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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Ann Epidemiol. Author manuscript; available in PMC 2017 March 24.
Published in final edited form as:
PMCID: PMC5364809

Genetic polymorphisms of phase I metabolizing enzyme genes, their interaction with lifetime grilled and smoked meat intake, and breast cancer incidence



To examine associations between 22 CYP single nucleotide polymorphisms (SNPs) and breast cancer incidence and their interactions with grilled–smoked meat intake, a source of polycyclic aromatic hydrocarbons.


White women with first primary in situ or invasive breast cancer (n = 988) and frequency-matched controls (n = 1021) from a population-based study were interviewed to assess lifetime grilled–smoked meat intake. SNPs with minor allele frequencies of greater than 0.05 were selected because of their links to carcinogenesis. We used multivariable unconditional logistic regression to estimate odds ratios (ORs) and 95% confidence intervals (CIs).


Breast cancer was inversely associated with CYP1A1 rs104C8943 AG + GG genotype (OR = 0.71, 95% CI = 0.50–0.99; vs. AA genotype) and positively associated with CYP1B1 rs10175338 TT genotype (OR = 1.59, 95% CI = 1.12–2.26; vs. GG genotype) and the CYP3A4 rs2242480 CT + TT genotype (OR = 1.25, 95% CI = 1.00–1.56; vs. CC genotype). The sum of the number of “at-risk” alleles for the CYP SNPs was positively associated with breast cancer incidence (4–6 “at-risk” alleles OR = 2.33, 95% CI = 1.37–3.99 vs. 0-1 alleles; PTrend < .01). We observed multiplicative and additive interactions (P <.05) between grilled –smoked meat intake (low vs. high) with CYP1A1 rs1048943 and CYP1B1 rs10175338 SNPs.


Phase I metabolizing enzyme gene SNPs may play a role in breast cancer development and may modify the grilled–smoked meat intake–breast cancer association.

Keywords: Breast cancer, Cytochrome p450 enzymes, Polymorphism, Grilled and smoked meat, Gene–environment interactions


Breast cancer is the most frequently diagnosed cancer among women in the United States with more than 231,000 new breast cancer cases estimated in 2016 [1]. Environmental exposures may play a role in breast carcinogenesis [2], particularly in concert with polymorphic low penetrance, but common genes [3]. Exposure to polycyclic aromatic hydrocarbons (PAHs), a group of more than 100 different chemicals that are formed during the incomplete combustion of coal, oil, and gas and other organic substances like tobacco and are in charbroiled and/or smoked meat [4], has been associated with elevated breast cancer incidence [5]. During grilling and barbecuing, specifically, PAHs are generated through pyrolysis of meat products when fat drips from the meat onto a heated surface and produces smoke that coats the food with the compounds [6]. Dietary PAH exposures from grilled–smoked meat, the primary source of PAH exposure among nonsmokers [7], have been associated with breast cancer incidence, with effect estimates ranging from 1.47 to 2.21 when comparing the highest to the lowest quantiles of intake of well-done meat [812].

Once ingested, PAHs induce expression of and are metabolized by phase I and phase II metabolizing enzymes. In phase I metabolism, PAH parent compounds are activated to dihydrodiol intermediates by cytochrome P450 (CYP) enzymes [13]. The dihydrodiols are further oxidized by CYPs into highly reactive diol epoxides, which are able to covalently bind to exocyclic amino groups of adenine and guanine, forming stable adducts on DNA [14,15]. The DNA adducts can cause mismatch in DNA replication and may alter promoter methylation or promoter binding, leading to inheritable DNA mutations or abnormal gene expression [16]. The main enzymes involved in phase I PAH metabolism include CYP1A1 (CYP1A1 located on chromosome 15q24.1), CYP1A2 (CYP1A2 located on chromosome 15q24.1), CYP1B1 (CYP1B1 located on chromosome 2p22.2), and CYP3A4 (CYP3A4 located on chromosome 7q21.1), four of approximately 60 CYP enzymes [13].

CYP enzymes are primarily and abundantly expressed in the liver, kidneys, gastrointestinal tract, and lungs [17], but they are also expressed in normal breast tissue [18]. PAHs are activated and metabolized by breast epithelial cells [19], and overexpression of CYP enzymes and elevated levels of PAH-DNA adduct have been observed in breast tumor tissue [20]. Given the central role of CYP enzymes in the metabolism of xenobiotics, polymorphisms in CYP genes, especially those that may potentially alter the activity (e.g., rs1048943, rs2472299, and rs2567206 located in promoter regions) or inducibility (e.g., rs1056836, rs1800440, and rs10012 located in exonic regions) relative to the common alleles may influence breast cancer risk [21].

