Molecular Human Reproduction, Vol. 9, No. 1, 19-33,
January 2003
© 2003 European Society of Human Reproduction and Embryology
Article |
Determination of the transcript profile of human endometrium
Submitted on August 6, 2002; accepted on September 15, 2002
1 Reproductive Molecular Research Group, University of Cambridge, Departments of Pathology and Obstetrics & Gynecology, Cambridge CB2 1QP, 2 Biostatistics Unit, Medical Research Council, Robinson Way, Cambridge CB2 2SR and 3 Pfizer Global Research & Development, Ramsgate Rd, Sandwich, Kent CT13 9NJ, UK 4 To whom correspondence should be addressed at: Reproductive Molecular Research Group, University of Cambridge, Department of Pathology, Tennis Court Rd, Cambridge CB2 1QP, UK. e-mail: jmb88{at}cam.ac.uk
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The response of the human endometrium to the ovarian hormones, estrogen and progesterone, has been the focus of decades of research. In order to understand this critical aspect of endometrial physiology, we undertook a genome-wide analysis of transcript abundance and changes in transcript level between normal endometrium in the proliferative and secretory phases of the menstrual cycle. A high-density, oligonucleotide gene array, comprising 60 000 gene targets, was used to define the gene expression profile of proliferative and secretory phase endometrium. Results from the arrays were verified using real-time PCR. The expression levels of 149 transcripts differed significantly between the two phases of the cycle determined by stringent range limits (99.99%), calculated using local variance values. These transcripts include previously documented steroidally responsive genes (such as placental protein 14 and stromelysin-3) and novel transcripts not previously linked to either endometrial physiology or steroid regulation (such as intestinal trefoil factor and a number of expressed sequence tags). Examination of the 5' promoter regions of these genes identified many putative estrogen and progesterone receptor DNA binding domains, suggesting a direct response of these genes to the ovarian hormones.
Key words: endometrium/glutathione peroxidase 3/intestinal trefoil factor/microarray analysis/steroid response element
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Introduction |
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The human endometrium is a complex tissue and its cyclic regulation requires the successful interaction of hundreds of factors. Normal human endometrium exhibits an idealized 28 day cycle, strictly controlled by the ovarian sex steroid hormones, estrogen and progesterone. The steroid hormones elicit their actions by binding to specific high-affinity receptors [estrogen receptor (ER)-
, ER-ß and progesterone receptor (PR)]; these act as ligand-dependent transcription factors (O’Malley and Tsai, 1992). In order to turn transcription on, the steroid hormones form homodimers and bind to the corresponding hormone. This complex then binds to the steroid response element to activate the transcription factors and begin transcription. Cooke et al. (1997) used the ERKO (estrogen receptor knock-out) mouse model to demonstrate that the proliferative effect of estrogen on uterine epithelium was a paracrine event, mediated through stromal estrogen receptors. Estrogen binds to the estrogen receptor in uterine stromal cells to trigger production of paracrine factors which act on uterine epithelium to stimulate mitogenesis (Cooke, 1997). These indirect mechanisms rely on the correct functioning and interaction of many local factors in the endometrium. It is these crucial local factors, or the pathways that lead to their generation, which we aimed to identify. We propose that this information will allow a greater understanding of the processes which regulate the human endometrium. Previous methods of investigation have limited research to small sub-groups of factors. Here we use oligonucleotide microarrays to assess the levels of all known transcripts in the human endometrium. Microarrays are now a widely recognized tool for effective assessment of thousands of genes in a single sample. Many different types of arrays are available, depending on the experimental needs. Affymetrix chips are two-dimensional, high-density oligonucleotide arrays capable of assessing the level of 60 000 transcripts within a single sample.
