glutathione s-transferase pa and n-acetyltransferase 2 ...we conducted a case-control study to...

Vol. 7, 875-883, October 1998 Cancer Epidemiology, Biomarkers & Prevention 875

Glutathione S-Transferase pA and N-Acetyltransferase 2 GeneticPolymorphisms and Exposure to Tobacco Smoke in Nonsmoking and

Smoking Lung Cancer Patients and Population Controls’

Fredrik Nyberg,2 Sai-Mei Hou, Kari Hemminki,

Bo Lambert, and G#{246}ranPershagen

Division of Environmental Epidemiology, Institute of Environmental Medicine,

Karolinska Institute, SE-17l 77 Stockholm [F. N., G. P.]; and Center for

Nutrition and Toxicology, Department for Biosciences. Novum, Karolinska

Institute, SE-14l 57 Huddinge [S-M.H., K.H., B.L.], Sweden

Abstract

We conducted a case-control study to assess the risk oflung cancer in relation to genetic polymorphisms of thedetoxifying enzymes glutathione-S-transferase il(GSTM1) and N-acetyl transferase 2 (NAT2), focusing onnever-smokers, women, and older people. The study baseconsisted of persons �30 years of age in StockholmCounty from 1992 to 1995. We recruited never-smokinglung cancer cases and a sex- and age-matched sample ofever-smoking cases at the three county hospitals mainlyresponsible for diagnosing and treating lung cancer. A

total of 185 cases (25.4% men; 47.6% never-smokers) and164 frequency-matched population controls (28.7% men;48.2% never-smokers) supplied blood for genotyping.Detailed information was collected by interview on activeand passive smoking, occupations, residences, and diet.

The overall odds ratio (OR) for lung cancerassociated with the GSTMJ null (GSTMJ-) versusGSTMJ+ genotype was 0.8 [95% confidence interval

(CI), 0.5-1.2], with an OR close to unity among smokers,and lower ORs suggested among never-smokers. ForNAT2 slow versus rapid acetylator genotypes, the OR was1.0 (95% CI, 0.6-1.5) overall, which broke down into anincreased risk for slow acetylators among never-smokersbut an increased risk for rapid acetylators amongsmokers. Among never-smokers, a gene interaction wassuggested, with combined slow acetylator and GSTMJ +genotype conferring particularly high risk (OR = 3.1;95% CI, 1.1-8.6), but no clear pattern emerged amongsmokers. A detailed analysis among smokers showed nointeraction between pack-years of smoking and the

GSTMJ genotype but suggested a steeper increase in risk

Received 1/30/98; revised 6/15/98; accepted 7/9/98.

The costs of publication of this article were defrayed in part by the payment of

page charges. This article must therefore be hereby marked advertisement in

accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

I This study received financing from the Swedish Environmental Protection

Agency, the Swedish Cancer Society, and Swedish Match.

2 To whom requests for reprints should be addressed, at the Division of Envi-

ronmental Epidemiology. Institute of Environmental Medicine, Karolinska Insti-

tute, Box 210, SE-17l 77 Stockholm, Sweden. Phone: 46-8-7287457; Fax:

46-8-30457 1 ; E-mail: [email protected].

with increasing pack-years of smoking exposure for rapidthan for slow acetylators.

Our results do not support a major role for theGSTMJ genetic polymorphism as a risk factor for lungcancer among smokers or nonsmokers. There was,however, some suggestion that the slow acetylatorgenotype may confer an increased risk among never-smokers and that the rapid acetylator genotype interactswith pack-year dose to produce a steeper risk gradientamong smokers.

Introduction

Lung cancer has well known environmental causes, of which

smoking is the most important both by virtue of the strength ofthe association and the prevalence of the risk factor. In recent

years, altered function of phase I and phase II detoxifyingenzymes have been suggested to affect the susceptibility toenvironmental carcinogens. The basic hypothesis is that in-creased activity of phase I enzymes that produce activatedmetabolites from environmental procarcinogens and decreasedactivity of phase II enzymes that conjugate and detoxify these

activated metabolites may lead to an accumulation of activatedgenotoxic metabolites, causing increased risk of lung cancer(1).

GSTM13 and NAT2 are both phase II enzymes, althoughthe role of NAT2 appears to be more complex. A recentmeta-anabysis suggests a statistically significant but modest

increase in the OR for the GSTMJ-null genotype (GSTMJ-)among lung cancer patients compared to hospital or population

controls (2), and further studies with varying results have ap-peared (3-13). The NAT2 gene has been much less investigated

with regard to lung cancer and presents a more complex picture.An increased susceptibility related slow acetylator genotypeswas suggested for bladder cancer (14-16), particularly amongoccupationally exposed or smokers, and, recently, for postm-enopausal breast cancer related to smoking dose (17). The

effect of NAT2 may be both to deactivate or activate arylaminecompounds, and the rate-limiting step may depend on sub-

strates and target organ (18, 19). Regarding lung cancer, anincreased OR was associated with the slow acetylator pheno-type in one small study (20) and with slow acetylator genotypes

in a population with low prevalence of such genotypes foradenocarcinomas but not for squamous cell cancers (2 1 ). How-

ever, most of the phenotyping or genotyping studies on lungcancer show no overall lung cancer risk related to the slowacetylator genotype (22-27). The complex cooperation of the

3 The abbreviations used are: GSTM 1, glutathione S-transferase pA ; NAT, N-

acetyltransferase; OR, odds ratio; ETS, environmental tobacco smoke; CI, con-

fidence interval.

on June 6, 2020. © 1998 American Association for Cancer Research. cebp.aacrjournals.org Downloaded from

http://cebp.aacrjournals.org/

876 GSTMI and NA T2 Genotypes, Tobacco Smoke, and Lung Cancer

NATs NAT2 and NAT1 with the CYP1A1 phase I enzyme informing reactive arylnitrenium ions from arybamine carcino-

gens, such as those in tobacco smoke (18, 19, 28, 29), suggeststhat, contrary to the general hypothesis regarding phase II

enzymes (1), the possibility of an increased lung cancer riskrelated to rapid acetylator genotypes, particularly in the ho-

mozygous form (27), cannot be excluded.The aim of this study was to evaluate the hypothesis of an

increased risk of lung cancer in never-smoking and smokingsubjects related to the GSTMJ-null (GSTMJ-) and slow acet-

ylator genotypes, which are associated with reduced activity of

the corresponding phase II enzymes. On the basis of recent

contradictory results (2 1 , 27), we also examined the impact ofthe rapid acetylator genotype on increasing lung cancer riskamong smokers.

Our study has several novel aspects and strengths. It in-cludes a comparatively large number of never-smokers, a group

that has not been extensively investigated previously with re-gard to the studied genotypes. In addition, our study includes a

majority of women. Special attention was given to validation ofsmoking status, a detailed history of exposure to ETS fromdifferent sources, and evaluation of potential confounders.

Materials and Methods

Study Subjects. Subjects and methods, as well as results re-

lating to passive smoking and lung cancer among the never-smokers in the study population, have been described in detail

elsewhere (30). The original study base comprised Swedish-speaking people who were �30 years of age and who residedin Stockholm county (- I .7 million inhabitants in 1995) from

October 1, 1989, to September 30, 1995. Only subjects inter-viewed after January 1 , 1992, were eligible to enter into thisstudy.