In the present study, we had two study goals. First, to examine the associations between 22 single nucleotide polymorphisms (SNPs) in four CYP enzyme genes (CYP1A1, CYP1A2, CYP1B1, and CYP3A4) and breast cancer incidence. Second, to examine whether the SNPs associated with breast cancer also modify the positive association between intake of grilled–smoked meat and breast cancer incidence previously reported by our group [8]. We hypothesized that polymorphisms that lead to increased enzymatic activity and therefore increased production of procarcinogens would be positively associated with breast cancer incidence, whereas those that lead to decreased enzymatic activity would be inversely associated with breast cancer. We also hypothesized that high intake of grilled–smoked meat and SNPs that confer increased enzymatic activity would act synergistically to increase the risk of incident breast cancer.

Materials and methods

This study used resources from the case–control component of the Long Island Breast Cancer Study Project (LIBCSP), a population-based study of adult women living in Nassau and Suffolk Counties on Long Island, New York [22].

Study population

Details of the LIBCSP case–control participants have been previously described [22]. In brief, women aged older than 20 years who were residents of Nassau and Suffolk Counties on Long Island, New York, and who were diagnosed with invasive or in situ breast cancer in 1996–1997 were identified using a rapid reporting system established for the LIBCSP. Diagnosed breast cancer cases were confirmed by each case’s physician and by medical record review. Of the 2271 total women identified, consent was obtained for 1837, and of these, 1508 (82.1%) completed the main questionnaire. Control women were residents of the same two Long Island counties who were frequency matched to the expected age distribution of the case women on 5-year age group. Control women aged 65 years and older were identified by Health Care Finance Administration rosters and those aged younger than 65 years were identified by random digit dialing [23]. Of the 2714 women identified as potential controls, consent was obtained by 2481, and of these, 1556 (62.7%) completed the main questionnaire. Participants ranged in age from 20 to 95 years at diagnosis or date of identification for controls, and most were postmenopausal (66%) and self-identified as White (93%), which reflects the underlying racial distribution of these Long Island counties at the time of data collection.


This study was approved by the Institutional Review Board of the University of North Carolina at Chapel Hill (approval no. 12-0131). Written informed consent was obtained from participants before data collection.

Assessment of dietary intake

On average, within 3 months of breast cancer diagnosis, LIBCSP participants completed an interviewer-administered main questionnaire and a self-administered food frequency questionnaire. The questionnaire elicited information on known and suspected risk factors for breast cancer, including reproductive, occupational, lifestyle, medical and environmental factors, as well as demographic characteristics. The food frequency questionnaire, which was completed by 98% of respondents, elicited information on approximately 100 food items that assessed usual diet in the previous year and was used to determine consumption of energy (kcal/day), fruit and vegetable intake (servings per day), and multivitamin supplement use (ever/never). The main questionnaire also included an assessment of intake of four categories of grilled–barbecued meat and smoked meat (grilled–barbecued beef, lamb, or pork; grilled–barbecued poultry or fish; smoked beef, lamb, or pork; and smoked poultry or fish) in each decade of life (<20 years, 20–29 years, 30–39 years, 40–49 years, 50–59 years, and ≥60 years), which was used to estimate the lifetime consumption of grilled, barbecued, and smoked meat [8,24]. We previously reported that total intake of grilled–smoked meat (lifetime servings) was the variable definition most strongly associated with breast cancer incidence [8], and thus it is the definition we use in the gene–environment study reported here.

SNP selection and genotyping

We selected 24 polymorphisms representing four genes of phase I metabolizing CYP enzymes: CYP1A1 (rs1531163, rs2472299, rs2606345, rs4646903, rs1048943, and rs1800031), CYP1A2 (rs2069522, rs2470890, rs2472304, and rs762551), CYP1B1 (rs10175338, rs10175368, rs1056836, rs10916, rs162330, rs162555, rs162556, rs162557, rs162562, and rs1800440), and CYP3A4 (rs11773597, rs12333983, rs2242480, and rs2740574). The 24 polymorphisms were selected because of the documented role of the CYP enzymes in the activation of PAHs [13], the reported link of the SNPs to carcinogenesis [25], and previously reported minor allele frequencies of at least 0.05 in Caucasian women [25].

