PD1hi CD200hi CD4+ exhausted T cell increase immunotherapy resistance and tumour progression by promoting epithelial-mesenchymal transition in bladder cancer

Abstract

Background: Bladder cancer (BLCA) is one of the most diagnosed cancers in humans worldwide. Recently, immunotherapy has become a main treatment option for BC. However, most BLCA patients do not respond to immune checkpoint inhibitors or relapse after immunotherapy. Therefore, it is very important to identify novel biomarkers for the prediction of immunotherapy response in B patients.

Methods: Pancancer single-cell RNA sequencing (scRNA-seq) data were used to identify the clusters of CD4⁺ T cells in the tumour microenvironment (TME). The clinical significance of key CD4⁺ T-cell clusters was evaluated based on the survival data of two independent immunotherapy bladder cancer (BLCA) cohorts. We also investigated the function of key clusters of CD4⁺ T cell in the TME of BC cells in vitro.

Results: This study identified two novel exhausted CD4⁺ T-cell subpopulations with the expression of PD1^hi CD200^hi or PD1^hi CD200^low in BC patients. Moreover, BLCA patients with a high level of PD1^hi CD200^hi CD4⁺ exhausted T cell showed immunotherapy resistance. Cell function analysis demonstrated that PD1^hi CD200^hi CD4⁺ exhausted T cell can promote epithelial-mesenchymal transition (EMT) and angiogenesis in BLCA cells. In addition, PD1^hi CD200^hi CD4⁺ exhausted T cells were shown to communicate with malignant BLCA cells through the GAS6-AXL axis. Finally, we also found that GAS6 expression is upregulated in B cells by METTL3-mediated m6A modification.

Conclusions: PD1^hi CD200^hi CD4⁺ exhausted T cell may serve as a novel biomarker for poor prognosis and immunotherapy resistance in B. Targeted inhibitors of PD1^hi CD200^hi CD4⁺ exhausted T cells may help improve the efficacy of immunotherapy.

Keywords: CD200; CD4 exhausted T cells; GAS6; N6-methyladenosine.

FIGURE 1

Two subclusters of CD4⁺ exhausted T cells were defined in the tumour microenvironment using the pancancer CD4⁺ T cell atlas: (A) the UMAP plot of the subclusters of CD4⁺ T cells integrated from nine tumour types. Each dot indicated a single cell. Colour‐coded for the cell type; (B) the dot plot showing the particular genes for each subcluster of CD4⁺ T cells; (C) tissue prevalence estimated by Ro/e score in pan‐CD4⁺ T cells; (D) the violin plot showing exhausted‐related genes expression in each cluster; (E) volcano map showing differentially expressed genes between CD4_ex2 and CD4_ex1 subclusters (ex2: logFC > .3 and log p‐value >2; ex1: logFC < −.3 and log p‐value >2); (F) the UMAP plot showing the IFNG expression in pan‐CD4⁺ T cells; (G) the barplot showing the pathway enrichment of CD4_ex1 subcluster; (H) the UMAP plot showing the CD200 expression in pan‐CD4⁺ T cells; (I) Barplot** showing the correlation between T cell exhausted‐related genes and CD200 in The Cancer Genome Atlas (TCGA)‐BLCA; (J) multiplex immunofluorescence staining was performed for DAPI (blue), CD4 (white), PD1 (red) and CD200 (green); each stain was shown separately and merged. The circles represent the PD1^hi CD200^hi CD4⁺ exhausted T cells. The field of view in the square is the reduced field of view.

FIGURE 2

The PD‐1^hi CD200^hi CD4⁺ exhausted T cells predict a poor response to immunotherapy: (A) overall survival of patients with immunotherapy in PDCD1^low, PDCD1^hi CD200^low and PDCD1^hi CD200^hi groups in the GSE176307 and IMvigor210 cohorts; (B) barplots showing the proportion of responders among PDCD1^low, PDCD1^hi CD200^low and PDCD1^hi CD200^hi groups in the GSE176307 and IMvigor210 cohorts; (C) violin plots showing the estimation of the abundance of CD8 T cells and M1 macrophages in the PDCD1^low, PDCD1^hi CD200^low and PDCD1^hi CD200^hi groups using CIBERSORT algorithm; (D) the expression of IFN‐γ between the PD‐1^hi CD200^low CD4⁻ T cells and PD‐1^hi CD200^hi CD4⁻ T cells was measured by intracellular flow cytometry. Summary data of IFN‐γ staining (right) are presented as mean ± SD (n = 3), **p < 0.01, ***p <0.001; (E) multiplex immunofluorescence staining was performed for DAPI (blue), CD4 (white), PD1 (red), CD200 (green) and IFNG (yellow). The circles represent the PD1^hi CD200^hi CD4⁺ exhausted T cells. The arrows represent the IFNG.

