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Oncology and Molecular Endocrinology Research Center, Centre Hospitalier de l'Université Laval (CHUL) Research Center, Centre Hospitalier Universitaire de Québec (CHUQ), Department of Anatomy and Physiology, Laval University, Quebec, Canada
| ABSTRACT |
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17ß-estradiol; 17ß-estradiol modulation; ovariectomized mice; oligonucleotide microarray; protein tyrosine phosphatase
| INTRODUCTION |
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17ß-Estradiol (E2) is well known to play the key role in mammalian endometrial physiology, since the proliferation of endometrial cells and the extension of spiral vessels that occur during the proliferative phase of the menstrual cycle are controlled by E2 (20, 46). Estrogen is also frequently associated with endometrial cancer, which comprises two subtypes: endometrioid carcinomas (type I) related to estrogen exposure and nonendometrioid carcinomas (type II), which are independent of E2 action (16). Type I cancers are characterized by mutation or upregulation of the expression of genes involved in cell cycle/intracellular trafficking, structural/cytoskeleton, and peptidases/proteases functions. Defects in DNA repair and a near-diploid karyotype are also observed.
Type II cancers often display mutations or amplification of cell cycle- and intracellular trafficking-related genes and growth factor-related genes (37, 41, 56). However, the majority of cases of endometrial cancers lack mutations in the family of genes cited above, thus suggesting that the molecular pathogenesis of endometrial cancer is not well understood. Furthermore, disregulation of specific groups of genes leads to numerous physiological disorders, namely, endometriosis (32), excessive bleeding (8), and cell aberrant growth (28, 32).
Therefore, to identify key genes that could be potentially implicated in uterine cancer susceptibility, this study focused particularly on the E2 modulation of the insulin-like growth factor I (IGF-I) signal transduction pathway, which involves the action of insulin-like growth factor binding proteins (IGFBPs) and the regulation of protein tyrosine phosphatases (PTPs) and MAPK phosphatases (MKPs).
IGF-I is defined as an estromedin transcriptionally activated by E2. IGF-I exerts also a strong influence on cell proliferation and differentiation (59) and is a potent inhibitor of apoptosis in human osteoblasts (33). The action of IGF-I is mainly mediated through the IGF-I receptor (IGF-IR), which is found throughout the uterus (myometrium, epithelium, and stroma), where cells proliferate in response to added IGF-I (63). IGF-I signal transduction involves the activation of several intracellular signaling pathways, including the Ras/Raf/MAPK and the phosphatidylinositol 3-kinase (PI3K) pathways (68). Furthermore, IGF-I is seen as an important mediator of the E2 uterotrophic action in mouse (42), as IGF-I-deficient female mice are infertile and display uterine hypoplasia (3), thus suggesting that the IGF-I action is an important determinant of uterine function. Interestingly, it has been indicated that, in the uterus, E2 can rapidly stimulate a sustained increase in the tyrosine phosphorylation of IGF-IR and insulin receptor substrate-1 (IRS-1) (55).
In contrast, PTPs can modulate protein kinase activity either directly or by controlling the phosphorylation state of protein kinase substrates. Disregulation of PTP functions induces an aberrant tyrosine phosphorylation and contributes to the development of many human diseases (73). For example, it has been shown that PTP1B can inhibit the tyrosine activity of the full-length IGF-IR in mammalian cells (7) and is also able to inhibit hormone-induced phosphorylation of the insulin receptor by specifically targeting the pTyr-1162 residue on its activation segment (58). The MKPs are dual-specificity phosphatases that inactivate MAPKs by specifically dephosphorylating their pTyr and pThr residues, and whose expression is in turn transcriptionally regulated by MAPKs. It has also been demonstrated that the growth factor-stimulating network containing MAPK1/2 follows a two-states model, which is MKP concentration dependent (5).
Even if several genes are known to be E2 responsive, the mechanisms regulating their temporal modulation remain poorly understood, and previous studies have mainly been performed on cultured cells. Microarray analysis provides a powerful tool for analyzing complex biological systems, allowing the identification of gene expression patterns. However, other studies of the rodent uterine genomic profiles have been performed using supraphysiological doses of E2 and/or less time points following E2 exposure (26, 27, 39, 70). Hence, in this study, to better understand the in vivo events triggered by a physiological dose of E2 at the transcriptional level in the uterus, time course uterine gene expression profiles were examined using oligonucleotide microarray analysis and further validated by quantitative real-time PCR (Q-RT-PCR). Our data provide new insights into how E2 finely modulates the IGF-I signal effect in uterine cells and could potentially lead to the identification of cancer susceptibility genes in uterus or other E2-dependent tissues like breast or ovary.