One significant problem with microarray experiments is how to effectively analyse the data and determine the statistical significance of the observed changes. Many studies simply assess fold change values between genes in control and experimental samples, accepting any gene with a fold change greater than a previously designated threshold value. However, this method is simplistic and prone to a high false positive rate. This is because there is considerably more variation in the signals obtained for transcripts with low signal values and small changes in the absolute value are greater. For example, a fold change of 20 may appear to be more interesting than a fold change of 4, but if the transcript levels actually change from 8000 to 32 000 (a 4-fold change) then this would be of more importance than a change of 2 to 40 (a 20-fold change). We have developed a novel method of statistical analysis of chip data to overcome these limitations.
Although endometrial physiology has been the focus of decades of research, many unresolved questions remain. Due to the large number of factors acting in combination, it is particularly difficult to gain a clear understanding of endometrial regulation. By determining the response of all the transcripts in this steroidally controlled tissue, we offer a description of those factors of importance in normal cyclic endometrium including a number of factors previously unreported in human endometrium.
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Tissue collection
Endometrial samples (10–500 mg) were obtained from five women between days 9 and 11 of the menstrual cycle (the proliferative phase group) and a further five samples from women, 6–8 days after the LH surge, as judged by measurement of urinary levels of LH.
All women had a normal pelvice (i.e. no endometriosis) as assessed by laparoscopic investigation for unexplained infertility (n = 1), dyspareunia (n = 5), sterilization (n = 3) or fertility investigation (n = 1). Of the 10 women included in the study, one was nulliparous, one had one child, four had two children, two had three children and two were unknown. None of the 10 patients had received any hormone therapy within 3 months before the biopsies were taken. The median age of patients was 35.7 years and the range was between 23 years and 44 years. All women had regular cycles (between 28 and 32 days). All tissues were examined by a histopathologist, who was unaware of the day of collection and all samples were found to be consistent with the appropriate stage of the cycle. For women in the secretory phase of the menstrual cycle, plasma levels of progesterone were determined by radioimmunoassay and all levels were >25 nmol/l. This project was approved by the Ethics Committee of Addenbrookes’ Hospital NHS Trust and written consent was obtained from all patients.
RNA extraction and performance of Affymetrix arrays
Total RNA was separately extracted from each tissue using Trizol Reagent (Invitrogen Life Technologies, Paisley, UK) and cleaned up using RNeasy affinity columns (Qiagen, Crawley, Sussex, UK). Total RNA was pooled into each group (proliferative or secretory) to give a total of 10 µg total RNA (2 µg from each sample). A sample of 5ug total RNA from each group was taken to run on the microarrays. Biotin labelling was performed according to the manufacturer’s instructions (Affymetrix Expression Analysis Technical Manual). Briefly, double-stranded cDNA (ds-cDNA) was synthesized and purified by phenol/chloroform/isoamyl alcohol. In-vitro transcription was performed with biotin-labelled CTP and UTP (Enzo Diagnostics, Farmingdale, NY, USA). RNeasy affinity columns (Qiagen) were used for clean-up of the labelled probe. Samples were hybridized to Affymetrix HG_U95 chips A–E and stained with a streptavadin–phycoerythrin (SAPE) stain. These arrays together cover 60 000 human genes and expressed sequence tags (EST) with roughly 12 000 being distributed over each of the five chips. All Affymetrix work was performed at Pfizer Global Research & Development, Sandwich, UK.
Although Affymetrix chips address the same questions as other microarrays, their method of assessment is markedly different. Each transcript is represented on the chip as a set of 16–20 ‘probe pairs’ with each pair containing a ‘perfect-match’ and a ‘mis-match’. The perfect-match is the precise reverse complement of the sequence of the transcript of interest. The mis-match is the same oligonucleotide as the perfect match but with a single base substitution at the central position. By comparing the hybridization level between the perfect-match and the mis-match, one can correct for the amount of non-specific hybridization. The Affymetrix Absolute Analysis algorithm (version 4.0) was used to analyse the scanned image. Global scaling techniques were used for all probe sets, to make the average intensity of each image equal to an arbitrary target intensity, set to 300. Transcript levels were assessed for all 60 000 genes and EST.
