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Cancer Research 67, 10694, November 15, 2007. doi: 10.1158/0008-5472.CAN-07-1621
© 2007 American Association for Cancer Research
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Molecular Biology, Pathobiology, and Genetics

Cyclooxygenase-2 Is a Target Gene of Rho GDP Dissociation Inhibitor ß in Breast Cancer Cells

Dario Schunke1, Paul Span3, Henrike Ronneburg1, Angela Dittmer1, Martina Vetter1, Hans-Jürgen Holzhausen2, Eva Kantelhardt1, Sylke Krenkel4, Volkmar Müller4, Fred C.G.J. Sweep3, Christoph Thomssen1 and Jürgen Dittmer1

1 Klinik für Gynäkologie and 2 Institut für Pathologie, Universität Halle, Halle (Saale), Germany; 3 Department of Chemical Endocrinology, Radboud University Nijmegen Medical Centre, Nijmegen, the Netherlands; and 4 Klinik für Gynäkologie, Universitätsklinikum Hamburg-Eppendorf, Hamburg, Germany

Requests for reprints: Jürgen Dittmer, Klinik für Gynäkologie, Universität Halle, Ernst-Grube-Str. 40, 06097 Halle (Saale), Germany. Phone: 49-345-557-1338; Fax: 49-345-557-5261; E-mail: juergen.dittmer{at}medizin.uni-halle.de.


   Abstract
Top
 Abstract
Introduction
 Materials and Methods
 Results
 Discussion
 References
 
Rho GDP dissociation inhibitor ß (Rho-GDIß), an inhibitor of Rho GTPases, is primarily expressed by hematopoietic cells but is also found in epithelial cancer cells. Recently, we have identified Rho-GDIß as a target of the transcription factor Ets1. Here, we show that, in breast cancer cells, Ets1 regulates Rho-GDIß expression and binds to the upstream region of the Rho-GDIß gene. Furthermore, in primary breast cancer, Rho-GDIß is coexpressed with Ets1. Studying the function of Rho-GDIß in breast cancer, we found that a Rho-GDIß–specific small interfering RNA increased cellular migration but also decreased the expression of cyclooxygenase-2 (Cox-2) oncogene as shown by microarray, quantitative reverse transcription-PCR, and Western blot analyses. Further studies revealed that Rho-GDIß regulates Cox-2 gene at least partly on the transcriptional level, most likely by activating nuclear factor of activated T cells 1 (NFAT-1). Vav-1, an interaction partner of Rho-GDIß, was also found to interfere with Cox-2 expression and NFAT-1 cellular distribution, suggesting a cooperative action of Rho-GDIß and Vav-1 on Cox-2 expression. To explore the importance of Rho-GDIß for the survival of breast cancer patients, two cohorts, including 263 and 117 patients, were analyzed for clinical outcome in relation to Rho-GDIß RNA and protein levels, respectively. Expression of Rho-GDIß was not associated with either disease-free or overall survival in the two patient population. Our data suggest that the expression of Rho-GDIß in breast cancer is neither beneficial nor disadvantageous to the patient. This may be the net effect of two opposing activities of Rho-GDIß, one that suppresses tumor progression by inhibiting migration and the other that stimulates it by enhancing Cox-2 expression. [Cancer Res 2007;67(22):10694–702]


   Introduction
Top
 Abstract
 Introduction
Materials and Methods
 Results
 Discussion
 References
 
The family of Rho GDP dissociation inhibitors (Rho-GDI) consist of three members: Rho-GDI{alpha}, Rho-GDIß, and Rho-GDI{gamma} (1–3). Whereas Rho-GDI{alpha} is ubiquitously expressed, the expression of Rho-GDIß and Rho-GDI{gamma} is more limited to certain cell types. Rho-GDIs are inhibitors of Rho GTPases. Rho GTPases cycle between an active, membrane-bound GTP-bound form and an inactive, cytosolic GDP-bound form. Rho-GDIs bind to and stabilize the GDP-bound form, thereby keeping the Rho protein inactive. Rho proteins, such as RhoA, Rac1, and CDC42, are important regulators of cellular migration and adhesion (4, 5). They regulate the dynamics of actin, allowing stress fibers, lamellipodia, and filopodia to be formed. They are also involved in epithelial-mesenchymal transition during cancer progression (6) and overexpressed in breast cancer (7).

Rho-GDIß is primarily expressed in hematopoietic cells (8) but is also found in epithelial cancer cells (9–11). In bladder and lung cancer, Rho-GDIß suppresses invasion and metastasis (9, 10), and in bladder cancer, Rho-GDIß is a positive prognostic factor (12). If truncated, Rho-GDIß can promote metastasis of colon cancer (13). Rho-GDIß is also part of a 76-gene signature that predicts distant metastasis in lymph node–negative breast cancer (14).

