Characterization of the tumor immune infiltrate by multiparametric flow cytometry and unbiased high-dimensional data analysis

利用多参数流式细胞术和无偏高维数据分析对肿瘤免疫浸润进行表征

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Abstract

The tumor microenvironment (TME) is a highly complex and dynamic ensemble of cells of which a variety of immune cells are a major component. The unparalleled results obtained with immunotherapeutic approaches have underscored the importance of examining the immune landscape of the TME. Recent technological advances have incorporated high-throughput techniques at the single cell level, such as single cell RNA sequencing, mass cytometry, and multi-parametric flow cytometry to the characterization of the TME. Among them, flow cytometry is the most broadly used both in research and clinical settings and multi-color analysis is now routinely performed. The high dimensionality of the data makes the traditional manual gating strategy in 2D scatter plots very difficult. New unbiased visualization techniques provide a solution to this problem. Here we describe the steps to characterize the immune cell compartment in the TME in mouse tumor models by high-parametric flow cytometry, from the experimental setup to the analysis methodology with special emphasis on the use of unsupervised algorithms.

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