Gene polymorphisms of biotransforming enzymes (GSTs) and their association with lung cancer in the Slovakian population

• Published in: European journal of medical research 2009-12, Vol.14 Suppl 4 (Suppl 4), p.275-279
• Main Authors: Matakova, T, Sivonova, M, Halasova, E, Mistuna, D, Dzian, A, Berzinec, P, Letkova, L, Dobrota, D
• Format: Article
• Language: English
• Subjects: Analysis; Cancer genetics; Cancer research; Epidemiology; Genes; Genetic aspects; Genetic polymorphisms; Genotype; Glutathione S-Transferase pi - genetics; glutathione S-transferase T1, M1, and P1; Glutathione transferase; Glutathione Transferase - genetics; Health aspects; Humans; Logistic Models; Lung cancer; Lung Neoplasms - genetics; polymorphism; Polymorphism, Genetic; Risk factors; Slovakia
• ISSN: 0949-2321; 2047-783X; 2047-783X
• DOI: 10.1186/2047-783X-14-S4-275

The aim of present study was to present the results of a case-control study focused on genetic polymorphisms of selected Phase II metabolizing enzymes (GSTM1, T1, and P1) and to investigate the association of these polymorphisms with lung cancer risk in the Slovakian population. The study encompassed 160 lung cancer cases and 220 controls. DNA was extracted from peripheral blood leukocytes, and the polymorphisms of GSTM1, GSTT1 and GSTP1 enzymes were determined by PCR-based methods. We determined the genotype distribution of all these genes and their combinations. The association between specific genotypes and the development of lung cancer were examined using logistic regression analysis to calculate odds ratios (OR) and 95% confidence intervals (CI). We found that the GSTM1 null genotype (OR=1.6; 95% CI=1.03-2.4; chi(2)=4.08, and P=0.04) was associated with elevated risk. A significant correlation also was found for the combined genotypes of GSTM1 null and GSTP1 Ile/Val and Val/Val (OR=2.01; 95% CI=1.1-6.1; chi(2)=3.6, and P=0.02) and GSTM1 null and GSTT1 positive (OR=2.00; 95% CI=1.2-3.2; chi(2)=7.3, and P=0.006). We conclude that the genotype of metabolizing enzymes and allelic combinations underscore the risk for lung cancer. Individual risk assessment may be further improved by increasing the number of polymorphisms studied and combining them with the traditional epidemiological risk factor.