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. Author manuscript; available in PMC: 2014 Aug 1.
Published in final edited form as: Endocr Relat Cancer. 2014 Feb 27;21(2):263–273. doi: 10.1530/ERC-13-0233

Serum estrogen receptor bioactivity and breast cancer risk among postmenopausal women

Vanessa W Lim 1, Jun Li 1, Yinhan Gong 1, Aizhen Jin 2, Jian-Min Yuan 3, Eu Leong Yong 1,*, Woon-Puay Koh 4,5,*
PMCID: PMC3962747  NIHMSID: NIHMS548477  PMID: 24322303

Abstract

The estrogen levels of Asian women are different from those of Western women, and this could affect estrogen receptor (ER) bioactivity and breast cancer risk. We conducted a case-control study of 169 postmenopausal breast cancer cases and 426 matched controls nested within a population-based prospective cohort, The Singapore Chinese Health Study, to evaluate serum levels of estrogens and their receptor (ERα and ERβ)-mediated estrogenic activities in relation to breast cancer risk. Breast cancer cases had higher levels of estrogens and estrogen receptor mediated bioactivities in baseline serum than controls. Compared to the lowest quartile, women in the highest quartile for estrone or ERα-mediated bioactivity had increased breast cancer risk. After additional adjustment for ERβ bioactivity, free E2 and estrone; serum ERα-mediated estrogenic activity remained associated with increased breast cancer risk. Compared to the lowest quartile, women in the highest quartile for ERα-mediated bioactivity had an odds ratio of 2.39 (95% confidence interval=1.17–4.88, p for trend=0.016). Conversely, the positive association between estrone and cancer risk became null after adjustment for ERα-mediated estrogenic activity, suggesting that the effect of estrone could be mediated through ERα. Identification of the factor(s) contributing to increased ERα-mediated estrogenic bioactivity in sera, and its role as a predictor for breast cancer risk needs to be validated in future studies.

Keywords: breast cancer, estrogen, estrogen receptor, estrogen receptor bioassay

Introduction

There is ample experimental, epidemiologic and clinical evidence linking estrogens and breast cancer risk (Henderson and Feigelson 2000; Russo and Russo 2006). Several established risk factors for breast cancer are strongly associated with sex hormone levels, suggesting that these factors affect the estrogen-signaling pathway to impact breast cancer risk (Key, et al. 2011). Endogenous hormone levels have been used to estimate breast cancer risk in nine previous prospective studies done among postmenopausal women (Key, et al. 2002). An analysis of pooled data from these studies showed that postmenopausal women with relatively high serum concentrations of sex hormones such as estradiol and testosterone had a roughly two-fold higher risk for breast cancer compared to women with lower levels. Of those studies, all but one in Japan (Kabuto, et al. 2000), were conducted in North America or Europe where women were known to have higher body mass index compared to their leaner Asian counterparts, and also more likely to use hormone replacement therapy. Obesity could contribute to higher estrogen levels since adipose tissues are a source of estrogen in postmenopausal women (Siiteri 1987). Furthermore, marked differences in circulating estrogen concentrations have been reported between Asian and Caucasian women (Bernstein, et al. 1990; Shimizu, et al. 1990; Wu and Pike 1995).

The estrogen receptor (ER) α and β bioassays are classically used to identify estrogenic compounds present in the environment, or to detect persistent organic pollutants in the serum of humans (Djiogue, et al. 2010; Du, et al. 2010; Hjelmborg, et al. 2006; Kanno, et al. 2007; Kruger, et al. 2008). Recently, use of the ERα assay have demonstrated that ERα mediated bioactivity is serum can predict hip fracture risk in menopausal women (Lim, et al. 2012). The strength of such ER bioassays is that the overall effects of all factors (known and unknown) on estrogen receptor activation can be quantified. These ER bioassays therefore measure summated activity of all agonists and antagonists that either activate or inhibit the ER.

In terms of breast cancer, the bioactivities of both ERα and ERβ have been shown to be independently associated with increased risk in European studies (Fourkala, et al. 2012; Widschwendter, et al. 2009). Specifically, in a case-control study conducted in Germany, women in the highest quintile of both serum ERα and ERβ bioactivities had approximately seven times the risk of breast cancer compared to women in lower levels of both receptor bioactivities (Widschwendter et al. 2009). More recently, in a case-control study nested in a cohort of women in UK, ERα bioactivity was shown to be independently associated with breast cancer risk in serum collected more than two years before diagnosis for breast cancer cases (Fourkala et al. 2012). These studies suggest that assays for serum ERα and ERβ bioactivity may be useful in the prediction and management of breast cancer at a population level as well as at clinical setting.

Singapore Chinese women are currently experiencing one of the highest rates of increase in breast cancer incidence globally. Over the past 35 years from 1970 to 2005, incidence of breast cancer in Singapore has tripled from 20.0 to 60.0 per 100,000 (National Registry of Diseases Office, 2008). Factors causing the rapid increase in this historically low-risk population are largely unclear. Utilizing prospectively collected questionnaire data and serum from women of a population-based cohort study in Singapore, we investigated the associations between levels of estrogens and estrogen receptor-mediated bioactivity and breast cancer risk among postmenopausal women in an Asian country. We provide evidence to suggest that factors other than estrone and estradiol may activate ERα-mediated signaling pathways to increase breast cancer risk.

Methods

Study population

Both cases and controls were participants of the Singapore Chinese Health Study, a population-based prospective cohort of 63,257 Chinese subjects (including 35,298 women) who were of ages 45 to 74 years during recruitment between April 1993 and December 1998 (Hankin, et al. 2001). All participants of this cohort were residents of government-subsidized housing schemes, in which the majority (86%) of Singaporeans resided at the time of recruitment. Study subjects were restricted to the two major Chinese dialect groups: Hokkien and Cantonese, who originated from two contiguous prefectures in southern China. The Institutional Review Board at the National University of Singapore approved this study.

At recruitment, subjects were interviewed in-person using a structured questionnaire to collect information on the use of tobacco, medical history, as well as a dietary component assessing current intake patterns. In addition, information on menstrual (including menopausal status) and reproductive (including use of menopausal hormone therapy) histories were collected from the women. Between April 1994 and December 1999, blood and single-void urine specimens were collected from a random 3% sample of study enrollees. Details of the biospecimen collection, processing and storage procedures have been described previously (Koh, et al. 2003b). Between January 2000 and April 2005, we extended our biospecimen collection to all surviving cohort members and collected biospecimens (blood/buccal cells and urine) from 32,575 participants, representing a consent rate of about 60% of surviving cohort participants at that time. Among the 35,298 women in this cohort, 15,415 (44%) gave blood for research. Only postmenopausal women without a history of breast cancer at recruitment were included for the present study.

