Signaling Dynamics of TSHR-Specific CAR-T Cells Revealed by FRET-Based Biosensors

基于 FRET 的生物传感器揭示 TSHR 特异性 CAR-T 细胞的信号传导动力学

阅读:24
作者:Jing Zhou, Jiangqing Chen, Yanjie Huang, Xiaofei Gao, Chun Zhou, Xianhui Meng, Jie Sun

Abstract

Although most patients with thyroid cancers have good prognosis and long-term survival, some patients are refractory to traditional therapeutic approaches and face a high risk of mortality. CAR-T therapy provides an attractive strategy to treat these patients. Considering the limited expression in thyroid tissues, thyroid-stimulating hormone receptor (TSHR) has been considered as a promising candidate as CAR-T target. However, it is still a challenge to find the optimal CAR design for the treatment of thyroid cancers. Dynamic signaling cascade is initiated by CAR molecules during CAR-T cell activation. The development of FRET-based biosensors enables us to detect the signaling dynamics of key kinases during CAR-T cell activation with high spatiotemporal resolution. Here using the ZAP70 and ERK biosensors, we visualized the dynamics of ZAP70 and ERK activities in TSHR-specific CAR-T cells upon antigen stimulation. We first constructed several TSHR-targeting CARs for the treatment of advanced thyroid cancers. The TSHR CAR-T cells with CD28 or 4-1BB co-stimulatory signaling domains exhibited potent cytotoxicity in vitro. By FRET imaging, we observed rapid increase of ZAP70 and ERK activities in TSHR CAR-T cells upon target cell binding. Even though CD28-based CAR-T cells had similar ZAP70 activation dynamics as 4-1BB-based CAR-T cells, they displayed slightly enhanced ERK activation, which may contribute to their faster anti-tumor kinetics in vivo. These results demonstrated the efficacy of TSHR CAR-T cells to treat advanced thyroid cancers. Our study indicated the potential of applying FRET biosensors to optimize the design of CAR for effective CAR-T therapy.

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。