Nucleotide excision repair polymorphisms and survival outcome for patients with metastatic breast cancer

Abstract

Inter-individual variations in treatment efficacy may be influenced by polymorphisms in DNA repair genes. We investigated the association of 3 functional polymorphisms in the nucleotide excision repair (NER) pathway with survival outcome of 95 patients with metastatic breast cancer (MBC) treated with DNA-damaging chemotherapy. ERCC1 8092 C/A, ERCC2 Asp312Asn and ERCC2 Lys751Gln were determined using Taqman-based genotyping assays. Genotype associations with breast cancer-specific survival (BCSS) and progression-free survival (PFS) were evaluated using Kaplan-Meier estimates and hazard ratios calculated using Cox regression analysis. Tests for trend were conducted by calculating P-values for the HR coefficient in proportional hazards regression models. ERCC2 Lys751Gln was significantly associated with BCSS (median: 24.8 months for AA/AC combined and 14.2 months for CC, HR: 1.9 (95% CI 1.06-3.26)). Median BCSS decreased with increasing number of designated adverse genotypes for the 3 polymorphisms (P (trend) = 0.003). Risk estimates for PFS were nonsignificantly elevated and were significantly elevated for BCSS for patients with 2 (HR = 2.21, 95% CI: 1.04-4.72) or 3 (HR = 6.67, 95% CI: 2.19-20.29) adverse genotypes. In treatment subgroup analysis, risk estimates for BCSS were significantly elevated for patients with 3 adverse genotypes treated with cyclophosphamide, mitoxantrone and vinblastine (HR: 11.9, 95% CI 1.77-79.51) and P (trend) = 0.02 for increasing number of adverse genotypes. Risk of progression was significantly increased for patients with 1 adverse genotype treated with cyclophosphamide, mitoxantrone and carboplatin (HR: 3.5, 95% CI 1.19-10.6) and P (trend) = 0.02 for increasing number of adverse genotypes. Polymorphisms in NER pathway may impact survival outcome for patients with MBC following treatment with DNA-damaging chemotherapy. These results provide support for a polygenic pathway approach for assessing the prognostic and predictive potential of polymorphisms in treatment outcome.