Statistical analysis
In order to highlight genes of particular interest, scatter plots were generated of average log transcript level in both phases of the cycle (x-axis) against difference in log transcript levels between the phases (y-axis). This was done for transcripts on chip A and for transcripts on chips B–E. Using the methods described below, we determined reference boundary limits (95, 97.5, 99, 99.5 and 99.99%). Genes/transcripts falling outside of these boundaries were taken to be significant.
The log-transformation allows the results to be interpreted in relation to the original expression data. The variables XPg and XSg represent the intensities corresponding to a gene (or EST) g in the proliferative and secretory samples respectively. Genes (or EST) with negative intensities in either one or both samples (a total of 22 321) are removed from the analysis.
A Bland–Altman type plot of the difference in log-intensities, also known as the log-intensity ratio, i.e.
versus the mean of the log-intensities, or the log-geometric mean intensity, i.e.
is plotted (Altman and Bland, 1983; Bland and Altman, 1986, 1999). Superimposed on the graph are upper and lower reference lines (collectively known as the reference boundary ranges), which indicate different levels of belief on whether there is either up- or down- regulation of a gene in the secretory sample compared with the proliferative sample. For this study, a gene (or EST) is potentially differentially expressed if its log-intensity ratio falls outside the 99.99% reference boundary range. The 99.99% limit was chosen instead of lesser extreme ones to overcome the problem of identifying too many false positives.
The Bland–Altman approach for constructing limits of agreement in method comparison studies is applied here to form the 99.99% [or any other, say 100(1 – )%] reference boundary. The upper and lower 100(1 – )% reference points of the reference boundary are defined for each gene (or EST), g, as
where
/2 is the (1/2) upper percentile point of the standard normal distribution. Thus the 99.99% reference points for a gene g are obtained from (1) with z1–/2 replaced by 3.89.
Note that
where n is the number of genes (or EST) considered and Var(.) and IQR represent the sample variance and the inter-quartile range of the mean log-intensity data respectively. Note that other choices of h can be used. The h chosen here is obtained from the Kernel Density Estimation literature (see Silverman, 1986). Note that we have chosen to borrow strength from the neighbours of a gene in order to calculate its SD. Thus we implicitly assume that genes with mean log-intensities that are similar also have similar variability in their log-intensity ratios.
The upper and lower reference coordinates of g are defined on the (x,y)-Cartesian Coordinate System as
with some abuse of notation. To produce smooth curves (upper and lower) from these reference coordinates, a robust locally linear scatter plot smoother called ‘lowess’, available in the statistical software package S-PLUS 2000© (1988–2000, MathSoft Inc; Cambridge, MA, USA), is employed.
Promoter analysis
Many of the transcripts identified in cyclic endometrium are under the direct influence of steroid hormone control. We investigated transcripts’ promoter regions for candidate steroid hormone response elements in silico using the MatchTM database hosted by the Gene Regulation website (http://www.gene-regulation.com/cgi-bin/pub/programs/match/match.cgi). Transcript promoter regions were determined by analysis of the DNA sequence upstream of the 5' start region of the gene of interest, as determined by investigation of corresponding genomic DNA and chromosomal sequences. Approximately 1 kb of promoter region from each transcript was used in each analysis. Only the vertebrate matrix was investigated. Core similarity and matrix similarity thresholds were set at the most stringent levels of 0.9 and 0.95 respectively and the number of candidate estrogen response elements (ERE) and progesterone response elements (PRE) determined.
Real-time PCR verification
In order to verify the results obtained from the Affymetrix chips, real-time PCR (Taqman) verification was performed for five genes: glutathione peroxidase 3 (GPX3), 17ß-hydroxysteroid dehydrogenase (17ß-HSD), metallothionein-1G (MT-1G), intestinal trefoil factor (TFF3) and lysyl tRNA synthetase. Primers and probes were designed using the Primer Express v1.5 software (Applied Biosystems, Warrington, UK) and purchased from Applied Biosystems and Sigma Genosys (Cambridge, UK). RNA from four of the five samples from the proliferative phase endometrium which were pooled for the Affymetrix chips and all five of the secretory phase samples were analysed individually. Details of the primers and probes used in the verification analyses are detailed below. All primers were labelled with 5'FAM and all probes were high-performance liquid chromatography-purified and labelled with TAMRA as the quencher.
