Phenotypic anchoring of gene expression changes during estrogen-induced uterine growth.

A major challenge in the emerging field of toxicogenomics is to define the relationships between chemically induced changes in gene expression and alterations in conventional toxicologic parameters such as clinical chemistry and histopathology. We have explored these relationships in detail using the rodent uterotrophic assay as a model system. Gene expression levels, uterine weights, and histologic parameters were analyzed 1, 2, 4, 8, 24, 48, and 72 hr after exposure to the reference physiologic estrogen 17[beta]-estradiol ([E.sub.2]). A multistep analysis method, involving unsupervised hierarchical clustering followed by supervised gene ontology--driven clustering, was used to define the transcriptional program associated with [E.sub.2]-induced uterine growth and to identify groups of genes that may drive specific histologic changes in the uterus. This revealed that uterine growth and maturation are preceded and accompanied by a complex, multistage molecular program. The program begins with the induction of genes involved in transcriptional regulation and signal transduction and is followed, sequentially, by the regulation of genes involved in protein biosynthesis, cell proliferation, and epithelial cell differentiation. Furthermore, we have identified genes with common molecular functions that may drive fluid uptake, coordinated cell division, and remodeling of luminal epithelial cells. These data define the mechanism by which an estrogen induces organ growth and tissue maturation, and demonstrate that comparison of temporal changes in gene expression and conventional toxicology end points can facilitate the phenotypic anchoring of toxicogenomic data. Key words: estrogen, gene expression, microarray, phenotypic anchoring, uterus. Environ Health Perspect 112:1589-1606 (2004). doi: 10.1289/txg.7345 available via http://dx.doi.org/[Online 7 October 2004]

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Gene expression profiling, used within the existing framework of toxicologic assessment, promises to advance significantly the mechanistic understanding and prediction of adverse effects. To benefit fully from the opportunities offered by gene expression profiling, we must first understand the relationships between changes in gene expression and alterations in traditional toxicology parameters. The process by which gene expression changes are linked to changes in phenotype has been termed "phenotypic anchoring" (Cunningham et al. 2003; Paules 2003; Schmidt 2003). This approach has been used successfully to identify groups of genes whose expression correlates with specific pathologic changes during griseofulvin-induced chronic liver injury (Gant et al. 2003), renal toxicity (Amin et al. 2004), furan-mediated hepatotoxicity (Hamadeh et al. 2004), and acetaminophen-induced hepatotoxicity (Heinloth et al. 2004). In the present study we used phenotypic anchoring, in conjunction with gene ontology analysis, to define the transcriptional program associated with the response of the rodent uterus to a reference estrogen and to identify groups of genes that may drive specific histologic changes.

The immature mouse uterus is a major estrogen-responsive organ and forms the basis for a reference assay of estrogenic activity of chemicals (Owens and Ashby 2002). The physiologic response of the uterus to exogenous estrogens has been documented in detail (Clark and Mani 1994). The immature mouse uterus is sensitive to elevations in endogenous levels of 17[beta]-estradiol ([E.sub.2]) that occur during puberty. [E.sub.2] releases the immature uterus from quiescence and promotes cell proliferation and differentiation. The initial effects of [E.sub.2] are rapid (4-6 hr) and involve the uptake of fluid resulting from hyperemia and vasodilation of uterine capillaries, which causes the uterus to swell. This phenomenon is termed "water imbibition" and increases the availability of substrates and ions required for growth. Another early event is an increase in overall levels of mRNA and protein synthesis. The uterus then enters a proliferative phase that is responsible, at least in part, for the large increase in uterine weight that occurs 16-30 hr after [E.sub.2] exposure. Later responses mimic the changes in uterine physiology that accompany the onset of puberty and include alterations in the surface of the luminal epithelia.

Although the events described above have been characterized at the physiologic level, little is known about how [E.sub.2] acting through the estrogen receptors ER-[alpha] and ER-[beta], coordinates at the molecular level the myriad cellular processes involved, despite significant progress in elucidating the molecular mechanisms by which ERs regulate gene expression in vitro (Hall et al. 2001; McKenna and O'Malley 2002; Metivier et al. 2003; Moggs and Orphanides 2001; Moggs et al. 2003; Tremblay and Giguere 2002). Our data reveal the transcriptional program associated with [E.sub.2]-induced uterine growth. We show that [E.sub.2] induces a tightly coordinated transcriptional program that regulates successive and interlinked cellular processes during the uterotrophic response. Moreover, by comparing changes in gene expression with alterations in uterine weight and histology, we have identified classes of genes that may drive specific histologic changes in the uterus, including fluid uptake, coordinated cell division, and remodeling of the luminal epithelial cell layer in preparation fur embryo implantation. Our data also provide novel insights into how [E.sub.2] initiates paracrine signaling events, recruits immune and inflammatory cells, increases mRNA and protein synthesis, and suppresses apoptosis.

These data describe, at an unprecedented level of detail, how [E.sub.2] induces organ growth and maturation and provide a paradigm for understanding the mechanisms of action of other nuclear receptors. Furthermore, this study demonstrates that analysis of the temporal associations between a chemically induced transcriptional program and the accompanying histologic changes can provide valuable insight into the relationships between gene expression changes and phenotypic alterations.

Materials and Methods

Animals

Female Alpk:[Ap.sub.f]CD-1 mice (19 20 days old), weighing no more than 14 g on arrival in the laboratory, were obtained from a barriered animal breeding unit (AstraZeneca, Macclesfield, Cheshire, UK). The animals were housed five per cage in solid-bottom cages and allowed to acclimatize for 24 hr. They were allowed RM1 diet (Rat and Mouse No. 1; Special Diet Services Ltd., Witham, Essex, UK) and water ad libitum for the duration of the study. All animal experimentation described in this article was conducted in accord with accepted standards (local and national regulations) of humane animal care. Group sizes of 10 animals were used for the first two of the three replicate studies. Five animals per group were used in the third replicate study.

Uterotrophic Assays

The mice were given a single subcutaneous injection of [E.sub.2] (400 [micro]g/kg) or arachis oil (AO; vehicle control) using a dosing volume of 5 mL/kg body weight. A single dose of [E.sub.2] was used to avoid the complex transcriptional program that may result from the standard uterotrophic assay exposure regime (i.e., repeated administration on 3 consecutive days; Odum et al. 1997). The relatively high dose level of 400 pg/kg was chosen to ensure a sustained and significant increase in blotted uterine weight during the 72-hr sampling period (Supplemental Data, Figure 1). No overt toxicity was observed during the 72-hr exposure to [E.sub.2] (400 [micro]g/kg). All animals were terminated at the appropriate time using an overdose of halothane (Concord Pharmaceuticals Ltd., Essex, UK) followed by cervical dislocation. Vaginal opening was recorded, and the uterus was then removed, trimmed free of fat, gently blotted, and weighed. Blotted uterine weights were analyzed by covariance with terminal body weights (SAS Institute Inc. 1999). Half of each left uterine horn was fixed in 10% formol saline and processed to paraffin wax for histologic analysis (Odum et al. 1997). The mean thickness of the endometrial and epithelial cell layers, indicators of cellular hypertrophy, were calculated based on the assessment of 10 locations on hemotoxylin-and eosin-stained longitudinal uterine sections for each animal. All hypertrophy data were assessed for statistical significance by analysis of variance (ANOVA). The remainder of the uterus was snap frozen in liquid nitrogen and stored at 70[degrees]C for RNA extraction.

[FIGURE 1 OMITTED]

Mitotic Index

The total number of mitotic figures in each uterus section was counted, noting the tissue location, and the area of the section was measured using a KS400 image analysis system (Imaging Associates, Bicester, UK). The number of mitotic figures per square millimeter was calculated, and the frequency after administration of [E.sub.2] was compared with the frequency seen after the administration of AO using an appropriate statistical procedure. The number of mitoses per square millimeter was considered by a fixed-effects ANOVA allowing for treatment, time, and the treatment by time interaction. Analyses were carried out using the MIXED procedure in SAS, version 8.2 (SAS Institute Inc. 1999). Contrasts within the treatment by time interaction provided estimates of differences in [E.sub.2] and control response at each time point. These were compared statistically using a two-sided Student t-test based on the error mean square in the ANOVA.

