In women, breast cancer is the most common malignant disease in industrialised countries.
About 5–10% are the so-called familial cases, which can be mainly attributed to deleterious
mutations in BRCA1 and BRCA2 (Dunning et al, 2001; Nathanson and Weber, 2001), and
also for the remaining majority of spontaneous breast cancer cases a strong genetic
component has been postulated (Lichtenstein et al, 2000). Although finally having
a strong impact, the responsible genetic markers may be common, low-penetrance genetic
variants that modify susceptibility to breast cancer.
Potential candidates for these markers are single-nucleotide polymorphism (SNPs) that
alter the sequence or the expression of a gene product (Lander and Schork, 1994; Cargill
et al, 1999; Gray et al, 2000; Risch, 2000; Sunyaev et al, 2001). A large variety
of SNPs have already been investigated for their association with breast cancer (Dunning
et al, 2001; Nathanson and Weber, 2001). These were SNPs in DNA repair genes, steroid
hormone metabolism genes and carcinogen metabolism genes (see also, Goode et al, 2002).
We have chosen eight different SNPs from six genes. These were Q356R and P871L in
BRCA1, N372 H in BRCA2, R72P inTP53, C112R (E4) and R158C (E2) in ApoE, P187S in NQO1
and C825 T in GNB3.
BRCA1 and BRCA2 are the well-established susceptibility genes for familial breast
cancer (Dunning et al, 1997, 2001; Healey et al, 2000; Nathanson and Weber, 2001;
Goode et al, 2002), TP53 is a gene involved in apoptosis (Dumont et al, 2003), ApoE
influences lipid metabolism and cardiovascular disease (Menzel et al, 1983) and may
be involved in tumour proliferation (Moysich et al, 2000; Zunarelli et al, 2000),
NQO1 is engaged in carcinogen metabolism (Nebert et al, 2002) and GNB3 is part of
a signal transduction pathway (Siffert et al, 1998).
Searching the literature, no association with breast cancer has been found for Q356R
and P871L (BRCA1), although the authors claimed that being homozygous for 356R might
protect against breast cancer (Dunning et al, 1997). In case of the 372H allele (BRCA2),
an increased risk for developing breast cancer has been observed (Healey et al, 2000)
together with an association with foetal survival. The 72P allele of the polymorphism
in TP53 was only weakly associated with an increased risk for breast cancer (Nathanson
and Weber, 2001). No association of breast cancer was observed with the apolipoprotein
E polymorphism (Moysich et al, 2000; Zunarelli et al, 2000). For the P187S polymorphism
in NQO1, conflicting results were published (Siegelmann-Danieli and Buetow, 2002;
Hamajima et al, 2002). The C825 T polymorphism in GNB3 has not been investigated so
far.
A central consideration with case–control studies are spurious results due to a large
variety of reasons (Lander and Schork, 1994). It is therefore mandatory to repeat
published studies in different populations, and also null results should be published
to avoid bias (Hemminki and Shields, 2002). One of the reasons for spurious results
is a general statistical problem due to multiple testing. This can either be accounted
for by applying statistical correction methods (e.g. Bonferoni) or by investigating
at least two different populations.
Here we present the results of repetitive SNP association studies in our case–control
study and of a new one that was performed in two independent populations, one from
Tyrol, Austria and the other from Prague, Czech Republic. In addition, we have analysed
the concomitant effect of two polymorphisms in two different genes in order to mimic
the situation in vivo where the different genes/gene products do not act as single
entities but as members of an ‘orchestra’, as suggested by Risch (2000).
MATERIALS AND METHODS
Control and patient populations
Controls from Tyrol
The controls (400 women) were randomly drawn from a group of 13 000 apparently healthy
blood donors from Tyrol. All came from the same geographical area as the patient group.
The mean age of the control group was 39±12 years. The control persons were all anonymous,
and only their age and gender were known. For the investigation of a possible association
of the N372H polymorphism with gender, we randomly chose additional 600 women and
1600 men.
Controls from Prague
The control group enclosed 231 women from Prague with a mean age of 60±23 years. Controls
were recruited from the staff of the National Institute of Public Health, nurses and
patients of collaborating hospitals in Prague and inhabitants of houses for elderly
citizens living in the same urban area as the patients. Controls were interviewed
and only those having no personal history neither of breast cancer nor other malignancies
were included into the study. The composition of the control group was comparable
to cases in terms of age. Controls were asked to read and sign an Informed Consent
protocol.
