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ToxSci Advance Access originally published online on October 20, 2008
Toxicological Sciences 2009 107(1):40-55; doi:10.1093/toxsci/kfn219
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© The Author 2008. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved. For permissions, please email: journals.permissions@oxfordjournals.org

The Genomic Response of a Human Uterine Endometrial Adenocarcinoma Cell Line to 17{alpha}-Ethynyl Estradiol

Jorge M. Naciff*,1, Zubin S. Khambatta*, Ryan G. Thomason*, Gregory J. Carr*, Jay P. Tiesman*, David W. Singleton{dagger}, Sohaib A. Khan{dagger} and George P. Daston*

* Miami Valley Innovation Center, The Procter and Gamble Company. Cincinnati, Ohio 45253 {dagger} Department of Cell Biology, Neurobiology, and Anatomy, Vontz Center for Molecular Studies, University of Cincinnati, Cincinnati, Ohio 45267

1 To whom correspondence should be addressed at The Procter and Gamble Company, Miami Valley Innovation Center, P. O. Box 538707 #805, Cincinnati, OH 45253-8707. Fax: (513) 627-0323. E-mail: naciff.jm{at}pg.com.

Received September 29, 2008; accepted October 9, 2008


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 FUNDING
 SUPPLEMENTARY DATA
 REFERENCES
 
We have determined the gene expression profile induced by 17 {alpha}-ethynyl estradiol (EE) in Ishikawa cells, a human uterine–derived estrogen-sensitive cell line, at various doses (1pM, 100pM, 10nM, and 1µM) and time points (8, 24, and 48 h). The transcript profiles were compared between treatment groups and controls (vehicle-treated) using high-density oligonucleotide arrays to determine the expression level of approximately 38,500 human genes. By trend analysis, we determined that the expression of 2560 genes was modified by exposure to EE in a dose- and time-dependent manner (p ≤ 0.0001). The annotation available for the genes affected indicates that EE exposure results in changes in multiple molecular pathways affecting various biological processes, particularly associated with development, morphogenesis, organogenesis, cell proliferation, cell organization, and biogenesis. All of these processes are also affected by estrogen exposure in the uterus of the rat. Comparison of the response to EE in both the rat uterus and the Ishikawa cells showed that 71 genes are regulated in a similar manner in vivo as well as in vitro. Further, some of the genes that show a robust response to estrogen exposure in Ishikawa cells are well known to be estrogen responsive, in various in vivo studies, such as PGR, MMP7, IGFBP3, IGFBP5, SOX4, MYC, EGR1, FOS, CKB, and CCND2, among others. These results indicate that transcript profiling can serve as a viable tool to select reliable in vitro systems to evaluate potential estrogenic activities of target chemicals and to identify genes that are relevant for the estrogen response.

Key Words: Ishikawa cells; human uterus; gene expression profiling; microarrays; 17 {alpha}-ethynyl estradiol; in vitro.


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 FUNDING
 SUPPLEMENTARY DATA
 REFERENCES
 
To better understand the relationship of altered gene expression to frank toxicity, most of the experimental work we have done has involved the evaluation of gene expression profiles in various in vivo systems, exposed to model chemicals representing graded levels of estrogenic activity, for example, the estrogens: 17 {alpha}-ethynyl estradiol (EE), bisphenol A (BPA), and genistein, using high-density oligonucleotide arrays (Naciff et al., 2007Go, 2005aGo, 2005bGo, 2003Go, 2002Go). The quantitative relationships between changes in gene expression and manifestations of estrogenicity in vivo, that we have determined using the rat uterus as the experimental model, clearly supports the use of transcript profiling as an endpoint in quantitative assessments of estrogenicity for any given chemical. This uterine genomic response encompasses the gene expression changes induced in the different cell types that constitute this organ. We hypothesize that using transcript profiling, we can identify the genomic response of cultured individual cell types derived from the uterus to estrogen exposure, which should be part of the response determined in vivo (at an organ level, i.e., uterus). To test this hypothesis, and to reduce the limitations of existing cell culture systems currently used to determine estrogenic activity of chemicals of interest, in the present study we have evaluated the genomic response of a human uterine–derived endometrial adenocarcinoma cell line, the Ishikawa cells, to an estrogen-receptor agonist and compared this response to the one determined in vivo. We reason that if similar expression profiles are determined in specific cell types (in vitro models), when compared with the whole organ response (in vivo data), then the need for animal experimentation to evaluate the potential estrogenicity of any given chemical could be further reduced, by at least helping to select tiered-testing strategies, or even eliminated. The identification of an in vitro system to screen chemicals for potential estrogenic activity will be a great asset to assist in the evaluation of chemical safety. Moreover, this system could be of great benefit to respond to the demand for chemical toxicity data to fulfill the requirements of regulatory programs such as the Registration, Evaluation, Authorisation and Restriction of Chemicals program within the EU and the High Production Volume challenge program in the United States.