We have identified Rho-GDIß as a target gene of the transcription factor Ets1 and its regulator PKC{alpha} in breast cancer cells (15). Like Rho-GDIß, Ets1 is primarily expressed in hematopoietic cells but is also found in epithelial cancer cells (16–18), where it is associated with increased expression of matrix metalloproteinases and invasive behavior. Like Ets1, PKC{alpha} is able to promote tumor progression (19, 20). Rho-GDI{alpha} and Rho-GDIß are substrates of the protein kinase Src (21), which plays a key role in the progression of breast cancer cells (22). The observation that two tumor promoter proteins regulate Rho-GDIß prompted us to analyze the function and the prognostic value of Rho-GDIß protein in breast cancer. We identified tumor promoter protein cyclooxygenase-2 (Cox-2) as a new target of Rho-GDIß, suggesting that Rho-GDIß may stimulate tumor progression.


   Materials and Methods
Top
 Abstract
 Introduction
 Materials and Methods
Results
 Discussion
 References
 
Cell lines, small interfering RNA, and transient transfection. MDA-MB-231, MCF-7, SKBR-3 breast cancer, and Jurkat T cells were maintained in RPMI 1640 (Invitrogen) supplemented with 10% FCS (Biochrom) in the absence of antibiotics. For RNA interference studies, cells were transfected with small interfering RNA (siRNA) by electroporation as described (23), grown for 3 days, and lysed for RNA or protein analysis. The siRNAs used were purchased from MWG Biotech and are listed in Supplementary Table S1.

Quantitative reverse transcription-PCR. Preparation of RNA, cDNA synthesis, and PCR were carried out essentially as described (23). The relative RNA level of each gene of interest was calculated relative to RNA levels of the housekeeping genes glyceraldehyde-3-phosphate dehydrogenase (GAPDH) or HPRT. The primers were purchased from MWG Biotech and are listed in Supplementary Table S2.

Microarrays. In three independent transfection experiments, MDA-MB-231 cells were transfected with siRß or siLuc (control), RNA was isolated, and the six RNAs were analyzed by using Affymetrix probe type HG-U133A arrays. The analyses were carried out as described (23). Normalization of the raw data was done by using the Affymetrix MAS5.0 software, which uses the Tukey's biweight method to estimate the amount of variation in the data. For each replicate, the signal log ratio between sample (siRß) and control (siLuc) was estimated. The signal log ratio (log to the basis 2) was converted into fold induction (siRß/siLuc), and the average fold induction ± SD was calculated from the values of the three replicates.

Protein extraction and Western blot analyses. Cytosolic and nuclear protein extracts were prepared as described (23). To extract proteins from tumor tissue, 100 to 300 mg of tissue were pulverized in a Microdismembrator U (Sartorius), and the pulverized tissue was rehydrated in 200 µL TBS containing 1% Triton X-100 and rotated overnight at 4°C. The homogenate was centrifuged at 100,000 x g for 1 h at 4°C, and the supernatant was collected for further analysis. Protein amounts were measured by using the bicinchoninic acid protein assay kit (Pierce).

Western blot analysis was done as described previously (24). The Rho-GDIß protein was detected by incubating the protein blot with polyclonal rabbit anti-D4-GDI antibody (BD PharMingen) at a dilution of 1:5,000. For the detection of the Cox-2 protein, a monoclonal mouse anti-Cox-2 antibody from Cayman was used at a dilution of 1:200. Antibodies recognizing nuclear factor of activated T cells 1 (NFAT-1), Ets1, or extracellular signal-regulated kinase 1/2 (ERK1/2) were from BD Transduction Laboratories (1:2,500), Santa Cruz Biotechnology, Inc. (C20, 1:2,000), or Cell Signaling (1:1,000), respectively. GAPDH-specific (1:5,000; Ambion) and ERK1/2-specific antibodies were used to check for equal protein loading (25). As GAPDH is also abundant in the nucleus (26), we used the GAPDH-specific antibody also to control protein loading of nuclear extracts. Secondary antibodies conjugated with horseradish peroxidase specific for mouse or rabbit primary antibodies were purchased from Cell Signaling or GE-Amersham. Peroxidase activity was visualized by chemiluminescence using enhanced chemiluminescence (ECL) Plus (GE-Amersham) followed by exposure to Hyperfilm ECL (GE-Amersham).

Chromatin immunoprecipitation assay. The chromatin immunoprecipitation (ChIP) assay was done by using a ChIP kit (Lake Placid Biologicals) following the instructions of the manufacturer. After fixation of MDA-MB-231 cells with formaldehyde, chromatin was sheared by 10 cycles of sonication (10 s each) by using a Branson Sonifier 250 (duty cycle, 60%; output, 5). Between sonications, cell extracts were kept on ice for 1 min. Following immunoprecipitation by using 10 µL of anti-Ets1 antibody (C20, Santa Cruz Biotechnology) or no antibody (control), DNA was eluted, ethanol precipitated, and dissolved in 15 µL DNase-free water. Specific sequences between –121 and –197 or –775 and –878 (relative to the translational start site) of the Rho-GDIß upstream gene region were amplified by conventional PCR by mixing 0.5 µL of the DNA solution with 3.5 µL water, 2x GoTaq (Promega), and 1 µL each of a forward and the corresponding reverse primer (10 pmol/µL). The sequences of the primers used are shown in Supplementary Table S2. Conservative PCR was carried out in a Biometra TGradient PCR machine.

