Department of Stem Cell Biology and Regenerative Medicine, Keck School of Medicine of the University of Southern California, Los Angeles, CA, 90033, USA.
USC Norris Comprehensive Cancer Center, Keck School of Medicine of the University of Southern California, Los Angeles, California, 90033, USA.
Sci Rep. 2019 Nov 25;9(1):17470. doi: 10.1038/s41598-019-53899-4.
Circulating tumor cells (CTCs) shed from solid tumors can serve as a minimally invasive liquid biopsy for monitoring disease progression. Because CTCs are rare and heterogeneous, their biological properties need to be investigated at the single cell level, which requires efficient ways to isolate and analyze live single CTCs. Current methods for CTC isolation and identification are either performed on fixed and stained cells or need multiple procedures to isolate pure live CTCs. Here, we used the AccuCyte-RareCyte system to develop a Protocol for Integrated Capture and Retrieval of Ultra-pure single live CTCs using Negative and positive selection (PIC&RUN). The positive selection module of PIC&RUN identifies CTCs based on detection of cancer surface markers and exclusion of immune markers. Combined with a two-step cell picking protocol to retrieve ultrapure single CTCs, the positive selection module is compatible for downstream single cell transcriptomic analysis. The negative selection module of PIC&RUN identifies CTCs based on a live cell dye and the absence of immune markers, allowing retrieval of viable CTCs that are suitable for ex vivo culture. This new assay combines the CTC capture and retrieval in one integrated platform, providing a valuable tool for downstream live CTC analyses.
循环肿瘤细胞(CTCs)从实体瘤中脱落,可以作为监测疾病进展的微创液体活检。由于 CTCs 数量稀少且异质性强,需要在单细胞水平上研究其生物学特性,这就需要有效的方法来分离和分析活的单个 CTCs。目前的 CTC 分离和鉴定方法要么是对固定和染色的细胞进行操作,要么需要多个步骤来分离纯活的 CTCs。在这里,我们使用 AccuCyte-RareCyte 系统,开发了一种使用负选和正选(PIC&RUN)集成捕获和回收超纯单个活 CTC 的方案。PIC&RUN 的正选模块基于检测癌症表面标志物和排除免疫标志物来识别 CTCs。与两步细胞挑取方案结合,可回收超纯单个 CTCs,正选模块兼容下游单细胞转录组分析。PIC&RUN 的负选模块基于活细胞染料和缺乏免疫标志物来识别 CTCs,可回收适合体外培养的有活力的 CTCs。这种新的检测方法将 CTC 的捕获和回收集成在一个平台上,为下游的活 CTC 分析提供了一个有价值的工具。