help button home button Endocrine Society Endocrinology
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Endocrinology, doi:10.1210/en.2003-0567
This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow All Versions of this Article:
144/10/4562    most recent
Author Manuscript (PDF)
Right arrow Purchase Article
Right arrow View Shopping Cart
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow Request Copyright Permission
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Frasor, J.
Right arrow Articles by Katzenellenbogen, B. S.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Frasor, J.
Right arrow Articles by Katzenellenbogen, B. S.
Endocrinology Vol. 144, No. 10 4562-4574
Copyright © 2003 by The Endocrine Society

Profiling of Estrogen Up- and Down-Regulated Gene Expression in Human Breast Cancer Cells: Insights into Gene Networks and Pathways Underlying Estrogenic Control of Proliferation and Cell Phenotype

Jonna Frasor, Jeanne M. Danes, Barry Komm, Ken C. N. Chang, C. Richard Lyttle and Benita S. Katzenellenbogen

Department of Molecular and Integrative Physiology, University of Illinois (J.F., J.M.D., B.S.K.), Urbana, Illinois 61801; and Women’s Health Research Institute, Wyeth Research (B.K., K.C.N.C., C.R.L.), Collegeville, Pennsylvania 19426

Address all correspondence and requests for reprints to: Dr. Benita S. Katzenellenbogen, Department of Molecular and Integrative Physiology, University of Illinois, 524 Burrill Hall, 407 South Goodwin Avenue, Urbana, Illinois 61801-3704. E-mail: katzenel{at}life.uiuc.edu.


   Abstract
Top
 Abstract
Introduction
 Materials and Methods
 Results
 Discussion
 References
 
Estrogens are known to regulate the proliferation of breast cancer cells and to alter their cytoarchitectural and phenotypic properties, but the gene networks and pathways by which estrogenic hormones regulate these events are only partially understood. We used global gene expression profiling by Affymetrix GeneChip microarray analysis, with quantitative PCR verification in many cases, to identify patterns and time courses of genes that are either stimulated or inhibited by estradiol (E2) in estrogen receptor (ER)-positive MCF-7 human breast cancer cells. Of the >12,000 genes queried, over 400 showed a robust pattern of regulation, and, notably, the majority (70%) were down-regulated. We observed a general up-regulation of positive proliferation regulators, including survivin, multiple growth factors, genes involved in cell cycle progression, and regulatory factor-receptor loops, and the down-regulation of transcriptional repressors, such as Mad4 and JunB, and of antiproliferative and proapoptotic genes, including B cell translocation gene-1 and -2, cyclin G2, BCL-2 antagonist/killer 1, BCL 2-interacting killer, caspase 9, and TGFß family growth inhibitory factors. These together likely contribute to the stimulation of proliferation and the suppression of apoptosis by E2 in these cells. Of interest, E2 appeared to modulate its own activity through the enhanced expression of genes involved in prostaglandin E production and signaling, which could lead to an increase in aromatase expression and E2 production, as well as the decreased expression of several nuclear receptor coactivators that could impact ER activity. Our studies highlight the diverse gene networks and metabolic and cell regulatory pathways through which this hormone operates to achieve its widespread effects on breast cancer cells.


   Introduction
Top
 Abstract
 Introduction
Materials and Methods
 Results
 Discussion
 References
 
ESTROGENS REGULATE DIVERSE physiological processes in reproductive tissues and in mammary, cardiovascular, bone, liver, and brain tissues. The effects of estrogens are mediated via its receptors [estrogen receptor (ER)], which are members of the nuclear receptor superfamily of ligand-activated transcription factors that control these physiological processes, in large part through the regulation of gene transcription (1, 2, 3).

The ER uses multiple mechanisms to either activate or repress transcription of its target genes. These mechanisms include 1) direct interaction of the ligand-occupied receptor with DNA at estrogen response elements, followed by recruitment of transcriptional coregulator or mediator complexes; 2) interaction of the ligand-occupied ER with other transcription factors, such as activating protein-1 (AP-1) (4), Sp1 (5), or nuclear factor-{kappa}B (NF-{kappa}B) (6); or 3) indirect modulation of gene transcription via sequestration of general/common transcriptional components (7, 8). To add a further layer of complexity, the ability of ER to regulate transcription through these various mechanisms appears to be cell type specific, perhaps due to differences in the complement of transcriptional coregulatory factors available in each cell type (9, 10, 11). Also, transcriptional regulation is dependent upon the nature of the ligand, with various natural and synthetic selective ER modulators (SERMs) acting as either ER agonists or antagonists through each of these various mechanisms (12, 13, 14, 15).

With the sequencing of the human genome as well as the advent of microarray technology, it is now possible to investigate the complexities of ER-mediated gene transcription on a more global scale rather than one estrogen-responsive target gene at a time. One area where this would be of great importance is in the study of the regulation of gene expression by both estrogens and SERMs, such as tamoxifen or raloxifene, in ER-positive breast cancer. The effects of estradiol (E2) on increased breast cancer cell proliferation and tumorigenesis have been well documented, and several recent studies using microarray techniques have begun to document the gene expression profiles in breast cancer. Most of these studies have focused on identifying genes overexpressed in breast cancer (16) or patterns of gene expression associated with clinical outcome or prognosis (17, 18), responses to chemotherapy or drug resistance (19), tumor aggressiveness (20), or classification of primary tumors (21, 22, 23). The role of ER expression has also been addressed in several studies in which distinct gene expression patterns associated with ER status have been identified (24, 25, 26).

Despite these recent investigations, the exact role of estrogen-mediated gene regulation in ER-positive breast cancer and the manner in which these changes in gene expression affect breast cancer proliferation and progression are far from clear. Relatively few microarray studies have examined the role of estrogens in regulating gene expression, and the studies that have been performed in breast cancer cells have been on a relatively limited scale, with few genes examined or over a limited time course of hormone treatment (27, 28, 29, 30).

In this study the ER-positive breast cancer cell line MCF-7 was treated with E2 for different times up to 48 h, and gene expression profiling was carried out using the Affymetrix human GeneChip U95A, which contains oligonucleotide probes for approximately 12,000 human genes. Our findings reveal that E2 regulates gene expression with several distinct time-course patterns, that almost 70% of the genes regulated by E2 are, in fact, down-regulated, and that numerous cell cycle-associated genes as well as expression of novel transcription factors, receptors, and signaling pathways are modulated by E2, many of which could play roles in mediating the effects of E2 on breast cancer proliferation and cell phenotype.


   Materials and Methods
Top
 Abstract
 Introduction
 Materials and Methods
Results
 Discussion
 References
 
Cell culture and RNA extraction
The MCF-7 cell line was routinely maintained in MEM (Sigma-Aldrich Corp., St. Louis, MO) supplemented with 5% calf serum (HyClone, Logan, UT). Four days before E2 treatment, cells were switched to phenol red-free MEM containing 5% charcoal-dextran-treated calf serum. Medium was changed on d 2 and 4 of culture, and then cells were treated with 10 nM E2 (Sigma-Aldrich Corp.) for 4, 8, 24, or 48 h. The time-course experiment was repeated three times, with two of the three replicates used for microarray analysis and all three used for real-time PCR. In experiments using cycloheximide (CHX), CHX at 10 µg/ml was present throughout the 24-h period of exposure to E2 or control (0.1% ethanol) vehicle. Total RNA was prepared using TRIzol reagent (Invitrogen, Carlsbad, CA) according to the manufacturer’s instructions. RNA was further purified using RNeasy columns (Qiagen, Valencia, CA) and treatment with ribonuclease-free deoxyribonuclease I (Qiagen).

