Purpose: Genetic polymorphisms may affect not only cancer development but also cancer progression, and as a result could influence cancer phenotypes. The aim of this study was to examine the relationship between breast cancer susceptibility gene polymorphisms and clinicopathological features.

Experimental Design: We genotyped 664 Korean primary breast cancer patients for 17 single-nucleotide polymorphisms (SNPs) in nine genes, using a high-throughput SNP scoring method.

Results: CYP1A1 codon 462 Ile/Val or Val/Val variants and the CYP1B1 codon 432 Leu/Val variant were found more in breast cancer patients ≤35 years of age at onset than the common homozygote [odds ratio (OR), 1.6 and 1.7, respectively]. In combination analysis of these two SNPs, the OR was 1.9 when one of them was heterozygous or a rare homozygous form, and increased to 2.3 when both were variants (P = 0.006). Cases with Ile/Val at CYP1A1 codon 462 were 2.6-fold and those with Val/Val were 5.1-fold more likely to have first-degree relatives with breast cancer than those with Ile/Ile (P = 0.002). In the haplotype study of BRCA1, the 2430C/2731T/3667G/4427C/4956G homozygote showed less estrogen receptor negativity than the most common diplotype (OR, 0.5; 95% confidence interval, 0.26–0.94). TP53 codon 72 Arg/Pro or Pro/Pro variants were associated with negative axillary lymph node status (OR, 0.7; 95% confidence interval, 0.49–0.94).

Conclusions: These results indicate that polymorphisms of some selected breast cancer susceptibility genes are associated with the clinicopathological phenotypes of breast cancer.

Hereditary breast cancer accounts for 5–9% of all breast cancers (1). It was recently estimated that a combination of BRCA1 and BRCA2 gene mutations is responsible for only ∼30% of hereditary breast cancer cases (2) and <2% of all breast cancer (3), suggesting that there may be other, low-penetrance genes that also increase an individual’s susceptibility to breast cancer. Candidate low-penetrance breast cancer susceptibility genes include those in pathways involved in DNA repair, steroid hormone metabolism and signaling, and carcinogen metabolism (4). Because of the accessibility of enormously expanding genomic databases and the rapid development of high-throughput automated genotyping, an ever-increasing number of association studies between breast cancer risk and genetic polymorphisms, particularly for single-nucleotide polymorphisms (SNPs), have been published. Many of these have demonstrated significant associations, although few studies have elucidated how a germline polymorphism can affect breast cancer development. Some authors have reported associations between various genetic polymorphisms and phenotypic features of breast cancer. These include TP53 codon 72 and low-grade histology (5), a TP53 intron 3 16-bp insertion and poor histological grade, p21 codon 31 polymorphism and progesterone receptor (PR) status (6), CYP1B1 codon 432 and steroid receptor status (7), ESR1 codon 325 and expression of PR and p53 (8), VDR and nodal status (9), PSA promoter and less aggressive breast cancer (10), and SRD5A2 codon 89 and early-onset, aggressive forms of breast cancer (11). In addition, many authors have reported associations between genetic polymorphisms of GSTP1(12), GSTM1 and GSTT1(13), SRD5A2(11), SULT1A1(14), LIG4(4), and GSTA1(15) and survival of breast cancer patients.

The results of these previous reports suggested that genetic polymorphisms may associate with cancer development as well as progression, and as a result may affect cancer phenotype and prognosis. However, these results were anecdotal and have not been reproduced in other studies. More systematic analysis involving several candidate genes and various clinical parameters is required to confirm the hypothesis that genetic polymorphisms are associated with cancer phenotype. We selected the genes that have been reported or hypothesized to associate with breast cancer risk in other studies with rare allele frequencies exceeding 10% in our preliminary study population, focusing mainly on the genes involved in estrogen metabolism. They included genetic polymorphisms that we have previously reported to be associated with breast cancer susceptibility (16, 17, 18, 19, 20, 21). These were CYP19 codons 80 and 264; CYP1A1 codon 462; CYP1B1 codons 48 and 432; COMT codon 158; GSTP1 codon 105; ESR1 codons 325 and 594; TP53 codon 72; TGFBR2 codon 389; BRCA1 codons 771, 871, 1183, 1436, and 1613; and BRCA2 codon 372.

The purpose of the present work was to evaluate possible associations between polymorphisms in these genes and clinicopathological features of breast cancer by use of a high-throughput SNP scoring technique.

Study Subjects.

