Progestin effects on cell proliferation pathways in the postmenopausal mammary gland
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Menopausal hormone therapies vary widely in their effects on breast cancer risk, and the mechanisms underlying these differences are unclear. The primary goals of this study were to characterize the mammary gland transcriptional profile of estrogen + progestin therapy in comparison with estrogen-alone or tibolone and investigate pathways of cell proliferation in a postmenopausal primate model.
Ovariectomized female cynomolgus macaque monkeys were randomized into the following groups: placebo (Con), oral conjugated equine estrogens (CEE), CEE with medroxyprogesterone acetate (MPA) (CEE + MPA), and tibolone given at a low or high dose (Lo or Hi Tib). All study treatment doses represented human clinical dose equivalents and were administered in the diet over a period of 2 years.
Treatment with CEE + MPA had the greatest effect on global mRNA profiles and markers of mammary gland proliferation compared to CEE or tibolone treatment. Changes in the transcriptional patterns resulting from the addition of MPA to CEE were related to increased growth factors and decreased estrogen receptor (ER) signaling. Specific genes induced by CEE + MPA treatment included key members of prolactin receptor (PRLR)/signal transducer and activator of transcription 5 (STAT5), epidermal growth factor receptor (EGFR), and receptor activator of nuclear factor kappa B (RANK)/receptor activator of nuclear factor kappa B ligand (RANKL) pathways that were highly associated with breast tissue proliferation. In contrast, tibolone did not affect breast tissue proliferation but did elicit a mixed pattern of ER agonist activity.
Our findings indicate that estrogen + progestin therapy results in a distinct molecular profile compared to estrogen-alone or tibolone therapy, including upregulation of key growth factor targets associated with mammary carcinogenesis in mouse models. These changes may contribute to the promotional effects of estrogen + progestin therapy on breast cancer risk.
KeywordsPostmenopausal hormone therapy Estrogen Progestin Tibolone Breast cancer Gene expression RANKL Denosumab
Analysis of variance
Conjugated equine estrogens
Epidermal growth factor receptor
Estrogen + progestin therapy
Growth regulation by estrogen in breast cancer 1
17-beta hydroxysteroid dehydrogenase type 1
17-beta hydroxysteroid dehydrogenase type 2
3-beta-hydroxysteroid dehydrogenase/delta-5-delta-4 isomerase
Insulin-like growth factor binding protein 1
Antigen identified by monoclonal antibody Ki-67
Principal components analysis
Quantitative real-time polymerase chain reaction
Receptor activator of nuclear factor kappa B
Receptor activator of nuclear factor kappa B ligand
Signal transducer and activator of transcription 5
Trefoil factor 1
Transforming growth factor
Women’s Health Initiative.
Different types of postmenopausal hormone therapy (HT) have been widely used for more than 60 years to alleviate symptoms of menopause and prevent associated conditions such as osteoporosis. The primary form of HT during much of this time has been estrogen-alone therapy (ET) . In the mid-1990s, the clinical use of estrogen plus progestin therapy (EPT) began after several studies demonstrated that progestins opposed the adverse effects of ET on endometrial cancer risk . These findings helped spur a rapid increase in EPT prescriptions from less than two million in 1995 to 24 million in 2001 . At the time, the most common type of HT used in the US was conjugated equine estrogens (CEE) with or without the progestin medroxyprogesterone acetate (MPA), which together accounted for more than 60% of total HT prescriptions .
Use of HT fell dramatically in 2002 after the release of the primary results from the Women’s Health Initiative (WHI) Estrogen + Progestin Trial [1, 3]. In this large randomized clinical trial, postmenopausal women receiving EPT (CEE + MPA) treatment had significantly higher incidence of invasive breast cancer compared with those taking the placebo [3, 4]. Subsequent reports noted increased breast cancer mortality for women taking EPT  and decreased breast cancer incidence following discontinuation of EPT . These results supported prior epidemiologic studies [7, 8] but differed from the sister WHI Estrogen-Alone Trial, in which CEE alone did not increase the incidence of invasive breast cancer among women with a prior hysterectomy [9, 10]. Collectively, these studies confirmed that the promotional effects of EPT on certain types of breast cancer were greater than those seen with estrogen alone.
A prominent alternative to traditional menopausal HTs used outside the US is tibolone. This unique steroidal compound is converted in a tissue-selective manner to estrogenic, progestogenic, and androgenic metabolites. Estrogenic metabolites have been shown to reduce menopausal symptoms and fracture risk [11, 12], whereas the progestogenic Δ-4 isomer metabolite (selectively produced in the uterus) has been shown to provide endometrial protection from estrogenic effects [13, 14]. However, the effects of tibolone therapy on breast cancer risk are controversial. In a randomized clinical trial of older postmenopausal women, tibolone therapy resulted in a significantly lower breast cancer risk , whereas in a separate clinical trial, breast cancer survivors had increased risk of recurrence following tibolone treatment .
