Department of Cardiothoracic Surgery, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
Cytometry A. 2013 Jan;83(1):141-9. doi: 10.1002/cyto.a.22156. Epub 2012 Oct 18.
Single cell analysis and cell sorting has enabled the study of development, growth, differentiation, repair and maintenance of "liquid" tissues and their cancers. The application of these methods to solid tissues is equally promising, but several unique technical challenges must be addressed. This report illustrates the application of multidimensional flow cytometry to the identification of candidate stem/progenitor populations in non-small cell lung cancer and paired normal lung tissue. Seventeen paired tumor/normal lung samples were collected at the time of surgical excision and processed immediately. Tissues were mechanically and enzymatically dissociated into single cell suspension and stained with a panel of antibodies used for negative gating (CD45, CD14, CD33, glycophorin A), identification of epithelial cells (intracellular cytokeratin), and detection of stem/progenitor markers (CD44, CD90, CD117, CD133). DAPI was added to measure DNA content. Formalin fixed paraffin embedded tissue samples were stained with key markers (cytokeratin, CD117, DAPI) for immunofluorescent tissue localization of populations detected by flow cytometry. Disaggregated tumor and lung preparations contained a high proportion of events that would interfere with analysis, were they not eliminated by logical gating. We demonstrate how inclusion of doublets, events with hypodiploid DNA, and cytokeratin+ events also staining for hematopoietic markers reduces the ability to quantify epithelial cells and their precursors. Using the lung cancer/normal lung data set, we present an approach to multidimensional data analysis that consists of artifact removal, identification of classes of cells to be studied further (classifiers) and the measurement of outcome variables on these cell classes. The results of bivariate analysis show a striking similarity between the expression of stem/progenitor markers on lung tumor and adjacent tumor-free lung.
单细胞分析和细胞分选使研究“液体”组织及其癌症的发育、生长、分化、修复和维持成为可能。这些方法在固体组织中的应用同样有前景,但必须解决几个独特的技术挑战。本报告说明了多维流式细胞术在识别非小细胞肺癌和配对正常肺组织中候选干细胞/祖细胞群体的应用。在手术切除时收集了 17 对肿瘤/正常肺样本,并立即进行处理。组织通过机械和酶解分离成单细胞悬液,并使用一组用于阴性门控(CD45、CD14、CD33、糖蛋白 A)的抗体进行染色,鉴定上皮细胞(细胞内细胞角蛋白),并检测干细胞/祖细胞标记物(CD44、CD90、CD117、CD133)。添加 DAPI 以测量 DNA 含量。福尔马林固定石蜡包埋组织样本用关键标记物(细胞角蛋白、CD117、DAPI)染色,用于流式细胞术检测到的群体的免疫荧光组织定位。分散的肿瘤和肺制剂中包含大量可能干扰分析的事件,如果不通过逻辑门控消除,这些事件将被消除。我们展示了如何包含双联体、具有亚二倍体 DNA 的事件以及也染色造血标记物的细胞角蛋白+事件,这会降低定量上皮细胞及其前体的能力。使用肺癌/正常肺数据集,我们提出了一种多维数据分析方法,该方法包括去除伪影、鉴定要进一步研究的细胞类别的分类器以及对这些细胞类别的结果变量进行测量。双变量分析的结果显示,肺肿瘤和相邻无肿瘤肺组织上干细胞/祖细胞标记物的表达之间存在惊人的相似性。