Three hospitals, Karolinska Hospital, Huddinge Hospital,

and S#{246}dersjukhuset, are mainly responsible for diagnosing lungcancer cases in this population, defining three catchment areas.Cases had a microscopically confirmed diagnosis or unambig-

uous chest X-ray pictures with a typical clinical course. Iden-tifled never-smoking cases were recruited, and the next diag-

nosed ever-smoking case of the same sex and age group (threeage groups: 30-49 years, 50-69 years, and �70 years) in thesame hospital was recruited, for a frequency-matched smokingcase group. Ever-smoking was defined as having smoked � 1

cigarette/day, 10 cigarettes/week, or 40 cigarettes/month or 4cigarillos/month, 3 cigars/week, or 4 pipes/week for 1 year.

Of lung cancer cases among never-smokers, 8.3% diedbefore an interview could be scheduled or were identified atautopsy, and 6.2% refused to participate (total nonparticipation

rate = 14.5%). Among ever-smokers, 4.4% died before aninterview could be scheduled, and 8.8% refused to participate

(nonparticipation rate = 13.2%). A total of 92 eligible never-smoking cases and 99 ever-smoking cases were interviewed.

Patients were approached when a diagnosis of lung cancer

had been established. Because blood parameters that were sen-sitive to radiation or chemotherapy were also measured, ever-smokers were not enrolled if such treatment had been initiated

before blood sampling, which occurred for some patients (par-ticularly with small cell cancers) due to rapid hospital proce-

dures. Instead, the next diagnosed matching ever-smoking casewas then included. Of 99 smoking cases, 71 were initialchoices, and 28 were “replacements” due to such nonenrolbedtreated cases or because initially selected cases refused or died

before interview. Nonetheless, four smokers were inadvertently

enrolled despite started treatment. In contrast, all never-smok-

ing cases were enrolled because of their rarity, including sixcases who had started treatment.

For 96% of cases, we retrieved histological or cytological

slides, which one pulmonary pathologist reviewed to validatethe original diagnosis, according to the WHO histological typ-

ing of lung tumors (31).Controls from the Stockholm county population register

were frequency matched to cases in strata defined by sex, age

group, and hospital catchment area. They were selected every 6months, based on the case distribution at the time. For controls

sampled in 1995, matching was only for sex and age because

administrative changes in the health care system had lead to less

well-defined catchment areas. Controls were contacted by mail

or by telephone if they did not respond, screened for smokingstatus, and asked to participate if they suited the supplementary

frequency-matching criteria for smoking. The matching cate-

gories used were: never-smoker, former smoker (quit smoking

>2 years previously), and three levels of current smoker (i.e.,still smoked or quit more recently than 2 years previously), 0-9

cigarettes/day, 10-19 cigarettes/day, and �20 cigarettes/day.We were unable to contact or locate 6. 1 % of potential

controls drawn from population registers. The subsequentscreening of contacted persons gave a nonresponse rate of

17.8%. Among never-smokers, approximately twice the num-

ber of controls to cases was interviewed, but only every secondcontrol was asked to give a blood sample. As a result, 85

eligible never-smoking and 94 ever-smoking controls wereincluded in this study.

In total, 370 interviewed subjects were eligible for bloodsampling. Six of 191 cases (3.1%) and 15 of 179 controls

(8.4%) refused or could not provide blood, leaving 349 subjectswith blood samples (185 cases and 164 controls) as the studypopulation. The results of both GSTMJ and NAT2 analyses

were missing for one case and three controls, and the results ofthe NAT2 analyses only were missing for one additional case

and three additional controls. The combined genotype analysis,thus, included 341 subjects.

Exposure Information. A trained physician or nurse inter-

viewed subjects using a structured questionnaire. A personal

visit was scheduled when possible (96.3%). Otherwise, a tele-

phone interview was conducted, and blood samples were cob-lected at a separate visit. Both interviewers interviewed cases

and controls. The questionnaire comprised questions regardingoccasional smoking; a residential history, including addressesand building characteristics; a lifetime occupational history;and a food frequency assessment of foods rich in vitamin A,

carotene, and vitamin C. We assessed exposure to ETS using a

core questionnaire developed on the basis of a study on urinary

cotinine and ETS exposure (32). Exposure to known or sus-

pected occupational lung carcinogens (33) was evaluated basedon all occupations in the working history, classified as to

occupational code (ISCO-68; Ref. 34) and industrial code(ISIC-71; Ref. 35).

GSTM1 and NAT2 Genotyping. Blood was collected in four10-mb tubes containing heparmn. Leukocytes were isolated by

fractionation in Polymorphprep (Pharmacia, Uppsaba, Sweden)and preserved. Granubocytes were freshly lysed, and the DNAwas extracted with saturated NaCb according to a protocol

described by Andersson et a!. (36).

Genotyping was basically carried out as described previ-ously (37). The presence or absence of the GSTMJ gene wasdetected by genomic PCR of a short internal GSTMJ genesegment (177 bp) together with a NAT2 segment (284 bp) as aninternal PCR control. The GSTMJ primers were: 5’-CTG CAA



Cancer Epidemiology, Biomarkers & Prevention 877

TGT GTA GGG GGA AG-3’ (forward) and 5’-CTG GAT TGTAGC AGA TCA TG-3’ (reverse), annealing to the 5’ region of

intron 4 and the 3’ region of exon 5, respectively. The NAT2

primers were 5K (5’-GGA AGC TCC TCC CAG ATG TG-3’,

forward at positions 376-395) and 3T (5’-GTG GTF ATAAAT GAA GAT G’VF G-3’, reverse at positions 659-638).

Approximately 100 ng of DNA were used in a 50-gb

reaction containing 10 mrvi Tris-HC1 (pH 8.4), 50 mt�i KC1, 1.5

mM MgC12, 0.2 mM dNTP, and 0.4 �tM each primer. One unit of

Taq polymerase (Promega) was added into each tube after a

5-mm hot start at 95#{176}C.The DNA was amplified by 33 cycles

of denaturation (94#{176}C,30 s; first cycle, 6 mm), annealing

(58#{176}C,30 s), and elongation (72#{176}C,30 s; last cycle, 8 mm) ina thermocycler (model 2400; Perkin-Elmer), followed by elec-trophoretic separation in a 5% polyacrylamide gel.

Identification of the slow NAT2 alleles was performed byrestriction analysis of a 578-bp genomic PCR product covering

the major part of the intronless NAT2 coding region. Theprimers used were 5K (described above) and 3N (5’-GAG AGG

ATA TCT GAT AGC AC-3’, reverse at positions 953-934).

Ten p.1 of the PCR product were digested by 5 units of KpnI,

TaqI, BamHI, or Dde! (Promega) in an appropriate buffer for

4 h at 37#{176}C(65#{176}Cfor TaqI) in a total volume of 20 p1 The

TaqI- and DdeI-digested products were separated by electro-

phoresis in 7% polyacrylamide gel, and the others were run in

5% gels.The predominating NAT2*5A/B (341C, 481T) and

NAT2*6AIB (590A) alleles were identified by loss of restrictionsites for KpnI and TaqI, respectively. Individuals in whom no

or only one of the slow alleles could be identified by these

enzymes were further analyzed by BamHI and DdeI digestionto identify the NAT2*7A/B (857A) and NAT2*5C (341C, 803G)

alleles, respectively. An allele-specific PCR for the normal or

mutated nucleotide at position 341 (T>C, NAT2*5 specific)was incorporated to distinguish between the slow NAT2*5C

allele and the rapid NAT2*12 (803G only) allele. The following

primers were used at an annealing temperature of 53#{176}C:5 ‘-CTCCTG CAG GTG ACC AT/C-3’ (forward at positions 325-341;

341T/C) and 5’-GTG GTF ATA AAT GAA GAT GTF G-3’

(reverse at positions 659-638; 3T).