The Ishikawa cell line is one of the best-characterized human endometrial cell lines currently available. These are cells derived from a well-differentiated adenocarcinoma of the human endometrial epithelium, and express functional steroid receptors for estrogen, progesterone, and androgen (Croxtall et al., 1990Go; Lessey et al., 1996Go; Lovely et al., 2000Go; Nishida, 2002Go, Nishida et al., 1985Go), which makes them an ideal model to study the response of the endometrial epithelium to estrogen exposure. The human endometrium is a unique uterine tissue that lines the lumen of the uterus and undergoes cyclic regeneration after each menstrual cycle in anticipation of pregnancy. This cyclic regeneration of endometrial lining is driven by changes in steroid hormone levels, which occurs as part of the estrous cycle in most mammals, or through the menstrual cycle in humans and the great apes (Jabbour et al., 2006Go). In either case, the endometrium proliferates initially under the influence of estrogen. Once ovulation occurs, in addition to estrogen, the ovary will start to produce progesterone and thereby change the proliferative pattern of the endometrium to a secretory lining. In time, the secretory lining provides the environment for the establishment of receptivity towards embryo implantation. If conception does not occur (no fertilized egg is detected), the progesterone level drops and the endometrial lining is either reabsorbed (estrous cycle) or shed (menstrual cycle). It has been proposed that the responsiveness of the endometrium to estrogen makes this tissue particularly susceptible to many pathological states including endometrial polyps, endometriosis, hyperplasia, and cancer (Attar and Bulun, 2006Go; Deroo and Korach, 2006Go). The characteristics of the Ishikawa cells make them a good surrogate cell model to study the estrogen response of the endometrial epithelium.

We are aware of the potential limitations of using in vitro systems to evaluate the genomic response to chemical exposure. The main limitation of in vitro models is that the relationships and interactions between the metabolites of multiple organs, between biological processes and molecular components of the different cell types that take place in an intact animal and affect gene expression are hard or even impossible to simulate (in vitro). Transcript profiling does not overcome these and other disadvantages. Further, in a cell culture system, the major systemic metabolic processes are missing and consequently the effect of a given chemical could be partially misrepresented. Thus, it can be predicted that not all the gene expression changes induced by chemical exposure in an in vitro model are necessarily the same that are induced in vivo. Nonetheless, with the information we have gathered through gene expression profiling of target organs from intact animals, we are now in a position to better evaluate the response of various in vitro models that potentially could be use in the screening for chemicals with estrogenic activity. Using this approach we have identified a cultured cell line capable of mounting a genomic response to estrogen exposure which has a high degree of concordance with the response determined in vivo.

In this study, we have determined the gene expression profile induced by EE (a potent ER agonist) in Ishikawa cells, at various doses and time points. The doses tested were: 1pM, 100pM, 10nM, and 1µM, and the time points were 8, 24, and 48 h. Our results indicate that the genomic response of the Ishikawa cells after exposure to EE is time and dose dependent. This response is monotonic, as occurs in vivo, and has a clear overlap (molecular fingerprint) with the in vivo response to estrogen exposure. The analysis of the EE response in vivo (juvenile rat uterus) versus in vitro (Ishikawa cells) shows that 71 genes are regulated in a similar manner (up- or downregulated). Within this group of genes, there are some of the classical estrogen-responsive genes identified in multiple systems, such as progesterone receptor, MYC, FOS, SRY (sex determining region Y)-box 4, insulin-like growth factor binding protein (IGFBP) 3 and 5, and brain creatine kinase among others. These data indicate that our in vitro system is capable of mounting a proper estrogenic response. The Ishikawa cells respond to estrogen exposure by modifying some cellular pathways also affected by estrogen in vivo, and these cells offer a robust in vitro system to evaluate the potential estrogenicity of chemicals of interest.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 FUNDING
 SUPPLEMENTARY DATA
 REFERENCES
 
Chemicals.
EE was obtained from Sigma Chemical Company (St Louis, MO).

Cell culture.
Tissue culture flasks (430725 and 3506) and plastic disposables were obtained from Corning (Corning, Inc., Corning, NY). Dulbecco's modified Eagle medium (DMEM)/F12 was purchased from Invitrogen Corporation (Carlsbad, CA), and the fetal calf serum came from Hyclone (Logan, UT). The Ishikawa cell line is derived from a well-differentiated adenocarcinoma of a human endometrium and was a generous gift from Dr Masato Nishida (Kasumigaura National Hospital, Tsuchiura-shi, Ibaraki-ken, Japan). The cells were routinely maintained in DMEM/F12 supplemented with 10% fetal bovine serum (FBS) and antibiotic/antimycotic solution containing 100 units/ml penicillin-G, 100 µg/ml streptomycin and 0.25 µg/ml amphotericin B (Invitrogen Corporation/Gibco Life Technologies, Grand Island, NY) in a 37°C incubator at 5% CO2. Two days (48 h) before the experiments started, cells were stripped of endogenous steroids and cultured onwards in phenol red–free DMEM/F12 + 10% dextran-coated charcoal–treated (DCC) FBS (Invitrogen Corporation/Biosource Biofluids Cell Culture Products, Rockville, MD). After steroid starvation for 48 h, the cells were exposed to vehicle-control (0.1% ethanol in culture media), or to EE at doses of 10–12M (1pM, vL), 10–10M (100pM, L), 10–8M (10nM, H), and 10–6M (1µM, vH) for 8, 24, or 48 h. The doses tested include the EE concentrations that correspond to the IC50 determined for the recombinant human estrogen-receptor beta (~10–8M) (Han et al., 2002Go) and alpha (~10–10M) (Gutendorf and Westendorf, 2001Go) and should result in significant activation of these receptors. The indicated concentrations of EE were prepared in fresh phenol red–free DMEM/F12 + 5% DCC-treated FBS. Five independent cell cultures per time point and dose were used as "biological replicas".