Transcript Profiling and Data Analysis

Three independent biologic replicates of the entire time course study for [E.sub.2]-treated and time-matched AO-treated groups of animals were used to generate transcript profiling data and for subsequent statistical analysis. To minimize the effect of any interanimal variability, total RNA was isolated from the pooled uteri for each treatment group (n = 10 in the first two studies; reduced to n = 5 for the last study because of highly similar transcriptional responses being obtained in replicate studies 1 and 2) using RNeasy Midi kits (Qiagen Ltd., Crawley, West Sussex, UK). Biotin-labeled complementary RNAs were synthesized using the Enzo Bioarray HighYield RNA transcript labeling kit and hybridized to Affymetrix routine U74-Av2 GeneChips as described previously (Zhu et al. 2001) and in the Affymetrix GeneChip expression analysis technical manual (Affymetrix, Inc. 2002). Probe arrays were scanned and the intensities were averaged using Microarray Analysis Suite 5.0 (Affymetrix, High Wycombe, UK). The mean signal intensity of each array was globally scaled to a target signal value of 500. To select [E.sub.2]-responsive genes, each gene was subjected to a mixed-model ANOVA allowing for treatment, time, and the treatment by time interaction as fixed effects and replicate study as a random effect. The use of mixed ANOVA models for the analysis of differential gene expression in microarray experiments has been previously described (Churchill 2004; Cui and Churchill 2003). Analyses were carried out using the MIXED procedure in SAS, version 8.2 (SAS Institute Inc. 1999). Contrasts within the treatment by time interaction provided estimates of differences in [E.sub.2] and control response at each time point. These were compared statistically using a two-sided Student t-test based on the error mean square in the ANOVA [Supplemental Data, Table 1 (http://ehp.niehs.nih.gov/txg/ members/2004/7345/supplemental.pdf)]. Data for genes exhibiting significant changes in expression (p, < 0.01, two-sided) at one or more time points were then exported into GeneSpring 6.0 (SiliconGenetics, Redwood City, CA, USA), and a data transformation (values < 0.01 set to 0.01) and per-chip normalization (to the 50th percentile) were applied. Genes that did not have a Present detection call (Affymetrix) in any of the 14 treatment groups were removed from further analysis. Ratios of changes in gene expression were then calculated by normalizing each [E.sub.2]-treated sample to its corresponding time-matched vehicle (AO)-treated control. GeneChip data sets for the three independent biologic replicates were interpreted in log of ratio analysis mode, with biologic replicates being selected as a noncontinuous parameter. A total of 3,538 [E.sub.2]-responsive genes exhibiting a minimum of 1.5-fold up- or down-regulation in at least one rime point were then subjected to gene tree-based hierarchical clustering (Pearson correlation). To identify genes that function in specific biologic pathways, these 3,538 genes were further filtered using functional annotations derived from the NetAffx database, Analysis Center (Liu et al. 2003; http:// www.affymetrix.com/analysis/index.affx), together with manual annotations from published literature, before hierarchical clustering using GeneSpring. Gene names used in this article (see Appendix) were derived by homology searching of nucleotide sequence databases (BLASTn; http://www.ncbi.nih.gov/BLAST/) using Affymetrix probe target sequences and the interrogation of NetAffx (Liu et al. 2003) database. All genes described in the figures and text showed statistically significant alterations in expression in all three replicate studies. MIAME (Minimum information About a Microarray Experiment)-compliant microarray data for the three independent replicate studies are available as supplementary information and have been submitted to the Gene Expression Omnibus (GEO) database (http://www.ncbi.nlm.nih.gov/geol).

Quantitative Real-Time Polymerase Chain Reaction

Uterine RNA was isolated and purified from all [E.sub.2]-treated and time-matched vehicle control groups (each consisting of pooled uteri) in all three replicate time course studies using the Qiagen RNeasy Midi kit (Qiagen). Before reverse transcription, RNA was treated with Dnase I (DNA-free kit; Ambion, Huntington, UK) to remove any contaminating genomic DNA. For each pool, 2 [micro]g total RNA was reverse transcribed in a 25-[micro]L reaction using SuperScript II (Invitrogen, Paisley, UK) and oligo-dT primer according to the manufacturer's instructions. Polymerase chain reaction (PCR; 25 [micro]L) containing 2 [micro]L first-strand eDNA (1:10 dilution), 12.5 [micro]L of SYBR Green PCR Master Mix (Applied Biosystems, Warrington, UK), and 0.3 [micro]M each of forward and reverse primers were run For 40 amplification cycles in an ABI PRISM 7700 Sequence Detection System (Applied Biosystems). Cycling conditions were 50[degrees]C for 2 min, 9[degrees]C for 10 rain, 95[degrees]C for 15 sec, and 60[degrees]C for 1 min. All reactions were run in triplicate.

Real-time (RT) PCR primers for FOS (5'-CTGTGGCCTCCCTGGATTTG-3 "and 5'-TGAGAAGGGGCAGGGTGAAG-3'), LTF (5'-CGGGGGCCTTCAGACCATC3' and 5'-CTAAAGTGACAGCAGGG AGTG-3'), and the control gene RPBI (5'-GTTCTGGACCCCATTTTT GATAGGC-3' and 5'-CAGGGGACTGGCAGGGTAACAA-3') were designed using Primer Express software (version 1.5; Applied Biosystems) to generate amplicons within their corresponding Affymetrix probe set target sequences.

Results

Histologic Changes and Increases in Uterine Weight

Our aim was to identify the genes and molecular networks associated with the uterotrophic response and to define the relationships between gene expression changes and histologic alterations. To this end, we gave immature female mice a single subcutaneous injection of [E.sub.2] (400 [micro]g/kg) or vehicle and used DNA microarrays to measure uterine gene expression profiles at seven different times (1, 2, 4, 8, 24, 48, and 72 hr) after exposure. To facilitate the phenotypic anchoring of expression changes, we also measured blotted uterine weights and determined the average heights of the luminal epithelium and stromal endometrium for each animal. Three independent replicate experiments were carried out to allow a rigorous statistical analysis of the gene expression data (see "Materials and Methods"). We chose to use a single dose of [E.sub.2] to avoid the complex transcriptional program that may result from the standard uterotrophic assay exposure regime in which test compound is dosed by repeated administration on 3 consecutive days (Odum et al. 1997). This dose induced a sustained increase in blotted uterine weight that was similar in the three replicate experiments (Figure 1A). in each replicate experiment, a significant increase (p < 0.01) in uterine weight was observed 4 hr after exposure to [E.sub.2] and reached maximal levels between 24 and 72 hr (Figure 1A).

Histologic analysis of uterine sections revealed the cellular changes associated with the increase in uterine weight between 1 and 72 hr (Figure 2A). Consistent with previous reports (Clark and Mani 1994), the weight increase that occurred within 4 hr of exposure (Figure 1A) was associated with thickening of the stromal endometrium (Figure 2B) resulting from the uptake of fluid. The larger increase in uterine weight that occurred between 8 and 24 hr was due to hypertrophy and cell proliferation (Kaye et al. 1971; Quarmby and Korach 1984), which caused an increase in thickness of the luminal epithelium between 8 and 24 hr (Figure 2C). We conclude that the single dose of [E.sub.2] used induced a conventional uterotrophic response. Furthermore, the expression profiles of two classical [E.sub.2]-responsive genes, lactotransferrin (LTF; Liu and Teng 1992) and the proto-oncogene C-FOS (Weisz and Bresciani 1988), demonstrate that [E.sub.2] elicited a robust transcriptional response that was similar in the three replicate experiments (Figure 1B).

