N-Acetyltransferase 2 polymorphisms, cigarette smoking and alcohol consumption, and oral squamous cell cancer risk
Chu Chen1,3,4,6,
Sherianne Ricks1,
David R. Doody1,
E.Dawn Fitzgibbons1,
Peggy L. Porter2,5 and
Stephen M. Schwartz1,3
1 Program in Epidemiology and
2 Program in Cancer Biology, Divisions of Public Health Sciences and Human Biology, Fred Hutchinson Cancer Research Center, Seattle, WA 98109-1024,
3 Department of Epidemiology, School of Public Health and Community Medicine,
4 Department of Otolaryngology: Head and Neck Surgery and
5 Department of Pathology, School of Medicine, University of Washington, Seattle, WA 98195, USA
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Abstract
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The risk of squamous cell cancers of the oral cavity (OSCC) is strongly related to the use of tobacco and alcohol. N-Acetyl transferases 1 and 2 (NAT2) metabolize aryl- and heterocyclic amines that are present in tobacco smoke. NAT2 slow acetylator phenotype or genotype is related to reduced ability to detoxify these xenobiotics that are carcinogenic in tissues in which smoking-related cancers develop (e.g. bladder). We studied the association between the deduced NAT2 acetylator phenotypes and OSCC risk in a population-based study of 341 cases and 552 controls. In-person interviews provided information on tobacco use and alcohol consumption. Nucleotide substitutions at position 191, 341, 590, 803 and 857 were determined by a combination of oligonucleotide ligation assays and PCR/RFLP assays. There was no overall association between acetylator status with OSCC risk; the odds ratios for slow and intermediate acetylators, as compared with the rapid acetylators, were 1.2 (95% CI 0.72.2) and 1.1 (95% CI 0.62.0), respectively. The percent increase in risk of OSCC per pack-year cigarette smoking was similar among slow acetylators (3.0%, 95% CI 2.14.0) and the combined intermediate and rapid acetylators (3.5%, 95% CI 2.45.0). In contrast, the risk of OSCC per weekly alcoholic drink was stronger among the combined rapid and intermediate acetylators (3.3%, 95% CI 1.84.9) compared with slow acetylators (1.6%, 95% CI 0.62.7) (interaction P = 0.055). These data raise the possibility that NAT2 may be involved in the activation of one or more pro-carcinogens associated with alcohol consumption.
Abbreviations: NAT, N acetyl transferases; OR, odds ratio; OSCC, squamous cell cancers of the oral cavity; SEER, Surveillance, Epidemiology; End Results
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Introduction
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Based on records of 49 cancer registries in 23 areas on five continents, approximately 211 500 new cases of oral cavity cancers were diagnosed worldwide in 1990 (1). In 1999, an estimated 33 900 new cases of oral and oropharyngeal cancers were diagnosed in the US, with 10 000 deaths (2). Smoking cigarettes, consuming large quantity of alcoholic beverages and/or chewing betal quid are strongly related to the risk of developing squamous cell carcinoma of the oral cavity or oropharynx (35).
Among the major procarcinogens present in tobacco smoke are polycyclic aromatic hydrocarbons, aryl- and heterocyclic amines and nitroso-compounds. N-Acetyl transferases (NAT) 1 and 2 catalyze the N-, O- or N,O-acetylation of the aryl- and heterocyclic amines. The role of N-acetyltransferases in cancer predisposition varies between different organs. A case in point is the comparison between bladder and colorectal cancers or adenoma. A number of studies have observed an association between NAT2 slow acetylator status and an increased risk of bladder cancer, suggesting that N-acetyltransferase 2 may detoxify compounds such as 4-amino biphenyl in the bladder (69) . In contrast, the rapid acetylator status has been found to be associated with colon cancer risk in some, though not all, studies (1019). The apparently different effect of NAT2 acetylator status on the risk of colon cancer might be due to the extensive activation by NAT2 of a number of heterocyclic amines that are present in cooked meats and to some extent in tobacco smoke.
While several studies have examined the etiologic role of NAT2 in head and neck cancer (2024), few have focused on oral cancer specifically (25). These studies had relatively small sample sizes and few examined potential interactions with cigarette smoking and alcohol consumption. We investigated whether individuals having different genotypes for the N-acetyl transferase 2 gene differ in their risk of OSCC. We hypothesized that individuals with genotypes known to be associated with the slow acetylator phenotype would be less able to detoxify tobacco smoke-associated aryl- and heterocyclic amines, and are thus more susceptible to the development of OSCC.
