Engineering the bone metastatic prostate cancer niche through a microphysiological system to report patient-specific treatment response

Abstract Bone is the most common site of prostate cancer metastasis, leading to significant morbidity, treatment resistance, and mortality. A major challenge in understanding treatment response is the complex, bone metastatic niche. Here, we report the first patient-specific microphysiological syste...

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Main Authors: Cristina Sánchez-de-Diego, Ravi Chandra Yada, Nan Sethakorn, Peter G. Geiger, Adeline B. Ding, Erika Heninger, Fauzan Ahmed, María Virumbrales-Muñoz, Nikolett Lupsa, Emmett Bartels, Kacey Stewart, Suzanne M. Ponik, Marina N. Sharifi, Joshua M. Lang, David J. Beebe, Sheena C. Kerr
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Communications Biology
Online Access:https://doi.org/10.1038/s42003-025-08384-2
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Summary:Abstract Bone is the most common site of prostate cancer metastasis, leading to significant morbidity, treatment resistance, and mortality. A major challenge in understanding treatment response is the complex, bone metastatic niche. Here, we report the first patient-specific microphysiological system (MPS) to incorporate six primary human stromal cell types found in the metastatic bone niche (mesenchymal stem cells, adipocytes, osteoblasts, osteoclasts, fibroblasts, and macrophages), alongside an endothelial microvessel, and prostate tumor epithelial spheroids in an optimized media that supports their viability and phenotype. We tested two standard of care drugs, darolutamide and docetaxel, in addition to sacituzumab govitecan (SG), currently in clinical trials for prostate cancer, demonstrating that the MPS accurately replicates androgen response sensitivity and captures stromal microenvironment-mediated resistance. This advanced MPS provides a robust platform for investigating the biological mechanisms of treatment response and for identification and testing of therapeutics to advance patient-specific MPS towards personalized clinical-decision making.
ISSN:2399-3642