A fast, simple, and cost-effective method of expanding patient-derived xenograft mouse models of pancreatic ductal adenocarcinoma

Advancements in Preclinical Models of Pancreatic Cancer

ABSTRACT

Pancreatic cancer remains one of the deadliest of all cancer types with a 5-year overall survival rate of just 12%. Preclinical models available for understanding the disease pathophysiology have evolved significantly in recent years. Traditionally, commercially available 2-dimensional cell lines were developed to investigate mechanisms underlying tumorigenesis, metastasis, and drug resistance. However, these cells grow as monolayer cultures that lack heterogeneity and do not effectively represent tumor biology. Developing patient-derived xenografts and genetically engineered mouse models led to increased cellular heterogeneity, molecular diversity, and tissues that histologically represent the original patient tumors. However, these models are relatively expensive and very timing consuming. More recently, the advancement of fast and inexpensive in vitro models that better mimic disease conditions in vivo are on the rise. Three-dimensional cultures like organoids and spheroids have gained popularity and are considered to recapitulate complex disease characteristics. In addition, computational genomics, transcriptomics, and metabolomic models are being developed to simulate pancreatic cancer progression and predict better treatment strategies. Herein, we review the challenges associated with pancreatic cancer research and available analytical models. We suggest that an integrated approach toward using these models may allow for developing new strategies for pancreatic cancer precision medicine.

Patient-derived tumor models: a suitable tool for preclinical studies on esophageal cancer

Esophageal cancer (EC) is the tenth most common cancer worldwide and has high morbidity and mortality. Its main subtypes include esophageal squamous cell carcinoma and esophageal adenocarcinoma, which are usually diagnosed during their advanced stages. The biological defects and inability of preclinical models to summarize completely the etiology of multiple factors, the complexity of the tumor microenvironment, and the genetic heterogeneity of tumors severely limit the clinical treatment of EC. Patient-derived models of EC not only retain the tissue structure, cell morphology, and differentiation characteristics of the original tumor, they also retain tumor heterogeneity. Therefore, compared with other preclinical models, they can better predict the efficacy of candidate drugs, explore novel biomarkers, combine with clinical trials, and effectively improve patient prognosis. This review discusses the methods and animals used to establish patient-derived models and genetically engineered mouse models, especially patient-derived xenograft models. It also discusses their advantages, applications, and limitations as preclinical experimental research tools to provide an important reference for the precise personalized treatment of EC and improve the prognosis of patients.

Patient-derived xenograft models in cancer therapy: technologies and applications

Patient-derived xenograft (PDX) models, in which tumor tissues from patients are implanted into immunocompromised or humanized mice, have shown superiority in recapitulating the characteristics of cancer, such as the spatial structure of cancer and the intratumor heterogeneity of cancer. Moreover, PDX models retain the genomic features of patients across different stages, subtypes, and diversified treatment backgrounds. Optimized PDX engraftment procedures and modern technologies such as multi-omics and deep learning have enabled a more comprehensive depiction of the PDX molecular landscape and boosted the utilization of PDX models. These irreplaceable advantages make PDX models an ideal choice in cancer treatment studies, such as preclinical trials of novel drugs, validating novel drug combinations, screening drug-sensitive patients, and exploring drug resistance mechanisms. In this review, we gave an overview of the history of PDX models and the process of PDX model establishment. Subsequently, the review presents the strengths and weaknesses of PDX models and highlights the integration of novel technologies in PDX model research. Finally, we delineated the broad application of PDX models in chemotherapy, targeted therapy, immunotherapy, and other novel therapies.

In vivo models of pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy with high mortality rate. Within the next decade, PDAC is projected to become the second leading cause of cancer-associated death in the United States. Understanding the pathophysiology of PDAC tumorigenesis and metastases is crucial toward developing new therapeutics. One of the challenges in cancer research is generating in vivo models that closely recapitulate the genomic, histological, and clinical characteristics of human tumors. An ideal model for PDAC not only captures the tumor and stromal environment of human disease, but also allows for mutational control and is easy to reproduce in terms of time and cost. In this review, we highlight evolution of in vivo models for PDAC including spontaneous tumors models (i.e., chemical induction, genetic modification, viral delivery), implantation models including patient derived xenografts (PDX), and humanized PDX. We discuss the implementation of each system and evaluate the benefits and shortcomings of these models. Overall, this review provides a broad overview of prior and current techniques of in vivo PDAC modeling and their associated challenges.

ICIs-Related Cardiotoxicity in Different Types of Cancer

Immune checkpoint inhibitors (ICIs) are rapidly developing immunotherapy cancer drugs that have prolonged patient survival. However, ICIs-related cardiotoxicity has been recognized as a rare, but fatal, consequence. Although there has been extensive research based on different types of ICIs, these studies have not indicated whether cardiotoxicity is specific to a type of cancer. Therefore, we conducted a systematic review to analyze a variety of ICIs-related cardiotoxicity, focusing on different types of cancer. We found that the incidence of ICIs-related cardiac adverse events (CAEs) and common cardiotoxic manifestations vary with cancer type. This inspired us to explore the underlying mechanisms to formulate targeted clinical strategies for maintaining the cardiovascular health of cancer patients.

A pancreas tumor derived organoid study: from drug screen to precision medicine

Pancreatic ductal adenocarcinoma (PDAC) one of the deadliest malignant tumor. Despite considerable progress in pancreatic cancer treatment in the past 10 years, PDAC mortality has shown no appreciable change, and systemic therapies for PDAC generally lack efficacy. Thus, developing biomarkers for treatment guidance is urgently required. This review focuses on pancreatic tumor organoids (PTOs), which can mimic the characteristics of the original tumor in vitro. As a powerful tool with several applications, PTOs represent a new strategy for targeted therapy in pancreatic cancer and contribute to the advancement of the field of personalized medicine.