Identification of a hormone-regulated dynamic nuclear actin network associated with estrogen receptor alpha in human breast cancer cell nuclei.

Estrogen receptor alpha (ERalpha) is a modular protein of the steroid/nuclear receptor family of transcriptional regulators that upon binding to the hormone undergoes structural changes, resulting in its nuclear translocation and docking to specific chromatin sites. In the nucleus, ERalpha assembles in multiprotein complexes that act as final effectors of estrogen signaling to the genome through chromatin remodeling and epigenetic modifications, leading to dynamic and coordinated regulation of hormone-responsive genes. Identification of the molecular partners of ERalpha and understanding their combinatory interactions within functional complexes is a prerequisite to define the molecular basis of estrogen control of cell functions. To this end, affinity purification was applied to map and characterize the ERalpha interactome in hormone-responsive human breast cancer cell nuclei. MCF-7 cell clones expressing human ERalpha fused to a tandem affinity purification tag were generated and used to purify native nuclear ER-containing complexes by IgG-Sepharose affinity chromatography and glycerol gradient centrifugation. Purified complexes were analyzed by two-dimensional DIGE and mass spectrometry, leading to the identification of a ligand-dependent multiprotein complex comprising beta-actin, myosins, and several proteins involved in actin filament organization and dynamics and/or known to participate in actin-mediated regulation of gene transcription, chromatin dynamics, and ribosome biogenesis. Time course analyses indicated that complexes containing ERalpha and actin are assembled in the nucleus early after receptor activation by ligands, and gene knockdown experiments showed that gelsolin and the nuclear isoform of myosin 1c are key determinants for assembly and/or stability of these complexes. Based on these results, we propose that the actin network plays a role in nuclear ERalpha actions in breast cancer cells, including coordinated regulation of target gene activity, spatial and functional reorganization of chromatin, and ribosome biogenesis.

Global analysis of estrogen receptor beta binding to breast cancer cell genome reveals an extensive interplay with estrogen receptor alpha for target gene regulation.

BACKGROUND: Estrogen receptors alpha (ERα) and beta (ERß) are transcription factors (TFs) that mediate estrogen signaling and define the hormone-responsive phenotype of breast cancer (BC). The two receptors can be found co-expressed and play specific, often opposite, roles, with ERß being able to modulate the effects of ERα on gene transcription and cell proliferation. ERß is frequently lost in BC, where its presence generally correlates with a better prognosis of the disease. The identification of the genomic targets of ERß in hormone-responsive BC cells is thus a critical step to elucidate the roles of this receptor in estrogen signaling and tumor cell biology. RESULTS: Expression of full-length ERß in hormone-responsive, ERα-positive MCF-7 cells resulted in a marked reduction in cell proliferation in response to estrogen and marked effects on the cell transcriptome. By ChIP-Seq we identified 9702 ERß and 6024 ERα binding sites in estrogen-stimulated cells, comprising sites occupied by either ERß, ERα or both ER subtypes. A search for TF binding matrices revealed that the majority of the binding sites identified comprise one or more Estrogen Response Element and the remaining show binding matrixes for other TFs known to mediate ER interaction with chromatin by tethering, including AP2, E2F and SP1. Of 921 genes differentially regulated by estrogen in ERß+ vs ERß- cells, 424 showed one or more ERß site within 10 kb. These putative primary ERß target genes control cell proliferation, death, differentiation, motility and adhesion, signal transduction and transcription, key cellular processes that might explain the biological and clinical phenotype of tumors expressing this ER subtype. ERß binding in close proximity of several miRNA genes and in the mitochondrial genome, suggests the possible involvement of this receptor in small non-coding RNA biogenesis and mitochondrial genome functions. CONCLUSIONS: Results indicate that the vast majority of the genomic targets of ERß can bind also ERα, suggesting that the overall action of ERß on the genome of hormone-responsive BC cells depends mainly on the relative concentration of both ERs in the cell.

Estrogen receptor alpha controls a gene network in luminal-like breast cancer cells comprising multiple transcription factors and microRNAs.

