Health state dependent multiphoton induced autofluorescence in human 3D in vitro lung cancer model

Abstract

Lung diseases pose the highest risk of death and lung cancer is a top killer among cancers with a mortality rate up to 70% within 1 year after diagnosis. Such a fast escalation of this cancer development makes early diagnosis and treatment a highly challenging task, and currently there are no effective tools to diagnose the disease at an early stage. The ability to discriminate between healthy and tumorous tissue has made autofluorescence bronchoscopy a promising tool for detection of lung cancer; however, specificity of this method remains insufficiently low. Here, we perform autofluorescence imaging of human lung cancer invading a human functional airway using an in vitro model of Non Small Cell Lung Cancer which combines a reconstituted human airway epithelium, human lung fibroblasts and lung adenocarcinoma cell lines, OncoCilAir™. By using two-photon laser induced autofluorescence microscopy combined with spectrally resolved imaging, we found that OncoCilAir™ provides tissue’s health dependent autofluorescence similar as observed in lung tissue in patients. Moreover, we found spectral and intensity heterogeneity of autofluorescence at the edges of tumors. This metabolic related heterogeneity demonstrates ability of tumor to influence its microenvironment. Together, our result shows that OncoCilAir™ is a promising model for lung cancer research.