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. 2012 Apr 13;3(3):345–356. doi: 10.18632/oncotarget.457

Drug-Targeted Inhibition of Peroxisome Proliferator-Activated Receptorγ Enhances the Chemopreventive Effect of Anti-Estrogen

Hongyan Yuan 1, Levy Kopelovich 2, Yuzhi Yin 1,3, Jin Lu 1, Robert I Glazer 1
PMCID: PMC3359890  PMID: 22538444

Abstract

The peroxisome proliferator-activated receptorγ (PPARγ) is a key regulator of metabolism, proliferation, inflammation and differentiation, and upregulates tumor suppressor genes, such as PTEN, BRCA1 and PPARγ itself. Examination of mammary carcinogenesis in transgenic mice expressing the dominant-negative Pax8PPARγ fusion protein revealed that tumors were estrogen receptorα (ER)-positive and sensitive to the ER antagonist, fulvestrant. Here we evaluated whether administration of an irreversible PPARγ inhibitor in vivo could similarly induce ER expression in otherwise ER-negative mammary tumors following induction of carcinogenesis, and sensitize them to the antitumor effects of fulvestrant. In addition, we wished to determine whether the effect of GW9662 was associated with a PPAR-selective gene expression profile. Mammary carcinogenesis was induced in wild-type FVB mice by treatment with medroxyprogesterone and dimethylbenz(a)anthracene (DMBA) that were subsequently maintained on a diet supplemented with 0.1% GW9662, and tumorigenesis and gene expression profiling of the resulting tumors were determined. Administration of GW9962 resulted in ER+ tumors that were highly sensitive to fulvestrant. Tumors from GW9662-treated animals exhibited reduced expression of a metabolic gene profile indicative of PPARγ inhibition, including PPARγ itself. Additionally, GW9662 upregulated the expression of several genes associated with the transcription, processing, splicing and translation of RNA. This study is the first to show that an irreversible PPARγ inhibitor can mimic a dominant-negative PPARγ transgene to elicit the development of ER-responsive tumors. These findings suggest that it may be possible to pharmacologically influence the responsiveness of tumors to anti-estrogen therapy.

Keywords: PPARγ, ERα, fulvestrant, GW9662

INTRODUCTION

The peroxisome proliferator-activated receptor (PPAR) nuclear receptor subfamily regulates a number of metabolic processes, including fatty acid β-oxidation, glucose utilization, cholesterol transport, energy balance and adipocyte differentiation [1-4]. PPARs also play important roles in modulating inflammation, proliferation, angiogenesis and neoplasia [5-8]. PPARs function as heterodimeric partners with RXR, and require high-affinity binding of PPAR isotype-specific ligands to engage transcription. Of the three subtypes, PPARγ is the major species expressed in the mammary gland and in primary and metastatic breast cancer and breast cancer cell lines [5].

PPARγ and PPARδ modulate cell fate in the mammary gland [6, 9, 10], suggesting that PPAR agonists or antagonists may have the potential to regulate differentiation and hence tumor progression. PPARγ agonists are potent chemopreventive agents in mammary carcinogenesis [11], which is consistent with the enhancement of mammary tumorigenesis by PPARγ heterozygosity [12]. In a large percentage of follicular thyroid cancers, PPARγ exists as the dominant-negative fusion protein, Pax8-PPARγ, associated with the t(2;3)(q13;p25) translocation [13]. Pax8PPARγ potently blocks PPARγ function [13, 14], rather than merely serving as a low affinity receptor that can be activated at high ligand concentrations [15]. Importantly, the irreversible PPARγ ‘suicide’ inhibitor, GW9662 [16], mimics the growth promoting effects of Pax8PPARγ in thyroid cells [17], suggesting that selective pharmacological manipulation of PPARγ is feasible.

