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.
Highlights
Pancreatic ductal adenocarcinoma (PDAC) is the fourth leading cause of cancer-related mortality in the United States[1]
CD8_s2 appeared to be a transitional state[26] between naive and exhausted T cells based on trajectory and TCR analysis. These findings suggest that Radiofrequency ablation (RFA) treatment enhanced the antitumor immune response by promoting functional CD8 accumulation, and these effects were most evident in the antigen-specific CD8+ T cells
Our study has demonstrated that RFA could result in a strong T-cellmediated immune response in distant tumors[13]
Summary
We used the ImmGen. To perform pathway analysis, we used the R package ClusterProfiler[19] to compared clusters inside cohorts (e.g., T cells, macrophages) with different parameters (0 fold and threshold of at least 10% of cells, expressing this gene inside cluster) to find the differential expression markers. PCA, UMAP, clustering (resolution 1 on 40 first PCAs) and marker selection analysis was performed as described above. We obtained the CD45+ immune cells from tumor mass and analyzed them by scRNA-seq and single-cell TCR sequencing with a 10× genomics pipeline (Fig. 2). We performed scRNA-seq analysis on CD45+ cells isolated from the tumor tissues of control group (n = 10,659 cells sequenced, coverage of 84 655 mean reads per cell) and the non-RFA side of the RFA-treated group (n = 8005 cells sequenced, coverage of 112,967 mean reads per cell). Clusters are annotated as “XXX_s#” where “XXX” represents the cell types, “s” represents the scRNA-seq, and “#” the different clusters
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