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124 Vol. 10, 124 –130, January 1, 2004
Clinical Cancer Research
Associations between Breast Cancer Susceptibility Gene
Polymorphisms and Clinicopathological Features
Wonshik Han,1 Daehee Kang,2 In Ae Park,3
Seok Won Kim,1 Ji Yeon Bae,4 Ki-Wook Chung,5
and Dong-Young Noh1,4
Departments of 1Surgery, 2Preventive Medicine, and 3Pathology, and
4
Cancer Research Institute, Seoul National University College of
Medicine, Seoul; and 5Center for Breast Cancer, National Cancer
Center, Goyang, Korea
ABSTRACT
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 ⴝ 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 ⴝ 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).
Received 6/3/03; revised 9/2/03; accepted 9/22/03.
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:
[email protected].
Conclusions: These results indicate that polymorphisms
of some selected breast cancer susceptibility genes are associated with the clinicopathological phenotypes of breast
cancer.
INTRODUCTION
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, lowpenetrance 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 lowgrade 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 earlyonset, 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 –
21). These were CYP19 codons 80 and 264; CYP1A1 codon 462;
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Clinical Cancer Research 125
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 highthroughput SNP scoring technique.
MATERIALS AND METHODS
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 antiFITC-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.
Table 1
Characteristics of breast cancer cases
n
No. of subjects
Median (range) age at diagnosis, years
Age distribution
ⱕ30 years
30–40 years
40–50 years
50–60 years
60–70 years
⬎70 years
Family history of breast cancer
First-degree relatives
Second-degree relatives
Histological subtype
Ductal
Lobular
Mucinous
Papillary
Tubular
Medullary
Metaplastic
Other
Histological grade
1
2
3
Unknown
T stage
Tis
T1
T2
T3
T4
Unknown
Lymph node status
Negative
Positive
Unknown
Distant metastasis
Estrogen receptor status
Negative
Positive
Unknown
Progesterone receptor status
Negative
Positive
Unknown
%
664
46.0 (22–82)
27
148
265
168
48
8
50
28
22
4.1
22.3
39.9
25.3
7.2
1.2
7.5
4.2
3.3
582
21
17
13
7
6
6
12
87.7
3.2
2.6
2.0
1.1
0.9
0.9
1.8
54
260
192
158
8.1
39.2
28.9
23.8
39
320
261
18
8
18
5.9
48.2
39.3
2.7
1.2
2.7
438
221
5
8
66.0
33.3
0.8
1.2
250
347
67
37.7
52.3
10.1
344
253
67
51.8
38.1
10.1
Statistical Analysis. The ␹2 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).
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126 Breast Cancer Susceptibility Genes and Phenotype
Table 2
Variation
n
Common homozygote,
n (%)
Heterozygote,
n (%)
Rare homozygote,
n (%)
Rare allele
frequency
V80V (GTA⬎GTG)
R264C (CGC⬎TGC)
I462V (ATT⬎GTT)
R48G (CGG⬎GGG)
L432V (CTG⬎GTG)
V158M (GTG⬎ATG)
I105V (ATC⬎GTC)
P325P (CCC⬎CCG)
T594T (ACG⬎ACA)
R72P (CGC⬎CCC)
N389N (AAC⬎AAT)
L771L (TTG⬎CTG)
P871L (CCG⬎CTG)
K1183R (AAA⬎AGA)
S1436S (TCT⬎TCC)
S1613G (AGT⬎GGT)
N372H (AAT⬎CAT)
655
664
661
657
664
661
664
664
662
664
661
657
661
662
664
662
664
203 (31.0)
457 (68.8)
377 (57.0)
436 (66.4)
508 (76.5)
352 (53.3)
448 (67.5)
184 (27.7)
421 (63.6)
288 (43.4)
368 (55.7)
315 (47.9)
316 (47.8)
318 (48.0)
318 (47.9)
317 (47.9)
364 (54.8)
320 (48.9)
183 (27.6)
248 (37.5)
199 (30.3)
143 (21.5)
259 (39.2)
192 (28.9)
317 (47.7)
220 (33.2)
305 (45.9)
238 (36.0)
279 (42.5)
281 (42.5)
281 (42.4)
288 (43.4)
281 (42.4)
258 (38.9)
132 (20.1)
24 (3.6)
36 (5.4)
22 (3.3)
13 (2.0)
50 (7.5)
24 (3.6)
163 (24.5)
21 (3.2)
71 (10.7)
55 (8.3)
63 (9.6)
64 (9.7)
63 (9.5)
58 (8.7)
64 (9.7)
42 (6.3)
0.45
0.17
0.24
0.18
0.13
0.27
0.18
0.48
0.20
0.34
0.26
0.31
0.31
0.31
0.30
0.31
0.26
Gene
CYP19
CYP1A1
CYP1B1
COMT
GSTP1
ESR1
TP53
TGFBR2
BRCA1
BRCA2
Gene list and genotype frequencies
RESULTS
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 (ⱕ35 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
Table 3
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).
