Cytochrome P450 1B1 gene polymorphisms and postmenopausal breast cancer risk

Tove Rylander-Rudqvist1,5, Sara Wedrén2, Fredrik Granath2, Keith Humphreys2, Susanne Ahlberg1, Elisabete Weiderpass2,3, Mikael Oscarson1, Magnus Ingelman-Sundberg1 and Ingemar Persson2,4

1 Division of Molecular Toxicology, Institute of Environmental Medicine, Karolinska Institutet, SE-171 77 Stockholm, Sweden
2 Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, SE-171 77 Stockholm, Sweden
3 International Agency for Research on Cancer, Lyon, France
4 Swedish Medical Products Agency, Uppsala, Sweden

5 To whom correspondence should be addressed Email: tove.rylander{at}imm.ki.se


    Abstract
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
Cytochrome P450 1B1 (CYP1B1) is active in the metabolism of estrogens to reactive catechols and of different procarcinogens. Several studies have investigated the relationship between genetic polymorphisms of CYP1B1 and breast cancer risk, however, with inconsistent results. We investigated such an association in postmenopausal Swedish women, with special emphasis on long-term menopausal hormone users, in a large population-based case-control study. We genotyped 1521 cases and 1498 controls for the CYP1B1 single nucleotide polymorphisms (SNPs) m2, m3 and m4 and reconstructed haplotypes. The frequencies of CYP1B1*1, CYP1B1*2, CYP1B1*3 and CYP1B1*4 alleles among controls were estimated to be 0.087, 0.293, 0.444 and 0.175, respectively. It thus appeared that very few haplotypes contained combinations of SNPs at two or three loci and that single SNP genotype data effectively represented haplotypes. Odds ratios (OR) and 95% confidence intervals (CI) were calculated from logistic regression models. We found no overall association between any CYP1B1 genotype and breast cancer risk. The data indicated, however, that women who had used meno- pausal hormones for 4 years or longer, and carried the CYP1B1*3/*3 genotype may be at increased risk of breast cancer, OR 2.0 (95% CI 1.1–3.5), compared with long-term users without this genotype. We explored the effect of CYP1B1 genotype on breast cancer risk in subgroups defined by body mass index, family history, smoking and catechol-O-methyl transferase genotype, but found no convincing evidence for interaction. In summary, our results strongly indicate that the studied CYP1B1 gene polymorphisms do not influence breast cancer risk overall but may modify the risk after long-term menopausal hormone use.

Abbreviations: BMI, body mass index; CI, confidence interval; COMT, catechol-O-methyl transferase; CYP1B1, cytochrome P450 1B1; DASH, dynamic allele-specific hybridization; OR, odds ratio; SNP, single nucleotide polymorphisms


    Introduction
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
Estrogen is postulated to play a dual role in breast carcinogenesis by acting both as a proliferator and as an initiator (1). In the degradation pathway of estrogen, potentially genotoxic catechol estrogens may be formed although the rate of formation is unclear. The cytochrome P450 1B1 (CYP1B1) metabolizes estradiol to 4-hydroxyestradiol, a catechol estrogen that has been shown to induce tumors in animal models (25).

In addition to estrogen metabolism, CYP1B1 also bioactivates a range of chemically diverse procarcinogens (6,7). CYP1B1 is expressed in the normal breast, where it is thought to be involved in the metabolic control of estrogen homeostasis, and highly induced in breast tumors (811). The CYP1B1 gene is polymorphic and 23 different alleles have been identified (http://www.imm.ki.se/CYPalleles). Most alleles are rare and contain deleterious mutations associated to glaucoma (12). Four single nucleotide polymorphisms (SNPs), m1, m2, m3 and m4, causing amino acid changes have been identified in Caucasians. As the m1 and m2 SNPs seem to be in complete linkage disequilibrium (12,13), there are 23 = 8 possible haplotypes of which five have been described previously (see Table I for nomenclature of CYP1B1 haplotypes). A number of investigators have expressed such CYP1B1 variants in bacteria or yeast and examined the catalytic properties towards 17ß-estradiol (1320). From these experiments it can be concluded that CYP1B1.2 and CYP1B1.4 most likely exhibit no altered enzyme function. Some studies report that the activity of the CYP1B1.3 enzyme may have an altered function. Shimada et al. (14) report an increased Vmax and (Vmax4-OH/Km4-OH)/(Vmax2-OH/Km2-OH) ratio for CYP1B1.3 compared with CYP1B1.1. These findings are supported by Shimada (15) and Watanabe (16) who both report an increased Vmax 4-OH/2-OH ratio of CYP1B1.3 compared with CYP1B1.1. Li et al. (18), show increased intrinsic clearance by CYP1B1.3 compared with CYP1B1.1. All these investigators used bacterial expression systems. However, Hanna and collaborators (19), who examined the properties of purified CYP1B1 enzyme, describe a decreased (Vmax4-OH/Km4-OH)/(Vmax2-OH/Km2-OH) ratio for CYP1B1.3, and Aklillu et al. (20), who expressed CYP1B1 in yeast, report no altered kinetic properties of CYP1B1.3 as compared with CYP1B1.1.