All study subjects were recruited from September 2001 to January 2003 at Seoul National University Hospital with the approval of the Institutional Review Board. Breast cancer patients (n = 664) underwent surgery for primary breast cancer from January 1988 to January 2003, and the diagnoses of cancer were confirmed histopathologically at Seoul National University Hospital. Informed consent was obtained from all participants at the time of blood withdrawal. Patients who refused to donate blood, who had life-threatening disease progression, who had other malignancies than breast cancer, or whose clinical and pathological data were not available were excluded from the study.

The characteristics of the breast cancer patients and their tumors are shown in Table 1. Age at onset, family history of breast cancer, tumor size, lymph node status, and histological grade (Scarff-Bloom-Richardson classification) were reviewed. Immunohistochemical studies were performed to determine expression of the tumor markers estrogen receptor (ER) and PR. Clinicopathological data were compared among genotypes and analyzed for significant differences.

SNP Genotyping for Allele Frequency.

We selected 72 SNPs from a list of low-penetrance breast cancer susceptibility genes. After performing preliminary genotyping, we selected 17 SNPs with a rare allele frequency exceeding 10% in the Korean population (Table 2). All SNPs were in the coding region of each gene, with 11 being nonsynonymous and 6 being synonymous changes.

SNP genotyping was performed by SNP-IT assay using the SNPstream 25K System (Orchid Biosciences, Princeton, NJ). Briefly, the genomic DNA region spanning the polymorphic site was PCR-amplified using one phosphothiolated primer and one regular PCR primer. The amplified PCR products were then digested with exonuclease. The 5′ phosphothioates protected one strand of the PCR product from exonuclease digestion, generating a single-stranded PCR template. The single-stranded PCR template was overlaid on a 384-well plate that contained a covalently attached SNP-IT extension primer designed to hybridize immediately adjacent to the polymorphic site. The SNP-IT primer was extended for a single base with DNA polymerase and a mixture of the appropriate acycloterminators labeled with either FITC or biotin and complementary to the polymorphic nucleotide. The identity of the incorporated nucleotide was determined by serial colorimetric reactions with anti-FITC-alkaline phosphatase and streptavidin-horseradish peroxidase, respectively. The resulting yellow and/or blue color was measured with an ELISA reader, and the final genotype calls were made using a QCReview program.

Statistical Analysis.

The χ2 test (Pearson statistic) was used to determine associations between the frequencies of the polymorphic alleles and the various clinicopathological features of breast tumors and to ensure the independence of alleles (Hardy-Weinberg equilibrium). The odds ratios (ORs) and 95% confidence intervals (CIs) were calculated by use of an unconditional logistic regression model. To determine the presence of a linear increase in risk with exposure, a linear-by-linear association test was performed. All analyses were carried out using SPSS version 10.0 (Chicago, IL).

BRCA1 haplotypes were constructed from genotype data from five SNPs by use of the HAPLOTYPER2 program (software for haplotype inference based on the Bayesian algorithm; Ref. 22). The genetic status of subjects was expressed as the combination of two haplotypes (diplotype configuration).

The allele frequencies of the 17 SNPs are shown in Table 2. The wild-type and variant alleles were in Hardy-Weinberg equilibrium.

Analysis of the association between each SNP and the clinicopathological features of breast cancer showed some significant associations (Table 3). CYP1A1 codon 462 and CYP1B1 codon 432 polymorphisms were found to be associated with young onset (≤35 years at onset; Table 4). A young age at onset was found more in cases with the Ile/Val or Val/Val genotype in CYP1A1 codon 462 than in those with Ile/Ile (OR, 1.64; 95% CI, 1.03–2.60). Similarly, a young age at onset was found more in cases with Leu/Val heterozygosity in CYP1B1 codon 432 than in those with Leu/Leu (OR, 1.71; 95% CI, 1.02–2.86). Study subjects were assigned to one of three groups to examine synergistic effects of combined CYP1A1 codon 462 and CYP1B1 codon 432 polymorphisms on onset of breast cancer at a young age (Table 4). We found that if one of the two SNPs was heterozygous or a rare homozygous form, there was a higher correlation with young age at onset of breast cancer (OR, 1.92; 95% CI, 1.14–3.24). When both SNPs were heterozygous or rare homozygous forms, the OR increased to 2.35 (95% CI, 1.14–4.86; P for trend = 0.006).

