将T细胞动态映射到分子配置文件,通过行为引导的转录学.
A K L Wezenaar1,2, U Pandey1,2, F Keramati1
1Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands.
Nature protocols
|February 10, 2025
概括
这项研究引入了行为引导转录学 (BGT),将实时成像与单细胞RNA测序相结合,以将T细胞行为与其基因表达联系起来. 这种方法可以识别生物标志物,以提高癌症免疫疗法的有效性.
科学领域:
- 癌症研究 癌症研究
- 免疫学 免疫学 免疫学
- 生物技术是生物技术.
背景情况:
- 细胞免疫疗法和免疫瘤学共同培养对于评估抗瘤反应至关重要.
- BEHAV3D平台提供T细胞与瘤相互作用的3D实时成像,但缺乏分子洞察力.
- 单细胞RNA测序 (scRNA-seq) 提供了分子数据,但缺乏时空分辨率.
研究的目的:
- 将实时成像数据与scRNA-seq集成,以全面了解癌症治疗中的T细胞行为.
- 开发行为引导转录学 (BGT),将动态T细胞行为与特定的基因程序联系起来.
- 确定用于增强细胞免疫疗法治疗疗效的新生物标志物.
主要方法:
- 扩展BEHAV3D协议,将scRNA-seq.纳入其中.
- 使用实时成像数据来指导基于患者衍生瘤有机体 (PDO) 参与的细胞分离.
- 使用光激活细胞分类 (FACS) 和scRNA-seq.
- 整合in silico模拟以从转录基因数据推断T细胞行为.
主要成果:
- 成功整合动态T细胞成像与单细胞转录组学.
- 在瘤向过程中识别与特定的T细胞行为相关的基因程序.
- 发现了新的生物标志物,表明了功能性和无效的T细胞.
- 证明BGT在增强治疗疗效方面的潜力.
结论:
- 行为引导转录学 (BGT) 弥合了动态细胞行为和分子概况之间的差距.
- 通过BGT,可以发现优化癌症免疫治疗的生物标志物.
- 该协议具有适应性,易于使用,可以在一个月内完成.
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