Despite numerous preclinical and clinical studies, the mechanistic actions of different HTs on breast tissue have not been clearly defined. In mouse models, ovarian hormones contribute significantly to mammary gland carcinogenesis ; however, differences between mouse and human mammary gland anatomy, development, and/or hormonal control of proliferation may limit the translational relevance of targets identified in the mouse for estrogen and progestogen function. Macaques are anthropoid primates with high overall genetic coding sequence identity to humans, including key genes related to breast cancer susceptibility . Prior work has shown close similarities between macaque and human mammary gland biology, including responses to exogenous estrogen and progestogen therapies, sex steroid receptor expression, and age-related hyperplastic and neoplastic lesions . This includes a study on aged rhesus macaques and suggests a lifetime incidence of mammary gland cancer at about 6% , similar to lower-risk human populations. Previous studies in this model have also shown that the addition of a progestin to an estrogen increases mammary gland proliferation and density beyond that seen with estrogen alone, in support of the later WHI findings related to breast cancer risk . The primary aim of this study was to assess the effects of long-term treatment with CEE, CEE + MPA, or tibolone on the transcriptional profiles and signaling pathways of the normal postmenopausal primate mammary gland. Our main goals were to identify specific targets associated with hormone-induced breast proliferation and evaluate their relations with candidate pathways known to drive mammary carcinogenesis in mouse tumor models.
Study design and treatments
This study utilized archived tissue samples from a parallel-arm design experiment in which 149 ovariectomized adult female cynomolgus macaques (Macaca fascicularis) with a mean estimated age of six to eight years were randomized to receive one of the following five treatments for two years: placebo (control; n = 31); CEE at 0.042 mg/kg (CEE; n = 28); CEE + MPA at 0.167 mg/kg (CEE + MPA; n = 29); tibolone at 0.05 mg/kg (Lo Tib; n = 30); and tibolone at 0.2 mg/kg (Hi Tib; n = 31). Dose equivalents approximated standard HT doses of CEE (0.625 mg/day) and MPA (2.5 mg/day) in postmenopausal women, and tibolone doses were designed to approximate 0.75 mg/day (low) and 3.0 mg/day (high) doses in women. Serum concentrations of estrogens, MPA, and tibolone metabolites were similar to those reported in women taking comparable therapies . Treatments were administered in the control diet with casein plus lactalbumin as the protein source and macronutrient composition based on a typical human diet in the USA . Animals were housed in social groups of five animals each and fed 60 kcal/kg (plus 10% extra to account for waste) twice daily, with drug treatments split between the two feedings. Daily doses were scaled to 1,800 kcal of diet (the estimated daily intake for a US woman) to account for differences in metabolic rates between monkeys and human subjects. All animals were considered multiparous based on historical data from the original breeding colony and uterine histology. Histology outcomes were described previously ; no mammary gland tumors were detected.
All procedures involving macaques in this study were conducted in compliance with State and Federal laws and standards of the US Department of Health and Human Services and were approved by the Wake Forest University Animal Care and Use Committee. The facilities and laboratory animal program of Wake Forest University are fully accredited by the Association for the Assessment and Accreditation of Laboratory Animal Care.
Gene microarray analyses
Mammary gland tissues were collected during necropsy at the end of the two-year treatment period , and designated portions were snap-frozen in liquid nitrogen and stored at −70°C for gene expression analyses. Total mammary gland RNA was extracted from frozen samples using Tri Reagent (Molecular Research Center, Cincinnati, OH, USA), purified using RNeasy Mini kit (QIAGEN, Valencia, CA, USA), and quantitated using a NanoDrop ND-1000 UV–vis spectrophotometer (NanoDrop, Wilmington, DE, USA). Nucleic acid intactness and quality were confirmed using an Agilent 2100 Bioanalyzer (Agilent Technologies, Wilmington, DE, USA). Biotinylated cRNA samples were prepared according to the standard Enzo Bioarray™ protocol (Enzo Life Sciences, Farmingdale, NY, USA) and hybridized using the standard Affymetrix (Santa Clara, CA, USA) protocol for eukaryotic samples. Biotinylated cRNA from each sample was hybridized to Affymetrix GeneChip Rhesus Macaque Genome Arrays (Santa Clara, CA, USA), washed and stained in an Affymetrix GeneChip Fluidics Station (Santa Clara, CA, USA), and scanned with an Affymetrix GeneChip® Scanner 3000 (Santa Clara, CA, USA). Intensity data were extracted from scanned images and checked for quality using Affymetrix GeneChip Operating Software and Expression Console (MAS5 algorithm; Santa Clara, CA, USA). Microarray assays were performed at Beckman Coulter Genomics (Morrisville, NC, USA). Four randomly selected samples per group were run on microarray from control, CEE, CEE + MPA, and Hi Tib groups.