Patient groups
The patient group from Tyrol, 220 women, had a mean age of 56±13 years and the patient
group from Prague consisted of 190 women with an average age of 58±13 years. All patients
gave Informed Consent. In all cases, the diagnosis of breast cancer was confirmed
histological. The cases from Prague were all incident cases, whereas the cases from
Tyrol were a mixture of incident and prevalent cases with a median of one survival
year (mean 2.5±3.7).
Genotyping
All samples were genotyped by the 5′exonuclease assay with fluorescent MGB-probes
on an ABI PRISM 7000 Sequence Detection System™ from Applied Biosystems. In addition,
some samples were also genotyped by conventional methods (PCR and digestion) (Q356R,
patients and controls from Tyrol and P187S, patients and controls from Prague) and
by Pyrosequencing™ (P871L, controls from Tyrol). All methods gave identical results
and not a single deviation was observed. The sequences of the primers designed for
the analysis are given in appendix.
Statistical analysis
The χ
2-test was used to compare the distribution of genotypes between cases, controls and
expected genotypes assuming a Hardy–Weinberg equilibrium. The risk attributed to individual
alleles or genotypes for breast cancer was calculated as odds ratio from 2 × 2 tables.
A possible association of genotypes with age and survival was analysed by the Kruskal–Wallis
test.
RESULTS
The genotype frequencies of the eight SNPs investigated in the control and case groups
from Tyrol and Prague are given in Tables 1
Table 1
Tyrol
Gene
SNP
Controls
Patients
Statistics spec. Genotype
Statistics allelefr
Rare allele frequency
Genotypes
N
(%)
Rare allele frequency
Genotypes
N
(%)
OR
P
OR
95% CI
P
BRCA1
Q356R
0.09
QQ
335
(84)
0.09
QQ
189
(88)
1.0
0.76
QR
58
(15)
QR
25
(11)
0.76
0.29
0.47–1.22
RR
5
(1)
RR
2
(1)
0.71
0.68
0.24
BRCA1
P871L
0.30
PP
184
(48)
0.33
PP
91
(43)
1.0
1.14
PL
171
(45)
PL
102
(49)
1.11
0.57
0.88–1.49
LL
29
(8)
LL
18
(8)
1.20
0.59
0.3
BRCA2
N372H
0.27
NN
482
(53)
0.29
NN
104
(50)
1.0
1.08
NH
361
(40)
NH
91
(43)
1.17
0.33
0.85–1.37
HH
69
(7)
HH
16
(7)
1.07
0.80
0.5
TP53
R72P
0.24
RR
191
(59)
0.28
RR
109
(53)
1.0
1.25
RP
112
(34)
RP
79
(38)
1.24
0.26
0.93–1.67
PP
22
(7)
PP
19
(9)
1.51
0.21
0.16
GNB3
C825T
0.33
CC
176
(47)
0.33
CC
102
(48)
1.0
1.11
CT
159
(43)
CT
82
(38)
0.91
0.60
0.86–1.45
TT
36
(10)
TT
31
(14)
1.49
0.15
0.4
ApoE
C112R (E4)
0.13
CC
292
(77)
0.15
CC
159
(73)
1.0
1.12
CR
81
(21)
CR
52
(24)
1.18
0.42
0.78–1.60
RR
9
(2)
RR
6
(3)
1.22
0.71
0.5
ApoE
R158C (E2)
0.08
RR
288
(85)
0.07
RR
185
(86)
1.0
0.91
RC
49
(14)
RC
31
(14)
0.98
0.95
0.55–1.46
CC
2
(1)
CC
0
(0)
—
0.7
NQO1
P187S
0.17
PP
290
(67)
0.21
PP
133
(61)
1.0
1.37
PS
126
(31)
PS
76
(35)
1.32
0.13
1.01–1.85
SS
8
(2)
SS
9
(4)
2.45
0.06
0.035
OR=odds ratio; CI=confidence interval; P=probability that the difference is caused
by chance.