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Table I. Description of CYP1B1 haplotypes

 
The variant CYP1B1 enzymes have commonly been studied in relation to different forms of cancer, in particular breast cancer. Indeed, CYP1B1 that may produce genotoxic estrogen metabolites and may affect local concentrations of estrogen is, as mentioned, present at elevated levels in breast cancer tissue. This postulates a role for the polymorphic CYP1B1 in breast cancer etiology either as an enzyme creating genotoxic estrogen metabolites or which by its metabolism lowers the surrounding estrogen concentrations reducing its co-carcinogenic effects.

Several relatively small studies have evaluated previously the importance of m1, m2, m3 and m4 for breast cancer risk (16,2125), with inconclusive results. In order to investigate, with substantial statistical power, whether CYP1B1 genotype affects breast cancer risk, we designed a large case-control study of post-menopausal Swedish women. We considered the importance of defining haplotypes and estimated the CYP1B1 haplotype frequencies in the population. Using information from questionnaires we also investigated whether the effect of CYP1B1 genotype on breast cancer risk varied with extent of menopausal hormone use, and explored possible genotype effects in subgroups defined by body mass index (BMI), family history, smoking and catechol-O-methyl transferase (COMT) genotype. Our a priori hypothesis was that any influence of CYP1B1 genotype would be more pronounced among long-term menopausal hormone users, thus, long-term users were over-sampled to increase the power in subgroup analysis.


    Materials and methods
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
Parent study
This nationwide population-based case-control study encompassed all incident cases of primary breast cancer among women 50 and 74 years of age resident in Sweden between October 1993 and March 1995 as described in detail previously (26). Breast cancer patients were identified at diagnosis through a notification system organized within the six Swedish regional cancer registries, to which reporting of all malignant tumors is mandatory. Controls were randomly selected in 5-year age strata (to match the expected age frequency distribution among the cases) from the Swedish Total Population Register.

Cases were asked to participate in the study by their respective physicians. We were notified of the identity and address only of consenting patients, to whom we mailed questionnaires asking for detailed information about intake of menopausal hormones and oral contraceptives, weight, height, reproductive history, medical history and other lifestyle factors. Controls were contacted directly with the questionnaire. Eighty-four percent of eligible cases (n = 3345) and 82% of the controls (n = 3454) ultimately participated in the study. Among these controls, 455 who failed to return the mailed questionnaire were interviewed by phone. Results from the parent study have been published (2631). Information about tumor type, stage and estrogen and progesterone receptor expression in the tumors has been collected from medical records in an ongoing follow-up study of all breast cancer cases.

Selection of present study population
We randomly selected 1500 women with invasive breast cancer and 1500 controls (frequency-matched by age) among postmenopausal participants without any previous malignancy (except in-situ cervix carcinoma or non-melanoma skin cancer) in the parent study. In order to increase statistical power in subgroup analyses, we additionally selected all remaining eligible cases and controls who had taken menopausal hormone treatment (either medium potency estrogen treatment only or medium potency estrogen in combination with progestin) for at least 4 years (191 cases and 108 controls) and all women with self-reported diabetes mellitus (110 cases and 104 controls). In total, 1801 cases and 1712 controls were selected. In addition, 345 controls selected for a parallel endometrial cancer study and drawn from the same source population who fulfilled the inclusion criteria could be added to our sample of breast cancer free controls. The present study was approved by the Institutional Review Boards at Karolinska Institutet.

Collection of biological samples
All selected living women were contacted by mail and those who gave informed consent received a blood sampling kit by mail. Whole blood samples were drawn at a primary health care facility close to the woman's home and were sent to us by standard mail. A majority of the samples arrived at the department 1 day after blood sampling. All blood samples were immediately stored at -20°C. Breast cancer cases who declined to donate a blood sample were asked to permit to our use of normal breast tissue from archived paraffin-embedded tissue taken at breast cancer surgery. We also attempted to retrieve archived tissue samples from all deceased breast cancer cases. Samples were coded and transferred to the laboratories. Blood samples or archived tissue samples were obtained for 1322 and 247 breast cancer patients, respectively, and blood samples from 1524 control women, yielding participation rates of 87% for cases and 74% for controls.

