Kabat, Geoffrey C.*; O'Leary, Erin S.†; Gammon, Marilie D.‡; Sepkovic, Daniel W.§¶; Teitelbaum, Susan L.∥; Britton, Julie A.∥; Terry, Mary B.**; Neugut, Alfred I.**††; Bradlow, H Leon§¶
Specific pathways involved in estrogen metabolism may play a role in the etiology of breast cancer.1–3 Broadly speaking, there are 2 contending, and perhaps complementary, schools of thought concerning which metabolites are relevant. Schneider et al4 proposed that 2-hydroxyestrone (2-OHE1) and 16α-hydroxyestrone (16-OHE1) influence breast cancer risk. They cite evidence that the 2 metabolites have different biologic activities: 16-OHE1 is a potent estrogen and has uterotopic activity similar to estradiol, whereas 2-OHE1 is weakly estrogenic and possibly antiestrogenic.5 Furthermore, 16-OHE1 forms covalent bonds with amino groups of macromolecules and is genotoxic.6,7 Based on these findings, Bradlow et al8 have suggested that the ratio of 2-OHE1/16-OHE1 (2/16 ratio) may serve as a marker of breast cancer risk. A second school of thought argues that the catechol estrogens, particularly 4-hydroxyestrogens (4-OHE), play a key role in breast carcinogenesis by virtue of their ability to be further oxidized to form reactive semi-quinones and quinones capable of forming direct adducts with glutathione and purines in DNA.9,10 4-OHE also can undergo redox cycling to generate reactive oxygen species that can cause oxidative damage.9,10
To date, only a small number of studies have examined the association of estrogen metabolites with breast cancer in women. Two early studies used a radiometric assay11 and gas chromatography-mass spectroscopy,12 but interpretation of the results is hampered by the small number of patients and by lack of adjustment for potential confounding factors in the statistical analysis. More recent studies have used an enzyme immunoassay method to measure 2-OHE1 and 16-OHE1.13–20 Existing studies have had different designs, have been conducted in different populations, and some have extremely small sample sizes. Their results are inconsistent, with some showing a strong inverse association of increasing levels of the 2-OHE1/16-OHE1 ratio with breast cancer,13,14 some showing a modest association,15,17–19 and still others showing no association.16,20 A recent study conducted in China17 found an inverse association of the 2/16 ratio with breast cancer using urine samples collected before surgery but a positive association using postsurgery samples. A low-cost assay has been developed using gas chromatography-mass spectroscopy to measure estrone, estradiol, 2-OHE, 4-OHE, 16-OHE, and estriol,21 but epidemiologic studies using this assay are not yet available.
We report here on the results of a large population-based case–control study of breast cancer on Long Island in which rapid ascertainment was used to obtain as many biologic specimens as possible before major treatment, especially chemotherapy. Enzyme-immunoassay was used to measure 2-OHE1 and 16-OHE1. In addition to women with invasive breast cancer, a group of women with newly diagnosed in situ cancer of the breast was examined separately.
A spot urine sample was obtained as part of the Long Island Breast Cancer Study Project, a population-based case–control study of breast cancer in residents of Nassau and Suffolk Counties on Long Island, New York. The background, design, and recruitment of the Long Island Breast Cancer Study Project have been described in detail.22 Briefly, cases were women newly diagnosed with a first primary in situ or invasive breast cancer between 1 August 1996 and 31 July 1997. Rapid ascertainment of cases through daily and weekly contacts with pathologists was instituted to obtain blood and urine samples before chemotherapy. Physicians of potentially eligible case women were contacted to confirm the diagnosis and the date of diagnosis, and for permission to contact the women. Control women were a random sample of current Nassau and Suffolk county residents who spoke English and who were frequency-matched to the expected distribution of cases by 5-year age group. Control patients were identified through random-digit dialing for women younger than 65 years of age and via Health Care Financing Administration (HCFA) rosters for women 65 years and older. The study protocol and consent form were approved by the institutional review boards of all collaborating institutions.