Luminal-like breast tumor cells express estrogen receptor alpha (ERalpha), a member of the nuclear receptor family of ligand-activated transcription factors that controls their proliferation, survival, and functional status. To identify the molecular determinants of this hormone-responsive tumor phenotype, a comprehensive genome-wide analysis was performed in estrogen stimulated MCF-7 and ZR-75.1 cells by integrating time-course mRNA expression profiling with global mapping of genomic ERalpha binding sites by chromatin immunoprecipitation coupled to massively parallel sequencing, microRNA expression profiling, and in silico analysis of transcription units and receptor binding regions identified. All 1270 genes that were found to respond to 17beta-estradiol in both cell lines cluster in 33 highly concordant groups, each of which showed defined kinetics of RNA changes. This hormone-responsive gene set includes several direct targets of ERalpha and is organized in a gene regulation cascade, stemming from ligand-activated receptor and reaching a large number of downstream targets via AP-2gamma, B-cell activating transcription factor, E2F1 and 2, E74-like factor 3, GTF2IRD1, hairy and enhancer of split homologue-1, MYB, SMAD3, RARalpha, and RXRalpha transcription factors. MicroRNAs are also integral components of this gene regulation network because miR-107, miR-424, miR-570, miR-618, and miR-760 are regulated by 17beta-estradiol along with other microRNAs that can target a significant number of transcripts belonging to one or more estrogen-responsive gene clusters.

Pharmacogenomics and analogues of the antitumour agent N6-isopentenyladenosine.

N(6)-isopentenyladenosine (i(6)A), a member of the cytokinin family of plant hormones, has potent in vitro antitumour activity in different types of human epithelial cancer cell lines. Gene expression profile analysis of i(6)A-treated cells revealed induction of genes (e.g., PPP1R15A, DNAJB9, DDIT3, and HBP1) involved in the negative regulation of cell cycle progression and reportedly up-regulated during cell cycle arrest in stress conditions. Of 6 i(6)A analogues synthesized, only the 1 with a saturated double bond of the isopentenyl side chain had in vitro antitumour activity, although weaker than that of i(6)A, suggesting that i(6)A biological activity is highly linked to its structure. In vivo analysis of i(6)A and the active analogue revealed no significant inhibition of cancer cell growth in mice by either reagent. Thus, although i(6)A may inhibit cell proliferation by regulating the cell cycle, further studies are needed to identify active analogues potentially useful in vivo.

Time-course analysis of genome-wide gene expression data from hormone-responsive human breast cancer cells.

BACKGROUND: Microarray experiments enable simultaneous measurement of the expression levels of virtually all transcripts present in cells, thereby providing a 'molecular picture' of the cell state. On the other hand, the genomic responses to a pharmacological or hormonal stimulus are dynamic molecular processes, where time influences gene activity and expression. The potential use of the statistical analysis of microarray data in time series has not been fully exploited so far, due to the fact that only few methods are available which take into proper account temporal relationships between samples. RESULTS: We compared here four different methods to analyze data derived from a time course mRNA expression profiling experiment which consisted in the study of the effects of estrogen on hormone-responsive human breast cancer cells. Gene expression was monitored with the innovative Illumina BeadArray platform, which includes an average of 30-40 replicates for each probe sequence randomly distributed on the chip surface. We present and discuss the results obtained by applying to these datasets different statistical methods for serial gene expression analysis. The influence of the normalization algorithm applied on data and of different parameter or threshold choices for the selection of differentially expressed transcripts has also been evaluated. In most cases, the selection was found fairly robust with respect to changes in parameters and type of normalization. We then identified which genes showed an expression profile significantly affected by the hormonal treatment over time. The final list of differentially expressed genes underwent cluster analysis of functional type, to identify groups of genes with similar regulation dynamics. CONCLUSIONS: Several methods for processing time series gene expression data are presented, including evaluation of benefits and drawbacks of the different methods applied. The resulting protocol for data analysis was applied to characterization of the gene expression changes induced by estrogen in human breast cancer ZR-75.1 cells over an entire cell cycle.

Quantitative expression profiling of highly degraded RNA from formalin-fixed, paraffin-embedded breast tumor biopsies by oligonucleotide microarrays.

Microarray-based gene expression profiling is well suited for parallel quantitative analysis of large numbers of RNAs, but its application to cancer biopsies, particularly formalin-fixed, paraffin-embedded (FFPE) archived tissues, is limited by the poor quality of the RNA recovered. This represents a serious drawback, as FFPE tumor tissue banks are available with clinical and prognostic annotations, which could be exploited for molecular profiling studies, provided that reliable analytical technologies are found. We applied and evaluated here a microarray-based cDNA-mediated annealing, selection, extension and ligation (DASL) assay for analysis of 502 mRNAs in highly degraded total RNA extracted from cultured cells or FFPE breast cancer (MT) biopsies. The study included quantitative and qualitative comparison of data obtained by analysis of the same RNAs with genome-wide oligonucleotide microarrays vs DASL arrays and, by DASL, before and after extensive in vitro RNA fragmentation. The DASL-based expression profiling assay applied to RNA extracted from MCF-7 cells, before or after 24 h stimulation with a mitogenic dose of 17beta-estradiol, consistently allowed to detect hormone-induced gene expression changes following extensive RNA degradation in vitro. Comparable results where obtained with tumor RNA extracted from FFPE MT biopsies (6 to 19 years old). The method proved itself sensitive, reproducible and accurate, when compared to results obtained by microarray analysis of RNA extracted from snap-frozen tissue of the same tumor.