Although many studies have addressed the interactions between different nuclear receptor subfamilies, an area of relevance to breast cancer is the inhibitory effect of PPARγ on ERα (ER) promoter activation through its interaction with ER response elements [18]. Conversely, ER may bind to PPARγ response elements (PPREs) to inhibit PPAR-dependent transcription [19]. The ER and PPARγ pathways produce opposite effects on PI3K/AKT signaling, accounting in part, for the divergent responses produced by their cognate ligands in estrogen-dependent human breast cancer cells [19]. These findings suggest that suppression of PPARγ may upregulate ER expression in tumors to allow the implementation of anti-estrogen therapy. As a proof of principle, this was demonstrated by the effectiveness of the ER antagonist, fulvestrant, in preventing mammary tumorigenesis in MMTV-Pax8PPARγ mice, in which tumors normally present with a more aggressive progenitor cell phenotype [10]. Therefore, from a chemoprevention perspective, it would be important to be able to mimic the MMTV-Pax8PPARγ transgene pharmacologically by administering a PPARγ antagonist to increase the percentage of ER+ tumors and render them amenable to anti-estrogen therapy. This approach would be dependent on whether a PPAR antagonist could be developed with favorable specificity and pharmacokinetic properties to achieve selective and sustained inhibition of PPARγ. Examples of PPARγ antagonists are the suicide inhibitors, GW9662 (2-chloro-5-nitro-N-phenylbenzamide) [16], 2-bromo-5-nitro-N-phenylbenzamide [20] and the structurally similar T0070907 [21], as well as the partial PPARγ agonists, GW0072 [22] and L-764406 [23]. Although, GW9662 and T0070907 have also been reported to produce off-target effects in vitro [24-26], their in vivo selectivity has yet to be demonstrated. In this report, we show that GW9662 when administered continuously in the diet beginning at the onset of mammary carcinogenesis induces ER-responsive tumors susceptible to fulvestrant therapy. Furthermore, GW9662 inhibited a PPARγ-dependent metabolic gene expression signature, including PPARγ itself. These results are the first to demonstrate that GW9662 is at least in part PPARγ-selective, and can induce sensitivity to anti-estrogen therapy.

RESULTS

GW9662 induces sensitivity to antiestrogen therapy

To evaluate the chemopreventive effect of GW9662 on mammary tumor development, carcinogenesis was induced in FVB mice by progestin and DMBA treatment. Animals were maintained on either a control diet or a diet supplemented with 0.1% GW9662 beginning one day after the last dose of DMBA, and both groups were administered either vehicle or 250 mg/kg fulvestrant by subcutaneous injection every other week (Figure 1). Animals maintained on GW9662 alone exhibited a modest reduction in survival (Figure 1A) similar to what was observed previously in MMTV-Pax8PPARγ transgenic mice [10], but not a reduction in the total number of tumors (Figure 1B). While no significant difference in survival was noted for fulvestrant-treated control mice, a marked increase in survival (Figure 1A) and a reduction in tumor number (Figure 1B) were observed in animals maintained on GW9662 and treated with fulvestrant. Consistent with these findings was an increase in ER expression in tumors from GW9662-treated mice in comparison to animals maintained on the control diet as determined by immunohistochemical (Figure 2A) and western analyses (Figure 2B). Increased ER, as well as PR expression, was accompanied by an increase in Esr1 and Pgr mRNA levels (Figure 3A). GW9662 treatment also resulted in a reduction of PPARγ protein (Figure 2B) and mRNA (Figure 3A). Histological evaluation of the tumors indicated that GW9662, but not fulvestrant, produced a significant increase in the percentage of adenocarcinomas (P=0.0333) (Table S1).

Figure 1. GW9662 enhances the sensitivity of mammary tumors to fulvestrant.

