Zebrafish in Personalized Breast Cancer Medicine

Breast cancer is a biologically heterogeneous disease in which substantial variation in molecular characteristics, tumor evolution, and treatment response presents major challenges for personalized therapeutic decision-making. Although genomic and molecular profiling have improved patient stratification, these approaches do not always accurately predict the functional response of an individual tumor to specific therapies. Consequently, there is increasing interest in functional precision-oncology models that can complement molecular profiling by directly assessing tumor behavior and drug sensitivity. Zebrafish ( Danio rerio ) have emerged as a promising platform for this purpose because of their rapid development, optical transparency, genetic tractability, relatively low experimental requirements, and suitability for medium- to high-throughput in vivo drug screening. In particular, patient-derived xenografts established in zebrafish, commonly referred to as zebrafish avatars (zAvatars), enable tumor cells obtained from individual patients to be engrafted into zebrafish embryos or larvae and subsequently challenged with candidate anticancer therapies. This review examines the development and application of zebrafish models in personalized breast cancer medicine, with emphasis on the transition from established breast cancer cell-line xenografts to patient-derived zAvatars. zAvatars show promising feasibility and preliminary patient-response concordance, but their predictive performance requires independent validation. Their clinical utility remains unestablished, and they should currently be considered investigational tools rather than validated guides for routine treatment selection. Future integration of zebrafish avatars with complementary precision-medicine technologies and larger prospective clinical studies may establish their role as rapid and scalable platforms for individualized breast cancer therapeutic selection. However, challenges including variable engraftment, incomplete representation of the human tumor microenvironment, drug pharmacokinetic differences, limited clinical validation, and the need for standardized response criteria currently constrain routine clinical implementation.