3D lung cancer invasion model
November 2017
University of Geneva, Geneva, Switzerland
Lung diseases commonly drive to fatal events, like cancer, which reaches a mortality rate of 70% within 1 year after diagnosis. However, there is a lack of effective tools to efficiently diagnose lung cancer at early stages. Autofluorescence bronchoscopy is a promising tool to distinguish between cancerous and healthy lung tissues, but needs further optimization to be efficient. Here, a 3D model is developed, reproducing the human lung cancer cells invasion of a functional airway. The model contains human airway epithelial cells, human lung fibroblasts and human lung adenocarcinoma cells, allowing to test the potential of two-photon laser induced autofluorescence in order to discriminate healthy and carcinogenic tissues. The results showed that autofluorescence can be detected similarly like in patient's tissue samples and can be related to the health status. Moreover, the edges of the tumors had spectral and intensity heterogeneity, showing that metabolic changes in the tumor influence its microenvironment. Overall, the researchers provide a new model that can be used to extend the research on lung cancer and improve the efficiency of autofluorescence-based diagnostic tools.
Health state dependent multiphoton induced autofluorescence in human 3D in vitro lung cancer model
Vasyl Kilin
Added on: 11-22-2021
[1] https://www.nature.com/articles/s41598-017-16628-3[2] https://data.jrc.ec.europa.eu/dataset/176d71e6-5082-4b29-8472-b719f6bda323
