Abstract 6078: Integrating patient-derived systems to model metastatic prostate cancer and decode therapy resistance

Abstract Prostate cancer (PCa) lethality is driven by treatment-refractory disease and skeletal metastases, yet progress in understanding these processes has been hindered by the lack of physiologically relevant models. To address this gap, we developed an integrated platform of MD Anderson PCa Patient-Derived Xenografts (MDA PCa PDXs) and PDX-derived organoids, that recapitulate the heterogenous biology of advanced PCa. These models enable genetic manipulation and mechanistic interrogation of metastasis, therapeutic resistance and microenvironment influence. Our PDX series comprises over 150 models with molecular characterization. When engrafted intrafemorally, these models reproduce hallmark osteogenic phenotypes observed clinically, as monitored by multi-modal imaging and bone histomorphometry analyses. Particularly, MDA PCa PDX 118b, a double-negative PDX, generates bone even when injected subcutaneously. Moreover, we performed intracardiac injections of luciferase engineered cell lines and PDXs. This approach allowed us to explore their metastatic potential and tropism using in vivo imaging systems (IVIS), providing a model to study therapeutic approaches that could mitigate progression. Through cross-species molecular profiling and spatial analysis, we contrasted subcutaneous and intrabone tumors. This revealed how epithelial-stromal interactions and transcriptional reprogramming at the bone-tumor interface drive niche-specific adaptations. Building on these observations, we investigated molecular drivers of skeletal colonization. We have previously identified Fibroblast Growth Factor Receptor 1 (FGFR1) signaling as a key driver of skeletal colonization. Thus, we tested Erdafitinib, a pan-FGFR inhibitor, using intrabone PDX models with different FGFR status. We observed significant changes on both tumor growth and, mainly, in bone compartment architecture, highlighting the importance of the metastatic niche in supporting tumor growth. Beyond skeletal colonization, we also sought to model relapse trajectories. Using relapsed PDXs, we uncovered metabolic rewiring upon castration resistance, including enhanced ketone body utilization. In our in vitro and in vivo models, targeting the ketogenic enzyme ACAT1 emerged as a promising strategy to counteract therapy-induced metabolic plasticity. Together, these therapeutic insights complement our platform’s broader utility. Collectively, these models bridge clinical observations with experimental systems, enabling functional studies of metastatic tropism and therapeutic escape. The combination of PDXs, organoids, different engraftment approaches, and in vitro studies, integrated with ongoing clinical feedback, iteratively refines experimental strategies and enhances model accuracy of disease complexity. Citation Format: Agustina Sabater, Pablo Sanchis, Jun Yang, Jiabin Dong, Peter Shepherd, Nicolas Anselmino, Christopher J. Logothetis, Geraldine Gueron, Estefania Labanca. Integrating patient-derived systems to model metastatic prostate cancer and decode therapy resistance abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 6078.