Expression profiling.
Total RNA was extracted from each individual cell culture "biological replica" using TRI-REAGENT (Molecular Research Center, Inc., Cincinnati, OH), 8, 24, and 48 h after exposure to vehicle (controls) or EE (at the different doses tested). Total RNA was further purified by RNeasy kit (Qiagen, Valencia, CA). Ten µg of total RNA from each sample were converted into double-stranded cDNA using SuperScript Choice system (Invitrogen Corporation/GIBCO BRL, Rockville, MD) with an oligo-dT primer containing a T7 RNA polymerase promoter. The double-stranded cDNA was purified by phenol/chloroform extraction, and then used for in vitro transcription using ENZO BioArray RNA transcript labeling kit (Enzo Life Sciences, Inc., Farmingdale, NY). Biotin-labeled cRNA was purified by RNeasy kit (Qiagen), and a total of 20 µg of cRNA were fragmented randomly to ~200 bp at 94°C for 35 min (200mM Tris-acetate, pH 8.2, 500mM KOAc, 150mM MgOAc). After determining the target cRNA quality, using the Agilent 2100 bioanalyzer (Agilent Technologies, Inc., Palo Alto, CA), samples from five individual samples (replicates) from each treatment group with high quality cRNA were selected and hybridized to Affymetrix Human Genome U133 Plus 2.0 high-density oligonucleotide microarrays (Affymetrix Inc., Santa Clara, CA) for 16 h. The microarrays were washed and stained by streptavidin-phycoerythrin (SAPE) to detect bound cRNA. The signal intensity was amplified by second staining with biotin-labeled anti-streptavidin antibody and followed by SAPE staining. Fluorescent images were read using the Affymetrix GeneChip Scanner 3000 with Autoloader (Affymetrix, Inc.).

Real-time reverse transcriptase–PCR.
In order to corroborate the relative changes in gene expression in selected genes identified by the oligonucleotide microarrays, we used a real-time (kinetic) quantitative reverse transcriptase–PCR (QRT-PCR) approach, as described (Naciff et al., 2003Go). Table 1 shows the nucleotide sequences for the primers used to test the indicated gene products. Preliminary experiments were done with each primer pair to determine the overall quality and specificity of the primer design. To confirm the amplification specificity from each primer pair, the amplified PCR products were size-fractioned by electrophoresis in a 4% agarose gel in Tris borate ethylene diamine tetraacetic acid (TBE) buffer and photographed after staining with ethidium bromide. After QRT-PCR only the expected products, at the correct molecular weight, were observed.


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  		TABLE 1 Primers Used to Verify the Array-Based Gene Expression Changes Induced by EE in the Ishikawa Cells by QRT-PCR

 
Data analysis.
Potential interindividual variability was addressed by using independent samples of each dose group (n = 5) for analysis. For gene expression analysis, scanned output files of Affymetrix microarrays were visually inspected for hybridization artifacts and then analyzed using Affymetrix Microarray Suite (version 5.0) and Data Mining Tool (version 3.0) software, as described (Lockhart et al., 1996Go; http://www.affymetrix.com/index.affx). Arrays were scaled to an average intensity of 1500 units and analyzed independently. The Affymetrix Human Genome U133 Plus 2.0 microarrays used in this study have 54,613 probe sets which include 38,500 annotated human genes, and expressed sequence tags (ESTs). For a full description of the Human Genome U133 Plus 2.0 array content see http://www.affymetrix.com/products/arrays/specific/rat230.affx. Each gene or EST is represented by 11 pairs of 25-mer oligonucleotides that span the coding region. Each probe pair consists of a perfect match sequence that is complementary to the cRNA target and a sequence that is mismatched by a single base change at the middle of the 25-mer oligonucleotide, a region critical for target hybridization. The mismatched oligonucleotide serves as a control for nonspecific hybridization. For the entire analysis, each probe set was analyzed as an individual entity, based upon its Affymetrix ID number (Affy ID), regardless of the multiplicity of probe sets representing any given gene product, and were considered as representing an individual gene until the completion of the analysis. Subsequently, all the probe sets (Affy IDs) were annotated and when possible, identified by its corresponding gene acronym. Distinct algorithms made an absolute call, present/marginal/absent, for each transcript, and calculated the average difference between perfect match and mismatch probe pairs (signal value). The mathematical definitions for each algorithm are described in the Affymetrix Microarray Suite User's Guide, Version 5.0.

The gene expression values derived from The Microarray Analysis Suite (MAS 5.0; Affymetrix), hereafter termed signal, were evaluated for quality based upon both overall measures of the microarray quality, and simple outlier detection methods. None of the microarrays were detected as outliers. The samples (microarrays) from the quality control analysis were then analyzed for treatment and time effects using a linear model for the log signal value that is a function of both treatment and time, where time is treated as a nominal factor. For each probe set (Affy ID) separately, treatment effect was assessed by comparing the model that estimates signal uniquely for each combination of time and treatment to the model that estimates signal for each time, but with no allowance for any treatment effect. This approach makes no assumptions about the functional form of the time course of response, which is unlikely to be of a uniform magnitude for all time points. For the purposes of summarization, follow-up analyses that evaluate treatment effect at each time point were also conducted. An analysis of the effect of time was also conducted on control samples only, using a standard single factor analysis of variance on the log signal response. Probe sets (Affy IDs) for which any of the tests had p ≤ 0.0001 was taken as evidence that the expression of these probe sets (Affy IDs) was modified by EE treatment at the time and dose being tested. This procedure was done for each time point and dose group versus the time-matched control, and for the full group of study results (vehicle vs. EE-treated at various doses, at all time points). Fold-change summary values for genes were calculated as a signed ratio of mean signal values (for each time and dose point-group compared with the appropriate time-matched control). Because fold-change values can become artificially large or undefined when mean signal values approach zero, all the values < 100 were set to 100 before calculating the mean signal values that are used in the fold-change calculation. Note that all statistical analyses use the measured signal values, even if they were smaller than 100 units. After selecting all the significant probe sets, for any given time and dose being evaluated, for vehicle-control and EE-treated samples, we eliminated probe sets representing the same gene product (or EST), leaving only one probe set (with the most significant p value) per annotated gene (or EST) listed for each group.