Fifty of our cases had a family history of breast cancer. Twenty-eight of the 50 had first-degree relatives and 22 had second-degree relatives but no first-degree relatives with breast cancer (Table 1). Subjects with Ile/Val in CYP1A1 codon 462 were 2.0-fold more likely to have first- or second-degree relatives with breast cancer, and those with Val/Val were 2.9-fold more likely (P for trend = 0.008). The significance increased when the cases were restricted to those who definitely had first-degree relatives with breast cancer (P for trend = 0.002; Table 5). When we combined age and family history and analyzed the association with the CYP1A1 codon 462 polymorphism, younger patients (≤35 years) with a family history (first- or second-degree relative) were 8.8-fold more likely to have the Ile/Val or Val/Val variants than the Ile/Ile, the wild type (OR, 8.89; 95% CI, 1.06–74.35; data not shown).

The five BRCA1 SNPs showed no association with any clinicopathological feature individually. We constructed haplotypes with these five SNPs, using the haplotype inference program HAPLOTYPER2 (Table 6). Four types of haplotype were found, and two of them accounted for >99% of our study cases. The haplotypes found and their frequencies were very similar in all 60 controls (data not shown). The association between haplotype combination (diplotype) and clinicopathological features was analyzed. A relatively rare homozygote, type II/II combination, showed significantly less ER negativity (OR, 0.49; 95% CI, 0.26–0.94) and less PR negativity (OR, 0.56; 95% CI, 0.31–1.02) than the most common I/I combination (Table 7).

TP53 codon 72 polymorphisms were associated with axillary lymph node metastasis (Table 3). Cases with Arg/Pro or Pro/Pro variants in TP53 codon 72 had less axillary lymph node metastasis than those homozygous for the Arg/Arg variant (OR, 0.68; 95% CI, 0.49–0.94).

Given the many polymorphisms examined, we needed to adjust for multiple comparisons. We assessed 12 polymorphisms and a haplotype in 10 genes; therefore, a conservative Bonferroni correction of the P would require the significance level to be 0.05/13 = 0.003. When we applied this stringent criterion for significance, the association between the CYP1A1 codon 462 polymorphism and a family history of breast cancer in at least one first-degree relative remained significant (P = 0.002).

Although many somatic genetic changes correlate with phenotypes in breast cancer (23), limited evidence is available about the influence of common germline genetic variations on clinical outcome. Because of possible effects on protein function or expression, it is reasonable to suspect that polymorphisms in genes involved in carcinogen metabolism, estrogen synthesis/metabolism, DNA repair, and cell-cycle control could predispose individuals to breast cancer and could also influence the clinical phenotype of the tumor. We looked for relationships between polymorphisms of candidate genes for breast cancer susceptibility and cancer phenotypes.

The most remarkable finding was the association between germline genetic polymorphisms in CYP1A1 and CYP1B1 and age at onset of breast cancer. Several investigators have demonstrated that breast cancer in young women, compared with their older counterparts, differs in terms of pathological features and clinical outcomes. Moreover, age has been shown to be an independent prognostic factor, suggesting that early- and late-onset breast cancers have different biological origins (24, 25). It is possible that some unknown genetic factor may contribute to these different propensities with age. In the literature, GSTM1, GSTT1, and CYP17 polymorphisms have been proposed as associated with a young age at onset of breast cancer (26, 27). CYP1A1 and CYP1B1 are enzymes involved in the production of carcinogenic estrogen metabolites and the activation of environmental carcinogens. The association between polymorphisms in these genes and breast cancer risk is controversial (7, 28, 29, 30). Our results suggest that germline polymorphisms in CYP1A1 and CYP1B1 might affect development of cancer in younger patients, whereas other factors may have more influence in carcinogenesis in older subjects. Although the difference between age groups regarding exposure to carcinogens could explain the difference in cancer risk and tumor characteristics according to age of onset, it is more reasonable to postulate that genetic insults may have greater influence on earlier onset diseases.

We also showed an association between CYP1A1 and family history of breast cancer. Hypothetically, CYP1A1 is a low-penetrance gene for breast cancer, and its polymorphisms would not show strong familial aggregation. Nevertheless, a woman with a family history has a higher risk for developing breast cancer, suggesting that other factors may be already working in this population. It is possible that the effect of genetic polymorphisms on the development of cancer is more apparent in this genetically labile population. Our results showed that the effect was maximized in breast cancer patients who were young at disease onset who also had a family history of breast cancer in close relatives.