Figure 1

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(A) Survival curves of mice administered a control diet, a diet supplemented with 0.1% (w/w) GW9662, 250 mg/kg fulvestrant administered s.c. every other week or the combination of the GW9662 diet and fulvestrant. GW9662 treatment alone produced a significant reduction in survival vs. control mice (P=0.0382), but not vs. fulvestrant treatment (P=0.0759); fulvestrant treatment alone did not significantly affect survival (P=0.7223). GW9662 and fulvestrant treatment produced a significant increase in survival vs. fulvestrant (P=0.0008) or GW9662 (P=0.0001) treatment alone. Each group contained 10 mice. Statistical significance was determined by the log rank test. (B) Tumor formation in the experimental groups indicated in (A). Neither GW9662 (P=0.3942) nor fulvestrant (P=0.3339) treatment alone significantly affected tumor number vs. control mice. GW9662 and fulvestrant treatment produced a significant reduction in tumor number vs. either fulvestrant (P=0.0001) or GW9662 (P=0.0004) treatment alone. Each group contained 10 mice. Statistical significance was determined by the two-tailed Student's t test.

Figure 2. ER expression in adenocarcinomas from control and GW9662 mice.

Figure 2

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(A) Immunohistochemical detection of ER expression. Two representative tumors from control and GW9662-treated mice are shown. ER expression was increased following GW9662 treatment. Magnification 200X. (B) Western analysis of ER and PPARγ expression. Two representative tumors from control and GW9662-treated mice are shown. ER expression was increased, and PPARγ expression reduced following GW9662 treatment. The bar graph represents quantitation of the western blot normalized to actin expression.

Figure 3. (A) qRT-PCR analysis of gene expression in adenocarcinomas from control and GW9662-treated mice.

Figure 3

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Gene selection was based on the data in Table 1. (B) Heat map of changes in gene expression based on the data in Table S2.

Gene expression analysis

Gene microarray analysis of tumors from control and GW9662-treated animals indicated that 356 genes were differentially affected by GW9662 treatment (Figure 3B). Of the 303 genes downregulated by GW9662, 24% were metabolic genes, and 55% of which contain PPREs (Table 1). In addition, there were 10 genes regulated by transcription factors Cebpa and Pouf1, which are PPAR-regulated. Overall, 67% of the metabolic genes were directly or indirectly regulated by GW9662. Gene ontology of the differentially expressed genes (Table S1) indicated that the largest percentage were associated with transport, glucose and lipid metabolism, and developmental processes (Table 2). Pathway linkage analysis revealed that most of the genes whose expression was downregulated by GW9662 were linked directly or indirectly to PPARγ (Figure 4), whereas, those genes whose expression was increased by GW9662 were connected to Mapk3, Mapk8 and Akt signaling (Figure S1). Interestingly, the majority of the genes upregulated by GW9662 were associated with transcription, splicing, processing and translation of RNA (Table S2). In particular, RBM39, whose expression was increased 6.6-fold by GW9662, was recently reported to be increased in ER-dependent mammary tumors developing in caveolin-1 knockout mice [27].

Table 1. Metabolic genes downregulated by GW9662.

Shown are genes whose signal was >300 in either group and were changed [3] 2.5-fold in GW9662-treated animals vs. control. The full list of changes in gene expression are presented in Table S2. Gene symbols in bold contain PPREs.

