GSTP1 and NQO1 polymorphisms as risk indicators of lung cancer in Lebanon. (c2006)

Abstract

GSTP 1 and NQO 1 gene polymorphisms were considered to be risk indicators of tobacco induced lung cancer. GSTP 1 gene expresses a detoxifying enzyme and its polymorphism leads to a change in the amino acid IIe to Val at position 105 in the amino acid sequence of the enzyme. Thus changing its specificity and activity towards potent carcinogens, like the active benzo(a) pyrene-diolepoxide (BPDE) present in tobacco. NQO1 gene expresses a detoxifying enzyme, it protect cells and DNA from both natural and chemical quinones. NQO 1 gene polymorphism at position 609 in DNA sequence is a C-T transition which leads to a change in enzymatic activity to almost null activity. Both polymorphisms have been characterized by restriction fragment length polymorphism (RFLP). The sampled population comprised 195 individuals from a controlled population at both LAU Beirut and Byblos campuses. All individuals voluntarily gave sputum sample and answered a respiratory health questionnaire. DNA was extracted from each sputum sample and polymerase chain reaction (PCR) and RFLP were performed for each of the genes respectively. Sampled individuals were of two age groups: 107 were under 25 and 88 were over 40. They were equally divided between smokers and nonsmokers. For GSTP 1 the genotypic frequency distribution in the total population was: (IT) 26.15%, (IV) 60.51% and (VV) 13.33%. While for NQO1 the genotypic frequency was (CC) 31.28%, (CT) 55.38%, (TT) 14.87%. In the overall population a higher GSTP 1 (II) genotype frequency was determined in smokers while (IV) and (VV) were more frequent in non-smokers. The higher (II) frequency would suggest a lower risk of lung cancer in smokers. The NQO 1 (CC) genotype frequency was highest in smokers while that of (CT) and (TT) was highest in non-smokers, thus indicating a lower risk in smokers. The stratified analysis according to age and smoking showed unreliable and controversial spectrum of susceptibility between age groups which could be due to decrease of sample size with subgrouping.