GeneChip microarrays
Total RNA was used to generate cRNA, which was labeled with biotin according to techniques recommended by Affymetrix (Santa Clara, CA). cRNA was then hybridizd to Affymetrix Hu95A GeneChips, which contain approximately 12,000 human oligonucleotide probe sets. After washing, the chips were scanned and analyzed using MicroArray Suite 5.0 (Affymetrix). Average intensities for each GeneChip were globally scaled to a target intensity of 150. Further analysis was performed using GeneSpring software version 5.0.1 (Silicon Genetics, Redwood City, CA) to obtain fold change and P values for each gene at each time point relative to untreated control.

Identification of E2-regulated genes
To identify genes significantly regulated by E2 treatment, a confidence score (CS) was calculated for each gene at each time point of E2 treatment, based on the report by Jelinksy et al. (31) with some modifications. The CS was defined as the sum of individual scores given for fold change (FC), P value (PV), expression level (EL), and present calls (PC), so that CS = FC + PV + EL + PC. The score for FC was 5 if the fold change was 2.0 or more for stimulated genes or 0.5 or less for inhibited genes, it was 2 if the fold change was more than 1.5 for stimulated genes or less than 0.67 for inhibited genes, and it was -0.5 if the fold change was less than 1.5 or 0.67 or more for stimulated or inhibited genes, respectively. The PV score was 3 if P < 0.05, it was 2 if P < 0.1, and it was -0.5 if P >= 0.1. The expression level was based on the scaled intensity for each gene, with the EL score being 3 if the intensity was more than 20, 1 if the intensity was more than 15, or -0.5 if the intensity was 15 or less. The PC score was 3 if the gene was present in at least two of the four samples, was 1 if the gene was present in only one of the four samples, or was -0.5 if the gene was absent. Based on this scoring, the maximum CS for any gene would be 14.0. We considered a gene to be significantly regulated by E2 if the CS was 12.0 or greater. Our selection of this CS identified genes known to be estrogen regulated and gave highly reproducible patterns of regulation for newly identified genes.

Real-time PCR
Real-time PCR was carried out on over 50 genes to verify the regulation of expression by E2. One microgram of total RNA was reverse transcribed in a total volume of 20 µl using 200 U reverse transcriptase, 50 pmol random hexamer, and 1 mM deoxy-NTP (New England Biolabs, Beverly, MA). The resulting cDNA was then diluted to a total volume of 100 µl with sterile H2O. Each real-time PCR reaction consisted of 1 µl diluted RT product, 1x SYBR Green PCR Master Mix (PE Applied Biosystems, Foster City, CA), and 50 nM forward and reverse primers. Reactions were carried out on an ABI PRISM 7700 Sequence Detection System (PE Applied Biosystems) for 40 cycles (95 C for 15 sec, 60 C for 1 min) after an initial 10-min incubation at 95 C. For the genes whose regulation is described in detail in this report, the primers used for real-time PCR are listed in Table 1Go. The fold change in expression of each gene was calculated using the {Delta}{Delta} Ct method, with the ribosomal protein 36B4 mRNA as an internal control (32).


View this table:
[in this window]
[in a new window]
  		TABLE 1. Primers used for real-time PCR

 

   Results
Top
 Abstract
 Introduction
 Materials and Methods
 Results
Discussion
 References
 
Identification of E2 up- and down-regulated genes
To examine the time-dependent regulation of gene expression by E2 in breast cancer cells, MCF-7 cells were treated with E2 for different lengths of time, ranging from 4–48 h, and RNA from duplicate samples at each time point was analyzed using oligonucleotide microarrays. A CS was calculated for each gene at each time point of E2 treatment, as described in Materials and Methods. The advantage of using a CS is that it takes into account the fold change and statistical significance (P value) of the multiple measurements for each gene compared with control as well as the expression level and the present/absent calls for each gene represented on the array. Using a CS cut-off of 12.0 or greater, 438 genes were identified to be significantly regulated by E2. This cut-off ensured that the fold change was at least 2.0, the P value was less than 0.1, and the gene was expressed at a level detectable by microarray. Surprisingly, only 30% (n = 132) of these genes were up-regulated by E2, whereas the majority (70%; n = 306 genes) were down-regulated.

Time-course patterns of gene regulation
Three types of analyses were performed to identify different patterns of gene regulation based on the time course of E2 treatment. First, gene cluster analysis was performed using GeneSpring software (Fig. 1AGo). Each row represents a single time point (0–48 h) and contains all 438 regulated genes, with stimulated genes in red, inhibited genes in blue, and genes not different from control in yellow. The pattern for each cluster of genes can be observed vertically over the different treatment times. Using this method, several patterns of E2 regulation are visible, as is the fact that the majority of genes are inhibited by E2. Clusters labeled A through C demonstrate three patterns of stimulated genes, with A showing genes highly regulated at all time points examined, B showing genes stimulated at the earlier time points only, and C showing genes stimulated only at the later time points. Clusters labeled D and E show two patterns of down-regulated genes: genes highly down-regulated at all time points (in D) and genes down-regulated at later time points only (in E).



View larger version (37K):
[in this window]
[in a new window]
  		FIG. 1. Cluster analysis for the time-course pattern of E2-regulated gene expression (A) and scatterplots for E2-regulated genes at 4, 8, 24, and 48 h of E2 exposure (B). MCF-7 breast cancer cells were treated with 10 nM E2 for the times indicated before cell harvest and Affymetrix gene chip microarray analysis. Gene cluster analysis (A) was performed for 438 genes found to be significantly regulated by E2 using GeneSpring software. Stimulated genes are shown in red, inhibited genes in blue, and genes not regulated in yellow. Clusters A through C show 3 different time-course patterns of stimulated genes; clusters D and E demonstrate 2 distinct time-course patterns of down-regulated genes. Scatterplots in B were produced for each time point using the normalized signal for each of the E2-regulated genes at the time of interest, plotted against the control signal for that gene on the x-axis. The outer diagonal lines represent a 2-fold increase or decrease in expression. Stimulated genes are in red, inhibited genes are in blue, and genes not different from control are in yellow.

 
In a second type of analysis, scatter plots were produced to examine the proportion of genes stimulated or inhibited at each distinct time point of the experiment (Fig. 1BGo). In these plots, the normalized signal for each of the E2-regulated genes at the time of interest is plotted on the y-axis against the control signal on the x-axis. The outer diagonal lines represent 2-fold changes in expression. This type of analysis demonstrates that at early time points, a greater proportion of genes are up-regulated by E2 (red) compared with down-regulated genes (blue), whereas at later time points a far greater number of genes are down-regulated in relation both to early time points and to the number of up-regulated genes.

