A novel xenograft model in zebrafish for high-resolution investigating dynamics of neovascularization in tumors

一种用于高分辨率研究肿瘤新生血管形成动态的斑马鱼异种移植模型

阅读:1

Abstract

Tumor neovascularization is a highly complex process including multiple steps. Understanding this process, especially the initial stage, has been limited by the difficulties of real-time visualizing the neovascularization embedded in tumor tissues in living animal models. In the present study, we have established a xenograft model in zebrafish by implanting mammalian tumor cells into the perivitelline space of 48 hours old Tg(Flk1:EGFP) transgenic zebrafish embryos. With this model, we dynamically visualized the process of tumor neovascularization, with unprecedented high-resolution, including new sprouts from the host vessels and the origination from VEGFR2(+) individual endothelial cells. Moreover, we quantified their contributions during the formation of vascular network in tumor. Real-time observations revealed that angiogenic sprouts in tumors preferred to connect each other to form endothelial loops, and more and more endothelial loops accumulated into the irregular and chaotic vascular network. The over-expression of VEGF165 in tumor cells significantly affected the vascularization in xenografts, not only the number and size of neo-vessels but the abnormalities of tumor vascular architecture. The specific inhibitor of VEGFR2, SU5416, significantly inhibited the vascularization and the growth of melanoma xenografts, but had little affects to normal vessels in zebrafish. Thus, this zebrafish/tumor xenograft model not only provides a unique window to investigate the earliest events of tumoral neoangiogenesis, but is sensitive to be used as an experimental platform to rapidly and visually evaluate functions of angiogenic-related genes. Finally, it also offers an efficient and cost-effective means for the rapid evaluation of anti-angiogenic chemicals.

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。