DNA was isolated from 3 ml whole blood using Wizard Genomic DNA Purification Kit (Promega, Madison, WI) according to the manufacturer's instructions. From non-malignant cells in paraffin-embedded tissue, we extracted DNA using a standard phenol–chloroform–isoamylalcohol protocol (32).

Genetic analyses
Two methods were used for CYP1B1 genotyping: multiplex fluorescent solid-phase minisequencing (hereafter called minisequencing) (33), and dynamic allele-specific hybridization (DASH) (34). The multiplex PCR used for mini-sequencing was sensitive to DNA quality. In order to include suboptimal samples and increase genotyping success we also used the robust high throughput DASH method. Results from the two methods were validated with a two-step allele-specific PCR method for m2, m3 and m4 (20) and through replicates, 24% of the samples were analysed with both minisequencing and DASH, and the genotypes obtained were identical. The primer and probe sequences used in the minisequencing and DASH protocols are shown in Table II.


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Table II. Primers and probes used for genotyping of CYP1B1

 
Minisequencing
Five SNPs were analysed simultaneously, three in the CYP1B1 gene, reported here, and two in other genes, reported elsewhere. Since the two polymorphisms m1 and m2 are in linkage disequilibrium in Caucasians (12,13) we analysed only m2, as the corresponding fragment was easier to amplify in the multiplex PCR. SNPs were detected by specific extension with single fluorescein labeled (NEN/DuPont, Boston, MA) ddNTPs, of a primer that anneals immediately adjacent to the variable site. To minimize pipetting steps, an AutoLoad kit (Amersham, Pharmacia Biotech, Uppsala, Sweden) where PCR products were immobilized on streptavidin-coated comb shaped manifold supports was used. Approximately 100 ng of DNA was subjected to a multiplex PCR using a Perkin Elmer GeneAmp 9700 system. The 25 µl reactions contained 20 mM Tris–HCl pH 8.4, 50 mM KCl, 0.2 mM of each dNTP, 1.8 mM MgCl2, 10% DMSO, 0.625 U of Platinum® Taq polymerase (Life Technologies, Rockville, MD), and 0.25 µM of each multiplex PCR primer. The initial denaturation was performed at 95°C for 2 min, followed by 35 cycles each consisting of denaturation at 95°C for 15 s, annealing at 56°C and extension at 72°C for 1 min, followed by a final extension at 72°C for 7 min. All samples were analysed on agarose gels to verify that all fragments in the multiplex PCR reaction had been amplified. Six microliters of biotinylated PCR product was immobilized on streptavidin-coated sequencing combs. The minisequencing procedure was performed as described by Pastinen et al. (33), with the following modifications: the four minisequencing reaction mixtures contained 26 mM Tris–HCl pH 9.5, 6.5 mM MgCl2, 2 µM of each sequencing primer (Table II), 0.05 µM of F-ddGTP or 0.25 µM of F-ddATP or 0.5 µM of F-ddCTP or 0.5 µM of F-ddUTP, 0.5 µM of the three other unlabeled ddNTPs and 0.26 U of Thermo Sequenase DNA polymerase (Amersham Pharmacia Biotech). The extended primers were analysed on an ALF DNA-Autosequencer (Amersham, Pharmacia Biotech) and the chromatograms were interpreted by direct visual inspection.

DASH
The PCR mix contained 10 ng DNA, 15 mM Tris–HCl pH 8.0, 50 µM KCl, 0.12 µM biotinylated 5'-primer, 0.6 µM 3'-primer (Table I), 0.2 mM of each dNTP (HPLC purified, Interactiva GmbH, Ulm, Germany), 3.0 mM MgCl2, 5% DMSO, 0.6 U of AmpliTaq GOLD polymerase (Applied Biosystems, Foster City, CA) in a total volume of 25 µl. The PCR was carried out using a Perkin Elmer GeneAmp 9700 system. The initial denaturation was performed at 95°C for 10 min, followed by 38 cycles each consisting of denaturation at 95°C for 15 s, annealing at 60°C for 30 s, followed by a final extension at 72°C for 4 min. PCR products were checked on 2% low-melting agarose gels. DASH assays were performed as described by Prince et al. (34) and genotypes were scored from fluorescence curves as described by Howell et al. (35).

