CYP2D6, HUMAN EPIDERMAL GROWTH FACTOR RECEPTOR 2, AND BEYOND: PHARMACOGENOMICS-GUIDED PERSONALIZATION IN BREAST CANCER MANAGEMENT
DOI:
https://doi.org/10.22159/ajpcr.2026v19i3.57622Keywords:
Breast Cancer, Pharmacogenomics, CYP2D6, HER2, Precision OncologyAbstract
Breast cancer is a serious worldwide health concern, and it is highly fatal, debilitating, and unpredictable because of tumor heterogeneity and an individual difference in the metabolism and toxicity of drugs. The development of pharmacogenomics has been a potent instrument in overcoming these issues by incorporating individual genetic data into the decision-making process of the therapeutic process. This is a review that summarizes existing evidence regarding the use of pharmacogenomics determinants to affect endocrine therapy, immunotherapy, and chemotherapy in breast cancer. Polymorphism in CYP2D6 plays a potentially significant role in tamoxifen activation and endoxifen concentrations in hormone receptor-positive disease, and variants in CYP19A1, ESR1, and ESR2 also play a role in the efficacy and toxicity of aromatase inhibitor. The FCGR3A and FCGR2A polymorphisms of PI3K/AKT pathways, as well as HER2 structural changes, can predict the responsiveness to trastuzumab in HER2-positive breast cancer and determine how to use the new agents like trastuzumab deruxtecan and margetuximab. In the case of triple-negative breast cancer, the biomarkers such as PD-L1 expression, immune-related gene signature, HLA variants, and polygenic risk scores narrow immune checkpoint inhibitors selection and determine vulnerability to immune-related adverse events. Also, germline mutations in DPYD, CYP2C8, ABCB1, UGT2B7, and anthracycline cardiotoxicity-related genes assist in the reduction in dose and toxicity of anthracycline. The increased use of pharmacogenomics testing, multigene panels, and next-generation sequencing in both clinical research and clinical practice highlight the growing importance of this technology in precision oncology. Together, the pharmacogenomics allow the use of more personalized therapy choice, reduce the adverse effects, and increase the overall outcome of treatment in breast cancer.
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