Loading
Life sciences · Journal article
Obm Genetics · September 21, 2026
No summary has been generated for this record yet. What follows is drawn from its source metadata only.
Journal article.
No findings were extractable from the material analysed.
Safety was not reported in the material analysed. Check the source before drawing any conclusion about harm.
The source did not state who this applies to in practice.
Graded across the dimensions that decide whether you should act, each from what the source actually supports. There is no single score, and where a dimension was not assessed it says so.
This record has not been graded across any dimension yet. Treat the label above as provisional and read the source.
What is missing. This record has no bottom line, key findings, reported figures, evidence dimensions. That is a gap in the analysis, not a judgement about the study.
Tamoxifen remains a cornerstone in the treatment of estrogen receptor-positive (ER+) breast cancer; however, variability in patient response underscores the necessity of a pharmacogenomic approach. This review integrates germline and somatic pharmacogenomics to elucidate the molecular determinants of tamoxifen metabolism, efficacy, and resistance. Germline polymorphisms, particularly in CYP2D6, CYP3A4/5, UGT2B7, and SULT1A1, significantly influence endoxifen levels, driving therapeutic variability across ethnic populations. Moreover, somatic mutations, notably in ESR1, TP53, and enhancer regions, confer acquired resistance and affect treatment outcomes. Ethnicity-specific distributions of these variants further highlight the inadequacy of a one-size-fits-all dosing strategy. Although CPIC and DPWG guidelines focus on CYP2D6 genotyping, they do not incorporate critical somatic data and phase II metabolism. To achieve truly personalized tamoxifen therapy, clinical algorithms must evolve to integrate germline and somatic profiles, enabling predictive, population-aware, and mutation-guided endocrine treatment. This review advocates for expanded multi-omics frameworks and multiethnic databases to optimize tamoxifen use and overcome endocrine resistance globally.