Statistical analyses
We determined whether CYP1B1 genotype frequencies were in Hardy– Weinberg equilibrium using standard {chi}2-statistics and used the Expectation-Maximization (EM)-based algorithm to reconstruct haplotypes (36). Odds ratios (OR) and 95% confidence intervals (CI) were calculated from conditional logistic regression models using the maximum likelihood method. Models were conditioned on age group and on sampling category to ensure that age-associated non-participation or over-sampling of long-term menopausal hormone users and diabetics did not introduce bias in the overall analyses. We also investigated whether the effect of CYP1B1 genotype varied over strata of menopausal hormonal use. As a result of the sampling scheme, the main effect of hormone use could not be estimated. Thus, the test for interaction compared a pure genotype effect model to a model that allowed variation of genotype effects over strata of hormone use. In secondary analyses, we explored possible interactions between CYP1B1 genotype and BMI, family history, smoking and COMT genotype. For formal tests we used the likelihood ratio test to compare a model with only main effects to a model with the joint effects of genotype and risk factor exposure. We investigated if there was any association between genotype and other breast cancer risk factors among controls by paired t-test or by {chi}2-statistics. Variables associated with CYP1B1 genotype among controls were tested in the logistic regression model to assess the potential for confounding. These analyses revealed that CYP1B1 genotype was associated with age at menopause and height among controls. However, when these variables were introduced into the logistic regression model the effect estimates of CYP1B1 genotype were not altered. In addition, we examined whether CYP1B1 genotype was associated with histological subtype (ductal or lobular), estrogen receptor (ER) status or progesterone receptor (PR) status.

All analyses were performed using SAS system PHREG, UNIVARIATE or FREQ procedures (Release 8.01, SAS institute Inc., Cary, NC).


    Results
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 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
We successfully genotyped 98% of the blood DNA samples and 90% of the tissue DNA samples, and obtained m2, m3 and m4 genotypes for 1521 cases and 1498 controls. Reasons for unsuccessful genotyping were no PCR amplification, apparently due to impure DNA since these samples in general could not be amplified by any PCR reaction, or loss of DNA during preparation. Genotype frequencies among controls were in Hardy–Weinberg equilibrium (P = 0.16 for m2, P = 0.45 for m3 and P = 0.16 for m4).

Genotyping data are shown in Table III. In our study population ~50% of all individuals were heterozygous for more than one SNP and the haplotype could therefore not be directly determined from analysis of the individual SNPs. As no high-throughput method is available for haplotype analysis, we used the EM algorithm (36) to estimate the haplotype frequencies. Using this method the haplotype frequencies among controls were estimated to 0.087, 0.293, 0.444 and 0.175 for the CYP1B1*1, CYP1B1*2, CYP1B1*3 and CYP1B1*4 alleles, respectively. Two individuals carried a previously not identified haplotype composed of m2 + m4 together with the CYP1B1*4 allele. Since it appeared as if very few of the present haplotypes contained combinations of SNPs at two or three loci and consequently that SNP indicator variables effectively represented haplotypes, we report SNP analyses, estimation of association between CYP1B1 and breast cancer risk using reconstructed haplotypes yielded similar results.


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Table III. Observed CYP1B1 genotypes among cases and controls

 
Selected characteristics of the study participants are summarized in Table IV. In the overall analyses we found no associations between any of the CYP1B1 genotypes investigated and breast cancer risk (Table V). However, we found an association between CYP1B1 genotype and breast cancer risk among users of menopausal hormones (Table VI). Women homozygous for the CYP1B1*3 allele who had taken menopausal hormones for 4 years or longer (61 cases and 28 controls) were at higher risk for developing breast cancer, OR 2.0 (95% CI 1.1–3.5) compared with long-term users who did not carry this genotype. Also, among short-term users of menopausal hormones (<4 years) there seemed to be an increased risk for individuals being homozygous for the CYP1B1*3 allele; however, the estimates were not statistically significant. P for interaction was 0.07. There were no certain associations between m2 or m4 and breast cancer risk among menopausal hormone users.


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Table IV. Selected characteristics of breast cancer cases and controls with complete information on CYP1B1 genotype

 

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Table V. Overall associations between CYP1B1 genotype and breast cancer risk with OR and 95% CI

 

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Table VI. Association between CYP1B1 genotype and breast cancer risk stratified by duration of menopausal hormone use with OR and 95% CI

 
In secondary stratified analyses we found a non-significant association between carriers of either one or two copies of the CYP1B1*2 allele and breast cancer risk among women with a first-degree family history of breast cancer. ORs were for heterozygous for the CYP1B1*2 allele 1.4 (95% CI 0.9–2.3) and for homozygous for the CYP1B1*2 allele 1.8 (95% CI 0.8–4.5) (Table VII). We found no associations between any CYP1B1 genotype and breast cancer risk in subgroups defined by BMI, smoking or COMT genotype (data not shown).