| MATERIALS AND METHODS |
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Animals, weighing between 20 and 24 g, were randomized according to their body weights and were assigned to 6 groups of 14 animals each as follows: group 1, gonadectomized (GDX) control; groups 26, GDX + 17ß-estradiol (E2; 0.05 µg/mouse). On day 1 of the study, animals were bilaterally ovariectomized (GDX) under isoflurane anesthesia. Before the necropsy, performed on day 8 of the study, mice received a single subcutaneous injection (0.2 ml/mouse) of the vehicle alone (5% ethanol-0.4% methylcellulose; group 1) or E2 (groups 26). The injection of vehicle was performed 24 h before the necropsy for animals in group 1, while E2 was injected 1 h (group 2), 3 h (group 3), 6 h (group 4), 12 h (group 5), or 24 h (group 6) before the necropsy.
On day 8 of the study, mice under isoflurane anesthesia were exsanguinated at the abdominal aorta followed by cervical dislocation. The uterus was collected and rapidly frozen in liquid nitrogen. Tissues were pooled and kept at 80°C until RNA extraction. According to the treatment, the temporal mRNA changes of 12,000 genes were analyzed by Affymetrix oligonucleotide microarray analysis (MG-U74 v2).
RNA Isolation and Microarray Hybridization and Analysis
Total RNA was isolated using Trizol (Invitrogen, Burlington, ON, Canada), following the manufacturer's protocol. Total RNA (20 µg) was converted to cDNA by incubation with 400 U of SuperScript II RT (Invitrogen) using a T7-oligo-d(T)24 primer [5'-GGCCAGTGAATTGTAATACGACTCACTATAGGGAGGCGG-(dT)24-3'], 1x first-strand buffer (50 mM Tris·HCl, pH 8.3, 75 mM KCl, 3 mM MgCl2, 10 mM DTT), and 0.5 mM dNTPs at 42°C for 1 h. Second-strand synthesis was performed using 40 U of DNA polymerase I, Escherichia coli DNA ligase, 2 U of RNase H (Invitrogen), 1x reaction buffer [18.8 mM Tris·HCl, pH 8.3, 90.6 mM KCl, 4.6 mM MgCl2, 3.8 mM DTT, 0.15 mM NAD, 10 mM (NH4)2SO4], and 0.2 mM dNTPs at 16°C for 2 h. cDNAs were blunt-ended with 10 U of T4 polynucleotide kinase (Invitrogen) incubated 5 min at 16°C. cDNA was then extracted with phenol-chloroform using phase lock gels (Brinkman, Mississauga, ON, Canada), ethanol precipitated, and resuspended in 10 µl of diethyl pyrocarbonate-treated H2O. cDNA was in vitro transcribed using a T7 BioArray High Yield RNA Transcript Labeling Kit (Enzo Diagnostics, Farmingdale, NY) to produce biotinylated cRNA. The mixture (20-µl final volume) was incubated at 37°C for 5 h, with gentle mixing every 30 min. Labeled cRNA was purified with an RNeasy Mini Kit (Qiagen, Valencia, CA) according to the manufacturer's protocol. Purified cRNA was then fragmented to 30- to 200-mer cRNA, using a fragmentation buffer (100 mM potassium acetate-30 mM magnesium acetate-40 mM Tris-acetate, pH 8.1), for 20 min at 94°C. The quality of total RNA, cDNA synthesis, cRNA amplification, and cRNA fragmentation was monitored by microcapillary electrophoresis (Bioanalyzer 2100; Agilent Technologies, Palo Alto, CA).
cRNA probes were hybridized to the MG-U74 v2 Genechip Set (Affymetrix, Santa Clara, CA). Fragmented cRNA (15 µg) was incubated with 1x hybridization buffer (0.1 mg/ml herring sperm DNA, 0.5 mg/ml acetylated BSA, 5 nM control oligonucleotide B2) and 1x eukaryotic hybridization control solution (1.5 pM BioB, 5 pM BioD, 25 pM BioD, and 100 pM cre) for 16 h at 45°C with constant rotation (60 rpm). The cRNA probe from the control group was hybridized on two microarrays (duplicate), while the cRNA probe corresponding to each time point was hybridized on separate microarrays. Microarrays were then processed using an Affymetrix Genechip Fluidic Station 400 (protocol EukGE-WS2Av4). Staining was performed with streptavidin-conjugated phycoerythrin (SAPE) followed by amplification with a biotinylated anti-streptavidin antibody and by a second round of SAPE solution. Genechips were scanned with the use of Genechip Scanner 3000 (Affymetrix). Signal intensities for ß-actin and GAPDH genes were used as internal quality controls. The ratio of fluorescent intensities for 5' and 3' of these housekeeping genes was <2. Scanned images were analyzed and normalized (target intensity equal to 500) with Microarray Suite (MAS) 5.0 (Affymetrix).
