2018
DOI: 10.1088/1361-6528/aac7a4
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Tumor-on-a-chip platforms for assessing nanoparticle-based cancer therapy

Abstract: Cancer has become the most prevalent cause of deaths, placing a huge economic and healthcare burden worldwide. Nanoparticles (NPs), as a key component of nanomedicine, provide alternative options for promoting the efficacy of cancer therapy. Current conventional cancer models have limitations in predicting the effects of various cancer treatments. To overcome these limitations, biomimetic and novel 'tumor-on-a-chip' platforms have emerged with other innovative biomedical engineering methods that enable the eva… Show more

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Cited by 19 publications
(6 citation statements)
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“…This means that nanomedicines should to take into account the particle type and cancer, since one-size-fits-all does not seem to work (for more information, please read the commentary from Chauhan and Jain [175]). Wang and coworkers recently reviewed the “tumor on a chip” platforms that facilitate clinical translation of nanoparticles-based cancer therapies [178]. Overchuck and Zheng stated that nanomedicines should be combined with pre-treatment strategies to improve their target achievement, thus not only tailoring nanomedicines’ features with TME cells and conditions, but also, depending on this highly variable TME and its components, subtle changes (pre-treatments such as radiation, hyperthermia and photodynamic therapy) can be applied in the tumor microenvironment to promote the accumulation of such nanoformulations (for more information, please check [173]).…”
Section: Nanomedicinesmentioning
confidence: 99%
“…This means that nanomedicines should to take into account the particle type and cancer, since one-size-fits-all does not seem to work (for more information, please read the commentary from Chauhan and Jain [175]). Wang and coworkers recently reviewed the “tumor on a chip” platforms that facilitate clinical translation of nanoparticles-based cancer therapies [178]. Overchuck and Zheng stated that nanomedicines should be combined with pre-treatment strategies to improve their target achievement, thus not only tailoring nanomedicines’ features with TME cells and conditions, but also, depending on this highly variable TME and its components, subtle changes (pre-treatments such as radiation, hyperthermia and photodynamic therapy) can be applied in the tumor microenvironment to promote the accumulation of such nanoformulations (for more information, please check [173]).…”
Section: Nanomedicinesmentioning
confidence: 99%
“…The 2D co-culture model still lacks many important tumour microenvironment (TME) characteristics, like heterogeneity, the oxygen and nutrient gradient, cell-matrix interaction, cellcell signalling and fluid shear stress found in vivo. [63][64][65] Those dynamic conditions can be mimicked by the use of a commercially available U-CUP perfusion bioreactor device (Fig. 7A).…”
Section: Nanoscale Papermentioning
confidence: 99%
“…[ 212 ] Efficient active targeting can be assessed by investigating the accumulation, efficacy, and toxicity of NPs. [ 197 ] Some systems can even integrate the synthesis of NPs with evaluation models, potentially promoting their discovery and clinical translation. [ 213 ] A microfluidic model tests NPs against prostate cancer cells and directly delivers them for in vitro high throughput screening of polymeric NP precursors with varying sizes and surface composition (Figure 8d).…”
Section: Microfluidic Reconstitution Of Tem For In Vitro Evaluation Of Nanomedicinesmentioning
confidence: 99%
“…[23] Microfluidic platforms mimic key biological delivery roots or barriers in the TME, including leaky tumor vasculature and an ECM with tumor tissues, to visualize the delivery and specific antitumor effect of NPs. [197] Breast cancer cells (MCF-7) cocultured with human microvascular endothelial cells (hMVECs) in a microfluidic model successfully mimicked in vivo TME features such as high interstitial pressure, poor permeability, and defective lymphatic drainage. [198] Complex transport of NPs to the tumor was simulated, providing quantitative information on their dynamic transport behavior (Figure 8a).…”
Section: Models For Passive Targeting Nanoparticlesmentioning
confidence: 99%