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Updated: May 17, 2025

3D Cell-Printed Hypoxic Cancer-on-a-Chip for Recapitulating Pathologic Progression of Solid Cancer
Published on: January 5, 2021
Cancer-on-a-chip for precision cancer medicine
Lunan Liu1, Huishu Wang1, Ruiqi Chen2
1Department of Mechanical and Aerospace Engineering, New York University Tandon School of Engineering, Brooklyn, NY 11201, USA. wchen@nyu.edu.
Abstract:
Many cancer therapies fail in clinical trials despite showing potent efficacy in preclinical studies. One of the key reasons is the adopted preclinical models cannot recapitulate the complex tumor microenvironment (TME) and reflect the heterogeneity and patient specificity in human cancer. Cancer-on-a-chip (CoC) microphysiological systems can closely mimic the complex anatomical features and microenvironment interactions in an actual tumor, enabling more accurate disease modeling and therapy testing. This review article concisely summarizes and highlights the state-of-the-art progresses in CoC development for modeling critical TME compartments including the tumor vasculature, stromal and immune niche, as well as its applications in therapying screening. Current dilemma in cancer therapy development demonstrates that future preclinical models should reflect patient specific pathophysiology and heterogeneity with high accuracy and enable high-throughput screening for anticancer drug discovery and development. Therefore, CoC should be evolved as well. We explore future directions and discuss the pathway to develop the next generation of CoC models for precision cancer medicine, such as patient-derived chip, organoids-on-a-chip, and multi-organs-on-a-chip with high fidelity. We also discuss how the integration of sensors and microenvironmental control modules can provide a more comprehensive investigation of disease mechanisms and therapies. Next, we outline the roadmap of future standardization and translation of CoC technology toward real-world applications in pharmaceutical development and clinical settings for precision cancer medicine and the practical challenges and ethical concerns. Finally, we overview how applying advanced artificial intelligence tools and computational models could exploit CoC-derived data and augment the analytical ability of CoC.
Insights
Cancer-on-a-chip (CoC) models offer a more accurate preclinical testing platform by mimicking the tumor microenvironment (TME). This review highlights CoC advancements for precision cancer medicine and drug discovery.
Area of Science:
- Biomedical Engineering
- Oncology
- Microfluidics
Background:
- Current cancer preclinical models fail to accurately represent human tumor complexity and patient specificity.
- This limitation leads to high failure rates of cancer therapies in clinical trials.
- The tumor microenvironment (TME) plays a critical role in cancer progression and therapy response.
Purpose of the Study:
- To review the state-of-the-art in Cancer-on-a-chip (CoC) technology for modeling the TME.
- To discuss the application of CoC systems in cancer therapy screening and drug discovery.
- To explore future directions for developing next-generation CoC models for precision cancer medicine.
Main Methods:
- Summarization of recent advancements in CoC development for modeling tumor vasculature, stromal, and immune niches.
- Review of CoC applications in therapeutic screening.
- Exploration of future CoC technologies including patient-derived chips, organoids-on-a-chip, and multi-organ systems.
Main Results:
- CoC systems closely mimic in vivo tumor anatomy and microenvironment interactions, enabling more accurate disease modeling.
- CoC technology facilitates high-throughput screening for anticancer drug discovery.
- Integration of sensors and AI can enhance CoC data analysis and disease investigation.
Conclusions:
- CoC technology is crucial for advancing precision cancer medicine by providing patient-specific and high-fidelity preclinical models.
- Future CoC development should focus on standardization, translation to clinical settings, and integration with AI.
- Addressing practical challenges and ethical concerns is essential for the widespread adoption of CoC technology.
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