Association of varianta of each polymorphism with clinicopathological features of breast cancer
n (%)
Characteristic
Age
⬎35 years
ⱕ35 years
Family history
No
Yesc
Histologic grade
1 or 2
3
T stage
Tis or T1
T2–T4
Lymph node
Negative
Positive
Estrogen receptor
Positive
Negative
TP53
R72P
TGFBR2 BRCA2
N389N N372H
582 395 (69) 176 (30) 240 (41) 191 (33) 130 (22) 269 (46) 187 (32) 421 (72) 214 (37) 333 (57)
82 57 (72) 31 (38) 44 (54)b 30 (38) 26 (32) 40 (49) 29 (35) 59 (72) 27 (33) 43 (52)
256 (44) 261 (45)
37 (45) 39 (48)
614 415 (68) 188 (31) 254 (42) 208 (34) 146 (24) 122 (49) 198 (32) 443 (72) 220 (36) 350 (57)
50 37 (76) 19 (37) 30 (60)b 13 (25) 10 (20) 153 (45) 16 (31) 37 (73) 21 (41) 26 (51)
271 (44) 276 (45)
22 (43) 24 (47)
314 216 (66)
192 133 (71)
n
CYP19
V80V
CYP19
R264C
CYP1A1 CYP1B1 CYP1B1 COMT
I462V
R48G
L432V V158M
GSTP1
I105V
ESR1
P325P
ESR1
T594T
95 (30) 143 (46)
58 (30) 73 (38)
100 (32)
64 (34)
78 (25) 141 (45) 101 (32) 225 (72) 117 (38) 176 (56)
43 (23) 93 (48) 56 (29) 141 (73) 68 (35) 109 (57)
142 (45) 149 (47)
69 (36) 81 (42)
359 236 (69) 102 (30) 153 (45)
287 191 (69) 94 (33) 118 (42)
110 (32)
97 (35)
80 (23) 170 (50) 108 (32) 239 (69) 114 (33) 204 (59)
66 (24) 118 (42) 89 (31) 211 (75) 113 (40) 151 (53)
155 (45) 154 (45)
116 (41) 127 (45)
438 269 (66) 133 (32) 179 (44)
221 156 (72) 63 (29) 93 (42)
138 (34)
72 (33)
88 (22) 196 (48) 138 (34) 290 (70) 144 (35) 262 (60)b 174 (42) 183 (44)
63 (29) 94 (43) 62 (28) 165 (75) 84 (39) 111 (50) 105 (48) 100 (45)
347 240 (70) 111 (32) 148 (43)
250 164 (67) 77 (31) 106 (43)
117 (34)
82 (33)
81 (24) 169 (49) 111 (32) 254 (73) 136 (39) 200 (58)
64 (26) 106 (43) 78 (31) 178 (71) 86 (35) 135 (54)
162 (47) 159 (46)
99 (40) 117 (47)
a
Heterozygote or rare homozygote.