After an initial contact to determine eligibility, study interviewers visited each subject's home to administer a comprehensive questionnaire and obtain a blood and urine specimen. Written informed consent was obtained from all participants. The average interval between the reference date (date of diagnosis for cases and date of identification for controls) and interview date was 96 days for case and 167 days for control subjects. Participation rates for the interview were 82% among case and 62% among control subjects. A spot urine sample was obtained from 1403 case (93.0%) and 1296 control (83.3%) subjects. Urines were treated with sodium ascorbate as a preservative and shipped on ice by overnight courier to Columbia University for aliquotting and storage at −80°C.23 At the time of urine collection, each woman was asked to fill out a specimen checklist, which inquired about the date of last menstrual period if she was still menstruating; selected foods and medications used and cigarettes smoked and alcohol intake during the preceding 2 days; and any breast cancer surgery or treatment undergone in the past 6 months. At the time of urine sample collection, participants also completed a 2-hour, interviewer-administered questionnaire that included an in-depth assessment of established and suspected risk factors for breast cancer.22
Selection of Samples for Analysis
Urine samples were selected for the enzyme immunoassay of estrogen metabolites by the following process. A random sample of urine specimens from all invasive case and control subjects was selected. In addition, we included assay results from all in situ cases (n = 218) and from all remaining African Americans (n = 28). Random sampling accounted for 99% of case and 95% of control patients. The assay was performed on a total of 1121 samples (469 invasive cases, 218 in situ cases, and 434 controls). For 6 women, the 2-OHE1/16-OHE1 ratio could not be computed because of missing data on 1 or both metabolites.
Preliminary data analysis revealed that the levels of the ratio and individual metabolites were higher among postmenopausal controls who reported taking hormone-replacement therapy (HRT) within 2 days of urine collection compared with postmenopausal controls who did not. For this reason, 80 current users of HRT (13 invasive cases, 4 in situ cases, and 63 controls) were excluded from the analysis. In addition, women were excluded for the following reasons: missing data regarding HRT use within 2 days (n = 20); use of oral contraceptives (OCs) within 2 days of urine collection (n = 11); missing data on whether they had menstruated within the past 12 months (n = 5); missing 2/16 ratio (n = 6); use of tamoxifen within 2 days of the urine collection or “hormones” (for example tamoxifen or Nolvadex) during the 6 months before urine collection (n = 141); missing information on tamoxifen or hormone use (n = 11); use of HRT 6 months before the reference date (n = 74) or OCs during the 6 months before the reference date (n = 16) or missing information on ever use of OCs (n = 1); and controls who reported receiving treatment of cancer other than the breast during the 6 months before donating the urine sample (n = 3). After exclusions, 269 invasive cases, 158 in situ cases, and 326 controls were available for analysis. Of these, 105 invasive cases, 70 in situ cases, and 129 controls were premenopausal.
Definition of Menopausal Status
Women were defined as premenopausal if the interval between the self-reported first day of the last menstrual cycle on the specimen checklist interview and the date of urine collection was less than 12 months.
Urinary levels of the 2 estrogen metabolites were measured using an improved enzyme-linked immunoassay (Immunacare, Inc., Bethlehem, PA). The urine samples were hydrolyzed by the addition of 190 μL of hydrolysis buffer (containing 500 units of Glusulase™, a Helix pomatia liver preparation containing glucuronidase and sulfatase activity, in a pH 5.0 acetate buffer) to 10 μL of urine and incubating for 2 hours as described previously.24 The samples were then diluted with a neutralization buffer (200 μL) to bring the pH back to 7.0. Aliquots (75 μL) of the hydrolyzed urine samples, steroid coupled to phosphorylase, and a specific antibody were then added to wells coated with a proprietary reagent that binds the antibodies and allowed to interact for 3 hours. The plates were then washed to remove excess phosphorylase. The color was developed by addition of p-nitro-phenyl phosphate in buffer. The plates were incubated for 5 minutes and then read successively at 2-minute intervals for 10 times with shaking between readings in the plate reader. The accurate working range of the assay is 0.625–16.0 ng/mL. The assay values were then calculated from the slope of the optical density curve as described previously.25 Unlike the old procedure, the new procedure is applicable to samples with low levels of the estrogen metabolites. Because of the different order of addition of the reagents, the new kit results in a time-invariant system, which leads to more reproducible results than the older kit model.25,26
The enzyme immunoassay was performed on batches composed of 40 samples, 4 blind duplicates, and 3 quality control samples. Each batch always contained both cases and controls. The 3 quality control samples consisted of pooled samples from 3 healthy individuals with low, intermediate, and high estradiol levels, as obtained, respectively, from a male, a postmenopausal female, and a premenopausal female in the luteal phase of her cycle. Quality control data showed that for the individual metabolites and their ratio, the values for the 3 samples over 36 batches were in almost all cases within 2 standard deviations of the mean. All samples were labeled only with the subject's study identification number using bar codes, and laboratory personnel were blinded as to the case-control status of the subjects.
