Does Next Generation Sequencing ( <scp>NGS</scp> )‐Based <scp> <i>CYP2D6</i> </scp> Sequencing Improve Genotype–Phenotype Concordance in Tamoxifen‐Treated Patients?

CYP2D6 metabolizes about 20% of commonly used drugs, including tamoxifen, a major hormone therapy for breast cancer. Although the relationship between tamoxifen pharmacokinetics and CYP2D6 genotype has been demonstrated, residual variability in drug exposure remains unexplained. Given the high genetic polymorphism of CYP2D6, including copy number variations and hybrid genes, targeted genotyping may fail to capture rare or complex alleles. To explore this limitation, 68 individuals from a cohort of tamoxifen-treated patients were selected based on discordance between CYP2D6 genotype determined by a targeted approach and phenotype assessed from pharmacokinetic data, and were analyzed using full-gene next-generation sequencing with in-house panel and bioinformatics pipeline. Full CYP2D6 gene sequencing refined genotypes in 41% of patients, and changed metabolizer status in 19%, mainly by detecting common alleles missed by the initial targeted assay. After removing these sources of discrepancy, sequencing improved diplotype assignment in 23.5% and metabolizer status classification in 7.4% of patients, largely driven by the detection of structural variants, with an additional contribution from the rare nonfunctional CYP2D6*62 allele, identified in one patient. In addition, several rare variants or variants of uncertain significance (including CYP2D6*22, *23, *28, p.Ala165Gly. and p.Pro264Thr) were identified and further evaluated using adapted in silico prediction strategies, compared with patients' phenotypes and published in vitro data. Comprehensive CYP2D6 sequencing improved gene profiling accuracy in our preselected cohort, while highlighting the remaining challenges of rare variant interpretation in pharmacogenetics-guided therapeutic drug monitoring.