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Toxicol Sci. 2009 November; 112(1): 211–220.
Published online 2009 August 19. doi:  10.1093/toxsci/kfp199
PMCID: PMC2782353

N-acetyltransferase 2 Genotype Modification of Active Cigarette Smoking on Breast Cancer Risk among Hispanic and Non-Hispanic White Women

Abstract

While it has been demonstrated that cigarette smoke contains aromatic and heterocyclic amines that initiate carcinogenesis, the association between cigarette smoking and breast cancer remains controversial. N-acetyltransferase 2 (NAT2) catalyzes arylamine carcinogen biotransformation and NAT2 genetic polymorphisms may contribute to differential susceptibility to breast cancer. We tested whether NAT2 modified the association between cigarette smoking and breast cancer risk in a population-based study of Hispanic and non-Hispanic white women in the Southwest United States. Data were available for cigarette smoking and NAT2 polymorphisms for 717 cases (Hispanic, 251 and non-Hispanic white, 466) and 735 controls (Hispanic, 245 and non-Hispanic white, 490). NAT2 genotypes were translated into rapid, intermediate, slow, or very slow acetylator phenotypes. Odds ratios (ORs) and 95% confidence intervals (95% CIs) for the joint association of NAT2 with smoking on breast cancer risk were estimated using logistic regression. Non-Hispanic white women were more likely (p < 0.001) than Hispanic women to have a slow (41.7 vs. 33.5%) or very slow (19.0 vs. 11.1%) acetylator status and less likely to have rapid/intermediate phenotypes (39.2 vs. 54.4%). Breast cancer risk was significantly increased in non-Hispanic white women with a very slow acetylator phenotype who smoked: ever versus never (OR, 2.57; 95% CI, 1.49–4.41), never versus former (OR, 2.69; 95% CI, 1.41–5.17) or current (OR, 2.46; 95% CI, 1.07–5.65), and 16 + pack-years (OR, 2.29; 95% CI, 1.16–4.51). Results for Hispanic women were not statistically significant. These findings support smoking as a risk factor for breast cancer among non-Hispanic white women with very slow NAT2 acetylator phenotype.

Keywords: acetylator, phenotype, arylamine carcinogens, breast cancer, cigarette smoking, Hispanic, N-acetyltransferase 2

The association between cigarette smoking and breast cancer risk in women is controversial. Evidence from animal studies strongly suggests that heterocyclic and aromatic amines in tobacco smoke are genotoxic carcinogens that induce mammary tumors (el-Bayoumy, 1992). Studies of human mammary tissue report evidence for carcinogen-DNA adducts linked to cigarette smoking (Perera et al., 1995). Nonetheless, results from human epidemiological studies are null or inconsistent (Terry and Rohan, 2002).

The N-acetyltransferases are enzymes involved in both the detoxification and the activation of heterocyclic and aromatic amines (Hein, 2002). It has been demonstrated that both heterocyclic and aromatic amines undergo metabolism catalyzed by N-acetyltransferase 2 (NAT2) and that genetic polymorphisms in NAT2 affect the efficiency of the enzyme for the detoxification of carcinogenic amines (Hein, 2002). Ambrosone et al. (1996) first reported that breast cancer risk was specifically increased in postmenopausal women with the slow acetylator NAT2 genotype. Subsequent studies have been inconsistent, but most support the association between slow acetylator status and smoking with breast cancer risk. Ambrosone et al. (2008) conducted a meta-analysis and pooled subset analysis of 13 studies and reported a significant interaction between cigarette smoking and NAT2 genotype on breast cancer risk (p = 0.03). This interaction was consistent across multiple measures of smoking exposure. In particular, duration and intensity of smoking had a significant association with breast cancer risk among women with slow acetylator status, with the highest risk in those with 20 or more pack-years (meta-analysis odds ratio [OR], 1.44; 95% confidence interval [CI], 1.23–1.68 and pooled analysis OR, 1.49; 95% CI, 1.08–2.04).Further research on the interaction of NAT2 genotypes with smoking on breast cancer risk is important because breast cancer is the most common cancer diagnosed among women, accounting for an estimated 27% of all cancers among women in the United States (Jemal et al., 2009), and the prevalence of slow acetylator status is high in some populations (up to 50–60%) (Wacholder et al., 2000). Moreover, there are racial/ethnic differences in the frequencies of NAT2 genotypes (Garcia-Martin, 2008) that may explain differences in tobacco smoke susceptibility across populations (Hein, 2009). The 4-Corners Breast Cancer Study (4-CBCS) is a population-based case-control study of breast cancer among women in the Southwest 4-Corners region (New Mexico, Utah, Colorado, and Arizona) that was designed to explore the contradiction between breast cancer incidence rates and prevalence of exposures among Southwestern Hispanic/American Indian women and non-Hispanic white women. In this analysis, we tested the hypothesis that a slow or very slow NAT2 acetylator phenotype is associated with an increased breast cancer risk among women smokers and that risk may be modified by ethnicity and menopausal status.

MATERIALS AND METHODS

Study population.