Microarray data analyses were performed using the GeneSifter® software program (Perkin Elmer/Geospiza, Seattle, WA, USA). Intensity data were RMA-normalized, converted to a log2 scale, screened for heterogeneity among samples and groups, and evaluated using supervised analysis of variance (ANOVA) and pairwise comparisons between treatments. Principal components analysis (PCA), pattern navigation, cluster analysis, heat mapping, and KEGG pathway analyses were performed on filtered data subsets, as described in the Results section. Differences in gene numbers altered by each treatment were compared using either Fisher’s exact test or chi-square test. Euclidean distances (representing the numeric difference between treatment vectors) were calculated as part of hierarchical clustering dendrograms using average linkage. Pathways related to cell proliferation were evaluated using z-scores generated in KEGG analyses; a z-score more than 2.0 was considered significant overrepresentation of genes in a particular pathway. All P values were corrected when possible for multiple comparisons using the Benjamini and Hochberg method (P adj ), which derives a false discovery rate estimate from the raw P-values . Representation of differentially expressed genes within specific functional categories was evaluated using Ingenuity Pathway Analysis software v6 (Ingenuity Systems, Redwood City, CA, USA) using a Fisher’s exact test with Benjamini and Hochberg correction and expressed as -log10 of the P value for gene numbers within each treatment group. Microarray data are publicly available on the NCBI Gene Expression Omnibus database (accession number GSE27228).
Quantitative gene expression
Expression of genes associated with proliferation, epithelial density, growth factor signaling, oestrogen receptor (ER) expression and activity, estrogen metabolism, and receptor activator of nuclear factor kappa-B (RANK)/RANK ligand (RANKL) pathway activity were measured in mammary gland samples using quantitative real-time reverse transcriptase polymerase chain reaction (qPCR). Macaque-specific qPCR primer-probe sets for internal control genes (glyceraldehyde-3-phosphate dehydrogenase (GAPDH); beta-actin (ACTB)) were generated through the Applied Biosystems Taqman Assay-by-Design service (Foster City, CA, USA). Sources for all target primer/probe sets are given in Additional file 1: Table S1. All probes spanned an exon-exon junction to eliminate genomic DNA amplification. qPCR reactions (20 μl volume) were performed on an Applied Biosystems 7500 Fast Real-Time PCR system (Foster City, CA, USA) using standard Taqman reagents and thermocycling protocol . Relative expression was determined using the ΔΔCt method. The Ct values for the control genes GAPDH and ACTB were averaged for use in internal calibration, and premenopausal breast tissue RNA was a reference for plate-to-plate parallel calibration. Calculations were performed using Applied Biosystems Relative Quantification 7500 Software v2.0.1 (Foster City, CA, USA).
Immunohistochemical (IHC) staining was performed on fixed paraffin-embedded mammary gland sections. Slides were deparaffinized, rehydrated in water, prepared by heat-induced epitope retrieval using Diva Decloaker (Biocare Medical, Concord, CA, USA) and Decloaking Chamber Plus (Biocare Medical, Concord, CA, USA) at heat and pressure cycles of 125°C for 30 and 10 seconds. Slides were gradually cooled by replacing the retrieval solution with deionized water and rinsed twice in wash buffer (Dako Wash Buffer, DakoCytomation Carpinteria, CA; five minutes) before loading on a Dako Autostainer (Dako North America Inc, Carpinteria, CA). Sections were blocked for endogenous peroxidases and nonspecific binding of staining reagents by sequentially incubating with 3% hydrogen peroxidase (hydrogen peroxidase block, Thermo Scientific Waltham, MA; 10 minutes), Avidin (Vector Labs, Burlingame, CA; 15 minutes), Biotin (Vector Labs, Burlingame, CA; 15 minutes), and TNB (Perkin Elmer; 20 minutes). Tris-NaCl-blocking buffer was removed and replaced with anti-human RANK (N-2B10.1 or N-1H8.1; Amgen, Seattle, WA) or RANKL (M366; Amgen, Seattle, WA) mouse monoclonal antibodies or isotype-matched control mouse IgG (BD Pharmingen, San Jose, CA) at concentrations of 5 μg/mL for anti-RANK and 1 μg/mL for anti-RANKL for 60 minutes. A biotinylated, goat anti-mouse IgG (Vector Labs, Burlingame, CA) secondary antibody in 10% normal human serum Tris-NaCl-blocking buffer was applied at a concentration of 7.5 μg/mL followed by a 30 minute incubation. Slides were sequentially incubated with streptavidin-horseradish peroxidase (SA-HRP; Perkin Elmer, Waltham, MA; 30 minutes) at a 1:1500 dilution in TNB, tyramide signal amplification TSA (Perkin Elmer, Waltham, MA; five minutes) at a 1:100 dilution in amplification diluent (Perkin Elmer, Waltham, MA), and then SA-HRP (Perkin Elmer, Waltham, MA; 30 minutes) at a 1:1500 dilution in TNB. Slides were then incubated with diaminobenzidine chromogen (Dako, Carpinteria, CA; five minutes), counterstained with hematoxylin (Dako, Carpinteria, CA; 30 seconds), allowed to turn blue in tap water for two minutes before dehydrating with ascending concentrations of ethanol, cleared with xylene, and mounted.