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Table VII. Analyses of the association between CYP1B1 genotype and breast cancer risk stratified by family history with OR and 95% CI

 
No associations between CYP1B1 genotype and tumor type or estrogen or progesterone receptor status were found (data not shown).


    Discussion
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 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
In this study, which is the largest published to date, we found no overall association between CYP1B1 genotype and breast cancer risk. Previous studies that showed such an association may have suffered from lack of precision due to small sample sizes. We collected information on menopausal hormone use and on other important breast cancer risk factors in order to study gene–environment interactions as well. We found a 2-fold increased risk of breast cancer for long-term users of menopausal hormones with two copies of the CYP1B1*3 allele, compared with long-term users who were non-carriers.

In contrast to the rare allelic variants of BRCA1, BRCA2 and TP53 that confer a relatively high risk to the individual by themselves, the effects of allelic variants of estrogen metabolism genes or carcinogen metabolism genes, such as CYP1B1, are thought to be moderate or manifested only in conjunction with certain exposures (37). A possible biological explanation for the effect on breast cancer risk of the CYP1B1*3 allele among long-term users of menopausal hormones, could be that these women might possess an enhanced activation of estrogen by CYP1B1. This is in line with the elevated activity of the CYP1B1.3 enzyme seen in heterologous bacterial expression systems as discussed above. An increased activity of the enzyme and an increased level of substrate, as in menopausal hormone users, would elevate the risk for formation of genotoxic metabolites, DNA damage and thereby initiation of cancer.

Given the sample size of this study and a 5% significance level, we had 85% statistical power to detect ORs of >=1.4, >=1.3 and >=1.7 for the CYP1B1*2/*2, CYP1B1*3/*3 and CYP1B1*4/*4 genotypes, respectively, in overall analysis. Despite the number of tests performed in our study we have chosen not to correct for multiple testing. All tests done are based on preconceptions about whether an association/interaction is biologically plausible. To date little is known regarding gene–environment interaction in breast cancer etiology. We therefore present the results as they are while admitting the possibility of false positive associations. Any positive finding has to be substantiated in future studies.

Several enzymes, including CYP1B1, determine the estrogen levels by oxidation and conjugation reactions. In addition, these enzyme systems may metabolically activate estrogen. The CYP1B1 metabolite 4-hydroxyestrogen may be further oxidized into reactive quinone intermediates that are hypothesized to be genotoxic. They have been shown to cause depurinating adducts both in vitro and in vivo (38,39). The role of these metabolites in estrogen-related cancers is, however, debated, and it is questioned whether the local concentrations of estrogen in the tissue is high enough to result in significant amounts of genotoxic metabolites. This critique is based on the assumption that tissue levels are equal to plasma levels; however, local production of estrogen by aromatase may play a relevant role (40). It has been shown that breast cancer tissue levels are 10–50-fold higher in postmenopausal women than predicted from plasma levels (41). Thus, the local concentration of estrogen and thereby the potential for formation of genotoxic metabolites may be of importance in postmenopausal women.

Genetic polymorphisms can be associated with breast cancer susceptibility either by affecting the biological function of a protein involved in, for example, estrogen metabolism, carcinogen metabolism or DNA repair, or by linkage to another locus functionally related to breast cancer. In our study, we investigated the relation between CYP1B1 polymorphisms and breast cancer risk primarily from a functional point of view. In order to fully allow for the different genetically determined phenotypes, it is important to define haplotypes. Because of cost and time consumption we did not perform laboratory haplotype analysis. After haplotype reconstruction we found that the predominant haplotypes were CYP1B1*1, CYP1B1*2, CYP1B1*3 and CYP1B1*4 and that the proportion of other haplotypes was close to zero. It thus appeared that very few haplotypes contained combinations of SNPs at two or three loci and that single SNP genotype data effectively represented haplotypes and we therefore performed the statistical analysis on m2, m3 and m4 genotypes separately.

Our finding of no overall association is in accordance with the studies of Bailey and De Vivo (21,24), who also investigated Caucasian populations of 164 cases and 164 controls, and 453 cases and 456 controls, respectively. However, in a study of 84 Turkish cases and 103 Turkish controls, Kocabas et al. (23) found an overall association between carriers of the CYP1B1*3 allele and breast cancer risk. No other study has investigated the influence of CYP1B1 genotype on breast cancer risk in relation to menopausal hormone use or family history of breast cancer. Bailey and De Vivo (21,24) reported that women with the CYP1B1*3/*3 genotype had a higher percentage of estrogen receptor positive tumors compared with women without this genotype, Bailey also found a similar association with progesterone receptor status. We found no such association between estrogen or progesterone receptor status and CYP1B1 genotype. Neither could we reproduce the results by Kocabas et al. (23) who detected an increased risk for women with a BMI >24 kg/m2 carrying the CYP1B1*3 allele. Although smoking is not an established risk factor for breast cancer, we investigated whether CYP1B1 genotype influenced breast cancer risk among smokers, as CYP1B1 can bioactivate tobacco smoke-related compounds such as polycyclic aromatic hydrocarbons (6,7), but found no association.

