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INSERM U170, 94807 Villejuif, France [I. S.]; International Agency for Research on Cancer, 69008 Lyon, France [P. B.]; Finnish Institute of Occupational Health, FIN-00250 Helsinki, Finland [S. A., A. H.]; INSERM U351, 94805 Villejuif, France [S. B.]; National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina 27709 [S. L.]; and Ospedale Policlinico IRCCS, University of Milan, 20122 Milan, Italy [E. T.]
| Abstract |
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| Introduction |
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Eleven metabolic gene polymorphisms have been studied with respect to individual susceptibility to lung cancer (2)
. In particular, polymorphisms have been described for the genes encoding for the enzymes GST, which are involved in the conjugation of electrophilic metabolites of xenobiotics. These cytosolic isoenzymes are divided into five major classes (
, µ,
,
, and
); genetic polymorphisms have been detected in the genes encoding GSTM1 (µ class), GSTM3, GSTT1 (
class), and GSTP1 (
class), and GSTZ1 (
class) (3)
. GSTs are involved in the metabolism of environmental carcinogens, such as PAHs, and in the conjugation of ROS. The role of the different class of GSTs in the trap of ROS, however, is not well understood (4)
.
The GSTM1 locus is deleted (null genotype) in
50% of Caucasians and in a lower proportion of people from other ethnic groups. The GSTM1-null genotype has been associated with a small increased risk of lung cancer in several studies. Recent meta-analyses of the studies performed in Caucasian populations resulted in a summary estimate of 1520% increased risk of lung cancer associated with the GSTM1-null genotype (5, 6, 7)
. The GSTT1-null genotype, on the other hand, occurs in 1020% of Caucasians and in
50% of Asians, whereas little data are available for African-Americans.3
Only a few reports with inconsistent results are available on the association between lung cancer risk and GSTT1-null genotype (6
, 8
, 9)
.
Similarly, only a few studies have addressed the role of metabolic gene polymorphisms in modulating the risk of pathologies associated with occupational exposure to carcinogens, and their interpretation is hampered by small numbers. One study suggested an effect of past occupational exposure to asbestos in lung cancer risk among CYP2D6-extensive metabolisers but not among poor metabolisers (10) . Another study found a nonsignificantly higher risk of lung cancer associated with the GSTM1-null genotype among subjects with possible or probable past occupational exposure to asbestos than among nonexposed subjects (11) . In Finland, an increased risk of mesothelioma has been observed among asbestos-exposed workers lacking the GSTM1 gene (12 , 13) . Studies on the nonmalignant, asbestos-associated pulmonary disorders, pleural plaques, did not, on the other hand, give consistent results for the potential role of either GSTM1 or GSTT1 genotypes in development of the plaques (12 , 14 , 15) .
Several cross-sectional studies have looked for an effect of occupational PAH exposure on different biomarkers, mainly adducts and 1-OH pyrene, taking into account genetic polymorphisms (16, 17, 18, 19, 20, 21, 22) . Moreover, a single case control study has suggested that OR of lung cancer associated to past occupational PAH exposure might be higher among CYP2D6-extensive metabolisers than among poor metabolisers (10) . To our knowledge, no studies have been reported addressing the interaction between occupational lung carcinogens other than asbestos or PAHs and metabolic gene polymorphisms in lung cancer.
The aim of this work was to assess the interaction between occupational lung carcinogens and metabolic gene polymorphisms in a pooled analysis of studies on lung cancer. However, since asbestos was the only occupational carcinogen assessed jointly in the five case control studies, the pooled analysis was restricted to this agent. Mechanisms of carcinogenicity of asbestos have been reviewed recently (23) . There is increasing evidence that generation of reactive free radicals is a key factor underlying cytotoxic and cell-activation responses. These radicals may be generated through redox reactions catalyzed by metals on the surface of the fibers (24) . Radicals may also be generated after the phagocytosis of fibers by inflammatory cells (25) .
The role of GSTM1 in the conjugation of ROS leads to the hypothesis of an interaction between GSTM1 and asbestos. The work presented here examined whether asbestos and GSTM1 genotype are independent risk factors of lung cancer or act synergistically in asbestos carcinogenicity.
| Materials and Methods |
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A hospital-based case control study was carried out between 1988 and 1992 in Caucasians in France (8) . Incident cases (150) were included in the study. Controls were patients without a malignant disease. Only regular smokers were included in the study. Detailed information on lifetime occupational history was collected. Occupational exposure to asbestos was assessed from specific questionnaires according to jobs known to entail carcinogen exposure.
An additional hospital-based case control study was carried out among men in France during 19891992 (27) . Cases were incident primary lung cancer patients (n = 310), with a histologically confirmed diagnosis. Patients with lung diseases or cancer were excluded from the controls (n = 302). Cases and controls were Caucasians, born in France, and of native French parents. Detailed information on lifetime occupational history was collected. Asbestos exposure was derived from an evaluation of all jobs held by the subjects by a panel of industrial hygienists trained in asbestos exposure.
