Regulation of DNA Replication Fork Genes by 17ß-Estradiol

Edward K. Lobenhofer, Lee Bennett, P. LouAnn Cable, Leping Li, Pierre R. Bushel and Cynthia A. Afshari

Gene Regulation Group (E.K.L., P.L.C., C.A.A.), Laboratory of Molecular Carcinogenesis, National Institute of Environmental Health Sciences Microarray Center (L.B., P.R.B., C.A.A.), and Biostatistics Branch (L.L.), National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina 27709

Address all correspondence and requests for reprints to: Edward K. Lobenhofer, National Institute of Environmental Health Sciences, P.O. Box 12233 MD2-04, Research Triangle Park, North Carolina 27709. E-mail: lobenho1{at}niehs.nih.gov.


    ABSTRACT
 TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 
The steroid hormone estrogen can stimulate mitogenesis in hormone-responsive breast cancer epithelial cells. This action is attributed to the transcriptional activity of the ER, a ligand-dependent transcription factor. However, the exact molecular mechanism underlying estrogen-induced proliferation has yet to be completely elucidated. Using custom cDNA microarrays containing many genes implicated in cell cycle progression and DNA replication, we examined the gene expression of a hormone-responsive breast cancer cell line (MCF-7) treated with a mitogenic dose of estrogen in the absence of confounding growth factors found in serum. Gene expression changes were monitored 1, 4, 12, 24, 36, and 48 h after estrogen stimulation so that RNA levels at critical times throughout cell cycle progression could be monitored. Significant changes include the altered transcript levels of genes implicated in transcription, cellular signaling, and cell cycle checkpoints. At time points during which increased numbers of cells were progressing through S phase, a majority of the genes associated with the DNA replication fork were also found to be induced. The coexpression of DNA replication fork genes by estrogen without the support of serum growth factors indicates an important estrogen regulatory component of the molecular mechanism driving estrogen-induced mitogenesis.


    INTRODUCTION
 TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 
THE HYPOTHESIS THAT the ovaries could cause increased growth of breast cancer tumors was initially postulated over 100 yr ago (1). Since that original theory was published, the ability of the ovaries to effect the proliferation of some malignant breast tumors was determined to result from the ovarian production of the steroid hormone estrogen (reviewed in Ref. 2). The molecular mechanisms underlying estrogen’s proliferative action have been studied extensively. According to the classical model, estrogen binds a member of the nuclear receptor superfamily known as the ER (reviewed in Ref. 3). Upon ligand binding, ER undergoes a conformational change, enabling receptor dimerization and subsequent binding to DNA at specific palindromic consensus sequences (estrogen response elements or EREs). Once bound to an ERE, the ER dimer recruits members of the general transcription machinery to modulate the transcription of target genes. EREs have been identified for several genes involved in cell cycle progression, such as the immediate early genes c-myc and c-fos (4, 5). In addition, estrogen’s regulation of gene expression may also result from the ability of ER to complex with other transcription factors, such as Sp1 and AP-1 (reviewed in Refs. 6, 7).

The nongenomic actions of estrogen may also modulate gene expression patterns. For example, several groups demonstrated that estrogen activates the MAPK cascade in breast cancer cells (8, 9). Although the kinetics of the induction are debated, pharmacological inhibition of this pathway abrogates estrogen-induced mitogenesis of estrogen-responsive, breast carcinoma-derived MCF-7 cells (10, 11). This suggests MAPK activity is a requirement for estrogen action; one of the culminating events of the MAPK cascade is activation of the transcription factor elk1, which may lead to further estrogen-associated gene expression changes (12).

Estrogen’s ability to regulate gene expression in cell culture model systems is affected by culturing conditions. The ability of MCF-7 cells to proliferate in response to a physiologically relevant concentration of estrogen is retained in serum-free conditions, albeit at a slower rate than cells stimulated in the presence of charcoal-stripped serum (CSS) (13). Estrogen treatment of MCF-7 cells in the presence of serum growth factors results in increased expression of the progesterone receptor (14, 15). However, Katzenellenbogen and Norman (16) demonstrated that in the absence of serum, a broad range of estrogen concentrations are unable to stimulate progesterone receptor levels. This suggests that a component of serum is necessary but not sufficient to increase progesterone receptor levels. Interestingly, synergy of estrogen with serum components is not necessary for induction of all estrogen-responsive genes. For example cathepsin-D levels are increased in response to estrogen regardless of the presence or absence of serum (17). Additional studies, including the one presented here, that analyze the effect of estrogen in serum-free conditions will allow further elucidation of the estrogen targets vs. those that result from multiple growth factor triggers/synergies.

A significant amount of research has focused on the changes evoked by estrogen that enable a cell to proceed through the G1/S checkpoint. Cumulatively, these studies have demonstrated that increased expression of cyclin D1 is one of the rate-limiting steps for progression into the DNA replication stage of the cell cycle (reviewed in Ref. 18). Cyclin D1 protein then binds to the cyclin-dependent kinase cdk4, generating an active kinase complex. This complex, as well as cyclin E/cdk2, phosphorylate the retinoblastoma (Rb) protein, which is bound to the transcription factor E2F. Phosphorylation of Rb stimulates the dissociation of E2F, enabling E2F to mediate the transcription of responsive genes required for DNA replication (19). These findings suggest that estrogen-induced expression of cyclin D1 is capable of relieving the negative regulation of E2F, thereby permitting replication of the genome. Many E2F target genes with functions implicated in DNA replication have been identified, most recently in microarray-based studies (20, 21, 22). However, increased expression of these genes, with the exception of proliferating cell nuclear antigen (PCNA), in response to estrogen stimulation has not been previously examined.