Differentially expressed genes were selected using a variable-limit fold change (LFC) (44) decreasing with gene expression value [LFC = a + (b/x), where x is the minimum intensity of gene expression]. The curve was estimated based on a ratio distribution calculated from replicated chips. The resulting cut-off point, LFC = 1.9 + (x60.0), produces an approximately constant rate of false positive-modulated genes of 0.1%. Genes over this criterion must also be called present at least in 2 points of the experiment using the MAS5.0 program. Affymetrix MAS5.0-normalized signal intensities were submitted to the Gene Expression Omnibus (GEO; http://www.ncbi.nlm.nih.gov/geo/) and are available under the following series ID: GSE6219.
Clustering Analysis
The differentially expressed genes were clustered using GeneCluster2 software based on a self-organizing maps algorithm. Genes showing a maximum-to-minimum ratio >1.9-fold in their gene expression levels and >300 in their expression intensities were selected. Selected genes were then normalized to obtain a mean value of zero and a standard deviation of one. Finally, the normalized data were clustered. The expression patterns of certain PTPs and MKPs, as well as selected genes belonging to the IGF-I pathway, were validated by Q-RT-PCR. The L2L software was used to classify genes from each cluster into biological processes (45). When genes could not be classified by this software, EASE software (29) was used to identify the biological process associated with the gene. With the use of L2L, the fold enrichment of specific subclasses of general functions was also calculated along with the corresponding P value derived from a binomial distribution (when applicable). Genes were classified in more than one major biological process, since several proteins can demonstrate many different physiological activities in cell metabolism, which is more representative of the gene function.
Q-RT-PCR
cDNA corresponding to 20 ng of total RNA coming from samples of a duplicated in vivo protocol was used to perform fluorescent-based real-time PCR quantification using the Light Cycler Real-Time PCR apparatus (Roche Inc, Nutley, NJ). Reagents were obtained from the same company and were used as described by the manufacturer. The conditions for PCR reactions were as follows: denaturation at 95°C for 10 s, annealing at 5666°C for 5 s, and elongation at 72°C for 713 s. The reaction was then heated for 3 s at 2°C lower than the melting temperature of the DNA fragment. Reading of the fluorescence signal was taken at the end of the heating to avoid nonspecific signal. A melting curve was performed to assess nonspecific signal. Oligoprimer pairs that allow the amplification of
200 bp were designed by GeneTools software (Biotools, Edmonton, Alberta, Canada), and their specificity was verified by basic local alignment search tool in the GenBank database. Data calculation and normalization were performed using the second-derivative and double-correction method, as described previously (36a), and with use of the housekeeping gene hypoxanthine guanine phosphoribosyl transferase-1 (Hprt1). Hprt1 gene is recognized to display stable expression levels from embryonic life through adulthood in various tissues (69). mRNA expression levels are expressed as number of copies per microgram of total RNA using a standard curve of Cp vs. logarithm of the quantity, where Cp is crossing point. The standard curve was established using known cDNA amounts of 10, 102, 103, 104, 105, and 106 copies of Hprt1 and the Light Cycler 3.5 program provided by the manufacturer (Roche).
| RESULTS |
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Among the downregulated genes represented (clusters E, F, and G), energy metabolism is the main biological process downregulated in cluster E, while in cluster F, there is a slight decrease of expression of genes implicated in signal transduction, transcription, and protein metabolism compared with cluster E. In cluster G, genes related to defense and inflammation appear in preponderance.
Specific early modulated genes: 06 h (clusters A, B, and E).
As shown in Fig. 3, the genes associated with signal transduction were predominantly observed in cluster A, especially those belonging to the protein kinase cascade, the MAPKK cascade, and mRNA catabolism, which demonstrated a fold enrichment of 3.6, 5.7, and 11.1, respectively. Several transcription regulators like Fos, Junb, and Egr1 are well recognized as E2-responsive genes (12, 14, 36). The genes involved in translation, ribosome biogenesis, and amino acid activation are particularly enriched in cluster B in a range covering 6- to 10.8-fold. The downregulated genes included in cluster E are involved in fatty acid and aldehyde metabolisms (34).