These observations were confirmed using a third analysis (Fig. 2Go), in which the 438 genes regulated by E2 were assigned to one of three distinct patterns: 1) regulated early only (>=2-fold at 4 and/or 8 h only), 2) regulated early and late (>=2-fold at 4 and/or 8 h and at 24 and/or 48 h), or 3) regulated late only (>=2-fold at 24 and/or 48 h only). For stimulated genes, an approximately equal number of genes were observed in each of the 3 patterns (early, n = 44; early and late, n = 46; late, n = 42), with the most robustly stimulated genes in the early and late patterns (Fig. 2Go, left panel). In contrast, very few inhibited genes showed the early only pattern (n = 11), with the majority of genes being down-regulated at either the early and late (n = 110) or the late time points only (n = 185; Fig. 2Go, right panel). As our first time point was 4 h, it is possible that some additional early response genes may not have been identified.



View larger version (17K):
[in this window]
[in a new window]
  		FIG. 2. Time-course patterns of gene regulation in MCF-7 cells upon E2 treatment. All E2-stimulated (left panel) or inhibited (right panel) genes were assigned to one of three categories. For early only regulated genes, the fold change was 2-fold or greater at 4 and/or 8 h only. For early and late regulated genes, the fold change was 2-fold or greater at 4 and/or 8 h and at 24 and/or 48 h. For late only regulated genes, the fold change was 2-fold or greater at 24 and/or 48 h only. Once genes were assigned to one of the three time-course patterns, the mean fold change (±SEM) was calculated and plotted for all genes in that pattern. The number of genes in each category is indicated.

 
Functional categories of genes regulated by E2
Of the 438 genes found to be regulated by E2, approximately 80% of the stimulated genes and 70% of the inhibited genes encode proteins with either a known or an inferred function. The major functional categories for these genes (Fig. 3Go) include apoptosis, cell adhesion/extracellular matrix, cell cycle, cytoskeleton/structural, enzymes/metabolism, growth factors/hormones/cytokines, nucleotide processing, protein processing, receptors, signal transduction, transcription, and transporters. With a few exceptions, the proportion of stimulated to inhibited genes in each category was similar (Fig. 3Go). A substantially greater proportion of genes involved in cell cycle and nucleotide processing, such as DNA repair or RNA splicing, were stimulated by E2, whereas a greater proportion of cell adhesion and extracellular matrix genes as well as enzymes were inhibited by E2.



View larger version (35K):
[in this window]
[in a new window]
  		FIG. 3. Functional categories of genes stimulated or inhibited by E2 in MCF-7 breast cancer cells. Where possible, E2-regulated genes were assigned to 1 of 12 functional categories or to the other/unknown category (not shown). The percentage of stimulated or inhibited genes in each category was calculated based on the number of genes assigned to the category divided by the total number of stimulated or inhibited genes.

 
Fifty-two genes have been examined using real-time PCR for regulation by E2, with 51 of the 52 showing a high degree of correlation to our microarray data. If anything, the microarray data tend to underestimate the fold change due to E2. Regulation of specific genes by E2 within specific categories is discussed further below, and the genes found in these categories are listed in Tables 2–5GoGoGoGo.


View this table:
[in this window]
[in a new window]
  		TABLE 2. E2 up-regulated (top) and down-regulated (bottom) genes involved in cell cycle and apoptosis

 

View this table:
[in this window]
[in a new window]
  		TABLE 3. E2 up-regulated (top) and down-regulated (bottom) genes that encode growth factors, cytokines, and hormones

 

View this table:
[in this window]
[in a new window]
  		TABLE 4. E2 up-regulated (top) and down-regulated (bottom) genes that encode receptors and signal transduction proteins

 

View this table:
[in this window]
[in a new window]
  		TABLE 5. E2 up-regulated (top) and down-regulated (bottom) genes that encode transcription factors and transcriptional coregulators

 
E2 regulation of genes promoting cell proliferation and survival
It is well established that E2 stimulates MCF-7 cell proliferation, and as expected, we identified a number of genes, quite a few novel ones as well as some previously known, that are stimulated by E2 and are associated with the cell cycle (Table 2Go). The time courses of regulation for the known E2-stimulated genes cyclin D1 and cell division cycles 2 and 20 (CDC2 and CDC20) are shown in Fig. 4AGo. Figure 4BGo shows real-time PCR data for the time course of identified E2-stimulated genes, minichromosome maintenance genes (MCM2, MCM3, and MCM5), CDC6, and replication factor C4 (RFC4), all of which have roles in DNA synthesis. Of interest, the time course information indicates that the majority of cell cycle-associated genes that are stimulated by E2 are regulated late, at 24 h or later. Only cyclin D1 and CDC6 are up-regulated by E2 within the first 4 h of treatment.



View larger version (20K):
[in this window]
[in a new window]
  		FIG. 4. Regulation of cell cycle-associated genes by E2 in MCF-7 cells. A, Microarray data over the 48-h treatment period for three cell cycle-associated genes stimulated by E2, demonstrating the different time-course patterns observed. B, Real-time PCR data over the 48-h treatment period for five E2 up-regulated genes that play roles in DNA synthesis. C, Microarray data over the 48-h treatment period for three novel cell cycle-associated genes found to be down-regulated by E2.

 
In addition to these E2-stimulated genes, we identified a number of antiproliferative and proapoptotic genes to be down-regulated by E2 (Table 2Go and Fig. 4CGo). Two members of the pheochromacytoma cell-3 (PC3)/B cell translocation gene (BTG)/transducer of ERBB2 (TOB) family, BTG-1 and BTG-2, which have been shown to be induced by p53 and to inhibit cell cycle progression, are down-regulated by E2, although their precise molecular functions are not known (33). Also down-regulated by E2 is cyclin G2, a gene known to induce cell cycle arrest and to be up-regulated when cells undergo arrest or apoptosis (34). It also appears that E2 may influence not only proliferation, but also cell survival through the up-regulation of the antiapoptotic gene survivin and the down-regulation of multiple proapoptotic genes, including BCL 2-interacting killer, BCL-2 antagonist/killer 1, immediate early response 3 (also known as IEX-1), and caspase 9. Hence, E2 acts to stimulate genes associated with cell proliferation, in particular genes associated with DNA synthesis, as well as to down-regulate antiproliferative and proapoptotic genes, probably leading to an overall increase in both proliferation and cell survival.

E2 regulation of genes encoding growth factors, cytokines and hormones
Our findings support the proposal (35) that major changes in breast cancer cell proliferation by E2 involve the up-regulation of growth factors that can act in an autocrine manner. We have found several growth factors, cytokines, and hormones to be regulated by E2 in MCF-7 cells (Table 3Go). Amphiregulin, stromal cell-derived factor 1 (SDF-1; also known as chemokine ligand 12), stanniocalcin 2, and vascular endothelial growth factor (VEGF), all previously identified as E2-stimulated genes, showed early increases after E2 exposure, and as shown in Fig. 5Go, each of these genes had a unique time course of regulation, with amphiregulin and SDF-1 showing sustained high fold stimulated levels over the 48 h, and VEGF and stanniocalcin being elevated primarily at early times only.