Raw Value
Gene symbol Gene Title Fold Change WT GW9662
Ces3 carboxylesterase 3 −105.7 2733 25
Gys2 glycogen synthase 2 −74.7 558 7
Lep leptin −74.7 1231 16
Aqp7 aquaporin 7 −55.6 3523 63
Pnpla3 patatin-like phospholipase domain containing 3 −53.9 1301 24
Cox8b cytochrome c oxidase, subunit VIIIb −51.0 1324 26
Cyp2e1 cytochrome P450 family 2, subfamily e, polypeptide 1 −44.3 5209 118
Pck1 phosphoenolpyruvate carboxykinase 1, cytosolic −43.9 3071 70
Retn resistin −35.7 10637 298
Rbp4 retinol binding protein 4, plasma −33.9 3187 94
Lao1 L-amino acid oxidase 1 −30.2 3092 103
Fabp3 fatty acid binding protein 3, muscle and heart −27.0 886 33
Cd36 CD36 antigen −22.5 6726 306
Car4 carbonic anhydrase 4 −22.3 982 44
Fabp4 fatty acid binding protein 4, adipocyte −21.7 7777 3543
Adipoq adiponectin, C1Q and collagen domain containing −21.6 10299 522
Adig adipogenin −20.8 1676 85
Acsl1 acyl-CoA synthetase long-chain family member 1 −18.6 3172 374
Lipe lipase, hormone sensitive −16.2 1329 82
Hsd11b1 hydroxysteroid-11-beta dehydrogenase 1 −15.7 28.15 1.79
Pparg peroxisome proliferator activated receptor gamma −13.9 967 69
Pc pyruvate carboxylase −13.1 1588 95
Dgat2 diacylglycerol O-acyltransferase 2 −12.4 4000 521
Cel carboxyl esterase lipase −12.1 955 79
Acacb acetyl-Coenzyme A carboxylase beta −11.5 530 46
Acaa1b acetyl-Coenzyme A acyltransferase 1B −10.6 696 66
Ephx2 epoxide hydrolase 2, cytoplasmic −10.0 1402 140
Lpl lipoprotein lipase −9.6 6823 713
Pgam2 phosphoglycerate mutase 2 −8.9 628 70
Cox6a2 cytochrome c oxidase, subunit VI a, polypeptide 2 −8.1 405 50
Fasn fatty acid synthase −7.3 11558 1579
Ptger3 prostaglandin E receptor 3 (subtype EP3) −7.1 1106 157
Sorbs1 sorbin and SH3 domain containing 1 −6.5 2532 581
Pygl liver glycogen phosphorylase −6.4 1600 250
Scd1 stearoyl-Coenzyme A desaturase 1 −6.4 7943 2026
Chpt1 choline phosphotransferase 1 −5.8 1658 327
Slc1a5 solute carrier family 1 (neutral amino acid transporter), member 5 −5.6 2664 476
Acss2 acyl-CoA synthetase short-chain family member 2 −5.5 969 160
Mgll monoglyceride lipase −5.5 3443 632
Pnpla2 patatin-like phospholipase domain containing 2 −5.1 4552 890
Eno3 enolase 3, beta muscle −4.9 672 136
Cyp2f2 cytochrome P450 family 2, subfamily f, polypeptide 2 −4.9 550 112
Lpin1 lipin 1 −4.8 1167 268
Ido1 indoleamine 2,3-dioxygenase 1 −4.8 406 85
Sod3 superoxide dismutase 3, extracellular −4.7 678 145