At the time of the interview, approximately 73% of participants provided a nonfasting blood sample. As previously reported [22], participants were more likely to donate blood if they were aged younger than 65 years, used oral contraceptives–hormone replacement, drank alcohol, and had ever received a mammogram, but were nonsmokers. Genomic DNA was extracted from the mononuclear cells in whole blood separated by Ficoll (Sigma Chemical Co., St. Louis, MO). CYP1A1 SNPs rs4646903, rs1048943, and rs1800031 were genotyped by BioServe Biotechnologies (Laurel, MD) using Sequenom’s (San Diego, CA) high-throughput matrix-assisted laser desorption/ionization time-of-flight mass spectrometry [26]. The remainder of the SNPs were genotyped at the University of North Carolina at Chapel Hill using the Illumina GoldenGate assay (Illumina, Inc., San Diego, CA). For the latter, assay intensity data and genotype cluster images for all SNPs were reviewed individually using GenomeStudio software, v. 2011.1. Blind duplicates of 56 samples were genotyped to verify the reproducibility of genotype calls. Concordance between duplicates was greater than 99.4% for all pairs.

Statistical analysis

This study is restricted to the 2009 women (n cases = 988 and n controls = 1021) who self-identified as White and for whom genotyping data were available because of the small sample sizes in other race–ethnicity groups. We tested for Hardy–Weinberg equilibrium among the control women using Proc Allele on SAS/Genetics version 9.3 (Cary, NC) at an alpha level of 0.05. Two SNPs (rs4646903 and rs11773597) exhibited significant departure from Hardy–Weinberg equilibrium and were not considered further. We also examined all SNPs for linkage disequilibrium (LD) using the SNAP database based on HapMap [27]. The following pairwise SNPs were in LD: CYP1A2 rs2470890 and rs2472304; CYP1B1 rs10175338 and rs10175368; and CYP1B1 rs10916 and rs162562. For the three pairs of SNPs in LD, only the results for one SNP (rs2470890, rs10175338, rs10916) are presented.

For the statistical analysis, we addressed our two study goals. First, to examine whether 22 SNPs in four CYP genes are associated with breast cancer risk. And, second, to examine whether interactions between these SNPs and intake of grilled–smoked meat were associated with breast cancer. To address the first goal, odds ratios (ORs) and 95% confidence intervals (CIs) of the associations between 22 CYP genotypes and breast cancer incidence were estimated using unconditional logistic regression [28] in SAS version 9.4 (Cary, NC). In the text, we present results of dominant models; results of additive models are presented in Supplemental Table 1. All models were adjusted for age to account for frequency matching. Common homozygote genotypes defined among the control women were the referent group for all analyses. We created a summary SNP index for each participant by summing the number of “at-risk” alleles present for each SNP that was found to be associated with breast cancer (total of three SNPs). Based on the associations presented in Table 1, the “at-risk” allele was defined as the less common (variant) allele (CYP1B1 rs10175338: T allele; and CYP3A4 rs2242480: T allele), with the exception of the CYP1A1 rs1048943 SNP where the more common allele (A allele) was associated with increased risk in this population. SNPs that were significantly associated with breast cancer incidence were further considered as interactions with lifetime grilled–smoked meat intake, dichotomized at the median (high = 4297 to 51,652 vs. low = 0 to 4296) among controls.

Table 1
Age-adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for cytochrome P450 genotypes in breast cancer cases and controls in the Long Island Breast Cancer Study Project (n = 2009)

To address our second study goal, the interaction of CYP genotypes with intake of grilled–smoked meat was evaluated by including cross-product terms in the logistic regression models. Multiplicative interactions were examined by comparing the models with the interaction term against a reduced model that included only terms for the main effects and conducting a likelihood ratio test; the results are presented by stratifying the grilled–smoked meat intake–breast cancer association by CYP genotype. For additive interaction, we explored the joint effects of lifetime grilled–smoked meat intake and CYP genotype (heterozygous + variant allele vs. common allele); we created three indicator variables for each SNP and included all three variables in a single logistic regression model. The following covariates were considered as potential confounders of the association between grilled–smoked meat intake and incident breast cancer: age, menopausal status, education, parity, use of hormone replacement therapy, smoking status, physical activity, body mass index, alcohol intake, energy intake, intake of fruits and vegetables, and single and multiple vitamin use [8]. Of these, the following covariates were found to change the effect estimate for the association between grilled–smoked meat intake and breast cancer incidence by more than 10% and were included in the final multivariable models: age at diagnosis (5-year age groups), energy intake (continuous), fruit and vegetable intake (categorized as quintiles of intake in the past 12 months), and multivitamin supplement use (yes vs. no).