2
Table 2
Prague
Gene
SNP
Controls
Patients
Statistics spec. genotype
Statistics allelefr
Rare allele frequency
Genotypes
N
(%)
Rare allele frequency
Genotypes
N
(%)
OR
P
OR
95% CI
P
BRCA1
Q356R
0.06
QQ
128
(87)
0.08
QQ
83
(84)
1.0
1.27
QR
19
(13)
QR
16
(16)
1.30
0.48
0.60–2.67
RR
0
(0)
RR
0
(0)
—
—
0.5
BRCA1
P871L
0.36
PP
64
(43)
0.32
PP
44
(45)
1.0
0.85
PL
63
(42)
PL
45
(46)
1.04
0.89
0.57–1.26
LL
22
(15)
LL
9
(9)
0.60
0.24
0.4
BRCA2
N372H
0.26
NN
84
(55)
0.26
NN
53
(57)
1.0
0.93
NH
57
(38)
NH
35
(37)
0.97
0.92
0.61–1.47
HH
11
(7)
HH
6
(6)
0.86
0.79
0.8
TP53
R72P
0.25
RR
84
(56)
0.30
RR
49
(51)
1.0
1.31
RP
58
(39)
RP
35
(37)
1.03
0.90
0.85–2.01
PP
8
(5)
PP
11
(12)
2.36
0.08
0.2
GNB3
C825T
0.30
CC
73
(48)
0.30
CC
48
(50)
1.0
1.00
CT
66
(43)
CT
39
(41)
0.90
0.70
0.66–1.52
TT
13
(8)
TT
9
(9)
1.05
0.91
1.0
ApoE
C112R (E4)
0.12
CC
115
(77)
0.09
CC
79
(84)
1.0
0.73
CR
34
(22)
CR
13
(14)
0.56
0.10
0.38–1.39
RR
1
(1)
RR
2
(2)
2.91
0.36
0.3
ApoE
R158C (E2)
0.09
RR
127
(84)
0.08
RR
84
(84)
1.0
0.89
RC
23
(15)
RC
16
(16)
1.05
0.90
0.45–1.78
CC
2
(1)
CC
0
(0)
—
0.7
NQO1
P187S
0.13
PP
175
(76)
0.20
PP
127
(67)
1.0
1.76
PS
53
(23)
PS
48
(25)
1.25
0.34
1.20–2.60
SS
3
(1)
SS
15
(8)
6.89
0.006
0.002
OR=odds ratio; CI=confidence interval; P=probability that the difference is caused
by chance.
, respectively. In every group or subgroup, the genotype frequencies were in accordance
with the assumption of a Hardy–Weinberg equilibrium. No association between genotype
frequencies and age was observed except for the C112R (E4) polymorphism in the controls
from Prague. Also, no association between genotypes and survival was discovered in
the patient group from Tyrol, which is in agreement with the paper of Goode et al
(2002). When allele frequencies were compared between cases and controls, only one
significant deviation was observed: the P187S SNP in the NQO1 gene (see Tables 1 and
2). The 187S allele was found significantly more frequently in breast cancer patients
than in controls. The same deviation could be observed in both populations from Tyrol
and Prague. Regarding all other SNPs no significant differences were observed (Tables
1 and 2).
With respect to this association, we also tested for possible deviations of genotype
frequencies of the P187S SNP and compared the homozygote ratio between cases and controls.
In the group from Prague, there were in addition to the significant allele frequency
difference also highly significant differences of all genotypes (P=0.0025) and of
the ratio of the two homozygous genotypes (PP/SS) (odds ratio (OR)=6.9; 95% confidence
interval (CI) 1.8–30.6; P=0.0006).
Between the respective groups from Tyrol and Prague, there was no significant difference
of the allele frequencies and genotype frequencies of all SNPs under investigation.
In order to increase power, we therefore combined the respective cases and controls
groups from the two middle European populations. Again, in case of the P187S SNP,
there was a significant difference of the allele frequencies (OR=1.46; 95% CI 1.16–1.85;
P=0.001), the genotype frequencies (P=0.0003) and the homozygote ratio between patients
and controls (OR=3.8; 95% CI 1.73–8.34; P=0.0001). In addition, also the R72P SNP
in the TP53 gene showed a borderline significant difference regarding allele frequencies
(OR=1.27; 95% CI 1.00–1.61; P=0.044) and the homozygote ratio (OR=1.77; 95% CI 1.00–3.13;
P=0.04). No significant difference was observed between cases and controls when we
compared frequencies of heterozygotes, both P187S and R72P, and of homozygotes for
the common allele, P187 and R72, respectively.
