关键词: 胰腺癌, 动物模型, 数据挖掘, 应用分析

Abstract: Objective　To explore the factors and characteristics of animal model of pancreatic cancer, and provide reference and suggestions for the establishment of animal model of pancreatic cancer. Methods　With “pancreatic cancer” and “animal model” as the theme, the experimental literatures on pancreatic cancer animal models from 2000 to 2024 were retrieved from China National Knowledge Infrastructure(CNKI), Wanfang, Chongqing VIP, Chinese Medical Journal Full-Text Database and PubMed. The database was established for statistical analysis by collating animal species,sex, classification of animal models,method of model replication,types of cancer cell lines and detection indicators of experimental animals, and so on.Results　A total of 380 experimental research literature were selected. The most used animal models for pancreatic cancer were BALB/c nude mice, most of which were 4 to 8 weeks old. The modeling method was mostly heterotopic subcutaneous graft tumor model, with the injection site being the back subcutaneous tissue. The cell line used was mostly SW1990 and PANC-1. The subcutaneous tumorigenesis time was mostly 7-10 d, and the modeling time was mostly 4 weeks. Most of the model detection indexes were tumor tissue apparent indexes (tumor growth, volume, weight), tumor bearing animal apparent indexes (weight, mental state, hair color, diet, subcutaneous tissue growth), pathological changes of the tumor tissue, immunohistochemical staining of the tumor tissue, CT/MRI/ultrasound/MicroPET, Western blot of the tumor tissue protein, and Real time polymerase chain reaction, and so on.Conclusion　Currently, the animal models of pancreatic cancer do not match the pathogenic mechanisms of clinical pancreatic cancer very well. This article discusses the selection of experimental animals and cell lines, model preparation, and index detection for the study of pancreatic cancer animal models, providing reference and ideas for researchers to choose, apply, and improve experimental animal models.

Key words: pancreatic cancer, animal model, data mining, application analysis