The individual metabolites 2-OHE1 and 16-OHE1 are reported normalized for creatinine. Thus, in the results section and tables, “2-OHE1” means ng 2-OHE1/mg creatinine, and “16-OHE1” stands for ng 16-OHE1/mg creatinine. The ratio is independent of creatinine, because the creatinine concentration is the same in both the numerator and the denominator.
In previous work, the 2/16 ratio has been shown to be reproducible throughout the day, throughout the menstrual cycle in premenopausal women, and during a 6-month interval in postmenopausal women.25,27 The coefficient of variation of the ratio was 7.6 for within-assay variation and 13.0 for between assay variation.25
In the present study, we determined the correlation of blind duplicates with the original sample by linear regression for the ratio and the 2 individual metabolites. The R2 was 0.78 for the ratio (2-OHE1/16-OHE1), 0.80 for 2-OHE1, and 0.79 for 16-OHE1. To determine whether treatment of breast cancer (particularly chemotherapy) affects the metabolites, we resampled 155 women with invasive breast cancer after chemotherapy whose urine had also been collected before chemotherapy. In 135 breast cancer cases who were not receiving HRT or OCs at the time of urine collection, the means and 95% confidence intervals (95% CIs) of the differences between the pre- and postchemotherapy samples were 0.06 (95% CI = −0.16 to 0.28) for the ratio; −1.96 (−4.23 to 0.31) for 2-OHE1; and −1.18 (−2.14 to −0.22) for 16-OHE1. Overall, 74% of cases (65% premenopausal invasive cases; 78% postmenopausal invasive cases) had not received chemotherapy in the 6 months preceding urine collection.
We have previously found parity, age at first birth, lactation, use of hormone replacement, and family history of breast cancer to be associated with breast cancer in this study population.22 Associations of these risk factors with breast cancer were generally similar in the subsample of women included in the estrogen metabolite analyses, after exclusions (data not shown).
The individual metabolites and the ratio were right-skewed. Therefore, we constructed tertiles of the metabolites and their ratio based on the distribution in the controls. Odds ratios (ORs) and their 95% CIs were computed, taking the lowest tertile as the referent category. Unconditional logistic regression models were used to obtain adjusted estimates in the presence of covariates and to assess interaction between risk factors. We created separate models for invasive and in situ breast cancer cases, stratified by menopausal status. First, univariate ORs were calculated with breast cancer as the dependent variable for the following variables: age at reference date, parity, family history of breast cancer (mother, sister, or daughter), education (defined as less than high school or high school graduate as the referent, and some college, college graduate, or postcollege education), history of benign breast disease, history of fertility problems, age at first birth (<26 years as the referent, ≥26 years, or nulliparous), age at menarche, ever lactated, ever used HRT (postmenopausal women only), age at menopause (postmenopausal women only), ever used OCs, body mass index (kg/m2) at reference date, body mass index at age 20, ever used alcohol, age first moved to Long Island, total years of residence on Long Island, religion (Jewish, other), and any of the following in the 48 hours before urine collection: any medication, Synthroid, nonsteroidal anti-inflammatory drugs, broccoli, cauliflower, cabbage, cigarettes, and alcoholic beverages. Any variable with a univariate P value of <0.25 was included in the model with breast cancer as the dependent variable. After adding age at reference date, age at first birth, family history of breast cancer, and education into the model, any variable with multivariate P value of <0.05 was included in the model. The remaining covariates listed above were added to this model 1 by 1, after including tertiles of the ratio, 2-OHE1, or 16-OHE1. Any variable that changed the estimated coefficients by more than 10% was included in the final models.