A case series from Finland included 227 lung cancer patients (28 , 29) . Occupational history was obtained from personal interviews and a standardized questionnaire filled out by the occupational hygienist interviewer. The probability of past occupational exposure to asbestos was evaluated by the same hygienist on the basis of the occupational history.
All studies analyzed blood samples by PCR methodology to assess GSTM1 and GSTT1 genotypes. Details on the assays used are provided in the respective publications.
The first step of this analysis consisted of calculating for each study the OR of lung cancer for exposure to asbestos, GSTM1 and GSTT1 genotypes, and their combinations. ORs were calculated from unconditional logistic regression modeling, after adjustment for age, gender, and pack-years of tobacco smoking divided in four classes (<4 pack-years 527, 2845, and >45). Next, the heterogeneity of the ORs was estimated according to Greenland (30)
. At disposal of at least three independent results, and in case of evidence of lack of heterogeneity (P
0.10), a pooled OR was calculated based on a fixed effects model. The interaction between asbestos exposure and genotype was assessed as departure from the hypothesis of an independent effect of each agent and may be written as follows: OR interaction = ORga/(ORg x ORa), where ORga is the OR of lung cancer related to the joint effect of asbestos and genotype, ORg is the OR of lung cancer associated to genotype only, and ORa is the OR of lung cancer related to asbestos exposure only. In addition, we analyzed the series of cases from case control studies together with the study based on cases only (31)
. After stratification of cases on the basis of the asbestos exposure and genotype, and providing that these factors are unrelated in the population, the POR is related to the ORs for asbestos exposure and genotype according to the following formula: POR = ORge/(ORg x ORe) and is therefore equal to the OR of interaction derived in a case control approach. The POR was calculated by unconditional logistic regression after adjustment for age, gender, and tobacco smoking. In order to pool the PORs of the case-only analysis, we followed the same rules described above for the pooling of the ORs derived from the case control studies.
All statistical analyses were performed on a RS6000 IBM (UNIX system), using the SAS Version 6.12 (Cary, NC).
| RESULTS |
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All studies showed an independent effect of each risk factor on lung cancer, as displayed by nonsignificant interaction ORs. Results were highly homogenous (P = 0.89). On the whole population included in the pooled analysis, 53 controls and 54 cases exhibited GSTM1-null genotype and had been exposed to asbestos; the pooled OR of interaction was 1.1 (95% CI 0.62.1).
In the case-only approach, a total of 869 lung cancer patients was included. The prevalence of both asbestos exposure and GSTM1-null genotype was significantly different between studies (P < 0.001 for both). We did not observe any relation between asbestos exposure and GSTM1-null genotype among controls (P = 0.4). The study-specific PORs (i.e., the ORs for asbestos exposure and genetic polymorphism and equal to the OR of interaction derived in a case control approach) are reported in Table 4
. The P value for heterogeneity was 0.48, and we obtained a pooled POR of 1.2 (0.91.8). Given the number of cases, the prevalence of GSTM1-null genotypes, and the prevalence of exposure to asbestos, this study had an 80% statistical power to detect a POR of 1.56.
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| Discussion |
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Our meta-analysis was based on four case control studies and one case series, involving different populations. Particularly, the frequency of exposure to asbestos was higher in the case series than in the case control studies. On the contrary, one of the case control studies had a low frequency of asbestos exposure (27) . This was mainly attributable to the fact that the population included only Caucasian subjects, born in France from French-native parents, resulting in the exclusion of immigrants, which comprise a large proportion of blue collar workers exposed to asbestos in the construction and manufacturing industries. In spite of these differences in the prevalence of exposure to asbestos the meta-analysis based on the four case control studies resulted in a significant main effect of asbestos on lung cancer.
The prevalence of GSTM1-null genotype was in the expected range of 4555% in Caucasians. In the only study including African-Americans, the prevalence was 26%, which is also in accordance with the literature.3 The frequency of the deletion was slightly higher in the cases as compared with the controls, but the difference was nonsignificant. Therefore, our results on the main effect of GSTM1 polymorphism agree with recent reviews suggesting only a minor role of this factor in lung carcinogenesis (7) .
We repeated the analysis of the interaction between polymorphism and asbestos exposure after restricting the data to the lung cancer cases. This approach, which allowed us to include one additional study based on case series, is valid as long as the environmental exposure is randomly distributed, as regards metabolic gene polymorphism (31) . This was the case in our data. This approach, however, also failed to show any interaction between asbestos and GST polymorphism.
Furthermore, the PORs were homogenous according to smoking habits. Therefore, this cofactor does not confound the lack of interaction between asbestos and GSTM1.
The statistical power of this analysis was of 72% to detect a POR of 1.5 of GSTM1-null genotype for asbestos exposure. However, the power was >50% to detect a POR of 1.3. Regarding GSTT1 polymorphism, the statistical power was of 47% to detect an OR of 1.5.