[FIGURE 2 OMITTED]

Multistep Method for Analysis of Gene Expression Changes

Uterine RNA from the seven time points for each of the [E.sub.2]-treated and time-matched vehicle control groups was analyzed using Affymetrix MG-U74Av2 GeneChips. A total of 42 microarray data sets were collected for the three replicate experiments. We used a multistep method to analyze the microarray gene expression data (Figure 3A). First, data were filtered and subjected to statistical analyses to identify the 3,538 genes with altered expression in [E.sub.2]-treated mice (o < 0.01 and > 1.5-fold) during at least one time point (see "Materials and Methods"). Unsupervised hierarchical clustering was then used to group these genes into co-regulated clusters (Quackenbush 2002; Figure 3B), revealing a complex multistage transcriptional response to [E.sub.2] in the uterus (gene clusters A-I in Figure 3B). To gain an overview of the predominant molecular functions and biologic pathways that were regulated at the transcriptional level during the uterotrophic response to [E.sub.2], we interrogated the 3,538 [E.sub.2]-responsive genes using the GOStat gone ontology mining tool (http://gostat.wehi.edu.au) (Beissbarth and Speed 2004). This approach revealed that [E.sub.2] targets predominantly genes involved in protein metabolism, cell cycle, cell proliferation, DNA replication, RNA metabolism, mRNA transcription, and blood vessel development [Supplemental Data, Table 2 (http://ehp.niehs.nih.gov/txg/ members/2004/7345/supplemental.pdf)]. Next, we used a supervised clustering approach using customized gene ontology definitions (see "Materials and Methods") to identify gene functions that were predominant in each co-regulated cluster in Figure 3B. This revealed that [E.sub.2] regulates each class of gene during a narrow window of time and suggests that [E.sub.2] induces uterine growth and maturation by regulating successively the activities of different biologic pathways (described below). Finally, we analyzed the temporal associations between the gene expression program and alterations in uterine weight and histology to anchor the gene expression changes to alterations in uterine phenotype. These associations are described below.

[FIGURE 3 OMITTED]

Phase 1: Rapid Induction of Transcriptional Regulators and Signaling Components by [E.sub.2]

The first 4 hr of the uterotrophic response is characterized by the influx into the uterus of fluid that provides the nutrients and ions required for growth (Clark and Mani 1994). This leads to decompaction of stromal cells (Figure 4A) and thickening of the stromal endometrial layer at 4 hr (Figure 2B). This first phase of the uterotrophic response is accompanied by the rapid and transient regulation of genes encoding components of intra- and intercellular signaling pathways (Figure 4B) and sequence-specific transcriptional regulators (Figure 4C). Most of these genes show maximal expression between 1 and 4 hr, suggesting that the transcriptional effects of [E.sub.2], mediated via ER-[alpha] and ER-[beta], are amplified rapidly through the induction or modulation of multiple transcriptional and nontranscriptional signaling pathways.

[FIGURE 4 OMITTED]

Signaling Genes

The signaling genes rapidly up-regulated by [E.sub.2] function in a broad array of signal transduction pathways (Figure 4B). These genes include protein kinases (AKT, MEK1, PIM3), growth factors (VEGF, PLGF), GTPases (RHOC, RAB11A, DEXRAS1), cytokine signaling proteins (MCP1, SOCS1, SOCS3, WSB1, IL17R), and a Wnt signaling factor (WNT4). Several [E.sub.2]-induced genes may act to attenuate initial signaling events (e.g., the protein phosphatase MKP1 negatively modulates MAP kinase activity). Strikingly, many of the signaling genes induced within 4 hr of [E.sub.2] exposure have roles in the regulation of vascular permeability in other tissues, suggesting that they may be involved directly in initiating the influx of fluid into the uterus at this time (Figure 4B). These genes include angiogenic/vascular cell growth factors (VEGF, PLGF, ADM, ANGPT2, TGFB2), vasoactive serine proteases (KLK2, KLK6, KLK9, KLK22), and vascular endothelial receptors (IL17R, BDKRB1, ENG, GNA13). Furthermore, the vascular growth factor receptors TIE1 and TIE2 are rapidly down-regulated in response to [E.sub.2] (Figure 4B), which may serve to attenuate the uptake of fluid after 4 hr. Collectively, these genes shed light on the mechanism by which [E.sub.2] promotes fluid uptake in the uterus and provide a clear link between gene expression changes and histologic changes occurring at this time.

[FIGURE 4 OMITTED]

Transcriptional Regulators

The sequence-specific transcription factors induced during the first 4 hr of the response can be divided into four main classes (Figure 4C). The first contains members of the Jun, Fos, and ATF subgroups of transcription factors (C-FOS, FOSB, C-JUN, JUNB, ATF3, ATF4, ATF5) that form AP-1 dimers implicated in the regulation of cell proliferation and survival (Shaulian and Karin 2001). The second class contains genes that control cell differentiation during the development of a number of tissues (SOX11, SOX18, HEY1, CART1, PRX2, SMAD7, ID1). The early induction of members of this class suggests that [E.sub.2] deploys a diverse range of gene expression networks to control cell growth and differentiation in the uterus. The third class contains two genes that encode coregulators for nuclear receptors (RIP140, NCOP2), suggesting that these may act to modulate ER-mediated responses to [E.sub.2] in the uterus. The fourth class of genes encodes presumed transcriptional regulators of unknown function (e.g., GIF).

We conclude that the initial response to [E.sub.2] serves to a) modulate the activities of intra- and intercellular signaling pathways that, among other functions, promote vascular permeability and fluid uptake and b) up-regulate the expression levels of transcription factors that promote growth and differentiation. These early gene expression changes facilitate the amplification of the originating hormonal signal and set into motion the series of events that result in uterine growth and differentiation.

Phase 2: Coordinated Induction of Genes Required for mRNA and Protein Synthesis

No increase in uterine weight or obvious changes in uterine histology occur between 4 and 8 hr (Figures 1 and 2). Nevertheless, our data reveal that this phase is associated with the induction of a large cluster of genes (Figure 5). Most are induced 2 hr after [E.sub.2] administration, reach maximal expression at 4 or 8 hr, and return to control or subcontrol levels by 48 hr (Figure 5B). Most of these genes play roles in mRNA and protein synthesis, demonstrating that the bulk of transcriptional activity occurring at this time functions to increase the capacity of the uterus for new protein synthesis. This is consistent with earlier observations that exposure to [E.sub.2] results in a rapid increase in the mRNA and protein content of the uterus (Clark and Mani 1994). Our data define the molecular basis for these prior observations and identify the genes targeted by ERs to induce these effects.

In a broad sense, protein synthesis includes the interlinked processes of transcription, mRNA processing, mRNA export into the cytoplasm, protein translation, and protein folding (Orphanides and Reinberg 2002, and references therein; Figure 5G). Our data reveal the coordinated induction of genes involved in each of these processes (Figure 5A-F). These genes include a) components of the RNAP II general transcription machinery (RPB8, RPB10, TAF10; Figure 5A); b) transcription termination and polyadenylation factors (NSAP1; Figure 5A); c) mRNA splicing factors (SFPQ, U2AF1, RNPS1; Figure 5A); d) mRNA export proteins (NXF1; Figure 5C); e) protein translation factors (EIF1A, EIF2A, EIF2B, EIF3; ribosomal proteins RPL11, RPL12, RPL20, RPL52, RPS18b, and tRNA synthetases VALRS, GLURS, PHERS; Figure 5D), and f) protein folding factors (FKBP4, CCT3, CCT6a, CCT7, CCT8; Figure 5E). The down-regulation of several genes associated with transcriptional repression (HDA1, TGIF, MAD4, EZH1) and mRNA degradation (AUH; Figure 5B) may also contribute to the general elevation of mRNA synthesis. We also note a concurrent increase in the expression of components of the ubiquitin-proteasome proteolytic pathway (PAD1, SUG1; Figure 5F) and genes whose products are required for the nuclear import and export of proteins (IMPORTIN [alpha] 2, IMPORTIN [alpha] 3, RAE1, G3BP2; Figure 5C), indicating that [E.sub.2] additionally elevates proteasome levels and nuclear-cytoplasmic protein transport activity at this time. We conclude that [E.sub.2] is able to increase protein synthesis activity in the uterus by altering the expression of genes involved in all aspects of the protein biosynthesis pathway.

