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BackgroundPreclinical breast cancer models recapitulating the clinical course of metastatic disease are crucial for drug development. Highly metastatic cell lines forming spontaneous metastasis following orthotopic implantation were previously developed and characterized regarding their biological and histological characteristics. This study aimed to non-invasively and longitudinally characterize the spatiotemporal pattern of metastasis formation and progression in the MDA-MB-231-derived triple negative LM2-4 and HER2+ LM2-4H2N cell lines, using bioluminescence imaging (BLI), contrast enhanced computed tomography (CT), fluorescence imaging, and 2-deoxy-2-[fluorine-18]fluoro-D-glucose positron emission tomography ([18F]FDG-PET).Material and methodsLM2-4, LM2-4H2N, and MDA-MB-231 tumors were established in the right inguinal mammary fat pad (MFP) of female SCID mice and resected 14–16 days later. Metastasis formation was monitored using BLI. Metabolic activity of primary and metastatic lesions in mice bearing LM2-4 or LM2-4H2N was assessed by [18F]FDG-PET. Metastatic burden at study endpoint was assessed by CT and fluorescence imaging following intravenous dual-modality liposome agent administration.ResultsComparable temporal metastasis patterns were observed using BLI for the highly metastatic cell lines LM2-4 and LM2-4H2N, while metastasis formed about 10 days later for MDA-MB-231. 21 days post primary tumor resection, metastases were detected in 86% of LM2-4, 69% of LM2-4H2N, and 60% of MDA-MB-231 inoculated mice, predominantly in the axillary region, contralateral MFP, and liver/lung. LM2-4 and LM2-4H2N tumors displayed high metabolism based on [18F]FDG-PET uptake. Lung metastases were detected as the [18F]FDG-PET uptake increased significantly between pre- and post-metastasis scan. Using a liposomal dual-modality agent, CT and fluorescence confirmed BLI detected lesions and identified additional metastatic nodules in the intraperitoneal cavity and lung.ConclusionsThe combination of complementary anatomical and functional imaging techniques can provide high sensitivity characterization of metastatic disease spread, progression and overall disease burden. The described models and imaging toolset can be implemented as an effective means for quantitative treatment response evaluation in metastatic breast cancer.

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