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Predicting anti-tumor efficacy of multi-functional nanomedicine on decellularized hepatocellular carcinoma-on-a-chip.

Authors :
Chen Y
Lin G
Wang Z
He J
Yang G
Lin Z
Gong C
Liu N
Li F
Tong D
Lin Y
Ding J
Zhang J
Source :
Biosensors & bioelectronics [Biosens Bioelectron] 2024 Nov 15; Vol. 264, pp. 116668. Date of Electronic Publication: 2024 Aug 12.
Publication Year :
2024

Abstract

Traditional hepatocellular carcinoma-chip models lack the cell structure and microenvironments necessary for high pathophysiological correlation, leading to low accuracy in predicting drug efficacy and high production costs. This study proposed a decellularized hepatocellular carcinoma-on-a-chip model to screen anti-tumor nanomedicine. In this model, human hepatocellular carcinoma (HepG2) and human normal liver cells (L02) were co-cultured on a three-dimensional (3D) decellularized extracellular matrix (dECM) in vitro to mimic the tumor microenvironments of human hepatocellular carcinoma in vivo. Additionally, a smart nanomedicine was developed by encapsulating doxorubicin (DOX) into the ferric oxide (Fe <subscript>3</subscript> O <subscript>4</subscript> )-incorporated liposome nanovesicle (NLV/Fe+DOX). NLV/Fe+DOX selectively killed 78.59% ± 6.78% of HepG2 cells through targeted delivery and synergistic chemo-chemodynamic-photothermal therapies, while the viability of surrounding L02 cells on the chip model retained high, at over 90.0%. The drug efficacy tested using this unique chip model correlated well with the results of cellular and animal experiments. In summary, our proposed hepatocellular carcinoma-chip model is a low-cost yet accurate drug-testing platform with significant potential for drug screening.<br />Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.<br /> (Copyright © 2024 Elsevier B.V. All rights reserved.)

Details

Language :
English
ISSN :
1873-4235
Volume :
264
Database :
MEDLINE
Journal :
Biosensors & bioelectronics
Publication Type :
Academic Journal
Accession number :
39173340
Full Text :
https://doi.org/10.1016/j.bios.2024.116668