Therefore, during the first two phases of the transcriptional program, [E.sub.2] induces the expression of a battery of sequence-specific transcriptional regulators (phase 1; Figure 4C) and then induces the expression of genes in the protein synthesis pathway (phase 2; Figure 5). It appears, therefore, that, during phase 1, [E.sub.2] specifies the gene expression networks that will be active, and then ensures during phase 2 that these networks have sufficient mRNA and protein synthesis capacity to operate. In addition the increased expression of components of the RNA and protein synthesis machinery is likely to be a prerequisite for proliferation in the uterus because cells must increase their mass before division to provide sufficient cellular components required for survival of the daughter cells (Norbury and Nurse 1992). Consistent with this, we note that induction of protein synthesis components immediately precedes the up-regulation of genes required for proliferation (Figure 6; see below). An additional function of the increased uterine capacity for protein synthesis may be to facilitate the production of the abundant cytoarchitectural and secreted proteins induced at the end of the uterotrophic response (see below).

Phase 3: Coordinated Regulation of Genes Controlling Chromosome Replication and the Cell Cycle

The next phase in the urerotrophic response occurs between 8 and 24 hr and involves an approximate doubling in uterine weight (Figure 1A) and a large increase in the thickness of the luminal epithelium (Figures 2C, 6A). A quantitative histologic analysis of mitotic figures in the uterine cells ("Materials and Methods") revealed a clear and statistically significant (p < 0.01) increase with [E.sub.2] at 24 hr, whereas no [E.sub.2]-dependent increase was observed at 8, 48, or 72 hr (Table 1, Figure 6A). These observations are consistent with previous studies showing that most cells in the immature rodent uterus are stimulated to leave their quiescent state and divide synchronously under the influence of [E.sub.2] (Kaye et al. 1971; Quarmby and Korach 1984).

We found that genes required for the replication of chromosomal DNA (PCNA, FEN1, CDC6, MCM2, MCM3, MCM4, MCM5, ORC1, ORC6, RRM1, RRM2) and genes required for postreplicative phases of the cell division cycle (e.g., CCNB1, PLK1) are coordinately induced and reach maximal expression levels between 8 and 24 hr (Figure 6B), consistent with the timing of the histologic changes observed in Figure 6A. Genes required for maintaining genome integrity (CHK1, CKS1, GEMININ) and the epigenetic status of newly replicated DNA (CAF-1 p60, AHCY) are also up-regulated at 8 and/or 24 hr (Figure 6B). It is striking that after their induction during the proliferative phase (8-24 hr), the expression levels of most genes that regulate chromosome replication and cell division are reduced to levels well below those of control animals (Figure 6B). This suggests that mechanisms exist for the active repression of these genes to prevent further rounds of proliferation.

Declining [E.sub.2] levels in mice 48 hr after a single subcutaneous injection may also contribute to the cessation of proliferation. Together, these data provide a molecular explanation for the changes in uterine weight and histology that occur between 8 and 24 hr (Figures 1A, 2, and 6A) and support the assertion that tire early increase in weight seen at 4 hr is due to fluid uptake. Furthermore, these gene expression changes demonstrate that cell proliferation is restricted to a narrow window of time between 8 and 24 hr by the coordinated regulation of chromosome replication and cell division genes.

Regulation of Cell Division

Our data also provide insight into the mechanisms by which [E.sub.2] releases cells of the immature uterus from quiescence and promotes cell division. The [E.sub.2]-induced expression profile of E2F1, a key transcriptional regulator of DNA replication genes (Ohtani 1999), closely parallels the induction of the chromosome replication genes (Figure 6B), consistent with the proposal that E2F1 regulates the expression of components of the DNA replication fork in human breast cancer cell lines exposed to [E.sub.2] (Lobenhofer et al. 2002). Our data indicate that release from quiescence also involves the [E.sub.2]-induced down-regulation of genes that maintain cells in a growth-arrested state (KIP1, CCNG2, CCNG1). The principle way in which mitogens induce proliferation of quiescent cells involves a reduction in levels of the Kip1 protein, which inhibits the activities of cyclin-cdk complexes and induces cell cycle arrest (Olashaw and Pledger 2002). We found that KIP1 was down-regulated within 1 hr of [E.sub.2] exposure and remains repressed over a period of at least 24 hr, only reaching control levels when cell proliferation has ceased (Figure 6C). Furthermore, [E.sub.2] may promote degradation of the Kip1 protein via the induction of CDC34 (Figure 6C), a gene that has been implicated in the ubiquitin-mediated degradation of Kip1 (Koepp et al. 1999).

These data suggest that [E.sub.2] promotes cell proliferation by coordinately reducing Kip1 mRNA and protein levels. It is not clear whether KIP1 is a direct or indirect target of the activated ERs. However, KIP1 gene expression is controlled by ras-mediated PI3K signaling pathways (Olashaw and Pledger 2002), components of which are up-regulated rapidly in response to [E.sub.2] (e.g., DEXRAS1, RASSF1; Figure 4B).

Suppression of Apoptosis

[E.sub.2] protects against apoptosis in a number of tissues, including brain, testes, and uterus (Thompson 1994). Although the anti-apoptotic activity of estrogen in the uterus is thought to play a crucial role in the maintenance of uterine homeostasis, the mechanistic basis for this action has not been defined. Our data reveal that [E.sub.2] induces the expression of anti-apoptotic genes (BAG2, BAG3, DAD1) while simultaneously down-regulating the expression of pro-apoptotic genes (CASP2, NIX; Figure 6D). Thus, apoptosis appears to be suppressed through transcriptional mechanisms during [E.sub.2]-induced uterine growth. Consistent with these observations, [E.sub.2] also induces the apoptotic regulators BCL2 and BAG1 in cultured breast cancer cells (Perillo et al. 2000; Soulez and Parker 2001). It will be important to determine whether estrogens elicit similar changes in the expression of apoptosis-regulating genes in other tissues.

Phase 4: Induction of Genes Involved in Uterine Cell Differentiation and Defense Responses

The period from 24 to 72 hr after [E.sub.2] exposure is associated with remodeling of the luminal epithelial cell layer, including the formation of secretory epithelial cells and a glycocalyx layer consisting of glycoproteins (Paria et al. 2003; Weitlauf 1994). These changes result in the formation of a highly differentiated epithelial layer that is primed for cell recognition and adhesion events necessary for embryo attachment and implantation.

Changes in Cytoarchitecture

The final phase of the uterotrophic response coincides with the induction of a battery of genes involved in the cytoarchitectural remodeling of proliferating uterine cells, thus providing a further link between phenotypic and gene expression changes (Figure 7A). These genes encode components of desmosomes (DSG2), gap junctions (CX26), tight junctions (CLDN4, CLDN7), the cornified envelope (SPRRIA, 2A, 2B, 2E, 2F, 2G, 2I, 2J), intermediate filaments (KRT19), and a variety of cell-surface and extracellular-matrix glycoproteins (SPP1, BGP1, BGP2, MUC1, TROP2, CLU). The latter class of genes is likely to contribute to the formation of the glycocalyx layer present on differentiated uterine epithelium (Weitlauf 1994). The concomitant [E.sub.2]-dependent induction of a number of enzymes required for carbohydrate metabolism (MAN2B1, GALNT3) may provide the increase in sugar metabolism necessary for the production of these glycoprotcins. [E.sub.2] also induces genes encoding ion channels that regulate the balance of [Na.sup.+] absorption and [Cl.sup.-] secretion across the endometrial epithelium to maintain a luminal fluid microenvironment suitable for implantation (CFTR, CLCA3, MAT8; Figure 7A).

Defense Responses

A number of genes involved in host defense processes or detoxification are first regulated between 24 and 72 hr (Figure 7t3). We speculate that the products of these genes may provide an environment that is protective of, and facilitates, embryo implantation and development. These include genes encoding lysosomal enzymes (LYZP, LYZM, CTSH CTSL, CTSS, LGMN), genes involved in detoxification and clearance of xenobiotics (GSTO1, GSTT2, UGT1AI), and genes involved in immune and inflammatory responses (CD14, MX1, PIGR). The up-regulation of genes encoding chemoattractant cytokines (Figure 7C) for infiltrating eosinophils (EOTAXIN) and monocytes (MCP1/3) is consistent with previous observations of immune cell infiltration into the uterus (Gouon-Evans and Pollard 2001, and references therein). Another [E.sub.2]-regulated defense response may be provided by the induction of LTF (Liu and Teng 1992), an iron-binding protein with bacteriostatic activity (Singh et al. 2002). Our data reveal the induction of two additional iron metabolism genes at this time (CP, LCN2; Figure 7E; Kaplan 2002), suggesting a role for iron homeostasis in the uterotrophic response to [E.sub.2].