In order to help identify associations between the estrogen-responsive genes and specific biological processes affected by EE treatment, we used the Gene Ontology (GO) terms associated with these genes. The probe sets representing ESTs were not included for this analysis, because there is no annotation associated to them. The GO (http://geneontology.org/) project is a "collaborative effort to address the need for consistent descriptions of gene products in different databases". GO annotations capture the available functional information of a gene product and can be used as a basis for defining a measure of functional similarity between gene products. In order to assign a unique GO term to individual probe sets identified as statistically showing expression changes induced by EE exposure, we mapped the probe sets selected from the statistical analysis of the data (p ≤ 0.0001, t-test), to their corresponding annotations in the GO using the three major branches of the GO: biological process, cellular component, and molecular function. Redundancies due to multiple probe sets representing the same gene were eliminated for this analysis. The probe set selected showed the most statistically robust response. Each gene was assigned to all possible biologically descriptive GO terms, and processed to identify clusters of genes representing unique GO terms. The clusters in the ontology were identified using the algorithm of Joslyn et al. (2004)Go in combination with Fisher's Exact test (Beissbarth and Speed, 2004Go) to estimate the statistical significance of the mapping. This approach allows the identification of statistically over-represented GO terms within the significant group of estrogen-responsive genes. After determining orthologs (using public sources, including HUGO, Entrez Gene, Mouse Genome Informatics and Rat Genome Database), the annotation was used as a common vocabulary to annotate genes for comparison, and thus, helped to identify gene homologues between the in vivo (rat uterus) and the in vitro (human-derived Ishikawa cell line) data sets, given that the premise is that the products of the EE-responsive genes perform the same molecular functions, take part in the same biological processes and are located in the same cellular component in the two different species.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 FUNDING
 SUPPLEMENTARY DATA
 REFERENCES
 
In order to optimize the detection of the genomic response of cells after exposure to graded doses of EE, we used serum starvation, to synchronize the cells at G0/G1 stage of the cell's cycle (Cho et al., 2005Go; Kues et al., 2000Go). In the mouse uterus 17 β-estradiol stimulates the cells to undergo a synchronized wave of DNA synthesis and cell division (Cheng et al., 1985Go), exposure of the Ishikawa cells to estrogen stimulates this process (see for example Graziani et al., 2003Go; Vivacqua et al., 2006Go). It has been established that the estrogen-sensitive MCF-7 cells (a human-breast cancer epithelial cell line) that are growth-arrested by serum deprivation, are stimulated to continue the cell cycle (exiting the G1 stage induced by a 24-h serum-deprivation period) and proliferate by 17 β-estradiol (Lykkesfeldt et al., 1986Go). Because the serum provides essential components to maintain cellular viability and adequate responsiveness, the exposure to EE was done in media supplemented with DCC stripped serum (Invitrogen Corporation), which contains minimal quantities of steroids. The viability of the Ishikawa cells in the media containing 10% DCC-treated FBS without EE (controls cells) or with the various EE doses tested was determined, to ensure that the cell survival was not altered by either treatment. No differences in cell viability were observed, at any of the times evaluated (8, 24, or 48 h) in control and EE-treated cells. Further, the transcript profile determined in the 1pM EE-treated and the appropriate time-matched control cells is comparable (1pM; Figs. 1 and 2). The similarity in viability of control and EE-treated cells (even at the longest time point evaluated, 48 h) supports the statement that the gene expression changes determined are due to the EE treatment and not to differences in cell viability. Further, the gene expression analysis showed similar ratios of present and absent calls in control and EE-treated samples, which also indicates that both control and treated cells are biologically competent.


Figure 1
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  		FIG. 1. Temporal and dose-responsive gene expression changes induced by EE in Ishikawa cells. For this analysis the number of unique genes whose expression was affected by exposure to EE at the different times and doses were selected on the bases of significance (p ≤ 0.0001, t-test), and fold change (1.2-fold, up- or downregulated) compared with the appropriate time-matched control.

 

Figure 2
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  		FIG. 2. Eisen diagram (heat map) of the genes whose expression is modified at different times and doses of exposure to EE exposure in the Ishikawa cells. The genes showing a robust response after the indicated hours of EE exposure (p ≤ 0.0001, in multiple statistical tests, and at least 1.5-fold change, up- or downregulated) are shown in this diagram (2560 transcripts are displayed). Each cell of the data table is represented as a color-coded rectangle in which the color indicates the expression value (fold change calculated as described in "Methods") of unaffected (white), upregulated (red), or downregulated (blue) genes. The hierarchical clustering is based upon the dose response, and the positioning has been established according to the similarity in response of these genes to EE at the different times evaluated. The length of the lines in the tree indicates the similarity in regulatory pattern for each gene, with shorter length indicating more similarity. The National Center for Biotechnology Information RefSeq accession number for each gene shown is available upon request (J.M.N.).