Individuals with one or two copies of the GSTMJ alleleshowed both the GSTMJ and the control band and were des-ignated GSTMJ + ; those with homozygous deletion of the

GSTMJ allele had only the control gene amplified, and weredesignated GSTMJ - (GSTMJ-null). Individuals with one or

two “rapid” alleles (NAT2*4, NAT2*12) were designated rapid

acetylators (38), whereas those with two “slow” alleles (NAT2

5AIB/C, 6AIB, 7A/B) were designated slow acetylators.

Statistical Methods. Whether the prevalence of genotypes in

the control population depends on factors such as sex, age, andsmoking habits was explored using ORs for genotype preva-

lence. These prevalence ORs and 95% CIs were estimated by

unconditional logistic regression analysis with genotype as

outcome, using only the population controls.

For case-control analyses, ORs and corresponding 95%CIs were obtained in unconditional logistic regression using

case status as outcome (39). In case-control studies with mci-

dence density (or “risk-set”) sampling of controls, such as thisone, the OR thus obtained may be considered an estimate of theincidence rate ratio for exposed versus unexposed (40, 41).

We converted pipes, cigarilbos, and cigars smoked to cig-

arette equivalents using factors of 2, 3, and 5. Pack-years (20cigarettes/day for 1 year) of smoking represent cumulative

smoking dose. The ETS exposure variables address different

Table I Distribution of selected characteristics in lung cancer cases and

control subjects from 1992 to 1995 in Stockholm, Sweden

Cases Controls

Variable �-�--�_I 85)

No. % No. (7(

Sex”

Male 47 25.4 47 28.7

Female 138 74.6 117 71.3

Age”” (yr)

30-49 18 9.7 19 11.6

50-59 23 12.4 39 23.8

60-69 53 28.7 30 18.3

70-79 67 36.2 48 29.3

�80 24 13.0 28 17.1

Smoking status”

Never 88 47.6 79 48.2

Former (quit >2 y ago) 28 15.1 25 15.2

Current (quit �2 y agoY

Last smoked <10 cigarettes/day 20 10.8 21 12.8

Last smoked 10-19 cigarettes/day 22 1 1.9 23 14.0

Last smoked �20 cigarettes/day 27 14.6 16 9.8

Duration of occupational history

Never employed 4 2.2 2 I .2

<l0years 6 3.2 7 4.3

�l0years 175 94.6 155 94.5

“ Matching factor (frequency matching).b Matched in strata of 30-49, 50-69, and �70 yr.

� Matching of current smokers in three strata according to last smoked amountwas not completely successful. However. many subjects in the �20 exposure

group in fact reported consuming exactly 20 cigarettes/day. and the two top

categories pooled were well balanced.

sources and environments, as well as time of exposure, and are

described elsewhere (30). The main variable used here repre-

sents exposure from the spouse and/or the workplace (the twomajor sources of ETS exposure) during the last 10 years (yes or

no).Age and cumulative active smoking (pack-years) were

included in the models as continuous variables. Nonparametricsmoothing and regression modeling indicated a nonlinear as-

sociation on the bogit between age and lung cancer risk, whichwas modeled using a second-degree polynomial (linear andquadratic term). The functional form for pack-years appeared tobe reasonably linear overall on the bogit of the probability fordisease but was also modeled with a second-degree polynomial

to allow for nonlinearity in subgroups. All case-control esti-mates were also adjusted for matching strata to account forselection probabilities: sex, three age groups (30-49 years,

50-69 years, and �70 years), three catchment areas, andsmoking category (never-smoker; former smoker; and currentsmoker at 0-9 cigarettes/day, 10-19 cigarettes/day, and �20

cigarettes/day); and for ETS exposure status (yes or no withinlast 10 years), where appropriate for confounding control.

In some cases, overall estimates are presented even wherepoint estimates in subgroups vary considerably, in which case

a cautious interpretation is recommended. However, subgroupvariability may also reflect random variation due to small

numbers. Furthermore, the overall estimates can also be useful

in interpreting our results in the light of previous studies.

Results

Subject Characteristics. The distributions of sex and age, aswell as some other characteristics of the subjects, are shown in

Table 1. The female subjects were slightly older, on average,



878 GSTMJ and NAT2 Genotypes, Tobacco Smoke, and Lung Cancer

Table 2 Distribution of tumor subtypes among lung cancer cases from 1992to 1995 in Stockholm, Sweden”

Variable

Males(n 47)

No. %

Fe(n

No.

males138)

%b

Histopathological tumor type

Adenocarcinoma 22 46.8 72 52.9

Squamous cell 18 38.3 29 21.3

Small cell 0 9 6.6

Large cell 2 4.3 5 3.7

Carcinoid 3 6.4 13 9.6

NSCLC,’ ‘�malignant cells,” and other types 2 4.3 8 5.9

Only clinical diagnosis 2

“ On the basis of histology for 76.0% of classified tumors. Only cytology was

available for 22 adenocarcinomas (23%), 1 1 squamous cell tumors (23%), 4 small

cell tumors (44%), 1 large cell tumor (14%), and 6 of 8 tumors classified as

non-small cell lung cancer or malignant cells (75%).

I, Percentage of subjects with available histopathological data.

‘. NSCLC, non-small cell lung cancer.

than the men (67.8 and 65.1 years for cases and 66.4 and 62.0years for controls, respectively).

All but two female cases were histologically (75.1%) or

cytologically (23.8%) confirmed, with a distribution of tumortypes according to Table 2. As noted in “Materials and Meth-ods,” some aspects of the case recruitment influenced the dis-tribution of tumor types among the ever-smokers. However,

squamous cell (41.7%), small cell (7.3%) and large cell (5.2%)cancers were still more common among ever-smokers, whereasadenocarcinomas (64.4%) and carcinoids (17.2%) were morecommon among never-smokers.

Distribution of the GSTMJ and NAT2 Polymorphisms

among Population Controls. The overall prevalence of theGSTMJ - genotype in the population control group was 50.3%.

The prevalences in four subgroups (men, women, never-smok-

ers, and ever-smokers) were 44.7%, 52.6%, 54.4%, and 46.3%,respectively, but differences were nonsignificant. The overallprevalence of the NAT2 slow acetylator genotype in the popu-

lation was 60.8%. The prevalences in the four subgroups were55.3%, 63.1%, 53.8%, and 67.5%, respectively, but again,

differences were nonsignificant (P = 0.08 for difference ofNAT2 slow prevalence between never- and ever-smokers).