It has been reported that cancers associated with BRCA1 mutations are less often positive for ER and PR and are more frequently medullary carcinoma and higher grade invasive ductal carcinomas than are sporadic breast cancers (31, 32). We tried to investigate whether a patient with sporadic breast cancer with a certain BRCA1 haplotype would have a different phenotype or age of onset from others. We found that 2430C/2731T/3667G/4427C/4956G homozygotes showed more ER and PR expression than the most common diplotype. Fan et al.(33) demonstrated that the wild-type BRCA1 gene inhibits signaling by ligand-activated ER-α through the estrogen receptor element and blocks the transcriptional activation function of activity function-2 of ER-α; they postulated that loss of this ability contributes to mammary carcinogenesis. Our results suggest that alterations in BRCA1, such as alternative haplotypes, although they may not cause the truncation mutation or change the breast cancer risk at all can affect the interaction of BRCA1 with ER.

Axillary lymph node status is the most significant prognostic factor in breast cancer. Therefore, any factor associated with lymph node metastasis is likely to be associated with survival. In our study, the TP53 codon 72 Pro allele was found to be associated with a negative lymph node status. Goode et al.(4) found a protective effect against death after breast cancer among patients who carried the Pro allele of the TP53 R72P polymorphism, but inclusion of known prognostic variables in the model reduced the apparent protective effect of this TP53 polymorphism. From these and our results, it appears that the TP53 codon 72 polymorphism may affect lymph node metastasis in breast cancer and, consequently, survival. Dumont et al.(34) indicated that the Arg72 variant of TP53 induces apoptosis markedly better than the Pro72 variant and suggested that these variants may alter cancer risk and that Arg72 homozygotes may respond more favorably to radiation or chemotherapy.

In conclusion, the present work confirms the hypothesis that polymorphisms in candidate breast cancer susceptibility genes can influence the clinicopathological features of the disease. In addition, the study demonstrates the feasibility of high-throughput SNP scoring for mass screening studies. Points of particular note are that the present study is large scale in terms of the number of subjects, SNPs, and genes examined; involved a very homogeneous ethnic population recruited from one institute; and involved an accurate genotyping methodology. This study has identified novel associations that provide insight into the role of germline polymorphisms in cancer biology and clinical outcome.

Grant support: Korea Health 21 R&D Project, Ministry of Health & Welfare, R.O.K. (01-PJ3-PG6-01GN07-0004).

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

Requests for reprints: Dong-Young Noh, M.D., Ph.D., Cancer Research Institute and Department of Surgery, Seoul National University College of Medicine, 28 Yongon-dong, Chongno-gu, Seoul 110-744, Korea. Phone: 82-2-760-2921; Fax: 82-2-766-3975; E-mail: dynoh@plaza.snu.ac.kr

Table 1

Characteristics of breast cancer cases

n%
No. of subjects 664  
Median (range) age at diagnosis, years 46.0 (22–82)  
Age distribution   
 ≤30 years 27 4.1 
 30–40 years 148 22.3 
 40–50 years 265 39.9 
 50–60 years 168 25.3 
 60–70 years 48 7.2 
 >70 years 1.2 
Family history of breast cancer 50 7.5 
 First-degree relatives 28 4.2 
 Second-degree relatives 22 3.3 
Histological subtype   
 Ductal 582 87.7 
 Lobular 21 3.2 
 Mucinous 17 2.6 
 Papillary 13 2.0 
 Tubular 1.1 
 Medullary 0.9 
 Metaplastic 0.9 
 Other 12 1.8 
Histological grade   
 1 54 8.1 
 2 260 39.2 
 3 192 28.9 
 Unknown 158 23.8 
T stage   
 Tis 39 5.9 
 T1 320 48.2 
 T2 261 39.3 
 T3 18 2.7 
 T4 1.2 
 Unknown 18 2.7 
Lymph node status   
 Negative 438 66.0 
 Positive 221 33.3 
 Unknown 0.8 
Distant metastasis 1.2 
Estrogen receptor status   
 Negative 250 37.7 
 Positive 347 52.3 
 Unknown 67 10.1 
Progesterone receptor status   
 Negative 344 51.8 
 Positive 253 38.1 
 Unknown 67 10.1 
n%
No. of subjects 664  
Median (range) age at diagnosis, years 46.0 (22–82)  
Age distribution   
 ≤30 years 27 4.1 
 30–40 years 148 22.3 
 40–50 years 265 39.9 
 50–60 years 168 25.3 
 60–70 years 48 7.2 
 >70 years 1.2 
Family history of breast cancer 50 7.5 
 First-degree relatives 28 4.2 
 Second-degree relatives 22 3.3 
Histological subtype   
 Ductal 582 87.7 
 Lobular 21 3.2 
 Mucinous 17 2.6 
 Papillary 13 2.0 
 Tubular 1.1 
 Medullary 0.9 
 Metaplastic 0.9 
 Other 12 1.8 
Histological grade   
 1 54 8.1 
 2 260 39.2 
 3 192 28.9 
 Unknown 158 23.8 
T stage   
 Tis 39 5.9 
 T1 320 48.2 
 T2 261 39.3 
 T3 18 2.7 
 T4 1.2 
 Unknown 18 2.7 
Lymph node status   
 Negative 438 66.0 
 Positive 221 33.3 
 Unknown 0.8 
Distant metastasis 1.2 
Estrogen receptor status   
 Negative 250 37.7 
 Positive 347 52.3 
 Unknown 67 10.1 
Progesterone receptor status   
 Negative 344 51.8 
 Positive 253 38.1 
 Unknown 67 10.1 
Table 2

