Bioengineering Approaches for the Pancreatic Tumor Organoids Research and Application

Pancreatic cancer is a highly lethal form of digestive malignancy that poses significant health risks to individuals worldwide. Chemotherapy-based comprehensive treatment is the primary therapeutic approach for midlife and late-life patients. Nevertheless, the heterogeneity of the tumor and individual genetic backgrounds result in substantial variations in drug sensitivity among patients, rendering a single treatment regimen unsuitable for all patients. Conventional pancreatic cancer tumor organoid models are capable of emulating the biological traits of pancreatic cancer and are utilized in drug development and screening. However, these tumor organoids can still not mimic the tumor microenvironment (TME) in vivo, and the poor controllability in the preparation process hinders translation from essential drug screening to clinical pharmacological therapy. In recent years, many engineering methods with remarkable results have been used to develop pancreatic cancer organoid models, including bio-hydrogel, co-culture, microfluidic, and gene editing. Here, this work summarizes and analyzes the recent developments in engineering pancreatic tumor organoid models. In addition, the future direction of improving engineered pancreatic cancer organoids is discussed for their application prospects in clinical treatment. By incorporating contemporary microfluidic technology, biological hydrogel technology, coculture, and gene-editing technology into the organoid culture system of pancreatic cancer, a pioneering tumor model can be developed in vitro. This model is expected to emulate the intricate microenvironment of pancreatic tumors more precisely, thereby expediting the utilization of this model for high-throughput drug screening, and new drug discovery.image

Automated summary

This work summarizes and analyzes the recent developments in engineering pancreatic tumor organoid models, and discusses the future direction of improving the organoid models for their application prospects in clinical treatment.