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Materials and methods
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Study population and specimen collection
The data and specimens for this analysis were obtained from two population-based casecontrol studies of OSCC. Cases and controls were residents of King, Pierce or Snohomish counties, Washington State, 1865 years of age, diagnosed with first, incident OSCC between January 1985 and June 1995. Cases were ascertained through the population-based Cancer Surveillance System, a participant in the Surveillance, Epidemiology and End Results (SEER) Program (26). In these two studies, OSCC referred to in situ and invasive tumors of the lips, tongue, gums, floor of the mouth, tonsils, oropharynx and other sites in the oral cavity. For the current investigation, we excluded cases with a cancer of the lip. The level of participation for eligible cases was 54% and 63% in the first and second studies, respectively, yielding 407 interviewed cases. Among the 275 non-participating cases in both studies, 125 had died prior to recruitment. Controls were identified through random digit telephone dialing; 63% and 61% of the controls participated in the first and second studies, respectively. Additional information about the design and conduct of the casecontrol studies can be found elsewhere (27,28).
In-person interviews were conducted in both studies using the same instrument to elicit demographic characteristics, detailed histories of tobacco and alcohol use, as well as other known or potential risk factors for oral cancer. Exfoliated oral cell samples and, in some instances, venous blood specimens were obtained. Across the two studies, one or more of these specimens were available from 89.7% (365 out of 407) of the interviewed cases and 93.7% (576 out of 615) of interviewed controls. NAT2 genotyping results were available for 341 cases and 552 controls who had been interviewed. To assess potential bias due to association between genotype and OSCC disease outcome, archival tumor specimens were obtained from 30 OSCC cases who were eligible for the second study but died prior to recruitment.
Determination of NAT2 genotypes
We extracted DNA from peripheral white blood cells using a salting-out procedure (29) or from exfoliated oral tissue using a phenol:chloroform method. A 846 bp fragment of NAT2 (bases 7681614; GenBank accession no. X14672) containing the polymorphic loci at nucleotides 191, 341, 590, 803 and 857 was amplified using primers NAT2fwd, 5'-GGAACAAATTGGACTTGG-3' and NAT2rev, 5'-GGTTTATTTTGTTCCTTATTC-3' in a 96-well plate thermal cycler (MJ Research, Watertown, MA). A 30 µl reaction contained 100 ng genomic DNA and 1x PCR Master Mix (Qiagen, Valencia, CA; 10 mM TrisHCl, 50 mM KCl, 1.5 mM MgCl2, 200 µM each dNTP and 0.025 U Taq polymerase). Thermal cycling was performed with an initial denaturation at 94°C for 5 min, followed by 40 cycles of 94°C for 1 min, 57°C for 1 min, 72°C for 2 min, and a final extension at 72°C for 5 min.
We identified the nucleotides at 191, 341, 590, 803 and 857 using a combination of single-well oligonucleotide ligation assay (OLA) (30) and PCR/RFLP. To proceed with the OLA, 30 µl PCR products were diluted with 60 µl 0.1% Triton X-100. Diluted product (10 µl) was mixed with 10 µl of a solution containing 2x ligase buffer (Epicentre; 40 mM TrisHCl pH 8.3, 50 mM KCl, 20 mM MgCl2, 1 mM NAD, 0.2% Triton X-100), 0.2 U Ampligase® DNA ligase (Epicentre, Madison, WI) and 200 fmol of each of the ligation primers (the two specific primers and the joining primer for the locus being tested). Sets of ligation primers were synthesized with a biotin molecule on the 5'-end of the common primer and the allele specific primers were phosphorylated on their 5'-end. The allele specific primers for each locus were labeled with either digoxigenin (WT) or fluorescein (MT) in a 3' tailing reaction using terminal deoxynucleotidyl transferase (Roche, Indianapolis, IN) and digoxigenin-11-dUTP or fluorescein-12-dUTP (Roche). The primer sequences are shown in Table I
.