View larger version (18K):
[in this window]
[in a new window]
  		FIG. 5. Regulation of growth factor gene expression by E2. Microarray data over the 48-h E2 treatment time reveals distinct time courses for the four up-regulated (SDF-1, amphiregulin, stanniocalcin 2, and VEGF) and the three down-regulated (TGFß3, BMP4, and inhibin ßB) genes encoding growth factors.

 
Several novel genes associated with the suppression of breast cancer cell proliferation were found to be down-regulated by E2, including TGFß3, bone morphogenic protein 4 (BMP4) and the inhibin ßB-subunit, which is common to both activin and inhibin (Table 3Go and Fig. 5Go). These data highlight that in addition to the stimulation of growth factors associated with increased cell proliferation, down-regulation of several growth inhibitory factors, particularly members of the TGFß family, including TGFß3, BMP4, and inhibin ßB, may contribute to the increased proliferation elicited by E2.

E2 regulation of receptors and signaling pathways
A significant number of receptors and signaling molecules were found to be regulated by E2, particularly at early times (Table 4Go). Two pathways of note, which are regulated at several levels, include the prostaglandin E pathway (Fig. 6AGo) and SDF-1 (up-regulated by E2; as shown in Fig. 5Go) and its chemokine receptor CXCR4 (Fig. 6BGo) pathway. The enzyme prostaglandin E synthase as well as the prostaglandin E receptor (EP3) were found to be stimulated by E2 (Fig. 6AGo). In contrast, the CXCR4 receptor, which may play a role in cell motility, was down-regulated by E2, as was BLNK (Fig. 6BGo), a B cell scaffolding protein that is involved in regulating the activity of CXCR4 (36). These findings suggest an overall decrease in signaling through the CXCR4 pathway, but an increase in prostaglandin E production and signaling in response to E2.



View larger version (31K):
[in this window]
[in a new window]
  		FIG. 6. Regulation by E2 of genes encoding receptors and signal transduction proteins. A and B, Microarray data are shown for prostaglandin E synthase (PGES) and prostaglandin receptor EP3, which are both stimulated by E2, and for the chemokine receptor CXCR4 and the signaling protein B cell linker (BLNK), which are both down-regulated by E2. C and D, Real-time PCR data are shown for four receptors found to be either rapidly up-regulated or down-regulated by E2.

 
Some other important receptors found to be regulated by E2 include the highly up-regulated calcitonin receptor (Fig. 6CGo) and the down-regulated erythropoietin receptor, IL-1 receptor type I, and Notch 3, which are rapidly decreased, by 4 and 8 h (Fig. 6DGo).

E2 regulation of transcription factors and transcriptional coregulators
Many novel transcription factors, including HOXC4, HOXC5, and HOXC6, were identified as being markedly stimulated by E2 (Fig. 7AGo and Table 5Go). Interestingly, these three genes had an identical time course of E2 regulation, with the maximum stimulation at 4 h, followed by a decrease. However, it should be noted that HOXC4 showed a much higher degree of stimulation and remained greatly elevated throughout the entire 48-h time course. The biological significance of these differences is not clear.



View larger version (29K):
[in this window]
[in a new window]
  		FIG. 7. Time course of regulation by E2 for members of two families of transcription factors (HOXC and Myb). A, Microarray data for HOXC4, C5, and C6 gene expression showing similar time courses, but different magnitudes of change. B, Real-time PCR data for A-Myb, B-Myb, and C-Myb transcription factors showing different time courses and magnitudes of change. C, Real-time PCR data investigating the ability of CHX to block the 24-h E2 stimulation of A-Myb, B-Myb, or C-Myb gene expression.

 
Other transcription factors, including c-Fos, c-Myc, BRCA1, and BRCA2, known to be stimulated by E2, were also found by our microarray studies (Table 5Go). However, our time-course analysis reveals some new information about E2 regulation of several of these factors. One example is that of the oncogene c-myb and two related transcription factors, A-Myb and B-Myb (also known as myb-like 1 and myb-like 2). All three were stimulated by E2, but had very different time courses and magnitudes of regulation (Fig. 7BGo). Both A-Myb and C-Myb were highly up-regulated within 4 h of E2 treatment and remained elevated throughout the 48 h, with the level of A-Myb stimulation being approximately three to four times greater at all time points. In contrast, B-Myb was not significantly up-regulated by E2 until 24 h of treatment, at which time a 4- to 5-fold stimulation was observed. This suggests that although these three related transcription factors are stimulated by E2, their regulation may be through different mechanisms. Indeed, studies with the protein synthesis inhibitor, cycloheximide (Fig. 7CGo), reveal that the rapidly up-regulated A-Myb and C-Myb genes are probably primary response genes as their stimulation is not blocked by cycloheximide whereas B-Myb, the more slowly responding gene is probably a secondary response gene, as its stimulation is prevented by cycloheximide treatment. Indeed, it is likely that the early changes in the expression of genes encoding transcription factors could impact the expression of later downstream genes.

Also of interest, a number of transcription factors thought to be transcriptional repressors were down-regulated by E2 (Fig. 8Go). These include Mad4, JunB, an Ets2 repressor factor (ERF), and two members of the Id family of transcriptional regulators, inhibitor of DNA binding 1 and 2. We also found mRNA encoding the high-mobility group (HMG) box-containing protein 1 (HBP1) and SATB1, an AT-rich binding protein and nuclear matrix scaffolding factor, to be down-regulated by E2, and the down-regulations observed by Affymetrix microarray analysis were confirmed by real-time PCR (Fig. 8BGo). The suppression of gene expression for multiple transcriptional repressors might enable E2 to increase the transcriptional activity of genes in numerous pathways in breast cancer cells.



View larger version (17K):
[in this window]
[in a new window]
  		FIG. 8. Down-regulation of transcriptional repressors by E2 in MCF-7 cells. A, Microarray data demonstrating the time courses for down-regulation of five transcriptional repressors by E2. B, Real-time PCR data for the regulation of two repressors of transcription, HBP-1 and SATB1, showing identical time courses and magnitudes of down-regulation by E2 over the 48-h treatment period.

 
In addition to transcription factors and transcriptional repressors, E2 regulated a number of genes encoding nuclear receptor transcriptional coregulators. Over time, as shown in Fig. 9Go, there appears to be a change in the complement of cell coregulators, with a down-regulation of steroid receptor coactivator (SRC)-2/glucocorticoid receptor interacting protein 1/transcriptional intermediary factor (TIF)2, SRC-3/amplified in breast cancer 1/ACTR (a novel coactivator), and TIF1{alpha} (37), as well as two other enhancers of ER activity, a small proline-rich coactivator termed PNRC2 (38) and SMAD3 [Sma and mothers against decapentaplegic (MAD) homolog 3], another transcription factor known to enhance ER activity (39). In contrast, the only coregulator we observed to be stimulated by E2 was receptor-interacting protein 140/nuclear receptor-interacting protein 1 (Table 5Go); it generally functions as a corepressor of ER, but can also exhibit coactivator activity and has previously been reported to be regulated by E2 (40).