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In cluster F, downregulated genes specifically involved in bone metabolism and cell differentiation are identified, with a fold enrichment of 14.8 and 7.1, respectively. Cluster G displays a significantly lower expression of genes related to immunity and RNA processing, particularly genes associated with antigen presentation and processing (human leukocyte antigen genes), which show a fold enrichment of 15.5.
Taken together, these observations point toward evidence of a rapid induction of transcriptional regulators and signaling component genes, followed by a late induction of cytoarchitectural genes, which have been well demonstrated in previous studies (27, 39, 70). Additionally, this study shows a significant time-dependent gradual diminution of specific genes involved in immunity and inflammation.
Estradiol Modulates the IGF-I Pathway
To confirm the temporal changes of gene expression levels of certain genes involved in the IGF-I pathway, Q-RT-PCR was performed (Fig. 4). Briefly, six IGF-related genes, three Ras/Raf/MAPK pathway-related genes, three PIK3 pathway-related genes, and five tyrosine and MAP kinase phosphatase genes were analyzed. All genes tested displayed an 82% correlation rate between microarrays and Q-RT-PCR.
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Ras/Raf/MAPK pathway.
Expression of the Cdc25c gene is strongly increased between 6 and 24 h (Fig. 4B). Furthermore, most Ras genes (Ran, Rasl2-9) are also induced within 3 h (see Supplemental Table S1). Then, MAPK1 (ERK2) expression shows a slight repression plateau between 6 and 18 h. The expression of the c-Myc gene is increased within 3 h, and expressed sequence tags (ESTs) similar to putative c-Myc-responsive genes (Homo sapiens) are induced within 18 h. In fact, c-Myc is an immediate early gene known to be activated after stimulation of the MAPK signal transduction pathway (11, 24). Following E2 treatment, the structural ornithine decarboxylase gene (ODC) is also upregulated within 6 h, its protein activity being well known to be induced after exposure to E2 in a tissue such as the uterus (72). Indeed, the ERK1/ERK2 activation has been shown to be essential for ODC induction, which is associated with cell proliferation (21, 57).
PI3K pathway.
From Fig. 4B, it can be seen that the expression of GAB1 and PIK3R2 genes is decreased within 6 h, while the SH3-domain GRB2-like B1 gene (SH3GLB1), which codes for an endophilin cell death promoter, is first slightly upregulated within 3 h and then inhibited between 6 and 12 h (data not shown). The BCL2-like 11 (apoptosis facilitator) gene is also downregulated within 12 h. The IGF-I activation of the PIK3 pathway is known to promote an anti-apoptotic effect (68).
Tyrosine and MAP kinase phosphatases.
As shown in Fig. 4C, the PTP genes PTP1B and PTP4A are early induced by E2 within 3 h. Similarly, MAP kinase phosphatase genes MKP1 and MKP3 are upregulated within 3 h. Then the STEP gene, whose product is known to deactivate the phosphotyrosine activity of ERK1/2 (associated with mitogenesis) (54), is induced within 6 h. The MKP1 gene product is also known to deactivate ERK (MAPK) (60), and the MKP3 gene product dephosphorylates the activated ERK2 (MAPK1) (43). Another gene belonging to this class is PTP1B, whose protein inhibits the activity of the full-length IGF-IR in mammals, while the product of PTP4A has been reported to stimulate cell growth and could be involved in tumorigenesis (10).
Taken together, these observations suggest that, as presented in Fig. 5, the PTPs and MKPs could be potentially closely involved in the extent and duration of the E2 uterotrophic effect in mice by targeting the IGF-I pathway.
