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


Authors: Ingle, J. N.; Kalari, K. R.; Barman, P.; Shepherd, L. E.; Ellis, M. J.; Goss, P. E.; Buzdar, A. U.; Robson, M. E.; Cairns, J.; Carlson, E. E.; Casey, A. E.; Hoskin, T. L.; Goodnature, B. A.; Haddad, T. C.; Goetz, M. P.; Weinshilboum, R. M.; Wang, L.
Article Title: Single-nucleotide polymorphism biomarkers of adjuvant anastrozole-induced estrogen suppression in early breast cancer
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.
Keywords: exemestane; aromatase inhibitors; predictive models; regression; selection; postmenopausal women; single-nucleotide polymorphisms; estrogen suppression
Journal Title: Pharmacogenetics and Genomics
Volume: 31
Issue: 1
ISSN: 1744-6872
Publisher: Lippincott Williams & Wilkins  
Date Published: 2021-01-01
Start Page: 1
End Page: 9
Language: English
ACCESSION: WOS:000588139200001
DOI: 10.1097/fpc.0000000000000415
PROVIDER: Clarivate Analytics Web of Science
PROVIDER: wos
PMCID: PMC7655717
PUBMED: 32649577
Notes: Article -- Source: Wos
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  1. Mark E Robson
    677 Robson