If genotypes are, in fact, associated with various diseasesthat have increased mortality (such as cancers), one wouldexpect a decreasing prevalence of a deleterious genotype withincreasing age in the surviving population. Such changes could

also be differential between subgroups with different expo-

sures, e.g. , across sexes or smoking habits, which would makethe selection of an appropriate control group, as well as adjust-

ment for matching factors in a case-control analysis, of utmostimportance for valid results. When this question was investi-gated in our sample of population controls, some tendenciesemerged in a logistic regression analysis. The prevalence ofboth the GSTMJ - and the slow acetylator genotype appearedto increase with age among never-smokers and decrease withage among ever-smokers (Table 3). There was a tendency for ahigher prevalence of both the GSTMI - and the slow acetylator

genotype among women than men, which was shown to be

restricted to the smoking subgroup. A higher prevalence of theslow acetylator genotype was again suggested among smokers

and an increase with cumulative exposure in this group,whereas the opposite relationship to smoking was suggested for

the GSTMJ - genotype.

Associations between the GSTMJ and NAT2 Polymor-phisms and Lung Cancer Risk. The overall OR of lungcancer associated with the genotype GSTMJ - versus GSTMJ +was 0.8 (95% CI, 0.5-1.2; Table 4). There was some hetero-

geneity between subgroups. The two point estimates above

unity for this polymorphism in Table 4 were attributable to

mainly male ex-smokers and smokers. Consistently lower ORswere seen among never-smokers, whereas for smokers the

overall estimate was close to unity.The overall OR associated with the slow versus rapid

acetylator genotype was 1.0 (95% CI, 0.6-1.5; Table 4).

This overall estimate should be interpreted cautiously be-

cause there were more marked differences between thesmoking and never-smoking subgroup. The point estimates

for never-smokers were consistently above 1 , whereasamong smokers there was an opposite tendency, implying anincreased risk for rapid acetylators. When we subdivided

rapid acetylators by zygosity, the ORs obtained amongsmokers were 1.5 (95% CI, 0.7-3.4) for heterozygous rapid

acetylators and 4.9 (95% CI, 0.8-29.9) for homozygousrapid acetylators (7 cases and 2 controls). Among never-

smokers, the trend again was reversed, with ORs of 0.7 (95%

CI, 0.4-1.4) and 0.2 (95% CI, 0.02-2.3; only one case and

three controls), respectively. Although statistically not sig-

nificant, increased risk was thus suggested for the GSTMJ +

and slow acetylator genotypes among never-smokers but forthe rapid acetylator genotype among ever-smokers.

Interactions between the GSTMJ and NAT2 Polymorphisms

and Lung Cancer Risk. To evaluate interaction between the

genotypes, we analyzed the combined genotype similarly in

subgroups, with the rapid acetylator and GSTMJ + genotype asreference. Never-smokers were at a particularly high risk if they

carried the combination of slow acetylator and GSTMJ + gen-otypes (OR = 3. 1 ; 95% CI, 1 . 1- 8.6; Table 5). The point

estimate for this genotype combination was higher among nev-

er-smokers exposed to ETS in the last 10 years (such exposurewas more common among men; Ref. 30) than it was among

those without such exposures. Among smokers, the results were

less consistent, and there was no clear relation to exposure

across smoking categories (data not shown). The two genotypecombinations including rapid acetylation appeared to be asso-

ciated with higher risks.

Interactions between Tobacco Smoke Exposure and theGSTMJ and NAT2 Polymorphisms and Lung Cancer Risk.To increase the power of detecting interaction and to avoiddependence on arbitrary cutoff points, we modeled pack-years

as a continuous variable, with linear and quadratic terms. Fig.

1 illustrates the relationship between cumulative tobacco con-

sumption (pack-years) and the OR for disease, stratified for the

GSTMJ and NAT2 genotypes, respectively. Fig. 1A shows anincreasing risk with increasing pack-years that does not seem todiffer between the GSTMJ genotypes. The curves follow each

other closely, with a slightly lower risk for subjects with gen-otype GSTMJ - in the bower dose range, which would be

consistent with the previously noted tendency to decrease inrisk for this genotype among never-smokers in our data. In Fig.lB. a different pattern appears for NAT2. There is little differ-

ence in risks between the genotypes at low doses of smoking.As the dose increases, however, the increase in risk is steeper

among subjects with the rapid acetylator genotype than amongthose with the slow acetylator genotype. A similar pattern wasseen in an analysis using a categorical pack-year variable (data

not shown). Nonetheless, due to the limited amount of data, wecannot reject a null hypothesis that the effect of smoking is the




Table 3 Prevalence ORs” in a control popu lation for having the GSTMJ - genotype vs. GSTMJ + and for having the slow vs. rapid acetyl

function of some important subject characteristicsator genotype. as a

Model” Population

Variables that could affect the balance of genotype prevalences

Time sinceFemale sex’ High aged Smoking status’ . � . �

stopping smoking’

A. Prevalence OR for GSTM1 - versus GSTMJ + genoiype

Pack-years”

1

2

3

All controls (n = 161)

Never-smokers (n 79)

Ever-smokers (n 82)

l.4� (0.7-2.8) 0.9 (0.4-1.8) 0.7(0.4-1.3)

1.1 (0.4-2.9) 1.6 (0.6-4.3)

1.7(0.6-5.1) 0.6(0.2-1.7) 0.8(0.4-1.7) 0.7 (0.1-3.2)

B. Prevalence OR for slow versus rapid acetylator genotype

1

2

3

All controls (n = 158)

Never-smokers (n = 78)

Ever-smokers (n = 80)

1.4 (0.7-2.8) 1.1 (0.5-2.2) 1.8 (0.9-3.4)

1 .0 (0.4-2.8) 1 .9 (0.7-5.2)

2.5 (0.8-8.0) 0.5 (0.2-1.8) 0.8 (0.4-1.6) 2.7 (0.4-16.1)

‘. Table estimates indicate the OR for being of genotype GSTMI - (vs. GSTM1 + ; A) or of slow vs. rapid acetylator genotype (B).b The respective logistic regression models include the variables on the corresponding row in the table exclusively.( The prevalence ORs for categorical variables are given for a woman compared to a man and an ever-smoker compared to a never-smoker.d The prevalence ORs for continuous variables are given for the difference between the 90th and the 10th percentile of the exposure distribution for that variable among

exposed controls, i.e., for 32 years difference for age. 16 years difference for time since stopping smoking. and 43.7 pack-years difference for smoking dose.

� Values indicate prevalence ORs (95% CIs).

Table 4 OR of lung cancer associated with the GSTMI - and NAT2 slow acetylator genetic polymorphisms. in subgroups defined by smoking habits”

Never-smokers Ever-smokers

ETS-exposed in the last 10 years”

All

Current’

Former’ .�3#{216} >30 All

pack-years pack-years

.All subjects

No Yes

GSTMI

Cases (GSTMJ+/-)

Controls (GSTMI +1-)

OR for GSTMI- vs. GSTMJ+ (95% CI)

NAT2

Cases (rapid/slow)

Controls (rapid/slow)

OR for slow vs. rapid (95% CI)

26/18

22/23

0.6 (0.2-1.5)

14/30

19/26

1.8 (0.7-5.0)

21/23

14/20

0.7 (0.2-1.9)

18/26

17/16

1.7 (0.6-4.8)

47/41

36/43

0.6 (0.3-1.1)

32/56

36/42

1.5 (0.8-3.0)

1 1/17 23/9 19/17 53/43

15/9 19/2 1 1 0/8 44/38

3.9 (0.8-18.2) 0.4 (0.1-1.6) 1.6 (0.4-7.1) 0.9 (0.4-1.9)

10/17 10/22 18/18 38/57

9/14 12/27 5/13 26/54

0.6 (0.1-2.8) 0.9 (0.2-3.7) 0.3 (0.1-1.3) 0.6 (0.3-1.2)

100/84

80/81

0.8 (0.5-1.2)

70/1 13

62/96

1.0 (0.6- 1.5)

a All estimates and CIs are adjusted for sex, age (matching strata and second-degree polynomial), and catchment area (matching strata). Adjustment was also made for

smoking status (matching strata), pack-years of smoking exposure (second-degree polynomial), and recent ETS exposure (yes/no). except in subgroup analyses where these

latter adjustments were not relevant.b Exposed to ETS from spouse or work during the previous 10 years.