Case ascertainment

Incident breast cancer cases were identified through the population-based cancer registry in Singapore (National Registry of Diseases Office, 2008). All cases were further verified by manual checking of pathological and medical records. As of 28 June 2010, among 25,584 women who were postmenopausal at recruitment, 573 had developed breast cancer. Among them, 169 women with breast cancer had donated blood prior to cancer diagnosis and were included as cases in this study. Compared to the other breast cancer patients who did not donate a blood sample, cases in this study were younger at diagnosis (66.7 versus 64.9 years). Patients who did not donate blood samples were less educated (45.3% had no formal education) than those who did (20.7% had no formal education). Those who did not donate biospecimens were also more likely to have advanced stage of breast cancer but less likely to use hormone replacement compared to those who donated. Otherwise, there was no significant difference in body mass index or prevalence of positive family history for breast cancer between the two groups of breast cancer patients.

Control selection

For each of the 169 cases, up to three control subjects were randomly selected among all female cohort participants who had donated blood samples, and who were alive and free of breast cancer history at the time of cancer diagnosis of their index case. The chosen controls were matched to the index case on age at study enrollment (±3 years), dialect group (Hokkien, Cantonese), dates of study enrollment (±2 year) and of blood collection (±6 months). Among the 169 cases, there were 19 cases having only one eligible control each and 43 cases having only two controls each. The other 107 cases had three controls each.

Blood analysis

Serum samples of a given matched set (containing the samples from the case and one to three matched controls) were arranged in random order, identified only by unique codes, and tested in the same laboratory batch for all measurements. Laboratory personnel were blinded to case or control status of the samples. Serum samples were thawed at 4°C and individually filtered via 0.22 μm sterile cartridges. Filtered sera were collected in aliquots for measurements of estrone, estradiol, sex hormone binding globulin (SHBG) and ERα and ERβ mediated estrogenic activity.

Serum estrone and estradiol were measured with liquid chromatography tandem mass spectrometer using d4-estrone and d5-estradiol as internal standards, as reported previously (Nelson, et al. 2004). The respective intra- and inter-assay variability [coefficient of variation (%)] ranges for estradiol were 3.9–14.5% (mean = 8.7%) and 1.2–13.3% (mean = 6.3%) under the condition of 10–1,000 pM estradiol, respectively. The corresponding figures for estrone were 1.3–15.7% (mean =8.2%) and 1.7–11.5% (mean =5.4%) under the condition of 25–1,000 pM estrone.

Serum SHBG concentrations were quantified by a solid-phase, two-site chemiluminescent immunoassay using the Immulite Analyzer [Siemens Medical Solutions USA Inc (Malvern, PA, USA)]. The solid phase is a polystyrene bead with a monoclonal antibody specific for SHBG. The intra- assay and inter-assay Relative Standard Deviation for SHBG in the range of 2–18 nM were 6.7% and 2.0%, respectively. Percent free estradiol was calculated from serum SHBG levels based on the following regression model: Percent free estradiol= −0.01533 × serum SHBG + 2.921 (Langley, et al. 1985). Free estradiol level for each subject was then computed as the product of percent free estradiol and total estradiol level.

Biological activity of estrogens in serum was assessed using a validated estrogen-driven recombinant cell bioassay (Li, et al. 2009; Wong, et al. 2007). Human uterine cervical HeLa cells [ATCC (Manassas, VA, USA)] were transformed to stably express either ERα (ESR1) or ERβ (ESR2). When exposed to test sera, luciferase activity expressed from these transformed HeLa cells reflect estrogenic bioactivity through 4 tandem copies of a consensus estrogen response element coupled to a luciferase gene stably incorporated into the genome. Such luciferase activity measured the summated bioactivity of estrogenic ligands in serum. Expression levels of ERα or ERβ in these recombinant cell lines were confirmed with immunoblotting. Strong expressions of ERα or ERβ protein were detected in the ERα or ERβ cell lines respectively (Figure 1A). HeLa cells do not express ERα, and the ERβ-stable cell line does not contain any detectable ERα protein. HeLa cells do express low levels of ERβ and the ERα-stable cell line reflects this, although the predominant receptor is ERα. In the presence of the natural ligands estrone and estradiol, the ERα and ERβ-cell lines exhibit dose-dependent bioactivity (Figure 1B).

Figure 1.

Figure 1

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Estrogen Receptor Bioassay. A) Immunoblot of ERα and ERβ proteins in stably transfected HeLa cells. Total cellular proteins were extracted from ERα or ERβ stably transfected HeLa cells, and the presence of ERα and ERβ proteins was detected with specific monoclonal antibodies. MCF-7 and MDA-MB-231 cell lysates were used as a positive and negative controls for ERα respectively. HeLa cells are original cells without any transfection of ERα or ERβ.

B) Dose-dependent activation of luciferase reporter gene in ERα and ERβ cells by estradiol(E2) and estrone(E1). Medium with 10% CT FBS was spiked with E2 and E1. Readings were expressed as % of highest activation of estradiol at 10nM.

C) Representative calibration curves of ER-driven reporter gene bioassays for quantification of ER- mediated bioactivity of serum samples.

Recombinant cells were passaged, plated in a 96 well plate in 10% charcoal treated (CT) FBS and allowed to adhere overnight. Culture medium was then removed and replaced with incremental amounts of estradiol in 10% male human serum [Sigma Chemical (St. Louis, MO, USA)] stripped of steroids using charcoal treatment for calibration standards. Stock solutions of estradiol were prepared in serum and diluted to 10% using culture medium media (Eagle’s Minimum Essential Medium) and duplicates of each concentration were included in the plate. Similarly test serum was also diluted to 10% using culture media and added to the cells in duplicates. Baseline level of estradiol in charcoal treated human serum is about 20pM tested using liquid chromatography tandem mass spectrometry. After an incubation period of 24 hours, medium was decanted, and cells were washed with phosphate saline buffer lysed with Mammalian Protein Extraction Reagent (MPER) from Thermo scientific (Rockford, IL USA). Luciferase activity was measured using the Luciferase Assay System (Promega (Madison, WI,USA)) on the Glomax 96-well Microplate Luminometer (Promega (Madison, WI,USA)).

All test sera were tested on the same day using the same batch of cells. Calibration standards and QC (quality control) samples were included in every 96-well plate. Readings from the plate were used if QC samples in that plate had relative errors of <30%. If the relative error was >30%, the assay would be repeated. The mean (SD) of relative errors for ERα bioassay was 5.85% (5.16) and for ERβ bioassay is 11.51% (7.87).

Calibration curves were fitted with a regression model that visually best fits the points within the range of the test samples and maximizes the correlation coefficient (R2) value. The R2 value for ERα and ERβ ranged from 0.96–0.99. Total estrogen-mediated activity was calculated based on the average luminescence readings for each test sera and was expressed as pM estradiol equivalent obtained by interpolation from calibration curves in each plate. Microsoft Excel software was used for curve fitting and interpolation. For the ERα bioassay, the calibration curve ranged from 5pM to 70pM, with intra- and inter-assay RSDs of 6% and 14%, respectively (Figure 1C, upper panel). For the ERβ bioassay, the calibration curve ranged from 5pM to 250pM and the intra- and inter-assay RSDs were 8.1% and 16%, respectively (Figure 1C lower panel). Five serum samples had ERβ values below detection limit and were thus omitted from the analysis.