Detailed descriptions of study methods, including subject selection, eligibility, recruitment, participation, and data collection, have been previously published (Slattery et al., 2006, 2007, 2008; Wang et al., 2009) and are summarized below. This analysis is restricted to data for the New Mexico site because NAT2 genotyping was not performed for the other 4-CBCS sites. Cases were ascertained through the New Mexico Tumor Registry, a member of the Surveillance, Epidemiology and End Results Program. Eligible cases included women diagnosed with a first primary breast cancer, either in situ or invasive disease (ICDO sites C50.0–C50.6, C50.8–C50.9) with a histological confirmation occurring between October 1999 and September 2002, age 25–79 years, and state residency at time of diagnosis. Only Hispanic, American Indian, and non-Hispanic white women were included as they account for 85% of the state population. The computer program, GUESS (Generally Useful Ethnic Search System) (Buechley, 1976), in conjunction with the Census Spanish Surname List (Word and Perkins, 1996) was used to identify women who were Hispanic when ethnicity was unknown. In New Mexico, all Hispanic, nonreservation American Indian, and non-Hispanic white cases under age 50 years were included with a 1:1 ratio for women over 50 years. Controls were frequency matched to breast cancer cases for ethnicity and 5-year age group. Controls under 65 years of age were randomly selected from the New Mexico driver’s license list and those 65 years and older were randomly selected from Center for Medicare Services lists. Eligibility and ethnicity were confirmed at the time of the screening telephone contact. The Institutional Review Board approved the study for human subjects, and all subjects provided written consent prior to participation.

Data collection.

A total of 2043 cases and 3689 controls were eligible for the study in New Mexico. Of this total, 1954 subjects participated (51.8% cases and 48.2% controls), accounting for 40% of all subjects in the four-state multicenter study. All participants were asked to complete an in-person interview, blood draw, and anthropometric measurements (weight, height, and waist/hip circumference). Data were collected from the participants by trained interviewers who used an interviewer-administered computerized questionnaire. The questionnaire collected information on demographics, breast cancer risk factors, including reproductive and menstrual history, menopausal status, medical and medication history, height, weight history, diet, physical activity, cigarette smoking, alcohol consumption, and education. The year prior to diagnosis of cases or selection of controls was used as the referent period. Ethnicity was confirmed by self-report at the time of interview. Respondents were interviewed in either English or Spanish based on the participant’s preference. Approximately 32% of interviews of Hispanic women were conducted completely or partially in Spanish. Participants were called to clarify missing or ambiguous responses when necessary. Quality control was based on a random review of audio taped interviews.

Genotyping.

Of the 1954 participants (1012 cases and 942 controls), 75% agreed to provide a blood sample for DNA extraction. Genomic DNA for genotype analyses was extracted from peripheral blood leukocytes. NAT2 genotypes were obtained for 1452 (74.3%) subjects, 717 cases (Hispanic, 251 and non-Hispanic white, 466), and 735 controls (Hispanic, 245 and non-Hispanic white, 490), respectively. NAT2 haplotypes, genotypes, and deduced phenotypes were determined as previously described (Doll and Hein, 2001; Hein, 2009). Briefly, SNP-specific PCR primers and fluorogenic probes were designed using Primer Express (Applied Biosystems, Foster City, CA). The fluorogenic probes are labeled with a reporter dye (either FAM or VIC) and are specific for one of the two possible bases identified at the seven SNPs in the NAT2 coding region. Controls (no DNA template) were run to ensure that there was no amplification of contaminating DNA, and each plate was run in duplicate. Subjects were classified as rapid, intermediate, slow, and very slow acetylator phenotypes. Individuals possessing two of the NAT2 alleles associated with rapid acetylation activity (NAT2*4, NAT2*12, and NAT2*13) were classified as rapid acetylators, individuals possessing one of these alleles and one allele associated with slow acetylation (NAT2*5, NAT2*6, NAT2*7, and NAT2*14) were classified as intermediate acetylators, and those individuals that possessed two slow acetylation alleles were classified as slow acetylators. Homozygous NAT2*5 acetylators were subclassified as very slow acetylators (Hein, 2009).

Statistical methods.