Gene list and genotype frequencies

GeneVariationnCommon homozygote, n (%)Heterozygote, n (%)Rare homozygote, n (%)Rare allele frequency
CYP19 V80V (GTA>GTG) 655 203 (31.0) 320 (48.9) 132 (20.1) 0.45 
 R264C (CGC>TGC) 664 457 (68.8) 183 (27.6) 24 (3.6) 0.17 
CYP1A1 I462V (ATT>GTT) 661 377 (57.0) 248 (37.5) 36 (5.4) 0.24 
CYP1B1 R48G (CGG>GGG) 657 436 (66.4) 199 (30.3) 22 (3.3) 0.18 
 L432V (CTG>GTG) 664 508 (76.5) 143 (21.5) 13 (2.0) 0.13 
COMT V158M (GTG>ATG) 661 352 (53.3) 259 (39.2) 50 (7.5) 0.27 
GSTP1 I105V (ATC>GTC) 664 448 (67.5) 192 (28.9) 24 (3.6) 0.18 
ESR1 P325P (CCC>CCG) 664 184 (27.7) 317 (47.7) 163 (24.5) 0.48 
 T594T (ACG>ACA) 662 421 (63.6) 220 (33.2) 21 (3.2) 0.20 
TP53 R72P (CGC>CCC) 664 288 (43.4) 305 (45.9) 71 (10.7) 0.34 
TGFBR2 N389N (AAC>AAT) 661 368 (55.7) 238 (36.0) 55 (8.3) 0.26 
BRCA1 L771L (TTG>CTG) 657 315 (47.9) 279 (42.5) 63 (9.6) 0.31 
 P871L (CCG>CTG) 661 316 (47.8) 281 (42.5) 64 (9.7) 0.31 
 K1183R (AAA>AGA) 662 318 (48.0) 281 (42.4) 63 (9.5) 0.31 
 S1436S (TCT>TCC) 664 318 (47.9) 288 (43.4) 58 (8.7) 0.30 
 S1613G (AGT>GGT) 662 317 (47.9) 281 (42.4) 64 (9.7) 0.31 
BRCA2 N372H (AAT>CAT) 664 364 (54.8) 258 (38.9) 42 (6.3) 0.26 
GeneVariationnCommon homozygote, n (%)Heterozygote, n (%)Rare homozygote, n (%)Rare allele frequency
CYP19 V80V (GTA>GTG) 655 203 (31.0) 320 (48.9) 132 (20.1) 0.45 
 R264C (CGC>TGC) 664 457 (68.8) 183 (27.6) 24 (3.6) 0.17 
CYP1A1 I462V (ATT>GTT) 661 377 (57.0) 248 (37.5) 36 (5.4) 0.24 
CYP1B1 R48G (CGG>GGG) 657 436 (66.4) 199 (30.3) 22 (3.3) 0.18 
 L432V (CTG>GTG) 664 508 (76.5) 143 (21.5) 13 (2.0) 0.13 
COMT V158M (GTG>ATG) 661 352 (53.3) 259 (39.2) 50 (7.5) 0.27 
GSTP1 I105V (ATC>GTC) 664 448 (67.5) 192 (28.9) 24 (3.6) 0.18 
ESR1 P325P (CCC>CCG) 664 184 (27.7) 317 (47.7) 163 (24.5) 0.48 
 T594T (ACG>ACA) 662 421 (63.6) 220 (33.2) 21 (3.2) 0.20 
TP53 R72P (CGC>CCC) 664 288 (43.4) 305 (45.9) 71 (10.7) 0.34 
TGFBR2 N389N (AAC>AAT) 661 368 (55.7) 238 (36.0) 55 (8.3) 0.26 
BRCA1 L771L (TTG>CTG) 657 315 (47.9) 279 (42.5) 63 (9.6) 0.31 
 P871L (CCG>CTG) 661 316 (47.8) 281 (42.5) 64 (9.7) 0.31 
 K1183R (AAA>AGA) 662 318 (48.0) 281 (42.4) 63 (9.5) 0.31 
 S1436S (TCT>TCC) 664 318 (47.9) 288 (43.4) 58 (8.7) 0.30 
 S1613G (AGT>GGT) 662 317 (47.9) 281 (42.4) 64 (9.7) 0.31 
BRCA2 N372H (AAT>CAT) 664 364 (54.8) 258 (38.9) 42 (6.3) 0.26 
Table 3

