High-dimensional single-cell analysis delineates radiofrequency ablation induced immune microenvironmental remodeling in pancreatic cancer

Abstract

Radiofrequency ablation (RFA) is an effective local therapy approach for treating solitary tumor of many types of malignancy. The impact of RFA on the tumor immune microenvironment on distant tumors after RFA treatment is still unclear. In this study, by using syngeneic tumor models and single-cell RNA and T-cell receptor sequencing, we have investigated the alterations of tumor-infiltrating immune cells in distant non-RFA tumors. Single-cell RNA sequencing identified six distinct lymphoid clusters, five distinct monocyte/macrophage clusters, three dendritic cells clusters, and one cluster of neutrophils. We found that RFA treatment reduced the proportions of immunosuppressive cells including regulatory T cells, tumor-associated macrophages and tumor-associated neutrophils, whereas increased the percentages of functional T cells in distant non-RFA tumors. Moreover, RFA treatment also altered gene expressions in single-cell level in each cell cluster. By using pseudo-time analysis, we have described the biological processes of tumor-infiltrating CD8⁺ T cells and monocytes/macrophages based on the transcriptional profiles. In addition, the immune checkpoints including PD-1 and LAG3 were upregulated in the T cells in distant non-RFA tumors after RFA treatment. In conclusion, our data indicate that RFA treatment induced remodeling of tumor immune microenvironment in distant non-RFA tumors in pancreatic cancer mouse model and suggest that combining RFA with immune checkpoint inhibitors may be an effective treatment approach.

Fig. 1. Changes in distant non-RFA tumor after RFA treatment.

a Diagram of control group and RFA group. RFA treatment was performed on the left side tumors (RFA side). The right side (non-RFA side) tumors were used to further analysis. b H&E staining of tumor tissues on RFA and non-RFA side after RFA treatment. Scale bar = 50 μm (red line at the bottom right). c After 2 weeks, tumors from control group and RFA group were harvested and measured. Tumor volumes were compared to each two groups. p values were calculated based on a Student’s t test (n = 4 per group). d, e Percentage of CD8⁺PD-1⁺ cells in distant non-RFA tumor on day 3, 5, and 8 after RFA treatment. p values were calculated based on a Student’s t test (n = 3 per group).

Fig. 2. Experimental setup. Syngeneic Panc02 mouse models were established and divided into two groups.

RFA Treatments were initiated on the left side in RFA group when the tumor volume reached ~500 mm³, whereas the tumor on the right side did not receive any intervention. Tumors were harvested on day 3 after RFA treatment, and then digested and sorted for CD45⁺ immune cells. CD45⁺ immune cells were pooled together from three mice in each group and then subjected to scRNA-seq and TCR sequencing using a 10× Genomics pipeline.

Fig. 3. Identification of cell populations based on single-cell gene expression in intratumoral CD45⁺ immune cells.

a UMAP plot of cells from two groups aggregated. b UMAP plot of immune cells displaying select marker-gene expression. c Heatmap displaying normalized expression for selecting genes in each cluster.

Fig. 4. RFA induces remodeling of tumor-infiltrating lymphoid cells.

a UMAP plot showing the merged data of intratumoral lymphocytes. b UMAP plot of lymphoid cells displaying select marker-gene expression. c Comparison of each cluster in two groups. d Percentage of cells in each cluster by condition. e Heatmap of gene ontology identifying pathway enrichment by each subpopulation. f Heatmap of KEGG enrichment analysis enrichment by clusters.

Fig. 5. Quantitative and qualitative changes of lymphocytes in individual clusters.

a Occupancy of clonotypes in each cluster by condition. b Pseudo-time trajectory of CD8⁺ T cells analyzed using Monocle 2. c CD8⁺ T-cell clusters from scRNA-seq overlaid on Monocle 2 pseudo-time plot. d UMAP plots showing CD4 (blue) and CD8 (red) expression in Mki67^hi_s1 by condition. e Percentage of CD4⁺ and CD8⁺ T cells in Mki67^hi_s1 by condition.

Fig. 6. RFA induces intratumoral monocytes/macrophages, DCs, and neutrophils remodeling.

a UMAP plots from merged data of these subpopulations. b UMAP plots with annotated clusters of these cells. c Heatmap displaying normalized expression of select markers. d Percentage of cells in each cluster by condition. e Heatmap of gene ontology enrichment analysis enrichment by clusters.

Fig. 7. Biological processes of intratumoral monocytes/macrophages.

a Trajectory plot with corresponding analysis of data by Monocle 2. b Seurat cluster of monocytes/macrophages clusters overlaid on Monocle 2 pseudo-time plot.