Results corresponding to our two study goals (to determine whether breast cancer risk was associated with 22 SNPs in four CYP genes and the interaction between CYP SNPs and intake of grilled–smoked foods) are presented in the following.

CYP SNPs and breast cancer risk

The CYP1A1 rs1048943 AG + GG genotype was inversely associated with breast cancer incidence (OR = 0.71, 95% CI = 0.50–0.99) relative to the AA genotype, as shown in Table 1. We observed increased ORs for the associations between breast cancer incidence and CYP1B1 rs10175338 TT (ORTT vs. GG = 1.59, 95% CI = 1.12–2.26), which was in LD with rs10175368, and CYP3A4 rs2242480 CT + TT (ORCT + TT vs. CC = 1.25, 95% CI = 1.00–1.56). The sum of the number of “at-risk” alleles for these three CYP SNPs (rs10175338, rs2242480, and rs1048943) was positively associated with breast cancer incidence (PTrend < .01); the odds of breast cancer incidence among women with 4–6 “at-risk” alleles was 2.33 (95% CI = 1.37–3.99) times the odds among women with 0 or 1 “at-risk” alleles.

CYP SNP interactions with grilled–smoked meat intake and breast cancer risk

We observed significant effect modification on a multiplicative scale of the association between total grilled–smoked meat intake over the life-course and breast cancer incidence by CYP1A1 rs1048943 (PInteraction = .03) and CYP1B1 rs10175338 (PInteraction < .01) SNPs (Table 2). Among women with the CYP1B1 rs10175338 GG genotype, the OR for the association with high grilled–smoked meat intake, compared with low intake, was increased approximately 60% (OR = 1.59, 95% CI = 1.15–2.20); but among women with the GT + TT genotypes and high grilled–smoked meat intake, the OR was decreased approximately 30% (OR = 0.71, 95% CI = 0.50–1.02). There was some suggestion of effect modification by the CYP3A4 rs2242480 genotype (PInteraction = .07); the OR for the grilled–smoked meat–breast cancer association was elevated 59% (OR = 1.59, 95% CI = 0.91–2.77) among women with the CT + TT genotype, but not among women with the CC genotype (OR = 1.01, 95% CI = 0.78–1.30). In addition, as shown in Table 3, we observed effect modification on the additive scale for CYP1A1 rs1048943 (interaction contrast ratio = −0.82, 95% CI = −1.62 to −0.01) and CYP1B1 rs10175338 (interaction contrast ratio = −0.97, 95% CI = −1.72 to −0.23).

Table 2
Multivariable-adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for total grilled–smoked meat intake (lifetime servings) over the life course, stratified by cytochrome P450 genotype, Long Island Breast Cancer Study Project (n = 2009) ...
Table 3
Multivariable-adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for the joint effects of total grilled–smoked meat intake (lifetime servings) and cytochrome P450 genotype, Long Island Breast Cancer Study Project (n = 2009)


In our population-based case-control study of 22 SNPs of four CYP genes, the variant allele of CYP1A1 rs1048943 was associated with a reduced OR for breast cancer, whereas the variant alleles of CYP1B1 rs10175338 and CYP3A4 rs2242480 were associated with an increased OR for breast cancer incidence. The association with breast cancer was further elevated in a dose-response manner when we considered the sum of the risk alleles of the three SNPs. When considering effect measure modification, we observed multiplicative interactions between lifetime grilled–smoked meat intake with CYP1A1 rs1048943 and CYP1B1 rs10175338 and additive interactions for CYP1A1 rs1048943 and CYP1B1 rs10175338.