The results of this study provide evidence that CYP1B1 polymorphisms do not strongly influence breast cancer risk. However, Swedish postmenopausal women who carry two copies of the CYP1B1*3 allele and take menopausal hormones for 4 years or longer may be at higher breast cancer risk compared with women without this genotype.


    Acknowledgments
 
We are grateful to all participating women who made this study possible. We also would like to thank Dr Jonathan Prince for access to DASH apparatuses. This study was supported by the National Institutes of Health, grant number R03 CA 83114, by the Swedish Cancer Society, grant number 4112-B99-02XBB and by the Swedish Research Council.


    References
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 

  1. Liehr,J.G. (2000) Is estradiol a genotoxic mutagenic carcinogen? Endocr. Rev., 21, 40–54.[Abstract/Free Full Text]
  2. Liehr,J.G., Fang,W.F., Sirbasku,D.A. and Ari-Ulubelen,A. (1986) Carcinogenicity of catechol estrogens in Syrian hamsters. J. Steroid Biochem., 24, 353–356.[CrossRef][ISI][Medline]
  3. Li,J.J. and Li,S.A. (1987) Estrogen carcinogenesis in Syrian hamster tissues: role of metabolism. Fed. Proc., 46, 1858–1863.[ISI][Medline]
  4. Hayes,C.L., Spink,D.C., Spink,B.C., Cao,J.Q., Walker,N.J. and Sutter,T.R. (1996) 17 Beta-estradiol hydroxylation catalyzed by human cytochrome P450 1B1. Proc. Natl Acad. Sci. USA, 93, 9776–9781.[Abstract/Free Full Text]
  5. Spink,D.C., Spink,B.C., Cao,J.Q., Gierthy,J.F., Hayes,C.L., Li,Y. and Sutter,T.R. (1997) Induction of cytochrome P450 1B1 and catechol estrogen metabolism in ACHN human renal adenocarcinoma cells. J. Steroid Biochem. Mol. Biol., 62, 223–232.[CrossRef][ISI][Medline]
  6. Shimada,T., Hayes,C.L., Yamazaki,H., Amin,S., Hecht,S.S., Guengerich,F.P. and Sutter,T.R. (1996) Activation of chemically diverse procarcinogens by human cytochrome P-450 1B1. Cancer Res., 56, 2979–2984.[Abstract]
  7. Shimada,T., Oda,Y., Gillam,E.M., Guengerich,F.P. and Inoue,K. (2001) Metabolic activation of polycyclic aromatic hydrocarbons and other procarcinogens by cytochromes P450 1A1 and P450 1B1 allelic variants and other human cytochromes P450 in Salmonella typhimurium NM2009. Drug Metab. Dispos., 29, 1176–1182.[Abstract/Free Full Text]
  8. Hellmold,H., Rylander,T., Magnusson,M., Reihner,E., Warner,M. and Gustafsson,J.Å (1998) Characterization of cytochrome P450 enzymes in human breast tissue from reduction mammaplasties. J. Clin. Endocrinol. Metab., 83, 886–895.[Abstract/Free Full Text]
  9. Larsen,M.C., Angus,W.G., Brake,P.B., Eltom,S.E., Sukow,K.A. and Jefcoate,C.R. (1998) Characterization of CYP1B1 and CYP1A1 expression in human mammary epithelial cells: role of the aryl hydrocarbon receptor in polycyclic aromatic hydrocarbon metabolism. Cancer Res., 58, 2366–2374.[Abstract]
  10. Eltom,S.E., Larsen,M.C. and Jefcoate,C.R. (1998) Expression of CYP1B1 but not CYP1A1 by primary cultured human mammary stromal fibroblasts constitutively and in response to dioxin exposure: role of the Ah receptor. Carcinogenesis, 19, 1437–1444.[Abstract]
  11. Murray,G.I., Taylor,M.C., McFadyen,M.C., McKay,J.A., Greenlee,W.F., Burke,M.D. and Melvin,W.T. (1997) Tumor-specific expression of cytochrome P450 CYP1B1. Cancer Res., 57, 3026–3031.[Abstract]
  12. Stoilov,I., Akarsu,A.N., Alozie,I. et al. (1998) Sequence analysis and homology modeling suggest that primary congenital glaucoma on 2p21 results from mutations disrupting either the hinge region or the conserved core structures of cytochrome P4501B1. Am. J. Hum. Genet., 62, 573–584.[CrossRef][ISI][Medline]