Association of varianta of each polymorphism with clinicopathological features of breast cancer

Characteristicnn (%)
CYP19 V80VCYP19 R264CCYP1A1 I462VCYP1B1 R48GCYP1B1 L432VCOMT V158MGSTP1 I105VESR1 P325PESR1 T594TTP53 R72PTGFBR2 N389NBRCA2 N372H
Age              
 >35 years 582 395 (69) 176 (30) 240 (41) 191 (33) 130 (22) 269 (46) 187 (32) 421 (72) 214 (37) 333 (57) 256 (44) 261 (45) 
 ≤35 years 82 57 (72) 31 (38) 44 (54)b 30 (38) 26 (32) 40 (49) 29 (35) 59 (72) 27 (33) 43 (52) 37 (45) 39 (48) 
Family history              
 No 614 415 (68) 188 (31) 254 (42) 208 (34) 146 (24) 122 (49) 198 (32) 443 (72) 220 (36) 350 (57) 271 (44) 276 (45) 
 Yesc 50 37 (76) 19 (37) 30 (60)b 13 (25) 10 (20) 153 (45) 16 (31) 37 (73) 21 (41) 26 (51) 22 (43) 24 (47) 
Histologic grade              
 1 or 2 314 216 (66) 95 (30) 143 (46) 100 (32) 78 (25) 141 (45) 101 (32) 225 (72) 117 (38) 176 (56) 142 (45) 149 (47) 
 3 192 133 (71) 58 (30) 73 (38) 64 (34) 43 (23) 93 (48) 56 (29) 141 (73) 68 (35) 109 (57) 69 (36) 81 (42) 
T stage              
 Tis or T1 359 236 (69) 102 (30) 153 (45) 110 (32) 80 (23) 170 (50) 108 (32) 239 (69) 114 (33) 204 (59) 155 (45) 154 (45) 
 T2–T4 287 191 (69) 94 (33) 118 (42) 97 (35) 66 (24) 118 (42) 89 (31) 211 (75) 113 (40) 151 (53) 116 (41) 127 (45) 
Lymph node              
 Negative 438 269 (66) 133 (32) 179 (44) 138 (34) 88 (22) 196 (48) 138 (34) 290 (70) 144 (35) 262 (60)b 174 (42) 183 (44) 
 Positive 221 156 (72) 63 (29) 93 (42) 72 (33) 63 (29) 94 (43) 62 (28) 165 (75) 84 (39) 111 (50) 105 (48) 100 (45) 
Estrogen receptor              
 Positive 347 240 (70) 111 (32) 148 (43) 117 (34) 81 (24) 169 (49) 111 (32) 254 (73) 136 (39) 200 (58) 162 (47) 159 (46) 
 Negative 250 164 (67) 77 (31) 106 (43) 82 (33) 64 (26) 106 (43) 78 (31) 178 (71) 86 (35) 135 (54) 99 (40) 117 (47) 
Characteristicnn (%)
CYP19 V80VCYP19 R264CCYP1A1 I462VCYP1B1 R48GCYP1B1 L432VCOMT V158MGSTP1 I105VESR1 P325PESR1 T594TTP53 R72PTGFBR2 N389NBRCA2 N372H
Age              
 >35 years 582 395 (69) 176 (30) 240 (41) 191 (33) 130 (22) 269 (46) 187 (32) 421 (72) 214 (37) 333 (57) 256 (44) 261 (45) 
 ≤35 years 82 57 (72) 31 (38) 44 (54)b 30 (38) 26 (32) 40 (49) 29 (35) 59 (72) 27 (33) 43 (52) 37 (45) 39 (48) 
Family history              
 No 614 415 (68) 188 (31) 254 (42) 208 (34) 146 (24) 122 (49) 198 (32) 443 (72) 220 (36) 350 (57) 271 (44) 276 (45) 
 Yesc 50 37 (76) 19 (37) 30 (60)b 13 (25) 10 (20) 153 (45) 16 (31) 37 (73) 21 (41) 26 (51) 22 (43) 24 (47) 
Histologic grade              
 1 or 2 314 216 (66) 95 (30) 143 (46) 100 (32) 78 (25) 141 (45) 101 (32) 225 (72) 117 (38) 176 (56) 142 (45) 149 (47) 
 3 192 133 (71) 58 (30) 73 (38) 64 (34) 43 (23) 93 (48) 56 (29) 141 (73) 68 (35) 109 (57) 69 (36) 81 (42) 
T stage              
 Tis or T1 359 236 (69) 102 (30) 153 (45) 110 (32) 80 (23) 170 (50) 108 (32) 239 (69) 114 (33) 204 (59) 155 (45) 154 (45) 
 T2–T4 287 191 (69) 94 (33) 118 (42) 97 (35) 66 (24) 118 (42) 89 (31) 211 (75) 113 (40) 151 (53) 116 (41) 127 (45) 
Lymph node              
 Negative 438 269 (66) 133 (32) 179 (44) 138 (34) 88 (22) 196 (48) 138 (34) 290 (70) 144 (35) 262 (60)b 174 (42) 183 (44) 
 Positive 221 156 (72) 63 (29) 93 (42) 72 (33) 63 (29) 94 (43) 62 (28) 165 (75) 84 (39) 111 (50) 105 (48) 100 (45) 
Estrogen receptor              
 Positive 347 240 (70) 111 (32) 148 (43) 117 (34) 81 (24) 169 (49) 111 (32) 254 (73) 136 (39) 200 (58) 162 (47) 159 (46) 
 Negative 250 164 (67) 77 (31) 106 (43) 82 (33) 64 (26) 106 (43) 78 (31) 178 (71) 86 (35) 135 (54) 99 (40) 117 (47) 
a