C Former smoker, quit >2 yr before study (average, 15.9 yr); current smoker, smokes or quit �2 yr before study (average. 3 months; 66.7% still smoke). The average

numbers of pack-years were 20.5 among former smokers. 17.4 among ‘current �30,” and 44.6 among “current >30.”

same across the NAT2 genotypes [likeihood ratio test f (two

degrees of freedom) = 1.29, P = 0.52]. The smoking relation-

ships for both GSTMJ and NAT2 genotype subgroups remained

similar if modeled with only a linear term, with a linear and a

square root term, or when estimated after excluding the moreextreme values for pack-years in our dataset (>60 pack-years).It is notable that, of eight subjects with smoking doses of >60

pack-years, six cases and one control have the GSTMJ + andslow acetylator genotype, perhaps suggesting that subjects with

this combination are more likely to tolerate high smoking dosesbefore developing lung cancer.

Similar interaction analyses among never-smokers forhours of exposure and time since last exposure to ETS from

spouse or work confirmed our previously published resultsregarding risk from ETS (30). However, the OR for the

GSTMJ - versus GSTMJ + and slow versus rapid acetylatorgenotypes were similar to the overall estimates for never-

smokers presented in Table 4 over the whole range of ETSexposure dose, with no clear interaction between dose and

genotype (data not shown).

Discussion

Many previous studies on genotype and lung cancer have used

only surgical or prevalent cases, which may be problematic ifgenotype is associated with tumor characteristics that influence

malignancy grade or survival. Our case series attempts to re-cruit all incident lung cancer cases among never-smokers and amatched sample of incident cases among smokers. The controlsare appropriately aged and incidence density sampled from the

study population that produced the cases. Our study populationwas well characterized in terms of sex; age; smoking habits,including passive smoking; diet; residence; and occupation. As

previously reported, the next-of-kin validation regarding smok-ing status of the never-smokers was highly concordant (99% for

cases and 97% for controls; Ref. 42). For the one case and threecontrols who reported occasional smoking when next-of-kin

reported “daily or almost daily” smoking, there were no majorcontradictions regarding total amount smoked, all smoking had

occurred � 1 8 years previously, and thus all never-smokerswere retained as such in the analyses. We evaluated potential

confounding and present results from multivariate analyses



880 GSTMI and NAfl Genotypes, Tobacco Smoke, and Lung Cancer

incorporating matching variables and relevant confounder van-

ables.

Nevertheless, the analyses suffer from the limited numberof subjects. A large majority of subjects were women, which

hampered attempts to make comparisons between sexes. Theparticipation among cases was high. However, a previous in-vestigation among women in Stockholm has shown that aproportion of all cases are not diagnosed in the hospitals usedfor recruitment in our study, particularly among elderly subjects

(43). How this applies to men and never-smoking cases cannotbe evaluated. Furthermore, it is not known if the recruitment ofcases was related to any of the exposure factors under study.Our results could be less generalizable to all lung cancer if theincluded cases represent a subgroup of tumors with particularcharacteristics.

The overall prevalence of the GSTMJ - genotype among

controls in our study agrees well with a published estimate of52.9% among 329 Swedish population controls pooled from

several sources (44). However, that control group consisted

almost exclusively of men (91%) and were all below 65 yearsof age, whereas our controls were 7 1% women with an averageage of 65.2 years. The similar estimates may indicate that the

GSTMI genotype prevalence does not vary by sex or agegroups in the Swedish population. On the other hand, in amultivariate analysis among our controls, we found suggestionsof higher GSTMJ - gene prevalence among women smokersand among never-smokers as compared to ever-smokers, aswell as different trends with age between never- and ever-

smokers. This suggests that the choice of a control group that

adequately represents the exposure distribution in the studybase deserves attention in studies of genetic polymorphisms.

Other studies of reasonable size (> 100 subjects) in Cau-casian populations have published overall genotype prevalencefigures for GSTMI - from 38 to 58% (45, 46). Althoughrandom variation could play a role (at such prevalences, a 95%CI in a 100 subject sample is about ± 10%), differences in

ethnicity, genetic setup, or age distribution cannot be ruled outas explanations.

Our overall estimate for the OR of lung cancer associatedwith the GSTMJ- genotype (0.8; 95% CI, 0.5-1.2) is some-

what at odds with previous studies. A recent meta-analysis

suggested an increased risk (OR = 1.34; 95% CI, 1.19-1.58),although the estimate for studies on Caucasian populations onlywas 1 . 17 (95% CI, 0.98-1 .40; Ref. 2). The decreased risk that

we observed was most apparent among never-smokers, with the

OR among smokers close to unity. Most previous studies haveinvestigated smokers, in many cases heavier smokers than inour study, and our results add to the evidence suggesting that

the GSTMJ - genotype is not associated with a substantialincrease in lung cancer risk in smoking Caucasian populations.The analysis of combined genotype effects suggests that thecombined slow acetybator and GSTMJ + genotype was respon-sibbe for most of the slight risk associated with GSTMJ+,which we observed particularly among ETS-exposed never-

smokers.

Our study found no clear indication of a GSTMJ - geno-type effect on the lung cancer risk among smokers and virtuallyno indication of interaction between GSTMJ genotype andsmoking dose. Several studies have previously evaluated the

interaction between GSTMI genotype or phenotype and smok-ing dose, with contradictory results. Five studies reported

higher risk associated with GSTMJ - among heavy smokers(47-51). Two of these were phenotyping studies, and threewere genotyping studies with hospital-based controls. Other

studies reported higher risks associated with GSTMJ - at low

Table 5ORof lung cancerassociated with combined genotypes of GSTMI

and NAfl, overall and in subgroups defined by smoking habits”

Never-smokers Ever-smokers All subjects

Cases (r+/s+/r-/s-)5 10/37/22/19 19/33/19/24 29170/41/43

Controls (r+/s+/r-/s-)” 17/19/19/23 14/29/12/25 31/48/31/48

Reference category (rapid/+ ) I I 1

OR for slow/+� (95% Cl) 3.1 (1.1-8.6) 0.5 (0.2-1.4) 1.4 (0.7-2.8)

OR for rapid/-’ (95% CI) I .4 (0.5-4.3) 0.8 (0.2-2.6) 1 .3 (0.6-2.7)

OR for slow/-’ (95% Cl) 1.1 (0.4-3.0) 0.5 (0.2-1.4) 0.8(0.4-1.7)

“ All estimates and confidence intervals are adjusted for sex, age (matching strata

and second degree polynomial), catchment area (matching strata), and recent ETSexposure (yes/no). Adjustment was also made for smoking status (matching

strata) and pack-years of smoking exposure (second-degree polynomial), except

in the subgroup analysis of never-smokers.

h Number of individuals with combinations of rapid (r) or slow (s) acetylator

genotypes with GSTMI + (+) or GSTMI - (-) genotypes.

