Issue 3, 2020

Exosome-mediated microRNA-497 delivery for anti-cancer therapy in a microfluidic 3D lung cancer model

Abstract

Non-small cell lung cancer (NSCLC) is one of the leading causes of death from cancer worldwide. The delivery and controlled regulation of miRNAs via exosomes is known as a potential therapeutic approach in the treatment of cancer. In this study, human cell-derived exosomes were used as delivery vehicles for miRNAs, and we investigated their anti-tumor and anti-angiogenic effects on NSCLCs that were cultured in 2D and 3D microfluidic devices. We demonstrated that exosomes that contained miRNA-497 (miR-497) effectively suppressed tumor growth and the expression of their associated genes, i.e., yes-associated protein 1 (YAP1), hepatoma-derived growth factor (HDGF), cyclin E1 (CCNE1), and vascular endothelial growth factor-A (VEGF-A), in A549 cells. Also, the level of VEGF-A-mediated angiogenic sprouting was decreased drastically in human umbilical vein endothelial cells (HUVECs) cultured in a microfluidic device. To mimic the in vivo-like tumor microenvironment of NSCLC, A549 cells were co-cultured with HUVECs in a single device, and miR-497-loaded exosomes were delivered to both types of cells. As a result, both the tube formation of endothelial cells and the migration of tumor decreased dramatically compared to the control. This indicated that miR-497 has synergistic inhibitory effects that target tumor growth and angiogenesis, so exosome-mediated miRNA therapeutics combined with the microfluidic technology could be a predictive, cost-efficient translational tool for the development of targeted cancer therapy.

Graphical abstract: Exosome-mediated microRNA-497 delivery for anti-cancer therapy in a microfluidic 3D lung cancer model

Supplementary files

Article information

Article type
Paper
Submitted
25 Sept. 2019
Accepted
05 Janv. 2020
First published
07 Janv. 2020

Lab Chip, 2020,20, 548-557

Exosome-mediated microRNA-497 delivery for anti-cancer therapy in a microfluidic 3D lung cancer model

K. Jeong, Y. J. Yu, J. Y. You, W. J. Rhee and J. A. Kim, Lab Chip, 2020, 20, 548 DOI: 10.1039/C9LC00958B

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