Association of nucleotide excision repair pathway gene polymorphisms with gastric cancer and atrophic gastritis risks

Polymorphisms of NER genes could change NER ability, thereby altering individual susceptibility to GC. We systematically analyzed 39 SNPs of 8 key genes of NER pathway in 2686 subjects including 898 gastric cancer (GC), 851 atrophic gastritis (AG) and 937 controls (CON) in northern Chinese. SNP genotyping were performed using Sequenom MassARRAY platform. The results demonstrated that DDB2 rs830083 GG genotype was significantly associated with increased GC risk compared with wild-type CC (OR=2.32, P= 6.62 × 10-9); XPC rs2607775 CG genotype conferred a 1.73 increased odds of GC risk than non-cancer subjects compared with wild-type CC (OR=1.73, P= 3.04 × 10-4). The combined detection of these two polymorphisms demonstrated even higher GC risk (OR=3.05). Haplotype analysis suggested that DDB2 rs2029298-rs326222-rs3781619-rs830083 GTAG haplotype was significantly associated with disease risk in each step of CON→AG→GC development (AG vs. CON: OR=2.88, P= 7.51 × 10-7; GC vs. AG: OR=2.90, P=5.68 × 10-15; GC vs. CON: OR=8.42, P=2.22 × 10-15); DDB2 GTAC haplotype was associated with reduced risk of GC compared with CON (OR=0.63, P= 8.31 × 10-12). XPC rs1870134-rs2228000-rs2228001-rs2470352-rs2607775 GCAAG haplotype conferred increased risk of GC compared with AG (OR=1.88, P= 6.98 × 10-4). XPA rs2808668 and drinking, DDB2 rs326222, rs3781619, rs830083 and smoking demonstrated significant interactions in AG; XPC rs2607775 had significant interaction with smoking in GC. In conclusion, NER pathway polymorphisms especially in "damage incision" step were significantly associated with GC risk and had interactions with environment factors. The detection of NER pathway polymorphisms such as DDB2 and XPC might be applied in the prediction of GC risk and personalized prevention in the future. NER pathway polymorphisms especially in "damage incision" step were significantly associated with GC risk and had interactions with environment factors, which might be applied in the prediction of GC risk and personalized prevention in the future.