Several components of the complement system are also induced 48-72 hr after exposure to [E.sub.2]. These include C1QA, C1QB, C1QC, C2, C3, C4, CFH, and CFI (Figure 7D). Although many complement components have been identified in female reproductive epithelium, only C3 has previously been established as an [E.sub.2]-responsive gene (Sundstrom et al. 1989). In addition to participating in immune and inflammatory responses and host resistance, there is increasing evidence that complement functions in tissue remodeling and organ regeneration (Mastellos and Lambris 2002). Intriguingly, complement also influences mammalian reproduction and particularly the integrity of maternofetal interfaces during pregnancy (Caucheteux et al. 2003; Mastellos and Lambris 2002). Therefore, it is possible that the complement system may play a noninflammatory role in the uterotrophic response.

Evidence for a Transcriptional Cascade in the Uterus

It is striking that many different induction profiles can be seen in the genes regulated by [E.sub.2]: some genes are induced within 1 hr of exposure, whereas others are not induced until 48 hr (Figure 3B). The induction of a large number of sequence-specific transcription factors during the first phase of the response suggests that a transcriptional cascade may operate in the uterus, with the products of genes induced at the beginning of the program regulating the transcription of those toward the end. The regulation of the SPRR genes provides evidence for the existence of such a cascade (Figure 8). The mouse SPRR genes are located in a tandem array at the same chromosomal locus, and their transcription is regulated by the AP-1 and Ets transcription factors (Patel et al. 2003; Figure 8A). Eight members of the SPRR gene family are induced between 4 and 72 hr, with maximal induction occurring between 24 and 48 hr (Figure 8B). Intriguingly, the mRNAs encoding Ets2 and components of AP-1 (c-Jun, JunB, c-Fos, FosB, and Atf3, Atf4, Atf5) are maximally induced during the first phase of the uterotrophic response, between 1 and 4 hr (Figure 8B). We speculate, therefore, that a transcriptional cascade operates, in which ER-[alpha] or ER-[beta] induces the expression of Ets2 and AP-1 components, which in turn regulate the transcription of the SPRR genes (Figure 8C). Alternatively, it is possible that ER-[alpha] or ER-[beta] cooperates with Ets2 and AP-1 to regulate the expression of the SPRR genes. In this way, transcription of the SPRR genes would not begin until sufficient levels of Ets2 and AP-1 were present. Consistent with this model, feed-forward loops (in which a transcriptional regulator controls a second transcription factor that then functions in concert with the initial regulator on a common downstream target gene) are emerging as common mechanisms in eukaryotes for transcriptional networks (Lee et al. 2002). It is likely that analysis of the regulatory regions of other [E.sub.2]-responsive genes during the uterotrophic response will suggest the existence of additional transcriptional networks.

Discussion

Our data describe at an unprecedented level of detail the molecular events that initiate and drive uterine physiologic changes upon exposure to the sex steroid hormone [E.sub.2] in the immature mouse uterus. Gene expression profiling reveals that [E.sub.2] induces a multistage and tightly coordinated transcriptional program that regulates successive and functionally interlinked cellular processes during the uterotrophic response (Figure 9). The temporal patterns of gene expression we have identified for [E.sub.2] are consistent with, and extend, those reported recently for the uterotrophic response of immature, ovariectomized mice after exposure to 17[alpha]-ethynylestradiol (Fertuck et al. 2003), in which concordant temporal responses were seen for genes involved in several functional categories in Figure 9. These include RNA and protein metabolism, cell cycle regulation, immune responses, and complement components. Furthermore, many of the genes regulated by exogenous [E.sub.2] in our study are also differentially regulated in response to endogenous hormones (Tan et al. 2003).

Comparison of gene expression changes with alterations in uterine weight and histologic alterations, and analysis of gene expression data according to gene function allowed us to implicate specific groups of genes in driving water imbibition in the stromal endothelium, synchronous cell proliferation, and cytoarchitectural changes associated with luminal epithelial cell differentiation. These data thus provide a detailed mechanistic view of the relationships between the uterotrophic response and the underlying transcriptional program. Furthermore, this work demonstrates that comparison of temporal changes in gene expression and conventional toxicology parameters (uterine weight and histologic changes) can provide an understanding of the relationships between gene expression patterns and phenotypic change.

[E.sub.2] can regulate transcription through a combination of at least two distinct signaling pathways: a) via activation of the nuclear transcription factors ER-[alpha] and ER-[beta] (Hall et al. 2001; McKenna and O'Malley 2002; Moggs and Orphanides 2001; Tremblay and Giguere 2002) and b) via extranuclear or "nongenomic" signaling events (Falkenstein et al. 2000; Hammes 2003; Moggs et al. 2003). The transcriptional responses to [E.sub.2] that we have defined here are likely to involve a combination of direct gene regulation by nuclear ERs and indirect gene regulation via extranuclear signaling pathways. Although the uterus of the immature mouse expresses both ER subtypes ([alpha] and [beta]) at comparable levels (Weihua et al. 2000), recent transcript profiling studies using ovariectomized ER-knockout mice revealed a predominant role for ER-[alpha] in the regulation of estrogen-responsive genes in the uterus (Hewitt et al. 2003; Watanabe et al. 2003) consistent with the observation that only a partial uterotrophic response occurs in ER-[alpha] knockout mice (Lubahn et al. 1993). Therefore, it is likely that most [E.sub.2]-responsive genes we have identified are regulated by ER-[alpha]. However, identification of the direct gene targets for each ER subtype will ultimately require the development of methods for measuring the occupancy of receptor subtypes at promoters in vivo. Nevertheless, our temporal analysis of [E.sub.2]-responsive genes provides novel insights into the transcriptional cascades that are initiated through [E.sub.2]-responsive transcription factors.

The molecular events described here for the reference natural estrogen [E.sub.2] provide the basis for understanding how other estrogenic chemicals, including synthetic estrogens and phytoestrogens, induce their effects (Moggs et al. 2004). Increasing attention is being paid to the use of gene expression changes in the uterus for the identification of surrogate markers for short-term rodent estrogenicity assays (Naciff et al. 2002, 2003; Owens and Ashby 2002; Watanabe et al. 2002), and our data reveal a large number of novel candidate marker genes. The insights provided by these data, into how an ER ligand coordinates transcriptional regulatory networks that result in proliferation and differentiation in a complex organ, provide a paradigm for understanding the modes of action of other nuclear receptors.

Appendix. Gene nomenclature and Affymetrix probe sets for
Figures 4-8. (a)