Heterozygote or rare homozygote.

b

P < 0.05.

c

First- or second-degree relatives with breast cancer.

Table 4

Onset of breast cancer at young age (≤35 years) and genetic polymorphisms in CYP1A1 codon 462 and CYP1B1 codon 432

GenotypeAge >35 years, n (%)Age ≤35 years, n (%)ORa (95% CI)P for trend
CYP1A1 codon 462     
 Ile/Ile 339 (58.5) 38 (46.3) 1.00 (reference)  
 Ile/Val 210 (36.3) 38 (46.3) 1.61 (1.00–2.61)  
 Val/Val 30 (5.2) 6 (7.3) 1.78 (0.70–4.56) 0.043 
 Ile/Val or Val/Val 240 (41.5) 44 (53.6) 1.64 (1.03–2.60)  
CYP1B1 codon 432     
 Leu/Leu 452 (77.7) 56 (68.3) 1.00 (reference)  
 Leu/Val 118 (20.3) 25 (30.5) 1.71 (1.02–2.86)  
 Val/Val 12 (2.1) 1 (1.2) 0.67 (0.09–5.27)  
 Leu/Val or Val/Val 130 (22.4) 26 (31.7) 1.61 (0.98–2.67)  
CYP1A1462/CYP1B1432     
 Wild-typeb/wild-type 271 (46.8) 25 (30.5) 1.00 (reference)  
 Wild-type/variantc or variant/wild-type 248 (42.8) 44 (53.7) 1.92 (1.14–3.24)  
 Variant/variant 60 (10.4) 13 (15.9) 2.35 (1.14–4.86) 0.006 
GenotypeAge >35 years, n (%)Age ≤35 years, n (%)ORa (95% CI)P for trend
CYP1A1 codon 462     
 Ile/Ile 339 (58.5) 38 (46.3) 1.00 (reference)  
 Ile/Val 210 (36.3) 38 (46.3) 1.61 (1.00–2.61)  
 Val/Val 30 (5.2) 6 (7.3) 1.78 (0.70–4.56) 0.043 
 Ile/Val or Val/Val 240 (41.5) 44 (53.6) 1.64 (1.03–2.60)  
CYP1B1 codon 432     
 Leu/Leu 452 (77.7) 56 (68.3) 1.00 (reference)  
 Leu/Val 118 (20.3) 25 (30.5) 1.71 (1.02–2.86)  
 Val/Val 12 (2.1) 1 (1.2) 0.67 (0.09–5.27)  
 Leu/Val or Val/Val 130 (22.4) 26 (31.7) 1.61 (0.98–2.67)  
CYP1A1462/CYP1B1432     
 Wild-typeb/wild-type 271 (46.8) 25 (30.5) 1.00 (reference)  
 Wild-type/variantc or variant/wild-type 248 (42.8) 44 (53.7) 1.92 (1.14–3.24)  
 Variant/variant 60 (10.4) 13 (15.9) 2.35 (1.14–4.86) 0.006 
a

OR, odds ratio; CI, confidence interval.

b

Wild-type, common homozygote.

c

Variant, heterozygote or rare homozygote.