The 96-well ligation plates were sealed with film and placed in a thermal cycler for 15 cycles at 93°C for 30 s, 58°C for 4 min. After amplification, the reactions were stopped by the addition of 10 µl 0.1 M EDTA in 0.1% Triton X-100. The entire reaction volume was transferred to a 96-well flat bottom microtiter plate (Falcon) that had been coated with 50 µl of a 25 µg/ml streptavidin (Sigma, St Louis, MO) solution. Streptavidin plates were blocked with 200 µl/well of a 0.5% BSA (Sigma) solution in 1x PBS for 30 min prior to use. Ligation products were allowed to bind to the streptavidin plate at room temperature for 1 h and the plate was washed twice with a 0.01 M NaOH/ 0.05% Tween-20 solution, followed by two washes with Tris buffer (100 mM TrisHCl pH 7.5, 150 mM NaCl/0.05% Tween-20). Forty µl of a 1:1500 dilution of horse radish peroxidase labeled anti-fluorescein antibodies and a 1:4000 dilution of alkaline phosphatase labeled anti-digoxigenin antibodies in 1x PBS/0.5% BSA was added to the streptavidin bound products in the microtiter plate. After incubation for 30 min at room temperature, plates were washed six times with Tris buffer. After washing, 50 µl TMB reagent (Sigma) was added to the wells and incubated at room temperature for 20 min. The plates were read at OD655 using a microplate reader (Spectramax, molecular Devices Corp., Sunnyvale, CA) and the OD readings recorded. After reading, the plate was washed six times with Tris buffer to remove the color product and to neutralize the pH. An ELISA Substrate reagent (25.0 µl; Gibco-BRL, Bethesda, MA) was added to each well and allowed to incubate at room temperature for 15 min. Subsequently, 25.0 µl ELISA Amplifier reagent (Gibco-BRL) was added to each well and allowed to incubate at room temperature for 15 min. The reaction was stopped with 25.0 µl 0.3 M sulfuric acid. The OD490 was read on the microplate reader (Spectramax).
In order to validate the OLA results, genomic DNA from 40 individuals were genotyped at each of the loci using PCR/RFLP methods of Leff et al. (31). These 40 samples of known genotype were then subjected to the OLA procedure in at least eight different runs. The OD readings generated from each run were averaged and compared with the RFLP data to confirm the OLA results and to determine cut-off OD readings. Based on these comparison results, reactions with an OD < 0.3 were considered negative; reactions with an OD > 0.5 were considered positive. Any sample with an OD between 0.3 and 0.5 was considered indeterminate and the OLA was repeated.
Although the OLA is, in general, robust some samples did not yield satisfactory results after three passes with the OLA method. These samples (n = 88) contained either DNA isolated from the paraffin-embedded tissue or archival DNA extracted from exfoliated oral tissue, for which we were unable to amplify the entire coding region of NAT2 in one piece. We genotyped these samples using a modified version of the PCR/RFLP method of Leff et al. (31) and designed primers that would amplify the region around each of the loci of interest. For nucleotide 191, we used primers 5'-CTCTAGGAACAAATTGGACTT-3' and 5'-CATCTGGGAGGAGCTTCCA-3'. For nucleotide 341, we used the modified primers described by Leff et al. (31) to create an AciI site in the mutant sequence. For nucleotide 590, we used primers 5'-TGGACCAAATCAGGAGAGAG-3' and 5'-GATGTGGTTATAAATGAAGATGT-3'. For nucleotides 803 and 857, we used primers 5'-GGTCGAGTTTAAAACTCTCAC-3' and 5'-GGGTTTATTTTGTTCCTTATTCT-3'. Thermal cycling parameters were as follows: initial denaturation at 94°C for 5 min, followed by 40 cycles of 94°C for 1 min, 55°C (58°C for nucleotide 341) for 1 min, 72°C for 2 min, and a final extension at 72°C for 5 min. Each resulting fragment was digested with the appropriate restriction endonucleases followed by agarose gel electrophoresis (31). In addition, the OLA reactions for the 341 locus gave high background readings when the OLA assay for this locus was originally optimized based on TspRI/RFLP results. We later adopted the AciI/RFLP method (31) that consistently gave clearer gel patterns of the restriction fragments to verify all the nucleotide 341 heterozygotes.