Identification of new genes associated with breast cancer progression by gene expression analysis of predefined sets of neoplastic tissues.

Gene expression profiles were studied by microarray analysis in 2 sets of archival breast cancer tissues from patients with distinct clinical outcome. Seventy-seven differentially expressed genes were identified when comparing 30 cases with relapse and 30 cases without relapse within 72 months from surgery. These genes had a specific ontological distribution and some of them have been linked to breast cancer in previous studies: AIB1, the two keratin genes KRT5 and KRT15, RAF1, WIF1 and MSH6. Seven out of 77 differentially expressed genes were selected and analyzed by qRT-PCR in 127 cases of breast cancer. The expression levels of 6 upregulated genes (CKMT1B, DDX21, PRKDC, PTPN1, SLPI, YWHAE) showed a significant association to both disease-free and overall survival. Multivariate analysis using the significant factors (i.e., estrogen receptor and lymph node status) as covariates confirmed the association with survival. There was no correlation between the expression level of these genes and other clinical parameters. In contrast, SERPINA3, the only downregulated gene examined, was not associated with survival, but correlated with steroid receptor status. An indirect validation of our genes was provided by calculating their association with survival in 3 publicly available microarray datasets. CKMT1B expression was an independent prognostic marker in all 3 datasets, whereas other genes confirmed their association with disease-free survival in at least 1 dataset. This work provides a novel set of genes that could be used as independent prognostic markers and potential drug targets for breast cancer.

Estrogens and progesterone promote persistent CCND1 gene activation during G1 by inducing transcriptional derepression via c-Jun/c-Fos/estrogen receptor (progesterone receptor) complex assembly to a distal regulatory element and recruitment of cyclin D1 to its own gene promoter.

Transcriptional activation of the cyclin D1 gene (CCND1) plays a pivotal role in G(1)-phase progression, which is thereby controlled by multiple regulatory factors, including nuclear receptors (NRs). Appropriate CCND1 gene activity is essential for normal development and physiology of the mammary gland, where it is regulated by ovarian steroids through a mechanism(s) that is not fully elucidated. We report here that CCND1 promoter activation by estrogens in human breast cancer cells is mediated by recruitment of a c-Jun/c-Fos/estrogen receptor alpha complex to the tetradecanoyl phorbol acetate-responsive element of the gene, together with Oct-1 to a site immediately adjacent. This process coincides with the release from the same DNA region of a transcriptional repressor complex including Yin-Yang 1 (YY1) and histone deacetylase 1 and is sufficient to induce the assembly of the basal transcription machinery on the promoter and to lead to initial cyclin D1 accumulation in the cell. Later on in estrogen stimulation, the cyclin D1/Cdk4 holoenzyme associates with the CCND1 promoter, where E2F and pRb can also be found, contributing to the long-lasting gene enhancement required to drive G(1)-phase completion. Interestingly, progesterone triggers similar regulatory events through its own NRs, suggesting that the gene regulation cascade described here represents a crossroad for the transcriptional control of G(1)-phase progression by different classes of NRs.

Influence of estrogens and antiestrogens on the expression of selected hormone-responsive genes.

Estrogen exerts a primary regulatory role on a wide variety of physiological processes in different tissues and organs. Agonistic ad antagonistic compounds are widely used in human health and, therefore, a deep understanding of their mechanisms of action at the molecular level is mandatory. The effect of 17beta-estradiol and three antiestrogenic drugs, comprising two selective estrogen receptor modulator (SERM, 4-OH-tamoxifen, Raloxifene) and the pure antiestrogen ICI 182,780, on genome-wide gene expression levels was evaluated in breast carcinoma cell lines by DNA microarray analysis. Different clusters of genes, showing specific coregulation patterns, were found. First, several groups of genes displaying temporal-specific up- or down-regulation were characterized. Second, clusters of genes responding to different antiestrogenic drugs in either antagonstic or agonistic fashion, were found. Genes responding specifically to antiestrogens, but not to estrogen, were also identified. In addition, each individual compound exhibited a very specific gene regulation. Bioinformatic analysis was applied to the regulatory sequences of different groups of genes and confirmed that specific pathways and secondary responses are activated at each temporal point and in response to different compounds. Our results underline the complexity of genomic responses to estrogen in breast cancer cells and strongly suggest that the molecular characterization of estrogen agonists and antagonists used in human therapy should be carefully studied.