Cyp4b1 cytochrome P450 family 4, subfamily b, polypeptide 1 −4.6 1286 283
Igf1 insulin-like growth factor 1 −4.3 558 153
Aacs acetoacetyl-CoA synthetase −4.1 1176 320
Acox1 acyl-Coenzyme A oxidase 1, palmitoyl −4.1 920 225
Xdh xanthine dehydrogenase −3.9 1400 362
Gpd1 glycerol-3-phosphate dehydrogenase 1 (soluble) −3.6 1710 283
Gpt2 glutamic pyruvate transaminase (alanine aminotransferase) 2 −3.6 1338 438
Gpt glutamic pyruvic transaminase, soluble −3.6 577 159
Abca8a ATP-binding cassette, sub-family A (ABC1), member 8a −3.5 1675 478
Me1 malic enzyme 1, NADP(+)-dependent, cytosolic −3.4 2810 900
Aqp1 aquaporin 1 −3.4 2841 848
Retsat retinol saturase (all trans retinol 13,14 reductase) −3.3 488 146
Slc27a1 solute carrier family 27 (fatty acid transporter), member 1 −3.2 522 163
Lipa lysosomal acid lipase A −3.2 374 117
Fads3 fatty acid desaturase 3 −3.2 1545 485
Alox12e arachidonate lipoxygenase, epidermal −3.1 818 262
Elovl6 ELOVL family member 6, elongation of long chain fatty acids (yeast) −3.1 1088 320
Gpam glycerol-3-phosphate acyltransferase, mitochondrial −3.0 2818 947
Nr1h3 nuclear receptor subfamily 1, group H, member 3 (LXR) −3.0 1137 379
Acly ATP citrate lyase −2.9 993 343
Pik3r1 phosphatidylinositol 3-kinase, regulatory subunit, polypeptide 1 (p85 alpha) −2.9 558 192
Rbp7 retinol binding protein 7, cellular −2.9 1212 418
Slc2a4 solute carrier family 2 (faciltated glucose transporter), member 4 −3.2 522 163
Crat carnitine acetyltransferase −2.8 537 191
Slc2a4 solute carrier family 2 (facilitated glucose transporter), member 4 −2.8 1021 364
Sord sorbitol dehydrogenase −2.8 700 250
Ehhadh enoyl-Coenzyme A, hydratase/3-hydroxyacyl Coenzyme A dehydrogenase −2.7 341 126
Hk2 hexokinase 2 −2.7 1447 534
Lpgat1 lysophosphatidylglycerol acyltransferase 1 −2.7 399 150
Gbe1 glucan (1,4-alpha-)branching enzyme −2.7 723 267
Apod apolipoprotein D −2.6 4011 1526
Gatm glycine amidinotransferase (L-arginine:glycine amidinotransferase −2.6 400 152
Ltc4s leukotriene C4 synthase −2.6 467 179
Pfkfb1 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 1 −2.6 320 124
Plin2 perilipin 2 −2.5 6773 2671
Cebpa CCAAT/enhancer binding protein (C/EBP), alpha −2.5 1819 734
Dgat1 diacylglycerol O-acyltransferase 1 −2.5 1065 425
Ptgs1 prostaglandin-endoperoxide synthase 1 −2.5 362 145
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Table 2. Gene ontology of differentially expressed genes affected by GW9662.