              Affymetrix
Gene symbol    Probe Set                 Gene description

Figure 4B--Signaling components

IL17R         99992_at      interleukin 17 receptor
RAP1          160822_at     Rap1, GTPase-activating protein 1
DEXRAS1       99032_at      RAS, dexamethasone-induced 1
MKP1          104598_at     dual specificity phosphatase 1
WNT4          103238_at     wingless-related MMTV integration site 4
IGFBP10       92777_at      cysteine rich protein 61
PIP92         99109_at      immediate early response 2
PIM3          96841_at      similar to serine/threonine-protein kinase
                              pim-3
ARHU          96747_at      ras homolog gene family, member U
CISH3         162206_f_at   cytokine inducible SH2-containing
                              protein 3
NAB2          100962_at     Ngfi-A binding protein 2
SOCS3         92232_at      cytokine inducible SH2-containing protein 3
EPLG2         98407_at      ligand for receptor tyrosine kinase ELK
IL17R         99991_at      interleukin 17 receptor
CDKN1A        98067_at      cyclin-dependent kinase inhibitor 1A(P21)
CDKN1A        94881_at      cyclin-dependent kinase inhibitor 1A (P21)
WSBI          98946_at      WD-40-repeat-containing protein with a SOCS
                              box
VEGF          103520_at     vascular endothelial growth factor A
GADD45        102292_at     growth arrest and DNA-damage-inducible 45
SYT           99610_at      synovial sarcoma translocation,
                              chromosome 18
SOCS1         92832_at      cytokine inducible SH2-containing protein 1
GADD45g       101979_at     growth arrest and DNA-damage-inducible 45
                              gamma
GLY96         94384_at      immediate early response 3
MAPKAP2       160353_i_at   MAP kinase-activated protein kinase 2
KLK22         101289_f_at   epidermal growth factor binding protein
                              type 1
TROB          99532_at      tob family
RGS3          160747_at     regulator of G-protein signaling 3
GNA13         100514_at     guanine nucleotide binding protein,
                              alpha 13
RAB11A        96238_at      RAB11a, member RAS oncogene family
PLGF          92909_at      placental growth factor
BDKRB1        101748_at     bradykinin B1 subtype receptor
CF3           97689_at      coagulation factor III
PDK4          102049_at     pyruvate dehydrogenase kinase, isoenzyme 4
HERPUD1       95057_at      homocysteine-inducible, endoplasmic
                              reticulum stress-inducible,
                              ubiquitin-like domain member 1
MYD116        160463_at     myeloid differentiation primary response
                              gene 116
NORE1         102028_at     Ras association (RaIGDS/AF-6) domain
                              family 5
NET1A         94223_at      neuroepithelial cell transforming gene 1
GEM           92534_at      GTP binding protein (gene overexpressed in
                            skeletal muscle)
SNRK          97429_at      SNF related kinase
ALASH         93500_at      aminolevulinic acid synthase 1
NTTP1         161171_at     dual specificity phosphatase 8
MAPKAP2       95721_at      MAP kinase-activated protein kinase 2
MEK1          92585_at      mitogen activated protein kinase kinase 1
RGSr          94378_at      regulator of G-protein signaling 16
RASSF1        102379_at     Ras association (RaIGDS/AF-6) domain
                              family 1
NGEF          93178_at      neuronal guanine nucleotide exchange factor
C-KIT         99956_at      kit oncogene
NOTCH1        97497_at      Notch gene homolog 1
BTG3          96146 _t      B-cell translocation gene 3
PC4           160092_at     interferon-related developmental
                              regulator 1
SGK           97890_at      serum/glucocorticoid regulated kinase
ADM           102798_at     adrenomedullin
ANGPT2        92210_at      angiopoietin 2
UBQLN1        95601_at      ubiquilin 1
THBS1         160469_at     thrombospondin
ROCK2         98504_at      rho-associated coiled-coil forming kinase 2
SNK           92310_at      serum-inducible kinase
MAP2K3        93315_at      mitogen activated protein kinase kinase 3
ENG           100134_at     endoglin
PTDSR         95486_at      phosphatidylserine receptor
SWIP2         160296_at     WD-40-repeat-containing protein with a SOCS
                              box
AKT           100970_at     thymoma viral proto-oncogene 1
RHOC          96056_at      ras homolog gene family, member C
TGFB2         93300_at      transforming growth factor, beta 2
EPCR          98018_at      protein C receptor, endothelial
KLK6          100061_f_at   kallikrein 6
GALN          100407_at     galanin
NEDD4B        103907_at     neural precursor cell expressed,
                              developmentally down-regulated gene
                              4-like
KLK22         95775_f_at    kallikrein 22
KLK9          94716_f_at    kallikrein 9
MCP1          102736_at     platelet-derived growth factor-inducible
                              protein JE
TIE1          99936_at      tyrosine kinase receptor 1
RAMP1         104680_at     receptor (calcitonin) activity modifying
                              protein 1
PGF           97769_at      prostaglandin F receptor
PDGF          95079_at      platelet derived growth factor
[alpha]RA                     receptor, alpha polypeptide
OB-RGRP       93600_at      leptin receptor
ERK1          101834_at     mitogen activated protein kinase 3
GRB7          103095_at     growth factor receptor bound protein 7
ADCY6         102321_at     adenylate cyclase 6
TIE1          161184_f_at   tyrosine kinase receptor 1
GNAI1         104412_at     guanine nucleotide binding protein, alpha
                              inhibiting 1
ADCY7         103392_at     adenylate cyclase 7
TIE2          102720_at     endothelial-specific receptor tyrosine
                              kinase
GPCR26        100435_at     endothelial differentiation,
                              lysophosphatidic acid G-protein-coupled
                              receptor, 2
Figure 4C--Transcription factors

GIF           99603_g_at    TGFB inducible early growth response
GIF           99602_at      TGFB inducible early growth response
ETS2          94246_at      E26 avian leukemia oncogene 2, 3' domain
ID1           100050_at     inhibitor of DNA binding 1
SMAD7         92216_at      MAD homolog 7
C-JUN         100130_at     Jun oncogene
BRF2          160273_at     zinc finger protein 36, C3H type-like 2
IRF8          98002_at      interferon concensus sequence binding
                              protein
AGP/EBP       92925_at      CCAAT/enhancer binding protein (C/EBP),
                              beta
C-FOS         160901_at     c-fos oncogene
KROX24        98579_at      zinc finger protein Krox-24
FOSB          103990_at     FBJ osteosarcoma oncogene B
NR4A1         102371_at     N10 nuclear hormonal binding receptor
SOX18         161025_f_at   SRY-box containing gene 18
SOX18         104408_s_at   SRY-box containing gene 18
KROX20        102661_at     Early growth response 2
ESG           104623_at     transducin-like enhancer of split 3,
                              homolog of Drosophila E(spl)
FOG           97974_at      zinc finger protein, multitype 1
NCOR2         95129_at      nuclear receptor co-repressor 2Gene symbol
SOX11         101631_at     SRY-box containing gene 11
C/EBP         94466_f_at    CCAAT/enhancer binding protein alpha
                              (C/EBP), related sequence 1
PRX2          103327_at     paired related homeobox 2
ATF4          100599_at     activating transcription factor 4
STAT5B        100422_i_at   signal transducer and activation of
                              transcription 5A
HEY1          95671_at      hairy/enhancer-of-split related with YRPW
                              motif 1
ATF5          103006_at     activating transcription factor 5
C/EBP         98447_at      CCAAT/enhancer binding protein
RIP140        103288_at     nuclear receptor interacting protein 1
CRTR1         103761_at     Tcfcp2-related transcriptional repressor 1
MEF2A         93852_at      myocyte enhancer factor 2A
TIS11         92830_s_at    zinc finger protein 36
STAT5B        100423_f_at   signal transducer and activation of
                              transcription 5A
ATF3          104155_f_at   activating transcription factor 3
CART1         100005_at     TNF receptor associated factor 4
JUNB          102362_i_at   transcription factor junB

Figure 5A--RNA synthesis

SFPQ          99621_s_at    splicing factor proline/glutamate rich
                            (polypyrimidine tract binding protein
                            associated)
U2AF1         97486_at      U2 small nuclear ribonucleoprotein
                              auxiliary factor (U2AF), 35 kDa
RBMXP1        160192_at     RNA binding motif protein, X chromosome
                              retrogene
DDX21         94361_at      DEAD/H (Asp-Glu-Ala-Asp/His) box
                              polypeptide 21 (RNA helicase II/Gu)
DDX3          101542_f_at   DEAD (aspartate-glutamate-alanine-
                              aspartate) box polypeptide 3
NSAP1         94985_at      NS1-associated protein 1
MKI67 bp      93342_at      Mki67 (FHA domain) interacting nucleolar
                              phosphoprotein
ELAVL1        94001_at      ELAV (embryonic lethal, abnormal vision,
                              Drosophila)-like 1 (Hu antigen R)
PSP1          103393_at     paraspeckle protein 1
SRP20         101003_at     splicing factor, arginine/serine-rich 3
                              (SRp20)
JKTBP         96084_at      heterogeneous nuclear ribonucleoprotein
                              D-like
RPA2          92225_f_at    RNA polymerase 1-2 (128 kDa subunit)
RALY          98511_at      hnRNP-associated with lethal yellow
SFRS10        95791_s_t     splicing factor, arginine/serine-rich 10
FBL           160503_at     fibrillarin
SNRPA1        101506_at     small nuclear ribonucleoprotein
                              polypeptide A'
TASR          98048_at      neural-salient serine/arginine-rich
RPB10         93551_at      RNA polymerase II subunit 10
AUF1          94303_at      heterogeneous nuclear ribonucleoprotein D
HRMT1L2       96696_at      heterogeneous nuclear ribonucleoproteins
                            methyltransferase-like 2
CGI-110       95714_at      pre-mRNA branch site protein p14
SMN           103620_s_at   survival motor neuron
RPB8          97254_at      RNA binding motif protein
RNPSI         93518_at      ribonucleic acid binding protein S1
NCL           160521_at     nucleolin
RPA1          93620_at      RNA polymerase 1-4 (194 kDa subunit)
HNRPA2B1      93118_at      heterogeneous nuclear ribonucleoprotein
                              A2/B1
SNRPD1        100577_at     small nuclear ribonucleoprotein D1
H/ALAsnRNP    97824_at      nucleolar protein family A, member 2
TAF10         103910_at     TAFII30
DDX24         99096_at      DEAD/H (Asp-Glu-Ala-Asp/His) box
                              polypeptide 13 (RNA helicase A)
Figure 5B
MAD4          99024_at      Max dimerization protein 4
EZH1          100486_at     enhancer of zeste homolog 1 (Drosophila)
HDA1          104376_at     histone deacetylase 5
AUH           96650_at      AU RNA binding protein/enoyl-coenzyme A
                              hydratase
TGIF          101502_at     TG interacting factor