Cox-2 promoter assay. MDA-MB-231 cells were first electroporated with siRNA as described above. After 3 days of incubation in 60-mm dishes, the medium was removed and cells were transfected with the p274-Cox-2 promoter firefly luciferase construct (27) by using transfectin (Bio-Rad). Cox-2 promoter DNA (5 µg) and 15 µL transfectin were separately mixed with 500 µL RPMI 1640 each, and the solutions were combined and incubated at room temperature for 20 min before this mixture was added together with 2 mL of fresh medium/serum to the cells. Following incubation overnight, cells were lysed and analyzed for luciferase activity by using a Luciferase Assay System kit (Promega) and a Sirius luminometer (Berthold Detection Systems).

Immunocytochemistry/immunohistochemistry. Cells transfected with siRNA were grown on slides (SuperFrostPlus, Menzel) for 3 days, washed with PBS, dried, and fixed in 4% buffered formaldehyde for 10 min. After washing once with PBS, slides were air dried and rehydrated in PBS containing hydrogen peroxide (10:1, v/v). After incubation of cells in this solution for 30 min, they were treated with citrate buffer (29.4 g trisodium citrate dihydrate/L, pH 6.0) at 95°C for 45 min and washed briefly with PBS. After blocking with a blocking solution (Zytomed) for 10 min, slides were incubated with the anti-D4-GDI antibody (diluted 1:500) at 37°C for 1 h. Detection of the primary antibody was achieved by using a biotinylated secondary antibody/streptavidin horse peroxidase conjugate-based assay (Zytomed) and following the manufacturer's instructions. The antibody complexes were visualized by using an AEC substrate kit (Zytomed). Reaction was stopped by rinsing the slides with water. Nuclei were stained by hematoxylin.

Immunohistochemical staining of paraffin sections was carried out as follows. Sections were incubated at 60°C for 1 h and washed twice in xylene for 10 min, once in 100% ethanol for 5 min, twice in 96% ethanol for 5 min, and once in 80% and 70% ethanol 5 min each. After washing the slides in water for 15 min, slides were treated with PBS containing hydrogen peroxide and then heat treated in citrate buffer, blocked, and incubated with antibodies as described above. The strength of the immunoreaction was evaluated by determining the immunoreactive score (IRS). The IRS was calculated by multiplying staining intensity (0 = no staining, 1 = weak, 2 = moderate, 3 = strong) by the percentage of stained tumor cells (0 = no cells stained, 1 = ≤10% of cells stained, 2 = 11–50% of cells stained, 3 = 51–80% of cells stained, 4 >81% of cells stained).

Migration assays. Cell migration was studied by seeding transfected cells (2 x 105) on a tissue culture insert (ThinCerts; pore size, 8 µm; Greiner) inserted into a well of a six-well plate. After 48 h, the number of cells on the underside of the insert was determined by microscopic counting (15 fields per insert).

Breast cancer biopsies. Two hundred sixty-three tumor samples from patients with unilateral operable breast cancer who underwent resection of their primary tumor between 1987 and 1997 were selected by availability of frozen tissue in the tumor bank in the Department of Chemical Endocrinology, Radboud University Nijmegen Medical Centre (Nijmegen, the Netherlands). Coded tumor tissues were used in accordance with the Code of Conduct of the Federation of Medical Scientific Societies in the Netherlands ("Code for Proper Secondary Use of Human Tissue in the Netherlands"),5 and this study adhered to all relevant institutional and national guidelines. Macroscopically selected representative parts of the breast cancer biopsies containing tumor cells at a percentage of 35% to 90% were pulverized under liquid nitrogen and total RNA was isolated for cDNA synthesis and quantitative reverse transcription-PCR (Q-RT-PCR). For immunohistochemical analysis, 117 formalin-fixed, paraffin-embedded tumor samples from patients that were first diagnosed with invasive breast cancer in 1999 or 2000 in the Clinic for Gynecology of the University of Halle (Halle, Germany) were selected by availability. The study was approved by the Institutional Review Board.

Statistical methods. Two-sided Pearson correlation coefficient was used to analyze the relationship between the relative expression of Rho-GDIß and the relative expression of other genes in breast cancer samples. The t test was used to compare Cox-2 promoter activities in Rho-GDIß–deficient cells versus control cells. The Mann-Whitney U test was applied for comparing age, menopausal status, and estrogen and progesterone receptor status with Rho-GDIß expression. The relationship between nodal status, tumor type, and histologic grade and Rho-GDIß RNA levels was analyzed by the Kruskal-Wallis test and that between tumor size and Rho-GDIß RNA levels by the Spearman correlation test. In immunohistochemical analysis, the {chi}2 test was used to test for association between the clinicopathologic factors and Rho-GDIß immunoreactivity (IRS of 0 was coded 0; IRS > 0 was coded 1). Survival analysis was carried out with the Kaplan-Meier method. For comparison of survival curves, the log-rank test was used. All statistical analyses were done with Statistical Package for the Social Sciences 12.0 software (SPSS, Inc.). P < 0.05 was considered significant.