View larger version (22K):
[in this window]
[in a new window]
  		FIG. 9. Regulation by E2 of nuclear receptor coregulator gene expression. Real-time PCR verification of the time course of down-regulation of the mRNAs for five coregulators known to enhance ER activity.

 

   Discussion
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
References
 
Estrogens are known to regulate the proliferation of breast cancer cells and to alter cytoarchitectural and other phenotypic properties of these cells, but the mechanisms and pathways by which estrogens regulate these events are only partially understood. We have used global gene expression profiling by microarray analysis, with quantitative PCR verification in many cases, to identify patterns and networks of genes that are either stimulated or inhibited by E2. We have observed that many genes whose expression is altered by this hormone, are associated with specific cell signaling pathways and regulatory factor-receptor loops. These include a general up-regulation of positive proliferation regulators and the down-regulation of negative proliferation regulators, which together may contribute to the overall stimulation of proliferation and suppression of apoptosis by estrogen in these ER-positive breast cancer cells. In addition to affecting several important regulators of the cell cycle, E2 altered the expression of many growth factors and growth factor receptors, and up-regulated hormone biosynthetic enzymes that might result in elevated levels of estrogen production.

Many genes affected by E2 are down-regulated
Of the more than 12,000 genes queried on the Affymetrix U95A microarray, we identified over 400 genes that showed a robust pattern of regulation by E2, but notably the majority of these genes (70%) were, in fact, down-regulated. Although there may be multiple mechanisms involved in this down-regulation, two mechanisms by which E2 has been shown to repress gene expression involve the inhibition of NF-{kappa}B, such as occurs for E2 down-regulation of IL-6, or squelching/sequestering of shared transcriptional coactivators that might be necessary for maintaining basal gene expression (6, 7, 8). Both mechanisms seem plausible, as NF-{kappa}B signaling has been detected in breast cancer cells and has been implicated in the progression of breast cancer from ER-positive to ER-negative status (41, 42). Also, our finding that multiple transcriptional coactivators are down-regulated by E2 suggests that some of the estrogen-induced down-regulation of genes could be due at least in part to changes in levels of limiting transcriptional coregulators.

Time course and level of regulation: primary vs. secondary responses
The time-course studies we have performed, spanning times up to 48 h, reveal a diversity of temporal patterns of gene regulation by E2. One can use these patterns as a general guide to assist in identifying genes that are likely to be primary responses vs. secondary responses to the hormone. Although genes that show rapid changes in mRNA levels are likely to be primary response genes, and those that show a lag before changing are likely to be secondary, the half-life of the specific mRNA will also be an important factor in determining how long it takes to detect a change, either up or down, in the mRNA level of a specific gene.

A more definitive way to distinguish primary from secondary responses often employs the use of cycloheximide, which should not affect primary gene responses, but should block secondary mRNA responses. We chose to probe this point in one particular case, that of the three Mybs. As seen in Fig. 7CGo, the A-, B-, and C-Myb transcription factors were all stimulated by E2, with the changes in A- and C-Myb being rapid, but B-Myb showing a distinct lag before stimulation. Cycloheximide had no effect on A- and C-Myb stimulation, but blocked B-Myb stimulation very effectively, indicating that the two genes that showed the rapid response were primary, whereas the gene with the late pattern of increase was not a primary response gene. Thus, in this case the time course of response to estrogen was predictive of primary vs. secondary gene responsiveness. Although time-course data can be useful as a general guide, definitive determination of whether a gene response is primary would need to be evaluated in genes of interest individually.

Motifs in the regulation of proliferation: up-regulation of positive and down-regulation of negative factors
E2 up-regulates genes such as cyclin D1, cyclin A2, cdc2 (cdk1), cdc20, and some novel genes we identified, such as Bub1, that are involved in the progression of the cell cycle, and genes involved in DNA synthesis, such as RFC4, proliferating cell nuclear antigen, CDC6, and MCM proteins 2, 3, and 5. Interestingly, the gene survivin (BIRC5), which encodes an inhibitor of apoptosis, was found by us to be up-regulated by E2 and has recently been shown to protect MCF-7 cells from etoposide-induced apoptosis (43). Other positive growth-promoting effects of E2 occur through the induction of growth factors and transcription factors, such as SDF-1, which was recently shown to play a role in E2 induced ovarian cancer cell proliferation (44). Interestingly, the transcription factors HOXC6 and A-Myb, which we found to be highly induced by E2 at early time points, have both been shown through mouse knockout models to be required for normal mammary gland development (45, 46). Although HOXC6 is essential for normal mammary gland development, it noteworthy that its synthesis is actually down-regulated by E2 in normal mouse mammary gland epithelium (45). Whether the up-regulation of HOXC6 or the primary induction of A-Myb by E2 in breast cancer cells contributes to the progression of breast cancer cell proliferation is currently under investigation.

Perhaps the most novel finding of this work is that E2-induced enhancement of cell proliferation and of cell cycle progression is associated with the down-regulation of numerous factors that are known to inhibit the cell cycle. Hence, E2 down-regulates genes directly involved in inhibition of the cell cycle, such as BTG-1, BTG-2, and cyclin G2, and also down-regulates cytokines and growth factors that are known to inhibit cell proliferation, such as members of the TGFß superfamily. Although TGF-ß3 is known to be down-regulated by E2 in MCF-7 cells and to inhibit breast cancer cell proliferation (47), BMP4 has not yet been shown to play a role in breast cancer. It is known to be stimulated by antiestrogens in bone cells, but it has not previously been implicated in playing a role in breast cancer, whereas BMP2 is known to inhibit breast cancer cell proliferation, suggesting that, like BMP2 and TGFß, BMP4 may also be growth inhibitory (48, 49). In addition, activin is growth inhibitory to breast cancer cells (41, 45), and it is of interest that its subunit inhibin ßB was significantly down-regulated by E2.

E2 down-regulation of multiple transcriptional repressors could also contribute to increased cell proliferation. For example, Mad4 antagonizes Myc action by competing for their binding partner Max and forming dimers with Max that bind to E boxes in Myc target genes, thereby repressing transcription (50). Thus, E2 could enhance Myc activity not only by up-regulating c-Myc, but additionally by down-regulating an inhibitor of Myc. Also, the transcription factor JunB, which is a member of the AP-1 transcription factor family, may act as a negative regulator of transcription through AP-1, particularly in the presence of c-Jun and when acting on cell proliferation-associated genes (51). Therefore, by up-regulation of c-Fos and down-regulation of JunB, E2 could further enhance growth stimulatory gene transcription through AP-1. Other transcriptional repressors whose down-regulation by E2 may contribute to enhanced cell proliferation include HBP1, which can represses Wnt signaling (52, 53), and ERF, which represses the transcription of promoters containing an ets-binding site and is inactivated by the Ras/MAPK pathway (54). This down-regulation of multiple transcriptional repressors (such as JunB, Mad4, HBP1, and ERF) suggests that one major function of E2 in breast cancer cells is perhaps to increase the transcriptional activity of numerous cell transduction pathways, several of which appear to be involved in the regulation of cell proliferation.