The intensity of IHC staining was scored on a semiquantitative scale (0 = absent, 1 = weak, 2 = moderate, 3 = intense), blinded to treatment group by a board-certified pathologist. Incidence was scored as a positive IHC signal (any intensity). Immunostaining of slides for Ki-67 antigen was described previously . For dual labeling experiments, the following modifications to the above procedure were performed. Antigen retrieval was performed using Diva AR reagent (Biocare, Concord, CA; DV2004G1) at 90°C overnight in the Decloaking Chamber. Sections were blocked as described above, incubated with either anti-progesterone receptor PGR (Dako, Carpinteria, CA; M3569 at 1:40; 40 minutes) or anti-Ki-67 (Epitomics, Burlingame, CA; 4203–1 at 1:400; 60 minutes), detected with Dako Mouse or Rabbit Envision + Systems (Dako, Carpinteria, CA, 30 minutes), and visualized by Dako DAB+ (Dako, Carpinteria, CA, 10 minutes). Antibody staining from the first PR/Ki-67 IHC incubation/staining were blocked by rinsing sections in distilled water, eluting, and incubating the slides in Diva AR reagent (Biocare, Concord, CA) at 98°C for 10 minutes. Slides were washed and blocked as described above; followed by incubation with either anti-RANKL (M366 at 2 μg/mL), anti-RANK (N-1H8.1 at 5 μg/mL), or mouse IgG1 isotype control (5 μg/mL) for 60 minutes. Secondary antibody incubation was performed as described above, followed by incubation in streptavidin alkaline phosphatase, tyramide amplification and repeat of strepavidin alkaline phosphatase. Slides were then incubated with permanent red chromogen (Dako, Carpinteria, CA; 20 minutes), counterstained with Mayer’s hematoxylin, washed and aqueous mounted. Histologic images were photographed using a Nikon Eclipse E600 microscope with a Nikon (Tokyo, Japan) DXM1200 digital camera. The resulting images were white-balanced using Adobe Photoshop CS software (San Jose, CA); no additional image modifications were employed.
Data were analyzed using the SAS statistical package v9 (SAS Institute, Cary, NC, USA). All data were evaluated for normal distribution and homogeneity of variances among groups. Gene expression data were evaluated using a nonparametric Kruskal-Wallis test followed by two-sided Wilcoxon rank sum pairwise analysis and reported as a fold-change of control with 90% confidence interval. One control group animal died during the course of the study, reducing the number of control animals to 30. All pairwise P values were adjusted for the number of pairwise tests using a Bonferroni correction. Pre-planned pairwise tests included each treatment group versus control and CEE + MPA versus CEE and Hi Tib groups. Intensity of RANK/RANKL immunostaining was evaluated using a one-way ANOVA with Bonferroni’s post test. To evaluate the correlation of gene or protein expression with IHC, data were log transformed and linear regression analysis was performed. A two-tailed significance level of 0.05 was used for all comparisons.
EPT elicits distinct effects on global gene expression profiles
EPT increases cell proliferation and growth factor signaling markers
Adding a progestin to ET inhibits ER activity
Tibolone treatment does not induce growth factor signals
The main transcriptional pattern among genes altered by the Hi Tib dose related to ER signaling; no other clear patterns were noted. Of the 24 identified genes with more than three FC and P < 0.05 compared with control, 20 genes were upregulated. Among these, there were seven known ER-sensitive genes (PGR, GREB1, stanniocalcin 2 [STC2], secretoglobin family 1D member 2 [SCGB1D2], kallikreins 11 [KLK11] and 12 [KLK12], and IGFBP1); two genes involved in steroid metabolism (cytochrome p450 family 2 subfamily A polypeptide 7 [CYP2A7] and 3-beta-hydroxysteroid dehydrogenase ∆-5-∆-4 isomerase type II [HSD3B2]); two secretoglobins (SCGB3A1 and SCGB1D2); and three peptidases (disintegrin and metalloproteinase with thrombospondin motifs 8 [ADAMTS8], KLK11, and KLK12). Notably, isoforms of HSD3B are the primary enzymes driving production of the progestogenic delta-4 tibolone metabolite . Despite a 6.5 FC increase in HSD3B2 expression in the Hi Tib group, no markers of progestogenic activity were noted.
EPT increases RANK/RANKL pathway expression
RANKL and RANK protein show distinct patterns of expression in the mammary gland
RANKL and RANK protein expression is associated with mammary epithelial cell proliferation
The addition of a progestin to ET is associated with increased breast tissue proliferation , mammographic density , and breast cancer risk in postmenopausal women [4, 7, 8]. Molecular mechanisms driving these effects are not clearly defined. In this study we show that adding the progestin MPA to CEE dramatically altered the mRNA profile in the normal primate mammary gland. This change was associated with greater mammary gland proliferation, decreased markers of ER activity, and increased markers of growth factor signaling. Many of the progestin-dependent changes observed here are also seen in the mouse mammary gland and have been associated with mammary carcinogenesis. These findings identify key differences among common types of menopausal HTs and highlight specific pathways relevant to hormonal promotion of mammary epithelial cell growth.