P ⬍ 0.05.
c
First- or second-degree relatives with breast cancer.
b
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Clinical Cancer Research 127
Table 4
Onset of breast cancer at young age (ⱕ35 years) and genetic polymorphisms in CYP1A1 codon 462 and CYP1B1 codon 432
Genotype
Age ⬎35 years, n (%)
Age ⱕ35 years, n (%)
ORa (95% CI)
339 (58.5)
210 (36.3)
30 (5.2)
240 (41.5)
38 (46.3)
38 (46.3)
6 (7.3)
44 (53.6)
1.00 (reference)
1.61 (1.00–2.61)
1.78 (0.70–4.56)
1.64 (1.03–2.60)
452 (77.7)
118 (20.3)
12 (2.1)
130 (22.4)
56 (68.3)
25 (30.5)
1 (1.2)
26 (31.7)
1.00 (reference)
1.71 (1.02–2.86)
0.67 (0.09–5.27)
1.61 (0.98–2.67)
271 (46.8)
248 (42.8)
60 (10.4)
25 (30.5)
44 (53.7)
13 (15.9)
1.00 (reference)
1.92 (1.14–3.24)
2.35 (1.14–4.86)
CYP1A1 codon 462
Ile/Ile
Ile/Val
Val/Val
Ile/Val or Val/Val
CYP1B1 codon 432
Leu/Leu
Leu/Val
Val/Val
Leu/Val or Val/Val
CYP1A1462/CYP1B1432
Wild-typeb/wild-type
Wild-type/variantc or variant/wild-type
Variant/variant
a
b
c
0.043
0.006
OR, odds ratio; CI, confidence interval.
Wild-type, common homozygote.
Variant, heterozygote or rare homozygote.
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 seconddegree 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 (ⱕ35 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%
Table 5
CYP-A1 codon 462
a
P for trend
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).
DISCUSSION
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 predis-
Family history of breast cancer and CYP1A1 codon 462 polymorphism
Genotype
No family
history,
n (%)
First- or
second-degree
relative,
n (%)
ORa
(95% CI)
Ile/Ile
Ile/Val
Val/Val
Ile/Val or Val/Val
357 (58.4)
223 (36.5)
31 (5.1)
254 (41.6)
20 (40.0)
25 (50.0)
5 (10.0)
30 (60.0)
1.00 (reference)
2.00 (1.09–3.69)
2.88 (1.01–8.20)
2.11 (1.17–3.80)
P for
trend
0.008
First-degree
relative,
n (%)
OR
(95% CI)
9 (32.1)
15 (53.6)
4 (14.3)
19 (67.9)
1.00 (reference)
2.67 (1.15–6.20)
5.12 (1.49–17.58)
2.97 (1.32–6.67)
OR, odds ratio; CI, confidence interval.
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P for
trend
0.002
128 Breast Cancer Susceptibility Genes and Phenotype
Table 6 Haplotypes of BRCA1 in 657 breast cancer cases
Exon 11
Haplotype
2430
2731
3667
Exon 13
4427
Exon 16
4956
n (%)
I
II
III
IV
T
C
C
T
C
T
T
C
A
G
G
A
T
C
T
T
A
G
G
G
906 (68.9)
403 (30.7)
4 (0.30)
1 (0.08)
a
a
Nucleotide position (reference sequence U14680.1).
pose 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 lateonset 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 –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 lowpenetrance 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 polymor-
phisms 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-␣ through the
estrogen receptor element and blocks the transcriptional activation function of activity function-2 of ER-␣; 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 highthroughput 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 in-
Table 7 BRCA1 haplotypes and ERa and PR status
ER
PR
Haplotype combination
(diplotype)
Positive, n (%)
Negative, n (%)
OR (95% CI)
Positive, n (%)
Negative, n (%)
OR (95% CI)
I/I
I/II
II/II
155 (45.7)
146 (43.1)
38 (11.3)
124 (50.2)
108 (43.7)
15 (6.1)
1.00 (reference)
0.93 (0.66–1.30)
0.49 (0.26–0.94)
113 (45.9)
104 (42.3)
29 (11.8)
166 (48.8)
150 (44.1)
24 (7.0)
1.00 (reference)
0.98 (0.69–1.39)
0.56 (0.31–1.02)
a
ER, estrogen receptor; PR, progesterone receptor; OR, odds ratio; CI, confidence interval.
Downloaded from clincancerres.aacrjournals.org on April 30, 2017. © 2004 American Association for Cancer
Research.
Clinical Cancer Research 129
stitute; 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.
ACKNOWLEDGMENTS
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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Associations between Breast Cancer Susceptibility Gene
Polymorphisms and Clinicopathological Features
Wonshik Han, Daehee Kang, In Ae Park, et al.
Clin Cancer Res 2004;10:124-130.
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