In silico Digital Twins of Bone Metastasis Enable Investigation of Tumor Progression and Therapy Response

Bone metastasis (BM) is a leading cause of morbidity and mortality in prostate and renal cancer patients. The complex and dynamic biological processes driving its progression present significant challenges for both understanding and treating this disease. While current in vivo research provides valuable insights, it is often limited by the inability to fully capture the intricate and multifactorial nature of bone metastasis. Thus, complementing existing in vivo models with multiscale computational approaches is crucial for dissecting the complex interactions between tumor cells and bone microenvironment to advance our understanding of the metastatic process and therapy response. Accordingly, we developed a series of in vivo-inspired, spatially explicit, multicellular agent-based models of bone metastasis (A(BM)2) that effectively recapitulate key aspects of tumor progression, including angiogenesis and bone resorption. The digital twins were rigorously calibrated using in vivo data from prostate and kidney tumors. The models have utility for evaluating therapy response, as verified by simulation of both the anti-angiogenic effects of cabozantinib and the anti-resorptive effects of zoledronic acid. These results highlight the predictive character of the A(BM)² in anticipating therapeutic outcomes and increasing our understanding of the complex dynamics of bone metastasis.