多参数流式细胞术用于详细分析卵巢癌患者腹腔免疫细胞。
Multiparameter Flow Cytometry for Detailed Characterization of Peritoneal Immune Cells from Patients with Ovarian Cancer.
机构信息
Department of Obstetrics and Gynecology, University of Wisconsin-Madison, Madison, WI, USA.
University of Wisconsin Carbone Comprehensive Cancer Center, University of Wisconsin-Madison, Madison, WI, USA.
出版信息
Methods Mol Biol. 2022;2424:43-58. doi: 10.1007/978-1-0716-1956-8_3.
Multiparameter flow cytometry is a convenient and efficient method for thorough phenotyping of cells, and especially immune cells from various tissues. We have successfully used multiparameter flow cytometry to characterize immune cells from patients with ovarian cancer and leveraged dimensionality reduction and machine learning for optimized visualization and analysis. Herein, we describe our optimized and established protocols for the labeling of cells with fluorophore-conjugated antibody panels, followed by details on data acquisition. Finally, we describe methods for analysis of the flow cytometry data using both FlowJo as well as R package, Cytofkit, for multidimensional data visualization.
多参数流式细胞术是一种方便、高效的方法，可以彻底分析各种组织来源的细胞表型，尤其是免疫细胞。我们已成功地将多参数流式细胞术应用于卵巢癌患者免疫细胞的特征分析，并利用降维和机器学习进行了优化，以实现可视化和分析。在此，我们描述了我们优化和建立的细胞荧光标记抗体组合方案，以及数据采集的详细信息。最后，我们描述了使用 FlowJo 和 R 包 Cytofkit 分析流式细胞术数据的方法，用于多维数据可视化。
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