Comparative analysis of zebrafish, organoid, and organ-on-chip models in breast cancer research

Breast cancer remains a leading cause of cancer mortality worldwide, underscoring the urgent need for advanced preclinical models that faithfully recapitulate tumor complexity and improve therapeutic prediction. Traditional two-dimensional cell cultures and animal models often fail to capture the heterogeneous and dynamic nature of the disease, limiting their translational relevance. This review addresses a critical gap in the literature by providing a comprehensive and integrated comparison of three contemporary, complementary platforms-patient-derived organoids, zebrafish xenografts, and organ-on-chip systems-within a unified translational framework for breast cancer research. We evaluate each model's capacity to elucidate key signaling pathways, model molecular and genetic alterations, and recapitulate the biology of major breast cancer subtypes. Furthermore, we critically assess their roles in drug screening, personalized treatment prediction, and the study of resistance mechanisms, explicitly distinguishing between early-stage proof-of-concept studies, validated preclinical applications, and emerging clinical predictability. A key contribution of this work is a practical, decision-oriented synthesis, supported by comparative matrices, that guides researchers in model selection based on biological relevance, throughput, cost, and clinical predictability. We also highlight current challenges in reproducibility, scalability, and clinical validation, and discuss how emerging technologies such as CRISPR/Cas9 gene editing, artificial intelligence, and bioprinting are poised to address these limitations. By synthesizing the distinct advantages and applications of each platform, this review aims to accelerate the rational use of these advanced models in mechanistic discovery, drug development, and the advancement of precision oncology for breast cancer.