Abstract
The encapsulation of Glucocorticoids (GCs) into long-circulating liposomes (LCLs) is a proven strategy to reduce the side effects of glucocorticoids and improve the treatment of inflammatory diseases, such as rheumatoid arthritis (RA). With the aim of supporting the development of GC-loaded LCLs, and potentially predict patient response to therapy clinically, we evaluated a direct PET imaging radiolabelling approach for preformed GC-LCLs in an animal model of human inflammatory arthritis. Methods: A preformed PEGylated liposomal methylprednisolone hemisuccinate (NSSL-MPS) nanomedicine was radiolabelled using [(89)Zr]Zr(oxinate)(4) ((89)Zr-oxine), characterised and tracked in vivo using PET imaging in a K/BxN serum-transfer arthritis (STA) mouse model of inflammatory arthritis and non-inflamed controls. Histology and joint size measurements were used to confirm inflammation. The biodistribution of (89)Zr-NSSL-MPS was compared to that of free (89)Zr in the same model. A therapeutic study using NSSL-MPS using the same time points as the PET/CT imaging was carried out. Results: The radiolabelling efficiency of NSSL-MPS with [(89)Zr]Zr(oxinate)(4) was 69 ± 8 %. PET/CT imaging of (89)Zr-NSSL-MPS showed high uptake (3.6 ± 1.5 % ID; 17.4 ± 9.3 % ID/mL) at inflamed joints, with low activity present in non-inflamed joints (0.5 ± 0.1 % ID; 2.7 ± 1.1 % ID/mL). Importantly, a clear correlation between joint swelling and high (89)Zr-NSSL-MPS uptake was observed, which was not observed with free (89)Zr. STA mice receiving a therapeutic dose of NSSL-MPS showed a reduction in inflammation at the time points used for the PET/CT imaging compared with the control group. Conclusions: PET imaging was used for the first time to track a liposomal glucocorticoid, showing high uptake at visible and occult inflamed sites and a good correlation with the degree of inflammation. A subsequent therapeutic response matching imaging time points in the same model demonstrated the potential of this radiolabeling method as a theranostic tool for the prediction of therapeutic response - with NSSL-MPS and similar nanomedicines - in the treatment of inflammatory diseases.