Comprehensive analysis of human monocyte subsets using full-spectrum flow cytometry and hierarchical marker clustering

Front Immunol. 2024 Apr 29:15:1405249. doi: 10.3389/fimmu.2024.1405249. eCollection 2024.

Abstract

Introduction: Exploring monocytes' roles within the tumor microenvironment is crucial for crafting targeted cancer treatments.

Methods: This study unveils a novel methodology utilizing four 20-color flow cytometry panels for comprehensive peripheral immune system phenotyping, specifically targeting classical, intermediate, and non-classical monocyte subsets.

Results: By applying advanced dimensionality reduction techniques like t-distributed stochastic neighbor embedding (tSNE) and FlowSom analysis, we performed an extensive profiling of monocytes, assessing 50 unique cell surface markers related to a wide range of immunological functions, including activation, differentiation, and immune checkpoint regulation.

Discussion: This in-depth approach significantly refines the identification of monocyte subsets, directly supporting the development of personalized immunotherapies and enhancing diagnostic precision. Our pioneering panel for monocyte phenotyping marks a substantial leap in understanding monocyte biology, with profound implications for the accuracy of disease diagnostics and the success of checkpoint-inhibitor therapies. Key findings include revealing distinct marker expression patterns linked to tumor progression and providing new avenues for targeted therapeutic interventions.

Keywords: immune checkpoints; immunophenotyping; mesenchymal stromal cells (MSCs); monocytes; spectral flow cytometry; t-distributed stochastic neighbor embedding (tSNE) analysis; tumor microenvironment (TME).

MeSH terms

  • Biomarkers*
  • Cluster Analysis
  • Flow Cytometry* / methods
  • Humans
  • Immunophenotyping* / methods
  • Monocytes* / immunology
  • Monocytes* / metabolism
  • Neoplasms / diagnosis
  • Neoplasms / immunology
  • Tumor Microenvironment / immunology

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This research was supported by the National Natural Science Foundation of China (No. 82100228, 82270161, 82202978), the Guangzhou Basic and Applied Basic Research Foundation (No.2024A04J10011, 2023A04J2359), and Southern Medical University college students innovation and entrepreneurship training program (S202312121108).