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CYP1A1, GSTM1 and GSTT1 polymorphisms and lung cancer: a pooled analysis of gene-gene interactions.
- Source :
- Biomarkers; May/Jun2004, Vol. 9 Issue 3, p298-305, 8p
- Publication Year :
- 2004
-
Abstract
- Gene-environment interactions have been extensively studied in lung cancer. It is likely that several genetic polymorphisms cooperate in increasing the individual risk. Therefore, the study of gene-gene interactions might be important to identify high-susceptibility subgroups. GSEC is an initiative aimed at collecting available data sets on metabolic polymorphisms and the risks of cancer at several sites and performing pooled analyses of the original data. Authors of published papers have provided original data sets. The present paper refers to gene-gene interactions in lung cancer and considers three polymorphisms in three metabolic genes: CYP1A1 , GSTM1 and GSTT1 . The present analyses compare the gene-gene interactions of the CYP1A1*2A , GSTM1 and GSTT1 polymorphisms from studies on lung cancer conducted in Europe and the USA between 1991 and 2000. Only Caucasians have been included. The data set includes 1466 cases and 1488 controls. The only clear-cut association was found with CYP1A1*2A . This association remained unchanged after stratification by polymorphisms in other genes (with an odds ratio [OR] of approximately 2.5), except when interaction with GSTM1 was considered. When the OR for CYP1A1*2A was stratified according to the GSTM1 genotype, the OR was increased only among the subjects who had the null (homozygous deletion) GSTM1 genotype (OR=2.8, 95% CI=0.9-8.4). The odds ratio for the interactive term ( CYP1A1*2A by GSTM1) in logistic regression was 2.7 (95% CI=0.5-15.3). An association between lung cancer and the homozygous CYP1A1*2A genotype is confirmed. An apparent and biologically plausible interaction is suggested between this genotype and GSTM1 . [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 1354750X
- Volume :
- 9
- Issue :
- 3
- Database :
- Complementary Index
- Journal :
- Biomarkers
- Publication Type :
- Academic Journal
- Accession number :
- 15545031
- Full Text :
- https://doi.org/10.1080/13547500400011070