GPX3 primers and probes were 5'CATCCCCTTCAAGCAGTATGCT-3' (forwards primer, Tm = 59), 5'GCCCGTCAGGCCTCAGTAG-3' (reverse primer, Tm = 59) and 5'AAATACGTCCTCTTTGTCAACGTGGCCA-3' (probe, Tm = 69). 17ß-HSD primers and probes were 5'GGCTTCCCAGGATCTGACT-3' (forwards primer, Tm = 59), 5'CCAGCTTTCCCACTTGTCACT-3' (reverse primer, Tm = 59) and 5'TTCCTTTCACCCCAGATATCGCAGGC-3' (probe, Tm = 69). MT-1G primers and probes were 5'GCCAAATTCCCAGACACCAT-3' (forwards primer, Tm = 58), 5'GAGTCCCCTTACCTCTGATAGCAA-3' (reverse primer, Tm = 59) and 5'AGTGTCCCTGGGTTTGAGGAGGTCGTAT-3' (probe, Tm = 68). TFF3 primers and probes were 5'CCTTGCCCGGCTGTGA-3' (forwards primer, Tm = 59), 5'GCTTGCCGGGAGCAAAG-3' (reverse primer, Tm = 59) and 5'TGCTGCCAGGCACTGTTCATCTCAGT-3' (probe, Tm = 69). Lysyl tRNA synthetase primers and probes were 5'CGTGGACCCAAATCAATACTACAA-3' (forwards primer, Tm = 59), 5'GGGTATGGGTCTTCCCCATT-3' (reverse primer, Tm = 58) and 5'TCCGCAGTCAAGCAATTCATCAGCTG-3' (probe, Tm = 69). In addition to the transcripts above, two endogenous controls (ß-actin and cyclophilin) were assayed using the pre-designed primers and probes from Applied Biosystems and their levels of expression did not change between phases (data not shown). Standard curves were generated between experimental and endogenous transcript levels to ensure that the transcripts amplified at the same rate. This allows for normalization of differing amounts of starting material between samples. GPX3 was normalized to cyclophilin and the remaining four transcripts were normalized to ß-actin. Cycle threshold (Ct) values were obtained and delta Ct (
Ct) values calculated (Ct = experimental Ct – endogenous Ct). This ratio of experimental to endogenous signal was then compared with the transcript level ratio for the same transcripts from the Affymetrix results.
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Results |
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Transcripts were ranked by abundance to assess the most highly expressed genes in human endometrium. As expected, the most abundant transcripts encoded ribosomal proteins and the spiked controls with the Alu-(Sq) sub-family consensus sequence being the second most highly expressed gene (data not shown). Of the 12 626 transcripts represented on the HG_U95A chip, 5114 were recorded as ‘present’ in the proliferative phase and 4370 in the secretory phase. Table I shows the top 200 most highly expressed transcripts in proliferative and secretory phase endometrium. There is little difference between the highest ranking transcripts of the two phases of the cycle; of the 200 most highly expressed genes in proliferative endometrium, 182 were also found in the 200 most highly expressed genes in secretory endometrium. On the remaining four chips covering 50 549 transcripts (HG_U95B-E chips), 14 549 transcripts were present in the proliferative phase and 12 401 were present in the secretory phase. Genes were sub-grouped according to function and ribosomal proteins and controls were excluded from the analyses to allow clearer evaluation of genes of interest. In order to identify transcripts that differ between the two phases of the menstrual cycle, we considered both the transcript level in each phase and the change in transcript level between the two phases.
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As described previously, the Affymetrix analysis software often assigns negative values to the ‘average difference value’ or transcript level. Transcripts which fall into this category (in either of the two phases) have been excluded from our initial statistical analyses since negative numbers cannot be log-transformed. We have therefore excluded 3868 and 18 453 transcripts from the chip A and chips B–E analyses respectively. Transcripts that have been excluded from this type of analysis are discussed later.