The CYP1A1 rs1048943, an A >G transition in exon 7, leads to the substitution of isoleucine (Ile) for valine (Val), resulting in increased enzymatic activity [29]. This suggests more efficient generation of reactive PAH intermediates, and thus increased breast cancer risk. However, CYP1A1 also catalyzes the conversion of estradiol into noncarcinogenic 2-hydroxyestradiol in extra-hepatic tissues, which may explain the inverse association we observed in this study between the CYP1A1 rs1048943 Ile/Val-genotype and breast cancer. Our findings are consistent with at least one other case–control study [30] of Japanese women in which the Ile/Val-genotype was found to be associated with reduced breast cancer incidence compared with the Ile/Ile genotype; however, a meta-analysis did not report reduced breast cancer incidence for the Ile/Val or Val/Val genotypes [31]. Prior studies also have not supported an association between breast cancer risk and CYP3A4 rs2242480 [32] and CYP1B1 rs10175368 [33,34] variants. In contrast, in this study, we report a positive association with the variant alleles of CYP1B1 rs10175338 and CYP3A4 rs2242480. These SNPS occur within the noncoding regions of CYP1B1 and CYP3A4, and the associations may be explained by linkage of these SNPS with other polymorphisms that have an effect on enzymatic function. For example, in addition to being in LD with each other, CYP1B1 rs10175338 and rs10175368 are also in LD with CYP1B1 rs1056827 [27], located in the second exon of chromosome 2p21.22 that results in an amino acid change from alanine to serine [35]. However, it is possible that these SNPS may have functional effects as well. Polymorphisms in noncoding sequences may influence gene function by altering the level, location, stability, or timing of gene expression [36]. rs2242480, a C > T substitution in intron 10 of CYP3A4, significantly increases its transcription [37].

No previous studies have examined the joint effects on breast cancer risk of CYP genotype and grilled–smoked meat intake, an important source of PAH exposure [7]. However, the interaction between the CYP1A1 variants and environmental exposures has been studied in relation to cigarette smoking, polychlorinated biphenyls, and alcohol intake with some positive results [31]. For example, Ambrosone et al. found that carriers of the CYP1A1 Ile/Val genotype versus the Ile/Ile genotype who were nonsmokers, light smokers, and heavy smokers had relative risks of breast cancer of 1.30 (95% CI = 0.62–2.70), 5.22 (95% CI = 1.16–23.56), and 0.86 (95% CI = 0.24–3.09), respectively [38]. Consistent with the findings of an elevated risk of breast cancer among nonsmokers and light smokers with CYP variant alleles, we observed elevated ORs among women with the rs10175338 variant allele and 4–6 “at-risk” alleles and low intake of grilled–smoked meats (Table 3). As is hypothesized in the smoking and lung cancer literature [39], this may suggest that subtle changes in enzyme function based on genotype are masked among those who have high levels of exposure. Our results reported here show that the CYP genes may act antagonistically and synergistically to influence breast cancer development in the presence of dietary exposures. These results further contribute to the growing evidence for a role of PAHs in the etiology of breast cancer [40].

Our study used a large population-based case–control design to examine the genetic variants of the four main CYP enzymes involved in the metabolism of PAHs; however, several limitations should be noted. First, the large number of statistical tests could have resulted in spurious results. However, the associations examined here are biologically plausible as polymorphisms in genes encoding the CYP metabolizing enzymes are known to have the potential to alter enzyme activity and inducibility. In this report, we were interested understanding the main effects of the CYP genetic polymorphisms as well as their interactions with intake of grilled–smoked meat. We therefore do not present Bonferroni-corrected results, which can be overly conservative. Second, it is possible that the associations observed here are confounded by other SNPs not measured in our study. This may be especially true for the SNPs that occur in noncoding regions. However, the SNPs examined in this study have been shown to impact CYP enzyme activity. Third, approximately, 73% of case participants and 73% of control participants provided blood samples for analyses resulting in a sample size of 2009 for the present study. Donation of biological samples varied with age with lower proportions of older women, and in particular older control women, donating blood [22]. It is possible that this selection could bias our results; however, the proportion of eligible subjects who donated blood is comparable with other population-based studies that collected blood [41]. Thus, LIBCSP study results are likely to be as representative of the general population as those from other major population-based studies of breast cancer. Fourth, we used a self-reported measure of lifetime intake of grilled–smoked meat rather than an estimate of PAH intake specifically or a PAH biomarker. Grilling and smoking foods is well-known to increase the level of carcinogenic PAHs [7]. Importantly, measurement of PAH exposure by use of biomarkers reflects short-term exposure as adducts are excised, and DNA is repaired. Therefore, self-reported measurements of long-term exposure are our best alternative. Although the validity of recall of lifetime intake of grilled–smoked meat has not been directly examined, prior studies have reported modest correlations between dietary assessment at one point in time and recall of the same diet up to 20 years later [42,43]. Misclassification of the intake of grilled–smoked meat could result in bias toward or away from the null. In addition, while our categorization of lifetime intake of grilled–smoked meat intake at the median maximized our power to examine interactions and allowed us to more easily examine both multiplicative and additive interactions, this categorization scheme limits our ability to make clinical or public health recommendations regarding specific quantities in intake of grilled–smoked meat as related to risk of breast cancer. In a previous report where we describe our results of examining the intake of grilled–smoked foods in association with the risk of developing breast cancer [8], we considered intake at various ages and lag times. However, the strongest associations with breast cancer risk were with cumulative lifetime intake. Thus, for the interaction analysis, we a priori decided to consider lifetime intake only. Furthermore, we also decided against including a lag period since the main carcinogens in grilled–smoked meat, PAHs, could act as both initiators and promoters—several PAHs including chrysene and fluoranthene show estrogenic activity in vitro [44]— and so including a lag may underestimate the associations. Finally, it is possible that there could be differential recall of grilled– smoked meat intake by case–control status; however, previous studies of long-term recall of diet have not found differential recall between cancer cases and controls [45].

