BD Technologies, Research Triangle Park, Durham, North Carolina.
Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina.
Mol Cancer Res. 2017 Apr;15(4):429-438. doi: 10.1158/1541-7786.MCR-16-0286-T. Epub 2016 Dec 30.
Cancer tissue functions as an ecosystem of a diverse set of cells that interact in a complex tumor microenvironment. Genomic tools applied to biopsies in bulk fail to account for this tumor heterogeneity, whereas single-cell imaging methods limit the number of cells which can be assessed or are very resource intensive. The current study presents methods based on flow cytometric analysis and cell sorting using known cell surface markers (CXCR4/CD184, CD24, THY1/CD90) to identify and interrogate distinct groups of cells in triple-negative breast cancer clinical biopsy specimens from patient-derived xenograft (PDX) models. The results demonstrate that flow cytometric analysis allows a relevant subgrouping of cancer tissue and that sorting of these subgroups provides insights into cancer cell populations with unique, reproducible, and functionally divergent gene expression profiles. The discovery of a drug resistance signature implies that uncovering the functional interaction between these populations will lead to deeper understanding of cancer progression and drug response. PDX-derived human breast cancer tissue was investigated at the single-cell level, and cell subpopulations defined by surface markers were identified which suggest specific roles for distinct cellular compartments within a solid tumor. .
肿瘤组织作为一个多样化细胞的生态系统,在复杂的肿瘤微环境中相互作用。应用于活检的基因组工具未能解释这种肿瘤异质性,而单细胞成像方法限制了可评估的细胞数量或非常耗费资源。本研究提出了基于流式细胞分析和使用已知细胞表面标志物(CXCR4/CD184、CD24、THY1/CD90)的细胞分选的方法,以鉴定和分析源自患者来源异种移植(PDX)模型的三阴性乳腺癌临床活检标本中的不同细胞群。结果表明,流式细胞分析允许对肿瘤组织进行相关的亚群分类,并且这些亚群的分选提供了对具有独特、可重复和功能不同的基因表达谱的癌细胞群体的深入了解。耐药性特征的发现表明,揭示这些群体之间的功能相互作用将导致对癌症进展和药物反应的更深入理解。在单细胞水平研究了 PDX 衍生的人类乳腺癌组织,并鉴定了通过表面标志物定义的细胞亚群,这些亚群表明在实体瘤内的不同细胞隔室中具有特定的作用。