We also analysed the H372 H polymorphism in the BRCA2 gene to test for a previously
found association with gender (Healey et al, 2000) in 2442 controls (1530 men and
912 women). No difference of genotype frequencies between men and women (P=0.73) was
found and also no deviation from expected frequencies assuming Hardy–Weinberg equilibrium
(P=0.99).
Since we had analysed eight different SNPs in six different genes, we also investigated
for the presence of linkage disequilibrium and for pair-wise locus association. The
two SNPs of BRCA1 and ApoE, respectively, were in linkage disequilibrium as expected.
The calculation of association for pair-wise loci as outlined by the two-locus genetic
model of Risch (2000) was performed for the polymorphism at the NQO1 and TP53 gene
loci, since these were the only two polymorphic sites that showed a significant association
if the two studies were combined. Further, the associations of the two gene loci with
breast cancer are the only ones that showed in both studies a trend in the same direction
and a gene dosage effect (Hemminki and Shields, 2002) in contrast to the other polymorphic
sites. When single-locus heterozygote and common allele homozygote frequencies were
compared between patients and controls, there was no significant difference. The double
heterozygotes (P187S/R72P) were more frequent in patients (40%) than in controls (28%)
compared to the common allele double homozygotes (P187/R72) (67 vs 71%; OR=1.88; 95%
CI 1.12–3.15; P=0.011).
Individuals with two or more “deleterious” alleles (Table 3
Table 3
Genotype combinations at the NQO1 and TP53 loci for the combined populations from
Tyrol and Prague
Controls
Patients
Δ% controls−patients
Statistics specific genotypeb
Genotype NQO1/TP53
Number of “deleterious”a alleles in genotype
n
%
n
%
OR
P
SS/PP
4
1
0.22
1
0.34
−0.12
1.79
0.68
SS/rP
3
14
3.2
14
4.7
−1.5
1.79
0.14
pS/PP
SS/rr
pp/PP
2
64
14.4
72
24.3
−9.9
2.02
0.0009
pS/rP
pS/rr
1
184
41.4
104
35.1
6.3
1.01
0.94
pp/rP
pp/rr
0
181
40.8
101
34.1
6.7
1.0
Total
444
296
a deleterious alleles are 187S at the NQO1 locus and 72P at the TP53 locus; “non deleterious”
alleles are 187p at the NQO1 locus and 72r at the TP53 locus.
b OR=odds ratio; P=probability that the difference is caused by chance.
) were more frequent in the patients group than in the control group (OR=1.97; 95%
CI 1.31–2.97; P=0.0006). On the other hand, those with only one deleterious allele
or those with no deleterious allele at all (Table 3) had comparable ratios in both
patients and controls (OR=1.03; 95% CI 0.75–1.53; P=0.7).
DISCUSSION
This association study of breast cancer patients analysing eight different SNPs in
two different populations has shown in part accordance with previously published papers,
in part divergence with published results and finally new results. The investigated
SNPs in BRCA1 and BRCA2 showed no association with breast cancer in the two populations
from Austria and the Czech Republic. This is in agreement with previous results for
the P871L polymorphism (Dunning et al, 1997), but there are discrepancies for the
Q356R polymorphism in BRCA1 (Dunning et al, 1997) and the N372H polymorphism in BRCA2
(Healey et al, 2000). One paper (Dunning et al, 1997) claimed a protective effect
for the R356 allele in the homozygous state. In our population from Tyrol, the homozygotes
were found in the same ratio in both the control and the patient groups. There were
no homozygotes in the population from Prague, but because of the small group size
this was still in accordance with Hardy–Weinberg equilibrium. It remains doubtful
if the absence of the 356R homozygotes is real or spurious.
