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.

Project description:BACKGROUND: For over two decades, the Nottingham Prognostic Index (NPI) has been used in the United Kingdom to calculate risk scores and inform management about breast cancer patients. It is derived using just three clinical variables - nodal involvement, tumour size and grade. New scientific methods now make cost-effective measurement of many biological characteristics of tumour tissue from breast cancer biopsy samples possible. However, the number of potential explanatory variables to be considered presents a statistical challenge. The aim of this study was to investigate whether in ER+ tamoxifen-treated breast cancer patients, biological variables can add value to NPI predictors, to provide improved prognostic stratification in terms of overall recurrence-free survival (RFS) and also in terms of remaining recurrence free while on tamoxifen treatment (RFoT). A particular goal was to enable the discrimination of patients with a very low risk of recurrence. METHODS: Tissue samples of 401 cases were analysed by microarray technology, providing biomarker data for 72 variables in total, from AKT, BAD, HER, MTOR, PgR, MAPK and RAS families. Only biomarkers screened as potentially informative (i.e., exhibiting univariate association with recurrence) were offered to the multivariate model. The multiple imputation method was used to deal with missing values, and bootstrap sampling was used to assess internal validity and refine the model. RESULTS: Neither the RFS nor RFoT models derived included Grade, but both had better predictive and discrimination ability than NPI. A slight difference was observed between models in terms of biomarkers included, and, in particular, the RFoT model alone included HER2. The estimated 7-year RFS rates in the lowest-risk groups by RFS and RFoT models were 95 and 97%, respectively, whereas the corresponding rate for the lowest-risk group of NPI was 89%. CONCLUSION: The findings demonstrate considerable potential for improved prognostic modelling by incorporation of biological variables into risk prediction. In particular, the ability to identify a low-risk group with minimal risk of recurrence is likely to have clinical appeal. With larger data sets and longer follow-up, this modelling approach has the potential to enhance an understanding of the interplay of biological characteristics, treatment and cancer recurrence.

Project description:IntroductionTamoxifen is one of the most effective adjuvant breast cancer therapies available. Its metabolism involves the phase I enzyme, cytochrome P4502D6 (CYP2D6), encoded by the highly polymorphic CYP2D6 gene. CYP2D6 variants resulting in poor metabolism of tamoxifen are hypothesised to reduce its efficacy. An FDA-approved pre-treatment CYP2D6 gene testing assay is available. However, evidence from published studies evaluating CYP2D6 variants as predictive factors of tamoxifen efficacy and clinical outcome are conflicting, querying the clinical utility of CYP2D6 testing. We investigated the association of CYP2D6 variants with breast cancer specific survival (BCSS) in breast cancer patients receiving tamoxifen.MethodsThis was a population based case-cohort study. We genotyped known functional variants (n = 7; minor allele frequency (MAF) > 0.01) and single nucleotide polymorphisms (SNPs) (n = 5; MAF > 0.05) tagging all known common variants (tagSNPs), in CYP2D6 in 6640 DNA samples from patients with invasive breast cancer from SEARCH (Studies of Epidemiology and Risk factors in Cancer Heredity); 3155 cases had received tamoxifen therapy. There were 312 deaths from breast cancer, in the tamoxifen treated patients, with over 18000 years of cumulative follow-up. The association between genotype and BCSS was evaluated using Cox proportional hazards regression analysis.ResultsIn tamoxifen treated patients, there was weak evidence that the poor-metaboliser variant, CYP2D6*6 (MAF = 0.01), was associated with decreased BCSS (P = 0.02; HR = 1.95; 95% CI = 1.12-3.40). No other variants, including CYP2D6*4 (MAF = 0.20), previously reported to be associated with poorer clinical outcomes, were associated with differences in BCSS, in either the tamoxifen or non-tamoxifen groups.ConclusionsCYP2D6*6 may affect BCSS in tamoxifen-treated patients. However, the absence of an association with survival in more frequent variants, including CYP2D6*4, questions the validity of the reported association between CYP2D6 genotype and treatment response in breast cancer. Until larger, prospective studies confirming any associations are available, routine CYP2D6 genetic testing should not be used in the clinical setting.

Dataset Information

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

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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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