To clarify the molecular mechanisms underlying estrogen’s ability to drive cell cycle progression, we sought to identify transcriptional changes in genes associated with replication after estrogen stimulation in the absence of serum using cDNA microarray technology. To maximize statistical confidence in the data analysis, we employed a targeted gene chip for these studies (23). Our custom gene chip was spotted with 1,901 human genes containing genes especially selected for hormone-regulated studies. The chip contains genes from classes including transcription factors, kinases, phosphatases, growth factors, metabolism, and cell cycle genes, in addition to over 200 genes implicated in DNA replication and repair and the response to estrogen. This chip provided a powerful tool to study the global expression profile resulting from estrogen stimulation of MCF-7 cells. RNA isolated from MCF-7 cells treated with a physiological concentration of E2, the most prevalent estrogen produced by the ovaries, was harvested at six separate time points to follow the kinetics of regulated gene expression. In addition to revealing clues regarding the mechanisms of estrogen action, this work establishes an expression fingerprint for estrogen-regulated transcriptional events in breast epithelial-derived cells and adds to past studies using oligonucleotide arrays and other molecular techniques to identify estrogen- regulated targets (24, 25, 26, 27, 28). This information can be used as a benchmark to further explore the tissue-specific changes modulated by estrogen, and the action of clinically relevant estrogen antagonists (such as tamoxifen and raloxifene), as well as to serve as a base for the development of an estrogen-associated gene signature that may be used to screen for estrogen mimics (29).


    RESULTS
 TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 
Estrogen-Induced Proliferation
The breast cancer epithelial cell line MCF-7 is estrogen responsive. When these cells are deprived of serum for 24 h, the majority of the cells accumulate early in the G1 stage of the cell cycle (30). Treatment with E2 stimulates these growth-arrested cells to proliferate. We were specifically interested in identifying E2- mediated effects without potential confounding effects by serum factors to identify a pure estrogen gene expression signature. Therefore, the ability to use E2 in the absence of serum was explored so that the possibility of measuring effects related to the synergistic actions of E2 with peptide growth factors present in CSS was eliminated. Doses of E2 sufficient to stimulate mitogenesis were identified using a modified E-SCREEN proliferation assay (Fig. 1AGo). Consistent with previous findings (13, 31, 32), concentrations of E2 in excess of 1 x 10-11 M were able to stimulate a measurable increase in cell number (2.5- to 3-fold) in the presence or absence of CSS. The magnitude of the proliferative response was greater in the presence of serum, indicating the ability of E2 to synergize with growth factors present in the hormone-depleted serum.



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Figure 1. Proliferation and Viability of MCF-7 Cells in Response to Variable Concentrations of E2 in Different Serum Conditions

A, To measure proliferation, MCF-7 cells were deprived of steroid hormones for 24 h by culturing in either CSS (10% CSS, {blacksquare}) or complete serum starvation (No Serum, {square}). To assess the mitogenic potential of estrogen in these three different serum conditions, cells were then stimulated with various concentrations of E2 for 5 d. Total cell counts were assessed using a Coulter counter and are represented as an average of three independent samples. (The physiological range of total E2 in women is between 50 to 350 pg/ml (1.8 x 10-10 M to 1 x 10-9 M). B, To assess viability, MCF-7 cells were cultured in either complete medium containing 10% FCS (Log), phenol red free medium containing 10% CSS, or phenol red free medium without any serum additions (No Serum). After the indicated period of time, detached and attached cells for each condition were pooled and pelleted. Cell pellets were resuspended in a small volume of PBS and stained with erythrosin B. The percentage of cells excluding the dye (viable) was determined by microscopic examination (500 total cells counted in two separate experiments).

 
To ensure that the absence of serum would not dramatically alter cell survival, the viability of MCF-7 cells in serum-free and 10% CSS containing medium was characterized. After 48 h of treatment, there was little difference between the samples stimulated in the presence of 10% CSS and the serum-free samples (Fig. 1BGo). This is important to examine because microarray data are expressed as a ratio of the level of expression of estrogen-treated vs. control cells. Changes in the expression of genes in the control cells, due to cell death for example, would be reflected in the expression ratios, and could be wrongly interpreted as changes mediated by estrogen. The similarity of viability regardless of the presence or absence of 10% CSS (90% without serum, 92% with serum), at the 48-h time point (i.e. the longest time point in the experiment) assured us that the effects we were observing were due to estrogen-induced proliferation not cell death of controls.

Relative Levels of ER{alpha} and ERß in MCF-7 Cells
Currently, two distinct forms of the ER have been identified that not only demonstrate different expression patterns in target tissues but also regulate the expression of different genes (33, 34, 35). Therefore, a pervasive question in estrogen-associated mechanistic studies is which receptor is mediating the observed estrogen-induced responses. Though the tissue- specific expression of ER{alpha} and ERß has been documented, it was reported that different MCF-7 variants do not express the same levels of each receptor (36). For this reason, the relative expression level of each receptor was measured using semiquantitative RT-PCR (Fig. 2Go). Consistent with previously published findings, T47D and MCF-7 cells express ER{alpha}, whereas SKBR-3 cells do not (37). Furthermore, our particular T47D variant expresses ERß, whereas SKBR-3 and MCF-7 cells do not demonstrate detectable levels of this receptor. These findings indicate that the changes in the global expression profile of MCF-7 cells stimulated with estrogen in this study result from either the nongenomic actions of estrogen or transcriptional mechanisms involving ER{alpha}, or both.