Table 5

Family history of breast cancer and CYP1A1 codon 462 polymorphism

GenotypeNo family history, n (%)First- or second-degree relative, n (%)ORa (95% CI)P for trendFirst-degree relative, n (%)OR (95% CI)P for trend
CYP-A1 codon 462 Ile/Ile 357 (58.4) 20 (40.0) 1.00 (reference)  9 (32.1) 1.00 (reference)  
 Ile/Val 223 (36.5) 25 (50.0) 2.00 (1.09–3.69)  15 (53.6) 2.67 (1.15–6.20)  
 Val/Val 31 (5.1) 5 (10.0) 2.88 (1.01–8.20) 0.008 4 (14.3) 5.12 (1.49–17.58) 0.002 
 Ile/Val or Val/Val 254 (41.6) 30 (60.0) 2.11 (1.17–3.80)  19 (67.9) 2.97 (1.32–6.67)  
GenotypeNo family history, n (%)First- or second-degree relative, n (%)ORa (95% CI)P for trendFirst-degree relative, n (%)OR (95% CI)P for trend
CYP-A1 codon 462 Ile/Ile 357 (58.4) 20 (40.0) 1.00 (reference)  9 (32.1) 1.00 (reference)  
 Ile/Val 223 (36.5) 25 (50.0) 2.00 (1.09–3.69)  15 (53.6) 2.67 (1.15–6.20)  
 Val/Val 31 (5.1) 5 (10.0) 2.88 (1.01–8.20) 0.008 4 (14.3) 5.12 (1.49–17.58) 0.002 
 Ile/Val or Val/Val 254 (41.6) 30 (60.0) 2.11 (1.17–3.80)  19 (67.9) 2.97 (1.32–6.67)  
a

OR, odds ratio; CI, confidence interval.

Table 6

Haplotypes of BRCA1 in 657 breast cancer cases

HaplotypeExon 11Exon 13 4427Exon 16 4956n (%)
2430a27313667
906 (68.9) 
II 403 (30.7) 
III 4 (0.30) 
IV 1 (0.08) 
HaplotypeExon 11Exon 13 4427Exon 16 4956n (%)
2430a27313667
906 (68.9) 
II 403 (30.7) 
III 4 (0.30) 
IV 1 (0.08) 
a

Nucleotide position (reference sequence U14680.1).

Table 7

BRCA1 haplotypes and ERa and PR status

Haplotype combination (diplotype)ERPR
Positive, n (%)Negative, n (%)OR (95% CI)Positive, n (%)Negative, n (%)OR (95% CI)
I/I 155 (45.7) 124 (50.2) 1.00 (reference) 113 (45.9) 166 (48.8) 1.00 (reference) 
I/II 146 (43.1) 108 (43.7) 0.93 (0.66–1.30) 104 (42.3) 150 (44.1) 0.98 (0.69–1.39) 
II/II 38 (11.3) 15 (6.1) 0.49 (0.26–0.94) 29 (11.8) 24 (7.0) 0.56 (0.31–1.02) 
Haplotype combination (diplotype)ERPR
Positive, n (%)Negative, n (%)OR (95% CI)Positive, n (%)Negative, n (%)OR (95% CI)
I/I 155 (45.7) 124 (50.2) 1.00 (reference) 113 (45.9) 166 (48.8) 1.00 (reference) 
I/II 146 (43.1) 108 (43.7) 0.93 (0.66–1.30) 104 (42.3) 150 (44.1) 0.98 (0.69–1.39) 
II/II 38 (11.3) 15 (6.1) 0.49 (0.26–0.94) 29 (11.8) 24 (7.0) 0.56 (0.31–1.02) 
a

ER, estrogen receptor; PR, progesterone receptor; OR, odds ratio; CI, confidence interval.

We thank Dr. Jong Eun Lee at DNA Link, Inc. (Seoul, Korea) for valuable discussions and excellent genotyping work, and Eun-Kyoung Hwang for database and sample management.

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