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早期乳腺癌中辅助阿那曲唑诱导雌激素抑制的单核苷酸多态性生物标志物。

Single-nucleotide polymorphism biomarkers of adjuvant anastrozole-induced estrogen suppression in early breast cancer.

机构信息

Division of Medical Oncology, Department of Oncology.

Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota.

出版信息

Pharmacogenet Genomics. 2021 Jan;31(1):1-9. doi: 10.1097/FPC.0000000000000415.

Abstract

OBJECTIVES

Based on our previous findings that postmenopausal women with estrone (E1) and estradiol (E2) concentrations at or above 1.3 pg/ml and 0.5 pg/ml, respectively, after 6 months of adjuvant anastrozole therapy had a three-fold risk of recurrence, we aimed to identify a single-nucleotide polymorphism (SNP)-based model that would predict elevated E1 and E2 and then validate it in an independent dataset.

PATIENTS AND METHODS

The test set consisted of 322 women from the M3 study and the validation set consisted of 152 patients from MA.27. All patients were treated with adjuvant anastrozole, had on-anastrozole E1 and E2 concentrations and genome-wide genotyping.

RESULTS

SNPs were identified from the M3 genome-wide association study. The best model to predict the E1-E2 phenotype with high balanced accuracy was a support vector machine model using clinical factors plus 46 SNPs. We did not have an independent cohort that is similar to the M3 study with clinical, E1-E2 phenotypes and genotype data to test our model. Hence, we chose a nested matched case-control cohort (MA.27 study) for testing. Our E1-E2 model was not validated but we found the MA.27 validation cohort was both clinically and genomically different.

CONCLUSIONS

We identified a SNP-based model that had excellent performance characteristics for predicting the phenotype of elevated E1 and E2 in women treated with anastrozole. This model was not validated in an independent dataset but that dataset was clinically and genomically substantially different. The model will need validation in a prospective study.

摘要

目的

基于我们之前的研究发现,接受辅助阿那曲唑治疗 6 个月后雌酮(E1)和雌二醇(E2)浓度分别达到或高于 1.3pg/ml 和 0.5pg/ml 的绝经后妇女复发风险增加三倍。因此,我们旨在确定一种基于单核苷酸多态性(SNP)的模型,该模型可预测 E1 和 E2 升高,并在独立数据集进行验证。

患者和方法

测试集由 M3 研究中的 322 名女性组成,验证集由 MA.27 中的 152 名患者组成。所有患者均接受辅助阿那曲唑治疗,有阿那曲唑治疗期间的 E1 和 E2 浓度和全基因组基因分型。

结果

从 M3 全基因组关联研究中鉴定出了 SNPs。用于预测 E1-E2 表型的最佳模型是使用临床因素加 46 个 SNPs 的支持向量机模型,其具有较高的平衡准确性。我们没有具有类似 M3 研究的临床、E1-E2 表型和基因型数据的独立队列来测试我们的模型。因此,我们选择嵌套匹配病例对照队列(MA.27 研究)进行测试。我们的 E1-E2 模型未得到验证,但我们发现 MA.27 验证队列在临床和基因组上均存在差异。

结论

我们确定了一种基于 SNP 的模型,该模型对预测接受阿那曲唑治疗的女性 E1 和 E2 升高表型具有出色的性能特征。该模型未在独立数据集进行验证,但该数据集在临床和基因组上存在明显差异。该模型需要在前瞻性研究中进行验证。

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