Our results show clear differences between ET and EPT effects on breast tissue and support the hypothesis that EPT increases cell proliferation beyond that of ET alone due in part to specific growth factor signals. Three primary progestin-regulated pathways were identified in this study: prolactin receptor (PRLR)/STAT5, EGFR, and RANK/RANKL. The STAT5 pathway has been shown to mediate PRLR activity and regulate mammary gland development, differentiation, and proliferation [26, 34], whereas EGFR is a central growth factor pathway in mammary gland development and a subset of breast cancers . Both PRLR/STAT5 and EGFR pathways are also known targets of progestogen action in the mouse mammary gland [36, 37].
RANK/RANKL is the third pathway selectively modified by the combination of CEE + MPA. This pathway has important roles in lymph node development during embryogenesis and is essential for the formation, function, and survival of bone-resorbing osteoclasts . Modulation of the latter mechanism is the basis for the development of the fully human monoclonal antibody to RANKL, denosumab, recently approved for the prevention of skeletal-related events in patients with bone metastases from solid tumors . Analysis of RANK- and RANKL-knockout mice revealed defective mammary alveologenesis , which resembled the mammary morphogenic defect observed in PGR-knockout mice . Transcription of RANKL is rapidly induced upon progesterone exposure in mice  and co-localized with PGR within “transmitter” ER/PGR-positive luminal mammary epithelial cells . Subsequent studies have shown that RANKL is an essential paracrine mediator of progesterone function in the mouse mammary gland, leading to both mammary epithelial proliferation  and the transient expansion and increased regenerative potential of mammary stem cells [44, 45] during pregnancy and the estrous cycle. Importantly, these functionalities are not limited to normal mammary morphogenesis and observations in rodent models have now shown that RANKL, via activation of RANK within mammary epithelium, mediates progesterone-dependent mammary tumor formation [28, 29].
Currently, it is unclear whether the RANK/RANKL pathway functions similarly in human breast tissue. In the current study, we show that key components of the RANKL pathway are expressed in the normal primate mammary gland and modulated by long-term EPT exposure at clinically relevant doses. Protein expression patterns of RANKL and RANK protein were highly similar to those seen in the mouse  and human mammary gland (data not shown) . In each species, RANKL protein is focally expressed in discrete luminal epithelial cells of the ducts and lobules often separated by adjacent RANKL-negative cells. Dual immunolabeling revealed that RANKL protein expression was highly colocalized within PGR-positive luminal epithelial cells in this study, similar to what has been recently described in mice and humans [28, 32]. In contrast, RANK protein is segmentally expressed, sporadically in alveoli and often in cells located along the basal aspect of ducts but also in epithelial cells that extend from the basal compartment to the lumen. Similar to observations in mice, RANKL protein levels within the mammary epithelium of macaques were clearly elevated upon exposure to estrogen with a progestin but not estrogen alone. In the CEE + MPA group, we also observed decreased mRNA expression levels of OPG, the negative regulator of RANKL, thereby increasing the ratio of either RANKL/OPG or RANK/OPG. Increased RANKL protein expression was positively associated with increased ductal and alveolar proliferation driven by EPT. RANK protein was colocalized with Ki-67 in a subset of cells, suggesting that RANK-expressing breast cells directly respond to the RANKL signal and comprise at least part of the proliferative component after progestin exposure. Altogether, multiple mechanisms of hormone-dependent control contributing to the net increase in RANKL signal were identified and shown to be positively associated with increased epithelial proliferation (MKI67) and density (KRT19), suggesting that this pathway may be utilized across mammalian species for progestogen-dependent breast proliferation.
In premenopausal women, ovarian-produced progesterone may also contribute to the established relation between breast cancer risk and number of menstrual cycles or reproductive history , potentially via increased breast proliferation  and the non-proliferative expansion of normal or transformed mammary stem cells [44, 45, 48]. Using a candidate gene approach, a recent study identified RANKL, c-Kit, and gene signatures representing MaSC or luminal progenitors as each being associated with younger age at breast cancer diagnosis . Although the relative contribution of RANKL mRNA from normal breast versus tumor tissue was not specified in this analysis of patients with breast cancer, the authors concluded that the strong correlation of these gene sets (including RANKL expression) was independent of breast cancer subtype and instead represented unique biological pathways common to breast cancer in young women and perhaps related to the poor prognosis in these patients. Given the present evidence, the increased mammary mitogenesis observed during the progesterone-dominant luteal phase of the human menstrual cycle  could involve an operative role of RANKL. Recent gene expression analysis of fine-needle aspirates of human breast tissue demonstrating significant upregulation of RANKL mRNA during the luteal phase  is consistent with this notion. In fact, a recent publication  has demonstrated that RANKL levels in the human breast are correlated with serum progesterone levels. Furthermore, RANKL was not only sufficient to induce human breast cell proliferation but was also required for progesterone-induced breast cell proliferation. These data, with observations presented in this primate study, suggest that the increased RANKL signal in human breast tissue is a consequence of progestogen exposure in postmenopausal women or luteal phase ovarian progesterone in premenopausal women. Moreover, this increased RANKL may be correlated with the proliferative status and overall density of the mammary epithelium and contribute to hormone-dependent breast tumor formation.