E2 modification of its own synthesis and of ER actions
A particularly interesting regulatory loop that may contribute to the amplification of E2-induced processes is that involving prostaglandin and prostaglandin receptors, and the genes that they regulate. Prostaglandin E synthase (also known as PIG12) (55) and prostaglandin E receptor type 3 (EP3) were found to be up-regulated by E2. By up-regulating prostaglandin E synthase, estrogen could be increasing the production of prostaglandin E2. This hormone can act on the prostaglandin EP1 or EP2 receptors to stimulate aromatase activity in breast cancer, thereby raising estrogen levels in these cells (56). This suggests the intriguing possibility that E2 could be up-regulating its own synthesis in a feedforward cascade that involves up-regulation of prostaglandin E synthase and the subsequent action of increased prostaglandin E2 levels on prostaglandin receptors, which would up-regulate the aromatase gene.

In contrast to the potential stimulatory effects on its own production, E2 might act in a classical negative feedback loop on ER activity through the down-regulation of many genes, the products of which are known to enhance ER activity. These would include SRC2, SRC3, TIF1{alpha}, PNRC2, and SMAD3. In addition, as observed by others (41) and by us, E2 up-regulated the receptor corepressor RIP140. These observations are of particular interest because although the mechanisms of how coregulators function are being well studied, little is known about how coregulator expression is regulated. Overall, these findings suggest that E2 acts to alter levels of coregulators in a manner that would result in a decrease in ER{alpha} activity, but whether this represents a classical negative feedback mechanism is not known. Alternatively, these changes could represent an overall change in the complement of cellular coregulators, leading to the preferential action of some coregulators over others. For example, the level of SRC1, which was not regulated by E2, would be increased in MCF-7 cells relative to the p160 steroid receptor coactivators SRC2/TIF2 and SRC3, both of which are down-regulated by E2 (57). Several recent studies have shown that the levels of coregulators, relative to one another, may dictate how a cell will respond to hormone. For example, the level of SRC1 in uterine cells is a critical determinant of how these cells respond to the SERM tamoxifen (12). Also, the balance between SRC1 and SRC2, which is down-regulated by E2, can determine peroxisome proliferator-activated receptor {gamma} activity and adipogenesis in mice (58). Whether this down-regulation of important coactivators by E2 contributes to the E2-induced down-regulation of the numerous estrogen-responsive genes we have observed remains to be investigated.

In summary, our studies highlight the diverse gene networks and metabolic and cell regulatory pathways through which E2 operates to alter the proliferation and phenotype of breast cancer cells, and they demonstrate the very widespread effects of this hormone on breast cancer cells.


   Acknowledgments
 
We thank Dennis Akan and Mark Band (University of Illinois Biotechnology Center) for assistance with microarray analyses.


   Footnotes
 
This work was supported by NIH Grants CA-18119 and T32-HD-07028 and the Breast Cancer Research Foundation.

Abbreviations: AP-1, Activating protein-1; BMP4, bone morphogenic protein 4; BTG, B cell translocation gene; CDC, cell division cycle; CHX, cycloheximide; CS, confidence score; E2, estradiol; ER, estrogen receptor; ERF, Ets2 repressor factor; HBP1, HMG box-containing protein 1; HMG, high-mobility group; MAD, mothers against decapentaplegic; MCM, minichromosome maintenance; NF-{kappa}B, nuclear factor-{kappa}B; PC3 pheochromacytoma cell-3; RFC4, replication factor C4; SDF-1, stromal cell-derived factor 1; SERM, selective ER modulator; SMAD3, Sma and MAD3; SRC, steroid receptor coactivator; TIF, transcriptional intermediary factor; TOB, transducer of ERBB2; VEGF, vascular endothelial growth factor.

Received May 7, 2003.

Accepted for publication July 1, 2003.