 
Temporal and Dose-Responsive Gene Expression Changes Induced by EE
In order to determine the temporal and dose-responsive gene expression changes induced by EE in Ishikawa cells, we determined the gene expression profile at various doses (1pM, 100pM, 10nM, and 1µM) and time points (8, 24, and 48 h). The transcript profiles were compared between treatment groups (EE at the indicated doses) and controls (vehicle-treated) at 8, 24, and 48 h, using high-density oligonucleotide arrays to determine the expression level of 54,613 probe sets representing approximately 38,500 human genes and ESTs (Affymetrix Human Genome U133 Array). Trend analysis revealed that the expression of 2560 unique genes was modified by exposure to EE in a dose-dependent manner (p ≤ 0.0001). The number of genes which expression was affected by exposure to EE as a function of exposure time and doses is shown in Figure 1. For this analysis the genes affected by EE exposure were selected on the bases of significance (p ≤ 0.0001), and fold change (1.2-fold, up- or downregulated) compared with the appropriate time-matched control (Fig. 1). The exposure of the Ishikawa cells to 1pM, 100pM, 10nM, and 1µM EE induced the change in the expression of 17, 481, 611, and 639 unique genes respectively, across the different time points evaluated (with a p ≤ 0.0001, and fold change 1.5-fold, up- or downregulated). However, it must be emphasized that, if the fold-change cut-off is set to at least 20%, there are many more genes affected by EE at various time points, particularly at the three top EE doses tested (Fig. 1). These data shows that the genomic response of the Ishikawa cells to EE exposure is time and dose dependent.

The responsiveness of the Ishikawa cells to the potent ER agonist (EE) was barely detectable at the lowest dose evaluated (1pM). When we relax the fold-change cut-off value (20% fold change), the expression of 14, 9, and 11 genes was modified by 1pM EE at 8, 24, and 48 h after treatment, respectively, compared with the time-matched controls (p ≤ 0.0001). However, the genes affected by the low EE dose may be genuinely responsive to this estrogen (Table 2). For example, among the genes affected at this dose is transforming growth factor alpha (TGFA), whose expression is upregulated by 30% compared with controls, at 8 and 24 h after EE exposure and comes back to basal levels after 48 h. This relatively small change in the expression of TGFA mRNA induced by 1pM EE could be of biological significance because the corresponding protein has growth factor activity and is a key regulator of cell proliferation. Further, the expression of TGFA is upregulated more than 20-fold at higher EE concentrations and at all times evaluated (Tables 3Go–5). Another gene whose expression is also affected by the lowest dose of EE tested is Enhancer of yellow 2 homolog (Drosophila) (ENY2), however the change in its expression level is statistically significant only after 48 h of EE exposure. This gene encodes a protein that acts as a cofactor, which is required for full transcriptional activity by nuclear receptors. The expression of ENY2 is downregulated by EE after 48 h of exposure (Table 2), the same time requirement was observed even at higher doses, with a maximal downregulation (–1.6 fold) at 1µM EE.


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  		TABLE 2 Gene Expression Changes Induced by Exposure to 1pM EE

 

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  		TABLE 3 Gene Expression Changes Induced by Exposure to 100pM EE

 

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  		TABLE 4 Gene Expression Changes Induced by Exposure to 10nM EE

 

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  		TABLE 5 Gene Expression Changes Induced by Exposure to 1µM EE

 
The temporal and dose-dependent transcriptional response of the affected genes is shown in an Eisen diagram (Fig. 2), in which the relative expression levels of the 2560 genes showing the most robust response are compared at the different times and doses of EE exposure. These genes were selected by significance (p ≤ 0.0001) and magnitude of the change (≥1.2-fold change as compared with the appropriate control, up- or downregulated) at any given time and/or dose, and are ordered by similarity of temporal and dose expression through a "dendrogram" diagram. Each cell of the data table is represented as a color-coded rectangle in which the color indicates relative the expression value (normalized fold change) of unaffected (white), upregulated (red), or downregulated (blue) genes. Although there are quantifiable gene expression changes at each time point and dose evaluated, the largest number of genes being affected by EE is detected at 24–48 h after treatment, and these changes are induced by the highest doses tested (10nM and 1µM EE).

A list of selected genes (according to the highest fold change induced by treatment) whose expression was modified in the Ishikawa cells by EE at the indicated times and the different doses, along with their accession number, gene acronym, and the average fold change induced by EE is shown in Tables 244–5. The average of five independent samples was determined by comparing treatment versus control. In these tables, we have included the GO term from the biological process or the molecular function (when applicable), associated with each gene listed, in order to get a better insight of the potential functional implications for each individual gene affected by EE exposure. The complete data set is available at GEO (Accession GSE11869). As can be seen in Tables 234–5, there are multiple genes that responded to EE exposure, being up- or downregulated, in a consistent manner (by fold change and p value) in a time- and dose-dependent fashion, such as ALPP, PGR, TGFA, MLPH, GREB1, HES2, MMP10, NELL1, FGFR2, VGLL1, and PLXNA4A, to name a few. The change in the expression level of these and other genes, induced by EE exposure, is consistent with the estrogenic response of the Ishikawa cells observed in other studies. For example, EE induces the expression of ALPP in a time and dose-dependent fashion, with a maximal expression level determined after 48 h of exposure. This response supports previous findings where a marked increase in alkaline phosphatase activity was observed in Ishikawa cells exposed to estrogens (Holinka et al., 1986Go; Littlefield et al., 1990Go).

