Role of CYP2E1 polymorphisms in breast cancer: a systematic review and meta-analysis
Lu et al. Cancer Cell Int
Role of CYP2E1 polymorphisms in breast cancer: a systematic review and meta-analysis
Background: CYP2E1 polymorphisms have been reported to influence individual's breast cancer susceptibility as a phase I enzyme, but the results of these previous studies remain controversial. We performed a comprehensive metaanalysis to assess their association. Methods: A comprehensive search of literature included in various databases (PubMed, Web of Science and Google scholar), published before August 2016, was performed. Odds ratios (ORs) with 95% confidence intervals (CIs) calculated in fixed or random-effects models were used to estimate the strength of the associations between three polymorphisms of CYP2E1 and breast cancer susceptibility. Subgroup analysis, sensitivity analysis and test for publication bias were also performed. A total of 11 separate comparisons involving 4311 cases and 4407 controls were included in the meta-analysis. Results: Our result showed that there was no significant association between the two common polymorphisms CYP2E1 rs2031920 C>T, CYP2E1*5 Rsa I/Rst I (c1/c2) and BC risk. For CYP2E1*6 Dra I (D/C) polymorphism, a significantly increased BC risk in the overall population was found in genetic model D/C vs. D/D (OR = 1.29, 95% CI = 1.04-1.61, P = 0.023) and C/C + D/C vs. D/D (OR = 1.25, 95% CI = 1.04-1.51, P = 0.019), together with subjects who have at least one C allele (C vs. D: OR = 1.46, 95% CI = 1.20-1.79, P < 0.001). Similar results were also found in subgroup analyses in Caucasians of these three comparison models. Conclusions: The present meta-analysis suggests that CYP2E1*6 Dra I (D/C) variation significantly associated with the risk of BC. Individuals with D/C and C/C + D/C genotypes or carried at least one C allele of CYP2E1*6 Dra I (D/C) polymorphism had a significant higher susceptibility to develop BC.
Breast cancer; CYP2E1; Enzyme; Polymorphism; Meta-analysis
Worldwide, breast cancer (BC) represents the leading
cause of female gynecological cancer death. Its estimated
deaths (189,000) were reported almost equal to the
estimated number of deaths from lung cancer (188,000
deaths) , indicating that BC has become a global
burden. Known risks factors contribute to BC included
reproductive events, hormonal level, and family histories
, but they account for less than 47% cases . Other
etiology, though remains unknown, is believed causing
by an integrated function of carcinogen exposure and
polymorphisms in genes, especially genes involved in
carcinogen metabolism .
Cytochrome P4502E1 (CYP2El), a member of
Cytochrome P450 (CYP) super-family which involved in
the metabolism of many endogenous and exogenous
substance, is of pivotal importance in metabolizing ethanol
and low-molecular-weight carcinogens such as
N-nitrosamines in cigarettes [5, 6]. Alcohol intake, a risk factor for
cancer of various organs, has been proved associated with
BC . The relationship between tobacco smoke and BC
development, also continuously, been emphasized that
smoking could increased breast cancer risk, no matter
passively or actively . Furthermore, their association
with BC according to carcinogen-metabolizing
genotype was also investigated by more than 50 epidemiologic
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studies. Results indicating that gene polymorphisms,
including CYP450s, glutathione S-transferases,
N-acetyltransferases, and sulfotransferases, interacting with
carcinogen exposure, may modified one’s susceptibility
to cancer . Among the various CYPs, CYP2E1 is an
important Phase I enzyme involved in the metabolism of
alcohol and tobacco-generated N-nitrosamines, altering
its activity has been suggested might link to the
development of BC .