A few subjects reported American Indian ethnicity (N = 34, 2.34%) and 29% of these also reported Hispanic ethnicity, so their data were combined with those for Hispanic women. Previous 4-CBCS analyses on genetic admixture supports this combined grouping (Sweeney et al., 2007). Cigarette smoking status was defined as both never versus ever, based on smoking 100 or more cigarettes in the past, and as status at time of interview (never, former, and current). Data were collected on duration of smoking (years started and stopped) and dose (cigarettes smoked per day). Calculation of pack-years was based on the number of cigarettes smoked per day/20 times the number of years smoked and categorized as never, <1, <1–15, and >15 years. A total of 56 (3.86%) subjects smoked for less than one pack-year; these subjects were included with the never-smoked category for analyses. Long-term passive smoke exposure was collected on the number of hours per week that women reported for the referent year and at ages 15, 30, and 50 years. A categorical variable coded as none, low (<10 h/week), and high (≥10 h/week) was constructed based on average hours of passive smoke exposure at ages 15, 30, and referent year for premenopausal women and on average number of hours at ages 15, 30, 50, and referent year for postmenopausal women. Menopausal status was determined using an algorithm, based on age (<57 years) at referent date and responses to eight questions regarding menstrual status, hormone replacement use, and surgical or medical menopause. Women identified as perimenopausal (n = 186, 12.8%) were combined with the premenopausal group for analysis. Postmenopausal women at the time of referent date were also categorized by recent hormone exposure through use of hormone replacement therapy (HRT) or from recently going through menopause. Women were classified as exposed if they had used HRT within 2 years or were premenopausal or perimenopausal during the 2 years prior to the referent date. Parity, defined as the number of live births, was categorized as: nulliparous, one to two live births, three to four live births, and five or more live births. Age at first full-term birth was categorized as nulliparous, <20, 20–24, 25–29, and 30 years or older and age at menarche as <12, 13, 14, and 15 years or older. Family history of breast cancer was based on report for first-degree relatives (mother, sister, and daughter). A total of 25 (1.7%) women with missing data for family history were coded with the referent group and a sensitivity analysis conducted to determine if there were any differences for effect estimates. Alcohol drinking was based on data reported by women who reported having ever drunk an average of one or more alcoholic beverages (beer, wine, and liquor) a month for 1 year or more. A summary variable was constructed to combine long-term intake at ages 15, 30, and 50 years with current alcohol consumption reported for the referent year. Intake was categorized as low (0 to <10 g/day) versus moderate (≥10 g/day) consumption. Body mass index was calculated as weight (kilogram) divided by height (meter) squared and categorized on the basis of international cut-points of <25 (normal weight), 25–29.9 (overweight), and 30+ (obese). Long-term physical activity was based on metabolic equivalent of activity hours per week of moderate and vigorous activity reported at ages 15, 30, 50 years and during the referent year and categorized from lowest to highest activity level. A variable for well-done meat intake was categorized as rare or medium rare, medium well done, and well done. Women who did not report meat intake were categorized with the referent group, rare or medium rare intake. Education was categorized as less than high school, high school graduate, some college, and a bachelor’s degree or higher.

Unconditional logistic regression models were used to estimate ORs and 95% CIs for the association of NAT2 with smoking on breast cancer risk. Effect modification between smoking measures and acetylator phenotype was evaluated by constructing an indicator variable for the combined categories of each smoking measure (smoking history, smoking status, and pack-years) and NAT2 acetylator status in multivariate models. The rapid acetylator phenotype was combined with the intermediate acetylator phenotype to form the referent group for comparison with the slow and very slow acetylator groups. This classification has been previously used in other studies and in the recent meta-analysis and pooled analysis where rapid acetylators were defined as carriers of at least one of the rapid acetylator alleles (Ambrosone et al., 2008).

Test for interaction was performed using the log likelihood ratio test. Stratified analyses between NAT2 phenotype and breast cancer risk were performed by each smoking measure for all women, for Hispanic and non-Hispanic white women, and for premenopausal/perimenopausal and postmenopausal women. Linear trend p values were calculated based on linear trend across categorical variables. Multivariate models were adjusted for age (at diagnosis for cases, age at selection for controls), ethnicity, age at menarche, family history and menopausal status, and recent estrogen exposure for models restricted to postmenopausal women. Variables considered for additional adjustment, but which did not alter the findings, included education, body mass index, parity, age at first full-term birth, long-term moderate and vigorous physical activity, alcohol consumption, passive smoking history, and intake of well-done meat. Associations were stratified by menopausal status and by ethnicity. All statistical analyses were performed using SAS 9.1.3. (SAS Institute, Cary, NC) and STATA Statistical Software 10 (StataCorp, College Station, TX).

RESULTS

Analyses combined in situ (15%) and invasive (85%) cases, as there was no significant difference between stage of disease with either cigarette smoking (p = 0.26) or NAT2 phenotype (p = 0.55) for all women or by ethnicity (data not shown). Overall, cases did not differ significantly from controls within each ethnic group on population characteristics considered important as covariates for evaluation in multivariate analyses, although there were significant differences by ethnicity independent of case-control status for all covariates (Table 1). The prevalence of smoking was significantly lower in Hispanic compared to non-Hispanic white women: 38.5 versus 49.9% (p < 0.001), respectively. There were significant differences between cases and controls for only non-Hispanic white women for ever smokers versus never-smokers and for pack-years (Table 2).

TABLE 1
Characteristics of Study Population, Stratified by Ethnicity and Case-Control Status, 4-CBCS, New Mexico site, 1999–2002 (n = 1452)a
TABLE 2
Cigarette Smoking Measures, Stratified by Ethnicity and Case-Control Status, 4-CBCS, New Mexico site, 1999–2002 (n = 1452)a

NAT2*5B was the most common NAT2 allele in both breast cancer cases (40.9%) and controls (37.8%), followed by NAT2*6A (24.8% vs. 28.0%) and NAT2*4 (24.0% vs. 25.4%), respectively. Less frequent alleles identified in this population included NAT2*13, *12A, 5A, *5C, and *7B. The frequency of NAT2 alleles did not differ significantly (p > 0.05) between breast cancer cases and controls, but there were significant differences between Hispanic and non-Hispanic white women (Table 3). A total of 28 NAT2 genotypes were identified and assigned to rapid, intermediate, slow, and very slow acetylator phenotypes (Table 4). NAT2*4/*5B and NAT2*5B/NAT2*6A were the most common NAT2 genotypes in both breast cancer cases and controls. There were no statistically significant differences between cases and controls for NAT2 phenotypes. NAT2 phenotypes differed significantly by ethnic group (p < 0.001) and were significantly different by case-control status for non-Hispanic white women (Table 4). Non-Hispanic white compared to Hispanic women were more likely to be characterized by the slow (41.7% vs. 33.5%) and very slow (19.0% vs. 11.1%) NAT2 phenotype associated with increased breast cancer risk among smokers and less likely to have a rapid/intermediate (39.2% vs. 54.4%) NAT2 phenotype.

