Development and In Vivo Testing of Smart Nanoparticles for Enhanced Anti-Cancer Activity and Reduced Cardiotoxicity Associated with Tyrosine Kinase Inhibitors

Abstract

Tyrosine kinase inhibitors (TKIs) are new generation of anti-cancer drugs with very high efficiency against cancer cells. However, TKIs are associated with severe cardiotoxicity limiting their clinical benefits. One TKI that has been developed recently but not explored much is Ponatinib. The use of nanoparticles as a better therapeutic agent to deliver anti-cancer drugs and reduce their cardiotoxicity has been recently considered. In this study, PLGA-PEG-PLGA nanoparticles were synthesized to deliver Ponatinib while reducing its cardiotoxicity for treatment of chronic myeloid leukemia. Shape, size, surface charge and drug uptake ability of these nanoparticles were assessed using transmission electron microscopy (TEM), ZetaSIZER NANO and high-performance liquid chromatography (HPLC). Cardiotoxicity of Ponatinib, unloaded and loaded PLGA-PEG-PLGA nanoparticles were studied on zebrafish model through measuring the survival rate and cardiac function parameters, to optimize efficient drug concentrations in an in vivo setting. These particles were tested on zebrafish cancer xenograft model in which, K562 cell line, was transplanted into zebrafish embryos. We showed that, at an optimal concentration (0.0025mg/ml), Ponatinib loaded PLGA-PEG-PLGA particles are non-toxic/non-cardio-toxic and are very efficient against cancer growth and metastasis. Zebrafish is a good animal model for investigating the cardiotoxicity associated with the anti-cancer drugs such as TKIs, to determine the optimum concentration of smart nanoparticles with the least side effects and to generate xenograft model of several cancer types. Also, PLGA-PEG-PLGA NPs could be good candidate for CML treatment, but their cellular internalization should be enhanced. This could be achieved by coating and labeling the surface of PLGA-PEG-PLGA NPs with specific ligands that are unique to CML cells.