Abstract

Imaging spontaneous cancer cell metastasis or heterogeneous tumor responses to drug treatment in vivo is difficult to achieve. The goal was to develop a new highly sensitive and reliable preclinical longitudinal in vivo imaging model for this purpose, thereby facilitating discovery and validation of anticancer therapies or molecular imaging agents. The strategy is based on breast cancer cells stably expressing the human sodium iodide symporter (NIS) fused to a red fluorescent protein, thereby permitting radionuclide and fluorescence imaging. Using whole-body nano-SPECT/CT with (99m)TcO4(-), we followed primary tumor growth and spontaneous metastasis in the presence or absence of etoposide treatment. NIS imaging was used to classify organs as small as individual lymph nodes (LNs) to be positive or negative for metastasis, and results were confirmed by confocal fluorescence microscopy. Etoposide treatment efficacy was proven by ex vivo anticaspase 3 staining and fluorescence microscopy. In this preclinical model, we found that the NIS imaging strategy outperformed state-of-the-art (18)F-FDG imaging in its ability to detect small tumors (18.5-fold-better tumor-to-blood ratio) and metastases (LN, 3.6-fold) because of improved contrast in organs close to metastatic sites (12- and 8.5-fold-lower standardized uptake value in the heart and kidney, respectively). We applied the model to assess the treatment response to the neoadjuvant etoposide and found a consistent and reliable improvement in spontaneous metastasis detection. Importantly, we also found that tumor cells in different microenvironments responded in a heterogeneous manner to etoposide treatment, which could be determined only by the NIS-based strategy and not by (18)F-FDG imaging. We developed a new strategy for preclinical longitudinal in vivo cancer cell tracking with greater sensitivity and reliability than (18)F-FDG PET and applied it to track spontaneous and distant metastasis in the presence or absence of genotoxic stress therapy. Importantly, the model provides sufficient sensitivity and dynamic range to permit the reliable assessment of heterogeneous treatment responses in various microenvironments.

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