Statistical analysis

The distributions of all biomarkers measured were markedly skewed with a long tail toward high values, which were corrected, to a large extent, by transforming the original values to logarithmic values. Therefore, formal statistical test was performed on logarithmically transformed values, and geometric (as opposed to arithmetic) means were presented. The analysis of covariance (ANCOVA) method was used to examine the differences in the concentrations of serum biomarkers between breast cancer cases and control subjects with adjustment for other covariates, namely, body mass index (<20, 20–<24, 24–<28, and 28+ kg/m2), number of live births (none, one to two, three to four, five or more), age at menarche (<13, 13–14, 15–16, 17+ years), use of hormone replacement (yes, no) and family history of breast cancer (yes, no). We also included set-number as a covariate to account for the matched case-control design in this study.

We used the conditional logistic regression method to examine the associations between serum biomarkers measured and risk of breast cancer in our main analysis. For sub-analysis involving stratification by receptor positivity of breast cancer cases and time between blood draw and diagnosis, unconditional logistic regression models that included all the controls in this study were used to examine the association between serum biomarkers and breast cancer risk. In this study, our aim is to see how estrogen levels and bioactivity in cases compared to the controls may affect the risk of breast cancer. Hence, study subjects were grouped into quartiles of individual serum parameters based on their distributions among control subjects because they formed the baseline or comparison group. Furthermore, in the general population, since the number of women without breast cancer far outnumbers those with breast cancer, the levels in a population are essentially defined by the levels in the controls. The magnitude of the association was assessed by odds ratio (OR) and its corresponding 95% confidence interval (CI) and P value. Additional analysis also included quartile levels of estrone, free estradiol, SHBG and ERα and ERβ-mediated bioactivity in the same model. For the unconditional logistic regression analyses, age at blood draw was included as a covariate. All analyses were carried out using the SAS version 9.1 (SAS Institute Inc, Cary, North Carolina). All P values quoted were two-sided. The statistical significance level was set at two-sided P value of 0.05.

Results

Among the 169 cases of breast cancer, the mean time interval from blood draws to the occurrence of breast cancer was 4.0 years [standard deviation (SD) 2.5 years)], and only 43 cases (25%) had blood drawn within 2 years before cancer diagnosis. The mean age at cancer diagnosis was 64.9 (SD 7.5; range 48.3–82.0) years. Compared to controls, a higher proportion of women with breast cancer had BMI≥24 kg/m2, had secondary school education or higher, was nulliparous or had fewer live births, and was older at age of first live-birth, which were observations similar to previous results published from this cohort of women (Koh, et al. 2003a). Only 6.1% among controls and 10.7% among cases used hormone replacement therapy (Table 1).

Table 1.

Baseline characteristics of breast cancer cases and controls [mean (standard deviation) or number (percent)], The Singapore Chinese Health Study

Cases (n =169) Controls (n =426)
Mean age at blood taken (years) 60.9 (7.2) 60.0 (6.5)
Body mass index (kg/m2)
 <20 16 (9.5) 45 (10.6)
 20–24 86 (50.9) 246 (57.8)
 24–28 50 (29.6) 109 (25.6)
 28+ 17 (10.1) 26 (6.1)
Dialect (%)
 Cantonese 96 (56.8) 249 (58.5)
 Hokkien 73 (43.2) 177 (41.5)
Level of education (%)
 No formal education 35 (20.7) 109 (25.6)
 Primary school 81 (47.9) 195 (45.8)
 Secondary and above 53 (31.4) 122 (28.6)
Age at menarche (years)
 <13 27 (16.0) 82 (19.3)
 13–14 77 (45.6) 164 (38.5)
 15–16 52 (30.8) 139 (32.6)
 17+ 13 (7.6) 41 (9.6)
Number of live births
 None 20 (11.8) 32 (7.5)
 1–2 61 (36.1) 134 (31.5)
 3–4 54 (31.9) 184 (43.2)
 5+ 34 (20.1) 76 (17.8)
Use of menopausal hormone therapy (%) 18 (10.7) 26 (6.1)
Family history of breast cancer 4 (2.4) 5 (1.2)
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Breast cancer cases tended to have raised circulating serum levels of estrone, estradiol, free estradiol, ERα- and ERβ-mediated estrogenic activity, but lower serum SHBG levels than controls, although only the differences for estrone, free estradiol and ERα-mediated estrogenic activity levels reached statistical significance (Table 2). After adjusting for body mass index, number of live births, age at menarche, use of hormone replacement and family history of breast cancer; borderline dose-dependent activity was observed for estrone which exhibited a 60% increase in risk for women in the highest quartile relative to those in quartile one (OR: 1.60; 95% CI: 0.94–2.72; p for trend=0.05) (Table 3). There were no clear dose-dependent associations between serum total estradiol, free estradiol, SHBG and ERβ-mediated activity levels and risk of breast cancer. Strikingly, compared to women in the lowest quartile, ERα-mediated bioactivity was associated with a dose-dependent increase in breast cancer risk from a 45% higher risk in quartile two to 159% higher risk in the highest quartile (OR: 2.59; 95% CI: 1.44–4.65; p for trend=0.001) (Table 3). Reanalysis done with minimal value (20pM) assigned to five values of ERβ below the limit of detection showed essentially the same results; there was no significant association between serum ERβ levels and breast cancer risk. To examine independent effect of individual estrogenic factors measured on breast cancer risk, further adjustment for estrone, free estradiol, SHBG, and ERα- and ERβ-mediated bioactivity were conducted (Table 3, last column). After adjusting for ERα-mediated activity, the dose-dependent relationship between estrone and breast cancer risk was no longer evident, the ORs (95% CI) for those in quartiles 2, 3 and 4 were 0.80 (0.45–1.42), 0.88 (0.49–1.57) and 1.08 (0.58–1.99), respectively (p for trend=0.74), suggesting that ERα-mediated bioactivity was primarily responsible for the effect of estrone on breast cancer risk. Additional adjustment for free estradiol, SHBG and ERβ bioactivity did not materially change the risk estimates (Table 3). In contrast, even after adjusting for estrone, free estradiol levels, SHBG and ERβ bioactivity, the strong association with ERα-mediated activity was essentially unaltered with a 2.4-fold increase (OR = 2.39; 95% CI 1.17–4.88; p=0.016) in breast cancer risk (Table 3). To further delineate the role of serum ERα bioactivity, we also performed an analysis to compare risk in ERα-positive or ERα-negative tumors. ER receptor status was available for 58.6% of breast cancer cases. There were 69 ERα-positive and 30 ERα-negative breast cancer diagnoses. The results suggested that the positive association between ERα-mediated activity and breast cancer risk remained present in both subtypes of breast cancer. Compared to the lowest quartile, the ORs (95% CI) for women in the highest quartile were statistically significant at 2.43 (1.00–5.94) for ER positive breast cancer and 3.63 (1.01–13.08) for ER negative breast cancer (Table 4).

