Abstract 2143: From local growth to distant metastasis: A versatile in vivo imaging platform for modeling cancer progression.

Abstract Background: A comprehensive understanding of cancer progression requires experimental models capable of dynamically capturing both localized tumor growth and the multi-step process of systemic dissemination. Conventional models often recapitulate isolated aspects of this cascade, thereby limiting their translational relevance. Objective: To establish and validate an integrated in vivo platform that utilizes luciferase-based imaging to quantitatively model distinct stages of cancer progression—from primary engraftment to organotropic dissemination. Methods: We engineered a series of site-specific cancer models in immunodeficient mice, with disease progression continuously monitored by bioluminescent imaging (BLI). These included: 1. Intracardiac injection of MDA-MB-231-Luc2 cells to model disseminated metastatic seeding. 2. Intratibial and intracranial inoculation to evaluate site-specific growth of breast cancer cells in bone and brain microenvironments. 3. Intravenous injection of Ba/F3 and lymphoma cells to simulate hematogenous dissemination. 4. A systematic analysis of intracranial engraftment topography, where A375-GFP-Luc cells were inoculated at stereotactic coordinates 0.5 mm anterior, 1.5 mm anterior, and 0.5 mm posterior to the bregma. Results: The platform robustly recapitulated diverse disease phenotypes. Intracardiac injection resulted in widespread bioluminescent signals indicative of metastatic colonization. Orthotopic tibial and intracranial inoculations led to progressive, quantifiable local tumor growth. Intravenous injection of hematopoietic cells produced a systemic pattern of leukemic proliferation. Importantly, the intracranial implantation site emerged as a key determinant of disease progression: injections posterior to the bregma were associated with a significantly greater propensity for metastatic dissemination compared to anterior sites. Conclusion: We present a validated and versatile in vivo platform that enables the spatiotemporal quantification of tumor dynamics across multiple disease contexts. This integrated system provides a powerful tool for investigating organ-specific tumor biology and evaluating therapeutic efficacy against both primary and metastatic disease. Citation Format: Na Li, Hao Huang, Xinyu Zhong, Xuyang Duan, Xing Lan, Jinying Ning, Feng Hao. From local growth to distant metastasis: A versatile in vivo imaging platform for modeling cancer progression 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 2143.