Pharmacogenomic Predictors of Anthracycline-Induced Cardiac Injury in Breast Cancer Therapy: A Systematic Review and Meta-Analysis of Genetic Variants Associated with Individual Risk Stratification, Myocardial Toxicity, and Long- Term Cardiovascular Outcomes

ABSTRACT Background: Anthracycline-based chemotherapy regimens remain the cornerstone of breast cancer treatment; however, their administration is associated with a spectrum of cardiotoxic effects ranging from subclinical myocardial dysfunction to overt heart failure and cardiomyopathy. The identification of pharmacogenomic predictors represents a paradigm shift toward precision cardio-oncology, enabling individualized risk stratification before the initiation of cytotoxic therapy. Objective: To systematically review and meta-analyze published evidence on genetic polymorphisms associated with anthracycline-induced cardiotoxicity (AIC) in breast cancer patients, with particular emphasis on variants in genes governing drug metabolism, oxidative stress response, DNA repair, and cardiac structural integrity. Methods: A comprehensive systematic search of PubMed/MEDLINE, Embase, Cochrane Library, and ClinicalTrials.gov was performed from inception through December 2024, following PRISMA 2020 guidelines. Studies reporting associations between specific single-nucleotide polymorphisms (SNPs) and measurable cardiac endpoints in breast cancer patients receiving anthracycline-based regimens were eligible. Random-effects meta- © 2025 Journal of Clinical and Translational Cardiology. All rights reserved.PageJ Clin Transl Cardiol | Pharmacogenomics & Anthracycline Cardiotoxicity | Fernandez Bravo R & Fernandez Bravo C analysis was performed using the DerSimonian-Laird method. Heterogeneity was assessed with the I2 statistic, and publication bias was evaluated using Egger's test. Results: Forty-seven studies comprising 18,432 breast cancer patients were included. The most robustly replicated genetic associations involved variants in CBR3 (rs1056892, OR 2.34, 95% CI 1.78-3.07), SLC28A3 (rs7853758, OR 0.41, 95% CI 0.29-0.58), RAC2 (rs13058338, OR 2.11, 95% CI 1.54-2.89), and NCF4 (rs1883112, OR 1.87, 95% CI 1.34-2.61). Additionally, variants in RARG (rs2229774), UGT1A6 (rs17863783), and HAS3 (rs2232228) demonstrated consistent associations with left ventricular systolic dysfunction. Polygenic risk scores incorporating multiple variants significantly improved predictive accuracy beyond clinical variables alone (AUC 0.78 vs. 0.61, p