In summary, results from our population-based study indicate that genetic variants of four phase I metabolizing enzyme genes may play a role in breast cancer development and may modify the positive association between grilled–smoked meat intake and breast cancer.

Supplementary Material


The authors gratefully acknowledge grant support from The National Cancer Institute and the National Institutes of Environmental Health Sciences (UO1CA/ES66572, UO1CA66572, 1K07CA102640-01, T32ES007018, R25CA057726, ES009089) and the American Institute for Cancer Research (AICR-03B091).


Conflicts of interest: None declared.


1. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2015. CA Cancer J Clin. 2015;65:21254. [PubMed]
2. Wolff MS, Weston A. Breast cancer risk and environmental exposures. Environ Health Perspect. 1997;105(Suppl 4):891–6. [PMC free article] [PubMed]
3. Beggs AD, Hodgson SV. Genomics and breast cancer: the different levels of inherited susceptibility. Eur J Hum Genet. 2009;17:855–6. [PMC free article] [PubMed]
4. Agency for Toxic Substances and Disease Registry (ATSDR) [Accessed January 14, 2016];Public Health Statement: Polycyclic Aromatic Hydrocarbons (PAHs) 1995 :6. Available at:
5. Gammon MD, Santella RM. PAH, genetic susceptibility and breast cancer risk: an update from the Long Island Breast Cancer Study Project. Eur J Cancer. 2008;44:636–40. [PubMed]
6. Larsson BK. Formation of polycyclic aromatic hydrocarbons during the smoking and grilling of food. Prog Clin Biol Res. 1986;206:169–80. [PubMed]
7. Phillips DH. Polycyclic aromatic hydrocarbons in the diet. Mutat Res. 1999;443:139–47. [PubMed]
8. Steck SE, Gaudet MM, Eng SM, Britton JA, Teitelbaum SL, Neugut AI, et al. Cooked meat and risk of breast cancer–lifetime versus recent dietary intake. Epidemiology. 2007;18:373–82. [PubMed]
9. Dai Q, Shu XO, Jin F, Gao YT, Ruan ZX, Zheng W. Consumption of animal foods, cooking methods, and risk of breast cancer. Cancer Epidemiol Biomarkers Prev. 2002;11:801–8. [PubMed]
10. Zheng W, Gustafson DR, Sinha R, Cerhan JR, Moore D, Hong CP, et al. Well-done meat intake and the risk of breast cancer. J Natl Cancer Inst. 1998;90:1724–9. [PubMed]
11. De Stefani E, Ronco A, Mendilaharsu M, Guidobono M, Deneo-Pellegrini H. Meat intake, heterocyclic amines, and risk of breast cancer: a case-control study in Uruguay. Cancer Epidemiol Biomarkers Prev. 1997;6:573–81. [PubMed]
12. Knekt P, Steineck G, Jarvinen R, Hakulinen T, Romaa A. Intake of fried meat and risk of cancer: a follow-up study in Finland. Int J Cancer. 1994;59:756–60. [PubMed]
13. Luckert C, Ehlers A, Buhrke T, Seidel A, Lampen A, Hessel S. Polycyclic aromatic hydrocarbons stimulate human CYP3A4 promoter activity via PXR. Toxicol Lett. 2013;222:180–8. [PubMed]
14. Lin CH, Huang X, Kolbanovskii A, Hingerty BE, Amin S, Broyde S, et al. Molecular topology of polycyclic aromatic carcinogens determines DNA adduct conformation: a link to tumorigenic activity. J Mol Biol. 2001;306:1059–80. [PubMed]