TABLE 3
Distribution of NAT2 Alleles (Haplotype), Stratified by Case-Control Status, 4-CBCS, New Mexico site, 1999–2002 (n = 1452)a
TABLE 4
NAT2 Phenotype/Genotype Frequency, Stratified by Case-Control Status, 4-CBCS, New Mexico site, 1999–2002 (n = 1,452)a

Cigarette smoking was not directly associated with increased risk for breast cancer, regardless of whether the exposure was a generalized measure (ever vs. never: OR, 1.08; 95% CI, 0.88–1.34) or a more specific measure (status history and pack-years) and regardless of whether analyses were stratified by ethnicity (non-Hispanic white: OR, 1.30; 95% CI, 1.00–1.68 vs. Hispanic: OR, 1.08; 95% CI, 0.66–1.77) or menopausal status (postmenopausal: OR, 1.12; 95% CI, 0.86–1.45 vs. premenopausal: OR, 1.02; 95% CI, 0.71–1.47) (data not shown).

The interactions of NAT2 phenotypes with cigarette smoking on breast cancer risk are shown in Table 5. Breast cancer risk due to smoking was increased in women with the very slow acetylator NAT2 phenotype, regardless of whether the exposure was measured as ever versus never (OR, 1.83; 95% CI, 1.17–2.86), as never versus former (OR, 1.88; 95% CI, 1.07–3.28) or current (OR, 1.95; 95% CI, 0.99–3.85), or as the highest level of pack-years (OR, 2.05; 95% CI, 1.11–3.77) (Table 5). When the data were stratified on ethnicity, it was apparent that the interaction of smoking and NAT2 very slow phenotype was restricted to non-Hispanic white women: ever versus never (OR, 2.57; 95% CI, 1.49–4.41), never versus former (OR, 2.69; 95% CI, 1.41–5.17) or current (OR, 2.46; 95% CI, 1.07–5.65), and highest level of pack-years (OR, 2.29; 95% CI, 1.16–6.22) (Table 5). There was no evidence for increased risk associated with a very slow NAT2 phenotype among Hispanic smokers. There was, in fact, a nonsignificant trend that may indicate less susceptibility for Hispanic women with a rapid/intermediate NAT2 phenotype (e.g., ever vs. never rapid/intermediate NAT2 phenotype: OR, 0.63; 95% CI, 0.38–1.06). However, results were generally inconsistent and unstable, possibly due to the smaller number of Hispanic women. Analyses were also stratified on menopausal status. These results are not shown in Table 5 because, although not statistically significant for premenopausal women, the point estimates across strata were similar to those for postmenopausal non-Hispanic white women, which were statistically significant. Stratified analyses of the interaction between smoking and NAT2 phenotype on both ethnicity and menopausal status included sample sizes insufficient to provide adequate statistical power.

TABLE 5
Interaction of Cigarette Smoking and NAT2 Phenotype on Breast Cancer Risk for All Women and Stratified by Menopausal Status and Ethnicity, 4-CBCS, New Mexico site, 1999–2002 (n = 1,452)

DISCUSSION

Several studies over the past decade have suggested increased risk for breast cancer with smoking (Gram et al., 2005; Khuder et al., 2001; Nagata et al., 2006; Reynolds et al., 2004), but results have been inconsistent, and the 2004 report of the Surgeon General on the health effects of smoking concluded that evidence was insufficient to determine the presence of a causal effect between active smoking and breast cancer (USDHHS, 2004).

Some of this inconsistency may be attributed to population differences in NAT2 genotype frequencies that modify susceptibility to heterocyclic and aromatic amine carcinogens in tobacco smoke (Lin et al., 2008). Our study suggests that breast cancer risk is increased for non-Hispanic white smokers with the NAT2 very slow genotypes but not for Hispanic women who smoke. However, Hispanic women in our study were significantly less likely than non-Hispanic white women to have very slow and slow NAT2 phenotypes, which are associated with increased susceptibility for development of breast cancer and more likely to have rapid NAT2 phenotypes that may be associated with less susceptibility for breast cancer. If this finding is replicated in future studies, it might provide a partial explanation for the lower risk of breast cancer in Hispanic women compared with non-Hispanic white women.

The role of cigarette smoking in breast cancer risk is complex, as smoking is associated with several breast cancer risk factors, including body weight, age at menopause, and alterations in estrogen metabolism that could alter risk. We evaluated the adjustment for several factors thought to be associated in some way with estrogen exposure. We adjusted for recent estrogen exposure because smoking can have antiestrogenic effects (Tansavatdi et al., 2004) and because it was shown to be a confounder in an earlier analysis of cigarette smoking among women in the 4-CBCS (Slattery et al., 2008). An increased estrogen exposure, which may offset these effects can result in the formation of toxic mutagenic estrogen metabolites that have been found to be associated with a higher risk of breast cancer (Mueck and Seeger, 2005).

