High-Dimensional Analysis Delineates Myeloid and Lymphoid Compartment Remodeling during Successful Immune-Checkpoint Cancer Therapy

Abstract

Although current immune-checkpoint therapy (ICT) mainly targets lymphoid cells, it is associated with a broader remodeling of the tumor micro-environment. Here, using complementary forms of high-dimensional profiling, we define differences across all hematopoietic cells from syngeneic mouse tumors during unrestrained tumor growth or effective ICT. Unbiased assessment of gene expression of tumor-infiltrating cells by single-cell RNA sequencing (scRNAseq) and longitudinal assessment of cellular protein expression by mass cytometry (CyTOF) revealed significant remodeling of both the lymphoid and myeloid intratumoral compartments. Surprisingly, we observed multiple subpopulations of monocytes/macrophages, distinguishable by the markers CD206, CX3CR1, CD1d, and iNOS, that change over time during ICT in a manner partially dependent on IFNγ. Our data support the hypothesis that this macrophage polarization/activation results from effects on circulatory monocytes and early macrophages entering tumors, rather than on pre-polarized mature intratumoral macrophages.

Figure 1.. Identification of Intratumoral Cell Populations by scRNAseq

(A) T3 tumor growth in mice treated with different ICTs. (B) tSNE plot of intratumoral cells from all groups merged. (C) tSNE plot of infiltrating cells displaying marker gene expression. (D) Heat map displaying normalized expression of select genes in each cell cluster. (E) tSNE plots of infiltrating lymphoid and myeloid cells.

Figure 2.. ICT Remodels Tumor Infiltrating Lymphocytes

(A) tSNE scRNAseq plot from merged treatment data of exclusively intratumoral lymphocytes. (B) tSNE scRNAseq plot of lymphocytes displaying select marker gene expression. (C) tSNE scRNAseq plots with annotated clusters of intratumoral lymphocytes. (D) Percentage of cells in individual clusters by condition. (E) Histograms of Foxp3 expression in Tregs. Cells were gated on live CD45⁺ CD4⁺ Foxp3⁺ CD25⁺ cells. Histograms are representative from 3 individual mice per treatment condition and represent 2 independent experiments. (F) Heat map of GSEA identifying pathway enrichment by cluster. (G) Percentage of cells in Mki67^hi by condition and tSNE plots displaying Cd4 or Cd8 expression.

Figure 3.. Characterization of Intratumoral T Cell Populations by CyTOF

(A) tSNE plots of lymphoid cells identifying clustering strategy for T cell clusters. (B) tSNE plots of intratumoral CD4⁺ T cells by treatment condition annotated with distinct clusters. (C) Heat map displaying normalized expression of select genes in each cluster. (D) Percentage of cells in each clusters by condition. (E) tSNE plots of intratumoral CD8⁺ T cells (neoantigen-specific are highlighted) by treatment condition. (F) Percentage of cells in individual clusters by condition. (G) Heat map displaying normalized expression of select genes in each neoantigen-specific cluster. For C and F, each dot represents 2 pooled mice harvested and stained independently (N=5). Bar indicates mean percent ± SD of either (C) total lymphoid or (F) total CD8⁺ cells. Representative data from 3-4 independent experiments. *p<0.05, **p<0.01, ***p<0.001, Dunnett’s multiple comparison (DMC).

Figure 4.. ICT Remodels Intratumoral Monocytes/Macrophages

(A) tSNE plots from scRNAseq highlighting Mrc1 and Nos2 expressing cells. (B) iNOS and CD206 expression represented as mean fluorescent intensity with mean ± SEM (**p<0.01, ***p<0.005, unpaired t test). (C) tSNE plots with annotated clusters of intratumoral monocytes/macrophages. (D) Percentage of cells in individual clusters by condition. (E) Heat map displaying normalized expression of select genes in each monocyte/macrophage cluster. (F) Heat map of GSEA identifying pathway enrichment by cluster. Representative data (B) from 3 individual mice per treatment condition and represent 3 independent experiments.

Figure 5.. Characterization of Intratumoral Myeloid Cell Populations by CyTOF

(A) CyTOF tSNE plot of total tumor infiltrating CD45⁺ cells. Identification of individual populations is overlaid. (B) tSNE plots shown as the density of equal numbers of CD45⁺ viable cells per treatment group. (C) tSNE plots of annotated intratumoral monocytes/macrophages. (D) Percentage of cells in individual monocyte/macrophage clusters. (E) Heat map displaying normalized expression of selected genes in each cluster. (F) Percentage of cells in individual monocyte/macrophage clusters. For (D) and (F), each dot represents 2 pooled mice harvested and stained independently (N=5). Bar indicates mean percent ± SD of CD45⁺ cells upon different ICT. Representative data from 3-4 independent experiments. *p<0.05, **p<0.01, ***p<0.001, DMC.

Figure 6.. Restructuring of Intratumoral Monocytes/Macrophages Revealed by Longitudinal Analyses

(A) tSNE scRNAseq plot with corresponding analysis of monocyte/macrophage data by Monocle2. (B) Monocyte/macrophage clusters from scRNAseq overlaid on Monocle2 pseudotime plot. (C) CyTOF tSNE plot (all time points harvested combined and displayed) with macrophage/monocytes clusters annotated. (D) Heat map displaying normalized expression of markers in each monocyte/macrophage cluster. (E) tSNE plots of total CD45⁺ cells overlaid with individual markers per treatment group over time. (F) Kinetics of Mac_c3 (CX3CR1⁺ CD206⁺) or Mac_c8 (iNOS⁺). (G) Monocle2 analysis of CyTOF time course. (H) Individual markers overlaid on Monocle2 pseudotime plot. Representative data from 2-3 independent experiments.

Figure 7.. IFNγ-Dependent iNOS⁺ Monocyte/Macrophages Branching and Comparison to Human Macrophages

(A) Percentage of intratumoral monocytes/macrophages under different treatment conditions. (B) Comparison of mouse tumor infiltrating macrophage clusters with human macrophages under differing stimulation conditions (GSE46903) by principle component analysis (top) or represented as fold change enrichment (bottom). (C) tSNE Projection for the human monocyte/macrophage GSE46903 dataset.