CYP2E1 is located at chromosome 10. So far, more than
100 single nucleotide polymorphisms (SNPs) have been
found (http://www.ncbi.nlm.nih.gov/SNP). However,
only several common mutations were extensively
investigated as they might alter the activity of CYP2E1 [10,
11]. Rs3813867 G>C and rs2031920 C>T were two key
SNPs among them, with the former one associated with
Pst I restriction enzyme site and the later one with Rsa I
restriction enzyme site, their linkage disequilibrium also
lead to the CYP2E1*5 haplotype and form three types
of distinct genotypes: (1) c1/c1(Rsa I+ Pst I−),
homozygous of normal alleles; (2) c1/c2, heterozygous; (3) c2/
c2 (Rsa I− Pst I+), homozygous alleles after nucleotide
exchanged . Another polymorphism, recognized by
Dra I restriction enzyme in intron 6 (rs6413432), form
CYP2E1*6 polymorphism and also result in three
genotypes: C/C, C/D and D/D .
The relationship between above CYP2E1
polymorphisms and BC has been investigated by various studies,
however, presenting conflict results. One studies
conducted on patients suffering from primary unilateral BC
demonstrated the absence of any association between
CYP2E1*5 polymorphisms with BC, no matter in
premenopausal or postmenopausal women . However,
Wu et al. , who carried out a studies on non smoker
and non drinker women, reported that individuals with
the c2/c2 genotype of CYP2E1*5 had a lower BC risk than
that of c1/c1 (OR = 0.24, 95% CI = 0.08–0.74). While the
most recently study by Chong et al. . indicated that
the c1/c2 genotype or c2 allele carriers with CYP2E1*5
variation have an approximately 1.8-fold higher risk of
BC. Such controversy results may due to the relatively
low mutation frequency of CYP2E1 and small
epidemiologic studies with low statistic power; we therefore
systematically reviewed and performed a meta-analysis
to quantitatively evaluate the role of CYP2E1
polymorphisms in BC development.
A comprehensive search of literature listed in various
databases (PubMed, Web of Science and Google scholar),
published before August 2016, was performed using the
following key words ‘breast cancer’ or’ ‘breast carcinoma’,
‘polymorphism’ or ‘variant’ and ‘mutation’, all combined
with Medical Subject Heading (MeSH) term ‘CYP2E1’.
The eligible studies were retrieved, and their reference
lists were screen by hand to find every relevant paper.
No any restriction such as time and language was made
during the searches, as well as attempts to obtain
In this study, we performed the meta-analysis according
to the proposal of Meta-analysis of Observational Studies
in Epidemiology group (MOOSE) . The eligible studies
were requested to meet the following inclusion criteria:
(1) any type of comparative study; (2) evaluated the
association between CYP2E1 gene polymorphisms and breast
cancer risk; (3) in cases and controls, provided sufficient
data to estimate the odds ratio (OR) with their 95%
confidence intervals (95% CIs). Studies were excluded if one of
them existed: (1) insufficient data to extract; (2) without
control population; and (3) some CYP2E1 polymorphisms
that rarely reported. If overlapping data was found, either
the study with lower quality or the earlier published one
would be excluded in the following analysis.
Data extraction from each eligible study was conducted
by two independent investigators, which included: (1)
the first author’s name; (2) year of publication; (3) study
region or country; (4) ethnicity; (5) cancer confirmation;
(6) sample size (both cases and controls); (7) source of
control (together with matching criteria); (8)
polymorphisms of CYP2E1; (9) genotyping method; (10) genotype
distribution in cases and controls and whether P value of
the control population consistent with the
Hardy–Weinberg equilibrium (HWE). In the event of different results,
discussion was conducted to solve the discrepancies.
When a study reported the results on different CYP2E1
polymorphisms, we treated them as separate studies in
To evaluate the quality of the included studies, a set of
predefined criteria originally proposed by Thakkinstian
et al. . was used. The predefined criteria, which cover
the credibility of controls, the representativeness of cases,
specimens of cases when determining genotypes, Hardy–
Weinberg equilibrium in controls, and total sample size,
was structured as a 16-item list with scores ranging from
0 to 15 by Qin et al. . and has been quoted by
several meta-analyses [20, 21] (see Additional file 1: Table
S1). As done previously, the studies with scores ≥10 were
defined as high-quality studies, while the rest were
The association of each CYP2E1 polymorphisms with
breast cancer risk was estimated by calculating pooled
ORs and 95% CIs under different comparison models,
including additive models, recessive model, and dominant
model. Firstly, the heterogeneity between studies would
be assessed by the Q test and I2 statistics. According to the
presence (PQ < 0.1 or I2 ≥ 50%) or absence (PQ ≥ 0.1 and
I2 < 50%) of heterogeneity, different models would be used
to calculate the pooled ORs, with the former situation
using DerSimonian–Laird random-effects model while
the later using Mantel–Haenszel fixed-effects model.