Data analysis
For each of the five polymorphic NAT2 sites, we determined the distribution of genotypes (homozygous wild-type, homozygous mutant or heterozygous) and assessed whether the distributions were consistent with the HardyWeinberg equilibrium. We translated the nucleotide changes into functional NAT2 alleles, genotypes and inferred acetylation phenotypes (rapid, intermediate and slow) based on the nomenclature in Vatsis et al. (32). Throughout the remainder of this report we refer to our NAT2 results in terms of acetylator status (rapid acetylators, intermediate acetylators and slow acetylators) for simplicity. We used unconditional logistic regression to calculate odds ratio (OR) estimates for acetylator status and other characteristics under study. We computed 95% confidence intervals on the ORs using the standard error of the model coefficients and the normal approximation. We examined the modifying effect of NAT2 genotypes on cigarette smoking and alcohol consumption using both categorized data and continuous terms for these lifestyle characteristics. Statistical tests of heterogeneity of ORs for smoking and alcohol use across strata of NAT2 genotypes were performed using hierarchical logistic regression models and likelihood ratio tests.
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Results
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The characteristics of the study participants are shown in Table II
. The great majority of the cases and controls were white (93.8% of cases and 94.2% of controls). Both heavy smoking of cigarettes and alcohol consumption were strongly related to OSCC risk. Approximately 62% of the cases were current smokers at the time of diagnosis, with an associated OR of 4.5 (95% CI 3.06.8). The OR increased with increasing number of pack years smoked. Though there was no difference in risk between non-drinkers and persons who consumed one to seven alcoholic beverages per week, the incidence of OSCC rose steadily with increasing alcohol consumption above this level. The relative risk of OSCC in the presence of both smoking and heavy alcohol consumption exceeded that predicted based on the product of the relative risks associated with each exposure alone. Smokeless tobacco was used infrequently in our study population and only slightly more often by cases than controls. The distribution of characteristics in Table II
did not differ noticeably from the corresponding distributions among cases and controls who were interviewed but for whom no genotyping results were available (data not shown).
Of the 341 OSCC cases with genotyping results, 142 (41.6%) had cancers of the tongue, 78 (22.9%) had cancers of the tonsils/oropharynx, 51 (15%) had cancers of the floor of mouth, 16 (4.7%) had cancers of the gum and 54 (15.8%) had cancers at miscellaneous sites within the oral cavity.
The distribution of the genotypes among white controls at each of four of the five polymorphic NAT2 sites showed no evidence of departure from that expected under the HardyWeinberg equilibrium. For the fifth locus (nucleotide 191) we observed two persons who were homozygous mutant (versus 0 expected) and one person who was heterozygous mutant (versus five expected) (P < 0.0001). Table III
shows the distribution of NAT2 genotypes among the interviewed Caucasian cases and controls. There was no overall association between NAT2 acetylator status and OSCC risk (Table IV
). Compared with rapid acetylators, the age- and race-adjusted OR was 1.2 (95% CI 0.72.2) for slow acetylators and 1.1 (95% CI 0.62.0) for intermediate acetylators. Among the 30 eligible OSCC patients who had died prior to recruitment and for whom tissue samples were genotyped, 36.7% were slow acetylators, 50.0% were intermediate acetylators and 13.3% were rapid acetylators (P = 0.048 for comparison to distribution of acetylator status among interviewed cases).
The risk of oral cancer associated with cigarette smoking did not differ by NAT2 acetylator status (Table V
). Among the combined rapid and intermediate acetylators, the age, race, sex and alcohol consumption-adjusted ORs associated with 119, 2039 and 40+ pack-years smoking were 1.0 (95% CI 0.51.9), 2.8 (95% CI 1.55.2) and 7.4 (95% CI 3.714.6), when compared to never smokers. Among the subgroup of slow acetylators, the adjusted ORs associated with 119, 2039 and 40+ pack-years were 1.2 (95% CI 0.62.1), 3.0 (95% CI 1.65.3) and 6.2 (95% CI 3.411.6), when compared to never smokers. Relative to the baseline of persons who were never smokers and not slow acetylators, the ORs for pack-year cigarette smoking did not differ by acetylator status. When modeled as a continuous term and adjusted for age, sex, race and number of alcoholic drinks per week, each additional pack-year of cigarette-smoking was associated with a similar increase in OSCC risk regardless of NAT2 acetylator status. The percent increase in risk per pack-year was 3.5 (95% CI 2.45.0) and 3.0% (95% CI 2.14.0) for rapid and intermediate acetylators combined, and slow acetylators, respectively.