   Results
Top
 Abstract
 Introduction
 Materials and Methods
 Results
Discussion
 References
 
Ets1 regulates Rho-GDIß expression in breast cancer cells. We have previously shown that Rho-GDIß RNA levels are reduced when MDA-MB-231 cells were transfected with an Ets1-specific siRNA (siE1) or by a PKC{alpha}-specific siRNA (siP{alpha}; ref. 15). Here, we show that the same siRNAs also decrease the protein level of Rho-GDIß as determined by Western blot analysis (Fig. 1A ). Furthermore, a second Ets1-specific siRNA (siE1#2), which was as effective as siE1 in suppressing Ets1 expression, also decreased Rho-GDIß RNA levels, as measured by Q-RT-PCR (Fig. 1B). In another approach, we analyzed samples that were previously used to show that calphostin C, an inhibitor of PKC{alpha}, abrogates Ets1 expression for Rho-GDIß protein expression (24). We found that Rho-GDIß was eliminated along with Ets1 (data not shown). To analyze whether Ets1 directly regulates Rho-GDIß expression, we did ChIP assays. Searching for potential Ets binding sites in the first 1,000 bp upstream of the translational start site of the human Rho-GDIß gene, we found two clusters of GGAA(T) motives: one between –87 and –165 and a second one between –716 and –930 relative to the translational start site (Supplementary Fig. S1). As found with the University of California at Santa Cruz Genome Browser, these sequences overlap with genomic regions that are conserved among the human, rabbit, and dog Rho-GDIß gene. The conserved sequences include the GGAA(T) motives at positions –165, –159, –135, –764, –822, and –849. ChIP assays were done with chromatin from MDA-MB-231 cells in the presence or absence of an Ets1-specific antibody, which has already been successfully used for ChIP analyses (28, 29), followed by PCR amplification of Rho-GDIß–specific sequences between –121 and –197 and –775 and –878. We observed that the presence of the anti-Ets1 antibody slightly increased the amount of precipitated Rho-GDIß–specific DNA fragments that contained sequences between –121 and –197 (Fig. 1C). A much stronger effect of the anti-Ets1 antibody on the amount of precipitated Rho-GDIß–specific DNA was found for fragments harboring the sequence between –775 and –878. This suggests that Ets1 binds to one or more of the GGAA/T motives that are located between –716 and –930 relative to the translational start site of the Rho-GDIß gene. Collectively, these data suggest that Ets1 regulates Rho-GDIß expression in MDA-MB-231 cells.


Figure 1
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  		Figure 1. Rho-GDIß is a target gene of Ets1 in breast cancer cells. A, Western blot analysis of protein extracts from MDA-MB-231 breast cancer cells transfected with an Ets1-specific (siE1) or a PKC{alpha}-specific siRNA (siP{alpha}) or a control siRNA, siLuc (siL). To check for equal protein loading, the blot was reprobed with a GAPDH-specific antibody. Jurkat T cells were used as a positive control for Rho-GDIß. Note that Jurkat T cells also express a truncated form of Ets1, {Delta}VII-Ets1, which is missing in MDA-MB-231 cells (47). B, a second Ets1-specific siRNA (siE1#2) has the same effect as siE1 on Ets1 and Rho-GDIß RNA expression. MDA-MB-231 cells were transfected with the siRNA as indicated and analyzed for Ets1 and Rho-GDIß mRNA levels by Q-RT-PCR. Ets1 and Rho-GDIß RNA levels are given relative to the corresponding expression levels in the presence of siLuc. Student's t test showed that the Ets1 and Rho-GDIß RNA levels in the presence of siE1 and siE1#2 are significantly different to the corresponding control RNA (P < 0.005). C, ChIP assays in the presence or absence of an Ets1-specific antibody. The eluted DNAs and 1% of the input DNAs were analyzed by conventional PCR using primers designed to amplify Rho-GDIß–specific genomic sequences between –121 and –197 or –775 and –878 relative to the translational start site. PCR products were separated on a 2% agarose gel and stained by ethidium bromide. The results of two independent experiments (two different cell extracts) are shown. The data suggest that Ets1 binds to a region ~800 bp upstream of Rho-GDIß translational start site.