Functional Relevance of EE Regulated Genes
To facilitate the identification of associations between the estrogen-responsive genes and specific biological processes affected by EE treatment, we used the GO terms associated with these genes. The probe sets representing ESTs were not included for this analysis, because there is no annotation associated to them. In order to assign a unique GO term to individual probe sets identified as statistically showing expression changes induced by EE exposure, we mapped the probe sets selected from the statistical analysis of the data (p ≤ 0.0001, t-test; and fold change ≥1.5 or ≤–1.5), from any time and dose group, to their corresponding annotations in the GO using the three major branches of the GO: biological process, cellular component and molecular function. Redundancies due to multiple probe sets representing the same gene were eliminated for this analysis, which resulted in the annotation of 759 unique probe sets that matched the selection criteria (p value and fold change). These probe sets represent 542 individual genes whose expression showed the most robust response to EE exposure. Each gene was assigned to all possible biologically descriptive GO terms, and processed to identify clusters of genes representing unique GO terms. The clusters in the ontology were identified using the algorithm of Joslyn et al. (2004)Go in combination with Fisher's Exact test (Beissbarth and Speed, 2004Go) to estimate the statistical significance of the mapping. This approach resulted in the generation of clusters that contain genes which are both functionally related and highly coregulated by EE exposure, independent of the dose or time of exposure. This analysis indicated that EE elicits changes in the expression of genes associated with 44 unique GO biological processes, 31 unique GO molecular functions, and 9 unique GO cellular components. The clusters associated with the unique GO biological process are shown in the Supplementary Table 8, which also includes the results of the clustering analysis for the GO biological process and molecular function, where the data of all the genes that are affected by EE exposure, at the different doses and times, have been included without any restriction on p value and fold change. The GO annotation of some of the genes affected by EE treatment indicates biological processes that at first glance may seem irrelevant to describe the response of the Ishikawa cells, for example development, morphogenesis and organogenesis, containing 137, 68, and 38 genes in each respective cluster. However, these are parent GO terms that encompass multiple biological processes, some of which are relevant to understand the underlying mechanism of action of estrogens in these cells, and tissue from which they were derived (human uterine endometrium). For example, the GO term development encompasses cell differentiation, which by itself clustered 54 genes. One of the genes clustered within this GO term is TGFA, which is robustly upregulated by EE exposure, in a time and dose-dependent fashion (see Tables 2–5GoGoGo). TGFA has been associated with multiple biological processes, such as activation of mitogen-activated protein kinase (MAPK), angiogenesis, cell proliferation, positive regulation of epidermal growth factor receptor activity, positive regulation of mitosis, and positive regulation of epithelial cell proliferation, among other. Further, the GO terms listed (Supplementary Table 8) also indicate that genes linked to these terms must encode products for which functions are linked to the cellular (uterine) response to estrogens but which have not yet been characterized. The biological processes that are particularly associated with the response to the EE exposure are: cell proliferation, cell differentiation, cell migration, enzyme linked receptor protein signaling pathway, cell communication, transmembrane receptor protein tyrosine kinase signaling pathway and regulation of biological process. Although the molecular functions that are strongly associated with the EE response are: signal transducer activity, growth factor activity, receptor binding, calcium ion binding and heparin binding among others. The cellular components highly represented are: plasma membrane, extracellular region/space, and extracellular matrix.

Further, the genes identified as EE responsive at the different times were also mapped against a set of 141 canonical pathway maps from the Kyoto Encyclopedia of Genes and Genomes (KEGG). Most of these pathways represent small molecule metabolism, and a few describe portions of signal transduction and/or gene regulation networks (http://www.genome.jp/kegg/). From the metabolic pathways mapped, 41 contain a considerable number of genes whose expression was modified by EE exposure. The metabolic pathways that were particularly enriched with these genes include: genetic information processing, which includes transcription, translation, folding, sorting and degradation, replication and repair; translation, which incorporates protein biosynthesis, ribosome, and aminoacyl-tRNA biosynthesis; cellular processes, which incorporates cell growth and death, cell motility, cell communication; signal transduction which incorporates two-component system, and the signaling pathways for MAPK, ErbB, Wnt, Notch, Hedgehog, TGF-beta, vascular endothelial growth factor, Janus kinase- signal transducer and activator of transcription, calcium, phosphatidylinositol, and mTOR. The expression of the majority of genes that mapped to the indicated pathways was affected mostly at relatively high concentrations of EE exposure.