The age-, race-, sex- and pack-years cigarette smoking-adjusted risk of OSCC increased with increasing alcohol consumption among both slow and not slow acetylators (Table VI
). At the highest level of consumption (
43+ drinks per week) the association appeared to be less pronounced among slow acetylators (OR = 3.7, 95% CI 1.68.7) than among the combined group of rapid and intermediate acetylators (OR = 6.6, 95% CI 2.418.7). The differences in the pattern of ORs within strata of acetylator status were consistent with random variation (P = 0.385 for the likelihood ratio test for interaction). The percent increase in risk associated with each additional alcoholic drink per week, adjusted for age, sex, race, and number of pack-years of cigarette smoking, was lowest for the slow acetylators (1.6%, 95% CI 0.62.7) and progressively higher for intermediate acetylators (3.1%, 95% CI 1.44.8) and rapid acetylators (4.7%, 95% CI 0.59.0) (likelihood ratio test for interaction based on continuous alcohol consumption data, P = 0.055); for intermediate and rapid acetylators combined, the percent increase in risk (3.3%, 95% CI 1.84.9) was also higher than that for slow acetylators (likelihood ratio test for interaction based on categorized alcohol consumption data, P = 0.385) (Table VI
). There was no evidence that the stronger percent increase in risk associated with increasing alcohol consumption among rapid and intermediate acetylators was particularly pronounced among heavy smokers (
20 pack-years) than persons who smoked less (data not shown). The risk of OSCC associated with slow acetylator status did not vary across strata of pack-years cigarette smoking and variation in ORs across categories of alcohol consumption did not show a clear pattern (Table VII
).
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Table VII. Risk of oral cancer associated with cigarette smoking and alcohol consumption, by NAT2 acetylator status
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Discussion
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Contrary to our hypothesis, slow acetylators were not at increased risk of OSCC in this study. Further, although cigarette smoking was strongly related to OSCC risk in our population, we did not find evidence that this risk differed by NAT2 acetylator status, suggesting that tobacco associated aryl- and heterocyclic amines that are potential substrates for NAT2 may not play an etiologic role in OSCC development. In contrast, we found suggestive evidence that the risk of OSCC associated with alcohol consumption depended on NAT2 acetylator status, with the risk being strongest among NAT2 rapid or intermediate acetylators and weaker slow acetylators.
Previous studies of OSCC in relation to NAT2 genotype or phenotype have not produced consistent results. Two hospital-based studies, one in France (121 oral/pharyngeal cancers, 164 controls) and one in Japan (62 OSCC cases and 122 controls) observed moderate increases in risk (ORs 1.72-fold) associated with the slow acetylator genotypes (22,25). However, a second hospital-based Japanese study (23) of 45 hypo- or oropharynx cancer cases and 164 controls did not find an association between NAT2 slow acetylator genotype. [Studies of head and neck cancer other than OSCC, or in which OSCC was not distinguished analytically from other HNSCC, have also produced conflicting results (20,21,24)]. The prior OSCC studies differ substantially from ours in sample size, study design and the specific NAT2 alleles tested. Further, only the French study examined the joint effects of cigarette smoking and NAT acetylator status, observing that the increased risk was only present (OR = 3.1, 95% CI 1.37.2) among those individuals with the least extensive smoking history (
30 years duration) as compared with individuals with a more extensive smoking history (OR = 1.2, 95% CI 0.62.4). Differences in the types of cigarettes smoked and dietary intake of compounds that modify the activity of biotransformation enzymes may also have contributed to variation across these studies.
Prior studies of NAT2 and OSCC have not examined the possible combined associations of NAT2 acetylator status and alcohol consumption. While our findings raise the possibility that NAT2 acetylation capability and alcohol consumption, or correlates of these characteristics, may jointly influence OSCC risk, mechanistic evidence supporting such a relationship is lacking. To our knowledge, research has not been conducted to determine whether NAT2 is involved in the metabolic activation of acetaldehyde, a carcinogen produced from ethanol by alcohol and aldehyde dehydrogenases. Conceivably, the patterns we observed could also arise to the extent that alcohol consumption induces the activity of enzymes involved in activationdetoxification pathways in which NAT2 is involved. CYP1A2 can activate heterocyclic and aromatic amines (33,34) that are present in mainstream cigarette smoke and highly cooked meat to reactive intermediates, some of which are NAT2 substrates. CYP1A2 activity, in turn, can be affected by cigarette smoking, dietary factors, several drugs and exposure to polybrominated biphenyls and dioxin (35,36). There is conflicting evidence, however, as to whether cytochrome P450 1A2 expression is affected by alcohol consumption (3740). Since CYP1A2 contributes to the oxidative metabolism of ethanol (41), as well as pathways through which NAT2 affects carcinogen disposition, the absence of information on CYP1A2 activity or genotype in our population limits our ability to explore the possible basis for our results involving NAT2, alcohol use and oral cancer risk. Clarification of our results potentially could come from more precise consideration of specific types of alcoholic beverages consumed. The vast majority of alcohol consumed by our study subjects was in the form of beer or hard liquor; <3% of the cases and <2% of the controls reported at least daily consumption of wine. The imbalance in the types of alcohol consumed in our study, in conjunction with the limited sample size, prevented us from exploring this issue directly.