Distinct signaling pathways mediate stimulation of cell cycle progression and prevention of apoptotic cell death by estrogen in rat pituitary tumor PR1 cells.

Estrogens control cell growth and viability in target cells via an interplay of genomic and extragenomic pathways not yet elucidated. Here, we show evidence that cell proliferation and survival are differentially regulated by estrogen in rat pituitary tumor PR1 cells. Pico- to femtomolar concentrations of 17beta-estradiol (E2) are sufficient to foster PR1 cell proliferation, whereas nanomolar concentrations of the same are needed to prevent cell death that occurs at a high rate in these cells in the absence of hormone. Activation of endogenous (PRL) or transfected estrogen-responsive genes occurs at the same, higher concentrations of E2 required to promote cell survival, whereas stimulation of cyclin D3 expression and DNA synthesis occur at lower E2 concentrations. Similarly, the pure antiestrogen ICI 182,780 inhibits estrogen response element-dependent trans-activation and cell death more effectively than cyclin-cdk activity, G1-S transition, or DNA synthesis rate. In antiestrogen-treated and/or estrogen-deprived cells, death is due predominantly to apoptosis. Estrogen-induced cell survival, but not E2-dependent cell cycle progression, can be prevented by an inhibitor of c-Src kinase or by blockade of the mitogen-activated protein kinase kinase/extracellular signal-regulated kinase signaling pathway. These data indicate the coexistence of two distinguishable estrogen signaling pathways in PR1 cells, characterized by different functions and sensitivity to hormones and antihormones.

A genomic view of estrogen actions in human breast cancer cells by expression profiling of the hormone-responsive transcriptome.

Estrogen controls key cellular functions of responsive cells including the ability to survive, replicate, communicate and adapt to the extracellular milieu. Changes in the expression of 8400 genes were monitored here by cDNA microarray analysis during the first 32 h of human breast cancer (BC) ZR-75.1 cell stimulation with a mitogenic dose of 17beta-estradiol, a timing which corresponds to completion of a full mitotic cycle in hormone-stimulated cells. Hierarchical clustering of 344 genes whose expression either increases or decreases significantly in response to estrogen reveals that the gene expression program activated by the hormone in these cells shows 8 main patterns of gene activation/inhibition. This newly identified estrogen-responsive transcriptome represents more than a simple cell cycle response, as only a few affected genes belong to the transcriptional program of the cell division cycle of eukaryotes, or showed a similar expression profile in other mitogen-stimulated human cells. Indeed, based on the functions assigned to the products of the genes they control, estrogen appears to affect several key features of BC cells, including their metabolic status, proliferation, survival, differentiation and resistance to stress and chemotherapy, as well as RNA and protein synthesis, maturation and turn-over rates. Interestingly, the estrogen-responsive transcriptome does not appear randomly interspersed in the genome. In chromosome 17, for example, a site particularly rich in genes activated by the hormone, physical association of co-regulated genes in clusters is evident in several instances, suggesting the likely existence of estrogen-responsive domains in the human genome.

Effects of oestrogen on microRNA expression in hormone-responsive breast cancer cells.

Oestrogen receptor alpha (ERα) is a ligand-dependent transcription factor that mediates oestrogen effects in hormone-responsive cells. Following oestrogenic activation, ERα directly regulates the transcription of target genes via DNA binding. MicroRNAs (miRNAs) represent a class of small noncoding RNAs that function as negative regulators of protein-coding gene expression. They are found aberrantly expressed or mutated in cancer, suggesting their crucial role as either oncogenes or tumour suppressor genes. Here, we analysed changes in miRNA expression in response to oestrogen in hormone-responsive breast cancer MCF-7 and ZR-75.1 cells by microarray-mediated expression profiling. This led to the identification of 172 miRNAs up- or down-regulated by ERα in response to 17ß-oestradiol, of which 52 are similarly regulated by the hormone in the two cell models investigated. To identify mechanisms by which ERα exerts its effects on oestrogen-responsive miRNA genes, the oestrogen-dependent miRNA expression profiles were integrated with global in vivo ERα binding site mapping in the genome by ChIP-Seq. In addition, data from miRNA and messenger RNA (mRNA) expression profiles obtained under identical experimental conditions were compared to identify relevant miRNA target transcripts. Results show that miRNAs modulated by ERα represent a novel genomic pathway to impact oestrogen-dependent processes that affect hormone-responsive breast cancer cell behaviour. MiRNome analysis in tumour tissues from breast cancer patients confirmed a strong association between expression of these small RNAs and clinical outcome of the disease, although this appears to involve only marginally the oestrogen-regulated miRNAs identified in this study.