The three signaling pathways identified here as being selectively increased by EPT all exhibit signaling cross-talk that may be functionally important in breast cancer. Prior studies have shown that the induction of RANKL by MPA requires expression of PRLR and that prolactin signaling is necessary for nuclear translocation of STAT5A after EPT [29, 51]. These findings also indicate that the interferon-gamma responsive elements identified within the RANKL promoter are essential for activation of the JAK2/STAT5A response  and potentially important for progestogen-dependent increases. Other studies have shown that nuclear phosphorylated STAT5A is co-localized with PGR and RANKL in cells after EPT , further suggesting that progestogen-dependent increases in RANKL transcription may be governed at the RANKL promoter, at least in part, by a complex of PGR and STAT5A, similar to that observed with the β-casein promoter . Finally, EGFR ligands have been shown to strongly decrease OPG expression in an EGFR-dependent manner  and activate STAT5A in mammary tissue . Collectively, these data support a model in which progestogen activity in breast tissue may increase RANKL protein expression either directly, or indirectly, via PRLR/STAT5 signaling, whereas OPG protein expression may be decreased via EGFR signaling. Future studies are warranted to determine if multifactorial convergences of the PRLR/STAT5, EGFR, and RANK/RANKL pathways may contribute to breast cancer risk.
Unlike EPT, tibolone did not show a clear induction of mRNA markers in breast tissue related to growth factor signaling. This finding is consistent with the lack of increased mammary epithelial Ki-67 labeling reported previously  and the lack of increased breast cancer risk among older postmenopausal women receiving tibolone in the LIFT clinical trial . In contrast, tibolone treatment in the LIBERATE clinical trial was associated with a 40% increased risk of recurrence among breast cancer patients with ER-positive tumors and vasomotor symptoms . Sub-group analysis among women receiving adjuvant endocrine therapy indicated that tibolone interference was greater for aromatase inhibitors (which decrease systemic and local estrogen) than for tamoxifen (which blocks ERs). The authors of the study suggest that these findings point to potential ER agonist effects of tibolone on occult, estrogen-sensitive metastases . Results from the current study provide limited support for this idea, showing modest estrogenic effects of tibolone on some gene markers of ER activity but no clear progestogenic effects or activity related to specific growth factor pathways.
Minimizing breast cancer risk by mitigating potential adverse effects of hormonal agents is a central challenge in women’s health. Results of this study expand the current understanding of transcriptional patterns and signaling pathways underlying HT effects in mammalian breast tissue. Findings presented here identify PRLR/STAT5, EGFR, and RANK/RANKL as molecular pathways that may be relevant to increased breast tissue proliferation, mammographic density, and breast cancer risk in postmenopausal women taking EPT. These pathways are potential targets for assessing and preventing progestogen-associated risk, and this information should help inform clinical strategies to better prevent hormone-associated breast cancer and recurrence.
The authors would like to thank Lisa O’Donnell and Jean Gardin for their technical contributions, Tony Polverino for critical reading of the manuscript, and Albert Y. Rhee (Amgen Inc.) for editing assistance. This work was supported by research grants from the National Institutes of Health (K01 RR 021322–05) and Amgen Inc. Support for the original animal study was provided by NV Organon.