� OR for lung cancer among individuals with the indicated genotype combination,in relation to individuals in the reference category (rapid acetylator and

GSTMI+).

smoking dose (6, 9, 52, 53). A recent large study using analysesof continuous variables similar to ours, noted reduced riskassociated with GSTMJ - among heavy smokers (>50 pack-

years) but slightly increased risk among lighter smokers (themajority of subjects; Ref. 1 1). The interaction was not statisti-

cally significant, and the crossover of effects was judged to bebiologically implausible, so that the authors considered chanceto be a reasonable explanation.

Case and control selection and confounding issues may

contribute to the different results in these studies. In addition, itcan be difficult to evaluate interaction between a weak risk

factor, as these genotypes appear to be, and a strong risk factorsuch as smoking using only a few strata. Results may depend on

the selection of cutoff points and random variation in case andcontrol distribution between the strata selected. Evaluation on acontinuous scale is more likely to reveal actual patterns ofinteraction.

The proportion of slow acetybator genotypes among con-trols was somewhat higher than previously reported for Cau-casian populations. Earlier studies have reported 44-58%, with

larger studies generally in the higher end (14-17, 20, 22-25,54). BrockmOller et a!. (15) have reported as high as 69%

among women. The distribution of the slow and rapid acetyla-tor genotypes in our control population appeared to be more

strongly influenced than GSTMJ genotypes by sex, age, andsmoking dose, possibly suggesting that there is a stronger

association between acetylator genotype and various diseasesthat could cause the genotype prevalence to vary in different

sections of the population.We observed decreased risk of lung cancer associated with

the slow acetylator genotype among smokers (OR = 0.6; 95%CI, 0.3-1 .2) but increased risk among never-smokers (OR =

1.5, 95% CI, 0.8-3.0), with an overall OR of 1.0. Previousstudies have generally found ORs close to unity (22, 26) or

slightly less than one (23-25, 27) for the slow acetybator gen-otype, although one small study found a high OR (20). The

study subjects, in particular the cases, are generally smokers.One recent Japanese study reported a raised OR of 2.0 (95% CI,

1 .0-4.0) for adenocarcinomas, but OR 0.7 (95% CI, 0.2-2.0)for squamous cell carcinomas (2 1). No smoking data are given,but it may be noted that adenocarcinomas are proportionallymore common among never-smokers and light smokers, andsquamous cell cancers are more typical smoking related can-

cers, as in our study. Thus, our results agree well with previousreports and suggest a slightly increased risk associated with the



Fittedoddsratiooflungcancer

B

Fittedoddsratiooflungcancer

-�-�-I - I � I I �

0 10 20 30 40 50 60 70 80 90 100

pack-years of smoking dose

500#{149}

200�

100�

50

20

10 -

5-

2

.5 -

5000

2000

1000

500

200-

100-

50�

20�

10�5.

2

.5

0 NAT2 rapid acetylatorgenotypes

t’ NAT2 slow acetylator

genotypes

V

VV

VV

,0

V

V

VV

I � I I I � �

0 10 20 30 40 50 60 70 80 90 100


A

5000�

2000#{149}

1000W

0 GSTMI gene present a GSTMI null genotype

Fig. 1. Fined values for the rela-

tionship between estimated lung

cancer risk and pack-years, stratified

for the GSTMJ (A) and NAT2 (B)

polymorphisms, respectively. From

a logistic regression model that.apart from pack-years (second-dc-

gree polynomial) and GSTMI (A) or

NAT2 (B) genotype and interaction

terms between genotype and pack-

year variables, included sex, age

(matching strata and second-degreepolynomial), catchment area and

smoking status (matching strata), re-

cent ETS exposure (yes/no), and the

other genotype, NAT2 (A) or GSTMI

(B). Data points, actual values for

pack-years among study subjects,

plotted against fitted OR oflung can-

cer; lines, estimated relationships.

rapid acetylator genotype in smokers and, interestingly, that

instead among never-smokers the slow acetylator genotype is

associated with increased risk.The analysis of interaction between smoking dose and

NAT2 genotype suggested that the increased risk associatedwith the rapid acetylator genotype becomes increasingly

manifest at higher dose levels, i.e. , put differently, that the

OR associated with pack-years of smoking dose is strongeramong subjects with the rapid than among subjects with theslow acetylator genotype. In this context, the slight riskincrement associated with the slow acetylator genotypeamong never-smokers is notable. Another investigation has

dismissed a cross-over of effects as implausible for the

pack-years of smoking dose

GSTMJ polymorphism (1 1). The NAT2 enzyme, on the otherhand, is active both in pathways for deactivating and acti-vating carcinogens, depending on substrate and rate-limitingsteps. It is possible that both of these mechanisms are active

in lung cancer, for example, because different carcinogensand dose levels activate or saturate the two pathways differ-

ently.In summary, our results, based on a well-characterized

study population, do not support a major role for the GSTMJ -

genetic polymorphism as a risk factor for lung cancer among

smokers or nonsmokers. There was, however, a suggestion thatthe slow acetylator genotype may confer an increased riskamong never-smokers and that the rapid acetylator genotype



882 GSTM1 and NA T2 Genotypes, Tobacco Smoke, and Lung Cancer

interacts with pack-year dose to produce a steeper risk gradientamong smokers.

Acknowledgments

We are grateful for the cooperation of the departments of Respiratory Disease and

Pathology of the participating hospitals and of all hospital staff who helped make

this study possible. We thank Veronica Agrenius, Katharmna Svartengren, Christer

Svensson, and Cam Cavalli-Bjdrkman for interviewing study participants and

Susann Falt for excellent technical assistance.

References

I . Law, M. R. Genetic predisposition to lung cancer. Br. J. Cancer, 61: 195-206,

1990.

2. McWilliams, J. E.. Sanderson, B. J., Harris, E. L., Richert-Boe, K. E., andHenner, W. D. Glutathione S-transferase Ml (GSTMI) deficiency and lung

cancer risk. Cancer Epidemiol. Biomark. Prey., 4: 589-594, 1995.

3. Kaioh, T. The frequency of glutathione-S-transferase Ml (GSTMI) gene

deletion in patients with lung and oral cancer [in Japanesel. Sangyo. Igaku., 36:

435-439, 1994.

4. Kihara, M., and Nods, K. Distribution of GSTM1 null genotype in relation to

gender. age and smoking status in Japanese lung cancer patients. Pharmacoge-

neiics, 5: S74-S79, 1995.

5. Kihara, M., and Noda, K. Risk of smoking for squamous and small cell

carcinomas of the lung modulated by combinations of CYPIAI and GSTMI genepolymorphisms in a Japanese population. Carcinogenesis (Lond.), 16: 2331-

2336, 1995.

6. London, S. J., Daly. A. K., Cooper, J., Navidi, W. C., Carpenter, C. L., andldle, J. R. Polymorphism of glutathione S-transferase Ml and lung cancer riskamong African-Americans and Caucasians in Los Angeles County, California.