If heterogeneity existed, Galbraith plot analyses would
be carried out to investigate the sources of
heterogeneity among studies. Then, subgroup analysis by ethnicity
would be performed to address possible effects of these
polymorphisms on different population. To assess the
stability of the results, sensitivity analysis was performed by
sequential omission of individual studies, especially
studies whose genotype frequencies in the control populations
were deviated from HWE, as they may generate bias.
HWE in the control group population, if not reported in
the original article, would be tested via a goodness-of-fit
Chi square test. Finally, for each polymorphism, the Begg’s
funnel plots and Egger’s linear regression test was used to
test the publication bias (P < 0.05 indicated a significant
publication bias). All analyses were performed with Stata
software (Stata/SE version 12.0, Stata Corp, College
Station, TX) and all P values were two-sided.
There were 47 published articles relevant to the search
terms. By browsing the title and abstract, 25 studies were
excluded because of obvious irrelevance. After a
careful full-text review of the remaining 22 studies, a further
13 articles were removed: 7 were reviews; 2 were not
case–control studies; 2 focus on other SNPs of CYP2E1
or other cancer; and the rest 2 did not report sufficient
data. Additional eligible studies were not found through
manual search of the reference lists. Consequently,
night case–control studies focus on three CYP2E1
polymorphisms (rs2031920 C>T, CYP2E1*5 Rsa I/Pst I and
CYP2E1*6 Dra I) and breast cancer risk were included
in our meta-analysis [14, 15, 22–27]. Among them, the
study by Zgheib et al. . and Chong et al. . explored
the relationship of CYP2E1 mutation and breast cancer
risk in both CYP2E1*5 and CYP2E1*6 polymorphisms,
and were treated independently. As a result, a total of 11
separate comparisons involving 4311 cases and 4407
controls were finally included in the meta-analysis. A
schematic representation showing the process of inclusion/
exclusion of studies was illustrated in Fig. 1.
Fig. 1 Schematic representation of study selection procedure
Of all the selected articles, three studies consist of
1915 cases and 1793 controls evaluated the
association of CYP2E1 polymorphisms and breast cancer risk
in rs2031920 C>T polymorphism (one in African, one
in Asian and one in a mixed population) [14, 22, 23];
another four studies, with a total of 906 cases and 961
controls, was about CYP2E1*5 Rsa I/Pst I polymorphism
(three in Asian and one in Arab) [15, 24, 25]; the rest four
studies, including 1490 cases and 1653 controls, focus on
CYP2E1*6 Dra I polymorphism (two in Caucasian, one
in Arab and one in Asian) [25–27]. Among them, cases
were major confirmed pathologically (8 studies) with
their genotype determined using PCR–RFLP assays (7
studies), the rest were histologically confirmed or not
mentioned with genotyping via standard PCR methods
or TaqMan™ assays. The genotype distributions of the
controls in two studies were found to deviate from HWE
in rs2031920 C>T polymorphism while others were all
reported or calculated consistence with HWE. All studies
included met quality criteria ranging from 9 to 14, hence
two studies were regarded as low-quality and night was
high-quality. Basic characteristics of all eligible studies
were listed in Table 1.