   References
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 References
 

  1. Katzenellenbogen BS, Katzenellenbogen JA 2000 Estrogen receptor transcription and transactivation: estrogen receptor {alpha} and estrogen receptor ß: regulation by selective estrogen receptor modulators and importance in breast cancer. Breast Cancer Res 2:335–344[CrossRef][Medline]
  2. Hall JM, Couse JF, Korach KS 2001 The multifaceted mechanisms of estradiol and estrogen receptor signaling. J Biol Chem 276:36869–36872[Free Full Text]
  3. McDonnell DP, Norris JD 2002 Connections and regulation of the human estrogen receptor. Science 296:1642–1644[Abstract/Free Full Text]
  4. Kushner PJ, Agard DA, Greene GL, Scanlan TS, Shiau AK, Uht RM, Webb P 2000 Estrogen receptor pathways to AP-1. J Steroid Biochem Mol Biol 74:311–317[CrossRef][Medline]
  5. Safe S 2001 Transcriptional activation of genes by 17ß-estradiol through estrogen receptor-Sp1 interactions. Vitam Horm 62:231–252[Medline]
  6. McKay LI, Cidlowski JA 1999 Molecular control of immune/inflammatory responses: interactions between nuclear factor-{kappa}B and steroid receptor-signaling pathways. Endocr Rev 20:435–459[Abstract/Free Full Text]
  7. Harnish DC, Scicchitano MS, Adelman SJ, Lyttle CR, Karathanasis SK 2000 The role of CBP in estrogen receptor cross-talk with nuclear factor-{kappa}B in HepG2 cells. Endocrinology 141:3403–3411[Abstract/Free Full Text]
  8. Speir E, Yu ZX, Takeda K, Ferrans VJ, Cannon 3rd RO 2000 Competition for p300 regulates transcription by estrogen receptors and nuclear factor-{kappa}B in human coronary smooth muscle cells. Circ Res 87:1006–1011.[Abstract/Free Full Text]
  9. Cerillo G, Rees A, Manchanda N, Reilly C, Brogan I, White A, Needham M 1998 The oestrogen receptor regulates NF{kappa}B and AP-1 activity in a cell-specific manner. J Steroid Biochem Mol Biol 67:79–88[CrossRef][Medline]
  10. Evans MJ, Eckert A, Lai K, Adelman SJ, Harnish DC 2001 Reciprocal antagonism between estrogen receptor and NF-{kappa}B activity in vivo. Circ Res 89:823–830[Abstract/Free Full Text]
  11. Maret A, Clamens S, Delrieu I, Elhage R, Arnal JF, Bayard F 1999 Expression of the interleukin-6 gene is constitutive and not regulated by estrogen in rat vascular smooth muscle cells in culture. Endocrinology 140:2876–2882[Abstract/Free Full Text]
  12. Shang Y, Brown M 2002 Molecular determinants for the tissue specificity of SERMs. Science 295:2465–2468[Abstract/Free Full Text]
  13. Katzenellenbogen BS, Katzenellenbogen JA 2002 Defining the "S" in SERMs. Science 295:2380–2381[Abstract/Free Full Text]
  14. Margeat E, Bourdoncle A, Margueron R, Poujol N, Cavailles V, Royer C 2003 Ligands differentially modulate the protein interactions of the human estrogen receptors {alpha} and ß. J Mol Biol 326:77–92[CrossRef][Medline]
  15. Dang ZC, Audinot V, Papapoulos SE, Boutin JA, Lowik CW 2003 Peroxisome proliferator-activated receptor {gamma} (PPAR{gamma}) as a molecular target for the soy phytoestrogen genistein. J Biol Chem 278:962–967[Abstract/Free Full Text]
  16. Jiang Y, Harlocker SL, Molesh DA, Dillon DC, Stolk JA, Houghton RL, Repasky EA, Badaro R, Reed SG, Xu J 2002 Discovery of differentially expressed genes in human breast cancer using subtracted cDNA libraries and cDNA microarrays. Oncogene 21:2270–2282[CrossRef][Medline]
  17. van de Vijver MJ, He YD, van’t Veer LJ, Dai H, Hart AA, Voskuil DW, Schreiber GJ, Peterse JL, Roberts C, Marton MJ, Parrish M, Atsma D, Witteveen A, Glas A, Delahaye L, van der Velde T, Bartelink H, Rodenhuis S, Rutgers ET, Friend SH, Bernards R 2002 A gene-expression signature as a predictor of survival in breast cancer. N Engl J Med 347:1999–2009[Abstract/Free Full Text]
  18. van’t Veer LJ, Dai H, van de Vijver MJ, He YD, Hart AA, Mao M, Peterse HL, van der Kooy K, Marton MJ, Witteveen AT, Schreiber GJ, Kerkhoven RM, Roberts C, Linsley PS, Bernards R, Friend SH 2002 Gene expression profiling predicts clinical outcome of breast cancer. Nature 415:530–536[CrossRef][Medline]
  19. Sotiriou C, Powles TJ, Dowsett M, Jazaeri AA, Feldman AL, Assersohn L, Gadisetti C, Libutti SK, Liu ET 2002 Gene expression profiles derived from fine needle aspiration correlate with response to systemic chemotherapy in breast cancer. Breast Cancer Res 4:R3
  20. Zajchowski DA, Bartholdi MF, Gong Y, Webster L, Liu HL, Munishkin A, Beauheim C, Harvey S, Ethier SP, Johnson PH 2001 Identification of gene expression profiles that predict the aggressive behavior of breast cancer cells. Cancer Res 61:5168–5178[Abstract/Free Full Text]
  21. Perou CM, Sorlie T, Eisen MB, van de Rijn M, Jeffrey SS, Rees CA, Pollack JR, Ross DT, Johnsen H, Akslen LA, Fluge O, Pergamenschikov A, Williams C, Zhu SX, Lonning PE, Borresen-Dale AL, Brown PO, Botstein D 2000 Molecular portraits of human breast tumours. Nature 406:747–752[CrossRef][Medline]
  22. Sorlie T, Perou CM, Tibshirani R, Aas T, Geisler S, Johnsen H, Hastie T, Eisen MB, van de Rijn M, Jeffrey SS, Thorsen T, Quist H, Matese JC, Brown PO, Botstein D, Eystein Lonning P, Borresen-Dale AL 2001 Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci USA 98:10869–10874[Abstract/Free Full Text]
  23. Hedenfalk IA, Ringner M, Trent JM, Borg A 2002 Gene expression in inherited breast cancer. Adv Cancer Res 84:1–34[Medline]
  24. West M, Blanchette C, Dressman H, Huang E, Ishida S, Spang R, Zuzan H, Olson Jr JA, Marks JR, Nevins JR 2001 Predicting the clinical status of human breast cancer by using gene expression profiles. Proc Natl Acad Sci USA 98:11462–11467[Abstract/Free Full Text]
  25. Dressman MA, Walz TM, Lavedan C, Barnes L, Buchholtz S, Kwon I, Ellis MJ, Polymeropoulos MH 2001 Genes that co-cluster with estrogen receptor {alpha} in microarray analysis of breast biopsies. Pharmacogenom J 1:135–141
  26. Gruvberger S, Ringner M, Chen Y, Panavally S, Saal LH, Borg A, Ferno M, Peterson C, Meltzer PS 2001 Estrogen receptor status in breast cancer is associated with remarkably distinct gene expression patterns. Cancer Res 61:5979–5984[Abstract/Free Full Text]
  27. Soulez M, Parker MG 2001 Identification of novel oestrogen receptor target genes in human ZR75–1 breast cancer cells by expression profiling. J Mol Endocrinol 27:259–274[Abstract]
  28. Omoto Y, Hayashi S 2002 A study of estrogen signaling using DNA microarray in human breast cancer. Breast Cancer 9:308–311[Medline]
  29. Inoue A, Yoshida N, Omoto Y, Oguchi S, Yamori T, Kiyama R, Hayashi S 2002 Development of cDNA microarray for expression profiling of estrogen-responsive genes. J Mol Endocrinol 29:175–192[Abstract]
  30. Lobenhofer EK, Bennett L, Cable PL, Li L, Bushel PR, Afshari CA 2002 Regulation of DNA replication fork genes by 17ß-estradiol. Mol Endocrinol 16:1215–1229[Abstract/Free Full Text]
  31. Jelinsky SA, Harris HA, Brown EL, Flanagan K, Zhang X, Tunkey C, Lai K, Lane MV, Simcoe DK, Evans MJ 2003 Global transcription profiling of estrogen activity: estrogen receptor {alpha} regulates gene expression in the kidney. Endocrinology 144:701–710[Abstract/Free Full Text]
  32. Livak KJ, Schmittgen TD 2001 Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) method. Methods 25:402–408[CrossRef][Medline]
  33. Tirone F 2001 The gene PC3(TIS21/BTG2), prototype member of the PC3/BTG/TOB family: regulator in control of cell growth, differentiation, and DNA repair? J Cell Physiol 187:155–165[CrossRef][Medline]
  34. Bennin DA, Don AS, Brake T, McKenzie JL, Rosenbaum H, Ortiz L, DePaoli-Roach AA, Horne MC 2002 Cyclin G2 associates with protein phosphatase 2A catalytic and regulatory B’ subunits in active complexes and induces nuclear aberrations and a G1/S phase cell cycle arrest. J Biol Chem 277:27449–27467[Abstract/Free Full Text]
  35. Dickson RB, Lippman ME 1987 Estrogenic regulation of growth and polypeptide growth factor secretion in human breast carcinoma. Endocr Rev 8:29–43[Medline]
  36. Guinamard R, Signoret N, Ishiai M, Marsh M, Kurosaki T, Ravetch JV, Masamichi I 1999 B cell antigen receptor engagement inhibits stromal cell-derived factor (SDF)-1{alpha} chemotaxis and promotes protein kinase C (PKC)-induced internalization of CXCR4. J Exp Med 189:1461–1466[Abstract/Free Full Text]
  37. McKenna NJ, Lanz RB, O’Malley BW 1999 Nuclear receptor coregulators: cellular and molecular biology. Endocr Rev 20:321–344[Abstract/Free Full Text]
  38. Zhou D, Chen S 2001 PNRC2 is a 16 kDa coactivator that interacts with nuclear receptors through an SH3-binding motif. Nucleic Acids Res 29:3939–3948[Abstract/Free Full Text]
  39. Matsuda T, Yamamoto T, Muraguchi A, Saatcioglu F 2001 Cross-talk between transforming growth factor-ß and estrogen receptor signaling through Smad3. J Biol Chem 276:42908–42914[Abstract/Free Full Text]
  40. Thenot S, Charpin M, Bonnet S, Cavailles V 1999 Estrogen receptor cofactors expression in breast and endometrial human cancer cells. Mol Cell Endocrinol 156:85–93[CrossRef][Medline]
  41. Nakshatri H, Bhat-Nakshatri P, Martin DA, Goulet Jr RJ, Sledge Jr GW 1997 Constitutive activation of NF-{kappa}B during progression of breast cancer to hormone-independent growth. Mol Cell Biol 17:3629–3639.[Abstract]
  42. Biswas DK, Dai SC, Cruz A, Weiser B, Graner E, Pardee AB 2001 The nuclear factor {kappa}B (NF-{kappa}B): a potential therapeutic target for estrogen receptor negative breast cancers. Proc Natl Acad Sci USA 98:10386–10391[Abstract/Free Full Text]
  43. Choi KS, Lee TH, Jung MH 2003 Ribozyme-mediated cleavage of the human survivin mRNA and inhibition of antiapoptotic function of survivin in MCF-7 cells. Cancer Gene Ther 10:87–95[CrossRef][Medline]
  44. Hall JM, Korach KS 2003 Stromal cell-derived factor 1, a novel target of estrogen receptor action, mediates the mitogenic effects of estradiol in ovarian and breast cancer cells. Mol Endocrinol 17:792–803[Abstract/Free Full Text]
  45. Garcia-Gasca A, Spyropoulos DD 2000 Differential mammary morphogenesis along the anteroposterior axis in Hoxc6 gene targeted mice. Dev Dyn 219:261–276[CrossRef][Medline]
  46. Toscani A, Mettus RV, Coupland R, Simpkins H, Litvin J, Orth J, Hatton KS, Reddy EP 1997 Arrest of spermatogenesis and defective breast development in mice lacking A-myb. Nature 386:713–717[CrossRef][Medline]
  47. Arrick BA, Korc M, Derynck R 1990 Differential regulation of expression of three transforming growth factor ß species in human breast cancer cell lines by estradiol. Cancer Res 50:299–303[Abstract/Free Full Text]
  48. van den Wijngaard A, Mulder WR, Dijkema R, Boersma CJ, Mosselman S, van Zoelen EJ, Olijve W 2000 Antiestrogens specifically up-regulate bone morphogenetic protein-4 promoter activity in human osteoblastic cells. Mol Endocrinol 14:623–633[Abstract/Free Full Text]
  49. Ghosh-Choudhury N, Woodruff K, Qi W, Celeste A, Abboud SL, Ghosh Choudhury G 2000 Bone morphogenetic protein-2 blocks MDA MB 231 human breast cancer cell proliferation by inhibiting cyclin-dependent kinase-mediated retinoblastoma protein phosphorylation. Biochem Biophys Res Commun 272:705–711[CrossRef][Medline]
  50. Grandori C, Cowley SM, James LP, Eisenman RN 2000 The Myc/Max/Mad network and the transcriptional control of cell behavior. Annu Rev Cell Dev Biol 16:653–699[CrossRef][Medline]
  51. Shaulian E, Karin M 2002 AP-1 as a regulator of cell life and death. Nat Cell Biol 4:E131–136
  52. Tevosian SG, Shih HH, Mendelson KG, Sheppard KA, Paulson KE, Yee AS 1997 HBP1: a HMG box transcriptional repressor that is targeted by the retinoblastoma family. Genes Dev 11:383–396[Abstract/Free Full Text]
  53. Sampson EM, Haque ZK, Ku MC, Tevosian SG, Albanese C, Pestell RG, Paulson KE, Yee AS 2001 Negative regulation of the Wnt-ß-catenin pathway by the transcriptional repressor HBP1. EMBO J 20:4500–4511[CrossRef][Medline]
  54. Sgouras DN, Athanasiou MA, Beal Jr GJ, Fisher RJ, Blair DG, Mavrothalassitis GJ 1995 ERF: an ETS domain protein with strong transcriptional repressor activity, can suppress ets-associated tumorigenesis and is regulated by phosphorylation during cell cycle and mitogenic stimulation. EMBO J 14:4781–4793[Medline]
  55. Jakobsson PJ, Thoren S, Morgenstern R, Samuelsson B 1999 Identification of human prostaglandin E synthase: a microsomal, glutathione-dependent, inducible enzyme, constituting a potential novel drug target. Proc Natl Acad Sci USA 96:7220–7225[Abstract/Free Full Text]
  56. Brueggemeier RW, Richards JA, Joomprabutra S, Bhat AS, Whetstone JL 2001 Molecular pharmacology of aromatase and its regulation by endogenous and exogenous agents. J Steroid Biochem Mol Biol 79:75–84[CrossRef][Medline]
  57. Lauritsen KJ, List HJ, Reiter R, Wellstein A, Riegel AT 2002 A role for TGF-ß in estrogen and retinoid mediated regulation of the nuclear receptor coactivator AIB1 in MCF-7 breast cancer cells. Oncogene 21:7147–7155[CrossRef][Medline]
  58. Picard F, Gehin M, Annicotte JS, Rocchi S, Champy MF, O’Malley BW, Chambon P, Auwerx J 2002 SRC-1 and TIF2 control energy balance between white and brown adipose tissues. Cell 111:931–941[CrossRef][Medline]