 
Ets1 expression correlates with Rho-GDIß expression in breast cancer cell lines and primary breast cancer. We next compared the RNA levels of Ets1 and Rho-GDIß among breast cancer cell lines (MDA-MB-231, SKBR-3, and MCF-7 cells). We found that the Rho-GDIß level was much lower in cell lines that produce less Ets1 RNA (Fig. 2A ). We extended this study to primary breast carcinomas. Again, Rho-GDIß expression correlated well with that of Ets1 (r = 0.81; P < 0.001; Fig. 2B). In contrast, no correlation was observed between Rho-GDIß RNA level and the level of either Ets2 or Esx (Fig. 2C and D), two other Ets genes commonly expressed in breast cancer cells (17, 18). These results suggest that Ets1 may be of general importance for the regulation of Rho-GDIß expression in breast cancer cells.


Figure 2
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  		Figure 2. Rho-GDIß expression correlates with Ets1 expression in breast cancer cell lines and in primary breast cancer. A, comparison of Ets1 and Rho-GDIß RNA levels in MDA-MB-231, SKBR-3, and MCF-7 breast cancer cells by Q-RT-PCR analysis. Columns, average values of three independent experiments; bars, SD. B to D, the RNA level of Rho-GDIß in primary breast cancer was compared with those of Ets1 (B), Ets2 (C), and Esx (D) by Q-RT-PCR.

 
Rho-GDIß inhibits migration of breast cancer cells. To analyze the function of Rho-GDIß in breast cancer cells, we used a Rho-GDIß–specific siRNA, siRß, which strongly down-regulated the Rho-GDIß mRNA and protein level without affecting the expression of Rho-GDI{alpha} or Rho-GDI{gamma} (Fig. 3A and B ). We also examined the effect of siRß on Rho-GDIß expression by immunocytochemistry. In the presence of siRß, overall immunoreactivity to the Rho-GDIß–specific antibody dropped and the number of strongly stained cells was reduced from approximately 15% to 8% (Fig. 3C).


Figure 3
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  		Figure 3. Rho-GDIß expression can be efficiently suppressed by RNA interference. A, Q-RT-PCR analysis of Rho-GDI{alpha}–specific, Rho-GDIß–specific, and Rho-GDI{gamma}–specific transcripts in RNA isolated from MDA-MB-231 cells grown in the presence of either Rho-GDIß–specific siRNA (siRß) or a control siRNA, siLuc. B, levels of Rho-GDIß protein in MDA-MB-231 cells treated with either siRß or siLuc as determined by Western blot analysis. C, immunocytochemical analyses of MDA-MB-231 cells grown on glass slides. The immunoreactivity of cells to the Rho-GDIß–specific antibody is lower in siRß-treated compared with siLuc-treated cells. D, Rho-GDIß–specific siRNA increases the migratory activity of MDA-MB-231 cells. Cells were transfected with either siRß, the Ets1-specific siRNA siE1, or siLuc and allowed to migrate through an 8-µm filter. Student's t test showed that, in the presence of siE1 and siRß, the migratory activity of the cells is significantly different to that under control condition (P < 0.0007).

 
As a natural inhibitor of Rho GTPases, Rho-GDIß may inhibit migration of breast cancer cells. We compared the ability of siRß-transfected and control siRNA (siLuc)-treated MDA-MB-231 cells to migrate through an 8-µm filter in a Boyden chamber. We found that siRß increased migration of MDA-MB-231 cells by ~3-fold (Fig. 3D). Interestingly, a similar effect was observed when the Ets1-specific siRNA siE1 was used. These data suggest that Rho-GDIß inhibits migration of MDA-MB-231 cells.

Rho-GDIß regulates Cox-2 expression. To explore the possibility that Rho-GDIß may affect gene expression in breast cancer, we transfected MDA-MB-231 cells with either siLuc or siRß and analyzed changes in gene expression by cDNA microarray analyses by using Affymetrix HG-U233A gene chips. The data resulting from three independent transfection experiments are deposited in Gene Expression Omnibus as series GSE8087. Genes whose expression in all three experiments was found to be different in siRß-treated versus siLuc-treated cells by at least 2-fold are listed in Supplementary Table S3 and Fig. 4A . In addition to Rho-GDIß, these group of genes included GTP-binding protein 9 (GTPBP9), Cox-2, and collagen type IV {alpha}2 (COL4A2), all of which showed reduced expression in the presence of siRß. The expression of two genes, FLJ21424 and AKAP350 (A kinase anchor protein 9), was increased in the presence of siRß. By using Q-RT-PCRs, we could verify reduced RNA levels for GTPBP9, GTPBP9 isotype 1, Cox-2, and COL4A2 in the siRß samples (Fig. 4A) but failed to show increased levels for FLJ21424 (data not shown). The failure to confirm the increased expression of FLJ21424 by Q-RT-PCR might be the consequence of the existence of a specific splicing variant, which might have been detected by the microarray analysis but might have been missed by Q-RT-PCR. To check for out-of-target effects of siRß, we rerun the transfection experiments with a second Rho-GDIß–specific siRNA (siRß2) and analyzed the RNAs by Q-RT-PCR. Although siRß2 failed to interfere with the expression of GTPBP9, GTPBP isotype 1, or COL4A2, it affected Rho-GDIß and Cox-2 expression by a similar extent as in siRß (Fig. 4A). By Western blot analysis, we could also show that knockdown of Rho-GDIß reduces Cox-2 protein levels (Fig. 4A). We next compared Rho-GDIß and Cox-2 levels in primary breast cancer by analyzing 45 breast cancer samples by Q-RT-PCR. It was found that Cox-2 levels significantly correlate with those of Rho-GDIß (Supplementary Fig. S2). Collectively, these data suggest that Cox-2 is a target gene of Rho-GDIß in MDA-MB-231 breast cancer cells.


