40-Parameter/37-Color Spectral Cytometry Panel for Robust Immunoprofiling of Human Lymphoid Subsets in Cancer Patients.

IF 2.1 4区 生物学 Q3 BIOCHEMICAL RESEARCH METHODS
Ondrej Venglar, Eva Radova, Lucie Broskevicova, Roman Hajek, Tomas Jelinek
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引用次数: 0

Abstract

The analysis of immune cell compartments in cancer patients is crucial to predict treatment efficacy and relapse. We introduce a robust 40-parameter, 37-channel spectral cytometry panel designed to profile human lymphoid subsets and CAR-T cell expansion, with the capability to assess exhaustion status by profiling immune checkpoints and activating receptors in cancer patients. Developed for the 5-laser Cytek Aurora, the panel optimizes fluorophore selection and uses three pairs of mutually exclusive markers assigned to a single fluorescent parameter to simplify setup and ensure robust data, adopting a conservative design choice to keep similarity indices below 0.85; though higher overlaps can still yield high-quality data when best practices are applied. The panel enables detailed analysis of well-defined lymphoid subsets using a conventional gating strategy, as well as detection of unconventional subsets with variable expression patterns by unsupervised algorithm-based analysis. The effectiveness of the panel is demonstrated through a dataset simulating the progression of multiple myeloma, from pre-malignant disease to a highly aggressive stage.

40参数/37色光谱细胞仪检测癌症患者淋巴亚群的免疫谱图
肿瘤患者免疫细胞区室的分析是预测治疗效果和复发的关键。我们引入了一种强大的40参数,37通道的光谱细胞仪面板,旨在分析人类淋巴细胞亚群和CAR-T细胞扩增,能够通过分析癌症患者的免疫检查点和激活受体来评估衰竭状态。为5激光Cytek Aurora开发的面板优化了荧光团的选择,并使用分配给单个荧光参数的三对相互排斥的标记来简化设置并确保稳健的数据,采用保守的设计选择以保持相似指数低于0.85;尽管在应用最佳实践时,较高的重叠仍然可以产生高质量的数据。该小组可以使用传统的门控策略对定义明确的淋巴细胞亚群进行详细分析,也可以通过基于无监督算法的分析检测具有可变表达模式的非常规亚群。该小组的有效性通过模拟多发性骨髓瘤从恶性前疾病到高度侵袭性阶段的进展的数据集得到证明。
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来源期刊
Cytometry Part A
Cytometry Part A 生物-生化研究方法
CiteScore
8.10
自引率
13.50%
发文量
183
审稿时长
4-8 weeks
期刊介绍: Cytometry Part A, the journal of quantitative single-cell analysis, features original research reports and reviews of innovative scientific studies employing quantitative single-cell measurement, separation, manipulation, and modeling techniques, as well as original articles on mechanisms of molecular and cellular functions obtained by cytometry techniques. The journal welcomes submissions from multiple research fields that fully embrace the study of the cytome: Biomedical Instrumentation Engineering Biophotonics Bioinformatics Cell Biology Computational Biology Data Science Immunology Parasitology Microbiology Neuroscience Cancer Stem Cells Tissue Regeneration.
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