Background: siRNAs have a high potential for silencing critical molecular pathways that are pathogenic. Nevertheless, their clinical application has been limited by a lack of effective and safe nanotechnology-based delivery system that allows a controlled and safe transfection to cytosol of targeted cells without the associated adverse effects. Our group recently reported a very effective and safe hybrid nanoparticle delivery system composing human IgG and poloxamer-188 for siRNA delivery to cancer cells. However, these nanoparticles need to be optimized in terms of particle size, loading capacity and encapsulation efficiency. In the present study, we explored the effects of certain production parameters on particle size, loading capacity and encapsulation efficiency. Further, to make these nanoparticles more specific in their delivery of siRNA, we conjugated anti-NTSR1-mAb to the surface of these nanoparticles to target NTSR1-overexpressing cancer cells. The mechanism of siRNA release from these antiNTSR1-mAb functionalized nanoparticles was also elucidated.
Results: It was demonstrated that the concentration of human IgG in the starting nanoprecipitation medium and the rotation speed of the magnetic stirrer influenced the encapsulation efficiency, loading capacity and the size of the nanoparticles produced. We also successfully transformed these nanoparticles into actively targeted nanoparticles by functionalizing with anti-NTSR1-mAb to specifically target NTSR1-overexpressing cancer cells, hence able to avoid undesired accumulation in normal cells. The mechanism of siRNA release from these nanoparticles was elucidated to be by Fickian diffusion. Using flow cytometry and fluorescence microscopy, we were able to confirm the active involvement of NTSR1 in the uptake of these anti-NTSR1-mAb functionalized hybrid nanoparticles by lung adenocarcinoma cells.
Conclusions: This hybrid nanoparticle delivery system can be used as a platform technology for intracellular delivery of siRNAs to NTSR1-overexpressing tumor cells.