- 3.Rossouw JE, Anderson GL, Prentice RL, LaCroix AZ, Kooperberg C, Stefanick ML, Jackson RD, Beresford SA, Howard BV, Johnson KC, Kotchen JM, Ockene J, Writing Group for the Women's Health Initiative Investigators: Risks and benefits of estrogen plus progestin in healthy postmenopausal women: principal results From the Women’s Health Initiative randomized controlled trial. JAMA. 2002, 288: 321-333. 10.1001/jama.288.3.321.CrossRefPubMedGoogle Scholar
- 4.Chlebowski RT, Hendrix SL, Langer RD, Stefanick ML, Gass M, Lane D, Rodabough RJ, Gilligan MA, Cyr MG, Thomson CA, Khandekar J, Petrovitch H, McTiernan A, WHI Investigators: Influence of estrogen plus progestin on breast cancer and mammography in healthy postmenopausal women: the Women’s Health Initiative Randomized Trial. JAMA. 2003, 289: 3243-3253. 10.1001/jama.289.24.3243.CrossRefPubMedGoogle Scholar
- 5.Chlebowski RT, Anderson GL, Gass M, Lane DS, Aragaki AK, Kuller LH, Manson JE, Stefanick ML, Ockene J, Sarto GE, Johnson KC, Wactawski-Wende J, Ravdin PM, Schenken R, Hendrix SL, Rajkovic A, Rohan TE, Yasmeen S, Prentice RL, WHI Investigators: Estrogen plus progestin and breast cancer incidence and mortality in postmenopausal women. JAMA. 2010, 304: 1684-1692. 10.1001/jama.2010.1500.CrossRefPubMedPubMedCentralGoogle Scholar
- 6.Chlebowski RT, Kuller LH, Prentice RL, Stefanick ML, Manson JE, Gass M, Aragaki AK, Ockene JK, Lane DS, Sarto GE, Rajkovic A, Schenken R, Hendrix SL, Ravdin PM, Rohan TE, Yasmeen S, Anderson G, WHI Investigators: Breast cancer after use of estrogen plus progestin in postmenopausal women. N Engl J Med. 2009, 360: 573-587. 10.1056/NEJMoa0807684.CrossRefPubMedPubMedCentralGoogle Scholar
- 9.Stefanick ML, Anderson GL, Margolis KL, Hendrix SL, Rodabough RJ, Paskett ED, Lane DS, Hubbell FA, Assaf AR, Sarto GE, Schenken RS, Yasmeen S, Lessin L, Chlebowski RT, WHI Investigators: Effects of conjugated equine estrogens on breast cancer and mammography screening in postmenopausal women with hysterectomy. JAMA. 2006, 295: 1647-1657. 10.1001/jama.295.14.1647.CrossRefPubMedGoogle Scholar
- 10.LaCroix AZ, Chlebowski RT, Manson JE, Aragaki AK, Johnson KC, Martin L, Margolis KL, Stefanick ML, Brzyski R, Curb JD, Howard BV, Lewis CE, Wactawski-Wende J, WHI Investigators: Health outcomes after stopping conjugated equine estrogens among postmenopausal women with prior hysterectomy: a randomized controlled trial. JAMA. 2011, 305: 1305-1314. 10.1001/jama.2011.382.CrossRefPubMedPubMedCentralGoogle Scholar
- 11.Swanson SG, Drosman S, Helmond FA, Stathopoulos VM: Tibolone for the treatment of moderate to severe vasomotor symptoms and genital atrophy in postmenopausal women: a multicenter, randomized, double-blind, placebo-controlled study. Menopause. 2006, 13: 917-925. 10.1097/01.gme.0000247016.41007.c9.CrossRefPubMedGoogle Scholar
- 12.Cummings SR, Ettinger B, Delmas PD, Kenemans P, Stathopoulos V, Verweij P, Mol-Arts M, Kloosterboer L, Mosca L, Christiansen C, Bilezikian J, Kerzberg EM, Johnson S, Zanchetta J, Grobbee DE, Seifert W, Eastell R, LIFT Trial Investigators: The effects of tibolone in older postmenopausal women. N Engl J Med. 2008, 359: 697-708. 10.1056/NEJMoa0800743.CrossRefPubMedPubMedCentralGoogle Scholar
- 13.Tang B, Markiewicz L, Kloosterboer HJ, Gurpide E: Human endometrial 3 beta-hydroxysteroid dehydrogenase/isomerase can locally reduce intrinsic estrogenic/progestagenic activity ratios of a steroidal drug (Org OD 14). J Steroid Biochem Mol Biol. 1993, 45: 345-351. 10.1016/0960-0760(93)90003-F.CrossRefPubMedGoogle Scholar
- 15.Kenemans P, Bundred NJ, Foidart JM, Kubista E, von Schoultz B, Sismondi P, Vassilopoulou-Sellin R, Yip CH, Egberts J, Mol-Arts M, Mulder R, van Os S, Beckmann MW, LIBERATE Study Group: Safety and efficacy of tibolone in breast-cancer patients with vasomotor symptoms: a double-blind, randomised, non-inferiority trial. Lancet Oncol. 2009, 10: 135-146. 10.1016/S1470-2045(08)70341-3.CrossRefPubMedGoogle Scholar
- 16.Ismail PM, Amato P, Soyal SM, DeMayo FJ, Conneely OM, O’Malley BW, Lydon JP: Progesterone involvement in breast development and tumorigenesis–as revealed by progesterone receptor “knockout” and “knockin” mouse models. Steroids. 2003, 68: 779-787. 10.1016/S0039-128X(03)00133-8.CrossRefPubMedGoogle Scholar