Table 2.

Geometric means (95% confidence interval) of serum biomarkers in postmenopausal breast cancer cases and controls, The Singapore Chinese Health Study

Cases (n=169) Controls (n=426) 2-sided P*
Estrone (pM) 404.70 (355–461.36) 335.96 (308.28–366.12) 0.02
Estradiol (pM) 66.26 (57.26–76.66) 58.82 (53.46–64.74) 0.19
SHBG (nM) 44.60 (41.32–48.16) 47.62 (45.3–50.08) 0.16
Free estradiol (pM) 1.38 (1.2–1.6) 1.16 (1.06–1.28) 0.05
ERα activity (pM estradiol equivalent) 25.54 (24.66–26.44) 24.40 (23.84–24.96) 0.03
ERβ activity (pM estradiol equivalent) 25.22 (24.24–26.24) 24.22 (23.6–24.86) 0.10
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*

Adjusted for body mass index, number of live births, age at menarche, use of hormone replacement and family history of breast cancer

Table 3.

Serum estrogenic parameters and risk of postmenopausal breast cancer, The Singapore Chinese Health Study

Biomarker Range Cases Controls Model 1
OR (95% CI)a 		Model 2
OR (95% CI)b 		Model 3
OR (95% CI)c
Estrone
 Q1 23.65–205.5 37 106 1.00 1.00 1.00
 Q2 207.5–284.0 33 106 0.86 (0.49–1.51) 0.87 (0.49–1.54) 0.83 (0.45–1.51)
 Q3 285.5–455.5 39 107 1.02 (0.59–1.75) 1.10 (0.63–1.92) 0.90 (0.49–1.66)
 Q4 >=457.5 60 105 1.63 (0.97–2.73) 1.60 (0.94–2.72) 1.32 (0.63–2.75)
P for trend 0.04 0.05 0.54
Estradiol
 Q1 4.365–34.3 33 106 1.00 1.00 1.00
 Q2 34.4–50.25 42 107 1.21 (0.69–2.14) 1.15 (0.64–2.06) 1.01 (0.54–1.89)
 Q3 50.35–76.6 47 105 1.42 (0.80–2.50) 1.43 (0.80–2.54) 1.17 (0.61–2.26)
 Q4 >=76.95 47 106 1.40 (0.80–2.46) 1.33 (0.75–2.36) 0.78 (0.37–1.66)
P for trend 0.21 0.26 0.60
SHBG
 Q1 8.39–33.5 55 106 1.00 1.00 1.00
 Q2 33.7–47.4 34 106 0.62 (0.37–1.05) 0.65 (0.38–1.11) 0.72 (0.41–1.24)
 Q3 47.5–67.53 46 106 0.81 (0.49–1.33) 0.80 (0.47–1.34) 0.94 (0.55–1.61)
 Q4 >=68.1 34 106 0.61 (0.36–1.04) 0.65 (0.37–1.12) 0.74 (0.41–1.34)
P for trend 0.16 0.20 0.52
Free estradiol
 Q1 0.065–0.668 30 106 1.00 1.00 1.00
 Q2 0.673–1.04 42 106 1.33 (0.75–2.37) 1.29 (0.73–2.30) 1.07 (0.58–1.96)
 Q3 1.045–1.661 51 106 1.71 (0.97–3.00) 1.72 (0.97–3.03) 1.37 (0.74–2.54)
 Q4 >=1.666 46 106 1.56 (0.88–2.76) 1.47 (0.83–2.61) 0.78 (0.37–1.63)
P for trend 0.09 0.13 0.77
ERα activity
 Q1 12.39–21.01 26 107 1.00 1.00 1.00
 Q2 21.03–23.63 38 106 1.47 (0.81–2.66) 1.45 (0.79–2.64) 1.30 (0.69–2.45)
 Q3 23.66–26.64 41 106 1.64 (0.91–2.96) 1.60 (0.88–2.92) 1.44 (0.74–2.81)
 Q4 >=26.65 64 106 2.80 (1.58–4.97) 2.59 (1.44–4.65) 2.39 (1.17–4.88)
P for trend 0.0004 0.001 0.016
ERβ activity
 Q1 11.03–20.16 37 104 1.00 1.00 1.00
 Q2 20.22–24.46 40 104 1.07 (0.59–1.91) 1.01 (0.56–1.84) 0.99 (0.54–1.82)
 Q3 24.47–27.48 33 104 0.96 (0.48–1.94) 0.96 (0.47–1.95) 0.94 (0.46–1.94)
 Q4 >=27.51 54 104 1.74 (0.89–3.41) 1.53 (0.77–3.04) 1.41 (0.69–2.88)
P for trend 0.08 0.19 0.31
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a

Model 1: Unadjusted model

b

Model 2: Adjusted for body mass index (<20, 20–<24, 24–<28, and 28+ kg/m2), number of live births (none, one to two, three to four, five or more), age at menarche (<13, 13–14, 15–16, 17+ years), use of hormone replacement (yes, no) and family history of breast cancer (yes, no).

c

Model 3 was adjusted for covariates in model 1 and also quartile values of serum estrone, free estradiol or total estradiol (for SHBG), SHBG, ERα activity and ERβ activity.

OR: odds ratio; CI: confidence interval

Table 4.

Serum ERα-mediated bioactivity and risk of postmenopausal breast cancer according to ER status of cancer cases, the Singapore Chinese Health Study

Biomarker Cases Controls OR (95% CI)*
ER positive cancer
 ERα activity
  Q1 11 107 1.00
  Q2 17 106 1.46 (0.63–3.35)
  Q3 13 106 0.95 (0.39–2.34)
  Q4 28 106 2.43 (1.00–5.94)
 P for trend 0.10
ER negative cancer
 ERα activity
  Q1 5 107 1.00
  Q2 7 106 2.28 (0.66–7.88)
  Q3 9 106 3.26 (0.97–10.95)
  Q4 9 106 3.63 (1.01–13.08)
 P for trend 0.04
ER unknown cancer
 ERα activity
  Q1 10 107 1.00
  Q2 14 106 1.27 (0.53–3.07)
  Q3 19 106 1.56 (0.66–3.70)
  Q4 27 106 1.71 (0.70–4.20)
 P for trend 0.21
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Adjusted for body mass index (<20, 20–<24, 24–<28, and 28+ kg/m2), number of live births (none, one to two, three to four, five or more), age at menarche (<13, 13–14, 15–16, 17+ years), use of hormone replacement (yes, no), family history of breast cancer (yes, no) and quartile value of estrone and free estradiol levels.

OR: odds ratio; CI: confidence interval

Finally, we examined the association between ERα-mediated activity and breast cancer risk by time between blood draw and cancer diagnosis. Risk estimates obtained from analysis of cases with blood drawn within two years prior to cancer diagnosis were essentially similar to the estimates from analysis of cases with blood drawn two years or more. Although the p for trend was of borderline statistical significance (p=0.08) for the analysis limited to cases with blood drawn more than 2 years from cancer diagnosis, relative to the lowest quartile, women in the highest quartile in this group still had significantly increased breast cancer risk (OR = 2.15, 95% CI 1.07–4.33) (Table 5).

