Design and Evaluation of Engineered Extracellular Vesicle (EV)-Based Targeting for EGFR-Overexpressing Tumor Cells Using Monobody Display.

EGFR targeting EV engineering extracellular vesicles

Journal

Bioengineering (Basel, Switzerland)
ISSN: 2306-5354
Titre abrégé: Bioengineering (Basel)
Pays: Switzerland
ID NLM: 101676056

Informations de publication

Date de publication:
29 Jan 2022
Historique:
received: 20 12 2021
revised: 13 01 2022
accepted: 15 01 2022
entrez: 24 2 2022
pubmed: 25 2 2022
medline: 25 2 2022
Statut: epublish

Résumé

Extracellular vesicles (EVs) are attracting interest as a new class of drug delivery vehicles due to their intrinsic nature of biomolecular transport in the body. We previously demonstrated that EV surface modification with tissue-specific molecules accomplished targeted EV-mediated DNA delivery. Here, we describe reliable methods for (i) generating EGFR tumor-targeting EVs via the display of high-affinity monobodies and (ii) in vitro measurement of EV binding using fluorescence and bioluminescence labeling. Monobodies are a well-suited class of small (10 kDa) non-antibody scaffolds derived from the human fibronectin type III (FN3) domain. The recombinant protein consists of the EGFR-targeting monobody fused to the EV-binding domain of lactadherin (C1C2), enabling the monobody displayed on the surface of the EVs. In addition, the use of bioluminescence or fluorescence molecules on the EV surface allows for the assessment of EV binding to the target cells. In this paper, we describe methods of EV engineering to generate targeted delivery vehicles using monobodies that will have diverse applications to furnish future EV therapeutic development, including qualitative and quantitative in vitro evaluation for their binding capacity.

Sections du résumé

BACKGROUND BACKGROUND
Extracellular vesicles (EVs) are attracting interest as a new class of drug delivery vehicles due to their intrinsic nature of biomolecular transport in the body. We previously demonstrated that EV surface modification with tissue-specific molecules accomplished targeted EV-mediated DNA delivery.
METHODS METHODS
Here, we describe reliable methods for (i) generating EGFR tumor-targeting EVs via the display of high-affinity monobodies and (ii) in vitro measurement of EV binding using fluorescence and bioluminescence labeling. Monobodies are a well-suited class of small (10 kDa) non-antibody scaffolds derived from the human fibronectin type III (FN3) domain.
RESULTS RESULTS
The recombinant protein consists of the EGFR-targeting monobody fused to the EV-binding domain of lactadherin (C1C2), enabling the monobody displayed on the surface of the EVs. In addition, the use of bioluminescence or fluorescence molecules on the EV surface allows for the assessment of EV binding to the target cells.
CONCLUSIONS CONCLUSIONS
In this paper, we describe methods of EV engineering to generate targeted delivery vehicles using monobodies that will have diverse applications to furnish future EV therapeutic development, including qualitative and quantitative in vitro evaluation for their binding capacity.

Identifiants

pubmed: 35200409
pii: bioengineering9020056
doi: 10.3390/bioengineering9020056
pmc: PMC8869414
pii:
doi:

Types de publication

Journal Article

Langues

eng

Subventions

Organisme : Michigan State University
ID : N/A

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Auteurs

Hiroaki Komuro (H)

Institute for Quantitative Health Science and Engineering (IQ), Michigan State University, East Lansing, MI 48824, USA.
Department of Biomedical Engineering, Michigan State University, East Lansing, MI 48824, USA.

Shakhlo Aminova (S)

Institute for Quantitative Health Science and Engineering (IQ), Michigan State University, East Lansing, MI 48824, USA.
Department of Biomedical Engineering, Michigan State University, East Lansing, MI 48824, USA.

Katherine Lauro (K)

Institute for Quantitative Health Science and Engineering (IQ), Michigan State University, East Lansing, MI 48824, USA.
Department of Biomedical Engineering, Michigan State University, East Lansing, MI 48824, USA.

Daniel Woldring (D)

Institute for Quantitative Health Science and Engineering (IQ), Michigan State University, East Lansing, MI 48824, USA.
Department of Chemical Engineering and Materials Science, Michigan State University, East Lansing, MI 48824, USA.

Masako Harada (M)

Institute for Quantitative Health Science and Engineering (IQ), Michigan State University, East Lansing, MI 48824, USA.
Department of Biomedical Engineering, Michigan State University, East Lansing, MI 48824, USA.

Classifications MeSH