Influence of CYP19A1 polymorphisms on the treatment of breast cancer with aromatase inhibitors : a systematic review and meta-analysis

Abstract

Background: Many clinical trials have shown the efficacy of aromatase inhibitors (AIs) in the management of breast cancer (BC). There is growing evidence that CYP19A1 single-nucleotide polymorphisms (SNPs) are associated with clinical response (CR) and adverse effects (AEs) among BC patients treated with AIs. The aim of this study was to analyze the association between CYP19A1 polymorphisms and AI treatment in BC patients. Methods: A systematic review was performed in MEDLINE, EMBASE, and LILACS. A meta-analysis was conducted to compare the association between CYP19A1 variants and treatment response among BC patients. Results: A total of 12 studies were included in the final analysis. There was significant variation among the populations studied and the SNPs and outcomes investigated. A meta-analysis was only possible for the evaluation of SNP rs4646 vs. the wild-type variant with respect to time to progression (TTP) among metastatic BC patients treated with AI. TTP was significantly increased in patients with the rs4646 variant compared with the wild-type gene (hazard ratio (HR) = 0.51 [95 % confidence interval (CI), 0.33–0.78], P = 0.002). Seven studies analyzed the association between AEs with different polymorphisms of CYP19A1. Although there was a statistically significant association with musculoskeletal adverse events (rs934635, rs60271534, rs700518rs, and haplotype M_3_5) and with vasomotor symptoms (rs934635, rs1694189, rs7176005, and haplotype M_5_3) in individual studies, similar associations were not observed in further studies. No statistically significant association between musculoskeletal AEs and SNPs rs4646, rs10046, rs727479, and rs1062033 was found. Conclusions: These findings suggest that the presence of the rs4646 variant may be a predictive factor of the benefit of AI treatment for BC. The effects of CYP19A1 polymorphisms on clinical outcomes were most often detected in individual studies, suggesting that longer-term studies will better clarify these associations. Additional studies are needed to clarify the predictive value of other SNPs and whether CYP19A1 genotyping should be used to guide AI treatment.