The meta-analysis suggested that the rs2031920 C>T
polymorphism was not associated with BC risk in all
genetic models in the overall populations: (1) T vs. C
(OR = 0.91, 95% CI = 0.75–1.10, P = 0.317); (2) T/T
vs. C/C (OR = 0.87, 95% CI = 0.27–2.87, P = 0.821); (3)
C/T vs. C/C (OR = 0.94, 95% CI = 0.76–1.16, P = 0.549);
(4) T/T + C/T vs. C/C (OR = 0.92, 95% CI = 0.75–1.13,
P = 0.434); (5) T/T vs. C/T + C/C (OR = 0.87, 95%
CI = 0.26–2.89, P = 0.825) (Fig. 2a). Moreover, no
subgroup analysis was conducted in this mutation due to all
Table 1 Basic characteristics of all eligible studies in the meta-analysis
Case/control BC confirmation
CYP2E1*6 Dra I
CYP2E1*6 Dra I
CYP2E1*6 Dra I
Shields, 1996 New York,
Anderson, 2012 Canada
Zgheib, 2013 Lebanese
Chong, 2016 Malaysian
BC breast cancer, HC histologically confirmed, PC pathologically confirmed, NM not mentioned, PCR polymerase chain reaction, PCR–RFLP polymerase chain reaction–
restriction fragment length polymorphism, HB hospital-based, PB population-based, PI polymorphism(s) investigated, HWE Hardy–Weinberg equilibrium, QS quality
studies included were carried out in different ethnicity.
Considering the significant heterogeneity found in T/T
vs. C/C and T/T vs. C/T + C/C, random-effects model
were used in these comparison model, while the rest
using fix-effects model.
For the CYP2E1*5 Rsa I/Pst I (c1/c2)
polymorphism, we still failed to identify any significant
association with BC susceptibility: (1) c2 vs. c1 (OR = 0.97,
95% CI = 0.80–1.17, P = 0.718); (2) c2/c2 vs. c1/c1
(OR = 0.74, 95% CI = 0.42–1.30, P = 0.300); (3) c1/c2
vs. c1/c1 (OR = 1.03, 95% CI = 0.81–1.29, P = 0.797); (4)
c2/c2 + c1/c2 vs. c1/c1 (OR = 1.00, 95% CI = 0.80–1.24,
P = 0.994); (5) c2/c2 vs. c1/c2 + c1/c1 (OR = 0.75, 95%
CI = 0.43–1.30, P = 0.303) (Fig. 2b). Subgroup
analysis, focus on Asian population due to the limited
number of included studies, also found null association in all
comparison models. As no obvious heterogeneity was
observed, fix-effects model was used to pool all
comparison data of this polymorphism.
With regard to the CYP2E1*6 Dra I (D/C) variation,
our result indicated a significant increased BC risk in
genetic model D/C vs. D/D (OR = 1.29, 95% CI = 1.04–
1.61, P = 0.023) and C/C + D/C vs. D/D (OR = 1.25,
95% CI = 1.04–1.51, P = 0.019) (Fig. 2c), as well as in
allele model C vs. D (OR = 1.28, 95% CI = 1.05–1.55,
P = 0.014). When stratified by ethnicity, similar results
were also found in Caucasians in these three comparison
models. Details were present in Table 2. Because no
significant heterogeneity existed among all the comparison
models, fix-effects model were used.
As significant heterogeneity was found in the T/T vs.
C/C and T/T vs. C/T + C/C comparison models of
rs2031920 C>T polymorphism, Galbraith plot
analyses were carried out to detect the possible source of
heterogeneity. However, as show in Fig. 3, outliner was
observed in neither T/T vs. C/C model nor T/T vs.
C/T + C/C model, indicating that the studies included
in both two comparison models were not contributors to
Considering that there were two studies whose genotypes
inconsistent with HWE in rs2031920 C>T variation,
sensitivity analysis were performed to see if any single study
would greatly influenced the estimates of overall risk,
our result showed that the pooled ORs did not materially
altered with or without these studies (data not shown).
But we could not conduct sensitivity analysis for T/T vs.
C/C model and T/T vs. C/T + C/C model due to a
limited study number in these two models (only three
studies were included and one of them did not provided data
in T/T genotype).