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Figure 2. ER{alpha} and ERß Transcript Levels in MCF-7 Cells

SKBR-3, T47D, and MCF-7 cells were grown for 24 h in complete medium and harvested for RT-PCR analysis of ER{alpha}, ERß, and GAPDH levels as described in the Materials and Methods section. PCR products were separated and visualized on a 1.2-% agarose gel. No RNA was added to the "No template" reaction to serve as a negative control.

 
Expression Profiling of MCF-7 Cells Treated with E2
To gain insight into the estrogen-induced transcriptional events that drive cell cycle progression of hormone-responsive breast cancer epithelial cells, we examined the expression profile of serum-starved MCF-7 cells stimulated with a mitogenic dose of estrogen. Estrogen-treated cells were harvested after 1, 4, 12, 24, 36, and 48 h of treatment. RNA extracted from these cells was fluorescently labeled with either Cy3- or Cy5-dUTP via a reverse transcription reaction (38, 39). Labeled samples were hybridized along with a time-matched vehicle control (labeled with the other fluorophore) to the microarrays. To identify genes demonstrating altered expression, a probability distribution was fit to the calibrated ratios (estrogen-treated vs. control), and this distribution was then used to derive confidence levels for the ratios (40). We employed database filtering to compile genes significantly changed at each time point (41). We selected genes that were shown to be significantly changed by estrogen using a 95% confidence level in at least four hybridizations. A binomial probability calculation (Microarray Project Systems) indicated that selection from replicates reduced the probability of a false positive to less than 0.0004 (41). By reversing the fluorescently labeled nucleotides incorporated into the treated and vehicle samples, several genes were found to have discordant expression values for a given time point. These genes were considered as artifact of the fluorophore incorporation process and were excluded from the list of estrogen-regulated genes based on a coefficient of variance measure across replicate hybridizations in our database (see Data Analysis section of Materials and Methods for details) (41). This approach identified 105 different genes as estrogen-regulated for all 6 time points (Table 1Go). (For information pertaining to the level of induction and repression and at which time points these changes were statistically significant, see Table 4, which is published as supplemental data on The Endocrine Society’s Journals Online web site, http://mend. endojournals.org/). These genes were broadly categorized into nine different groups based on their known function, such as the transcription factors myc and myb, apoptotic genes including caspase 7, and genes involved in cellular signaling like PKC. Not surprisingly, several of these categories correlated well with the known phenotype resulting from estrogen stimulation, e.g. increased expression of genes involved in cell cycle progression and DNA replication. Many of these genes were previously identified as being regulated by estrogen stimulation (indicated in Table 1Go, e.g. cathepsin D, cyclin D1, c-myc, PCNA, etc.); however, many previously unreported genes also appeared to demonstrate estrogen-regulated expression, including two different DNA polymerases ({delta} and {epsilon}) as well as DNA ligase I. The induced expression of several genes involved in DNA replication was further validated by one of two different approaches (flap structure endonuclease-1 and Replication Factor C3 by Northern analysis and PCNA and stromal-derived factor-1 by real-time PCR) (data not shown). The expression levels measured by these alternative methods closely resembled the kinetics of expression observed with the microarray results.


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Table 1. Genes regulated by estrogen stimulation of MCF-7 cells

 
To ensure reproducibility of our data, we examined the variability in the expression of the all of the genes in the vehicle-control treated samples over the entire time course. The overall similarity of the controls at the six time points was measured by considering the correlation of the averaged log intensity values of 8 hybridizations for each of the six time points (Table 2AGo). The Pearson correlation coefficient was used to quantify this similarity, and the resulting correlation values suggest that there is good agreement between the controls across the six times. This process was also repeated using the 105 limited set of genes that were identified as significantly changed by estrogen exposure. The Pearson correlation coefficient values (see Table 2BGo) indicate that expression was generally stable as reflected by correlation, r-values, greater than 0.92 for the entire data set and 0.87 for the select gene set.


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Table 2. Correlation of the Expression Values Obtained from Ethanol (Control) Treatment

 
Finally, we wanted to be sure that none of the effects we observed could be attributed to the vehicle solvent, ethanol. The effect of ethanol in this model system was further explored by an additional series of four microarray hybridizations examining the expression profile of MCF-7 cells stimulated with ethanol (compared with no treatment) at 24 h. Analysis of the array data at the 95% confidence level indicates no genes were differentially expressed as a result of exposure to ethanol (Table 3Go). Cumulatively, the strong correlation of the ethanol-treated samples over time and the lack of any genes being identified as significantly regulated by ethanol indicates that the expression profiles observed in the estrogen-treated hybridizations is a result of the cellular response to estrogen as opposed to the vehicle. (The entire data set for ethanol and estrogen treatments is available at: http://dir.niehs.nih. gov/microarray/datasets/estrogen_ethanol_time_course.txt and http://mend.endojournals.org/).