Molecular bases of copper and iron deficiency-associated dyslipidemia: a microarray analysis of the rat intestinal transcriptome.

As essential cofactor in many proteins and redox enzymes, copper and iron are involved in a wide range of biological processes. Mild dietary deficiency of metals represents an underestimated problem for human health, because it does not cause clear signs and clinical symptoms, but it is associated to long-term deleterious effects in cardiovascular system and alterations in lipid metabolism. The aim of this work was to study the biological processes significantly affected by mild dietary deficiency of both metals in rat intestine, in order to better understand the molecular bases of the systemic metabolic alterations, as hypercholesterolemia and hypertriglyceridemia observed in copper-deficient rats. A gene-microarray differential analysis was carried out on the intestinal transcriptome of copper- and iron-deficient rats, thus highlighting the biological processes significantly modulated by the dietary restrictions. The gene array analysis showed a down-regulation of genes involved in mitochondrial and peroxisomal fatty acids beta-oxidation and an up-regulation of genes involved in plasmatic cholesterol transport (apoprotein E and lecithin:cholesterol acyltransferase) in copper deficiency. Furthermore, a severe down-regulation of ApoH was pointed out in iron-deficient animals.

Comparative gene expression profiling reveals partially overlapping but distinct genomic actions of different antiestrogens in human breast cancer cells.

Antiestrogens used for breast cancer (BC) treatment differ among each other for the ability to affect estrogen receptor (ER) activity and thereby inhibit hormone-responsive cell functions and viability. We used high-density cDNA microarrays for a comprehensive definition of the gene pathways affected by 17beta-estradiol (E2), ICI 182,780 (ICI), 4OH-tamoxifen (Tamoxifen), and raloxifene (RAL) in ER-positive ZR-75.1 cells, a suitable model to investigate estrogen and antiestrogen actions in hormone-responsive BC. The expression of 601 genes was significantly affected by E2 in these cells; in silico analysis reveals that 86 among them include one or more potential ER binding site within or near the promoter and that the binding site signatures for E2F-1, NF-Y, and NRF-1 transcription factors are significantly enriched in the promoters of genes induced by estrogen treatment, while those for CAC-binding protein and LF-A1 in those repressed by the hormone, pointing to novel transcriptional effectors of secondary responses to estrogen in BC cells. Interestingly, expression of 176 E2-regulated mRNAs was unaffected by any of the antiestrogens tested, despite the fact that under the same conditions the transcriptional and cell cycle stimulatory activities of ER were inhibited. On the other hand, of 373 antiestrogen-responsive genes identified here, 52 were unresponsive to estrogen and 25% responded specifically to only one of the compounds tested, revealing non-overlapping and clearly distinguishable effects of the different antiestrogens in BC cells. As some of these differences reflect specificities of the mechanism of action of the antiestrogens tested, we propose to exploit this gene set for characterization of novel hormonal antagonists and selective estrogen receptor modulators (SERMs) and as a tool for testing new associations of antiestrogens, more effective against BC.

Molecular identification of ERalpha-positive breast cancer cells by the expression profile of an intrinsic set of estrogen regulated genes.

Estrogens exert a key biological role in mammary gland epithelial cells and promote breast carcinogenesis and tumor progression. We recently identified a new large set of estrogen responsive genes from breast cancer (BC) cells by DNA microarray analysis of the gene expression profiles induced by 17beta-estradiol in ZR-75.1 and MCF-7 cells. The purpose of the present study was to test whether the expression pattern of hormone regulated genes from this set identifies estrogen receptor (ERalpha) positive, hormone responsive BC cells. To this aim, we carried out in silico metanalysis of ERalpha positive and ERalpha negative human BC cell line transcriptomes, focusing on two sets of 171 and 218 estrogen responsive genes, respectively. Results show that estrogen dependent gene activity in hormone responsive BC cells is significantly different from that of non-responsive cells and, alone, allows to discriminate these two cellular phenotypes. Indeed, we have identified 61 genes whose expression profile specifically marks ERalpha positive BC cells, suggesting that this gene set may be exploited for phenotypic characterization of breast tumors. This possibility was tested with data obtained by gene expression profiling of BC surgical samples, where the ERalpha positive phenotypes were highlighted by the expression profile of a subset of 27 such hormone responsive genes and four additional BC marker genes, not including ERs. These results provide direct evidence that the expression pattern of a limited number of estrogen responsive genes can be exploited to assess the estrogen signaling status of BC cells both in vitro and ex-vivo.