Transcripts were divided into two main groups, those present on the HG_U95A chip, being the 12 626 most well-defined genes, and the remaining 50 281 less well-defined transcripts and EST present on the HG_U95B-E chips. Signal intensities (‘average differences’) for individual transcripts were plotted as increasing average log transcript level from both phases of the cycle (x-axis) against the difference in log transcript level between the two phases (y-axis) (Figure 1). Values are either positive (more highly expressed in the secretory phase) or negative (more highly expressed in the proliferative phase). This method of representing the data provided an effective means of highlighting transcripts which are both highly expressed in the endometrium and changing significantly between the two phases of the menstrual cycle. Figure 1a represents 8758 transcripts and Figure 1b represents 31 828 transcripts. Reference limits (95, 97.5, 99, 99.5 and 99.99%) were set and the transcripts lying outside of each range noted.
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Table II lists the 146 genes that lay outside of the 99% reference limits for the HG_U95A chip, including the 30 genes that lay outside of the 99.99% reference limits (marked by an asterix). The list of genes found outside of the less extreme boundaries can be found on our website (www.obgyn.cam.ac.uk). Transcripts were grouped according to function to provide a framework for understanding the network of genes that influence endometrial physiology.
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As many of the transcripts which change with the cyclic endometrium may act under the influence of steroid hormones, we probed the promoter regions of genes of interest for candidate ERE and PRE. This was performed in silico using the online tool, MatchTM. Table II shows the results from the analysis. Promoter regions were defined as described in Materials and methods and probed for both putative ERE and PRE, as defined by the TransfacTM database. Many of the transcripts which increased in the secretory phase exhibited a number of candidate progesterone response elements, e.g. transcobalamin had eight putative PRE and one candidate ERE and GPX3 had three PRE and two ERE. However, the number of candidate steroid response elements did not always reflect the behaviour of the gene. Those transcripts seen to be up-regulated in the secretory phase and therefore probably responsive to progesterone stimulation, and did not necessarily show a corresponding increase in the number of candidate PRE.
A number of transcripts were excluded from our initial statistical analyses due to having a negative average difference in one of the samples, as described earlier. Many of these transcripts may be interesting, for example a transcript may be recorded as ‘absent’ by the Affymetrix software (and given a negative average difference value) in one phase but highly expressed in the other phase, therefore being of considerable interest. Table III lists the excluded transcripts with the highest apparent fold change (>6) as determined by the Affymetrix version 4.0 software. As with Table II, transcripts have been sub-grouped into families according to function and probed for candidate ERE and PRE.
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In order to verify our findings from the Affymetrix arrays, we performed real-time PCR (Taqman analysis) on five genes; GPX3, 17ß-HSD, MT-1G, TFF3 and lysyl tRNA synthetase. As can be seen from Figure 2, all five genes confirmed the results from our Affymetrix arrays. TFF3 had a greater transcript level in proliferative phase endometrium compared with secretory phase endometrium. GPX3, 17ß-HSD and MT-1G exhibited a greater transcript level in secretory phase endometrium compared with proliferative phase endometrium and the level of lysyl tRNA synthetase remained largely unchanged throughout the cycle.
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Discussion |
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The endometrial cycle is determined by the ovarian sex steroids, estrogen and progesterone. The action of these hormones can be direct or indirect; cells may be stimulated to proliferate or secrete a protein, or alternatively an epithelial cell, for example, may respond to an estrogen-induced factor synthesized by a stromal cell. In the course of this study we have identified transcripts that are regulated and that reflect both modes of action.