In Vivo versus In Vitro Data Comparison
In order to assess the value of the transcript profiling to improve interspecies extrapolation and to identify the robustness of the response of the Ishikawa cells (in vitro system) to screen chemicals for potential estrogenic activity, we compared the response of the Ishikawa cells to EE with the genomic response of the juvenile rat uterus (in vivo system) to this estrogen (Naciff et al., 2007Go). It has to be emphasized that this is not just an in vitro versus in vivo comparison, but also is an interspecies comparison (human vs. rat). For this comparison, only the data from the high dose (1µM EE) exposure of the Ishikawa cells was used and compared with the response of the juvenile rat uterus after exposure to a single dose of EE (10 µg/kg), at equivalent time points (8, 24, and 48 h). The probe sets representing ESTs whose expression was significantly regulated in both in vivo as well as in vitro by EE exposure were not included for this analysis, because there is no annotation associated to them and the consequent difficulty to clearly identify the corresponding homologs. Further, in this analysis the selection criteria for any given gene was that its response was statistically significant (p ≤ 0.0001, t-test). This comparison has shown that the change in the expression of 71 unique genes is identical in the direction of the change, although the magnitude of the change of some genes is different in the Ishikawa cells vs. the rat uterus exposed to EE. From these 71 common genes, only 56 showed a change in their expression level of at least 1.5-fold (up- or downregulated) at least at one time point both in vivo as well as in vitro and showed a great robustness in either system (p ≤ 0.0001, t-test) these genes are shown in Table 6. The genes that showed the most robust response to EE exposure in the Ishikawa cells include PGR, OLFML3, EGR1, IL6R, FOS, CKB [brain creatine kinase], SLC7A5, SLC9A3R1, VDAC1, and MMP7 (upregulated); and RASL11B, MYCN, ALDH1A1, LIMK2, SOX4, CTGF, COL5A2, IGFBP5, GABRP, FGFR2, PPARGC1A, PCM1, and NELL1 (downregulated). Although in the juvenile rat uterus, these genes are: MMP7, INSIG1, KLF4, GAL, FOS, CKB, SLC7A5, RFC3, NDUFB6, and IL6R (upregulated); and PTGS1, PRSS23, TSC22D3, TPM1, ALDH1A1, TSPAN1, IGFBP5, DKK3, SOX4, LRP2, CTGF, PPARGC1A, and IGFBP3 (downregulated).


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  		TABLE 6 Gene Expression Changes Induced by Exposure to EE both in Ishikawa Cells and the Rat Uterus

 
Using the annotation available for the genes responding to EE, we determined that the response of the Ishikawa cells as well as the juvenile rat uterus involves similar cellular processes, such as: regulation of transcription, signal transduction, cell proliferation, cell growth, cell differentiation and tissue remodeling, transport and metabolism.

Quantitative RT-PCR
The reliability of the microarray data was independently corroborated by QRT-PCR analysis of selected genes in samples from the same batch of RNA, from each sample, used for microarray analysis, at the different times and EE doses evaluated. The group of genes evaluated by QRT-PCR included genes up- and downregulated. The relative expression level of jagged 1 (Alagille syndrome) (JAG1), fibroblast growth factor receptor 2 (FGFR2), matrix metalloproteinase 10 (stromelysin 2) (MMP10), IGFBP3, TGFA, phosphatase, and tensin homolog (mutated in multiple advanced cancers 1) (PTEN), and progesterone receptor (PGR) was similar as that determined by microarray analysis (Table 7). The expression values of alkaline phosphatase, placental (Regan isozyme) (ALPP), which is highly induced by EE, were higher as measured by microarray analysis than with QRT-PCR, however its expression showed the same trend with time and dose responsiveness. No significant change in the expression levels of a housekeeping gene, peptidylprolyl isomerase B (cyclophilin B, PPIB), was identified by QRT-PCR or microarray analysis. These data clearly support the reliability of the gene expression changes of the Ishikawa cells induced by EE exposure identified by microarray analysis.


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  		TABLE 7 Selected Gene Expression Changes Induced by EE in the Ishikawa Cells, Confirmed by QRT-PCR

 
The reliability of the microarray data from the rat uterine–derived samples has been independently corroborated by QRT-PCR analysis of selected genes (including: PPIB, CLB3, HMGCS2, IL4R, HSD11B2, FBXI20, C3, MT3, MMP7, and PGR) in samples from the same batch of RNA, from each sample, used for microarray analysis, at the different times evaluated. These data have been published (Naciff et al., 2007Go).


   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
FUNDING
 SUPPLEMENTARY DATA
 REFERENCES
 
Existing in vitro cell-based assays that have been used to assess estrogenic activity are mostly based on cell proliferation, one of the hallmarks of estrogen action (i.e., induction of cell proliferation). However, there are uncertainties with these models that can be overcome by using another biological hallmark of estrogen exposure: the induction of changes in gene expression. We have demonstrated that the characterization of the most comprehensive transcript profile induced by chemicals with estrogenic activity, in vivo, increases the predictive accuracy of surrogate models, for example the rodent uterotrophic assay (Naciff et al., 2005bGo, 2007Go). Because the molecular pathways used by different cell types in multicellular organisms to maintain homeostasis are highly conserved among species, a genomic approach applied to surrogate models will minimize uncertainties in the extrapolation to humans. In order to reduce the limitations of existing cell culture systems currently used to determine estrogenic activity, we have focused our attention towards determining the genomic response induced by estrogen exposure of a human uterine-derived cell line and compared this response to the one determined in vivo. In this study, we identified the genomic response of the Ishikawa cells, a human-derived endometrial adenocarcinoma cell line, to EE, one of the most potent ER agonists. The analysis of the data indicates that this genomic response encompasses significant (p ≤ 0.0001) changes in the expression of 2560 genes. This genomic response is both time and dose dependent and follows a pattern suggestive of a monotonic or threshold response, as occurs in vivo in the uterus of the juvenile rat (Naciff et al., 2005bGo, 2007Go).