  13. McLellan,R.A., Oscarson,M., Hidestrand,M., Leidvik,B., Jonsson,E., Otter,C. and Ingelman-Sundberg,M. (2000) Characterization and functional analysis of two common human cytochrome P450 1B1 variants. Arch. Biochem. Biophys., 378, 175–181.[CrossRef][ISI][Medline]
  14. Shimada,T., Watanabe,J., Inoue,K., Guengerich,F.P. and Gillam,E.M. (2001) Specificity of 17beta-oestradiol and benzo[a]pyrene oxidation by polymorphic human cytochrome P4501B1 variants substituted at residues 48, 119 and 432. Xenobiotica, 31, 163–176.[CrossRef][ISI][Medline]
  15. Shimada,T., Watanabe,J., Kawajiri,K., Sutter,T.R., Guengerich,F.P., Gillam,E.M. and Inoue,K. (1999) Catalytic properties of polymorphic human cytochrome P450 1B1 variants. Carcinogenesis, 20, 1607–1613.[Abstract/Free Full Text]
  16. Watanabe,J., Shimada,T., Gillam,E.M., Ikuta,T., Suemasu,K., Higashi,Y., Gotoh,O. and Kawajiri,K. (2000) Association of CYP1B1 genetic polymorphism with incidence to breast and lung cancer. Pharmacogenetics, 10, 25–33.[CrossRef][ISI][Medline]
  17. Spink,D.C., Spink,B.C., Zhuo,X., Hussain,M.M., Gierthy,J.F. and Ding,X. (2000) NADPH- and hydroperoxide-supported 17beta-estradiol hydroxylation catalyzed by a variant form (432L, 453S) of human cytochrome P450 1B1. J. Steroid Biochem. Mol. Biol., 74, 11–18.[CrossRef][ISI][Medline]
  18. Li,D.N., Seidel,A., Pritchard,M.P., Wolf,C.R. and Friedberg,T. (2000) Polymorphisms in P450 CYP1B1 affect the conversion of estradiol to the potentially carcinogenic metabolite 4-hydroxyestradiol. Pharmacogenetics, 10, 343–353.[CrossRef][ISI][Medline]
  19. Hanna,I.H., Dawling,S., Roodi,N., Guengerich,F.P. and Parl,F.F. (2000) Cytochrome P450 1B1 (CYP1B1) pharmacogenetics: association of polymorphisms with functional differences in estrogen hydroxylation activity. Cancer Res., 60, 3440–3444.[Abstract/Free Full Text]
  20. Aklillu,E., Oscarson,M., Hidestrand,M., Leidvik,B., Otter,C. and Ingelman-Sundberg,M. (2002) Functional analysis of six different polymorphic CYP1B1 enzyme variants found in an Ethiopian population. Mol. Pharmacol., 61, 586–594.[Abstract/Free Full Text]
  21. Bailey,L.R., Roodi,N., Dupont,W.D. and Parl,F.F. (1998) Association of cytochrome P450 1B1 (CYP1B1) polymorphism with steroid receptor status in breast cancer. Cancer Res., 58, 5038–5041.[Abstract]
  22. Zheng,W., Xie,D.W., Jin,F., Cheng,J.R., Dai,Q., Wen,W.Q., Shu,X.O. and Gao,Y.T. (2000) Genetic polymorphism of cytochrome P450-1B1 and risk of breast cancer. Cancer Epidemiol. Biomarkers Prev., 9, 147–150.[Abstract/Free Full Text]
  23. Kocabas,N.A., Sardas,S., Cholerton,S., Daly,A.K. and Karakaya,A.E. (2002) Cytochrome P450 CYP1B1 and catechol O-methyltransferase (COMT) genetic polymorphisms and breast cancer susceptibility in a Turkish population. Arch. Toxicol., 76, 643–649.[CrossRef][ISI][Medline]
  24. De Vivo,I., Hankinson,S.E., Li,L., Colditz,G.A. and Hunter,D.J. (2002) Association of CYP1B1 polymorphisms and breast cancer risk. Cancer Epidemiol. Biomarkers Prev., 11, 489–492.[Abstract/Free Full Text]
  25. Lee,K.M., Abel,J., Ko,Y. et al. (2003) Genetic polymorphisms of cytochrome P450 19 and 1B1, alcohol use and breast cancer risk in Korean women. Br. J. Cancer, 88, 675–678.[CrossRef][ISI][Medline]
