in 50% of cancers. The clinical importance of pAKT localization and the mechanism(s) controlling this compartmentalization are unknown. In this study, we examined nuclear and cytoplasmic phospho-AKT (pAKT) expression by immunohistochemistry in a breast cancer tissue microarray (n = 377) with ≈15 years follow-up and integrated these data with the expression of estrogen receptor (ER)α, progesterone receptor (PR), and FOXA1. Nuclear localization of pAKT (nuclear-pAKT) was associated with long-term survival (P = 0.004). Within the ERα+/PR+ subgroup, patients with nuclear-pAKT positivity had better survival than nuclear-pAKT–negative patients (P ≤ 0.05). The association of nuclear-pAKT with the ERα+/PR+ subgroup was validated in an independent cohort (n = 145). TCL1 family proteins regulate nuclear transport and/or activation of AKT. TCL1B is overexpressed in ERα-positive compared with ERα-negative breast cancers and in lung metastasis–free breast cancers. Therefore, we examined the possible control of TCL1 family member(s) expression by the estrogen:ERα pathway. Estradiol increased TCL1B expression and increased nuclear-pAKT levels in breast cancer cells; short- interfering RNA against TCL1B reduced nuclear-pAKT. Overexpression of nuclear-targeted AKT1 in MCF-7 cells increased cell proliferation without compromising sensitivity to the anti-estrogen, tamoxifen. These results suggest that subcellular localization of activated AKT plays a significant role in determining its function in breast cancer, which in part is dependent on TCL1B expression

    Reporting guidelines for human microbiome research: the STORMS checklist

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    The particularly interdisciplinary nature of human microbiome research makes the organization and reporting of results spanning epidemiology, biology, bioinformatics, translational medicine and statistics a challenge. Commonly used reporting guidelines for observational or genetic epidemiology studies lack key features specific to microbiome studies. Therefore, a multidisciplinary group of microbiome epidemiology researchers adapted guidelines for observational and genetic studies to culture-independent human microbiome studies, and also developed new reporting elements for laboratory, bioinformatics and statistical analyses tailored to microbiome studies. The resulting tool, called 'Strengthening The Organization and Reporting of Microbiome Studies' (STORMS), is composed of a 17-item checklist organized into six sections that correspond to the typical sections of a scientific publication, presented as an editable table for inclusion in supplementary materials. The STORMS checklist provides guidance for concise and complete reporting of microbiome studies that will facilitate manuscript preparation, peer review, and reader comprehension of publications and comparative analysis of published results. The STORMS tool provides guidance for concise and complete reporting of microbiome studies to facilitate manuscript preparation, peer review, reader comprehension of publications, and comparative analysis of published results
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