Pancreatic Cancer Patient-Derived Organoid Platforms: A Clinical Tool to Study Cell- and Non-Cell-Autonomous Mechanisms of Treatment Response

Abstract

For many years, cell lines and animal models have been essential to improve our understanding of the basis of cell metabolism, signaling, and genetics. They also provided an essential boost to cancer drug discovery. Nevertheless, these model systems failed to reproduce the tumor heterogeneity and the complex biological interactions between cancer cells and human hosts, making a high priority search for alternative methods that are able to export results from model systems to humans, which has become a major bottleneck in the drug development. The emergent human in vitro 3D cell culture technologies have attracted widespread attention because they seem to have the potential to overcome these limitations. Organoids are unique 3D culture models with the ability to self-organize in contained structures. Their versatility has offered an exceptional window of opportunity to approach human cancers. Pancreatic cancers (PCs) patient-derived-organoids (PDOs) preserve histological, genomic, and molecular features of neoplasms they originate from and therefore retain their heterogeneity. Patient-derived organoids can be established with a high success rate from minimal tissue core specimens acquired with endoscopic-ultrasound-guided techniques and assembled into platforms, representing tens to hundreds of cancers each conserving specific features, expanding the types of patient samples that can be propagated and analyzed in the laboratory. Because of their nature, PDO platforms are multipurpose systems that can be easily adapted in co-culture settings to perform a wide spectrum of studies, ranging from drug discovery to immune response evaluation to tumor-stroma interaction. This possibility to increase the complexity of organoids creating a hybrid culture with non-epithelial cells increases the interest in organoid-based platforms giving a pragmatic way to deeply study biological interactions in vitro. In this view, implementing organoid models in co-clinical trials to compare drug responses may represent the next step toward even more personalized medicine. In the present review, we discuss how PDO platforms are shaping modern-day oncology aiding to unravel the most complex aspects of PC.

Emerging Trends and Research Foci in Tumor Microenvironment of Pancreatic Cancer: A Bibliometric and Visualized Study

“…The application of artificial intelligence has also improved the performance of EUS, which can assist doctors in making more accurate diagnoses ( 51 ). EUS-FNA (endoscopic ultrasound fine-needle aspiration) has become a first-line method for the diagnosis of pancreatic cancer due to its high accuracy and few complications, with a sensitivity of over 90% ( 52 , 53 ). Biomarkers such as proteins and mRNAs enriched in EUS-FNA-derived fluid can be used to evaluate the expression of genes in the tumor microenvironment, providing the possibility of early diagnosis of pancreatic cancer ( 54 ).…”

Pre-Training on In Vitro and Fine-Tuning on Patient-Derived Data Improves Deep Neural Networks for Anti-Cancer Drug-Sensitivity Prediction

“…PDOs have recently gained popularity in drug testing, since they map tumor heterogeneity while preserving the molecular characteristics of the original cancer. Their usage in personalized medicine is currently under investigation by many research groups [ 17 , 32 ]. We have explored how the large body of cell line drug-sensitivity data can be used to aid in this development.…”

Establishment of organoid models for pancreatic ductal adenocarcinoma and screening of individualized therapy strategy

“…Organoids are tissue‐ or organ‐like structures formed by the proliferation and differentiation of stem cells, which are 3D models in vitro culture 9 . The PDO model requires the extraction of primary cells from patients' tumor tissue and the use of external growth factors as well as an exogenous extracellular matrix to create a 3D growth environment 10–12 .…”