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Table 3. Number of Genes Regulated by Estrogen or Ethanol Stimulation at Different Time Points

 
The compiled list of genes identified as regulated by estrogen in the time course were subjected to higher order analyses. The average log2 calibrated ratio for the differentially expressed genes was calculated for each individual time point and subjected to a hierarchical clustering algorithm (42). The resulting similarity matrix is depicted in the form of a dendrogram shown in Fig. 3Go. The degree of similarity of the various time points is reflected in the tree (illustrated on the top of the enlarged node). The location of the 1-h time point on its own branch indicates that it is the most dissimilar sample compared with all of the time points. At this early time, the main response to estrogen is the increased expression of immediate early genes, such as c-myc. Maximal expression levels of c-myc are achieved between 1 and 2 h after estrogen stimulation, and by 4 h near basal levels have been restored (43). Therefore, it was expected that this time point would have the least in common with the other time points. The dendrogram clearly illustrates that little difference exists between the 24 and 36 h time points. This is in agreement with cell cycle data, which demonstrates that at these intervals, a large proportion of the cells are actively undergoing DNA synthesis and progressing toward the mitosis phase of the cell cycle (data not shown). Also illustrated in this cluster is the expression profile of MCF-7 cells treated with estrogen for 24 h in the presence of CSS. The overall pattern is very similar to the one observed in the absence of serum for the same time frame. However, the tree reveals that the 24-h sample derived in the absence of serum is more similar to the 12, 36, and 48 h samples also isolated in the absence of serum. This may be due to overall increased levels of induction and repression in the presence of CSS, which would also be consistent with the increased levels of proliferation observed in Fig. 1AGo.



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Figure 3. Cluster Analysis of Estrogen-Regulated Genes

The average log2 calibrated ratio for all the genes demonstrating significantly induced or repressed expression in response to E2 were clustered using Eisen’s algorithm (42 ). The resulting similarity matrix was visualized using a dendrogram. When no difference was detected between the estrogen-treated and vehicle control samples a black color is present in the cell for that particular time point. If the gene is induced in the presence or estrogen, the level of induction is correlated with the intensity of the red color in the cell. Repressed expression is illustrated with green hues. The node outlined in yellow is magnified on the right and illustrates a tightly regulated group of genes that are induced after 12, 24, and 36 h of estrogen stimulation. Interestingly, many of these genes have previously been implicated in cell cycle progression and DNA replication. For comparison, also included is the expression level of these genes when MCF-7 cells are treated with estrogen in the presence of peptide growth factors found in CSS.

 
The Eisen clustering algorithm does not only apportion the individual time points, but also individual genes based on the similarities in their expression kinetics. Theoretically, genes with similar expression profiles may also have related function; the enlarged node present in Fig. 3Go represents a cluster of genes that support this theory. Genes comprising this cluster have been implicated in either cell cycle progression or the mechanics of DNA synthesis (Fig. 3Go).

The majority of the 100 genes spotted on the microarrays with functions implicated in DNA replication/repair were not found to be regulated by estrogen action at the time points examined. To fully assess the expression levels of these genes, the average log2 calibrated ratio for each time point for all of these genes were subjected to hierarchical clustering and visualized using TreeView (Fig. 4Go) (42). The preponderance of black hue throughout the time course for many of the genes indicates that estrogen treatment did not effect the basal transcript levels for these genes. Most of these genes are part of the machinery designed to repair the genome as opposed to functioning in normal replication. However, many of the genes involved in the DNA replication fork were found to have induced expression at 12, 24, and 36 h, including a few of the genes that were not included in the 95% confidence level list (e.g. replication factor C4 and C5) (enlarged node). Cumulatively, these experiments indicate that the majority of the genes associated with the DNA replication fork are induced after estrogen stimulation, suggesting an important component of the molecular mechanism driving estrogen-induced cell cycle progression.



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Figure 4. Cluster Analysis of All DNA Replication/Repair Genes Present on ToxChip

The average log2 calibrated ratio for all the genes present on ToxChip with functions implicated in DNA replication/repair were clustered using Eisen’s algorithm and visualized using the Eisen Tree program (42 ). As detailed in the legend for Fig. 3Go, a black color denotes that no difference in the expression levels was detected between the estrogen-treated and vehicle control samples. A red-colored cell indicates that the gene is induced in the presence of estrogen and the level of induction is correlated with the intensity of the red color in the cell. Repressed expression is illustrated with green hues. The vast majority of the genes included on this list are not responsive to estrogen, whereas several are repressed to a slight degree. However, the area outlined in yellow (magnified on the right) illustrates the coordinated expression of genes induced by estrogen stimulation and associated with DNA replication fork activity. A blue dot preceding the Unigene CloneID denotes genes that have been previously shown to be regulated by E2F (20 22 ).

 

    DISCUSSION
 TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 
Estrogen is capable of inducing cell cycle progression in hormone-responsive breast cancer cells. This proliferative action is found not only in cells grown in culture, but also in clinical samples. Therefore, a greater understanding of the molecular mechanisms underlying this mitogenic response is of importance. To identify transcriptional changes resulting from estrogen stimulation, we examined the gene expression changes at key points during cell cycle progression. Represented in this time series was an immediate early time point (1 h) when most cells were in early G1, a delayed early time point (4 h) with cells progressing toward the G1/S checkpoint, time points representing entry into S phase (12 h) and subsequent replication of the genome (24 and 36 h), and finally a return to an asynchronous population (48 h).

Collectively, the microarray analyses revealed many known genes and several expressed sequence tags (ESTs) as estrogen responsive, including many that were previously identified as hormone responsive. Interestingly, a large family of genes associated with the DNA replication fork (replication factor C, PCNA, flap structure endonuclease 1, DNA polymerase {delta}, DNA polymerase {epsilon}, and DNA ligase) (reviewed in Ref. 44) were found to be significantly up-regulated 12, 24, and 36 h after estrogen stimulation. These findings corroborate the hypothesis that estrogen-induced DNA synthesis results from a complex transcriptional network regulating the expression of not only genes essential for progression through the G1 checkpoint, but also those required for DNA synthesis, and that the induction of these genes may be initiated solely through estrogen action without the confounding or synergistic effects of serum factors.