Reynolds et al. (2004) concluded that although their data provided evidence that active smoking may play a role in breast cancer etiology, further research is necessary, especially with respect to genetic susceptibilities. If 4-aminobiphenyl or other aromatic amines from cigarette smoke contribute to the etiology of human breast cancer, then it may be hypothesized that analogous to the role of NAT2 on bladder cancer (Hein, 2006), individual risk would be higher in NAT2 slow acetylators. It has been demonstrated that smoking-related DNA adducts are higher in breast tissues of individuals of the slow acetylator NAT2 genotype (Firozi et al., 2002). Additionally, it has been shown that smoking status correlates with aromatic amine DNA adduct levels in tumor tissue adjacent to normal tissue with a significant linear trend for current, former, and never-smokers (Faraglia et al., 2003).

Since the first study on NAT2, smoking and breast cancer risk (Ambrosone et al., 1996), subsequent studies (Delfino et al., 2000; Egan et al., 2003; Hunter et al., 1997; Krajinovic et al., 2001; Lash et al., 2005; Lissowska et al., 2006; Ochs-Balcom et al., 2007) have reported no appreciable difference between rapid and slow NAT2 acetylator smokers for breast cancer risk, while three suggested that rapid acetylator NAT2 smokers were possibly at increased risk (Chang-Claude et al., 2002; Millikan et al., 1998; Morabia et al., 2000). Studies in China (Huang et al., 1999), Sweden (Sillanpaa et al., 2005), and the United States (Alberg et al., 2004) found an increased risk for postmenopausal women who were slow NAT2 acetylator genotypes. The association between smoking and breast cancer in NAT2 slow acetylators recently was supported by a comprehensive meta-analysis (Ambrosone et al., 2008). However, studies focused on smoking may produce conflicting results for a number of reasons related to study design, statistical power, measurement related to intensity or duration of exposure, and differential effects related to genetic susceptibility (Phillips and Garte, 2008).

As previously reviewed (Hein, 2006, 2009; Walraven et al., 2008), slow acetylator NAT2 phenotypes result from different mechanisms depending upon genotype, suggesting that slow acetylator phenotype is not homogenous. The 341T>C (I114T) SNP associated with NAT2*5 alleles or haplotypes yields very large reductions in NAT2 protein and activity (Fretland et al., 2001; Hein et al., 1994, 1995; Zang et al., 2007) resulting from protein degradation (Zang et al., 2004). These findings suggest that very slow NAT2 acetylators (i.e., those possessing NAT2*5 alleles) may be at highest risk for breast cancer when exposed to aromatic amine carcinogens. One other epidemiological study also detected a significant association between breast cancer and very slow acetylator NAT2 alleles (NAT2*5) in women smokers with 20 or more years of exposure (OR, 2.29; 95% CI, 1.06–4.95) (van der Hel et al., 2003). The results of the present investigation extend this finding to include women from New Mexico.

There are a number of limitations common to case-control studies, including selection bias, recall bias, and misclassification. Previous studies have indicated that Hispanics tend to have lower participation in epidemiological studies (Baumgartner et al., 2002; Howard et al., 1983; Rowland and Forthofer, 1993). In a previous analysis, we evaluated potential factors that may have impacted the differential participation of Hispanic women compared to non-Hispanic white women in the 4-CBCS (Sweeney et al., 2007). Our results indicated that, based on age and community characteristics from the 2000 Census (income, education, urban/rural residency by ethnicity and age, and language acculturation for Hispanics), Hispanic nonparticipants (no contact made or refusals) did not differ significantly from non-Hispanic white nonparticipants, suggesting that differential selection bias was unlikely. Community characteristics also were not found to differ by case-control status.

Factors that contribute to subjects’ beliefs and that may influence potential recall bias are difficult to untangle. It has been reported that women living in the United States, regardless of age (<50 vs. 50+ years), associate smoking with breast cancer risk (87% vs. 80%) (Wold et al., 2005). However, this report also showed that current smokers more frequently reported that smoking was a risk factor for individuals other than themselves. Added to this complex mix of personal and cultural beliefs is the potential for misclassification when subjects attempt to recall cigarette smoking history for past time periods. It is difficult to determine how these beliefs and perceptions and potential for misclassification influence effect estimates. The strengths of the current study include a large number of Hispanic women, the ability to evaluate a number of potential confounders, and a sufficient sample size to detect ethnic differences across the different phenotypes.

Our findings suggest that breast cancer risk is increased for non-Hispanic white women who possess a slow to very slow NAT2 acetylator phenotype and smoke. The inconsistencies observed among studies that investigate associations between NAT2, smoking, and breast cancer incidence may reflect differences in exposure, genotyping misclassification (Deitz et al., 2004), and heterogeneity among the slow NAT2 acetylator phenotypes (Hein, 2009). Recent work (Bendaly et al., 2009) has further strengthened the importance of accounting for multiple slow acetylator phenotypes, noting that this heterogeneity may be responsible for some of the inconsistency across studies that have not further differentiated the slow acetylator status. Further studies are necessary to better define the role of NAT2 polymorphisms in the development of breast cancer following exposure to carcinogens such as those found in cigarette smoke.

FUNDING

United States Public Health Service grants (R01-CA034627, R01-CA78762, and P30-ES014443).

