Development Of A Non-Invasive Clinically Applicable Real Time Cell Tracking Platform For Evaluating Cell-Based Cancer Therapy Using Magnetic Resonance Imaging (Mri)

Abstract While advancement in chimeric antigen receptors (CARs) has greatly improved the anti-tumor activity of immune cell-based therapies utilizing modified T lymphocytes (CAR-T) and natural killer cells (CAR-NK), there remains a critical unmet need for diagnostic technologies to help evaluate their biological performance effectively and efficiently after injecting into the body.The ability to better understand the biodistribution of injected cells and devise dosing strategies are key determinants to the success or failure of cell therapy. However, clinicians are limited by the available technology for real time in-vivo tracking of cell therapy products in clinical settings. Here we present a clinically applicable novel magnetic agent that can effectively label a variety of cell types used in cancer cell therapy development including T cells, NK cells, and neural stem cells (NSCs), and when combined with the 3D ultrashort echo time Cones (3D UTE-Cones) sequence, can enable quantitative assessment of cell therapy products using MRI. In this study, we optimized loading of our tracking agent into T cells, NK cells, and NSCs, evaluated the morphology and viability of the labeled cells, and confirmed internalization of the labeling agent by Prussian blue staining and TEM. The in vitro MRI properties of the labeled cells were quantitated by the 3D UTE-Cones sequence. Ex vivo MRI analysis was performed by injecting labeled cells into harvested mouse livers and brains to ascertain their MRI visibility in tissues using a clinical MRI scanner. We confirmed that our magnetic labeling agent efficiently labeled each cell line tested, and the morphology or viability of the labeled cells were unaffected. The MRI detectability of labeled cells were confirmed by in vitro MRI phantoms. Further, using quantitative susceptibility mapping (QSM), T1, and T2* mapping based on 3D UTE-Cones sequences, we found near perfect correlations between cell density and MRI properties. By applying the parameters established in the MRI phantoms, we were able to detect and quantity the number of labeled cells injected into mouse livers and brains ex vivo. In summary, we have developed a clinically applicable imaging-based platform that empowers cell therapy researchers to better understand the results of their biodistribution and dosing studies through real-time cell tracking and quantitative assessments using MRI. Citation Format: Johnny C. Akers, Zhao Wei, Hyungseok Jang, Eric Chang, Jiang Du, Mya S. Thu. Development of a non-invasive clinically applicable real time cell tracking platform for evaluating cell-based cancer therapy using magnetic resonance imaging (MRI) [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr LB-024.