15. Cavalieri EL, Higginbotham S, RamaKrishna NV, Devanesan PD, Todorovic R, Rogan EG, et al. Comparative dose-response tumorigenicity studies of dibenzo [alpha,l]pyrene versus 7,12-dimethylbenz[alpha]anthracene, benzo[alpha] pyrene and two dibenzo[alpha,l]pyrene dihydrodiols in mouse skin and rat mammary gland. Carcinogenesis. 1991;12:1939–44. [PubMed]
16. Moorthy B, Chun C, Carlin DJ. Polycyclic aromatic hydrocarbons: from metabolism to lung cancer. Toxicol Sci. 2015;145:5–15. [PMC free article] [PubMed]
17. Xu C, Li CY-T, Kong A-NT. Induction of phase I, II and III drug metabolism/transport by xenobiotics. Arch Pharm Res. 2005;28:249–68. [PubMed]
18. Williams JA, Phillips DH. Mammary Expression of Xenobiotic Metabolizing Enzymes and Their Potential Role in Breast Cancer. Cancer Res. 2000;60:4667–77. [PubMed]
19. MacNicoll AD, Easty GC, Neville AM, Grover PL, Sims P. Metabolism and activation of carcinogenic polycyclic hydrocarbons by human mammary cells. Biochem Biophys Res Commun. 1980;95:1599–606. [PubMed]
20. Floriano-Sanchez E, Rodriguez NC, Bandala C, Coballase-Urrutia E, Lopez-Cruz J. CYP3A4 expression in breast cancer and its association with risk factors in Mexican women. Asian Pac J Cancer Prev. 2014;15:3805–9. [PubMed]
21. Sergentanis TN, Economopoulos KP. Four polymorphisms in cytochrome P450 1A1 (CYP1A1) gene and breast cancer risk: a meta-analysis. Breast Cancer Res Treat. 2010;122:459–69. [PubMed]
22. Gammon MD, Neugut AI, Santella RM, Teitelbaum SL, Britton JA, Terry MB, et al. The Long Island Breast Cancer Study Project: description of a multi-institutional collaboration to identify environmental risk factors for breast cancer. Breast Cancer Res Treat. 2002;74:235–54. [PubMed]
23. Waksberg J. Sampling methods for random digit dialing. J Am Stat Assoc. 1978;73:40–6.
24. Gammon MD, Santella RM, Neugut AI, Eng SM, Teitelbaum SL, Paykin A, et al. Environmental toxins and breast cancer on Long Island. I. Polycyclic aromatic hydrocarbon DNA adducts. Cancer Epidemiol Biomarkers Prev. 2002;11:677–85. [PubMed]
25. Rodriguez-Antona C, Ingelman-Sundberg M. Cytochrome P450 pharmacogenetics and cancer. Oncogene. 2006;25:1679–91. [PubMed]
26. Steck SE, Gammon MD, Hebert JR, Wall DE, Zeisel H. GSTM1, GSTT1, GSTP1, and GSTA1 polymorphisms and urinary isothiocyanate metabolites following broccoli consumption in humans. J Nutr. 2008;137:904–9. [PMC free article] [PubMed]
27. Johnson AD, Handsaker RE, Pulit SL, Nizzari MM, O’Donnell CJ, de Bakker PIW. SNAP: a web-based tool for identification and annotation of proxy SNPs using HapMap. Bioinformatics. 2008;24:2938–9. [PMC free article] [PubMed]
28. Kleinbaum DG, Klein M. Logistic Regression: A Self-Learning Text. 3. New York, NY: Springer; 2010.
29. Diergaarde B, Potter JD, Jupe ER, Manjeshwar S, Shimasaki CD, Pugh TW, et al. Polymorphisms in genes involved in sex hormone metabolism, estrogen plus progestin hormone therapy use, and risk of postmenopausal breast cancer. Cancer Epidemiol Biomarkers Prev. 2008;17:1751–9. [PMC free article] [PubMed]
30. Miyoshi Y, Takahashi Y, Egawa C, Noguchi S. Breast cancer risk associated with CYP1A1 genetic polymorphisms in Japanese Women. Breast J. 2002;8:209–15. [PubMed]