Table 5.

Serum ERα-mediated bioactivity and risk of postmenopausal breast cancer according to time between blood draw and cancer diagnosis for cases, the Singapore Chinese Health Study

Biomarker Cases Controls OR (95% CI)*
Within 2 years from blood draw to cancer diagnosis
 ERα activity
  Q1 8 107 1.00
  Q2 4 106 0.57 (0.16–2.02)
  Q3 11 106 1.46 (0.53–4.03)
  Q4 20 106 2.67 (0.94–7.54)
 P for trend 0.02
More than 2 years from blood draw to cancer diagnosis
 ERα activity
  Q1 18 107 1.00
  Q2 34 106 1.83 (0.95–3.50)
  Q3 30 106 1.48 (0.75–2.91)
  Q4 44 106 2.15 (1.07–4.33)
 P for trend 0.08
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Adjusted for body mass index (<20, 20–<24, 24–<28, and 28+ kg/m2), number of live births (none, one to two, three to four, five or more), age at menarche (<13, 13–14, 15–16, 17+ years), use of hormone replacement (yes, no), family history of breast cancer (yes, no) and quartile value of estrone and free estradiol levels.

OR: odds ratio; CI: confidence interval

Discussion

This is the first study to investigate the role of estrogens and ERα- and ERβ- mediated bioactivity on the risk of breast cancer in Chinese postmenopausal women. Our data showed that higher levels of ERα-mediated estrogenic activity in sera were associated with increased risk of cancer, and that estrogens, especially estrone, influenced cancer risk via interaction with ERα in the pathogenesis of postmenopausal breast cancer.

Geometric means of total free estradiol, estrone and ERα activity levels were significantly higher in pre-disease serum from breast cancer cases compared to controls. However, after dividing the biomarker levels into quartiles and looking at its association with risk of breast cancer, a borderline dose-dependent relationship was also observed with the highest quartile of estrone exhibiting 60% higher risk of breast cancer. Although high estradiol levels were known to be associated with higher risk of breast cancer in postmenopausal women (Baglietto, et al. 2010; Eliassen, et al. 2006; Farhat, et al. 2011; Kaaks, et al. 2005; Kabuto et al. 2000; Key, et al. 2003; Manjer, et al. 2003; Missmer, et al. 2004; Zeleniuch-Jacquotte, et al. 2004), the role of estrone in breast cancer carcinogenesis is less well appreciated. There is evidence that estrone levels, but not estradiol, can be higher depending on lifestyle factors. Japanese women born in USA have mean estrone levels higher than Caucasian counterparts, contrasting with the largely similar mean estradiol levels between these two populations (Probst-Hensch, et al. 2000). In that study, differences in estrone levels were still evident after adjustment for age, weight and androstenedione levels. On the other hand, Japanese women living in rural areas were found to have 43% lower estrone levels compared to weight and age-matched Caucasian women living in California (Wu & Pike, 1995), suggesting that the transition from a rural to urban lifestyle may have a contributory effect on high estrone levels. One lifestyle factor may be shift work, as women working graveyard night shifts have been reported to have significantly higher estrone levels (20 versus 11.5pg/ml) compared to those that never worked night shifts (Nagata, et al. 2008). Although estrone has 20 to 80% of the bioactivity of estradiol depending on the assay used (Fang, et al. 2000), its higher levels means that its contribution to overall estrogenicity and breast cancer risk is significant in the post-menopausal condition in our cohort. The challenge is to define the role of lifestyle modifications that may lower estrone levels and risk of breast cancer. The loss of statistically significant association with estrone levels in this study was primarily due to adjustment for ERα activity, and we deduced that the effect of estrone in the pathogenesis of postmenopausal breast cancer could be mediated via its binding to ERα.

Conversely, ERα-mediated bioactivity appeared to be an independent risk factor for breast cancer risk. Logistic regression analyses indicated that even after adjustment for known factors of estrogenic action such as estradiol, estrone and BMI; women whose ERα-mediated bioactivity was in the highest quartile still had significantly higher breast cancer risk compared to women in the lowest quartile, suggesting that other factor(s), besides estrone and estradiol, was acting via the ERα-mediated genomic signaling systems to increase breast cancer risk. This dose dependent increase in risk with high ERα-mediated bioactivity was evident for periods before 4 years and within 2 years of blood draw, indicating the robustness of the association. To our knowledge, this is the first study to use mammalian cell based bioassays to examine prospectively the relationship between ERα-mediated bioactivity and breast cancer risk. One recent UK study, utilizing a yeast-based reporter gene assay system, did not observe any overall relationship between cancer risk and receptor bioactivity. In this study (Fourkala et al. 2012), association between ERα-mediated bioactivity and breast cancer risk was only present in the subset of cases whose blood was collected more than 2 years before cancer diagnosis (Fourkala et al. 2012). This contradicted the findings from a case-control study that the same group of investigators had conducted in Germany using blood collected from cases after clinical diagnosis, and which showed a strong association between ERα bioactivity and cancer risk (Widschwendter et al. 2009). Differences between our study and that of the UK group could first be due to our use of mammalian cells, which are more physiologically relevant in differentiating between agonist and antagonist compared to yeast cell-based bioassays used by other investigators (Fourkala et al. 2012; Widschwendter et al. 2009). In addition, the coregulators involved in transactivation of estrogen sensitive reporter genes has been reported to be differ between yeast and mammalian systems (Kohno, et al. 1994).

Although the two most abundant estrogens present in the serum (estradiol and estrone) can bind to ERα and activate it, many other compounds in the serum are also known to be capable of activating the receptor. These include estrogen metabolites from birth control pills and endocrine disrupting compounds (EDCs) that have estrogenic activity. A wide range of synthetic endocrine disrupting chemicals such as dioxins and polychlorinated biphenyls, bisphenol A, pesticides (endosulfan, toxaphene, and dieldrin) are estrogenic compounds that can exert biological effects at trace concentrations and have the potential to provoke additive estrogenic mixture effects at low doses, even at no observed effect levels (Diamanti-Kandarakis, et al. 2009; Kandaraki, et al. 2011). Thus, ERα-mediated estrogenic activity could be a more comprehensive measurement of the combined effects of all known and unknown estrogenic compounds present in the sera of women, all of which could affect breast cancer risk. Our data indicating that the risk due to increased ERα-mediated bioactivity was independent of endogenous estrogens support the hypothesis that environmental factors may have a contributory factor in breast cancer risk in our cohort. More research is warranted to identify these endocrine-disrupting compounds. This is consistent with the rapid increase in breast cancer rates in rapidly modernizing Singapore.

