In the past, different spheroid-, organotypic-, and three-dimensional (3D) bioprinting lung cancer models were established for in vitro drug testing and personalized medicine. These tissue models cannot depict the tumor microenvironment (TME) and, therefore, research addressing tumor cell-TME interactions is limited. To overcome this hurdle, we applied patient-derived lung tumor samples to establish new in vitro models. To analyze the tissue model properties, we established two-dimensional (2D) and 3D coculture tissue models exposed to static and dynamic culture conditions that afforded tissue culture for up to 28 days. Our tissue models were characterized by hematoxylin eosin staining, M30 enzyme-linked immunosorbent assay, and immunofluorescence staining against specific lung cancer markers (TTF-1 and p40/p63), cancer-associated fibroblast (CAF) markers (α-SMA and MCT4), and fibronectin (FN). The 3D models were generated with higher success rate than the corresponding 2D model. The cell density of the static 3D model increased from 21 to 28 days, whereas the apoptosis decreased. The dynamic 3D model possessed an even higher cell density than the static 3D model. We identified lung cancer cells, CAFs, and FN. Therefore, a novel in vitro 3D lung cancer model was established, which simulated the TME for 28 days and possessed a structural complexity.
Keywords: 3D lung cancer model; NSCLC; TME; dynamic 3D model.