J. Nail. Cancer Inst. (Bethesda), 87: 1246-1253, 1995.

7. Deakin, M., Elder, J., Hendrickse, C., Peckham, D., Baldwin, D., Pantin, C.,Wild, N., Leopard, P., Bell, D. A., Jones, P., Duncan, H., Brannigan. K.,

Alldersea, J., Fryer. A. A., and Strange, R. C. Glutathione S-transferase GS17’Igenotypes and susceptibility to cancer: studies of interactions with GSTMI in

lung, oral, gastric and colorectal cancers. Carcinogenesis (Land.), 17: 881-884,

1996.

8. Moreira, A., Martins, G., Monteiro, M. J., Alves, M., Dias, J., da Costa, J. D.,

Melo, M. J., Matlas, D., Costa, A., Crisiovao, M., Rueff, J., and Monteiro, C.Glutathione S-transferase gz polymorphism and susceptibility to lung cancer in the

Portuguese population. Teratog. Carcinog. Mutagen.. 16: 269-274, 1996.

9. To-Figueras, J.. Gene, M., Gomez-Catalan, J., Galan, C., Firvida, J., Fuentes,

M., Rodamilans, M., Huguet, E., Estape, J., and Corbella, J. Glutathione-S-

transferase M I and codon 72 p53 polymorphisms in a northwestern Mediterra-nean population and their relation to lung cancer susceptibility. Cancer Epide-

miol. Biomark. Prey., 5: 337-342, 1996.

10. El-Zein, R. A.. Zwischenberger. J. B., Abdel-Rahman, S. Z., Sankar, A. B.,and Au, W. W. Polymorphism of metabolizing genes and lung cancer histology:

prevalence of CYP2EI in adenocarcinoma. Cancer Leit.. 112: 71-78, 1997.

I I . Garcia-Closas, M., Kelsey. K. T., Wiencke, J. K., Xu, X. P., Wan, J. C., and

Christiani, D. C. A case-control study of cytochrome P450 lAl, glutathioneS-iransferase M I , cigarette smoking and lung cancer susceptibility (Massachu-

setts, United States). Cancer Causes Control, 8: 544-553, 1997.

12. Kelsey, K. T., Spitz, M. R., Zuo, Z. F., and Wiencke, J. K. Polymorphisms

in the glutathione S-transferase class �z and 0 genes interact and increase suscep-

tibility to lung cancer in minority populations (Texas, United States). Cancer

Causes Control, 8: 554-559, 1997.

13. Sun, G. F., Shimojo. N.. Pi, J. B., Lee, S., and Kumagai. Y. Gene deficiency

of glutathione S-transferase �z isoform associated with susceptibility to lung

cancer in a Chinese population. Cancer Leit., 113: 169-172, 1997.

14. Risch. A., Wallace, D. M., Bathers, S., and Sim, E. Slow N-acetylation

genotype is a susceptibility factor in occupational and smoking related bladder

cancer. Hum. Mol. Genet., 4: 231-236, 1995.

15. Brockmdller, J., Cascorbi, I., Kerb, R., and Roots, I. Combined analysis of

inherited polymorphisms in arylamine N-acetyltransfera.se 2, glutathione S-trans-

fera.ses Ml and TI . microsomal epoxide hydrolase. and cytochrome P450 en-zymes as modulators of bladder cancer risk. Cancer Res., 56: 3915-3925, 1996.

16. Okkels, H., Sigsgaard, T., Wolf, H., and Autrup, H. Arylamine N-acetyl-

transferase I (NATI) and 2 (NAT2) polymorphisms in susceptibility to bladder

cancer: the influence of smoking. Cancer Epidemiol. Biomark. Prey., 6: 225-231,

I 997.

17. Ambrosone, C. B., Freudenheim, J. L., Graham, S., Marshall, J. R., Vena,

J. E.. Brasure, J. R., Michalek, A. M., Laughlin, R., Nemoto, T., Gillenwater,K. A., and Shields, P. G. Cigarette smoking, N-acetyltransferase 2 genetic

polymorphisms, and breast cancer risk. J. Am. Med. Assoc., 276: 1494-1501,

1996.

18. Minchin, R. F., Kadlubar, F. F., and lIeu, K. F. Role of acetylation in

colorectal cancer. Mutat. Res., 290: 35-42, 1993.

19. Lang, N. P., and Kadlubar, F. F. Aromatic and heterocyclic amine metabo-

lism and phenotyping in humans. Prog. Clin. Biol. Res., 372: 33-47, 1991.

20. Cofta. S., Lowicki, Z., and Mlynarczyk. W. Fenotyp acetylacji u chorych na

raka pluca [in Polish]. Pneumonol. Alergol. Polska, 63: 407-409, 1995.

21. Oyama, T., Kawamoto, T., Mizoue, T., Yasumoto, K., Kodama, Y., andMitsudomi, T. N-Acetylation polymorphism in patients with lung cancer and its

association with p53 gene mutation. Anticancer Res., 17: 577-581, 1997,

22. Burgess, E. J., and Trafford, J. A. P. Acetylator phenotype in patients with

lung carcinoma: a negative report. Eur. J. Respir. Dis., 67: 17-19, 1985.

23. Philip, P. A.. Fitzgerald, D. L., Cartwright, R. A., Peake, M. D., and Rogers,

H. J. Polymorphic N-acetylation capacity in lung cancer. Carcinogenesis (Land.),

9: 491-493, 1988.

24. Roots, I., Drakoulis, N., Ploch, M., Heinemeyer, G., Loddenkemper, R.,

Minks, T., Nitz, M., One, F., and Koch, M. Debrisoquine hydroxylation pheno-type, acetylation phenotype, and ABO blood groups as genetic host factors of lung

cancer risk. lOin. Wochenschr., 66 (Suppl. I I): 87-97, 1988.

25. Laredo Quesada, J. M., Jara Sanchez, C., Benitez Rodriguez, J., Fernandez

Gundin, M. J., Vargas Castrillon, E., Munoz Gonzalez, J. J., Llerena Ruiz, A.,Cobaleda Polo, J., and Perez-Manga, G. Polimorfismo acetilador en el cancer de

pulm#{233}n[in Spanishl. Ann. Med. Intern., 8: 66-68, 1991.

26. Martinez, C., Agundez, J. A., Olivera, M., Martin, R.. Ladero, J. M., and

Benitez, J. Lung cancer and mutations at the polymorphic NAT2 gene locus.

Pharmacogenetics, 5: 207-214, 1995.

27. Cascorbi, I., Brockm#{246}ller, J., Mrozikiewicz, P. M., Bauer, S., Loddenkemper,

R., and Roots, I. Homozygous rapid arylamine N-acetyltransferase (NA7’2)

genotype as a susceptibility factor for lung cancer. Cancer Res., 56: 3961-3966,

I 996.

28. Hem, D. W., Doll, M. A., Rustan, 1. D., Gray, K., Feng, Y., Ferguson, R. J.,

and Grant, D. M. Metabolic activation and deactivation of arylamine carcinogensby recombinant human NATI and polymorphic NAT2 acetyltransferases. Carci-

nogenesis (Land.), 14: 1633-1638, 1993.

29. Wild, D., Feser, W., Michel, S., Lord, H. L., and Josephy. P. D. Metabolic

activation of heterocyclic aromatic amines catalyzed by human arylamine N-acetyltransferase isozymes (NATI and NAT2) expressed in Salmonella typhi-

murium. Carcinogenesis (Land.), 16: 643-648, 1995.