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| DISCUSSION |
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The major cell cycle- and intracellular trafficking-related genes involving, notably, the protein kinase and MAPKK signaling cascades and heat shock protein (HSP) genes are upregulated early, i.e., within 06 h. Indeed, it has been shown that some HSPs would participate in cell proliferation by interacting with proteins needed for the proliferation process (50). Specifically, the oncogenes Fos and Junb are quickly upregulated (within 3 h), these genes being known to be rapidly induced by E2 (12, 36, 70). In addition, as previously reported for some of these genes (14, 39, 70), we observed that most signal transduction-related genes, transcription factors such as Egr1, Egr2, Cebpb and Nr4a1, and ribosomal protein genes are also stimulated during the first phase of the E2 effect (from 0 to 6 h). Taken together, these results are in line with previous observations confirming that, among E2-regulated genes in the mouse uterus, early induced transcription factors may play an important role in subsequent changes in gene expression (70), further suggesting that, in response to E2, a transcriptional cascade may operate in the uterus (39). Cardenas et al. (9) recently reported that the administration of E2 to ovariectomized gilts increased uterine weight. It is well known that proestrous in rodents is characterized by proliferation of endometrial cells accompanied by a gradual increase of estrogen concentrations (62). Interestingly, in contrast to previous studies, we report here for the first time that the Gadd45g gene is markedly stimulated very early (31.3-fold). Indeed, this gene has not been reported in previous studies (27, 39, 70). This regulation can, however, be taken seriously, given the additional confirmation by Q-RT-PCR and the modulation of several other known E2-responsive genes present in this study. Although no estrogen response elements (EREs) are present in the proximal region of the promoter of the Gadd45g gene, the presence of many SP1 sites could explain this regulation. Gadd45 proteins are involved in negative growth control, rendering this observation to be investigated more extensively. Interestingly, Gadd45g interacts with p21 and especially proliferative cell nuclear antigen (PCNA), which has been demonstrated to impede its effect on cell cycle arrest (2), as also observed for Gadd45
and Gadd45ß (66).
According to previous results (27, 39, 70), peptidase and protease genes reach their peak of expression at 12 h. It has been shown that peptidases, proteases, and their inhibitors could play an important role in balancing the uterine environment for appropriate sperm activity and the periodic remodeling of the uterine endometrium (62). Genes involved in intracellular transport and localization as well as protein targeting are also particularly predominant at 12 h. In agreement with the uterotrophic effect of E2, our data show a gradual upregulation (until 24 h) of most structural and cytoskeleton, extracellular matrix, and cell adhesion genes required for tissue development, which is also consistent with previous studies (27, 39, 70).
Interestingly, our data reveal a global modulation of many molecules associated with keratinization processes, mainly observed in cluster D, which is consistent with the cytoarchitectural structure evolution. In addition to the small proline-rich proteins (Sprr)-1A and -2A described previously by Hewitt et al. (27), we also report here the upregulation of Sprr1B, -2B, -2D, -2F, and -2G. Moreover, in addition to the keratin complex 1 gene-13 (Krt1-13) and -19 and Krt2-6a previously reported as E2 regulated (27), the data presented here also display the upregulation of Krt1-10, -16, -17, and -18 and Krt2-18 and -7 (cluster D) (see Supplemental Table S1). Therefore, as these above-mentioned regulations appear in conjunction with other genes known to be E2 responsive, it strengthens the reliability of data obtained and the efficacy of treatment.
Although the number of downregulated genes is more limited, we can point out the downregulation of inflammation genes occurring in the late phase (between 12 and 24 h). Besides, this downregulation, resulting in reduced levels of autoimmune disease activity, has been reported to correlate with high levels of circulating estrogen during pregnancy (1). Previous findings have also demonstrated that E2 has opposing effects on bone marrow lymphoid and myeloid differentiation (49). In concordance with these results, our data show that most of the immune genes early induced code for myeloid precursor-differentiated molecules, while the late-downregulated genes code mainly for lymphoid precursor-differentiated molecules (see Supplemental Table S1). Therefore, E2 may serve in promoting the myeloid-differentiated molecules action as well as inhibiting the lymphoid-differentiated molecules action in the mouse uterus.
Estrogens are known to behave as proadipogenic factors, and IGF-I has been shown to stimulate both growth and differentiation of preadipocytes (17). In this study, the expression of both lipid transport- and metabolism-related genes is decreased and then later increased by E2, which has not been observed in other studies. Interestingly, it has been suggested, although not significantly, that E2 could potentially downregulate triglycerides in liver, although it significantly induces serum triglycerides, while serum high-density lipoproteins seem to be slightly reduced in ovariectomized rats (23, 35, 53).
To further support our observations, we have developed a scheme illustrating how IGF-I pathway components interact and affect one another (Fig. 5). Consistent with the global expression profile revealed by our data, it has been suggested that IGF-I is a mediator of the E2 uterotrophic effect in the rat uterus (30, 42). The IGFBPs bind specifically to IGF-I with high affinity (18). As observed previously (40), the expression of IGFBP genes that inhibit the IGF-I effect (IGFBP3 and -6) appears to be repressed by E2, this inhibitory effect of IGFBP3 being well demonstrated in fibroblast cells (18), whereas the expression of IGFBP genes that potentiate the IGF-I effect (IGFBP2 and -5) is stimulated by E2, as previously reported in vascular endothelial cells (4).
