3D-bioprinted cholangiocarcinoma-on-a-chip model for evaluating drug responses

Cholangiocarcinoma (CCA) is characterized by heterogeneous mutations and a refractory nature. Thus, the development of a model for effective drug screening is urgently needed. As the established therapeutic testing models for CCA are often ineffective, we fabricated an enabling three-dimensional (3D)-bioprinted CCA-on-a-chip model that to a good extent resembled the multicellular microenvironment and the anatomical microstructure of the hepato-vascular-biliary system to perform high-content antitumor drug screening. Specifically, cholangiocytes, hepatocytes, and vascular endotheliocytes were employed for 3D bioprinting of the models, allowing for a high degree of spatial and tube-like microstructural control. Interestingly, it was possible to observe CCA cells attached to the surfaces of the gelatin methacryloyl (GelMA) hydrogelembedded microchannels and overgrown in a thickening manner, generating bile duct stenosis, which was expected to be analogous to the in vivo configuration. Over 4000 differentially expressed genes were detected in the CCA cells in our 3D coculture model compared to the traditional two-dimensional (2D) monoculture. Further screening revealed that the CCA cells grown in the 3D traditional model were more sensitive to the antitumoral prodrug than those in the 2D monoculture due to drug biotransformation by the neighboring functional hepatocytes. This study provides proof-of-concept validation of our bioprinted CCA-on-a-chip as a promising drug screening model for CCA treatment and paves the way for potential personalized medicine strategies for CCA patients in the future.

Automated summary

In order to effectively screen drugs, we have developed a 3D bioprinted model of cholangiocarcinoma that mimics the multicellular microenvironment and anatomical microstructure of the hepato-vascular-biliary system. By using cholangiocytes, hepatocytes, and vascular endotheliocytes for bioprinting, we were able to study the growth and drug response of cancer cells in the model. This model shows potential as a drug screening tool for cholangiocarcinoma treatment and paves the way for future personalized medicine strategies.