The proteins associated with DNA replication have been identified and their actions have been characterized and extensively reviewed (reviewed in Refs. 44, 45). Briefly, the process of replicating the genome commences with a localized separation of the two DNA strands. This enables a helicase enzyme to bind the DNA and move unidirectionally along a DNA strand, dissociating the two strands and forming single-stranded templates. To prevent reassociation of the DNA strands before they are replicated, a complex of 3 proteins (collectively referred to as replication factor A) bind to the single-stranded DNA. Replication of the strands requires an RNA primer to be synthesized, which is performed by DNA polymerase {alpha}-primase. In semidiscontinuous DNA replication, synthesis of the 5' -> 3' strand (leading strand) results from elongation of a single primer, whereas the complementary, 3' -> 5' strand (lagging strand) is replicated from many different primers. Primer elongation begins with the binding of the multisubunit replication factor C to the primer terminus, where it recruits PCNA. PCNA functions as a sliding clamp by anchoring DNA polymerase {delta} or {epsilon} to the DNA. These polymerases synthesize the nascent DNA strand with high fidelity due, in part, to their proofreading exonuclease activity. To generate complete DNA strands, the RNA primers are removed by RNase H1, which nicks the 5' side of the 3' ribonucleotide. This generates a topology that is recognized by flap structure endonuclease-1, which removes the 3' ribonucleotide, producing a gap that is filled by DNA polymerase. The resulting nicked double-stranded DNA is then joined by DNA ligase I.

Consistent with the proliferative phenotype of MCF-7 cells treated with estrogen, a large number of DNA replication fork-associated genes were induced by estrogen. Regulated expression was observed for several of the replication factor C subunits, PCNA, DNA polymerase {delta}1 (the catalytic subunit), DNA polymerase {epsilon}, flap structure endonuclease-1, and DNA ligase I. RNase H1 was not present on the microarray chips, so the expression pattern was not determined. Despite previous data that E2 regulates the transcriptional activation of DNA polymerase {alpha} (46), several components of DNA polymerase {alpha}-primase complex remain at, or near, basal levels throughout the time course. The apparent discrepancy may be the result of the time points that were selected for analysis as Samudio et al. (46) demonstrated increased expression of DNA polymerase {alpha} 6 h after estrogen stimulation with near basal levels restored by 12 h. Therefore, the gene may not appear to be regulated in our study as a result of the time points that were selected (provided transcript levels increase between 4 and 6 h). Alternatively, the activity of DNA polymerase {alpha} may not be regulated at the transcriptional level. Support for this theory comes from the recent work by Schub et al. (47) demonstrating that the polymerase (180 kDa) and regulatory (70 kDa) are phosphorylated in a cell cycle-dependent manner by the S phase cyclin, cyclin A, and its associated kinase cdk2. Cyclin A/cdk2 complex formation and kinase activation in response to estrogen has been demonstrated previously (48). Phosphorylation of p70 subunit of DNA polymerase {alpha} correlates with maximal DNA polymerase {alpha}-primase activity, whereas phosphorylation of both p70 and p180 subunits inhibits primer formation. This suggests that estrogen-induced initiation of DNA replication may result from activation of kinase activities rather than a direct transcriptional effect on the subunits comprising DNA polymerase {alpha}-primase.

A similar scenario may explain the lack of regulated expression of the replication factor A subunits. Estrogen stimulated a slight increase in expression for the smallest subunit (p14), but both the 32- and 70-kDa subunits were unaffected (see Fig. 4Go and data not shown). p32 is a substrate for cdk1 when this kinase is complexed with cyclin A or B and is phosphorylated at the end of G1 and through the end of the S phase of the cell cycle (49, 50, 51). Phosphorylated p32 is found in complexes with the other replication factor A subunits and associated with chromatin (51). Therefore, it may be the phosphorylation of p32 rather than the enhanced transcription of replication factor A subunits that enables estrogen to stimulate activity at the DNA replication fork.

While many genes associated with the replication fork are induced transcriptionally as a result of estrogen treatment, this does not necessarily imply that these genes are regulated according to the classical model (ER binding to an ERE). Alternatively, these genes may be transcribed via one of the many transcription factors induced by estrogen (Table 1Go), the nongenomic actions of estrogen culminating in the activation of a transcription factor, or by increased expression of a protein that has downstream effects on the activation of a transcription factor. Increased activation of the transcription factor E2F-1 has been shown to result from estrogen stimulation (6, 52, 53). (Unfortunately, E2F-1 is not present on the ToxChip version 1.0 microarray chip). As detailed in the Introduction, increased expression of cyclin D1 can result in phosphorylation of Rb, which causes dissociation of E2F from the transcriptionally inactive Rb-E2F complex. Previous studies have demonstrated that E2F’s transcriptional activity results in increased expression of genes involved in DNA synthesis (reviewed in Ref. 54). Using oligonucleotide arrays, Ishida et al. (22) recently demonstrated that PCNA, flap structure endonuclease 1, an EST similar to a replication factor C subunit, and DNA ligase I are transcriptionally responsive to E2F. Additional work by Ren et al. (20) has also implicated replication factor C (activator 1) 3, the catalytic subunit of DNA polymerase delta 1, and minichromosome maintenance (mcm3) as E2F target genes. Searches of the public sequence databases revealed E2F sites in the promoter or other regulatory elements for 4 genes implicated in DNA replication (PCNA, DNA polymerase {epsilon}, mcm3, and mcm7) and found to be estrogen-regulated in the microarray data (55). As the promoters for the remaining genes are defined, it will be interesting to see whether they also are E2F regulated.