In fact, these gene products are known to facilitate interaction with the receptor. Interestingly, IGFBP2 and -3 have been detected respectively in the luminal epithelium and in the stromal cells of the endometrium, while IGFBP5 and -6 are expressed in the myometrium (22). IGF-I binds to its receptor and induces a transphosphorylation that activates multiple signals that promote cellular proliferation. Indeed, it has been shown that a sustained increase in the tyrosine phosphorylation of IGF-IR and IRS-1 can be caused by E2 in the endometrial epithelial cells of ovariectomized mice (55).
E2 can then induce an IGF-I-activated signal transduction of the PIK3 and Ras/Raf/MAPK pathways. The E2 activation of the PIK3 protein thereafter induces the phosphorylation of AKT in endometrial cells (25) and the inactivation of the proapoptotic protein BAD, a member of the Bcl2 family that regulates the apoptotic response. E2 also inhibits SH3GLB1, an endophilin known to interact with the proapoptotic protein BAX and to promote cell death in mouse hematopoietic cells following interleukin-3 withdrawal (13), these genes being well known to contribute to apoptosis protection (52). Activation of the MAPK pathway has been shown to induce a transcriptional response associated with mitogenesis (38) and cell motility (6, 15, 64). As a consequence, genes that play important roles in cell proliferation induction, like c-Myc and ODC in this study, are upregulated following E2 stimulation of the MAPK signal transduction pathway. It has also been shown that the overexpression of ERK2 (MAPK1) activates Myc (11). Consistent with these results, Inoue et al. (31) recently suggested that endometrial IGF-I stimulates proliferation of mouse endometrial stromal cells, and that the MAPK pathway is involved in DNA replication of endometrial stromal cells. However, our results also show a slight E2 inhibition of the expression of the ERK2 (MAPK1) gene involved in the MAPK pathway and whose protein is phosphorylated after E2 exposure (Fig. 5). This could be explained by the activation of STEP, MKP3, and MKP1, whose gene products have been reported to inhibit MAPK1 (74). Moreover, it has to be stated that Myc can also be quickly transcriptionally activated by the direct action of E2, through the EREs present in its promoter (19).
In addition, IGF-IR overexpression and/or its constitutive activation have been associated with malignant transformation and have been linked to the metastatic properties of tumor cells. Particularly, endometrial tumors are more likely to overexpress IGF-IR (48). In the present data, IGF-IR is downregulated by E2, consistent with a cancer-free state. This could be explained by the activation of PTP1B, whose gene product has been shown to inhibit the tyrosine activity of full-length IGF-IR in mammalian cells (7). Analogous to what is seen in cardiac cells, where E2 increases MKP1 expression (61), we show that, in the uterus, E2 promotes the early induction of protein tyrosine and MKP genes such as PTP1B, MKP1, MKP3, and STEP, whose proteins target certain activated components of the IGF-I pathway, suggesting that these phosphatases may act as a negative control on IGF-I signaling in the mouse uterus. In the present study, E2 also downregulates some IGF-I pathway key components such as IGF-IR and MAPK1 (ERK2). However, the IGF-IR signaling pathways exhibit redundancy because of considerable cross talk among them (47). There is also evidence of an E2 regulation of IGF-I via androgen receptor (AR) production (51, 71) and of cross talk in IGF-IR and estrogen receptor signaling (26, 42, 68), thus illustrating the complexity of this process.
Our data support and confirm previous findings that E2 activates a transcriptional cascade resulting in an uterotrophic effect in the mouse. To control this process, E2 induces concomitantly genomic (gene modulation) and nongenomic (phosphorylation/dephosphorylation) mechanisms, although the changes observed in this study are all genomic, since they seem to result from altered gene expression. Although gene transcription changes represent a major cause of altered signaling pathways, we cannot exclude other nongenomic mechanisms, especially those involved in transduction signaling, that could be important mechanisms triggering protein level variations. A comprehensive knowledge of these mechanisms would be extremely useful for understanding the evolution and progression of uterine cancers as well as gynecological diseases and infertility. The role of the IGF-I pathway appears to be pivotal in this process, and therefore more work is definitely needed to further progress in this field.
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| FOOTNOTES |
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Article published online before print. See web site for date of publication (http://physiolgenomics.physiology.org).
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