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Computational identification of surface markers for isolating distinct subpopulations from heterogeneous cancer cell populations [scRNA-seq]

ABSTRACT: Intratumoral heterogeneity reduces treatment efficacy and complicates our understanding of tumor progression. There is a pressing need to understand how heterogeneous tumor cell subpopulations coexist within a tumor, yet biological systems to study these processes in vitro are limited. With the advent of single-cell RNA sequencing (scRNA-seq), it has been found that some cancer cell lines contain distinct subpopulations. These heterogeneous cell lines provide a unique opportunity to study coexistence and evolution between genetically similar cancer cell subpopulations in controlled experimental settings. Here, we present scEMD, a computational package that returns candidate surface makers maximally unique to transcriptomic subpopulations in scRNA-seq which may be used for FACS isolation. scEMD was experimentally validated using the MDA-MB-231 and MDA-MB-436 cell lines. ESAM and BST2/Tetherin were experimentally confirmed to identify and separate scRNA-seq cluster-matched subpopulations of MDA-MB-231 and MDA-MB-436 cells, respectively. Identification and enrichment of distinct subpopulations within cell line models using this computationally efficient and experimentally validated workflow paves the way for studies on the generation and maintenance of cellular heterogeneity in low-complexity in vitro systems.

ORGANISM(S): Homo sapiens

PROVIDER: GSE268249 | GEO | 2024/06/26

REPOSITORIES: GEO

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