The preponderance of E2F-regulated genes in this data set suggests a molecular mechanism by which estrogen is capable of inducing DNA replication. In a recent study (24), Soulez and Parker treated ZR75–1 cells, another hormone-responsive breast cancer cell line, with estrogen in the presence of cyclohexamide, which allowed a means to measure the direct transcriptional effects of estrogen. Cyclin D1 was found to be induced with 6 h; however, no DNA replication fork genes were significantly regulated by estrogen in the presence of the protein synthesis inhibitor, indicating that these transcriptional events may be an indirect or secondary effect of estrogen stimulation. However, examining the kinetics of expression of these genes (Fig. 5Go) indicates cyclin D1 accumulates before the increased expression of the DNA replication fork genes. Therefore, our data, coupled with the findings of Soulez and Parker, suggest that increased expression of cyclin D1 is a direct effect of estrogen stimulation. Accumulation of cyclin D1 initiates a cascade of reactions, resulting in the liberation of E2F from Rb and enabling transcriptional activation of the DNA replication fork genes (Fig. 6Go).



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Figure 5. Expression Kinetics of DNA Replication Fork Genes

The average log2 calibrated ratio for a subgroup of the estrogen-responsive genes implicated in DNA replication and reported as being transcriptional targets of E2F were plotted across the entire time course. Maximum expression levels for these genes were attained between 12 and 36 h. In contrast, peak expression of cyclin D1 (red line), which has been implicated in transcriptional activation of E2F, was achieved within the first 4 h of estrogen stimulation.

 


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Figure 6. Model for the Regulation of DNA Replication Fork Genes by Estrogen

In the absence of a mitogen, unphosphorylated Rb is bound to E2F, preventing the transcription of E2F-responsive genes, such as those involved in DNA replication. Stimulation with estrogen causes accumulation of cyclin D1 protein, which results in the activation of G1 cyclin/cdk complexes that are capable of phosphorylating Rb (64 ). Phosphorylation of Rb causes the dissociation of the Rb/E2F complex, thereby relieving the transcriptional repression of genes involved in DNA replication.

 
Our present study demonstrates that MCF-7 cells treated with a physiological concentration of E2, in the absence of additive/synergistic growth factors present in CSS, respond with gene expression changes that strongly correlate with the proliferative phenotype. Many classes of genes were found to be differentially expressed after estrogen treatment, including genes associated with the DNA replication fork. Cumulatively, these findings suggest that estrogen increases the expression of many of the replication fork genes and may change the phosphorylation status of others to enable replication of the genome and subsequent mitogenesis. Because our variant of MCF-7 cells do not express ERß, these transcriptional responses must be initiated by either the nongenomic actions of estrogen or via ER{alpha}-mediated events (either transcriptional or nongenomic).

In addition to the pathways altered by estrogen action, this study also provides a data source to which future expression profile studies using estrogen can be compared. For example, the tissue-specific pattern of expression resulting from estrogen stimulation, the different transcriptional regulation emanating from the {alpha} and ß isoforms of the ER. Additionally, the identical series of experiments could be repeated in a different estrogen-responsive breast cancer cell line (e.g. T47D or ZR-751) and compared with this data set to further identify the specific expression changes modulated by estrogen. Alternatively, this data set could also be compared with microarray data examining the expression changes resulting from estrogen mimics or clinically relevant estrogen antagonists (such as tamoxifen and raloxifene) to better understand the mechanisms of action of these compounds and their resulting phenotype.


    MATERIALS AND METHODS
 TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 
Cell Culture
MCF-7, T47D, and SKBR-3 cells were obtained from American Type Culture Collection (Manassas, VA) and propagated in DMEM/F12 medium supplemented with 10% (vol/vol) FCS (HyClone Laboratories, Inc., Logan, UT) and 0.1 U penicillin/ml and 0.1 µg streptomycin/ml (Life Technologies, Inc., Grand Island, NY) at 37 C in 95% O2/5% CO2. Cells were grown in 150 mm tissue culture dishes (Nunc, Rochester, NY, catalog no. 168381) and split a maximum of 25 times. For experimental purposes, cells were seeded in either T-75 flasks ((2 x 106 cells/flask) (Corning, Inc., Corning, NY, catalog no. 430720), 6-well dishes (250,000 cells/well) (Falcon, Palo Alto, CA, catalog no. 3046), or 12-well dishes (50,000 cells/well) (Falcon, catalog no. 3043) in complete medium and allowed to adhere for 24 h. These specific culture dishes were chosen due to the reduced presence of estrogen-like compounds in the plastic that could leach into the culturing medium (Janine Calabro, Tufts University, unpublished data) (56, 57). For microarray hybridization experiments, ten T-75 flasks of MCF-7 cells per treatment condition were washed twice in PBS/calcium and magnesium-free (PBS-CMF) and then maintained in the complete absence of estrogen [DMEM/F12 without phenol red and FCS, but supplemented with penicillin and streptomycin (starvation medium)] for 24 h (58). After serum starvation, cells were treated with starvation medium supplemented with a physiologically relevant dose, 1 x 10-10 M, of E2 [or an equal volume of vehicle control (ethanol)] for 1, 4, 12, 24, 36, or 48 h. Alternatively, to assess the additive/synergistic effects of estrogen in the presence of CSS, cells were hormone-deprived for 24 h in CSS-containing medium and then treated with 1 x 10-10 M E2 in fresh medium. Cells were harvested by washing once in ice-cold PBS-CMF followed by scraping (Costar Cell Scraper, Acton, MA) in 5 ml PBS-CMF. Similar cultures were pooled, pelleted, and stored at -80 C.

