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

James N. Ingle, Krishna R. Kalari, Poulami Barman, Lois E. Shepherd, Matthew J. Ellis, Paul E. Goss, Aman U. Buzdar, Mark E. Robson, Junmei Cairns, Erin E. Carlson, Abraham Eyman Casey, Tanya L. Hoskin, Barbara A. Goodnature, Tufia C. Haddad, Matthew P. Goetz, Richard M. Weinshilboum, Liewei Wang

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish (US)
Pages (from-to)1-9
Number of pages9
JournalPharmacogenetics and genomics
DOIs
StateAccepted/In press - 2020

Keywords

  • estrogen suppression
  • predictive models
  • single-nucleotide polymorphisms

ASJC Scopus subject areas

  • Molecular Medicine
  • Molecular Biology
  • Genetics
  • Genetics(clinical)

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