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Progress and application of lung-on-a-chip for lung cancer
Lantao Li1, Wentao Bo2, Guangyan Wang3
1Department of Anesthesiology, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu, China.
Abstract:
Lung cancer is a malignant tumour with the highest incidence and mortality worldwide. Clinically effective therapy strategies are underutilized owing to the lack of efficient models for evaluating drug response. One of the main reasons for failure of anticancer drug therapy is development of drug resistance. Anticancer drugs face severe challenges such as poor biodistribution, restricted solubility, inadequate absorption, and drug accumulation. In recent years, "organ-on-a-chip" platforms, which can directly regulate the microenvironment of biomechanics, biochemistry and pathophysiology, have been developed rapidly and have shown great potential in clinical drug research. Lung-on-a-chip (LOC) is a new 3D model of bionic lungs with physiological functions created by micromachining technology on microfluidic chips. This approach may be able to partially replace animal and 2D cell culture models. To overcome drug resistance, LOC realizes personalized prediction of drug response by simulating the lung-related microenvironment in vitro, significantly enhancing therapeutic effectiveness, bioavailability, and pharmacokinetics while minimizing side effects. In this review, we present an overview of recent advances in the preparation of LOC and contrast it with earlier in vitro models. Finally, we describe recent advances in LOC. The combination of this technology with nanomedicine will provide an accurate and reliable treatment for preclinical evaluation.
Insights
Lung-on-a-chip (LOC) models offer a novel approach to predict anticancer drug responses by simulating the lung microenvironment. This technology aims to overcome drug resistance and improve personalized lung cancer treatment strategies.
Area of Science:
- Biomedical Engineering
- Oncology
- Drug Development
Background:
- Lung cancer presents high global incidence and mortality, with current therapy strategies limited by a lack of effective drug response evaluation models.
- Drug resistance, poor drug properties (biodistribution, solubility, absorption), and accumulation pose significant challenges to anticancer drug efficacy.
- Organ-on-a-chip (OOC) platforms, including Lung-on-a-chip (LOC) models, are emerging as powerful tools for regulating and studying the biomechanical, biochemical, and pathophysiological microenvironments in vitro.
Purpose of the Study:
- To review recent advancements in Lung-on-a-chip (LOC) technology and its applications in preclinical drug evaluation.
- To highlight the potential of LOC models in overcoming drug resistance and enabling personalized medicine for lung cancer.
- To compare LOC models with traditional in vitro models and discuss their advantages in simulating lung physiology.
Main Methods:
- Micromachining technology on microfluidic chips to create 3D bionic lung models (LOC).
- Simulation of the lung-related microenvironment in vitro to assess drug responses.
- Integration of LOC technology with nanomedicine for enhanced preclinical evaluation.
Main Results:
- LOC models provide a more accurate and reliable platform for predicting drug response compared to traditional models.
- LOC technology facilitates personalized prediction of drug efficacy by simulating the specific lung microenvironment.
- LOC models demonstrate potential in enhancing therapeutic effectiveness, bioavailability, and pharmacokinetics while minimizing side effects.
Conclusions:
- Lung-on-a-chip technology represents a significant advancement over traditional in vitro models for studying lung cancer and evaluating drug responses.
- LOC models offer a promising avenue for personalized medicine, improving the prediction of drug efficacy and overcoming resistance.
- The combination of LOC with nanomedicine holds substantial potential for accurate preclinical evaluations and the development of more effective lung cancer treatments.
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