Of the 5611 transcripts identified as present in the endometrium, the majority remained unchanged throughout the cycle. Many of these genes are highly expressed in endometrium and further characterization may allow them to be used as tissue-specific markers of endometrium. Expression levels of other genes did alter between the two phases of the cycle. We designed a statistical approach which allows the identification of genes whose expression levels change significantly between the two phases of the cycle and, as would be expected, these factors cover a range of protein families and physiological roles. The utility of this statistical method has been confirmed in two ways. Firstly our data are in agreement with previous studies that have identified some of the genes thought to be regulated during the menstrual cycle. These genes, for example the progesterone-dependent PP14 (glycodelin), are listed in Table IV. In addition, we have identified known transcripts either not previously identified in the endometrium or known to be steroid responsive. We have confirmed the presence and cycle-dependent changes for a small number of these by real-time PCR (Taqman). All five Taqman experiments confirmed the results from our Affymetrix studies.
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A recent investigation by Kao et al. also investigated gene expression in cycling human endometrium using Affymetrix microarrays. We show a novel statistical approach that allows the simultaneous consideration of transcript level in the tissue and the change in transcript expression levels between phases of the menstrual cycle. Although the approach and analysis of the two investigations were markedly different, similar findings were obtained from both. This highlights the strength of Affymetrix microarrays as tools for large scale investigations and broadly confirms the findings of both studies. Additionally, we report a group of genes highly expressed in the endometrium that do not alter in expression levels between the two phases of the cycle. We propose that these genes may be useful as molecular markers of human endometrium. Our analysis also extended past the 12 626 named genes analysed by Kao et al., to include all known genes and EST covered by the Affymetrix HG_U95 chips (60 000 in total), thus providing access to the most comprehensive gene expression profile for human endometrium to date. Furthermore, we investigated the steroid hormones’ action on the human endometrium by promoter analysis, highlighting transcripts thought to be acting directly in response to steroid hormone stimulation.
Our analysis identified over 100 known genes as being differentially expressed by cycling endometrium. These factors were subdivided into a variety of functional families: transcription factors, cell death and survival factors, transport and carrier proteins and differentiation and embryonic polarity mediators such as the Wnt (wingless-type MMTV integratin site) family of genes (Tables II and III). A number of novel factors not previously documented in human endometrium or previously shown to be hormonally regulated were also discovered. Here, we focus on the roles of two genes poorly defined in the endometrium; TFF3 and GP3.
Proliferative endometrium needs a number of growth and remodelling factors for successful regeneration of the denuded endometrium. One gene that falls into the category of remodelling factors is TFF3. The trefoil family of peptides (TFF) are mucin-associated peptides found predominantly in mucus-secreting cells of the gastrointestinal mucosa (Poulsom and Wright, 1993). This family of peptides share a common domain of 42–43 amino acids, including six cysteine residues, which form three disulphide bonds. This gives the proteins their characteristic three-loop structure and the family name (Thim, 1997). TFF and the mucins are often co-expressed in mucous cells and are thought to be involved in mucus structure and processing. Another function of the trefoil peptides is to maintain the surface integrity of mucus epithelia (Mashimo et al., 1996; Poulsom, 1996). They act as motogens to promote epithelial cell migration (Dignass et al., 1994) and mediate epithelial repair after damage, also referred to as restitution (Poulsom, 1996; Podolsky, 1997). The expression of the trefoil peptides is rapidly up-regulated after mucosal damage in mice and TFF3 knockout mice exhibit impaired mucosal healing (Williams and Wright, 1997).
Previous literature on TFF3 expression in the human endometrium is conflicting. Wiede et al. (2001) reported the finding of trefoil peptides in the human uterus, specifically TFF3 mRNA being in the surface epithelium of the endocervix. TFF-1 and -2 mRNA were detected occasionally in the endocervix and very rarely in the endometrium. Western blot analysis revealed TFF3 to be a constituent of human cervical mucus and located in the gland-like structures of the cervical epithelium. By RT–PCR, TFF3 was detectable in the endometrium but no cycle-dependent changes were seen and the protein was not detectable by Western blot analysis. Our investigations showed a 52-fold greater level of TFF3 in the proliferative phase of the cycle compared with the secretory phase. Similarly, our real-time PCR studies showed an average 15-fold increase in TFF3 level in the proliferative phase compared with secretory phase. Promoter analysis identified two candidate ERE but no PRE in this gene. In agreement with our findings, Kao et al. (2002) reported the increased expression of TFF3 in proliferative endometrium compared with endometrium at the time of implantation as assessed by Genechip technology.
