Maximizing liposome tumor delivery by hybridizing with tumor-derived extracellular vesicles

Abstract

Extracellular vesicles (EVs) have gained widespread interest due to their potential in the diagnosis and treatment of inflammation, autoimmune diseases, and cancers. EVs are lipidic vesicles comprising vesicles of endosomal origin called exosomes, microvesicles from membrane shedding, and apoptotic bodies from programmed cell death membrane blebbing that carry complex sets of cargo from their cells of origin, including proteins, lipids, mRNA, and DNA. EVs are rich in integrin proteins that facilitate intrinsic cellular communication to deliver their cargo contents and can also be used as biomarkers to study respective cellular conditions. Within this background, we hypothesized that when these EVs are hybridized with synthetic liposomes, it would help navigate the hybrid construct in the complex biological environment to find its target. Toward this endeavor, we have hybridized a synthetic liposome with EVs (herein called LEVs) derived from mouse breast cancer (4T1 tumors) cells and incorporated a rhodamine-B/near-infrared fluorescent dye to investigate their potential for cellular targeting and tumor delivery. Using membrane extrusion, we have successfully hybridized both entities resulting in the formation of LEVs and characterized their colloidal properties and stability over a period. While EVs are broadly dispersed nano- and micron-sized vesicles, LEVs are engineered as monodispersed with an average hydrodynamic size of 140 ± 5. Using immunoblotting and ELISA, we monitored and quantified the EV-specific protein CD63 and other characteristic proteins such as CD9 and CD81, which were taken as a handle to ensure the reproducibility of EVs and thus LEVs. These LEVs were further challenged with mice bearing orthotopic 4T1 breast tumors and the LEV uptake was found to be maximum in tumors and organs like the liver, spleen, and lungs when compared to control PEGylated liposomes in live animal imaging. Likewise, the constructs were capable of finding lung metastasis as observed in ex vivo imaging. We anticipate that this study can open avenues for drug delivery solutions that are superior in target recognition.