Figure 4
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  		Figure 4. Cox-2 is a target gene of Rho-GDIß in breast cancer cells. A, MDA-MB-231 cells were treated with Rho-GDIß–specific siRNAs, siRß or siRß2, or with control siRNA (siLuc) and gene expression was analyzed by microarray (MA), Q-RT-PCR, or Western blot analysis. Microarray analyses showed that siRß reduced the expression of Rho-GDIß, GTPBP9, Cox-2, and COL4A2. This could be confirmed by Q-RT-PCR. In the case of GTPBP9, also transcripts specific for isoform 1 were analyzed. In contrast to siRß, siRß2 only decreased the expression of Cox-2 as determined by Q-RT-PCR. Columns, RNA levels of each gene in the presence of siRß or siRß2 relative to the corresponding levels in the presence of siLuc; bars, SD. Suppression of Rho-GDIß results in down-regulation of Cox-2 protein expression. Western blot analysis of cytosolic MDA-MB-231 cell protein extracts from siRß- or siLuc-treated cells by using a Cox-2–specific antibody. To check for equal protein loading, the blot was reprobed with ERK1/2- and GAPDH-specific antibodies. B, luciferase assays of extracts from MDA-MB-231 cells transfected with a –170/+104 Cox-2 promoter luciferase construct show that promoter activity is significantly reduced in the presence of siRß. *, P = 0.002, t test. RLU, relative luciferase units. C, Western blot analyses of nuclear extracts (NE) and cytosolic extracts (CE) of siLuc-, siRß-, and siV#1-treated MDA-MB-231 cells show that NFAT-1–specific bands II and III disappear in nuclear extracts from cells transfected with siRß and siV#1. D, suppression of Vav-1 expression by a Vav-1–specific siRNA, siV#1 or siV#2, results in down-regulation of Cox-2 RNA levels as analyzed by Q-RT-PCR. A, B, and D, columns, average value of at least three independent experiments; bars, SD.

 
To analyze the mechanism(s) underlying Rho-GDIß–depending Cox-2 regulation, we did promoter assays with a p274-Cox-2 luciferase promoter construct containing the sequences between –170 and +104 (relative to the transcriptional start site) of the human Cox-2 gene (27). The activities of this promoter in siRß- and siLuc-treated MDA-MB-231 cells were compared. In the presence of siRß, Cox-2 promoter activity was significantly lower (Fig. 4B), suggesting that Rho-GDIß at least partly regulates Cox-2 on the transcriptional level. No effect of siRß was observed on a control promoter (data not shown). One of the major regulators of the –170/+104 Cox-2 promoter fragment in breast cancer cells is the transcription factor NFAT-1 (30). NFAT activity depends on dephosphorylation (31). Dephosphorylation results in masking of a nuclear export signaling sequence within the NFAT-1 protein, allowing this protein to stay in the nucleus. We investigated the presence of NFAT-1 protein in nuclear and cytosolic extracts from siRß- and siLuc-treated MDA-MB-231 cells. Three different NFAT-1–specific bands, I, II, and III, representing different phosphorylated species (31, 32), were observed in nuclear as well as cytosolic extracts from siLuc-treated control cells (Fig. 4C). Of these bands, bands II and III, which most likely represent less phosphorylated forms, disappeared when nuclear extracts, but not cytosolic extracts, from siRß-treated cells were analyzed. These data suggest that less phosphorylated forms of NFAT-1 are excluded from the nucleus when Rho-GDIß is suppressed. Reprobing with anti-Rho-GDIß antibody confirmed that Rho-GDIß was strongly suppressed in siRß-treated cells. To show that the nuclear extract is enriched with nuclear proteins, we reprobed the blot with an antibody specific to Ets1. This nuclear protein was more abundant in the nuclear extract than in the cytosolic extract. In contrast, cytoplasmic Rho-GDIß was more prominent in the cytosolic extract.