- 27.Zhu J, Jia X, Xiao G, Kang Y, Partridge NC, Qin L: EGF-like ligands stimulate osteoclastogenesis by regulating expression of osteoclast regulatory factors by osteoblasts: implications for osteolytic bone metastases. J Biol Chem. 2007, 282: 26656-26664. 10.1074/jbc.M705064200.CrossRefPubMedGoogle Scholar
- 29.Schramek D, Leibbrandt A, Sigl V, Kenner L, Pospisilik JA, Lee HJ, Hanada R, Joshi PA, Aliprantis A, Glimcher L, Pasparakis M, Khokha R, Ormandy CJ, Widschwendter M, Schett G, Penninger JM: Osteoclast differentiation factor RANKL controls development of progestin-driven mammary cancer. Nature. 2010, 468: 98-102. 10.1038/nature09387.CrossRefPubMedPubMedCentralGoogle Scholar
- 31.Gonzalez-Suarez E, Branstetter D, Armstrong A, Dinh H, Blumberg H, Dougall WC: RANK overexpression in transgenic mice with mouse mammary tumor virus promoter-controlled RANK increases proliferation and impairs alveolar differentiation in the mammary epithelia and disrupts lumen formation in cultured epithelial acini. Mol Cell Biol. 2007, 27: 1442-1454. 10.1128/MCB.01298-06.CrossRefPubMedGoogle Scholar
- 32.Tanos T, Sflomos G, Echeverria PC, Ayyanan A, Gutierrez M, Delaloye JF, Raffoul W, Fiche M, Dougall W, Schneider P, Yalcin-Ozuysal O, Brisken C: Progesterone/RANKL is a major regulatory axis in the human breast. Sci Transl Med. 2013, 5: 182ra55-10.1126/scitranslmed.3005654.CrossRefPubMedGoogle Scholar
- 33.Hofseth LJ, Raafat AM, Osuch JR, Pathak DR, Slomski CA, Haslam SZ: Hormone replacement therapy with estrogen or estrogen plus medroxyprogesterone acetate is associated with increased epithelial proliferation in the normal postmenopausal breast. J Clin Endocrinol Metab. 1999, 84: 4559-4565. 10.1210/jc.84.12.4559.PubMedGoogle Scholar
- 34.Miyoshi K, Shillingford JM, Smith GH, Grimm SL, Wagner KU, Oka T, Rosen JM, Robinson GW, Hennighausen L: Signal transducer and activator of transcription (Stat) 5 controls the proliferation and differentiation of mammary alveolar epithelium. J Cell Biol. 2001, 155: 531-542. 10.1083/jcb.200107065.CrossRefPubMedPubMedCentralGoogle Scholar
- 39.Lipton A, Fizazi K, Stopeck AT, Henry DH, Brown JE, Yardley DA, Richardson GE, Siena S, Maroto P, Clemens M, Bilynskyy B, Charu V, Beuzeboc P, Rader M, Viniegra M, Saad F, Ke C, Braun A, Jun S: Superiority of denosumab to zoledronic acid for prevention of skeletal-related events: A combined analysis of 3 pivotal, randomised, phase 3 trials. Eur J Cancer. 2012, 48: 3082-3096. 10.1016/j.ejca.2012.08.002.CrossRefPubMedGoogle Scholar
- 40.Fata JE, Kong YY, Li J, Sasaki T, Irie-Sasaki J, Moorehead RA, Elliott R, Scully S, Voura EB, Lacey DL, Boyle WJ, Khokha R, Penninger JM: The osteoclast differentiation factor osteoprotegerin-ligand is essential for mammary gland development. Cell. 2000, 103: 41-50. 10.1016/S0092-8674(00)00103-3.CrossRefPubMedGoogle Scholar
- 49.Azim HA, Michiels S, Bedard PL, Singhal SK, Criscitiello C, Ignatiadis M, Haibe-Kains B, Piccart MJ, Sotiriou C, Loi S: Elucidating prognosis and biology of breast cancer arising in young women using gene expression profiling. Clin Cancer Res. 2012, 18: 1341-1351. 10.1158/1078-0432.CCR-11-2599.CrossRefPubMedGoogle Scholar
- 50.Wang J, Lee O, Heinz R, Ivancic D, Shcholtens D, Chatterton RT, Khan SA: Identification of hormone-responsive genes as biomarkers for menstrual cycle phases and menopausal status [abstract]. Cancer. 2011, 71:Google Scholar
- 52.Buser AC, Gass-Handel EK, Wyszomierski SL, Doppler W, Leonhardt SA, Schaack J, Rosen JM, Watkin H, Anderson SM, Edwards DP: Progesterone receptor repression of prolactin/signal transducer and activator of transcription 5-mediated transcription of the beta-casein gene in mammary epithelial cells. Mol Endocrinol. 2007, 21: 106-125.CrossRefPubMedGoogle Scholar
- 53.Gallego MI, Binart N, Robinson GW, Okagaki R, Coschigano KT, Perry J, Kopchick JJ, Oka T, Kelly PA, Hennighausen L: Prolactin, growth hormone, and epidermal growth factor activate Stat5 in different compartments of mammary tissue and exert different and overlapping developmental effects. Dev Biol. 2001, 229: 163-175. 10.1006/dbio.2000.9961.CrossRefPubMedGoogle Scholar
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