Figure 5C--Nuclear import/export

POM121        96174_at      nuclear pore membrane protein 121
NXF1          101079_at     nuclear RNA export factor 1 homolog (S.
                              cerevisiae)
IMPORTINa3    96010_at      karyopherin (importin) alpha 3
RAE1          160466_at     RNA export 1 homolog (S. pombe)
IMPORTINa2    92790_at      karyopherin (importin) alpha 2
G38P2         94913_at      Ras-GTPase-activating protein (GAP120)
                            SH3-domain binding protein 2
Figure 5D--Protein translation

elF3S7        99101_at      eukaryotic translation initiation factor 3,
                              subunit 7 (zeta, 66/67kDa)
elF2B         160365_at     eukaryotic translation initiation factor 2,
                              subunit 2 (beta, 38kDa)
elF3S4        96883_at      eukaryotic translation initiation factor 3,
                              subunit 4 (delta, 44kDa)
EBNA1-bp2     96297_at      EBNA1 binding protein 2
GLNRS         96628_at      glutamyl-prolyl-tRNA synthetase
NAT1          100535_at     eukaryotic translation initiation factor 4,
                              gamma 2
elF3S9        93973_at      eukaryotic translation initiation factor 3,
                              subunit 9
RPS18b        95159_at      ribosomal protein S18b
VALRS         97894_at      valyl-tRNA synthetase 2
RPL12         160431_at     mitochondrial ribosomal protein L12
eIF1A         93058_at      eukaryotic translation initiation factor 1A
eRF1          160451_at     translation releasing factor eRFI
eIF1A         103708_at     eukaryotic translation initiation factor 1A
eIF6          94826_at      integrin beta 4 binding protein
eRF1          98608_at      translation releasing factor eRFI
RPL20         94875_at      mitochondrial ribosomal protein L20
PHERS         94494_at      phenylalanine-tRNA synthetase-like
ASNS          95133_at      asparagine synthetase
eIF3S10       94250_at      eukaryotic translation initiation factor 3
NOP56         95109_at      nucleolar protein 5A
eIF2AS1       94253_at      eukaryotic translation initiation factor 2A
RRS1          96778_at      regulator for ribosome resistance homolog
                            (S. cerevisiae)
eRF1          96755_at      translation releasing factor eRFI
eRF1          96754_s_at    translation releasing factor eRFI
SUI1          92855_at      suppressor of initiator codon mutations,
                            related sequence 1 (S. cerevisiae)
RPL11         98876_at      mitochondrial ribosomal protein L11
RPL52         97443_at      mitochondrial ribosomal protein L52

Figure 5E--Protein folding

CCT3          98153_at      chaperonin subunit 3 (gamma)
FKBP4         92808_f_at    FK506 binding protein 4 (59 kDa)
CCT7          160562_at     chaperonin subunit 7 (eta)
PPID          97445_at      peptidylprolyl isomerase D (cyclophilin D)
CCT10         92829_at      heat shock 10 kDa protein 1 (chaperonin 10)
CCT8          160102_at     chaperonin subunit 8 (theta)
CCT6A         162279_f_at   chaperonin subunit 6a (zeta)
CCT3          161238_f_at   chaperonin subunit 3 (gamma)

Figure 5F--Protein degradation

PAD1          97274_at      26S proteasome-associated pad1 homolog
PSMB5         101558_s_at   proteasome (prosome, macropain) subunit,
                              beta type 5
PSMD4         94302_at      proteasome (prosome, macropain) 26S
                              subunit, non-ATPase, 4
PSMB3         94025_at      proteasome (prosome, macropain)
                            subunit, beta type 3
SUG1          160534_at     protease (prosome, macropain) 26S subunit,
                              ATPase 5
PSMB6         101992_at     proteasome (prosome, macropain) subunit,
                              beta type 6
PSMB2         94219_at      proteasome (prosome, macropain) subunit,
                              beta type 2
Figure 6B--DNA replication and cell division

SAKB          98996_at      serine/threonine kinase 18
RRM2          102001_at     ribonucleotide reductase M2
CAF1 p60      100890_at     chromatin assembly factor, p60 subunit
ORC6          95712_at      origin recognition complex, subunit 6-like
                              (S. cerevisiae)
PCNA          101065_at     proliferating cell nuclear antigen
MCM2          93112_at      mini chromosome maintenance deficient 2
CDC6          103821_at     cell division cycle 6 homolog (S.
                              cerevisiae)
MCM4          93041_at      mini chromosome maintenance deficient 4
                              homolog
MCM3          160496_s_at   mini chromosome maintenance deficient (S.
                              cerevisiae)
MCM3          100062_at     mini chromosome maintenance deficient (S.
                              cerevisiae)
TOPB1         103071_at     topoisomerase (DNA) II binding protein
CHK1          103064_at     checkpoint kinase 1 homolog (S. pombe)
MCM5          100156_at     mini chromosome maintenance deficient 5
CKSI          97468_at      CDC28 protein kinase 1
ORC1          92458_at      origin recognition complex, subunit 1-like
                              (S. cerevisiae)
RRM1          100612_at     ribonucleotide reductase M1
FEN1          97327_at      flap structure specific endonuclease 1
GEMININ       160069_at     geminin
E2F1          102963_at     E2F transcription factor 1
PLK1          93099_f_at    polo-like kinase homolog (Drosophila)
CCNB1         160159_at     cyclin B1, related sequence 1

Figure 6C--Cell-cycle regulators

CCND1         94232_at      cyclin D1
CDC34         94048_at      cell division cycle 34 homolog
KIP2          95471_at      cyclin-dependent kinase inhibitor 1C (P57)
CCNG2         98478_at      cyclin G2
KIP1          161010_r_at   cyclin-dependent kinase inhibitor (p27)
CCNI          94819_f_at    cyclin I

Figure 6D--Apoptosis

CASP2         99049_at      caspase 2
NIX           96255_at      BCL2/adenovirus E1B 19 kDa-interacting
                              protein 3-like
APR3          160271_at     apoptosis related protein APR3
TNFSF12       93917_at      tumor necrosis factor (ligand) superfamily,
                              member 12
PDCD4         103029_at     programmed cell death 4
MIAP2         102734_at     baculoviral IAP repeat-containing 3
MTD           98031_at      Bcl-2-related ovarian killer protein
SDNSF         97451_at      neural stem cell derived neuronal survival
                              protein
DAD1          96008_at      defender against Apoptotic Death 1
AAC11         101035_at     apoptosis inhibitor 5
BAG3          96157_at      Bcl2-associated athanogene 3
BAG2          161129_r_at   similar to BAG-family molecular chaperone
                              regulator-2
Figure 7A--Cytoarchitecture

