OMIP 071: A 31-Parameter Flow Cytometry Panel for In-Depth Immunophenotyping of Human T-Cell Subsets Using Surface...

Area of Science:

• Immunology
• Cell Biology
• Medical Diagnostics

Background:

• Understanding T-cell functional diversity is crucial for disease mechanism elucidation and therapeutic development.
• Characterizing various T-cell subsets, including adaptive, innate-like, and tissue-resident memory T cells, is complex.
• Existing methods may lack the comprehensive marker coverage for in-depth T-cell immunophenotyping.

Purpose of the Study:

• To design and validate a high-parameter (31-marker, 29-color) flow cytometry panel for comprehensive human T-cell subset characterization.
• To enable detailed immunophenotyping of T cells from peripheral blood and lymph nodes.
• To facilitate the identification of innate-like T cells (iNKT, γδ T, MAIT) and tissue-resident memory T (Trm) cells.

Main Methods:

• Development of a 31-parameter cell surface staining panel for flow cytometry.
• Inclusion of adaptive T-cell markers along with specific markers for iNKT, γδ T, and MAIT cells (TCR Vα24-Jα18, TCR γδ, TCR Vɑ7.2, CD161).
• Incorporation of chemokine receptors (CXCR3, CXCR4, CXCR5, CXCR6, CCR4, CCR6, CCR7) for Th and Tfh subset identification, differentiation markers (CD45RO, CD7), activation markers (CD57, CD95, HLA-DR), cosignaling molecules (PD-1, NKG2D, CD28), and Trm markers (CD69, CD103).

Main Results:

• A robust 31-parameter panel was successfully established for high-dimensional T-cell immunophenotyping.
• The panel enables precise identification and characterization of a wide array of T-cell subsets, including specialized populations.
• Demonstrated utility in analyzing cell differentiation, activation status, homing potential, and tissue residency.

Conclusions:

• The developed 31-parameter panel provides an advanced tool for in-depth immunophenotyping of human T-cell subsets.
• This comprehensive approach can significantly enhance mechanistic studies of immune-related diseases.
• The panel holds potential for application in disease monitoring, prognosis, and the development of targeted immunotherapies.