Real-Time Quantification of Cartilage Degeneration by GAG-Targeted Cationic Nanoparticles for Efficient Therapeutic...

One of the characterizations of degenerative cartilage disease is the progressive loss of glycosaminoglycans (GAGs). The real-time imaging method to quantify GAGs is of great significance for the biochemical analysis of cartilage and diagnosis and therapeutic monitoring of cartilage degeneration in vivo. To this end, a cationic photoacoustic (PA) contrast agent, poly-l-lysine melanin nanoparticles (PLL-MNPs), specifically targeting anionic GAGs was developed in this study to investigate whether it can image cartilage degeneration. PLL-MNP assessed GAG depletion by Chondroitinase ABC in vitro rat cartilage and intact ex vivo mouse knee joint. A papain-induced cartilage degenerative mice model was used for in vivo photoacoustic imaging (PAI). Oral cartilage supplement glucosamine sulfate was intragastrically administered for mice cartilage repair and the therapeutic efficacy was monitored by PLL-MNP-enhanced PAI. Histologic findings were used to further confirm PAI results. In vitro results revealed that the PLL-MNPs not only had a high binding ability with GAGs but also sensitively monitored GAG content changes by PAI. The PA signal was gradually weakened along with the depletion of GAGs in cartilage. Particularly, PLL-MNPs depicted the cartilage structure and the distribution of GAGs was demonstrated in PA images in ex vivo joints. Compared with the normal joint, a lower signal intensity was detected from degenerative joint at 3 weeks after papain injection, suggesting an early diagnosis of cartilage lesion by PLL-MNPs. Importantly, this PA-enhanced nanoprobe was suitable for monitoring in vivo efficacy of glucosamine sulfate, which effectively blocked cartilage degradation in a high dose manner. In vivo imaging findings correlated well with histological examinations. PLL-MNPs provided sensitive visualization of cartilage degeneration and promising monitoring of therapeutic response in living subjects.