Acknowledgments

Portions of this work were presented in abstract form at the 2008 annual meeting of the Society of Toxicology. This work also was in partial fulfillment for the Master of Science in Pharmacology and Toxicology awarded to T.J.S. at the University of Louisville and he contributed equally with K.B.B (Principal Investigator of the New Mexico 4-Corners Breast Cancer Study) in conducting the study and writing of this manuscript. The authors acknowledge the contributions of the Utah site for data co-ordination and to Leslie Palmer, Roger Edwards, Tara Patton, Jason Witter, and Kelly May to data collection and management.

References

  • Alberg AJ, Daudt A, Huang H-Y, Hoffman SC, Comstock GW, Helzlsouer KJ, Strickland PT, Bell DA. N-acetyltransferase 2 (NAT2) genotypes, cigarette smoking, and the risk of breast cancer. Cancer Detect Prev. 2004;28:187–193. [PubMed]
  • Ambrosone CB, Freudenheim JL, Graham S, Marshall JR, Vena JE, Brasure JR, Michalek AM, Laughlin R, Nemoto T, Gillenwater KA, et al. Cigarette smoking, N-acetyltransferase 2 genetic polymorphisms, and breast cancer risk. JAMA. 1996;276:1494–1501. [PubMed]
  • Ambrosone CB, Kropp S, Yang J, Yao S, Shields PG, Chang-Claude J. Cigarette smoking, N-acetyltransferase 2 genotypes, and breast cancer risk: pooled analysis and meta-analysis. Cancer Epidemiol. Biomarkers Prev. 2008;17:15–26. [PubMed]
  • Baumgartner KB, Annegers JF, McPherson RS, Frankowski RF, Gilliland FD, Samet JM. Is alcohol intake associated with breast cancer in Hispanic women? The New Mexico Women’s Health Study. Ethn. Dis. 2002;12:460–469. [PubMed]
  • Bendaly J, Doll MA, Millner LM, Metry KJ, Smith NB, Pierce WM, Hein DW. Differences between human slow N-acetyltransferase 2 alleles in levels of 4-aminobiphenyl-induced DNA adducts and mutations. Mut. Res. 2009 Online publication August 12, 2009, Doi: 10.1016/j.mrfmmm.2009.08.003. [PMC free article] [PubMed]
  • Buechley RW. Generally Useful Ethnic Search System: GUESS. Albuquerque, NW: Cancer Research and Treatment Center, The University of New Mexico; 1976.
  • Chang-Claude J, Kropp S, Jager B, Bartsch H, Risch A. Differential effect of NAT2 on the association between active and passive smoke exposure and breast cancer risk. Cancer Epidemiol. Biomarkers Prev. 2002;11:698–704. [PubMed]
  • Deitz AC, Rothman N, Rebbeck TR, Hayes RB, Chow WH, Zheng W, Hein DW, Garcia-Closas M. Impact of misclassification in genotype-exposure interaction studies: example of N-acetyltransferase 2 (NAT2), smoking, and bladder cancer. Cancer Epidemiol. Biomarkers Prev. 2004;13:1543–1546. [PubMed]
  • Delfino RJ, Smith C, West JG, Lin HJ, White E, Liao SY, Gim JS, Ma HL, Butler J, Anton-Culver H. Breast cancer, passive and active cigarette smoking and N-acetyltransferase 2 genotype. Pharmacogenetics. 2000;10:461–469. [PubMed]
  • Doll MA, Hein DW. Comprehensive human NAT2 genotype method using single nucleotide polymorphism-specific polymerase chain reaction primers and fluorogenic probes. Anal. Biochem. 2001;288:106–108. [PubMed]
  • Egan KM, Newcomb PA, Titus-Ernstoff L, Trentham-Dietz A, Mignone LI, Farin F, Hunter DJ. Association of NAT2 and smoking in relation to breast cancer incidence in a population-based case-control study (United States) Cancer Causes Control. 2003;14:43–51. [PubMed]
  • el-Bayoumy K. Environmental carcinogens that may be involved in human breast cancer etiology. Chem. Res. Toxicol. 1992;5:585–590. [PubMed]
  • Faraglia B, Chen SY, Gammon MD, Zhang Y, Teitelbaum SL, Neugut AI, Ahsan H, Garbowski GC, Hibshoosh H, Lin D, et al. Evaluation of 4-aminobiphenyl-DNA adducts in human breast cancer: the influence of tobacco smoke. Carcinogenesis. 2003;24:719–725. [PubMed]
  • Firozi PF, Bondy ML, Sahin AA, Chang P, Lukmanji F, Singletary ES, Hassan MM, Li D. Aromatic DNA adducts and polymorphisms of CYP1A1, NAT2, and GSTM1 in breast cancer. Carcinogenesis. 2002;23:301–306. [PubMed]
  • Fretland AJ, Leff MA, Doll MA, Hein DW. Functional characterization of human N-acetyltransferase 2 (NAT2) single nucleotide polymorphisms. Pharmacogenetics. 2001;11:207–215. [PubMed]
  • Garcia-Martin E. Interethnic and intraethnic variability of NAT2 single nucleotide polymorphisms. Curr. Drug Metab. 2008;9:487–497. [PubMed]
