CD4+ T regulatory cells (Tregs) are a specialized subset of T lymphocytes, which promote immune homeostasis and tumor immunosuppression by restricting effector T cell immune responses. The characterization of context-specific Treg phenotypic heterogeneity is pivotal to determine their potential contributions to diseases. In the recent years, high-dimensional single-cell technologies, such as single-cell RNA sequencing, mass cytometry, or polychromatic flow cytometry, have played a central role in elucidating the heterogeneity of the Treg compartment at the cellular and molecular levels. Here we describe an example of high-dimensional flow cytometry analysis capable of defining an effector Treg subpopulation that positively correlates with cancer progression. Moreover, we provide a workflow template of high-dimensional single-cell analysis that is readily applicable to any leukocyte subpopulation.

High-Dimensional Single-Cell Profiling of Tumor-Infiltrating CD4+ Regulatory T Cells

Puccio S.
Methodology
;
2023

Abstract

CD4+ T regulatory cells (Tregs) are a specialized subset of T lymphocytes, which promote immune homeostasis and tumor immunosuppression by restricting effector T cell immune responses. The characterization of context-specific Treg phenotypic heterogeneity is pivotal to determine their potential contributions to diseases. In the recent years, high-dimensional single-cell technologies, such as single-cell RNA sequencing, mass cytometry, or polychromatic flow cytometry, have played a central role in elucidating the heterogeneity of the Treg compartment at the cellular and molecular levels. Here we describe an example of high-dimensional flow cytometry analysis capable of defining an effector Treg subpopulation that positively correlates with cancer progression. Moreover, we provide a workflow template of high-dimensional single-cell analysis that is readily applicable to any leukocyte subpopulation.
2023
Istituto di Ricerca Genetica e Biomedica - IRGB - Sede Secondaria Milano
9781071626467
9781071626474
Autoimmunity
Cancer
Clustering
High-dimensional data
Phenograph
Polychromatic flow cytometry
Profiling
Single-cell
Treg
UMAP
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/517797
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