The increased level of TFF3 mRNA during menstrual repair and epithelial proliferation suggests that this factor may play a role at this time as considerable epithelial cell migration is required. Due to its motogenic and anti-apoptotic effects, we propose that human intestinal trefoil factor plays a key role in the regeneration of the human endometrium following menstruation.
Glutathione peroxidase 3 (GPX3) and metallothionein act to protect cells from damage from unstable reactive radicals and heavy metals (Kagi, 1991; Sies, 1993). The glutathione peroxidases are a family of reducing agents, which function to reduce hydrogen peroxide and organohydroperoxides (Ursini et al., 1995; Arthur, 2000). Cells exposed to such reactive oxygen species (oxygen free radicals) are subject to considerable damage, often resulting in death of the cell (Buttke and Sandstrom, 1994). Free radical damage is implicated in the pathophysiology of a number of organs including the endometrium (Ishikawa et al., 1993; Hubel, 1999; Beltran-Garcia et al., 2000). Glutathione peroxidases reduce these free radicals to harmless compounds. The glutathione peroxidase family are selenium-dependent proteins (Flohé et al., 1973; Rotruck et al., 1973). Selenium deficiency in women is associated with spontaneous abortion and infertility (Kingsley et al., 1998), thus the selenium-dependent GPX may play a role around the time of implantation to protect the embryo from oxidant damage and to create a safe environment for reception of a fertilized ovum.
Recently, glutathione peroxidase 1 (GPX1) was identified in the surface and glandular epithelium of normal, eutopic, human endometrium throughout the menstrual cycle. Expression was assessed by immunohistochemistry and GPX1 was weakly observed in the early proliferative phase, gradually increasing to a peak in the early secretory stage before decreasing again thereafter (Ota et al., 2000). To date, there are no published data describing the specific expression of plasma glutathione peroxidase (GPX3) in the human endometrium. We found that GPX3 was highly expressed in secretory phase endometrium but only detectable at very low levels in the proliferative phase (94.9-fold higher in secretory phase compared with proliferative phase). Similarly, our real-time PCR studies found an average 50-fold increase in GPX3 expression in secretory phase versus proliferative phase endometrium. However, this was only true for samples obtained on day LH+8 (70.8-fold and 172.86-fold increase). On assessment of the promoter region of the GPX3 gene, we identified three candidate PRE and two candidate ERE.
The metallothioneins are ubiquitous low molecular weight proteins that protect cells against heavy metal ion toxicity and damage from oxygen-derived free radicals (Kagi, 1991). Heavy metal ions and oxygen free radicals may be detrimental to the attachment, implantation and development of the embryo (Orsi and Leesse, 2001). Our study reports the differences in expression levels of metallothionein between the phases of the menstrual cycle. We show that four metallothionein isoforms are up-regulated in secretory phase endometrium (MT-1G, MT-1E, MT-1H and MT-III). We verified this finding with real-time PCR experiments (MT-1G) and our promoter analysis revealed four candidate PRE compared with only two candidate ERE for this gene.
It is possible that plasma glutathione peroxidase and the metallothioneins are up-regulated by progesterone in human endometrium to protect the implanting embryo from harmful reactive oxygen species and heavy metal ion toxicity.
Identification of candidate ERE and PRE in the promoters of these genes suggests the possibility of direct steroid regulation. A number of transcripts markedly up-regulated in the progesterone-dominated secretory phase (e.g. MT-1G and GPX3) displayed more candidate PRE than ERE. In addition, genes down-regulated in the secretory phase, e.g. MUC5B, also displayed more candidate PRE than ERE. However, some transcripts known to be steroidally responsive, such as osteopontin (Johnson et al., 2000), had no ERE or PRE at all when probed using the criteria previously described. These genes may contain the hormone response elements outside the region of the promoter we analysed or the criteria may have been too strict. Alternatively they respond to steroids via indirect mechanisms.
