Experimental models for breast cancer bone metastasis: Comparative insights into model selection, autophagy competency, and platform limitations

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Authors: Shaghayegh Haghjooy Javanmard, Bahareh Zarin, Zahra Malakoutikhah, Maryam Vatani, Ismail Laher, Golnaz Vaseghi
Cited by: 1
References: 66

Abstract

Bones are susceptible to breast cancer metastasis via multistep processes involving different microenvironments, including the primary tumor, the circulatory system, and the bone. A major challenge for developing treatments for bone metastasis is the lack of experimental models to recapitulate the progression, cellular players, extracellular matrix (ECM), and signaling pathways. We review developments in breast cancer-bone metastasis models, including in vitro, three-dimensional (3D), ex vivo, and animal models, and summarize the information gained from these experimental models for use in translational research. Various in vitro and in vivo models of breast cancer metastasis have been developed, each with unique characteristics that can advance our understanding of disease progression. We compare these platforms according to their suitability for specific biological questions across the breast cancer bone-metastatic cascade, including early signaling, migration, extravasation, colonization, dormancy, osteolysis, immune interactions, drug responses, and autophagy-related stress adaptation. Despite these developments, the stress-adaptive mechanisms that govern metastatic persistence within the bone microenvironment are not sufficiently captured by many existing models. Among these mechanisms, autophagy has emerged as a critical regulator of tumor cell dormancy, metabolic adaptation, and therapy resistance in the bone niche. Therefore, integrating autophagy-relevant parameters in experimental platforms may increase their translational predictive value and biological fidelity and provide a more comprehensive framework for studying breast cancer metastases in bone.

Fields of Study & Subjects

Cancer Hypoxia and Metabolism Cancer Cells and Metastasis Mathematical Biology Tumor Growth

Publication details

Journal / source
Cell Death
Publisher
Elsevier BV
Volume
2
Issue
3
Pages
100022–100022
Publication date
1 July 2026
Language
EN