Although the GSEC does not contain all studies on genetic susceptibility, and, therefore, it is likely that other (either published or unpublished) data on GSTM1 and/or T1 polymorphism and asbestos exposure may be available, it is likely that lack of participation in GSEC is nondifferential with respect to case control status, GST polymorphism, and asbestos exposure. For the interaction between GSTM1 genotype and asbestos exposure specifically, the sole study published to date is included in GSEC (11) . Lack of participation would have therefore resulted only in reducing the statistical power. Further possible bias in our analysis could have occurred as exposure assessment, genotype measurements, and case control status may be subjected to misclassification. As regards outcome, all cases were histologically confirmed, and it is therefore very unlikely that errors have occurred in the definition of lung cancer. On the other hand, it is very likely that misclassification in assessment of asbestos exposure has occurred, possibly differential with respect to lung cancer. This may lead to an overestimation of the OR but likely nondifferential with respect to GST genotypes. Hence, assessment of both asbestos exposure and GST genotypes has been made in a totally independent way from each other, as shown by our results among controls, which did not show a relationship between these two risk factors. Finally, errors in GST genotyping might also have occurred, but again, very unlikely differentially from case control status; genotyping in all studies included in the pooled analysis was assessed blindly. The scenario described above leads to bias toward the null in the estimate of the interaction effect. It is of course not possible to quantify sensitivity and specificity of asbestos exposure measurement or of genotyping, but even small amounts of misclassification may substantially decrease the interaction effect (2) .
On the other hand, it is unlikely that uncontrolled confounding occurred since none of the factors possibly associated with asbestos exposure (tobacco smoking and exposure to other occupational carcinogens) is known to be also associated with GST genotypes. The lack of confounding effect of smoking was confirmed by the results of the stratified analysis shown in Table 4
. Finally, the lack of inter-study heterogeneity in the results on GST-asbestos interaction speaks against a major role of bias in our data.
To our knowledge, several studies have examined the relationship between GSTM1 polymorphism and asbestos pulmonary disorders (12, 13, 14, 15 , 32 , 33) . As regards noncancerous pathologies, one study has found a significant excess of GSTM1-null genotypes among patients [OR = 1.8 (1.12.8)] (15) . This excess was also found in another study [OR = 1.5 (0.83.3)] (12) but not in an additional study by Jakobsson (32) . As far as mesothelioma is concerned, a population-based case control study showed a significant excess of GSTM1-null subjects among patients suffering from mesothelioma as compared with controls [OR = 1.8 (1.03.5)], with interaction [OR of 1.6 (0.55.8)] (13) . In a case control study set up in a cohort of workers with high asbestos exposure, the results showed a nonsignificant excess of GSTM1-null genotypes among mesothelioma patients, but the interaction was not evaluated (12) .
In conclusion, the results of our pooled analysis of five studies do not support the hypothesis that either GSTM1 or GSTT1 genotypes modify the risk of lung cancer after asbestos exposure. However, the statistical power being limited, in particular for GSTT1 polymorphism, the results do not allow us to rule out the possibility that an interaction does exist. Nevertheless, we can assume in the case of GSTM1 polymorphism, it is likely that this interaction would be of small magnitude, with OR <1.5. The interpretation of this result suggests that GSTM1 polymorphism is a lung cancer risk factor independently from asbestos-related lung carcinogenesis.
The mechanisms involved in fiber carcinogenesis are also still poorly understood (23) . One in vitro study suggested that mesothelioma cells lacking GSTM1 gene have increased toxicity in response to asbestos (34) . However, the relevance of these results to lung carcinogenesis is unclear.
Although our initial task was to assess the interaction between polymorphism to several metabolic genes and several occupational exposures, the data available in the GSEC database allowed us to address only one agent and two polymorphisms. This was despite the fact that the GSEC database is the largest available collection of data relevant to address the interaction between occupational exposures and metabolic polymorphisms. Additionally, large studies with a careful definition of exposure to occupational carcinogens are therefore needed to properly address the potential interaction between polymorphisms and occupational exposure.
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| Footnotes |
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1 To whom requests for reprints should be addressed, at INSERM U170, 16 Av Paul Vaillant Couturier, 94807 Villejuif, Cedex, France. Phone: 33-01-45-59-50-33; Fax: 33-01-45-59-51-51; E-mail: stucker{at}vjf.inserm.fr ![]()
2 The abbreviations used are: PAH, polycyclic aromatic hydrocarbons; GST, glutathione S-transferase; OR, odds ratio; ROS, reactive oxygen species; GSEC, Genetic Susceptibility to Environmental Carcinogens; POR, prevalence odds ratio; CI, confidence interval. ![]()
Received 12/20/00; revised 7/27/01; accepted 8/24/01.
| References |
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class glutathione transferase and maleylacetoacetate isomerase. Cytogenet. Cell Genet., 83: 109-114, 1998.[Medline]
and µ among asbestos cement workers. Toxicol. Lett. (Amst.), 77: 363-369, 1995.[Medline]
and µ deletion polymorphisms in asbestosis. Am. J. Med., 31: 274-279, 1997.
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