Orthotopic bladder cancer preclinical models: Comprehensive review and technique optimization

原位膀胱癌临床前模型:综合综述与技术优化

阅读:1

Abstract

BACKGROUND: In vivo modeling is essential to study bladder cancer biology. Orthotopic bladder tumor models involve direct introduction of tumor cells into the bladder of a laboratory animal. Common techniques for orthotopic tumor introduction include transurethral, ultrasound-guided, or surgical approaches. OBJECTIVE: We systematically collected data from published studies that have utilized orthotopic bladder tumor models in mice or rats to identify trends and outcomes across techniques. We used these data to optimize a surgical orthotopic technique. METHODS: A PubMed search was performed to identify articles involving orthotopic implantation of tumor cells into mouse or rat bladders for research purposes. Results were individually reviewed and filtered. All studies reporting preclinical models established via a surgical, transurethral, and/or ultrasound-guided approach were included. Surgical orthotopic tumor implantation experiments were performed and data collected. RESULTS: A total of 254 studies were identified, of which 187 met criteria and were included in the analysis. Data regarding each orthotopic technique was reviewed and trends were identified. Transurethral installation was the most commonly used method but had the lowest tumor take rate. The surgical approach had the highest metastatic rate. These data were used to inform optimization of the surgical orthotopic approach in our laboratory. The study is limited by its retrospective design and heterogeneity of data reporting across studies. CONCLUSIONS: Tumor take rates vary across orthotopic implantation techniques. Optimization of a surgical implantation approach is feasible. These findings can inform best practices for orthotopic bladder cancer models.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。