Shown are enrichment data with P<0.05 by Fisher's Exact test.

Name Total Entities Overlap Overlapping Entities p-value
DOWNREGULATED:
lipid metabolism 342 23 CHPT1,CD36,LEP,LPL,LIPE,APOD,NR1H3,SLC27A1,LIPA,ACSL1,HSD11B1,DGAT2,CRAT,ACLY,LPIN1,ACOX1,EHHADH,PNPLA2,PCK1,PNPLA3,MGLL,AACS,FADS3 1.92E-26
metabolism 858 21 LPGAT1,FASN,LIPE,ACACB,SLC27A1,EPHX2,ACSL1,GPAM,HSD11B1,ME1,PC,ACLY,PFKFB1,ACOX1,EHHADH,PNPLA2,GPD1,PNPLA3,ACSS2,PGAM2,AACS 3.71E-15
transport 1807 15 AQP1,CD36,APOD,SLC2A4,SLC27A1,FABP4,FABP3,CRAT,SORBS1,SLC1A5,AQP7,RBP4,CRABP1,RBP7,FADS3 6.01E-05
oxidation reduction 702 14 CYP2E1,PTGS1,SOD3,XDH,FASN,HSD11B1,ME1,ACOX1,EHHADH,GPD1,CYP4B1,SORD,RETSAT,FADS3 3.58E-09
fatty acid metabolism 110 12 CD36,PPARG,SLC27A1,LIPA,FABP4,ACSL1,GPAM,FABP3,CRAT,ACOX1,EHHADH,AACS 1.21E-16
response to drug 295 10 ADIPOQ,PPARG,LIPE,ACACB,FABP4,ACSL1,AQP7,SORD,ENO3,AACS 5.40E-09
response to insulin 37 10 LEP,RETN,PIK3R1,PFKFB1,PCK1,RBP4,PPARG,SORBS1,LPIN1,NRIH3 5.81E-10
fat cell differentiation 29 9 ADIG,CEBPA,ADIPOQ,PPARG,SLC2A4,FABP4,IGF1,AACS,RETN 1.21E-10
lipid biosynthesis 115 8 PTGS1,FASN,DGAT2,PC,ACLY,ELOVL6,ACSS2,FADS3 7.24E-10
gluconeogenesis 33 7 GPT,PC,PFKFB1,GPD1,PCK1,RBP4,PGAM2 2.60E-12
generation of precursor metabolites & energy 63 7 CEBPA,ADIPOQ,GYS2,ACOX1,AQP7,GBE1,COX6A2 3.17E-10
response to glucocorticoids 95 6 CEBPA,ADIPOQ,IGF1,FABP4,PIK3R1,PFKFB1 1.93E-07
response to nutrients 117 6 CEBPA,ADIPOQ,PPARG,ACSL1,GATM,AACS 6.62E-07
lipid catabolism 113 6 CEL,LPL,LIPE,LIPA,PNPLA2,PNPLA3 5.40E-07
glucose homeostasis 50 6 ADIPOQ,PPARG,SLC2A4,PCK1,RBP4,PYGL 3.87E-09
spermatogenesis 353 5 ADIG,ACOX1,AQP7,RBP4,PGAM2 2.38E-03
carbohydrate metabolism 296 5 SLC2A4,ME1,GPD1,PYGL,GBE1 1.10E-03
fatty acid biosynthesis 78 5 PTGS1,FASN,ACACB,ELOVL6,FADS3 1.98E-06
triglyceride biosynthesis 11 5 LPL,GPAM,DGAT1,DGAT2,PNPLA3 4.97E-11
glucose metabolism 115 5 ADIPOQ,LEP,HK2,PIK3R1,SORD 1.33E-05
inflammatory response 293 4 PPARG,LIPA,EPHX2,MGLL 7.45E-03
lung development 106 4 CEBPA,LIPA,HSD11B1,RBP4 1.78E-04
organ regeneration 49 4 CEBPA,PPARG,LPIN1,PFKFB1 8.49E-06
triglyceride catabolism 13 4 LPL,LIPE,PNPLA2,PNPLA3 3.08E-08
fatty acid beta-oxidation 32 4 ADIPOQ,FABP3,ACOX1,EHHADH 1.49E-06
glycolysis 68 4 HK2,PFKFB1,ENO3,PGAM2 3.14E-05
regulation of transcription 159 4 CEBPA,NR1H3,FABP4,PPARG 8.53E-03
response to ethanol 83 3 ADIPOQ,RBP4,AACS 1.37E-03
long-chain fatty acid transport 12 3 CD36,PPARG,FABP3 3.76E-06
aging 101 3 PTGS1,PIK3R1,ENO3 2.41E-03
fatty acid oxidation 18 3 CD36,ADIPOQ,PPARG 1.38E-05
glycogen metabolism 41 3 GYS2,PYGL,GBE1 1.72E-04
phospholipid biosynthesis 49 3 LPGAT1,CHPT1,GPAM 2.94E-04
regulation of cell proliferation 135 3 PTGS1,CEBPA,IGF1 5.44E-03
negative regulation of foam cell differentiation 10 3 ADIPOQ,PPARG,NR1H3 2.06E-06
UPREGULATED:
regulation of transcription 2501 9 ZBTB16,MAPK8,RHOX5,BRWD1,ESRRB,RBM39,TARDBP,NFIB,THRAP3 2.24E-02
RNA splicing 238 5 HNRNPA1,PABPC1,RBM39,TARDBP,RBMX 2.13E-05
mRNA processing 277 5 PABPN1,HNRNPA1,PABPC1,RBM39,TARDBP 4.40E-05
cell proliferation 324 4 PTHLH,EREG,ZBTB16,NFIB 1.13E-03
central nervous system development 140 3 ZBTB16,PCP4,NPTX1 1.04E-03
translational elongation 161 3 RPS25,RPS24,RPL41 1.55E-03
cell-cell signaling 275 3 CALCA,PTHLH,EREG 6.96E-03
apoptosis 550 3 ZBTB16,SLC5A8,NISCH 4.29E-02
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Figure 4. GW9662 signaling pathways in tumors from control and GW9662-treated animals.

Figure 4

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Pathways are based on the expression of genes that were reduced ≥2.5-fold by GW9662 in Table S1. Metabolic signaling pathways associated with genes that were downregulated by GW9662.