  • Gram IT, Braaten T, Terry PD, Sasco AJ, Adami HO, Lund E, Weiderpass E. Breast cancer risk among women who start smoking as teenagers. Cancer Epidemiol. Biomarkers Prev. 2005;14:61–66. [PubMed]
  • Hein DW. Molecular genetics and function of NAT1 and NAT2: Role in aromatic amine metabolism and carcinogenesis. Mutat. Res. 2002;506–507:65–77. [PubMed]
  • Hein DW. N-acetyltransferase 2 genetic polymorphism: effects of carcinogen and haplotype on urinary bladder cancer risk. Oncogene. 2006;25:1649–1658. [PMC free article] [PubMed]
  • Hein DW. N-acetyltransferase SNPs: emerging concepts serve as a paradigm for understanding complexities of personalized medicine. Expert Opin. Drug Metab. Toxicol. 2009;5:353–366. [PMC free article] [PubMed]
  • Hein DW, Doll MA, Rustan TD, Ferguson RJ. Metabolic activation of N-hydroxyarylamines and N-hydroxyarylamides by 16 recombinant human NAT2 allozymes: effects of 7 specific NAT2 nucleic acid substitutions. Cancer Res. 1995;55:3531–3536. [PubMed]
  • Hein DW, Ferguson RJ, Doll MA, Rustan TD, Gray K. Molecular genetics of human polymorphic N-acetyltransferase: enzymatic analysis of 15 recombinant wild-type, mutant, and chimeric NAT2 allozymes. Hum. Mol. Genet. 1994;3:729–734. [PubMed]
  • Howard CA, Samet JM, Buechley RW, Schrag SD, Key CR. Survey research in New Mexico Hispanics: some methodological issues. Am. J. Epidemiol. 1983;117:27–34. [PubMed]
  • Huang CS, Chern HD, Shen CY, Hsu SM, Chang KJ. Association between N-acetyltransferase 2 (NAT2) genetic polymorphism and development of breast cancer in post-menopausal Chinese women in Taiwan, an area of great increase in breast cancer incidence. Int. J. Cancer. 1999;82:175–179. [PubMed]
  • Hunter DJ, Hankinson SE, Hough H, Gertig DM, Garcia-Closas M, Spiegelman D, Manson JE, Colditz GA, Willett WC, Speizer FE, et al. A prospective study of NAT2 acetylation genotype, cigarette smoking, and risk of breast cancer. Carcinogenesis. 1997;18:2127–2132. [PubMed]
  • Jemal A, Center MM, Ward E, Thun MJ. Cancer occurrence. Methods Mol. Biol. 2009;471:3–29. [PubMed]
  • Khuder SA, Mutgi AB, Nugent S. Smoking and breast cancer: a meta-analysis. Rev. Environ. Health. 2001;16:253–261. [PubMed]
  • Krajinovic M, Ghadirian P, Richer C, Sinnett H, Gandini S, Perret C, Lacroix A, Labuda D, Sinnett D. Genetic susceptibility to breast cancer in French-Canadians: role of carcinogen-metabolizing enzymes and gene-environment interactions. Int. J. Cancer. 2001;92:220–225. [PubMed]
  • Lash TL, Bradbury BD, Wilk JB, Aschengrau A. A case-only analysis of the interaction between N-acetyltransferase 2 haplotypes and tobacco smoke in breast cancer etiology. Breast Cancer Res. 2005;7:R385–R93. [PMC free article] [PubMed]
  • Lin Y, Kikuchi S, Tamakoshi K, Wakai K, Kondo T, Niwa Y, Yatsuya H, Nishio K, Suzuki S, Tokudome S, et al. Active smoking, passive smoking, and breast cancer risk: findings from the Japan Collaborative Cohort Study for Evaluation of Cancer Risk. J. Epidemiol. 2008;18:77–83. [PubMed]
  • Lissowska J, Brinton LA, Zatonski W, Blair A, Bardin-Mikolajczak A, Peplonska B, Sherman ME, Szeszenia-Dabrowska N, Chanock S, Garcia-Closas M. Tobacco smoking, NAT2 acetylation genotype and breast cancer risk. Int. J. Cancer. 2006;119:1961–1969. [PubMed]
  • Millikan RC, Pittman GS, Newman B, Tse CK, Selmin O, Rockhill B, Savitz D, Moorman PG, Bell DA. Cigarette smoking, N-acetyltransferases 1 and 2, and breast cancer risk. Cancer Epidemiol. Biomarkers Prev. 1998;7:371–378. [PubMed]
  • Morabia A, Bernstein MS, Bouchardy I, Kurtz J, Morris MA. Breast cancer and active and passive smoking: the role of the N-acetyltransferase 2 genotype. Am. J. Epidemiol. 2000;152:226–232. [PubMed]
  • Mueck AO, Seeger H. Smoking, estradiol metabolism and hormone replacement therapy. Curr. Med. Chem. Cardiovasc Hematol. Agents. 2005;3:45–54. [PubMed]
  • Nagata C, Mizoue T, Tanaka K, Tsuji I, Wakai K, Inoue M, Tsugane S. Tobacco smoking and breast cancer risk: an evaluation based on a systematic review of epidemiological evidence among the Japanese population. Jpn. J. Clin. Oncol. 2006;36:387–394. [PubMed]
  • Ochs-Balcom HM, Wiesner G, Elston RC. A meta-analysis of the association of N-acetyltransferase 2 gene (NAT2) variants with breast cancer. Am. J. Epidemiol. 2007;166:246–254. [PubMed]