While the UK study only included ER-positive cases (Fourkala et al. 2012), our study included both ER-positive and ER-negative breast cancer cases, and showed that ERα-mediated bioactivity was associated with increased risk for both subtypes of cancers, suggesting that ER negative cancers also depend on estrogenic activity for growth. Intriguingly, risk was highest in patients with ERα-negative tumors, rising to 15-fold higher risk within the highest quartile of ERα-bioactivity, suggesting that compounds that were activating ERα-genomic signaling cascade were also capable of activating other estrogenic signaling pathways in breast cancer tissues with absent or significantly lower levels of ERα. Reports from earlier studies showed that ovariectomy prevented the formation of both ERα -positive and ERα -negative breast cancers, thus suggesting that the estrogen-driven pathway could also play a part in the development of ER-negative breast cancer (1992). Hence, we hypothesize that our mammalian reporter gene assay has reflected the presence of estrogenic compounds present in the serum of ERα-negative breast cancer patients that may activate estrogen signaling in the absence of intact ERα. One example is membrane-bound ERα 36, a truncated estrogen sensitive receptor present in ER-negative breast cancer, which can mediate nongenomic estrogen signaling in the carcinogenesis of ER-negative tumors (Rao, et al. 2011).

Although our data was suggestive of a 1.5 times increase in risk of breast cancer for women in the highest quartile level, the breast cancer-risk association with of ERβ bioactivity did not reach statistical significance and was weaker than the association with ERα bioactivity. The role of ERβ in breast cancer has been controversial. Breast cancer patients who are treated with tamoxifen and have high expression levels of ERβ were found to have better response and longer survival time (Esslimani-Sahla, et al. 2004; Hopp, et al. 2004). On the other hand, in ERα -negative breast cancer, high ERβ expression is positively correlated with poor prognostic phenotypes (Skliris, et al. 2006). Some of these ligands with preferential binding to ERβ have been shown to be associated with decreased breast cancer risk. For example, genistein is a soy phytoestrogen possessing a high affinity for ERβ (Lee, et al. 2004), and higher soy intake has been shown to be associated with reduced risk of breast cancer (Iwasaki, et al. 2008; Wu, et al. 2008).

The strength of our study is the nesting of the study within a population-based prospective cohort that provides the use of questionnaire data and blood specimens collected before the occurrence of breast cancer to reduce recall and reverse causality bias. Cancer cases were identified using a comprehensive nationwide cancer registry. Limitations of this study are that the results are based on a blood sample collected at single time point, as the natural fluctuation of biomarkers that most likely occurred equally in both cases and controls could lead to the underestimation of the true associations with breast cancer risk. In this cohort, among postmenopausal women who gave blood for research, we limited the selection of cases to women who donated blood prior to the occurrence of breast cancer. Differences in factors such as age and use of hormone replacement between breast cancer cases included and those excluded in this study were accounted for either by matching or statistical adjustment in our analyses. Furthermore, willingness to donate blood for research should not influence the biomarker-breast cancer associations in this study. In addition, we acknowledge that the presence of existing occult tumors could play a role in the association between ERα mediated bioactivity and breast cancer risk in this group of patients with a average period of follow up of 4 years. Finally, the relatively small sample size, especially in the stratification by estrogen receptor positivity, does not give us sufficient power to detect significant difference in the levels of most of the blood parameters between cases and controls.

In conclusion, ERα-mediated estrogenic activity in sera was independently associated with significantly increased risk of postmenopausal breast cancer. The measurement of this serum biomarker in postmenopausal women may have the potential to be developed into a clinical index for the prediction of breast cancer risk or the monitoring of patients on chemopreventive strategies of breast cancer.

Acknowledgments

Funding: Singapore Cancer Society Cancer Research Grant (DRA Ref: 2010-09-083), Singapore National Medical Research Council (R-174-000-137-275), and National Institutes of Health, USA (NCI RO1 CA55069, R35 CA53890, R01 CA80205 and R01 CA144034).

We would like to thank Zhiwei Zhang for assistance in the bioassays and Huey Min Tan for assistance in the LC-MS/MS analysis of the samples. We would also like to thank Siew-Hong Low of the National University of Singapore for supervising the field work of the Singapore Chinese Health Study and Kazuko Arakawa and Renwei Wang for development of the cohort study database. Finally, we acknowledge the founding, long-standing Principal Investigator of the Singapore Chinese Health Study – Mimi C. Yu.

Footnotes

Competing interest

The authors declare that they have no competing interests

Authors’ contribution

W-P Koh and EL Yong conceived of the study. VW Lim, J Li, Y Gong and EL Yong carried out the biomarker assays. A Jin, J-M Yuan and W-P Koh performed the statistical analysis. VW Lim, J-M Yuan, W-P Koh and EL Yong drafted the manuscript. All authors edited and approved the final manuscript.

