Dataset Information

Non-CYP2D6 Variants Selected by a GWAS Improve the Prediction of Impaired Tamoxifen Metabolism in Patients with Breast Cancer.

ABSTRACT: A certain minimum plasma concentration of (Z)-endoxifen is presumably required for breast cancer patients to benefit from tamoxifen therapy. In this study, we searched for DNA variants that could aid in the prediction of risk for insufficient (Z)-endoxifen exposure. A metabolic ratio (MR) corresponding to the (Z)-endoxifen efficacy threshold level was adopted as a cutoff value for a genome-wide association study comprised of 287 breast cancer patients. Multivariate regression was used to preselect variables exhibiting an independent impact on the MR and develop models to predict below-threshold MR values. In total, 15 single-nucleotide polymorphisms (SNPs) were significantly associated with below-threshold MR values. The strongest association was with rs8138080 (WBP2NL). Two alternative models for MR prediction were developed. The predictive accuracy of Model 1, including rs7245, rs6950784, rs1320308, and the CYP2D6 genotype, was considerably higher than that of the CYP2D6 genotype alone (AUC 0.879 vs 0.758). Model 2, which was developed using the same three SNPs as for Model 1 plus rs8138080, appeared as an interesting alternative to the full CYP2D6 genotype testing. In conclusion, the four novel SNPs, tested alone or in combination with the CYP2D6 genotype, improved the prediction of impaired tamoxifen-to-endoxifen metabolism, potentially allowing for treatment optimization.

SUBMITTER: Hennig EE

PROVIDER: S-EPMC6722498 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

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Non-CYP2D6 Variants Selected by a GWAS Improve the Prediction of Impaired Tamoxifen Metabolism in Patients with Breast Cancer.

Hennig Ewa E EE Piątkowska Magdalena M Goryca Krzysztof K Pośpiech Ewelina E Paziewska Agnieszka A Karczmarski Jakub J Kluska Anna A Brewczyńska Elżbieta E Ostrowski Jerzy J

Journal of clinical medicine 20190724 8

A certain minimum plasma concentration of (Z)-endoxifen is presumably required for breast cancer patients to benefit from tamoxifen therapy. In this study, we searched for DNA variants that could aid in the prediction of risk for insufficient (Z)-endoxifen exposure. A metabolic ratio (MR) corresponding to the (Z)-endoxifen efficacy threshold level was adopted as a cutoff value for a genome-wide association study comprised of 287 breast cancer patients. Multivariate regressio ...[more]

PMID: 31344832

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Project description:Background: Current reports suggest that a certain minimum plasma concentration of (Z)-endoxifen is required for breast cancer patient to benefit from tamoxifen therapy. A reliable prediction of which patients are at risk for insufficient exposure to (Z)-endoxifen would be relevant for optimizing treatment, e.g. by adjusting the dose, from the very beginning. The objective of this study was to search for new DNA variants that could be helpful in the preemptive prediction of impaired tamoxifen to endoxifen metabolism. Methods: The molecular ratio (MR) was defined as (Z)-endoxifen plasma concentration divided by the sum of concentrations of tamoxifen and other measured metabolites. The MR of 0.0146, previously delineated as corresponding to (Z)-endoxifen 6 ng/ml efficacy threshold level, was adopted as a cut-off value in a genome-wide association study (GWAS) comprising 287 breast cancer patients receiving tamoxifen 20 mg daily. Multivariate binary logistic regression was used for the pre-selection of variables that showed independent impact on MR and to develop models predictive for MR value below the threshold. Results: In total, 13 GWAS-selected single nucleotide polymorphisms (SNPs) located outside the CYP2D6 gene and two known CYP2D6 variants were significantly associated with the MR value below 0.0146. The strongest association was observed for rs8138080 in WBP2NL (p = 1.78 x 10-15). The minor allele of six SNPs was associated with a decreased risk of impaired tamoxifen metabolism. CYP2D6 genotype was found by Nagelkerke pseudo-R2 to explain 42.7% of a total variation observed in MR, while rs8138080 alone explained 33.7% of this variability. Two alternative models for MR prediction have been developed. The prediction accuracy of Model 1, including rs7245, rs6950784 and rs1320308 in addition to CYP2D6 genotype, was considerably higher than predictive performance of CYP2D6 genotype alone (AUC increase from 0.758 to 0.879). The AUC of 0.830 achieved for the Model 2, developed with the same three SNPs as in Model 1 and rs8138080 instead of CYP2D6 genotype, makes it an interesting, simplified alternative to the costly and time-consuming testing of full CYP2D6 genotype. Conclusions: The four novel SNPs, tested alone or in addition to CYP2D6 genotype, improved the prediction of impaired tamoxifen to endoxifen metabolism, allowing for adjustments in dosing regimen before the treatment begins.

Dataset Information

Non-CYP2D6 Variants Selected by a GWAS Improve the Prediction of Impaired Tamoxifen Metabolism in Patients with Breast Cancer.

Publications

Non-<i>CYP2D6</i> Variants Selected by a GWAS Improve the Prediction of Impaired Tamoxifen Metabolism in Patients with Breast Cancer.

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