  • Perera FP, Estabrook A, Hewer A, Channing K, Rundle A, Mooney LA, Whyatt R, Phillips DH. Carcinogen-DNA adducts in human breast tissue. Cancer Epidemiol. Biomarkers Prev. 1995;4:233–238. [PubMed]
  • Phillips DH, Garte S. Smoking and breast cancer: is there really a link? Cancer Epidemiol. Biomarkers Prev. 2008;17:1–2. [PubMed]
  • Reynolds P, Hurley S, Goldberg DE, Anton-Culver H, Bernstein L, Deapen D, Horn-Ross PL, Peel D, Pinder R, Ross RK, et al. Active smoking, household passive smoking, and breast cancer: evidence from the California Teachers Study. J. Natl. Cancer Inst. 2004;96:29–37. [PubMed]
  • Rowland ML, Forthofer RN. Investigation of nonresponse bias: Hispanic Health and Nutrition Examination Survey. Vital Health Stat. 1993;2:1–75. [PubMed]
  • Sillanpaa P, Hirvonen A, Kataja V, Eskelinen M, Kosma V-M, Uusitupa M, Vainio H, Mitrunen K. NAT2 slow acetylator genotype as an important modifier of breast cancer risk. Int. J. Cancer. 2005;114:579–584. [PubMed]
  • Slattery ML, Curtin K, Giuliano AR, Sweeney C, Baumgartner R, Edwards S, Wolff RK, Baumgartner KB, Byers T. Active and passive smoking, IL6, ESR1, and breast cancer risk. Breast Cancer Res. Treat. 2008;109:101–111. [PMC free article] [PubMed]
  • Slattery ML, Curtin K, Sweeney C, Wolff RK, Baumgartner RN, Baumgartner KB, Giuliano AR, Byers T, Slattery ML. Body size, weight change, fat distribution and breast cancer risk in Hispanic and non-Hispanic white women. Breast Cancer Res. Treat. 2007;102:85–101. [PubMed]
  • Slattery ML, Sweeney C, Edwards S, Herrick J, Murtaugh M, Baumgartner K, Guiliano A, Byers T. Physical activity patterns and obesity in Hispanic and non-Hispanic white women. Med. Sci. Sports Exerc. 2006;38:33–41. [PubMed]
  • Sweeney C, Edwards SL, Baumgartner KB, Herrick JS, Palmer LE, Murtaugh MA, Stroup A, Slattery ML. Recruiting Hispanic women for a population-based study: validity of surname search and characteristics of nonparticipants. Am. J. Epidemiol. 2007;166:1210–1219. [PubMed]
  • Tansavatdi K, McClain B, Herrington DM. The effects of smoking on estradiol metabolism. Minerva Ginecol. 2004;56:105–114. [PubMed]
  • Terry PD, Rohan TE. Cigarette smoking and the risk of breast cancer in women: a review of the literature. Cancer Epidemiol. Biomarkers Prev. 2002;11:953–971. [PubMed]
  • U.S. Department of Health and Human Services. The Health Consequences of Smoking: A Report of the Surgeon General. Atlanta, GA: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health; 2004.
  • van der Hel OL, Peeters PHM, Hein DW, Doll MA, Grobbee DE, Kromhout D, Bueno de Mesquita HB. NAT2 slow acetylation and GSTM1 null genotypes may increase postmenopausal breast cancer risk in long-term smoking women. Pharmacogenetics. 2003;13:399–407. [PubMed]
  • Wacholder S, Rothman N, Caporaso N. Population stratification in epidemiologic studies of common genetic variants and cancer: quantification of bias. J. Natl. Cancer Inst. 2000;92:1151–1158. [PubMed]
  • Walraven JM, Zang Y, Trent JO, Hein DW. Structure/function evaluations of single nucleotide polymorphisms in human N-acetyltransferase 2. Curr. Drug Metab. 2008;9:471–486. [PMC free article] [PubMed]
  • Wang C, Baumgartner RN, Yang D, Slattery ML, Murtaugh MA, Byers T, Hines LM, Giuliano AR, Baumgartner KB. No evidence of association between breast cancer risk and dietary carotenoids, retinols, vitamin C and tocopherols in Southwestern Hispanic and non-Hispanic White women. Breast Cancer Res. Treat. 2009;114:137–145. [PubMed]
  • Wold KS, Byers T, Crane LA, Ahnen D. What do cancer survivors believe causes cancer? (United States) Cancer Causes Control. 2005;16:115–123. [PubMed]
  • Word DL, Perkins RC. Building a Spanish surname list for the 1990’s–A new approach to an old problem. 1996. Technical Working Paper No. 13, pp. 1–25. Population Division, U.S. Bureau of the Census, Washington, DC.
  • Zang Y, Doll MA, Zhao S, States JC, Hein DW. Functional characterization of single-nucleotide polymorphisms and haplotypes of human N-acetyltransferase 2. Carcinogenesis. 2007;28:1665–1671. [PMC free article] [PubMed]
  • Zang Y, Zhao S, Doll MA, States JC, Hein DW. The T341C (Ile114Thr) polymorphism of N-acetyltransferase 2 yields slow acetylator phenotype by enhanced protein degradation. Pharmacogenetics. 2004;14:717–723. [PubMed]

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