Hybrid Nanoparticle System Integrating Tumor-Derived Exosomes and Poly(amidoamine) Dendrimers: Implications for an Effective Gene Delivery Platform

Abstract

Nanoscale drug delivery systems for cancer treatment have demonstrated promising results in enhancing the selectivity of therapeutic agents while reducing their toxic side effects. However, several biological and physical barriers, such as the immunogenicity and undesirable biodistributions of such delivery systems, have hindered their fast translation. To address these issues, we have developed an exosome–dendrimer hybrid nanoparticle (NP) platform to combine the advantageous biological properties of natural exosomes and synthetic dendrimers into a single NP system. The novel hybrid NPs, consisting of exosomes derived from MCF7 cells and functionalized poly(amidoamine) (PAMAM) dendrimers, were prepared using sonication and characterized in terms of loading efficiency, size, cytotoxicity, and cellular interactions. Our results indicate that the loading of dendrimers into exosomes is dependent on dendrimer size and charge. The hybrid NPs inherited the size (∼150 nm), surface charge (−10 mV), and surface protein markers (CD81 and CD63) of exosomes. Importantly, the hybrid NPs enhanced the cellular internalization of amine-terminated PAMAM dendrimers (p < 0.05) while exhibiting substantially lower cytotoxicity than the free positively charged dendrimers (113.3 vs 35.6% of cell viability at 500 nM, p < 0.05). These advantageous properties of hybrid NPs were leveraged for use as a gene delivery vehicle, resulting in enhanced oligonucleotide delivery (over 2-fold) to cancer cells, compared to dendrimers alone. Furthermore, the hybrid NPs effectively delivered small interfering RNA (siRNA) as well, downregulating programmed death-ligand 1 (PD-L1) expression significantly more (3.8-fold) than dendrimers alone (p < 0.05). Our results demonstrate that the individual characteristics of both exosomes and dendrimers can be integrated to generate a multifaceted NP platform, proposing a novel NP design strategy.