Interestingly, Rho-GDIß is able to cooperate with another hematopoietic protein, the Rho GTPase guanine nucleotide exchange factor Vav-1, which leads to activation of NFAT in Jurkat T cells (33). In the same cells, NFAT is a major regulator of the –170/+104 Cox-2 promoter fragment (27). To analyze the importance of Vav-1 for Cox-2 expression in MDA-MB-231 cells, we suppressed Vav-1 expression in these breast cancer cells by Vav-1–specific siRNAs siV#1 and siV#2. Both siRNAs were equally effective in reducing Vav-1 expression and also able to decrease Cox-2 expression (Fig. 4D). Furthermore, like siRß, siV#1 prevented the accumulation of NFAT protein species II and III in the nucleus (Fig. 4C). Importantly, siV#1 did not change Rho-GDIß protein levels, indicating that the effect of siV#1 on NFAT and Cox-2 was not the consequence of reduced Rho-GDIß expression levels. We also found that, in primary breast cancer, Vav-1 expression significantly correlates with Rho-GDIß expression (Supplementary Fig. S2). These data warrant a model by which Rho-GDIß and Vav-1 cooperate in breast cancer cells to induce nuclear translocation of specific NFAT-1 forms to activate Cox-2 gene transcription.

Rho-GDIß mRNA levels do not correlate with prognosis. To explore the importance of tumoral Rho-GDIß expression for the survival of breast cancer patients, we analyzed a cohort of 259 patients with invasive breast cancer for Rho-GDIß RNA expression in fresh-frozen breast cancer samples and compared these RNA levels with clinicopathologic data and with the patients' survival data. Although we found that Rho-GDIß RNA levels were significantly lower in tumors that grew larger (Supplementary Table S4), Kaplan-Meier survival curves showed that the likelihood of a patient to develop a relapse was the same, irrespective of whether the breast cancer produced Rho-GDIß at higher or lower levels (Fig. 5 ).


Figure 5
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  		Figure 5. The outcome of breast cancer patients is independent of the Rho-GDIß RNA level in the tumor. Kaplan-Meier curves for disease-free and overall survival for 259 patients with invasive breast cancer expressing Rho-GDIß either at low or high RNA levels as determined by Q-RT-PCR. Low or high levels of Rho-GDIß RNA were defined as to be the RNA levels that were lower or higher than the median Rho-GDIß RNA level, respectively. The log-rank test P values for the Rho-GDIß–high level compared with the Rho-GDIß–low level were 0.879 for disease-free survival and 0.947 for overall survival.

 
Rho-GDIß protein expression does not have an effect on patient's survival. We next analyzed Rho-GDIß protein levels in primary breast cancers. We prepared protein extracts from 87 invasive breast carcinomas and analyzed them by Western blot analysis for the Rho-GDIß protein. Forty-three percent of the carcinoma samples were found to express Rho-GDIß protein at the same or at a higher level as MDA-MB-231 cells (Fig. 6A ). Rho-GDIß protein expression in primary breast cancer was also studied by immunohistochemistry. Rho-GDIß–specific staining was observed in the cytoplasm of tumor as well as of stromal cells. An analysis of a total of 117 primary breast cancer samples revealed that in 74 (63%) no Rho-GDIß–specific immunoreactivity (IRS = 0) in the tumor cells could be observed. Of the remaining 37% breast cancer samples, 13 (11%) expressed Rho-GDIß at low levels (IRS 2 or 3), 11 (9.4%) at medium levels (IRS 4 or 6), and 19 (16.2%) at high levels (IRS > 8). For the statistical analysis, tumors showing an IRS of 0 were defined as Rho-GDIß–negative breast cancers and those with IRS > 0 as Rho-GDIß–positive cancers. When we compared the Rho-GDIß protein expression pattern with the classic clinicopathologic data, we could not find that the presence or absence of Rho-GDIß coincided with a particular status of one of the clinicopathologic factors (Supplementary Table S5). Survival analyses using Kaplan-Meier statistics showed no significant differences in overall survival (P = 0.534) between patients with Rho-GDIß–positive and Rho-GDIß–negative tumors (Fig. 6C, right). In disease-free survival, there was a tendency that patients with Rho-GDIß–positive tumors may have a better prognosis (Fig. 6C, left), but this tendency was not significant (P = 0.149). It was still not significant (P = 0.069 or 0.057) when the Rho-GDIß–negative group also included those breast cancer samples that showed Rho-GDIß IRS values of 2 to 3 or IRS values of 2 to 4, respectively. These data agree with the results obtained by the analysis of the Rho-GDIß RNA expression showing that Rho-GDIß has no prognostic value in breast cancer.


Figure 6
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  		Figure 6. A, Rho-GDIß protein is expressed in ~40% of breast cancer specimen tested. Western blot analysis of proteins isolated from representative fresh-frozen breast cancer samples. B, immunohistochemical analysis of a paraffin section of a Rho-GDIß–positive (left) and of a Rho-GDIß–negative (right) invasive breast cancer specimen by using a Rho-GDIß–specific antibody. C, the outcome of breast cancer patients is independent of the Rho-GDIß protein level in the tumor cells. Kaplan-Meier curves for disease-free and overall survival for 117 patients with invasive breast cancer expressing Rho-GDIß protein at either detectable level (IRS > 0, Rho-GDIß positive) or undetectable level (IRS = 0, Rho-GDIß negative) as determined by immunohistochemistry. The log-rank test P values for Rho-GDIß–positive breast tumors compared with the Rho-GDIß–negative breast tumors were 0.149 for disease-free survival and 0.534 for overall survival.

