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Metastasis-on-a-chip mimicking the progression of kidney cancer in the liver for predicting treatment efficacy
Metastasis is one of the most important factors that lead to poor prognosis in cancer patients, and effective suppression of the growth of primary cancer cells in a metastatic site is paramount in averting cancer progression. However, there is a lack of biomimetic three-dimensional (3D) in vitro mod...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Ivyspring International Publisher
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6929630/ https://www.ncbi.nlm.nih.gov/pubmed/31903121 http://dx.doi.org/10.7150/thno.38736 |
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author | Wang, Yimin Wu, Di Wu, Guohua Wu, Jianguo Lu, Siming Lo, James He, Yong Zhao, Chao Zhao, Xin Zhang, Hongbo Wang, ShuQi |
author_facet | Wang, Yimin Wu, Di Wu, Guohua Wu, Jianguo Lu, Siming Lo, James He, Yong Zhao, Chao Zhao, Xin Zhang, Hongbo Wang, ShuQi |
author_sort | Wang, Yimin |
collection | PubMed |
description | Metastasis is one of the most important factors that lead to poor prognosis in cancer patients, and effective suppression of the growth of primary cancer cells in a metastatic site is paramount in averting cancer progression. However, there is a lack of biomimetic three-dimensional (3D) in vitro models that can closely mimic the continuous growth of metastatic cancer cells in an organ-specific extracellular microenvironment (ECM) for assessing effective therapeutic strategies. Methods: In this metastatic tumor progression model, kidney cancer cells (Caki-1) and hepatocytes (i.e., HepLL cells) were co-cultured at an increasing ratio from 1:9 to 9:1 in a decellularized liver matrix (DLM)/gelatin methacryloyl (GelMA)-based biomimetic liver microtissue in a microfluidic device. Results: Via this model, we successfully demonstrated a linear anti-cancer relationship between the concentration of anti-cancer drug 5-Fluorouracil (5-FU) and the percentage of Caki-1 cells in the co-culture system (R(2) = 0.89). Furthermore, the Poly(lactide-co-glycolide) (PLGA)-poly(ethylene glycol) (PEG)-based delivery system showed superior efficacy to free 5-FU in killing Caki-1 cells. Conclusions: In this study, we present a novel 3D metastasis-on-a-chip model mimicking the progression of kidney cancer cells metastasized to the liver for predicting treatment efficacy. Taken together, our study proved that the tumor progression model based on metastasis-on-a-chip with organ-specific ECM would provide a valuable tool for rapidly assessing treatment regimens and developing new chemotherapeutic agents. |
format | Online Article Text |
id | pubmed-6929630 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Ivyspring International Publisher |
record_format | MEDLINE/PubMed |
spelling | pubmed-69296302020-01-04 Metastasis-on-a-chip mimicking the progression of kidney cancer in the liver for predicting treatment efficacy Wang, Yimin Wu, Di Wu, Guohua Wu, Jianguo Lu, Siming Lo, James He, Yong Zhao, Chao Zhao, Xin Zhang, Hongbo Wang, ShuQi Theranostics Research Paper Metastasis is one of the most important factors that lead to poor prognosis in cancer patients, and effective suppression of the growth of primary cancer cells in a metastatic site is paramount in averting cancer progression. However, there is a lack of biomimetic three-dimensional (3D) in vitro models that can closely mimic the continuous growth of metastatic cancer cells in an organ-specific extracellular microenvironment (ECM) for assessing effective therapeutic strategies. Methods: In this metastatic tumor progression model, kidney cancer cells (Caki-1) and hepatocytes (i.e., HepLL cells) were co-cultured at an increasing ratio from 1:9 to 9:1 in a decellularized liver matrix (DLM)/gelatin methacryloyl (GelMA)-based biomimetic liver microtissue in a microfluidic device. Results: Via this model, we successfully demonstrated a linear anti-cancer relationship between the concentration of anti-cancer drug 5-Fluorouracil (5-FU) and the percentage of Caki-1 cells in the co-culture system (R(2) = 0.89). Furthermore, the Poly(lactide-co-glycolide) (PLGA)-poly(ethylene glycol) (PEG)-based delivery system showed superior efficacy to free 5-FU in killing Caki-1 cells. Conclusions: In this study, we present a novel 3D metastasis-on-a-chip model mimicking the progression of kidney cancer cells metastasized to the liver for predicting treatment efficacy. Taken together, our study proved that the tumor progression model based on metastasis-on-a-chip with organ-specific ECM would provide a valuable tool for rapidly assessing treatment regimens and developing new chemotherapeutic agents. Ivyspring International Publisher 2020-01-01 /pmc/articles/PMC6929630/ /pubmed/31903121 http://dx.doi.org/10.7150/thno.38736 Text en © The author(s) This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/). See http://ivyspring.com/terms for full terms and conditions. |
spellingShingle | Research Paper Wang, Yimin Wu, Di Wu, Guohua Wu, Jianguo Lu, Siming Lo, James He, Yong Zhao, Chao Zhao, Xin Zhang, Hongbo Wang, ShuQi Metastasis-on-a-chip mimicking the progression of kidney cancer in the liver for predicting treatment efficacy |
title | Metastasis-on-a-chip mimicking the progression of kidney cancer in the liver for predicting treatment efficacy |
title_full | Metastasis-on-a-chip mimicking the progression of kidney cancer in the liver for predicting treatment efficacy |
title_fullStr | Metastasis-on-a-chip mimicking the progression of kidney cancer in the liver for predicting treatment efficacy |
title_full_unstemmed | Metastasis-on-a-chip mimicking the progression of kidney cancer in the liver for predicting treatment efficacy |
title_short | Metastasis-on-a-chip mimicking the progression of kidney cancer in the liver for predicting treatment efficacy |
title_sort | metastasis-on-a-chip mimicking the progression of kidney cancer in the liver for predicting treatment efficacy |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6929630/ https://www.ncbi.nlm.nih.gov/pubmed/31903121 http://dx.doi.org/10.7150/thno.38736 |
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