Literature DB >> 31794834

Nano-Ghosts: Biomimetic membranal vesicles, technology and characterization.

Jacopo Oieni1, Lior Levy1, Nitzan Letko Khait1, Liat Yosef1, Beth Schoen1, Miguel Fliman1, Hagit Shalom-Luxenburg1, Natali Malkah Dayan1, Domenico D'Atri1, Noa Cohen Anavy1, Marcelle Machluf2.   

Abstract

Currently, nano-carriers for anti-cancer drug delivery are complex systems, which struggle with immunogenicity and enhanced permeability effect (EPR)-related problems that halt the clinical translation of many therapeutics. Consequently, a rapidly growing field of research has been focusing on biomimetic nano-vesicles (BNVs) as an effective delivery alternative. Nevertheless, the translation of many BNVs is limited due to scalability problems, inconsistent production process, and insufficient loading efficiency. Here we discuss the process of our previously published BNVs, termed Nano-Ghosts (NGs), which are produced from the membrane of mesenchymal stem cells. We demonstrate the flexibility of the process, while alternating physical methodologies (sonication or extrusion) to produce the NGs while preserving their desired characteristics. We also show that our NGs can be labeled using multiple methods (fluorescence, radiolabeling, and genetic engineering) for tracking and diagnostic purposes. Lastly, we demonstrate that the loading efficiency can be improved by using electroporation to accommodate a range of therapeutics (small molecules, peptides and DNA) that can be delivered by the NGs. Our results emphasize the robustness of the NGs technology, its versatility and a vast range of applications, differentiating it from other BNVs and leading the way towards clinical translation.
Copyright © 2019 Elsevier Inc. All rights reserved.

Keywords:  Cancer drug delivery; Membrane-based nanoparticles; Mesenchymal stem cells; Nano-Ghosts; Nanovesicles

Mesh:

Substances:

Year:  2019        PMID: 31794834     DOI: 10.1016/j.ymeth.2019.11.013

Source DB:  PubMed          Journal:  Methods        ISSN: 1046-2023            Impact factor:   3.608


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