Fig. 2 Forest plots of CYP2E1 gene polymorphisms and breast cancer (BC) risk. a Forest plots of CYP2E1 rs2031920 C>T polymorphism and BC risk
(contrast T/T + C/T vs. C/C). b Forest plots of CYP2E1*5 Rsa I/Rst I (c1/c2) polymorphism and BC risk (contrast c2/c2 + c1/c2 vs. c1/c1). c Forest plots of
CYP2E1*6 Dra I (D/C) polymorphism and BC risk (contrast C/C + D/C vs. D/D); all using a fix-effect model
To assess possible publication bias, Begg’s funnel plots
and Egger’s tests were performed simultaneously. The
funnel plots were symmetrical in all genetic models of
three CYP2E1 polymorphisms, indicating no significant
publication bias existed in all the articles included. Egger’s
test, with all the P value larger than 0.05, also revealed no
evidence of publication bias in our meta-analysis (Fig. 4).
Breast cancer, of which heredity explains
approximately 10–15% of the cases, with only 5% can be
clarified by known genetic polymorphisms such as BRCA1
and BRCA2 . Such fact suggesting that other
potential, common, but low-penetrance genetic variants may
contribute to individual’s susceptibility to breast cancer.
CYP2E1, a Phase I enzyme responsible for the metabolic
activation of various carcinogens such as
N-nitrosaminesan and alcohol, was in different activity among
individuals . It has been assumed that polymorphisms
of CYP2E1*5 and CYP2E1*6 may lead to a decreased
activity in CYP2E1 enzyme, thus linked to a lower risk of
cancer. Nevertheless, the power of a single study was too
small to draw a precise conclusion, we therefore
investigated breast cancer and CYP2E1 polymorphisms in these
common mutations using a meta-analysis.
However, in the present study, no significant
association was found between SNP rs2031920 C>T
polymorphism and BC. The haplotype CYP2E1*5, which consist
of SNP rs2031920 C>T and 3813867 G>C, also failed to
identify any significant association with BC risk. Single
SNP rs3813867 G>C was also taken into consideration,
but further analysis was not carried out due to the
suboptimal study numbers (n = 1) . Such insignificant
Table 2 Meta-analysis of the CYP2E1 gene polymorphisms on breast cancer risk
c2/c2 + c1/c2 vs. c1/c1
c2/c2 vs. c1/c2 + c1/c1
C/C + D/C vs. D/D
C/C vs. D/D + D/C
F fixed-effects model, R random-effects model
Italic values indicate significant difference (p < 0.05)
results may be partially attributed to the different
distribution of the CYP2E1*5 polymorphism between
varies races, with the rarest 0.05 in Caucasians and the
highest 0.23 in oriental populations . Nevertheless,
after stratified the study populations into different races,
where we mainly focus on Asian populations, the results
still failed to indicate any association between CYP2E1*5
polymorphism and BC development. The pooled results
of rs2031920 C>T SNP and BC risk were consistent with
those studies included in the present meta-analysis, all
indicating an insignificant relationship between them;
and the overall results of CYP2E1*5 polymorphism and
BC were also accordance with half of those included,
though one of the rest observed a decreased risk of BC
while another revealed an increased risk. Taken together,
it may be concluded that CYP2E1*5 polymorphisms are
not associated with BC risk in the overall population.
Interestingly, when considering the CYP2E1*6
polymorphism, our study found that individuals with the D/C
and C/C + D/C genotype had a significantly higher risk
of BC compared to those with the D/D genotype,
similar increased result was also found in the C allele
carriers when compared with the D allele carriers, especially
in Caucasian population. These results suggested that
polymorphism in CYP2E1*6 could be a risk factor for
BC development. But such result was inconsistent with
those of the original studies, of which all suggested no
significant relationship between any comparison model
of CYP2E1*6 variation and BC development.
Actually, our results should explain with caution as
there is increasing evidence that metabolizing enzymes
do not act alone. In the study carried out by Choi et al.
. that explored the role of alcohol and genetic
polymorphisms of CYP2E1*5 in BC development, no
Fig. 3 Galbraith plots of CYP2E1 gene polymorphisms and breast cancer (BC) risk in comparison models with significantly heterogeneity. a T/T vs.