The association of the N372H polymorphism with breast cancer observed by Healey et
al (2000) could not be confirmed in this study. It is, however, striking that their
observation was only found in an English population but not in the German and Finnish
population in the later publication. It remains unclear if this is a special condition
in the English population. The other published results (Healey et al, 2000) concerning
the deviation from Hardy–Weinberg equilibrium and the differences between men and
women of the N372H polymorphism could not be confirmed by this study. When we tested
for deviation from Hardy–Weinberg by a χ
2-test using the published frequencies of the control groups, we obtained no significant
deviation. Our own results gave an excellent conformity with Hardy–Weinberg equilibrium.
For the R72P polymorphism in the TP53-gene, only a weak association was observed and
only in the combined population. In the literature, there are some publications stating
the same result but with smaller group sizes (Sjalander et al, 1996; Wang-Gohrke et
al, 1998). Most likely the effect is very small even in the homozygous state of the
72P allele.
The C825T polymorphism in GNB3 apparently does not influence the carcinogenesis of
breast cancer, which is also true for the Apo E polymorphism. The latter is in agreement
with the literature (Moysich et al, 2000; Zunarelli et al, 2000).
The association of the 187S allele of NQO1 could be observed in both populations from
Prague and Tyrol. The effect was more significant in the population from Prague than
in the Tyrolean population, which might be explained by the different recruiting of
the control groups. The Czech group are age-matched women, partly from a selected
environment, with no evidence of breast cancer, whereas the women from Tyrol are blood
donors between the age of 18 and 67 years incorporating a substantial number of women
who might still get breast cancer in their later years.
Choosing the right control population is a very critical aspect in every case–control
study. It has been a longstanding prerequisite that controls should be age matched
to patients. Unfortunately, this might lead in the case of late-onset diseases like
breast cancer to stratification due to selection bias. At the age in which most of
the cases of breast cancer occur, also a lot of circulatory diseases occur that might
change profoundly the composition of an age-matched control group. The fact that similar
results have been gained, although different recruiting strategies have been used,
further confirms that the actual findings of this study are real.
Comparison of our data on the P187S polymorphism in NQO1 with those in the literature
shows inconsistency (Hamajima et al, 2002; Siegelmann-Danieli and Buetow, 2002), particularly
with the one from Japan where the frequency for the 187S homozygotes was 16.5% in
the controls and 14.3% in the breast cancer patients group. In contrast, a group from
Philadelphia (Dunning et al, 1997) observed no significant difference, but the frequency
of the 187S allele was 19% in the case group and 15% in the control group, which is
in the same range as in our groups and shows the same trend as this study. The fact
that the American study (Siegelmann-Danieli and Buetow, 2002) showed no significant
difference in NQO1 polymorphism may be due to the low numbers of 187S homozygotes
in the patient group and high numbers of 187S homozygotes in the control group that
might have occurred by chance. Combining the numbers of the studies for this polymorphism
from Tyrol, Prague and Philadelphia, very significant differences in allele frequency,
genotypes and homozygotes ratio (data not shown) are observed.
NAD(P)H: quinone oxireductase (NQO1) is an enzyme that is involved in metabolising
numerous endogenous and environmental quinones. Exchange of the Proline at position
187 by Serine leads to a nonfunctional enzyme (Nebert et al, 2002). Individuals homozygous
for the 187S allele have a high risk for aplastic anaemia and leukaemia (Nebert et
al, 2002). Reports about the association of the P187S polymorphism with lung cancer
are inconsistent (Chen et al, 1999; Lewis et al, 2001). The association of the P187S
polymorphism with breast cancer found in this study is the first reported in the literature
and should be further investigated.
The increased risk of the double heterozygotes (P187S/R72P) to develop breast cancer
is a new finding, which is similar to the observation that double heterozygotes for
the Factor V “Leiden” and the Prothrombin mutation G20210>A have a 20-fold risk for
developing thrombosis, whereas the risk for single heterozygotes is only five-fold
and four-fold, respectively (Emmerich et al, 2001), and agrees with the two-locus
genetic model of Risch (2000). Whereas the interactions of the F5 and F2 gene products
in thrombosis are well understood, the way of interaction of the NQO1 and TP53 products
in breast cancer can only be speculated. Hydroquinone, a substrate for detoxification
by the NQO enzyme, can induce apoptosis (Moran et al, 1999), which is less stimulated
by the 72P variant of p53 (Dumont et al, 2003). How these pathways are actually interwoven
remains open for further investigations.