30. Nyberg, F., Agrenius, V., Svartengren, K., Svensson, C., and Pershagen, G.

Environmental tobacco smoke and lung cancer in nonsmokers: does time sinceexposure play a role? Epidemiology, 9: 301-308, 1998.

31 . WHO. The World Health Organization histological typing of lung tumors,second edition. Am. J. Clin. Pathol., 77: 123-136, 1982.

32. Riboli, E., Preston-Martin, S., Saracci, R., Haley, N. J., Trichopoulos, D.,Becher, H., Burch, J. D., Fontham, E. T., Gao, Y. T., Jindal, S. K., Koo, L. C.,

Le Marchand, L., Segnan, N., Shimizu, H., Stanta, 0., Wu-Williams, A. H., andZatonski, w. Exposure of nonsmoking women to environmental tobacco smoke:a 10-country collaborative study. Cancer Causes Control, 1: 243-252, 1990.

33. Boffetta, P., Kogevinas, M., Simonato, L., Wilbourn, J., and Saracci, R.

Current perspectives on occupational cancer. Int. J. Occup. Environ. Health, 1:

315-325, 1995.

34. WHO. World Health Organization Iniemational Standard Code for Occupa-

lions. Geneva: WHO. 1968.

35. WHO. World Health Organization Intemational Standard Industrial Code.

Geneva: WHO, 1971.

36. Andersson, B., Hou, S. M., and Lambert, B. Mutations causing defective

splicing in the human hprt gene. Environ. Mol. Mutagen., 20: 89-95, 1992.

37. Hou, S. M., Lambert, B., and Hemminki, K. Relationship between hprimutant frequency, aromatic DNA adducts and genotypes for GSTMJ and NAT2

in bus maintenance workers. Carcinogenesis (Land.), 16: 1913-1917, 1995.

38. Hem, D. W., Doll, M. A., Rustan, T. D., and Ferguson. R. J. Metabolic

activation of N-hydroxyarylamines and N-hydroxyarylamides by 16 recombinant

human NAT2 allozymes: effects of seven specific NAT2 nucleic acid substitu-

tions. Cancer Res., 55: 3531-3536, 1995.

39. Breslow, N. E., and Day, N. E. Statistical Methods in Cancer Research: The

Analysis of Case-Control Studies, Vol. 1. Lyon: IARC. 1980.

40. Pearce, N. What does the odds ratio estimate in a case-control study? Int. J.Epidemiol., 22: 1 189-1 192, 1993.

41. Pearce, N., and Boffetta, P. General Issues of Study Design and Analysis in

the Use of Biomarkers in Cancer Epidemiology. IARC Sci. PubI., 142: 47-57,1997.

42. Nyberg, F., Agudo, A., Boffetsa, P., Fortes, C., GonzAlez, C. A., and

Pershagen, G. A European validation study of smoking and environmental to-



Cancer Epidemiology, Blomarkers & Prevention 883

bacco smoke exposure in non-smoking lung cancer cases and controls. Cancer

Causes Control, 9: 173-182, 1998.

43. Svensson, C. Lung cancer etiology in women (Doctoral Thesis). Stockholm:

Karolinska Institute, 1988.

44. Alexandrie, A. K.. Sundberg, M. I., Seidegard, J., Tomling, G., and Rannug,A. Genetic susceptibility to lung cancer with special emphasis on CYPJAJ and

GSTMI: a study on host factors in relation to age at onset, gender and histological

cancer types. Carcinogenesis (Land.), /5: 1785-1790, 1994.

45. Lin, H. J., Han, C. Y., Bernstein, D. A., Hsiao, W., Lin, B. K., and Hardy, S.

Ethnic distribution of the glutathione transferase �z 1-1 (GSTMI) null genotype in1473 individuals and application to bladder cancer susceptibility. Carcinogenesis

(Land.), 15: 1077-1081, 1994.

46. Mikelsaar, A. V., Tasa, G., Parlist, P., and Uuskula, M. Human glutathione

S-transferase GSTMI genetic polymorphism in Estonia. Hum. Hered., 44: 248-

251, 1994.

47. Heckbert, S. R., Weiss, N. S., Hornung, S. K., Eaton, D. L., and Motulsky,

A. G. Glutathione S-transferase and epoxide hydrolase activity in human leuko-cytes in relation to risk of lung cancer and other smoking-related cancers. J. NatI.

Cancer Inst. (Bethesda). 84: 414-422, 1992.

48. Hirvonen, A., Husgafvel-Pursiainen, K., Anttila, S., and Vainio, H. TheGSTMJ null genotype as a potential risk modifier for squamous cell carcinoma ofthe lung. Carcinogenesis (Land.), 14: 1479-1481, 1993.

49. Kihara. M., and Noda, K. Lung cancer risk of GSTMI null genotype is

dependent on the extent of tobacco smoke exposure. Carcinogenesis (Land.). 15:

415-418, 1994.

50. Nazar-Stewart, V., Motulsky, A. G., Eaton, D. L., White, E., Hornung, S. K.,

Leng, Z. T., Stapleton, P., and Weiss, N. S. The glutathione S-transferase �spolymorphism as a marker for susceptibility to lung carcinoma. Cancer Res., 53

(Suppl.): 2313-2318, 1993.

51. Seidegard, J., Pero, R. W., Miller, D. G., and Beattie, E. J. A glutathione

transferase in human leukocytes as a marker for the susceptibility to lung cancer.

Carcinogenesis (Land.), 7: 751-753, 1986.

52. Brockm#{246}ller, J., Kerb, R., Drakoulis, N., Nitz, M., and Roots, I. Genotype

and phenotype of glutathione S-transferase class gz isoenzymes �a and Ii in lung

cancer patients and controls. Cancer Res., 53. 1004-101 1, 1993.

53. Nakachi, K., Imai, K., Hayashi, S., and Kawajiri, K. Polymorphisms of the

CYPJAJ and glutathione 5-transferase genes associated with susceptibility to lungcancer in relation to cigarette dose in a Japanese population. Cancer Res., 53:

2994-2999, 1993.

54. Bell, D. A., Stephens. E. A., Castranio, T., Umbach, D. M., Watson, M.,

Deakin, M., Elder, J., Hendrickse, C., Duncan, H., and Strange. R. C. Polyadenyl-

ation polymorphism in the acetyltransferase 1 gene (NAT!) increases risk of

colorectal cancer. Cancer Res., 55: 3537-3542, 1995.



1998;7:875-883. Cancer Epidemiol Biomarkers Prev F Nyberg, S M Hou, K Hemminki, et al. controls.nonsmoking and smoking lung cancer patients and populationgenetic polymorphisms and exposure to tobacco smoke in Glutathione S-transferase mu1 and N-acetyltransferase 2

Updated version

http://cebp.aacrjournals.org/content/7/10/875

Access the most recent version of this article at:

E-mail alerts related to this article or journal.Sign up to receive free email-alerts

Subscriptions

Reprints and

[email protected] at

To order reprints of this article or to subscribe to the journal, contact the AACR Publications

Permissions

Rightslink site. Click on "Request Permissions" which will take you to the Copyright Clearance Center's (CCC)

.http://cebp.aacrjournals.org/content/7/10/875To request permission to re-use all or part of this article, use this link



http://cebp.aacrjournals.org/cgi/alerts

mailto:[email protected]



glutathione s-transferase pa and n-acetyltransferase 2 ...we conducted a case-control study to...

Documents