References

  1. Systemic treatment of early breast cancer by hormonal, cytotoxic, or immune therapy. 133 randomised trials involving 31,000 recurrences and 24,000 deaths among 75,000 women. Early Breast Cancer Trialists’ Collaborative Group. Lancet. 1992;339:71–85. [PubMed] [Google Scholar]
  2. Baglietto L, Severi G, English DR, Krishnan K, Hopper JL, McLean C, Morris HA, Tilley WD, Giles GG. Circulating steroid hormone levels and risk of breast cancer for postmenopausal women. Cancer Epidemiol Biomarkers Prev. 2010;19:492–502. doi: 10.1158/1055-9965.EPI-09-0532. [DOI] [PubMed] [Google Scholar]
  3. Bernstein L, Yuan JM, Ross RK, Pike MC, Hanisch R, Lobo R, Stanczyk F, Gao YT, Henderson BE. Serum hormone levels in pre-menopausal Chinese women in Shanghai and white women in Los Angeles: results from two breast cancer case-control studies. Cancer Causes Control. 1990;1:51–58. doi: 10.1007/BF00053183. [DOI] [PubMed] [Google Scholar]
  4. Diamanti-Kandarakis E, Bourguignon JP, Giudice LC, Hauser R, Prins GS, Soto AM, Zoeller RT, Gore AC. Endocrine-disrupting chemicals: an Endocrine Society scientific statement. Endocrine Reviews. 2009;30:293–342. doi: 10.1210/er.2009-0002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Djiogue S, Njamen D, Halabalaki M, Kretzschmar G, Beyer A, Mbanya JC, Skaltsounis AL, Vollmer G. Estrogenic properties of naturally occurring prenylated isoflavones in U2OS human osteosarcoma cells: Structure-activity relationships. J Steroid Biochem Mol Biol. 2010;120:184–191. doi: 10.1016/j.jsbmb.2010.04.014. [DOI] [PubMed] [Google Scholar]
  6. Du G, Shen O, Sun H, Fei J, Lu C, Song L, Xia Y, Wang S, Wang X. Assessing hormone receptor activities of pyrethroid insecticides and their metabolites in reporter gene assays. Toxicol Sci. 2010;116:58–66. doi: 10.1093/toxsci/kfq120. [DOI] [PubMed] [Google Scholar]
  7. Eliassen AH, Missmer SA, Tworoger SS, Hankinson SE. Endogenous steroid hormone concentrations and risk of breast cancer: does the association vary by a woman’s predicted breast cancer risk? J Clin Oncol. 2006;24:1823–1830. doi: 10.1200/JCO.2005.03.7432. [DOI] [PubMed] [Google Scholar]
  8. Esslimani-Sahla M, Simony-Lafontaine J, Kramar A, Lavaill R, Mollevi C, Warner M, Gustafsson J-A, Rochefort H. Estrogen receptor beta (ER beta) level but not its ER beta cx variant helps to predict tamoxifen resistance in breast cancer. Clin Cancer Res. 2004;10:5769–5776. doi: 10.1158/1078-0432.CCR-04-0389. [DOI] [PubMed] [Google Scholar]
  9. Fang H, Tong W, Perkins R, Soto AM, Prechtl NV, Sheehan DM. Quantitative comparisons of in vitro assays for estrogenic activities. Environ Health Perspect. 2000;108:723–729. doi: 10.1289/ehp.00108723. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Farhat GN, Cummings SR, Chlebowski RT, Parimi N, Cauley JA, Rohan TE, Huang AJ, Vitolins M, Hubbell FA, Manson JE, et al. Sex hormone levels and risks of estrogen receptor-negative and estrogen receptor-positive breast cancers. J Natl Cancer Inst. 2011;103:562–570. doi: 10.1093/jnci/djr031. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Fourkala EO, Zaikin A, Burnell M, Gentry-Maharaj A, Ford J, Gunu R, Soromani C, Hasenbrink G, Jacobs I, Dawnay A, et al. Association of serum sex steroid receptor bioactivity and sex steroid hormones with breast cancer risk in postmenopausal women. Endocr Relat Cancer. 2012;19:137–147. doi: 10.1530/ERC-11-0310. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Hankin JH, Stram DO, Arakawa K, Park S, Low SH, Lee HP, Yu MC. Singapore Chinese Health Study: development, validation, and calibration of the quantitative food frequency questionnaire. Nutr Cancer. 2001;39:187–195. doi: 10.1207/S15327914nc392_5. [DOI] [PubMed] [Google Scholar]
  13. Henderson BE, Feigelson HS. Hormonal carcinogenesis. Carcinogenesis. 2000;21:427–433. doi: 10.1093/carcin/21.3.427. [DOI] [PubMed] [Google Scholar]
  14. Hjelmborg PS, Ghisari M, Bonefeld-Jorgensen EC. SPE-HPLC purification of endocrine-disrupting compounds from human serum for assessment of xenoestrogenic activity. Anal Bioanal Chem. 2006;385:875–887. doi: 10.1007/s00216-006-0463-9. [DOI] [PubMed] [Google Scholar]
  15. Hopp TA, Weiss HL, Parra IS, Cui Y, Osborne CK, Fuqua SAW. Low levels of estrogen receptor beta protein predict resistance to tamoxifen therapy in breast cancer. Clin Cancer Res. 2004;10:7490–7499. doi: 10.1158/1078-0432.CCR-04-1114. [DOI] [PubMed] [Google Scholar]
  16. Iwasaki M, Inoue M, Otani T, Sasazuki S, Kurahashi N, Miura T, Yamamoto S, Tsugane S Japan Public Health Center-based prospective study g. Plasma isoflavone level and subsequent risk of breast cancer among Japanese women: a nested case-control study from the Japan Public Health Center-based prospective study group. J Clin Oncol. 2008;26:1677–1683. doi: 10.1200/JCO.2007.13.9964. [DOI] [PubMed] [Google Scholar]
  17. Kaaks R, Rinaldi S, Key TJ, Berrino F, Peeters PHM, Biessy C, Dossus L, Lukanova A, Bingham S, Khaw KT, et al. Postmenopausal serum androgens, oestrogens and breast cancer risk: the European prospective investigation into cancer and nutrition. Endocr Relat Cancer. 2005;12:1071–1082. doi: 10.1677/erc.1.01038. [DOI] [PubMed] [Google Scholar]
  18. Kabuto M, Akiba S, Stevens RG, Neriishi K, Land CE. A prospective study of estradiol and breast cancer in Japanese women. Cancer Epidemiol Biomarkers Prev. 2000;9:575–579. [PubMed] [Google Scholar]
  19. Kandaraki E, Chatzigeorgiou A, Livadas S, Palioura E, Economou F, Koutsilieris M, Palimeri S, Panidis D, Diamanti-Kandarakis E. Endocrine Disruptors and Polycystic Ovary Syndrome (PCOS): Elevated Serum Levels of Bisphenol A in Women with PCOS. J Clin Endocrinol Metab. 2011;96:E480–484. doi: 10.1210/jc.2010-1658. [DOI] [PubMed] [Google Scholar]
  20. Kanno Y, Okada H, Kobayashi T, Takenaka T, Suzuki H. Effects of endocrine disrupting substance on estrogen receptor gene transcription in dialysis patients. Ther Apher Dial. 2007;11:262–265. doi: 10.1111/j.1744-9987.2007.00472.x. [DOI] [PubMed] [Google Scholar]
  21. Key T, Appleby P, Barnes I, Reeves G, Endogenous H Breast Cancer Collaborative G. Endogenous sex hormones and breast cancer in postmenopausal women: reanalysis of nine prospective studies. J Natl Cancer Inst. 2002;94:606–616. doi: 10.1093/jnci/94.8.606. [DOI] [PubMed] [Google Scholar]
  22. Key TJ, Appleby PN, Reeves GK, Roddam A, Dorgan JF, Longcope C, Stanczyk FZ, Stephenson HE, Falk RT, Miller R, et al. Body mass index, serum sex hormones, and breast cancer risk in postmenopausal women. J Natl Cancer Inst. 2003;95:1218–1226. doi: 10.1093/jnci/djg022. [DOI] [PubMed] [Google Scholar]
