METHODS: We analyzed GWAS data derived from ECOG-5103, first identifying SNPs that were most strongly associated with CIPN using Fisher\'s ratio (FR). We then ranked ordered those SNPs which discriminated CIPN-positive (CIPN +) from CIPN-negative phenotypes based on their discriminatory power and developed the cluster of SNPs which provided the highest predictive accuracy using leave-one-out cross-validation (LOOCV).
RESULTS: Using aggregated genotype data obtained from the previously reported ECOG-5103 clinical trial (in which two different arrays were used, HumanOmniExpress (727,227 SNPs) and HumanOmni1-Quad1 (1,131,857 SNPs)), we identified a 267 SNP cluster which was associated with a CIPN + phenotype with an accuracy of 96.1%.
CONCLUSIONS: A cluster of SNPs was identified which prospectively discriminated patients most likely to develop symptomatic CIPN following taxane exposure as part of a breast cancer chemotherapy regimen. Validation using an independent patient cohort should be performed.
方法:我们分析了来自ECOG-5103的GWAS数据,首先使用Fisher比率(FR)鉴定了与CIPN最密切相关的SNP。然后,我们根据区分能力对那些区分CIPN阳性(CIPN)和CIPN阴性表型的SNP进行排序,并使用留一交叉验证(LOOCV)开发了提供最高预测准确性的SNP簇。
结果:使用从先前报道的ECOG-5103临床试验中获得的汇总基因型数据(其中使用了两种不同的阵列,HumanOmniExpress(727,227SNPs)和HumanOmni1-Quad1(1,131,857SNPs)),我们鉴定出一个267个SNP簇,该簇与aCIPN+表型相关,准确率为96.1%.
结论:确定了一组SNP,这些SNP前瞻性地区分了紫杉烷暴露作为乳腺癌化疗方案的一部分后最有可能发生症状CIPN的患者。应使用独立的患者队列进行验证。