31. Masson LF, Sharp L, Cotton SC, Little J. Cytochrome P-450 1A1 gene polymorphisms and risk of breast cancer: a HuGE review. Am J Epidemiol. 2005;161:901–15. [PubMed]
32. Johnson N, Walker K, Gibson LJ, Orr N, Folkerd E, Haynes B, et al. CYP3A variation, premenopausal estrone levels, and breast cancer risk. J Natl Cancer Inst. 2012;104:657–69. [PubMed]
33. Gaudet MM, Chanock S, Lissowska J, Berndt SI, Yang XR, Peplonska B, et al. Genetic variation of cytochrome P450 1B1 (CYP1B1) and risk of breast cancer among Polish women. Pharmacogenet Genomics. 2006;16:547–53. [PubMed]
34. Huang Y, Trentham-Dietz A, García-Closas M, Newcomb PA, Titus-Ernstoff L, Hampton JM, et al. Association of CYP1B1 haplotypes and breast cancer risk in Caucasian women. Cancer Epidemiol Biomarkers Prev. 2009;18:1321–3. [PMC free article] [PubMed]
35. Yu PJ, Chen WG, Feng QL, Chen W, Jiang MJ, Li ZQ. Association between CYP1B1 gene polymorphisms and risk factors and susceptibility to laryngeal cancer. Med Sci Monit. 2015;21:239–45. [PMC free article] [PubMed]
36. Tabor HK, Risch NJ, Myers RM. Candidate-gene approaches for studying complex genetic traits: practical considerations. Nat Rev Genet. 2002;3:391–7. [PubMed]
37. He B, Shi L, Qiu J, Tao L, Li R, Yang L, et al. A functional polymorphism in the CYP3A4 gene is associated with increased risk of coronary heart disease in the Chinese Han population. Basic Clin Pharmacol Toxicol. 2011;108:208–13. [PubMed]
38. Ambrosone CB, Freudenheim JL, Graham S, Marshall JR, Vena JE, Brasure JR, et al. Cytochrome P4501A1 and glutathione S-transferase (M1) genetic polymorphisms and postmenopausal breast cancer risk. Cancer Res. 1995;55:3483–5. [PubMed]
39. Schwartz AG, Prysak GM, Bock CH, Cote ML. The molecular epidemiology of lung cancer. Carcinogenesis. 2007;28:507–18. [PubMed]
40. White AJ, Bradshaw PT, Herring AH, Teitelbaum SL, Beyea J, Stellman SD, et al. Exposure to multiple sources of polycyclic aromatic hydrocarbons and breast cancer incidence. Environ Int. 2016;89:185–92. [PMC free article] [PubMed]
41. Millikan RC, Pittman GS, Newman B, Millikan C, Pittman GS, Newman B, et al. Cigarette smoking, N-acetyltransferases 1 and 2, and breast cancer risk. Cancer Epidemiol Biomarkers Prev. 1998;7:371–8. [PubMed]
42. Bakkum A, Bloemberg B, van Staveren WA, Verschuren M, West CE. The relative validity of a retrospective estimate of food consumption based on a current dietary history and a food frequency list. Nutr Cancer. 1988;11:41–53. [PubMed]
43. Byers TE, Rosenthal RI, Marshall JR, Rzepka TF, Cummings KM, Graham S. Dietary history from the distant past: a methodological study. Nutr Cancer. 1983;5:69–77. [PubMed]
44. Fertuck KC, Kumar S, Sikka HC, Matthews JB, Zacharewski TR. Interaction of PAH-related compounds with the alpha and beta isoforms of the estrogen receptor. Toxicol Lett. 2001;121:167–77. [PubMed]
45. Lindsted KD, Kuzma JW. Long-term (24-year) recall reliability in cancer cases and controls using a 21-item food frequency questionnaire. Nutr Cancer. 1989;12:135–49. [PubMed]