Polymorphisms of Glutathione-S-Transferase and Arylamine N-Acetyltransferase Enzymes and Susceptibility to Colorectal Cancer

Abstract

Background: Glutathione-S-transferases (GSTs) and N-acetyltransferases (NATs) are involved in the metabolism of a wide range of carcinogenic chemicals. Allelic polymorphism of these enzymes is associated with variations in enzyme activity, hence it may affect the concentration of activated carcinogenic chemicals in the body. Previous studies suggest a possible cancer risk-modifying effect of these allelic polymorphisms, but the results are still controversial. We evaluated the effect of GSTM1, GSTT1, GSTP1, NAT1 and NAT2 enzymes on individual susceptibility to colorectal cancer, with particular attention to possible interactions between the studied genotypes. Materials and Methods: Five hundred colorectal cancer patients and 500 matched cancer-free controls were included in the study. The allelic polymorphisms of GSTM1, GSTT1 and GSTP1, NAT1 and NAT2 enzymes were determined by PCR-based methods, from peripheral blood leukocytes, and allelic distributions were compared between colorectal cancer patients and controls. Results: The GSTM1 0 allele (OR: 1.48, 95% CI: 1.15-1.92) and rapid acetylator genotypes of NAT2 (OR: 1.52, 95% CI: 1.17-1.98) were associated with an elevated risk. No statistically significant correlation between NAT1, GSTT1, GSTP1 genotypes and colorectal cancer was found. Remarkably increased risk was associated with the GSTM1 0 allele - NAT2 rapid acetylator genotype combination (OR: 2.39, 95% CI: 1.75-3.26) and with the GSTM1 0 allele - NAT2 and NAT1 rapid acetylator triple combination (OR: 3.28, 95% CI: 2.06-5.23). Carrying 4 or 5 putative “high-risk” alleles substantially increased the risk of colorectal cancer (OR: 3.69, 95% CI: 2.33-5.86). Conclusion: The genotype of certain metabolizing enzymes affects the risk for colorectal cancer. This effect is particularly important when certain allelic combinations are studied. In the near future, individual level risk assessment may be reached by further increasing the number of studied polymorphisms, combining them with traditional epidemiological risk factors.