Xenobiotic metabolizing gene polymorphisms and their influence on ovarian cancer susceptibility: A Case-Control and an in silico approach
1Citations
Identifying the impact of low-penetrance genes in ovarian cancer (OC) presents a significant challenge. Polymorphisms in xenobiotic metabolism genes (XMGs) have influenced carcinogen detoxification, cancer susceptibility, and treatment response in many cancers, yet their role in OC remains fragmentary. The present study examined the genetic variants in crucial XMGs such as CYP2D6, NQO1, GSTT1, GSTM1, and GSTP1 in 460 subjects (209 OC patients and 251 controls). PCR-RFLP (CYP2D6, NQO1, and GST-P1) and multiplex-PCR (GSTT1 and GSTM1) were used for genotyping. Logistic regression was employed to evaluate the association of genotypes with OC risk. MDR analysis was used to detect SNP-SNP interactions. Various computational tools were used to assess the impact of variants on protein function, structure, and stability. The results revealed that the intermediate metabolizers (GA) of CYP2D6*4 variant conferred a 2-fold elevated OC risk (OR 2.01; 95% CI 1.35-3.01; p = 0.0023). Similarly, for NQO1*2 (P187S) variant, the mutant TT genotype showed a significant association with increased OC risk (OR 2.35; 95% CI 1.25-4.42; p = 0.023). No association of GSTT1, GSTM1, and GSTP1 variants was observed in the present study. However, combinatorial gene analysis using MDR indicated that the AG (GSTP1), TT (NQO1), and GA (CYP2D6) genotypes conferred 18.4-fold increased OC risk (OR 18.42; 95% CI 2.18-155.21; p = 0.007). In silico analyses predicted the functional impact of two missense variants (rs1800566 and rs1695) and the effect on splicing for the CYP2D6*4 splice variant. The present study highlights the association of CYP2D6, GSTP1, and NQO1 variants with elevated risk of OC in South Indian women.