Transcriptional Profiling Reveals Kidney Neutrophil Heterogeneity in Both Healthy People and ccRCC Patients

Abstract

Neutrophil is known to critically impact the development of renal diseases (e.g., the clear cell renal cell carcinoma (ccRCC)), whereas the heterogeneity of neutrophils in ccRCC remains unclear. In the present study, kidney biopsies from healthy donors and ccRCC tissues were collected for single-cell RNA sequencing (scRNA-seq). In addition, the subpopulations of neutrophils in a healthy kidney and in the tumor microenvironment (TME) of ccRCC were expressed and then analyzed. The genes reported previously were mapped to all subpopulations identified here. On that basis, biological theme comparison and Gene Set Enrichment Analysis (GSEA) were employed to reveal and compare relevant biological functions. In a healthy kidney, neutrophils exhibit two subpopulations: one is more associated with renal autoimmunity, probably acting as therapeutic target; the other is suggested to resist infectious microorganisms. It is noteworthy that six subpopulations were identified in ccRCC biopsy, and two were more relevant to autoimmunity, while the other four are more relevant to the tumor pathology. Besides, ccRCC neutrophil could resist anticancer immune therapies of ipilimumab and pembrolizumab for their low/no expressions of CTLA-4, PD-1, and PD-L1. Thus, this study can help understand the heterogeneity and pathological significance of neutrophils in renal diseases.

Figure 1

scRNA-seq analysis of CD45+ cells in healthy kidney. (a) UMAP plot shows clustering results from CD45+ cells from healthy kidney. They are NK cells, neutrophils, Th cell, nephron epithelial cell, and B cells (dot size at 0.5). (b) Pie plot indicates the frequency of each cell type. (c) Feature plots show the expression of known markers for each cluster. (d) UMAP plot shows 2 subclusters of neutrophils in healthy kidney (dot size at 4). (e) Violin plots show the differential expression levels of selected 2 genes from each neutrophil subcluster.

Figure 2

Analysis of healthy kidney neutrophil. (a) Heatmap shows the differential expression levels of top 10 genes selected from each neutrophil subcluster of a healthy kidney. (b) Biological theme comparison of healthy kidney neutrophil subclusters. (c) Overrepresentation analysis (ORA) of each healthy kidney neutrophil subcluster. (d) Cow plots show the gene concept network of each healthy kidney neutrophil subcluster.

Figure 3

scRNA-seq analysis of neutrophils in ccRCC. (a) UMAP plot shows 6 neutrophil subclusters in ccRCC. (b) Pie plot indicates the frequency of each neutrophil subcluster in ccRCC. (c) Feature plots show the expression of 2 genes selected from each ccRCC neutrophil cluster. (d) Heatmap shows the differential expression levels of top 10 genes selected from each ccRCC neutrophil subcluster.

Figure 4

Analysis of ccRCC neutrophils. (a) Biological theme comparison of ccRCC neutrophil subclusters. (b) Overrepresentation analysis (ORA) of each ccRCC neutrophil subcluster. (c) Gene-concept network of each ccRCC neutrophil subcluster.

Figure 5

Analysis of integrated neutrophil of healthy kidney and ccRCC. (a) UMAP plot shows “Merged” healthy kidney neutrophils and ccRCC neutrophils based on all the genes detected. (b) UMAP plot shows 6 neutrophil subclusters of integrated neutrophils based on conserved genes. (c) Dot plots show the differential expression levels of the most significant genes for each cluster. (d) GSEA analysis of each integrated neutrophil subcluster. (e) Expression levels of CTLA-1, PD-1, and PD-L1 in ccRCC neutrophils.