肿瘤内异质性降低了治疗效果，并使我们对肿瘤进展的理解变得复杂，迫切需要了解肿瘤内异质性肿瘤细胞亚群的功能，但体外研究这些过程的系统是有限的。单细胞 RNA 测序 (scRNA-seq) 揭示了一些癌细胞系包含不同的亚群。在这里，我们提出了 clusterCleaver，一个计算包，它使用统计距离度量来识别 scRNA-seq 中转录组亚群最大独特的候选表面标记，可用于 FACS 分离。使用 clusterCleaver，ESAM 和 BST2/tetherin 经实验验证为表面标记，可分别识别和分离 MDA-MB-231 和 MDA-MB-436 细胞内的主要转录组亚群。 clusterCleaver 是一种计算效率高且经过实验验证的工作流程，用于识别表面标记，从而跟踪和分离细胞系内转录组不同的亚群。该工具为在明确的体外系统中研究共存的癌细胞亚群铺平了道路。© 2024。作者。

Intratumor heterogeneity reduces treatment efficacy and complicates our understanding of tumor progression and there is a pressing need to understand the functions of heterogeneous tumor cell subpopulations within a tumor, yet systems to study these processes in vitro are limited. Single-cell RNA sequencing (scRNA-seq) has revealed that some cancer cell lines include distinct subpopulations. Here, we present clusterCleaver, a computational package that uses metrics of statistical distance to identify candidate surface markers maximally unique to transcriptomic subpopulations in scRNA-seq which may be used for FACS isolation. With clusterCleaver, ESAM and BST2/tetherin were experimentally validated as surface markers which identify and separate major transcriptomic subpopulations within MDA-MB-231 and MDA-MB-436 cells, respectively. clusterCleaver is a computationally efficient and experimentally validated workflow for identification of surface markers for tracking and isolating transcriptomically distinct subpopulations within cell lines. This tool paves the way for studies on coexisting cancer cell subpopulations in well-defined in vitro systems.© 2024. The Author(s).