 

   Discussion
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
References
 
Our data suggest that Rho-GDIß protein is expressed in ~40% of all breast cancers. As an inhibitor of Rho GTPases, Rho-GDIß may simply act as an antimigratory protein as shown with T24 bladder cancer cells (9). In fact, we found that Rho-GDIß inhibits migration of MDA-MB-231 cells. Exerting such function, Rho-GDIß may be a tumor-suppressing protein. However, the clinical outcome of breast cancer patients is not improved when breast cancer cells express Rho-GDIß. Interestingly, Rho-GDIß is coexpressed with the transcription factor Ets1, a tumor-promoting protein (16). RNA interference or other means to suppress Ets1 expression as well as ChIP analyses revealed that this coexpression is not a coincidence but the consequence of a regulatory action of Ets1 on Rho-GDIß. Ets1-specific and Rho-GDIß–specific siRNA had also similar positive effects on cellular migration. This effect of Ets1-specific siRNA was unexpected as Ets1 has been previously reported to promote migration (34, 35). The discrepancy may be explained by the use of different inhibitors, siRNA versus Ets1-DNA binding domain. The Ets1-DNA binding domain, which acts as a transdominant-negative form of Ets1, may also affect the activity of other Ets proteins (36). Alternatively, the effect of Ets1 on migration may be cell type specific. Depending on which other migration-relevant genes Ets1 may target in a given cell, migration may be increased or decreased by Ets1.

The regulation of Rho-GDIß by the oncogene Ets1 may imply that Rho-GDIß may also have tumor-promoting functions. In support of this notion, Rho-GDIß has been reported to regulate the expression of integrin ß1, an integrin that plays a role in breast cancer progression (37). In our study, we identified Cox-2 as a target of Rho-GDIß. There is strong evidence that Cox-2 promotes tumor progression. Elevated Cox-2 protein levels are linked to decreased survival of breast cancer patients (38). In addition, Cox-2 stimulates metastasis of breast cancer to bone and lung (39, 40) and enhances invasion of breast cancer cells (30, 41). Our data suggest that Rho-GDIß regulates the expression of Cox-2 in breast cancer cells at least partly on the transcriptional level. We present evidence that Rho-GDIß targets NFAT-1. As NFAT is a major regulator of Cox-2 gene expression in breast cancer and T-leukemia cells (27, 30), NFAT is likely to mediate the effect of Rho-GDIß on Cox-2 transcription. We could further show that another Rho GTPase-regulating protein, Vav-1, regulates Cox-2 gene expression and also targets NFAT-1 in MDA-MB-231 cells. Vav-1 has been reported to bind to NFAT (42) and to cooperate with Rho-GDIß to activate NFAT in T cells (33). Like Cox-2, Vav-1 and NFAT-1 have been associated with cancer progression. Proto-oncogene Vav-1 has been shown to regulate proliferation of pancreas cancer cells and to contribute to unfavorable prognosis (43), whereas NFAT has been shown to increase the invasiveness of breast and colon cancer cells (32). Interestingly, like Rho-GDIß and Ets1, Vav-1 is primarily expressed in hematopoietic cells (44). Hence, it is tempting to hypothesize that breast cancer cells have adopted a mechanism allowing the expression and coordinate interaction of these hematopoietic factors to promote tumor progression. Besides Rho-GDIß and Vav-1, other proteins, including {alpha}6ß4 integrin and AKT, have been found to regulate NFAT-1 activity in breast cancer cells (32, 45). In addition to NFAT-1, transcription factors, such nuclear factor-{kappa}B, CAAT/enhancer binding protein {delta}, and transforming growth factor-ß–regulated Smads, have also been reported to activate Cox-2 transcription (39, 46), suggesting a complex interaction network that controls Cox-2 activity.

In summary, the stimulatory effect of Rho-GDIß on the Cox-2 oncogene on the one hand and its antimigratory activity on the other hand may even out and explain why Rho-GDIß does not have an effect on the clinical outcome of breast cancer patients. However, in individual tumors, the one or the other function of Rho-GDIß may prevail and Rho-GDIß expression may be either of advantage or disadvantage for the breast cancer patient.


   Acknowledgments
 
Grant support: Bundesministerium für Bildung und Forschung grant NBL3 FKZ13/11.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

We thank Katayoun Sheikheleslamy, Gareth Palidwor, and Pearl Campbell for doing the DNA microarray experiments and computational analyses and Miguel A. Íñiguez for providing us with the p274-Cox-2 promoter construct.


   Footnotes
 
Note: Supplementary data for this article are available at Cancer Research Online (http://cancerres.aacrjournals.org/).

5 http://www.fmwv.nl Back

Received 5/ 3/07. Revised 9/ 5/07. Accepted 9/19/07.


   References
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 Introduction
 Materials and Methods
 Results
 Discussion
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