Generation and application of patient-derived xenograft models in pancreatic cancer research

Chin Med J (Engl). 2019 Nov 20;132(22):2729-2736. doi: 10.1097/CM9.0000000000000524.

Abstract

Objective: Pancreatic ductal adenocarcinoma cancer (PDAC) is one of the leading causes of cancer-related death worldwide. Hence, the development of effective anti-PDAC therapies is urgently required. Patient-derived xenograft (PDX) models are useful models for developing anti-cancer therapies and screening drugs for precision medicine. This review aimed to provide an updated summary of using PDX models in PDAC.

Data sources: The author retrieved information from the PubMed database up to June 2019 using various combinations of search terms, including PDAC, pancreatic carcinoma, pancreatic cancer, patient-derived xenografts or PDX, and patient-derived tumor xenografts or PDTX.

Study selection: Original articles and review articles relevant to the review's theme were selected.

Results: PDX models are better than cell line-derived xenograft and other models. PDX models consistently demonstrate retained tumor morphology and genetic stability, are beneficial in cancer research, could enhance drug discovery and oncologic mechanism development of PDAC, allow an improved understanding of human cancer cell biology, and help guide personalized treatment.

Conclusions: In this review, we outline the status and application of PDX models in both basic and pre-clinical pancreatic cancer researches. PDX model is one of the most appropriate pre-clinical tools that can improve the prognosis of patients with pancreatic cancer in the future.

Publication types

  • Review

MeSH terms

  • Animals
  • Antineoplastic Agents / therapeutic use
  • Carcinoma, Pancreatic Ductal / drug therapy*
  • Carcinoma, Pancreatic Ductal / pathology*
  • Disease Models, Animal
  • Humans
  • Pancreatic Neoplasms / drug therapy*
  • Pancreatic Neoplasms / pathology
  • Precision Medicine / methods
  • Xenograft Model Antitumor Assays

Substances

  • Antineoplastic Agents