DISCUSSION

The present study was designed to determine if pharmacological inhibition of PPARγ could sensitize mammary tumor growth to antiestrogen therapy. This concept was based on our previous finding that induction of mammary carcinogenesis in transgenic mice expressing the dominant-negative Pax8PPARγ fusion protein resulted in increased ER expression and responsiveness to the ER antagonist, fulvestrant [10]. MMTV-Pax8PPARγ transgenic mice represent a rare mouse model in which the mammary gland exhibits a progenitor cell phenotype that results in the preferential development of ER+ rather than ER− tumors of mixed lineage following progestin/DMBA treatment [10, 28]. A similar mammary tumor phenotype developed in caveolin-1 knockout mice that was also associated with the induction of several stem/progenitor cell markers, including RBM39 [27], as found in the present study. RBM39 functions primarily in RNA splicing and may also be a putative partner of the co-activator Ncoa6/PRIP [29]. Thus, one unexpected finding was that GW9662 upregulated a number of genes associated with transcription, processing, splicing and translation that likely contribute to the diversity of the proteome [30].

GW9662 is an irreversible PPARγ antagonist [16], although in vitro cell studies have also reported off-target effects [24-26]. However, there are no in vivo studies that have established whether GW9662 is PPARγ-selective. In one instance, GW9662 was shown to reduce high fat diet-induced obesity in rats when administered in the diet at a concentration of 0.1% [31], which was identical to the GW9662 diet used in our study. GW9662 was also shown to block the anti-inflammatory effects of the PPARγ agonist, rosiglitazone, in endotoxin-induced acute lung injury after intravenous administration [32]. Based on gene array profiling, we found that GW9662 elicited PPARγ specificity based on its direct and indirect inhibitory effects on the expression of metabolic genes known to be under the control of PPARs.

An important caveat to the use of GW9662 is its ability to induce a modest acceleration of tumorigenesis when administered orally at the onset of carcinogenesis. We also observed a similar effect in MMTV-Pax8PPARγ mice following progestin/DMBA mammary carcinogenesis [10]. While this has not been reported previously, the ability of GW9662 to inhibit cell growth in vitro similarly to PPARγ agonists [24, 33, 34] suggests the presence of “off-target” effects. The increase in tumorigenesis observed with GW9662 and the dominant-negative Pax8PPARγ transgene suggests that partial antagonists rather than full antagonists or drugs with greater specificity may be a useful approach for further studies. Clearly, additional pharmacokinetic and pharmacodynamic studies in vivo are needed to establish the bioavailability and metabolic effects of GW9662. Overall, the positive aspect of inhibiting PPARγ was its ability to sensitize tumors to the ER antagonist fulvestrant, suggesting the potential for such an approach for hormone-insensitive malignancies.

MATERIALS AND METHODS

Animal model

FVB wild-type (WT) mice were obtained from Taconic Farms, Germantown, N.Y. All animal studies were conducted under protocols approved by the Georgetown University Animal Care and Use Committee.

Mammary carcinogenesis

Five week-old WT mice were treated with medroxyprogesterone acetate and DMBA as previously described [9, 28]. Briefly, mice were injected s.c. with 15 mg medroxyprogesterone acetate suspension (Depo-Provera?), and after seven days were administered four weekly doses of 1 mg DMBA/0.1 ml cottonseed oil by gavage. One day after the last dose of DMBA, mice were divided into four groups of 10 mice each: 1) one group was maintained on standard Purina Rodent Chow 5001, 2) one group was maintained on chow supplemented with 0.1% (w/w) GW9962, 2) one group was maintained on chow supplemented with GW9662 and injected s.c. every other week with 250 mg/kg fulvestrant (Faslodex®) and 4) one group was injected with 250 mg/kg fulvestrant every other week. GW9662 was provided by the Chemoprevention Branch, NCI. The histopathology of the resulting tumors is presented in Table S1.

Antibodies

The source of antibodies, their dilution and use were the following: rabbit anti-ERα (sc-542, Santa Cruz Biotechnology, 1:200 for IHC, 1:1,000 for western); rabbit anti-PgR (sc-538, Santa Cruz Biotechnology, 1:200 for IHC, 1:1,000 for western).