Tests for trend in breast cancer risk with increasing tertiles of the metabolites and their ratio were computed using the Wald χ2 statistic in unconditional logistic regression models. All tests of statistical significance were two-sided. Because treatment of breast cancer may affect levels of the metabolites, we repeated the main analyses among invasive cases according to whether they had had chemotherapy in the 6 months before urine collection. Similarly, analyses were repeated for invasive cases with estrogen receptor (ER)-positive, ER-negative, and unknown ER status (approximately one-third of cases were lacking data on ER status). Finally, to determine whether the association varied with age among postmenopausal women, we repeated the analysis of invasive cancer within 2 age-strata: <65 and ≥65 years.
Mean and median levels of 2-OHE1 and 16-OHE1 were consistently higher in premenopausal compared with postmenopausal women for both case and control subjects (Table 1). However, there was no difference in the 2/16 ratio between premenopausal and postmenopausal women. Mean and median levels of the individual metabolites and the ratio did not differ between either in situ cases and controls or between invasive cases and controls among premenopausal or postmenopausal women (Table 1).
Adjusted ORs for invasive and in situ breast cancer and their 95% CIs are presented for pre- and postmenopausal women in Table 2. The individual metabolites showed no substantial association with premenopausal or postmenopausal invasive breast cancer. In premenopausal women, the adjusted OR for invasive breast cancer for those in the highest tertile of the ratio was 0.50 (95% CI = 0.25–1.01; P value for trend = 0.05). In postmenopausal women the highest tertile of the ratio showed a slight reduction in the OR (0.78; 95% CI = 0.46–1.33). There were no associations or trends for the metabolites or the ratio with in situ breast cancer in either premenopausal or postmenopausal women.
The decreased risk with higher 2/16 ratio generally persisted in analyses stratified by whether cases had received chemotherapy within the 6 months before urine collection (Table 3). Associations were somewhat stronger among those who had received chemotherapy.
Table 4 presents the data stratified by estrogen-receptor status. In premenopausal women, the 2/16 ratio was inversely associated with ER-positive breast cancer (OR = 0.32; 95% CI = 0.12–0.84) and ER-negative breast cancer (0.52; 0.18–1.57), with no association in the group for which ER status was not ascertained. In postmenopausal women, the strongest inverse association with the ratio was seen for ER-negative cases (0.38; 0.15–1.01).
Among postmenopausal women younger than 65 years, the OR for invasive breast cancer for extreme tertiles of the ratio was 1.59 (0.74–3.39), whereas among women 65 years or older, the OR was 0.43 (0.19–0.99). In addition, 16-OHE1 was positively associated with invasive cancer (2.30; 0.99–5.33) in the older age group.
The results of this large population-based, case–control study of breast cancer on Long Island provide support for the hypothesis that a higher 2/16 ratio is associated with decreased risk of breast cancer. The ratio showed an inverse association with invasive cancer, which was most consistent in premenopausal women. There was no indication of an association of the ratio or the individual metabolites with in situ breast cancer. This is the first study to assess the association of estrogen metabolism with in situ breast cancer.
Among the strengths of the Long Island Breast Cancer Study Project are its large size, population-based sampling, rapid ascertainment of cases, and the use of extensive questionnaires, providing detailed information on lifestyle factors and exposures and permitting adjustment for potential confounding variables. The availability of information on food intake, medications, smoking and alcohol consumption, and breast cancer treatment within the 48 hours preceding urine collection, all of which could affect estrogen metabolism, made it possible to restrict the analysis to women who were not currently taking exogenous estrogens or tamoxifen. Because women with breast cancer were more likely to discontinue HRT after their diagnosis and because the use of tamoxifen may alter levels of the metabolites, inclusion of women with these exposures could distort the results. Thus, women who were current users of these medications were omitted from the analyses.
There was a high level of compliance with urine collection (93% for case and 83% for control subjects). Although only a subset of invasive cases and controls with available urine samples was randomly selected for the estrogen metabolism assay, women whose samples were analyzed were very similar to the total study population with respect to a wide range of demographic characteristics and risk factors.