In conclusion, we have catalogued all the transcripts present in human endometrium. Using a novel statistical approach, we have described transcripts with significantly different levels between the proliferative and secretory phases of the menstrual cycle. Additionally we identified candidate ERE and PRE in the promoter regions of these genes. We present two factors, GP3 and TFF3, as novel regulators of human endometrial function.
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Acknowledgements |
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We thank Claire M.Johnson for her technical help with the Affymetrix chips. This work was supported by a BBSRC CASE award in collaboration with Pfizer Ltd.
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S. Mirkin, G. Nikas, J.-G. Hsiu, J. Diaz, and S. Oehninger Gene Expression Profiles and Structural/Functional Features of the Peri-Implantation Endometrium in Natural and Gonadotropin-Stimulated Cycles J. Clin. Endocrinol. Metab., November 1, 2004; 89(11): 5742 - 5752. [Abstract] [Full Text] [PDF]
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C. Print, R. Valtola, A. Evans, K. Lessan, S. Malik, and S. Smith Soluble factors from human endometrium promote angiogenesis and regulate the endothelial cell transcriptome Hum. Reprod., October 1, 2004; 19(10): 2356 - 2366. [Abstract] [Full Text] [PDF]
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R. Grummer, S.W. Hewitt, O. Traub, K.S. Korach, and E. Winterhager Different Regulatory Pathways of Endometrial Connexin Expression: Preimplantation Hormonal-Mediated Pathway Versus Embryo Implantation-Initiated Pathway Biol Reprod, July 1, 2004; 71(1): 273 - 281. [Abstract] [Full Text] [PDF]
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A. Cervero, J. A. Horcajadas, J. MartIn, A. Pellicer, and C. Simon The Leptin System during Human Endometrial Receptivity and Preimplantation Development J. Clin. Endocrinol. Metab., May 1, 2004; 89(5): 2442 - 2451. [Abstract] [Full Text] [PDF]
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R. Varma, T. Rollason, J. K Gupta, and E. R Maher Endometriosis and the neoplastic process Reproduction, March 1, 2004; 127(3): 293 - 304. [Abstract] [Full Text] [PDF]
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B. Malette, E. Cherry, M. Lagace, M. Bernard, D. Gosselin, P. Hugo, and K. Shazand Large scale validation of human N-myc Downstream-Regulated Gene (NDRG)-1 expression in endometrium during the menstrual cycle Mol. Hum. Reprod., November 1, 2003; 9(11): 671 - 679. [Abstract] [Full Text] [PDF]
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S. Tulac, N. R. Nayak, L. C. Kao, M. van Waes, J. Huang, S. Lobo, A. Germeyer, B. A. Lessey, R. N. Taylor, E. Suchanek, et al. Identification, Characterization, and Regulation of the Canonical Wnt Signaling Pathway in Human Endometrium J. Clin. Endocrinol. Metab., August 1, 2003; 88(8): 3860 - 3866. [Abstract] [Full Text] [PDF]
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R.D. Catalano, A. Yanaihara, A.L. Evans, D. Rocha, A. Prentice, S. Saidi, C.G. Print, D.S. Charnock-Jones, A.M. Sharkey, and S.K. Smith The effect of RU486 on the gene expression profile in an endometrial explant model Mol. Hum. Reprod., August 1, 2003; 9(8): 465 - 473. [Abstract] [Full Text] [PDF]
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L. C. Kao, A. Germeyer, S. Tulac, S. Lobo, J. P. Yang, R. N. Taylor, K. Osteen, B. A. Lessey, and L. C. Giudice Expression Profiling of Endometrium from Women with Endometriosis Reveals Candidate Genes for Disease-Based Implantation Failure and Infertility Endocrinology, July 1, 2003; 144(7): 2870 - 2881. [Abstract] [Full Text] [PDF]
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