This article has been cited by other articles:


Home page
 J. Biol. Chem.Home page
G. M. Mager, R. M. Ward, R. Srinivasan, S.-W. Jang, L. Wrabetz, and J. Svaren
Active Gene Repression by the Egr2{middle dot}NAB Complex during Peripheral Nerve Myelination
J. Biol. Chem., June 27, 2008; 283(26): 18187 - 18197.
[Abstract] [Full Text] [PDF]

Home page
 J EndocrinolHome page
S. Raulic, Y. Ramos-Valdes, and G. E DiMattia
Stanniocalcin 2 expression is regulated by hormone signalling and negatively affects breast cancer cell viability in vitro
J. Endocrinol., June 1, 2008; 197(3): 517 - 529.
[Abstract] [Full Text] [PDF]

Home page
 Cancer Res.Home page
A. Boulay, M. Breuleux, C. Stephan, C. Fux, C. Brisken, M. Fiche, M. Wartmann, M. Stumm, H. A. Lane, and N. E. Hynes
The Ret Receptor Tyrosine Kinase Pathway Functionally Interacts with the ER{alpha} Pathway in Breast Cancer
Cancer Res., May 15, 2008; 68(10): 3743 - 3751.
[Abstract] [Full Text] [PDF]

Home page
 J Mol EndocrinolHome page
B. Tan, X. Long, H. Nakshatri, K. P Nephew, and R. M Bigsby
Striatin-3{gamma} inhibits estrogen receptor activity by recruiting a protein phosphatase
J. Mol. Endocrinol., May 1, 2008; 40(5): 199 - 210.
[Abstract] [Full Text] [PDF]