C/C in rs2031920 C>T polymorphism. b T/T vs. C/T + C/C in rs2031920 C>T polymorphism
significant overall differences were found in the c1/c2
genotype frequencies between BC cases and controls.
However, after taking the drinking situation into
consideration, a 1.9-fold increasing risk for developing BC
was found when comparing the ‘ever’-drinking women
with the c2 mutation to the non-drinkers with the c1/
c1 mutation. Another study, investigated lifetime
passive cigarette smoke exposures together with genetic
Fig. 4 Begg’s funnel plot analysis and Egger’s test to detect publication bias. Each point represents a separate study for the indicated association. a
Begg’s funnel plot analysis and Egger’s test for contrast T/T + C/T vs. C/C. b Begg’s funnel plot analysis and Egger’s test for contrast c2/c2 + c1/c2 vs.
c1/c1. c Begg’s funnel plot analysis and Egger’s test for contrast C/C + D/C vs. D/D
variants and BC risk in women who had never smoked,
found that interaction between passive smoke exposure
and CYP2E1*6 AA/AT (namely CC/CD) polymorphism
could significant increased breast cancer risk among
premenopausal women . In sum, such gene-environment
interaction should be taken into consideration when
investigating CYP2E1 polymorphism in the development
of BC, however, due to the limited studies included, our
study could not conduct further analysis with these
factors taken into consideration.
To our knowledge, this is the first meta-analysis carried
out to date to evaluate the role of CYP2E1 polymorphisms
in breast cancer susceptibility. Despite the findings
mentioned above, this study had several limitations. First, we
haven’t taken the gene-environment interaction into
consideration. As is known to all, apart from genetic factors,
smoking status and alcohol consumption are important risk
factors for BC; however, we could not conduct subgroup
analyses stratified by environmental exposure due to the
limited information on our included studies. Second, the
overall results of our study were based on crude ORs, but
a more precise evaluation should be adjusted for the know
risk factors such as age and menopause status. Third, the
number of studies included in this study is relatively small,
with three or four studies for each polymorphism, which
may lead to low statistical power and prevent us from
exploring a real association of the CYP2E1 polymorphism
and BC risk. Fourth, because no attempts were made to
access unpublished studies and studies in languages other
than English, publication bias may exist, though results of
our Begg’s funnel plot and Egger’s test did not reveal any
publication bias. Fifth, as most studies were conducted in
Asian and Caucasian population, the relative lack of ethnic
diversity demands for further studies.
Aside from the above limitations, this meta-analysis
suggests that CYP2E1*6 Dra I (D/C) polymorphism might be
associated with increased BC risk, individuals with D/C
and C/C + D/C genotypes or carried at least one C allele
of CYP2E1*6 Dra I (D/C) polymorphism had a
significant higher susceptibility to develop BC, in Caucasians,
particularly. Whereas, no any significant relationship
between CYP2E1*5 Rsa I/Rst I (c1/c2), rs2031920 C>T
polymorphisms and BC risk was found.
Additional file 1: Table S1. Scale for quality assessment.
OR: odds ratios; CI: confidence intervals; BC: breast cancer; SNP: single
nucleotide polymorphisms; HWE: Hardy–Weinberg equilibrium.
XQ and YL conceived and designed the experiments, XZ and CZ carried out
the experiments, KJ and CH analyzed the data, YL wrote the manuscript. All
authors read and approved the final manuscript.
The authors declare that they have no competing interests.
Availability of data and materials
All data generated or analysed during this study are included in this published
article (and its additional information files).
1. Ferlay J , Shin HR , Bray F , Forman D , Mathers C , Parkin DM . Estimates of worldwide burden of cancer in 2008: GLOBOCAN 2008. Int J Cancer . 2010 ; 127 ( 12 ): 2893 - 917 . doi:10.1002/ijc.25516.
2. Dumitrescu RG , Cotarla I. Understanding breast cancer risk-where do we stand in 2005? J Cell Mol Med . 2005 ; 9 ( 1 ): 208 - 21 .