Immunohistochemistry

IHC analysis was carried out as previously described [9, 10, 28].

Western Blotting

Western blotting was carried out as previously described [10]. Briefly, tissue was frozen in liquid nitrogen and pulverized in a mortar and pestle, and mixed with lysis buffer containing: 0.1% SDS, 0.5% NP-40, phenylmethylsulfonyl fluoride, 1 mM sodium vanadate, 50 mM sodium fluoride, 10 mM β-glycerophosphate, 5 mM sodium pyrophosphate, and protease inhibitor cocktail (Roche Diagnostics). Following incubation on ice for 30 min, lysates were cleared by centrifugation for 15 min at 13,000 x g at 4°C. Protein concentrations were determined by the Coomassie Plus Protein Assay (Pierce), and 50 μg of lysate was separated in a 4-12% NuPAGE Bis-Tris gel (Invitrogen). After wet transfer, membranes were blocked for 1 hr at room temperature in TBS (pH 7.4) containing 5% non-fat dry milk and 0.1% Tween 20. Primary antibody was incubated overnight at 4°C, and secondary antibody was incubated for 1 hr at room temperature. Proteins were visualized with either SuperSignal West Pico or SuperSignal West Dura (Pierce).

Gene Microarray Analysis

Total RNA was extracted using an RNeasy Mini Kit (Qiagen) following the manufacturer's protocol as previously described [10, 35]. cRNA was synthesized using the Affymetrix (Santa Clara, CA) protocol with minor modifications as described [28]. Biotin-labeled cRNA was fragmented for 35 min at 94°C and hybridized overnight to an Affymetrix mouse 430A 2.0 GeneChip® representing approximately 22,000 annotated mouse genes by the Genomics and Epigenomics Shared Resource, Lombardi Comprehensive Cancer Center, Georgetown University. Hybridization signals were detected with an Agilent Gene Array scanner, and grid alignment and raw data generation performed with Affymetrix GeneChip® Operating software 1.1. Changes in gene expression with a signal ≥300 (log2 ≥8.1) and ≥3-fold change [9, 35, 36] were clustered hierarchically with CIMiner software (National Cancer Institute, NIH). Array data are presented in Table S2, and complete data files were deposited in the GEO database under accession no. GSE33762.

Quantitative Real-Time Polymerase Chain Reaction (qRT-PCR)

Total RNA was extracted using the RNAeasy Mini Kit (Qiagen, Valencia, CA) according to the manufacturer's protocol as previously described [10, 35]. One μg of RNA was reverse transcribed in a total volume of 20 μl using the Cloned AMV First-Strand cDNA Synthesis kit (Invitrogen). PCR was performed in triplicate in an ABI 7900 instrument (Applied Biosystems, Foster City, CA) using SYBRGreen detection (Applied Biosystems, Foster City, CA) according to the manufacturer's protocol. qRT-PCR primers were designed using the primer design tool at http://www.idtdna.com/Scitools/Applications/RealTimePCR/. Efficiencies of all primer sets (Table S1) were validated using a standard curve of five serial cDNA dilutions in water in duplicate. Primers were acceptable if the deviation from the slope of the standard curve was <0.3, and if the melting curve showed only one product. The expression of each target gene was normalized to the expression of GAPDH, and the relative quantification method was applied using SDS2.3 software (Applied Biosystems, Foster City, CA). Primers are listed in Table S3.

Statistical Analysis

Survival curves were analyzed by Pearson's log rank test and cumulative tumor formation by Student's two-tailed t test at a significance level of P≤0.05.

SUPPLEMENTARY TABLES

Acknowledgments

This study was supported by contract 1NO1 CN43302-WA19 from the National Cancer Institute, NIH, and award P30CA051008 from the National Cancer Institute, NIH to the Lombardi Comprehensive Cancer Center (LCCC). This investigation was conducted using the Animal Research, Flow Cytometry, Genomics and Epigenomics, and Microscopy and Imaging Shared Resources of the LCCC, and by an animal facilities construction grant from the NIH..

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