  26. Magnusson,C., Baron,J.A., Correia,N., Bergstrom,R., Adami,H.O. and Persson,I. (1999) Breast-cancer risk following long-term oestrogen- and oestrogen-progestin-replacement therapy. Int. J. Cancer, 81, 339–344.[CrossRef][ISI][Medline]
  27. Magnusson,C., Baron,J., Persson,I., Wolk,A., Bergstrom,R., Trichopoulos,D. and Adami,H.O. (1998) Body size in different periods of life and breast cancer risk in post-menopausal women. Int. J. Cancer, 76, 29–34.[CrossRef][ISI][Medline]
  28. Magnusson,C., Colditz,G., Rosner,B., Bergstrom,R. and Persson,I. (1998) Association of family history and other risk factors with breast cancer risk (Sweden). Cancer Causes Control, 9, 259–267.[CrossRef][ISI][Medline]
  29. Magnusson,C.M., Persson,I.R., Baron,J.A., Ekbom,A., Bergstrom,R. and Adami,H.O. (1999) The role of reproductive factors and use of oral contraceptives in the aetiology of breast cancer in women aged 50 to 74 years. Int. J. Cancer, 80, 231–236.[CrossRef][ISI][Medline]
  30. Moradi,T., Nyren,O., Zack,M., Magnusson,C., Persson,I. and Adami,H.O. (2000) Breast cancer risk and lifetime leisure-time and occupational physical activity (Sweden). Cancer Causes Control, 11, 523–531.[CrossRef][ISI][Medline]
  31. Terry,P., Wolk,A., Persson,I. and Magnusson,C. (2001) Brassica vegetables and breast cancer risk. J. Am. Med. Assoc., 285, 2975–2977.[Free Full Text]
  32. Isola,J., DeVries,S., Chu,L., Ghazvini,S. and Waldman,F. (1994) Analysis of changes in DNA sequence copy number by comparative genomic hybridization in archival paraffin-embedded tumor samples. Am. J. Pathol., 145, 1301–1308.[Abstract]
  33. Pastinen,T., Partanen,J. and Syvanen,A.C. (1996) Multiplex, fluorescent, solid-phase minisequencing for efficient screening of DNA sequence variation. Clin. Chem., 42, 1391–1397.[Abstract/Free Full Text]
  34. Prince,J.A., Feuk,L., Howell,W.M., Jobs,M., Emahazion,T., Blennow,K. and Brookes,A.J. (2001) Robust and accurate single nucleotide polymorphism genotyping by dynamic allele-specific hybridization (DASH): design criteria and assay validation. Genome Res., 11, 152–162.[Abstract/Free Full Text]
  35. Howell,W.M., Jobs,M., Gyllensten,U. and Brookes,A.J. (1999) Dynamic allele-specific hybridization. A new method for scoring single nucleotide polymorphisms. Nature Biotechnol., 17, 87–88.[CrossRef][ISI][Medline]
  36. Dempster,A.P., Laird,N.M. and Rubin,D.B. (1977) Maximum likelihood from incomplete data via the EM algorithm. J. Royal Stat. Soc., 39, 1–38.[ISI]
  37. Armstrong,K. (2001) Genetic susceptibility to breast cancer: from the roll of the dice to the hand women were dealt. J. Am. Med. Assoc., 285, 2907–2909.[Free Full Text]
  38. Cavalieri,E.L., Stack,D.E., Devanesan,P.D. et al. (1997) Molecular origin of cancer: catechol estrogen-3,4-quinones as endogenous tumor initiators. Proc. Natl Acad. Sci. USA, 94, 10937–10942.[Abstract/Free Full Text]
  39. Nutter,L.M., Ngo,E.O. and Abul-Hajj,Y.J. (1991) Characterization of DNA damage induced by 3,4-estrone-o-quinone in human cells. J. Biol. Chem., 266, 16380–16386.[Abstract/Free Full Text]
  40. Jefcoate,C.R., Liehr,J.G., Santen,R.J. et al. (2000) Tissue-specific synthesis and oxidative metabolism of estrogens. J. Natl Cancer Inst. Monogr., 95–112.
  41. van Landeghem,A.A., Poortman,J., Nabuurs,M. and Thijssen,J.H. (1985) Endogenous concentration and subcellular distribution of estrogens in normal and malignant human breast tissue. Cancer Res., 45, 2900–2906.[Abstract]
Received May 6, 2003; revised June 18, 2003; accepted June 24, 2003.