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Background <p>The clinical utility of <i>CYP2D6</i> genotyping in predicting tamoxifen outcomes remains controversial, partly due to incomplete allele coverage and limited assessment of copy number variation (CNV). We aimed to expand <i>CYP2D6</i> genetic profiling in Syrian breast cancer patients and to reassess phenotype classification and its clinical relevance.</p> Methods <p>In this retrospective cohort of estrogen receptor–positive breast cancer patients treated with adjuvant tamoxifen, <i>CYP2D6</i> genotyping was performed using a test strip–based assay complemented by semi-quantitative PCR for CNV detection. Selected results were validated by next-generation sequencing (NGS). Diplotypes were translated into activity scores to assign metabolizer phenotypes. Disease-free survival (DFS) was evaluated using time-to-event analyses.</p> Results <p>Expanded <i>CYP2D6</i> profiling, incorporating broader allele coverage and CNV analysis, led to metabolizer phenotype reclassification in 19% of patients. NGS identified primer-binding region variants responsible for allele drop-out in conventional assays. No significant association between <i>CYP2D6</i> phenotype and DFS was observed in the overall cohort. However, exploratory stage-specific analyses suggested shorter DFS among patients with reduced CYP2D6 activity in Stage II disease (HR = 3.59; 95% CI 2.34–67.48), although estimates were imprecise due to small subgroup size.</p> Conclusions <p>Comprehensive <i>CYP2D6</i> profiling improves phenotype assignment and highlights methodological pitfalls that may contribute to inconsistencies in pharmacogenetic studies. While no definitive association with clinical outcomes was observed in the overall cohort, these findings underscore the importance of analytically robust genotyping strategies and warrant validation in larger, prospectively designed cohorts, and highlight the importance of comprehensive genotyping strategies in resolving inconsistencies across pharmacogenetic studies.</p>

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Comprehensive CYP2D6 genotyping improves phenotype classification and highlights methodological pitfalls in tamoxifen-treated breast cancer

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月1日

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  • Linda Alkebbeh,
  • Anne Berndt,
  • Christian Oberkanins,
  • Mazen Kenj,
  • Gernot Kriegshäuser,
  • Lama A. Youssef

摘要

Background

The clinical utility of CYP2D6 genotyping in predicting tamoxifen outcomes remains controversial, partly due to incomplete allele coverage and limited assessment of copy number variation (CNV). We aimed to expand CYP2D6 genetic profiling in Syrian breast cancer patients and to reassess phenotype classification and its clinical relevance.

Methods

In this retrospective cohort of estrogen receptor–positive breast cancer patients treated with adjuvant tamoxifen, CYP2D6 genotyping was performed using a test strip–based assay complemented by semi-quantitative PCR for CNV detection. Selected results were validated by next-generation sequencing (NGS). Diplotypes were translated into activity scores to assign metabolizer phenotypes. Disease-free survival (DFS) was evaluated using time-to-event analyses.

Results

Expanded CYP2D6 profiling, incorporating broader allele coverage and CNV analysis, led to metabolizer phenotype reclassification in 19% of patients. NGS identified primer-binding region variants responsible for allele drop-out in conventional assays. No significant association between CYP2D6 phenotype and DFS was observed in the overall cohort. However, exploratory stage-specific analyses suggested shorter DFS among patients with reduced CYP2D6 activity in Stage II disease (HR = 3.59; 95% CI 2.34–67.48), although estimates were imprecise due to small subgroup size.

Conclusions

Comprehensive CYP2D6 profiling improves phenotype assignment and highlights methodological pitfalls that may contribute to inconsistencies in pharmacogenetic studies. While no definitive association with clinical outcomes was observed in the overall cohort, these findings underscore the importance of analytically robust genotyping strategies and warrant validation in larger, prospectively designed cohorts, and highlight the importance of comprehensive genotyping strategies in resolving inconsistencies across pharmacogenetic studies.