3. Madigan MP , Ziegler RG , Benichou J , Byrne C , Hoover RN . Proportion of breast cancer cases in the United States explained by well-established risk factors . J Natl Cancer Inst . 1995 ; 87 ( 22 ): 1681 - 5 .
4. Dunning AM , Healey CS , Pharoah PD , Teare MD , Ponder BA , Easton DF. A systematic review of genetic polymorphisms and breast cancer risk . Cancer Epidemiol Biomarkers Prev . 1999 ; 8 ( 10 ): 843 - 54 .
5. Coon MJ , Koop DR . Alcohol-inducible cytochrome P-450 (P-450ALC) . Arch Toxicol . 1987 ; 60 ( 1-3 ): 16 - 21 .
6. Yang CS , Yoo JS , Ishizaki H , Hong JY. Cytochrome P450IIE1: roles in nitrosamine metabolism and mechanisms of regulation . Drug Metab Rev . 1990 ; 22 ( 2-3 ): 147 - 59 . doi:10.3109/03602539009041082.
7. Key J , Hodgson S , Omar RZ , Jensen TK , Thompson SG , Boobis AR , et al. Meta-analysis of studies of alcohol and breast cancer with consideration of the methodological issues . Cancer Causes Control . 2006 ; 17 ( 6 ): 759 - 70 . doi:10.1007/s10552- 006 - 0011 -0.
8. Dossus L , Boutron-Ruault MC , Kaaks R , Gram IT , Vilier A , Fervers B , et al. Active and passive cigarette smoking and breast cancer risk: results from the EPIC cohort . Int J Cancer . 2014 ; 134 ( 8 ): 1871 - 88 . doi:10.1002/ijc.28508.
9. Terry PD , Goodman M. Is the association between cigarette smoking and breast cancer modified by genotype? A review of epidemiologic studies and meta-analysis . Cancer Epidemiol Biomarkers Prev . 2006 ; 15 ( 4 ): 602 - 11 . doi:10.1158/ 1055 - 9965 . EPI-05-0853.
10. Hayashi S , Watanabe J , Kawajiri K. Genetic polymorphisms in the 5′-flanking region change transcriptional regulation of the human cytochrome P450IIE1 gene . J Biochem . 1991 ; 110 ( 4 ): 559 - 65 .
11. Watanabe J , Hayashi S , Kawajiri K. Different regulation and expression of the human CYP2E1 gene due to the RsaI polymorphism in the 5′-flanking region . J Biochem . 1994 ; 116 ( 2 ): 321 - 6 .
12. Han XM , Zhou HH . Polymorphism of CYP450 and cancer susceptibility . Acta Pharmacol Sin . 2000 ; 21 ( 8 ): 673 - 9 .
13. Uematsu F , Kikuchi H , Motomiya M , Abe T , Sagami I , Ohmachi T , et al. Association between restriction fragment length polymorphism of the human cytochrome P450IIE1 gene and susceptibility to lung cancer . Jpn J Cancer Res . 1991 ; 82 ( 3 ): 254 - 6 .
14. Khedhaier A , Hassen E , Bouaouina N , Gabbouj S , Ahmed SB , Chouchane L. Implication of xenobiotic metabolizing enzyme gene (CYP2E1, CYP2C19, CYP2D6, mEH and NAT2) polymorphisms in breast carcinoma . BMC Cancer . 2008 ; 8 :109. doi:10.1186/ 1471 - 2407 - 8 - 109 .
15. Wu SH , Tsai SM , Hou MF , Lin HS , Hou LA , Ma H , et al. Interaction of genetic polymorphisms in cytochrome P450 2E1 and glutathione S-transferase M1 to breast cancer in Taiwanese woman without smoking and drinking habits . Breast Cancer Res Treat . 2006 ; 100 ( 1 ): 93 - 8 . doi:10.1007/ s10549- 006 - 9226 -8.
16. Chong ET , Goh LP , See EU , Chuah JA , Chua KH , Lee PC . Association of CYP2E1, STK15 and XRCC1 polymorphisms with risk of breast cancer in Malaysian women . Asian Pac J Cancer Prev . 2016 ; 17 ( 2 ): 647 - 53 .
