Abstract Background: Inflammatory breast cancer (IBC) is distinguished by the presence of tumor emboli, clusters of tumor cells, found within breast parenchyma and dermal lymphatic vessels. These emboli serve as a crucial clinicopathological hallmark, believed to underlie the characteristic diffuse growth pattern and aggressive progression observed in IBC patients, with nearly 30% of patients presenting with metastatic disease at diagnosis. However, the rarity of this cancer and the absence of a solid tumor mass pose challenges in obtaining biospecimens, particularly those with evidence of tumor emboli. To address this pressing need for preclinical models that replicate this distinctive tumor growth pattern, we describe a tumor emboli culture platform that facilitates live imaging, enables compound screening by assessing various phenotypes of the emboli, and permits evaluation of emboli in an in vivo murine model. Methods: The tumor emboli culture system was evaluated for physiological measurements corresponding to dermal lymphatic vessels and subsequently employed to generate tumor emboli from diverse patient-derived cell lines and PDX. Confocal microscopy was employed to characterize cellular information across multiple slices of the tumor emboli. This provided a comprehensive, multi-parametric analysis of single-cell and spheroid phenotypes, including measurements of number, size, shape, and viability of the organoids. Furthermore, we developed imaging algorithms to evaluate phenotypic changes in tumor emboli in response to anti-cancer drug treatment. We also optimized a technique that allows for in vivo tumor emboli implantation including in a transgenic mice with red fluorescent lymphatic vasculature that were surgically implanted with a dorsal skin window chamber. This allowed for intravital optical imaging of the local tumor microenvironment and adjacent skin. Results: Our culture platform enables live imaging of the tumor emboli generated over a span of 7-10 days, maintaining key parameters including kinematic and dynamic viscosity, density along with sheer wall stress within the reported physiological range for lymphatics. Through higher resolution confocal image acquisition and multi-parametric analysis, we conducted particle counting and classification, providing statistically significant insights into the integrity of tumor emboli over time. Additionally, the developed algorithms allowed for quantitative analysis of images from tumor emboli cultures subjected to anti-cancer drugs, revealing disparities in drug efficacy on tumor emboli integrity and dispersion including inter-cluster space within the emboli. Intravital optical imaging, coupled with quantitative analysis of dispersion characteristics of the tumor emboli implanted in the murine model over 5-6 days, demonstrated a diffuse spread reminiscent of observations in IBC patients. Furthermore, immunohistochemistry staining showed marked Ki67, CD45, F4-80 revealing a proliferative tumor microenvironment with high levels of macrophage infiltration. Conclusions: As of now specific targeted therapies for IBC patients remain elusive. Our culture platform for tumor emboli, when combined with advanced imaging techniques both in vitro and in vivo and traditional approaches like immunohistochemistry and genomic evaluation, forms a powerful toolkit for assessing the phenotype and dispersion characteristics of this unique pathological feature in IBC. This preclinical model offers crucial insights, potentially paving the way for precision medicine strategies in the treatment of this understudied cancer. Funding in part from American Cancer Society Mission Boost MBG-20-141-01-MBG grant (GRD), Department of Defense W81XWH-20-1-0153 (GRD), Duke Consortium for Inflammatory Breast Cancer Education (AB, CW, RE). Citation Format: Dorababu Sannareddy, Theresa Charity, Alexandra Bennion, Caroline Way, Edwin Yu, Ralph Erdmann, Gregory M Palmer, Gayathri R Devi. A Tumor Emboli Platform for Morphometric Analysis, Drug screening and for Intravital Optical Imaging in a Murine Model to Simulate Clinicopathological Features of Inflammatory Breast Cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO5-27-02.
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