Evidence from previous studies of estrogen metabolism and breast cancer is inconsistent. Of 5 case–control studies using the enzyme immunoassay to measure urinary estrogen metabolites, 4 showed a significant or borderline inverse association with the ratio,13–15,17 and in several cases the magnitude of the associations was large.13,14 One study, in which urine samples were obtained from breast cancer survivors a number of years following enrollment in the original case-control study, found no evidence of an association.16 Of 3 prospective studies,18–20 1 reported a modest reduction in both pre- and postmenopausal women with increased 2/16 ratio,18 another19 showed a 45% reduction in risk in premenopausal women only, and the third showed no indication of an association.20 The variability in the results of these studies is not surprising, given the small samples sizes of some studies, the differences in populations and study designs, the large variability in the metabolite levels both between and within different populations, and the fact that behavioral factors, as well as disease progression and treatment, may alter estrogen metabolism. Our results are similar to those of Muti et al19 who reported a modest association of the ratio with premenopausal but not postmenopausal invasive breast cancer.
In case–control studies, a major concern is that current levels of a biomarker may not be reflective of past levels, particularly of predisease levels. Levels of metabolites measured in women after diagnosis could be altered by the disease process, by treatment, or by changes in lifestyle. In the present study, the inverse association with premenopausal invasive breast cancer appeared to be independent of chemotherapy status and ER status. In postmenopausal women, reduced ORs were seen for the ratio in the subgroup of cases who had received chemotherapy, the subgroup of ER-negative cases, and in women 65 years of age or older. Data from 2 previous studies13,16 suggest that an association of the ratio with breast cancer is limited to advanced disease. We were unable to address this possibility because detailed information on stage of invasive disease was not available.
In an analysis of participants in the Shanghai Breast Cancer Study,17 in which more than two-thirds of the urine specimens were obtained before surgery, Fowke et al reported that the association of the 2/16 ratio with breast cancer was dependent on the timing of urine collection in relation to surgery. Higher levels of the ratio measured in presurgery urine specimens were associated with reduced breast cancer risk, whereas higher levels of the ratio measured in postsurgery urine specimens were associated with increased risk. No studies have reported on differences in metabolites in the same individuals before and after surgery. In the present study, all breast cancer cases had had definitive surgery before urine specimen collection. Because little is known about the effects of surgery on levels of estrogen metabolites, we compared mean levels between cases who had had a lumpectomy versus those who had had a mastectomy within 6 months before specimen collection, within the 4 groups defined by menopausal status and in situ/invasive cancer. (Those who reported having both lumpectomy and mastectomy were excluded.) There were no clear differences in the ratio or individual metabolites between the 2 types of surgery and no consistent pattern of differences among the 4 groups. Thus, there is no indication of an effect of more extensive versus less extensive surgery in our data.
Owing to the large number of comparisons, it is possible that associations observed in subgroups according to chemotherapy and ER status could be the result of chance. Although the initial study population was large, many women (33%) had to be excluded from the analysis because of missing information, hormone use, or treatment with tamoxifen in the 6 months before urine collection. In stratified analyses by chemotherapy and ER status, the numbers of cases were small.
An additional limitation is that participation rates for the Long Island Breast Cancer Study Project interview declined with age, particularly in control subjects: 89% of case and 76% of control subjects younger than age 65 participated, compared with 72% and 43%, respectively, among those 65 years and older. Because the age-stratified results among postmenopausal women differed between women younger than 65 and those 65 years or older, we cannot rule out the possibility of selection bias in the older age group.
Elucidation of the possible role of estrogen metabolism in the development of breast cancer is complicated by the large number of factors that may affect levels of the metabolites, including lifestyle and dietary factors, medications and exogenous hormones, progression of disease, and treatment. Further studies are needed to clarify the association by stage of disease as well as the effect of specific treatment modalities (surgery, chemotherapy, radiation, and tamoxifen) on measurement of estrogen metabolites. The role of 4-hydroxyestrogens also needs to be included in epidemiologic studies, because these compounds may affect the balance between carcinogenic and anticarcinogenic activity. Finally, studies that include polymorphisms of genes involved in estrogen metabolism (eg, CYP1A1, CYP1A2, CYP3A4, and CYP1B1) as well as appropriate measurement of individual metabolites in populations with different rates of breast cancer could contribute to a better understanding of this question.
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