Proliferation Assay
Proliferation of MCF-7 cells was measured using a modified E-SCREEN assay (59). Briefly, 5 x 104 cells were seeded in 12-well dishes. After sufficient time for cells to adhere (24 h), the cells were washed twice with PBS-CMF and maintained in starvation medium for an additional 24 h. Cells were stimulated (in triplicate) with various concentrations of E2 in starvation medium containing 10% CSS or in the complete absence of serum. Five days after treatment, cells were harvested by trypsinization and relative cell numbers from each treatment condition were obtained using a Coulter counter (Beckman Coulter, Inc., Miami, FL).

Viability Assay
Cell viability was assessed by a dye exclusion technique. Cells were seeded in six-well dishes before treatment with either 10% CSS containing medium or serum-free medium. Detached and attached cells for each condition were pooled and pelleted. Cell pellets were resuspended in a small volume of PBS and stained with erythrosin B (0.075% final concentration). The percentage of cells excluding the dye (viable) was determined by microscopic examination (500 total cells counted in two separate experiments).

RNA Isolation
For microarray hybridizations, approximately 5 x 107 cells were resuspended in 4 ml of Buffer RLT (QIAGEN, Valencia, CA) before lysing using 3x 30-sec bursts of sonication in a Sonic Dismembrator (Fisher Scientific Model 60, Pittsburgh, PA) set at level 8. Total RNA was isolated using QIAGEN RNeasy Midi columns after the manufacturer’s protocol. Eluted RNA was concentrated (>=9 µg/µl) using Microcon-30 columns (Millipore Corp., Bedford, MA).

RT-PCR Analysis of ER{alpha} and ERß Expression
RNA was extracted from 1 x 106 cells using a combination of QiaShredder columns to lyse cells and QIAGEN RNeasy Mini columns to isolate total RNA. cDNA synthesis and amplification of ER{alpha}, ERß, and glyceraldehyde-3-phosphate dehydrogenase (GAPDH) messages was performed using the ProSTAR HF Single Tube RT-PCR System (Stratagene, La Jolla, CA) after the manufacturer’s protocol. All primers were previously described: Burow et al. (36) detailed the ERß and GAPDH primers, whereas Pasquali et al. (60) reported the use of the ER{alpha} primers.

Real-Time PCR
RNA (2 µg) from all time points and treatment conditions was reverse transcribed 250 U MultiScribe RTase (Applied Biosystems, Foster City, CA) in a 200 µl reaction mix containing 5.5 mM magnesium chloride, 1x PCR Buffer II (Applied Biosystems), 500 µM each deoxynucleotide triphosphate, 2.5 µM random hexamer (Applied Biosystems), 80 U RNase inhibitor (Applied Biosystems). The reaction was incubated at 25 C for 10 min, 48 C for 30 min, and finally 95 C for 5 min. The resulting cDNA (10 µl) was amplified in triplicate using gene specific primers (listed below) using the SYBR Green PCR Core Reagents (Applied Biosystems) after the manufacturer’s recommended protocol. The amplification reaction was performed in an ABI Prism 7700 Sequence Detector (Applied Biosystems) with the following cycling conditions: an initial incubation of 95 C for 10 min followed by 50 cycles of 95 C for 15 sec and 60 C for 1 min. The threshold cycle for each amplification was determined using Sequence Detection System software (Applied Biosystems). The levels of expression for each gene were normalized using 36B4 levels after the comparative threshold cycle method (61, 62).

Northern Blotting
RNA (5 µg) was electrophoresed on a 1% agarose-2.2 M formaldehyde gel then transferred onto a Nytran N membrane (Schleicher \|[amp ]\| Schuell, Inc., Keene, NH). Blots were cross-linked using UV irradiation and hybridized with 32P-labeled gene-specific probes generated by random priming. 36B4 Plasmid (kindly provided by Donald P. McDonnell) was digested with PstI and the 700-bp fragment was used in the labeling reaction. Flap structure-specific endonuclease 1 (Unigene CloneID 49950) was digested with NotI and HindIII and the resulting 1422-bp fragment was used in the labeling reaction. Replication factor C3 (38 kDa) (Unigene CloneID 256260) was digested with NotI and EcoRI and the resulting 1473-bp fragment was used in the labeling reaction). After overnight hybridizations, blots were washed for 10 min at 65 C with 2x SSC (150 mM NaCl and 15 mM Na3C6H3O7, pH 7.0) containing 1% SDS and then with 0.1x SSC/0.1% SDS before exposing a PhosphorImager screen (Molecular Dynamics, Inc., Sunnyvale, CA). IMAGEQuant (Molecular Dynamics, Inc.) was used to quantify the expression levels of the gene of interest and loading inconsistencies were corrected using detected levels of 36B4 expression.