MDEG2         99910_at      amiloride-sensitive cation channel 1,
                              neuronal (degenerin)
MAT8          103059_at     FXYD domain-containing ion transport
                              regulator 3
CLCA3         162287_r_at   chloride channel calcium activated 3
CD133         93389_at      prominin
CD133         93390_g_at    prominin
PIGF          104725_at     ras-like protein
DSG2          104480_at     desmoglein 2
MAN2B1        99562_at      mannosidase 2, alpha B1
CLDN4         101410_at     claudin 4
CLDN7         99561_f_at    claudin 7
SPRR2E        100723_f_at   small proline-rich protein 2E
SPRR2J        101755_f_at   small proline-rich protein 2J
SPRR2A        101025_f_at   small proline-rich protein 2A
TROP2         103648_at     tumor-associated calcium signal
                              transducer 2
SPRR21        95794_f_at    small proline-rich protein 21
SPRR2C        101761_f_at   small proline-rich protein 2C
SPRR2A        101024_i_at   small proline-rich protein 2A
LRG           97420_at      leucine-rich alpha-2-glycoprotein
TROP2         160651_at     tumor-associated calcium signal
                              transducer 2
SPRR2G        101754_f_at   small proline-rich protein 2G
SPRR2F        94120_s_at    small proline-rich protein 2F
BGP1          102805_at     CEA-related cell adhesion molecule 1
BGP1          102804_at     CEA-related cell adhesion molecule 1
BGP1          102806_g_at   CEA-related cell adhesion molecule 1
BGP2          101908_s_at   CEA-related cell adhesion molecule 2
CX26          98423_at      connexin 26
MUC1          102918_at     mucin 1, transmembrane
SPP1          97519_at      secreted phosphoprotein 1
CLU           161294_f_at   clusterin
CLU           95286_at      clusterin
CFTR          94757_at      cystic fibrosis transmembrane conductance
                            regulator homolog
KRT19         92550_at      keratin complex 1, acidic, gene 19
KRT19         102121_f_at   keratin complex 1, acidic, gene 19
SPRR1A        160909_at     small proline-rich protein 1A
GALNT3        162313_f_at   UDP-N-acetyl-alpha-D-
                              galactosamine:polypeptide
                              N-acetylgalactosaminyltransferase 3
Figure 7B--Defense responses

PLGR          99926_at      polyimmunoglobulin receptor
CTSL          101963_at     cathepsin L
LAMPI         100136_at     lysosomal membrane glycoprotein 2
CTSS          98543_at      cathepsin S
GST01         97819_at      glutathione S-transferase omega 1
GSTT2         104603_at     glutathione S-transferase, theta 2
CTSH          94834_at      cathepsin H
UGT1A1        99580_s_at    UDP glycosyltransferase 1 family,
                              polypeptide A6
CD14          98088_at      CD14 antigen
LGALS3        95706_at      lectin, galactose binding, soluble 3
PGLYRP        104099_at     peptidoglycan recognition protein
LGMN          93261_at      legumain
GARG16        100981_at     interferon-induced protein with
                              tetratricopeptide repeats
H2D1          99378_f_at    MHC beta-2-microglobulin
ISGFG3        103634_at     interferon dependent positive acting
                              transcription factor 3 gamma
H2Q1          101886_f_at   histocompatibility 2, D region locus 1
LYZP          101753_s_at   P lysozyme structural
LYZM          100611_at     lysozyme M
MLGP85        101389_at     scavenger receptor class B, member 2
H2D1          97540_f_at    histocompatibility 2, D region locus 1
CD68          103016_s_at   CD68 antigen
LY6A          93078_at      lymphocyte antigen 6 complex, locus A
MX1           98417_at      myxovirus (influenza virus) resistance 1

Figure 7C--Chemoattractant cytokines

MCP3          94761_at      monocyte chemoattractant protein 3
MCP1          102736_at     platelet-derived growth factor-inducible
                              protein JE
EOTAXIN       92742_at      small inducible cytokine al l
Figure 7D--Complement
CF1           99927_at      complement component factor i
C3            93497_at      complement component 3
CFH-related   92291_f_at    complement component factor-related
C2            103673_at     complement component 2 (within H-2S)
CFH-related   101853_f_at   complement component factor h
C1QA          98562_at      complement component 1, q subcomponent,
                            alpha polypeptide
C1QB          96020_at      complement component 1, q subcomponent,
                            beta polypeptide
C4            103033_at     complement component 4 (within H-2S)
C1QC          92223_at      complement component 1, q subcomponent, c
                              polypeptide
CFH-related   94743_f_at    complement component factor-related

Figure 7E--Iron homeostasis

CP            92851_at      ceruloplasmin
LTF           101115_at     lactotransferrin
LCN2          160564_at     lipocalin 2/24p3 gene.

Figure 8B

ETS2          94246_at      E26 avian leukemia oncogene 2, 3' domain
ATF3          104155_f_at   activating transcription factor 3
JUN           100130_at     Jun oncogene
JUNB          102362_i_at   transcription factor junB
FOS           160901_at     c-fos oncogene
FOSB          103990_at     FBJ osteosarcoma oncogene B
ATF5          103006_at     activating transcription factor 5
ATF4          100599_at     activating transcription factor 4
SPRR21        95794_f_at    small proline-rich protein 2I
SPRR2C        101761_f_at   small proline-rich protein 2C
SPRR2G        101754_f_at   small proline-rich protein 2G
SPRR2J        101755_f_at   small proline-rich protein 2J
SPRR2A        101025_f_at   small proline-rich protein 2A
SPRR2F        94120_s_at    small proline-rich protein 2F
SPRR2E        100723_f_at   small proline-rich protein 2E
SPRR1A        160909_at     small proline-rich protein 1A

(a) Gene annotations were derived by interrogation of the NetAffx (Liu
et al. 2003) database; http://www.affymetrix.com/analysis/index.affx
and by homology searching of nucleotide sequence databases (BLASTn;
http://www.ncbi.nih.gov/BLAST/) using Affymetrix probe target
sequences.

Table 1. Quantitative histologic analysis of mitotic
figures in uterine cells after exposure to [E.sub.2] for 8,
24, 48, and 72 hr. (a)

            Mitosis/m[m.sup.2] (mean [+ or -] SD)

Time (hr)        AO (5 mL)        [E.sub.2] (400 [micro]g)

8           1.36 [+ or -] 1.81      0.51 [+ or -] 0.41
24          3.86 [+ or -] 5.05     25.15 [+ or -] 6.37 **
48          3.81 [+ or -] 0.83      3.46 [+ or -] 3.26
72          3.88 [+ or -] 2.28      1.67 [+ or -] 1.77

Quantitative mitotic index data were derived from four
animals per group.

(a) Data were assessed for statistical significance using
ANOVA and a two-sided Student t-test (see "Materials
and Methods"I. **p < 0.01.

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Jonathan G. Moggs, (1) Helen Tinwell, (1) Tracey Spurway, (1) Hur-Song Chang, (2) * Ian Pate, (1) Fei Ling Lim, (1) David J. Moore, (1) Anthony Soames, (1) Ruth Stuckey, (1) Richard Currie, (1) Tong Zhu, (2) Ian Kimber, (1) John Ashby, (1) and George Orphanides (1)

(1) Syngenta Central Toxicology Laboratory, Alderley Park, Cheshire, United Kingdom; (2) Syngenta Biotechnology Inc., Research Triangle Park, North Carolina, USA

Address correspondence to G. Orphanides, Syngenta CTL, Alderley Park, Cheshire, SK10 4TJ, UK. Telephone: [phone]. Fax: [phone]. E-mail: [e-mail]

* Present address: Diversa Corporation, 4955 Directors Place, San Diego, CA 92121 USA.

Supplemental data is available online (http:// ehp.niehs.nih.gov/txg/members/2004/7345/ supplemental.pdf

We thank M.G. Parker, D.G. Deavall, N. Wallis, and T. Barlow for critical comments on the manuscript; P. Lefevre and J. Odum for technical assistance; and I. Kupershmidt and E. Hunter (Silicon Genetics) for advice on statistical analysis of microarray data.

This work was partially supported by the UK Food Standards Agency.

The authors declare they have no competing financial interests.

Received 22 June 2004; accepted 7 October 2004.