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

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).

Figure 1

(A) Gating strategy for lineage panel of peripheral blood leukocyte subsets. (B) Gating main PBMC cell subsets (T, B, NK, monocytes, and DCs) and Myeloids (eosinophil and neutrophil). C-Mono, classical monocytes; Inter-Mono, intermediate monocytes; Nc-Mono, non-classical monocytes; Eosin, Eosinophil; Neu, neutrophil.

Figure 2

Analysis of peripheral blood monocytes cells of myeloid markers and chemokine receptors. (A) Monocytes and DCs were isolated utilizing a bivariate CD14/CD16 plot. (B) Histogram overlays depicted the expression of myeloid markers and chemokine receptor markers within monocytes and DCs population. (C, D) Semi-automated analysis of flow cytometry data by tSNE. Scale bars of the tSNE plot represented color-coded scaled fluorescence intensity or cell count levels.

Figure 3

Expression of activating receptors and co-stimulation markers by monocyte subsets. (A) Three monocyte subsets clustered by tSNE. (B, C) Visualization of co-stimulation and activation markers in monocyte subsets, with the left side showing tSNE plots and the right side showing histogram plots.

Figure 4

Immune checkpoint molecule profiles on subsets of monocytes and dendritic Cells (A) Histogram plots illustrate checkpoint markers distribution among monocytes and DCs subsets. (B, C) tSNE visualization of checkpoint molecule expression and distribution in monocyte subsets from PBMCs. This figure maps 12 checkpoint molecules and cell counts in PBMC-derived monocytes, with scale bars indicating fluorescence and distribution metrics.

Figure 5

Differential expression of co-stimulatory, activation, and terminal differentiation/exhaustion markers cross monocyte subpopulations. (A) Visualization by tSNE reveals distinct monocyte populations, with the PhenoGraph algorithm identifying 8 unique cell clusters. Each cluster is visualized in a different color. The ClusterExplorer algorithm quantifies cell counts within these PhenoGraph clusters and facilitates the generation of a heatmap to examine protein expression patterns across each identified cluster[36]. (B) tSNE plots delineate the distribution of phenotypic markers among C-Mono, Inter-Mono, and Nc-Mono. (C) Histograms detail the distribution of phenotypic markers within monocyte subsets, highlighting differential expression profiles that distinguish monocyte subsets, shown are monocyte, C-Mono, Inter-Mono, and Nc-Mono. C-Mono, classical monocytes; Inter-Mono, intermediate monocytes; Nc-Mono.