cDNA Microarray
cDNA microarray analysis was conducted on two replicate cultures. A sufficient quantity of total RNA (35 µg for Cy3-labeled probes and 75 µg for Cy5 were used for microarray analysis of the first biological replicate; 30 µg was used for either label during the second replicate) in a volume of 17 µl was combined with 2 µl 500 µg/ml oligo(dT) (12, 13, 14, 15, 16, 18) primer (Amersham Pharmacia Biotech, Piscataway, NJ) and 1 µl RNasin (10 U/µl) (Invitrogen, Carlsbad, CA) before heating for 10 min at 70 C. After chilling on ice for 2 min, 9 µl 5x buffer (250 mM Tris-HCl, pH 8.3; 375 mM KCl; 15 mM MgCl2) (Invitrogen), 5 µl 0.1 M dithiothreitol (Invitrogen), 4 µl 25 nM FluoroLink Cy3-deoxyuracil triphosphate or Cy5-deoxyuracil triphosphate (Amersham Pharmacia Biotech), 1.2 µl [25 mM deoxy (d)-ATP, 25 mM dGTP, 25 mM dCTP, 15 mM deoxythymidine triphosphate] deoxynucleotide triphosphate mix (Amersham Pharmacia Biotech), and 2 µl SuperScript II Reverse Transcriptase (Invitrogen). Samples were incubated at 42 C for 1.5 h prior to adding an additional 2 µl of SuperScript II Reverse Transcriptase and incubating another 1.5 h. After cDNA synthesis, 30 µl of 0.1 M NaOH was added and incubated at 70 C for 30 min to degrade the RNA. The pH was then returned to neutral by adding 30 µl of 0.1 M HCl. Cy3- and Cy5-labeled probes were pooled and unincorporated label was removed by using a Microcon-30 filter (Millipore Corp.). Before recovering the probes 10 µg/µg of RNA of human COT1 DNA (Invitrogen), and 20 µg of yeast tRNA (Invitrogen) were added to limit nonspecific binding of the probe during the hybridization. Probes were added to a hybridization solution (3x SSC, 2x Denhardt’s, and 0.3x SSC), boiled for 2 min, and purified through a 0.45 µM filter (Millipore Corp.). The purified solution was then applied to a glass cDNA microarray slide, covered with a coverslip, and incubated for 16 h in a humidified chamber at 65 C. These custom cDNA chips (ToxChip version 1.0) contain 1901 known human genes and ESTs, categorized based on their cellular function: apoptosis, cell cycle control, DNA replication and repair, heat shock proteins, oncogenes and tumor suppressors, kinases, phosphatases, transcription factors, etc. (reviewed in Ref. 63). (The database of genes present on ToxChip version 1.0 can be searched at http://dir.niehs.nih.gov/microarray/chips.htm). Slides were inverted in 0.5x SSC, 0.01% SDS for 3 min in order to remove the coverslip passively and minimize spot damage. The slide was washed for an additional 3 min in a fresh 0.5x SSC, 0.01% SDS. The slide was then washed twice with 0.06x SSC for 3 min before spinning for 3 min at 1000 rpm. A GenePix 4000A-microarray scanner (Axon Instruments, Inc., Union City, CA) was used to scan and generate image files of the arrays. Each RNA was hybridized to four arrays, two with each dye orientation. Because each time point was also biologically replicated a total of eight arrays for each time point was analyzed.

Data Analysis
Signal intensities from the image files were quantified and normalized using IPLabs image processing software (Scanalytics, Inc., Fairfax, VA) with the ArraySuite extensions (National Human Genome Research Institute) that are based on the algorithm previously described by Chen et al. (40). This software package identifies genes that demonstrate statistically significant expression changes for a user-defined confidence level. Genes identified as being up- or down-regulated at the 95% confidence level were stored in Microarray Project Systems, a database that is used to manage and interpret gene expression data (41). (For information pertaining to the fold-cutoff that was used for all 60 hybridizations, see Table 5 in the supplemental data.) To increase the statistical confidence in the data, only the genes found to be altered at the 95% confidence level in at least four out of the eight hybridizations for a given time point were considered for further analysis. Furthermore, the average fold-induction of all eight hybridizations for these genes needed to exceed 1.3 to be included for further analysis. To identify genes in this list that demonstrated a bias for a particular fluorophore or highly variable expression, the coefficient of variation (CV) for each gene was calculated. The CV (SD/absolute value of the calibrated ratio) was computed using the log2 ratio intensity values of the genes detected as differentially expressed at a given confidence level. Genes with a CV value greater than 0.43 were eliminated from the list before clustering. (For information on the level of induction and repression, and at which time points the changes were statistically significant, see Table 4 in the supplemental data.)

Correlation Analysis
To assess the stability of gene expression for the vehicle-control treated cells, the pixel intensity values for the control samples were compiled from each array. After transforming to the log2 scale, each value was standardized using the mean and standard deviation of all log intensity values on that array using JMP (SAS Institute, Inc., Cary, NC). Averaging the standardized log intensities for replicates gave a 1900 x 6 matrix of values, where the rows represent all genes on the array and the columns represent the six time points. The similarity between the time points was then measured using Pearson correlation. The same procedure was carried out for the smaller set of genes that were identified as differentially expressed.


    ACKNOWLEDGMENTS
 
We thank Asad Umar and Tom Kunkel for generating the list of DNA replication and repair clones spotted on the microarray chip; Carolyn Markey and Janine M. Calabro for invaluable guidance on tissue culture conditions; Retha Newbold, Tom Kunkel, Richard Santen, Sylvia Hewitt, Richard DiAugustine for stimulating discussions and critical review of the manuscript; Karla Martin and Jeff Tucker for technical assistance and printing the cDNA microarray chips; Magdalena A. Bilska for experimental support; Chris R. Miller and Nigel Walker for invaluable expertise designing and performing the real-time PCR validation experiments; Jennifer B. Collins for tissue culture assistance and guidance in generating figures; and Jonathan Miller for bioinformatics support.


    FOOTNOTES
 
Abbreviations: cdk, Cyclin-dependent kinase; CMF, calcium and magnesium-free; CSS, charcoal-stripped serum; CV, coefficient of variation; d, deoxy; E2, 17ß-estradiol; ER, estrogen receptor; ERE, estrogen response element; EST, expressed sequence tag; GAPDH, glyceraldehyde-3-phosphate dehydrogenase; mcm, minichromosome maintenance; PCNA, proliferating cell nuclear antigen; Rb, retinoblastoma.

Received for publication January 3, 2002. Accepted for publication March 12, 2002.


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