Although the present study is population-based and considerably larger than previous studies, there are several limitations that necessitate cautious interpretation of the results. First, the response rate is low for both cases and controls. Second, the study population is predominantly Caucasian; hence, the results may not be applicable to non-Caucasians. Third, although this study included cases with OSCC at various oral sites, and smoking and drinking are related to the occurrence of all of them, the number of cases by site is too small to permit us to assess whether NAT2 genotypes are differentially associated with risk of OSCC at different sites. Fourth, in our analyses of the combined association of NAT2 acetylator status and alcohol consumption on OSCC risk, we could not take into account the potential effect of oral microflora. A recent study (42) suggests that both cigarette smoking and alcohol consumption alter the composition of the oral microflora, such as Neisseria, a bacterium that metabolizes ethanol to acetylaldehyde with high efficiency. If NAT2 is involved in the activation or detoxification of acetaldehyde, its metabolites or compounds for which the metabolism is affected by acetaldehyde, and if the production of acetaldehyde among heavy alcohol consumers varies according to oral microflora status, we might have been able to identify stronger differences in OSCC risk associated with alcohol use according to NAT2 status had data on oral microflora status been available.
Among our study participants, the frequencies of rapid acetylators, intermediate acetylators and slow acetylators among controls were 6, 37 and 57%, respectively. These distributions are similar to those reported for Caucasians (43). Although the frequency of the mutated nucleotide 191 allele was not in HardyWeinberg equilibrium, it is unlikely that our results would have been affected to any measurable degree; at most, there would have been an excess of two slow acetylators among over 300 slow acetylators among controls. We evaluated the possibility that deceased OSCC cases might have a different distribution of acetylator status than those we were able to recruit. Although this evaluation was based on only 30 patients, the results suggest that slow acetylators may have been over-represented (and intermediate and rapid acetylators under-represented) among our interviewed cases. Under the assumption that OSCC participants who we did not interview due to patient or physician refusal, as well as OSCC patients we interviewed but for whom we did not have genotyping results, have an acetylator status distribution similar to interviewed OSCC patients included in this analysis, the `true' prevalence of rapid, intermediate and slow acetylators among eligible cases would be approximately 7.9, 37.9 and 54.2%. These figures are only slightly different from those observed among the OSCC cases in our analysis, suggesting little bias in our study due to the apparent differences in acetylator status distribution between deceased and non-deceased patients.
For the future, joint analysis of data (and possibly specimens as well) from existing studies of OSCC could be conducted to begin to address, with larger sample sizes, basic questions of geneenvironment interaction involving NAT2, cigarette smoking and alcohol consumption. Ultimately, however, new studies with very large sample sizes, greater detail on lifestyle characteristics and comprehensive assessment of NAT2 alleles will be needed to provide more definitive evidence for or against the contribution of NAT2 (and thus by inference, aryl- and heterocyclic amines) in OSCC etiology. Such studies will also need to consider variation in other genes known to contribute to the metabolism of aryl- and heterocyclic amines, such as NAT1 and CYP1A2.
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Notes
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6 To whom correspondence should be addressed at: Program in Epidemiology, Fred Hutchinson Cancer Research Center, DE-320, 1100 Fairview Avenue N., Seattle, WA 98109-1024, USA Email: cchen{at}fhcrc.org 
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Acknowledgments
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This work was supported by grants and contracts from the National Institute of Dental and Craniofacial Research (DE12609) and National Cancer Institute (CA 48896, CN 05230), with additional support from the Fred Hutchinson Cancer Research Center. We thank Dr. David W.Hein for providing NAT2*14B plasmid to use as a standard and Dr. Ellen Kampman for assistance with the computer algorithm for deriving NAT2 alleles and inferred acetylator phenotypes from genotyping results.
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Received May 29, 2001;
revised August 29, 2001;
accepted September 14, 2001.