A 22-color spectral flow cytometry panel for characterizing T cell subsets and functional states in healthy and hematolymphoid malignancies 3106

Abstract Description Comprehensive immune profiling of T cells and their functional status is essential for understanding immune responses, particularly in diseases such as leukemia, solid tumors, and immune deficiency disorders. This study aimed to develop a robust, multiparametric approach to characterize diverse T cell subsets and their activation states. A 22-color T cell panel was optimized for use on a full spectrum flow cytometer. This panel enabled the identification of CD4+, CD8+, and TCRγδ+ T cells, including naive, memory, and effector subsets. Additionally, specialized T cell subsets, such as Th1, Th2, Th9, Th17, Th22, ThGM-CSF, T follicular helper (Tfh), and T peripheral helper (Tph), were characterized. Functional markers of T cell activation and exhaustion were included to assess the functional status of T cells across different sample types. The panel was successfully optimized for immunophenotyping of both peripheral blood mononuclear cells (PBMC) and whole blood samples providing robust, reproducible results across donors and sample types. Lymphoid malignancy patient whole blood samples were also analyzed, providing insights into the immune status and functional characteristics of T cells in disease. This 22-color spectral flow cytometry panel is a comprehensive tool for T cell profiling. The capacity to delineate distinct T cell subsets and functional status demonstrates the potential for use in both basic and clinical research applications in immunology. Topic Categories Immune Mechanisms of Human Disease (HUM)

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Publication Details

Journal
The Journal of Immunology
Published
2025-11-01
DOI
https://doi.org/10.1093/jimmun/vkaf283.944
Primary Topic
Single-cell and spatial transcriptomics
Type
article
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article

A 22-color spectral flow cytometry panel for characterizing T cell subsets and functional states in healthy and hematolymphoid malignancies 3106

Mark Edinger, Lily M. Park, Xiaoyang Wang, Jun Deng et al.
The Journal of Immunology
Single-cell and spatial transcriptomics
article

A 22-color spectral flow cytometry panel for characterizing T cell subsets and functional states in healthy and hematolymphoid malignancies 3106

Mark Edinger, Lily M. Park, Xiaoyang Wang, Jun Deng, Keon Anderson, Maria Jaimes, Kaska Wloska, Elisaveta Voynova
article en

Abstract

Abstract Description Comprehensive immune profiling of T cells and their functional status is essential for understanding immune responses, particularly in diseases such as leukemia, solid tumors, and immune deficiency disorders. This study aimed to develop a robust, multiparametric approach to characterize diverse T cell subsets and their activation states. A 22-color T cell panel was optimized for use on a full spectrum flow cytometer. This panel enabled the identification of CD4+, CD8+, and TCRγδ+ T cells, including naive, memory, and effector subsets. Additionally, specialized T cell subsets, such as Th1, Th2, Th9, Th17, Th22, ThGM-CSF, T follicular helper (Tfh), and T peripheral helper (Tph), were characterized. Functional markers of T cell activation and exhaustion were included to assess the functional status of T cells across different sample types. The panel was successfully optimized for immunophenotyping of both peripheral blood mononuclear cells (PBMC) and whole blood samples providing robust, reproducible results across donors and sample types. Lymphoid malignancy patient whole blood samples were also analyzed, providing insights into the immune status and functional characteristics of T cells in disease. This 22-color spectral flow cytometry panel is a comprehensive tool for T cell profiling. The capacity to delineate distinct T cell subsets and functional status demonstrates the potential for use in both basic and clinical research applications in immunology. Topic Categories Immune Mechanisms of Human Disease (HUM)

The Journal of ImmunologyVol. 214(Supplement_1)
Cytel (United States) (US)
Openalex Percentile: Top 68%
Single-cell and spatial transcriptomics
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