  23. Key TJ, Appleby PN, Reeves GK, Roddam AW, Helzlsouer KJ, Alberg AJ, Rollison DE, Dorgan JF, Brinton LA, Overvad K, et al. Circulating sex hormones and breast cancer risk factors in postmenopausal women: reanalysis of 13 studies. Br J Cancer. 2011;105:709–722. doi: 10.1038/bjc.2011.254. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Koh W-P, Yuan J-M, Sun C-L, van den Berg D, Seow A, Lee H-P, Yu MC. Angiotensin I-converting enzyme (ACE) gene polymorphism and breast cancer risk among Chinese women in Singapore. Cancer research. 2003a;63:573–578. [PubMed] [Google Scholar]
  25. Koh WP, Yuan JM, Sun CL, van den Berg D, Seow A, Lee HP, Yu MC. Angiotensin I-converting enzyme (ACE) gene polymorphism and breast cancer risk among Chinese women in Singapore. Cancer Res. 2003b;63:573–578. [PubMed] [Google Scholar]
  26. Kohno H, Gandini O, Curtis SW, Korach KS. Anti-estrogen activity in the yeast transcription system: estrogen receptor mediated agonist response. Steroids. 1994;59:572–578. doi: 10.1016/0039-128x(94)90050-7. [DOI] [PubMed] [Google Scholar]
  27. Kruger T, Spano M, Long M, Eleuteri P, Rescia M, Hjelmborg PS, Manicardi GC, Bizzaro D, Giwercman A, Toft G, et al. Xenobiotic activity in serum and sperm chromatin integrity in European and inuit populations. Mol Reprod Dev. 2008;75:669–680. doi: 10.1002/mrd.20747. [DOI] [PubMed] [Google Scholar]
  28. Langley MS, Hammond GL, Bardsley A, Sellwood RA, Anderson DC. Serum steroid binding proteins and the bioavailability of estradiol in relation to breast diseases. J Natl Cancer Inst. 1985;75:823–829. doi: 10.1093/jnci/75.5.823. [DOI] [PubMed] [Google Scholar]
  29. Lee GS, Choi KC, Kim HJ, Jeung EB. Effect of genistein as a selective estrogen receptor beta agonist on the expression of Calbindin-D9k in the uterus of immature rats. Toxicol Sci. 2004;82:451–457. doi: 10.1093/toxsci/kfh296. [DOI] [PubMed] [Google Scholar]
  30. Li J, Lee L, Gong Y, Shen P, Wong SP, Wise SD, Yong EL. Bioassays for Estrogenic Activity: Development and Validation of Estrogen Receptor (ERalpha/ERbeta) and Breast Cancer Proliferation Bioassays to Measure Serum Estrogenic Activity in Clinical Studies. Assay and Drug Development Technologies. 2009;7:80–89. doi: 10.1089/adt.2008.154. [DOI] [PubMed] [Google Scholar]
  31. Lim VW, Li J, Gong Y, Yuan JM, Wu TS, Hammond GL, Jin A, Koh WP, Yong EL. Serum free estradiol and estrogen receptor-alpha mediated activity are related to decreased incident hip fractures in older women. Bone. 2012;50:1311–1316. doi: 10.1016/j.bone.2012.03.006. [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Manjer J, Johansson R, Berglund G, Janzon L, Kaaks R, Agren A, Lenner P. Postmenopausal breast cancer risk in relation to sex steroid hormones, prolactin and SHBG (Sweden) Cancer Causes Control. 2003;14:599–607. doi: 10.1023/a:1025671317220. [DOI] [PubMed] [Google Scholar]
  33. Missmer SA, Eliassen AH, Barbieri RL, Hankinson SE. Endogenous estrogen, androgen, and progesterone concentrations and breast cancer risk among postmenopausal women. J Natl Cancer Inst. 2004;96:1856–1865. doi: 10.1093/jnci/djh336. [DOI] [PubMed] [Google Scholar]
  34. Nagata C, Nagao Y, Yamamoto S, Shibuya C, Kashiki Y, Shimizu H. Light exposure at night, urinary 6-sulfatoxymelatonin, and serum estrogens and androgens in postmenopausal Japanese women. Cancer Epidemiol Biomarkers Prev. 2008;17:1418–1423. doi: 10.1158/1055-9965.EPI-07-0656. [DOI] [PubMed] [Google Scholar]
  35. National Registry of Diseases Office. Trends in Cancer Incidence in Singapore 1968–2007. Singapore: Health Promotion Board; 2008. [Google Scholar]
  36. Nelson RE, Grebe SK, DJOK, Singh RJ. Liquid chromatography-tandem mass spectrometry assay for simultaneous measurement of estradiol and estrone in human plasma. Clin Chem. 2004;50:373–384. doi: 10.1373/clinchem.2003.025478. [DOI] [PubMed] [Google Scholar]
  37. Probst-Hensch NM, Pike MC, McKean-Cowdin R, Stanczyk FZ, Kolonel LN, Henderson BE. Ethnic differences in post-menopausal plasma oestrogen levels: high oestrone levels in Japanese-American women despite low weight. Br J Cancer. 2000;82:1867–1870. doi: 10.1054/bjoc.1999.1082. [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Rao J, Jiang X, Wang Y, Chen B. Advances in the understanding of the structure and function of ER-alpha36, a novel variant of human estrogen receptor-alpha. J Steroid Biochem Mol Biol. 2011;127:231–237. doi: 10.1016/j.jsbmb.2011.08.004. [DOI] [PubMed] [Google Scholar]
  39. Russo J, Russo IH. The role of estrogen in the initiation of breast cancer. J Steroid Biochem Mol Biol. 2006;102:89–96. doi: 10.1016/j.jsbmb.2006.09.004. [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Shimizu H, Ross RK, Bernstein L, Pike MC, Henderson BE. Serum oestrogen levels in postmenopausal women: comparison of American whites and Japanese in Japan. Br J Cancer. 1990;62:451–453. doi: 10.1038/bjc.1990.316. [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Siiteri PK. Adipose tissue as a source of hormones. Am J Clin Nutr. 1987;45:277–282. doi: 10.1093/ajcn/45.1.277. [DOI] [PubMed] [Google Scholar]
  42. Skliris GP, Leygue E, Curtis-Snell L, Watson PH, Murphy LC. Expression of oestrogen receptor-beta in oestrogen receptor-alpha negative human breast tumours. Br J Cancer. 2006;95:616–626. doi: 10.1038/sj.bjc.6603295. [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Widschwendter M, Lichtenberg-Frate H, Hasenbrink G, Schwarzer S, Dawnay A, Lam A, Menon U, Apostolidou S, Raum E, Stegmaier C, et al. Serum oestrogen receptor alpha and beta bioactivity are independently associated with breast cancer: a proof of principle study. Br J Cancer. 2009;101:160–165. doi: 10.1038/sj.bjc.6605106. [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Wong SP, Li J, Shen P, Gong Y, Yap SP, Yong EL. Ultrasensitive cell-based bioassay for the measurement of global estrogenic activity of flavonoid mixtures revealing additive, restrictive, and enhanced actions in binary and higher order combinations. Assay Drug Dev Technol. 2007;5:355–362. doi: 10.1089/adt.2007.056. [DOI] [PubMed] [Google Scholar]
  45. Wu AH, Koh WP, Wang R, Lee HP, Yu MC. Soy intake and breast cancer risk in Singapore Chinese Health Study. Br J Cancer. 2008;99:196–200. doi: 10.1038/sj.bjc.6604448. [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Wu AH, Pike MC. Dietary soy protein and hormonal status in females. Am J Clin Nutr. 1995;62:151–153. doi: 10.1093/ajcn/62.1.151. [DOI] [PubMed] [Google Scholar]
  47. Zeleniuch-Jacquotte A, Shore RE, Koenig KL, Akhmedkhanov A, Afanasyeva Y, Kato I, Kim MY, Rinaldi S, Kaaks R, Toniolo P. Postmenopausal levels of oestrogen, androgen, and SHBG and breast cancer: long-term results of a prospective study. Br J Cancer. 2004;90:153–159. doi: 10.1038/sj.bjc.6601517. [DOI] [PMC free article] [PubMed] [Google Scholar]

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