The response of the Ishikawa cells to chemicals with estrogenic activity has been evaluated in various studies, and in some cases the evaluation of gene expression changes have been included, although in a limited manner. When evaluated, these gene expression changes are consistent with our results. For example, Bramlett and Burris (2003)Go compared the effects of several ER ligands including some selective estrogen-receptor modulators on alkaline phosphatase activity and the expression of PGR, an ER target gene, in Ishikawa cells. They reported an estrogen-induced increase the alkaline phosphatase activity and the expression of PRG. Leong et al. (2004)Go also observed the effect of 10nM 17β-estradiol (after 6 h of exposure) on the expression of TGF-alpha, alkaline phosphatase, and PGR in the Ishikawa cells. Recently, Inoue et al. (2007)Go, examined the expression profile of Ishikawa cells exposed to 17β-estradiol (E2), diethylstilbestrol (DES), and BPA, using a limited custom array (with 120 estrogen-responsive genes). These authors determined that the response of these cells to E2 and DES was more similar to each other, than the response to BPA. However, these authors only tested one concentration of each chemical and one time point, and they did not show the response (i.e., fold-change values) of the individual genes evaluated. Without this information it is not feasible to determine the concordance between our results and those of Inoue et al. (2007)Go. In one other study, Johnson et al. (2007)Go evaluated the transcriptional response of the Ishikawa cell line to treatment with E2 (10nM) or 4-hydroxytamoxifen (1µM), using a custom array containing ~19,000 human genes. In agreement with our observations, these authors reported a robust response to estrogen exposure of ALPP-like 2 (ALPPL2), nuclear receptor interacting protein 1 (NRIP1), GREB1 (gene-regulated by estrogen in breast cancer), and CKB. Their conclusion that NRIP1 and GREB1 are the highest ranked ER direct target genes is supported by our findings that the expression of these two genes is upregulated by EE.

In order to better assess the value of the transcript profiling to improve interspecies extrapolation and to assess the robustness of the response of the Ishikawa cells (in vitro system) to screen chemicals for potential estrogenic activity, we compared the response of the Ishikawa cells to EE with the genomic response of the uterus of the juvenile rat (in vivo system) to this estrogen (Naciff et al., 2007Go), at equivalent time points (8, 24, and 48 h). This analysis showed that the expression of 71 unique genes is identical in the direction of the change, although the magnitude of the change of some genes is different, both in the Ishikawa cells and the rat uterus exposed to EE. Within this group, there are some of the classical estrogen-responsive genes identified in multiple systems, such as progesterone receptor, MYC, FOS, SRY-box 4, IGFBP 3 and 5, and CKB among others. Further, we have previously determined that the expression of CKB, COL5A1, EGR1, IGFBP3, KLF4, NDRG2, PGR, and RBP1 is also regulated by estrogens of various potencies (specifically EE, BPA, and genistein) in the fetal reproductive system of the rat (Naciff et al., 2002Go). In addition, using the annotation available for the genes identified as estrogen-regulated in the Ishikawa cells we determined that these cells respond to estrogen exposure by modifying some of the same cellular pathways affected by estrogen in vivo, such as: regulation of transcription, signal transduction, cell proliferation, cell growth, cell differentiation and tissue remodeling, transport and metabolism (Naciff et al. 2007Go).

Numerous genes whose expression is affected by EE in the Ishikawa cells are also regulated by estrogen in the human endometrium. In an attempt to identify key regulatory mechanisms in the growth and development of the human endometrium, Punyadeera et al. (2005)Go used microarray analysis to determine the gene expression of uncultured human endometrium collected during menstruation and the late-proliferative phase of the menstrual cycle, as well as after 24 h incubation (cultured as explants) in the presence of 17 β-estradiol. These authors demonstrated that in the human endometrium, E2 (1nM) regulates the expression of PGR, alkaline phosphatase placental (Regan isozyme), GREB1 protein, SRY-box 4, IGFBP 3, cylin A1, CD44 antigen, secretoglobin family 1D member 2 (lipophilin B), secretoglobin family 2A member 2 (uteroglobin), cyclohoxygenase 2, prostaglandin-endoperoxide synthase 2, fibroblast growth factor 9 and 18, flotillin 1, carbonic anhydrase II, glycerol kinase, ribosomal proteins S11 and large P2, among other genes. The expression of these genes was also regulated by EE, in some cases even at lower concentrations (1 and 10pM, Tables 2 and 3) than E2, in the Ishikawa cells. The similarities between the genomic response elicited by E2 in the human endometrium and the one elicited by EE in the Ishikawa cells makes a compelling case that our in vitro system is capable of mounting a proper estrogenic response.

The fact that multiple genes were similarly identified as being estrogen-responsive in the Ishikawa cells and in rat uterus provides rationale for using Ishikawa cells for gene expression profiling to determine the potential estrogenic activity of chemicals of interest. However, further validation of this in vitro system is necessary before it is used as a screening test for hazard assessment.


   FUNDING
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 FUNDING
SUPPLEMENTARY DATA
 REFERENCES
 
The Procter and Gamble Company.


   SUPPLEMENTARY DATA
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 FUNDING
 SUPPLEMENTARY DATA
REFERENCES
 
Supplementary data are available online at http://toxsci.oxfordjournals.org/.


   ACKNOWLEDGMENTS
 
We thank Donald J. Versteeg and Ting Hu for their helpful discussions.


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 DISCUSSION
 FUNDING
 SUPPLEMENTARY DATA
 REFERENCES
 
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