17. Stroup DF , Berlin JA , Morton SC , Olkin I , Williamson GD , Rennie D , et al. Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis of Observational Studies in Epidemiology (MOOSE) group . JAMA . 2000 ; 283 ( 15 ): 2008 - 12 .
18. Thakkinstian A , McElduff P , D'Este C , Duffy D , Attia J. A method for metaanalysis of molecular association studies. Stat Med . 2005 ; 24 ( 9 ): 1291 - 306 . doi:10.1002/sim. 2010 .
19. Qin X , Peng Q , Chen Z , Deng Y , Huang S , Xu J , et al. The association between MTHFR gene polymorphisms and hepatocellular carcinoma risk: a meta-analysis . PLoS ONE . 2013 ; 8 ( 2 ) :e56070 . doi:10.1371/journal. pone.0056070.
20. Ma L , Zhao J , Li T , He Y , Wang J , Xie L , et al. Association between tumor necrosis factor-alpha gene polymorphisms and prostate cancer risk: a meta-analysis . Diagn Pathol . 2014 ; 9 ( 1 ): 74 . doi:10.1186/ 1746 - 1596 - 9 - 74 .
21. Lu Y , Mo C , Zeng Z , Chen S , Xie Y , Peng Q , et al. CYP2D6*4 allele polymorphism increases the risk of Parkinson's disease: evidence from meta-analysis . PLoS ONE . 2013 ; 8 ( 12 ) :e84413 . doi:10.1371/journal. pone.0084413.
22. Sangrajrang S , Sato Y , Sakamoto H , Ohnami S , Khuhaprema T , Yoshida T. Genetic polymorphisms in folate and alcohol metabolism and breast cancer risk: a case-control study in Thai women . Breast Cancer Res Treat . 2010 ; 123 ( 3 ): 885 - 93 . doi:10.1007/s10549- 010 - 0804 -4.
23. McCarty CA , Reding DJ , Commins J , Williams C , Yeager M , Burmester JK , et al. Alcohol , genetics and risk of breast cancer in the prostate, lung, colorectal and ovarian (PLCO) cancer screening trial . Breast Cancer Res Treat . 2012 ; 133 ( 2 ): 785 - 92 . doi:10.1007/s10549- 012 - 1972 -1.
24. Choi JY , Abel J , Neuhaus T , Ko Y , Harth V , Hamajima N , et al. Role of alcohol and genetic polymorphisms of CYP2E1 and ALDH2 in breast cancer development . Pharmacogenetics . 2003 ; 13 ( 2 ): 67 - 72 . doi:10.1097/01. fpc. 0000054060 .98065.fc.
25. Zgheib NK , Shamseddine AA , Geryess E , Tfayli A , Bazarbachi A , Salem Z , et al. Genetic polymorphisms of CYP2E1, GST, and NAT2 enzymes are not associated with risk of breast cancer in a sample of Lebanese women . Mutat Res . 2013 ; 747 - 748 : 40 - 7 . doi:10.1016/j. mrfmmm. 2013 .04.004.
26. Shields PG , Ambrosone CB , Graham S , Bowman ED , Harrington AM , Gillenwater KA , et al. A cytochrome P4502E1 genetic polymorphism and tobacco smoking in breast cancer . Mol Carcinog . 1996 ; 17 ( 3 ): 144 - 50 . doi:10.1002/(sici) 1098 - 2744 (199611) 17:3<144:aid-mc6>3.0.co;2-f .
27. Anderson LN , Cotterchio M , Mirea L , Ozcelik H , Kreiger N. Passive cigarette smoke exposure during various periods of life, genetic variants, and breast cancer risk among never smokers . Am J Epidemiol . 2012 ; 175 ( 4 ): 289 - 301 . doi:10.1093/aje/kwr324.
28. Bennett IC , Gattas M , Teh BT . The genetic basis of breast cancer and its clinical implications . Aust N Z J Surg . 1999 ; 69 ( 2 ): 95 - 105 .