FIGURE 3

The PD‐1^hi CD200^hi CD4 exhausted T cells recruit tip cells to promote angiogenesis: (A) boxplot showing that estimation of the abundance of endothelial cells in the PDCD1^low, PDCD1^hi CD200^low and PDCD1^hi CD200^hi groups using xCell_counter algorithm; (B) volcano map showing differentially expressed genes between PDCD1^hi CD200^hi and PDCD1^hi CD200^low groups (PDCD1^hi CD200^hi: logFC >0.3 and log p‐value >2; PDCD1^hi CD200^low: logFC < −0.3 and log p‐value >2). Angiogenesis pathway‐related genes were highlighted; (C) gene set enrichment analysis (GSEA) showing that the angiogenesis pathway was overrepresented in PDCD1hi CD200hi groups; (D and E) fluorescence micrograph of tube formation by HMEC1 (top) and network mask (bottom). Branch points and capillary length were analysed to evaluate angiogenic activity. The bars represent mean ± SD (n = 3), **p <0.01, ***p < 0.001; (F) multiplex immunofluorescence staining was performed for DAPI (blue), CD4 (white), PD1 (red), CD200 (green) and CD31 (orange). The circles represent the PD1^hi CD200^hi CD4⁺ exhausted T cells. The arrows represent the CD31; (G) spatial distribution of CD31⁺ cells around PD‐1^hi CD200^hi CD4⁻ T cells. The histogram showing the distribution of distances from each the PD‐1^hi CD200^hi CD4⁻ T cells the nearest CD31⁺ cell; (H) the UMAP plot showing the clusters of endothelial cells. Each dot indicates a single cell; (I) the boxplot showing the angiogenesis‐related genes expression in subclusters of endothelial cells; (J) the aggregated cell–cell communication analysis of CD4_ex2 and endothelial cells in BLCA by CellChat; (K) a flow diagram showing the information flow of metabolite–sensor communications from CD4⁺ T cells to endothelial cells through metabolites and sensors. The size of dots represents the number of connections. The lines connect the sender, metabolite, sensor and receiver. The colour of the line indicates the −log10(p‐value), and the width of lines represents the communication score.

FIGURE 4

The PD1^hi CD200^hi CD4 exhausted T cells promote epithelial–mesenchymal transition (EMT): (A) boxplot showing that estimation of the abundance of epithelial and fibroblast cells in the PDCD1^low, PDCD1^hi CD200^low and PDCD1^hi CD200^hi groups using xCel algorithm; (B) volcano map showing differentially expressed genes between PDCD1^hi CD200^hi and PDCD1^hi CD200^low groups (PDCD1^hi CD200^hi: logFC > 0.3 and log p‐value >2; PDCD1^hi CD200^low: logFC < −0.3 and log p‐value >2). The EMT pathway‐related genes were highlighted; (C) correlation of CD200 expression with the expression of transcription factor of EMT. The colour indicates the Spearman correlation coefficient; (D) gene set enrichment analysis (GSEA) showing that the EMT pathway was overrepresented in PDCD1^hi CD200^hi groups; (E) the invasion of T24 and UMUC3 cells was detected by transwell assay after co‐cultured with the PD1^hi CD200^hi CD4⁺ or PD1^hi CD200^low CD4⁺ exhausted T cells. Results are presented as mean ± SD (n = 3), **p < 0.01, ***p < 0.001; (F) the UMAP plot showing the clusters of epithelial cells. Each dot indicated a single cell. Colour‐coded for the cell type; (G) the boxplot showing the EMT‐related genes expression in clusters of epithelial cells; (H) analysis of simulated differentiation trajectories of three epithelial cell subclusters (Epi_CXCL1, Epi_OLFM4, and Epi_COL1A2) in BLCA. Each dot corresponds to a cell, and each colour represents an epithelial cell subcluster; (I) the RNA velocity analysis graph reflected the evolutionary relationship among the three epithelial cell subclusters; (J) the significantly enriched ligand–receptor pairs between epithelial cells and CD4_ex2 subcluster T cells in primary tumour; (K) multiplex immunofluorescence staining was performed for DAPI (blue), CD4 (white), PD1 (green), CD200 (red) and GAS6 (lawngreen). The circles represent the PD1^hi CD200^hi CD4⁺ exhausted T cells. The arrows represent the GAS6; (L) spatial distribution of GAS6⁺ cells around PD‐1^hi CD200^hi CD4⁺ T cells, DAPI (blue), CD4 (white), PD1 (red), CD200 (green) and GAS6 (lawngreen); (M) overall survival between the high and low expressions of GAS6 or AXL groups in The Cancer Genome Atlas (TCGA)‐BLCA; (N) scatter plot showing the correlation between the expression of CD200 and GAS6 in TCGA‐BLCA; (O) barplot showing the correlation between the expression of EMT transcription factor gene, EMT signature and GAS6 in TCGA‐BLCA.

FIGURE 5

PD1^hi CD200^hi CD4⁺ exhausted T cells negatively correlate with the response to ICIs and positively recruit vascular cells in vivo: (A) schematic diagram of mice models; (B) schematic diagram of administration cycles in mice; (C) photographs of tumours dissected out from the three mice groups; (D) tumour volumes were measured once every days, and growth curves of tumours were shown; (E) multiplex immunofluorescence staining was performed for DAPI (blue), Cd4 (white), Pd1 (red) and Cd200 (green); each stain was shown separately and merged. Histograms show the percentages of Pd1hi Cd200hi Cd4⁺ exhausted T cells in anti‐PD1‐responsive and non‐responsive groups; (F) multiplex immunofluorescence staining was performed for DAPI (blue), Cd4 (white), Pd1 (red) and Cd200 (green); each stain was shown separately and merged. Histograms show the percentages of Pd1hi Cd200hi Cd4⁺ exhausted T cells in anti‐PD1‐responsive and non‐responsive groups; (G) multiplex immunofluorescence staining was performed for DAPI (blue), Cd4 (white), Pd1 (red), Cd200 (green) and Ifng (yellow); each stain was shown separately and merged. Histograms show the percentages of Ifng in anti‐PD1‐responsive and non‐responsive groups; (G) multiplex immunofluorescence staining was performed for DAPI (blue), Cd4 (white), Pd1 (red), Cd200 (green) and Cd31 (yellow); each stain was shown separately and merged. Histograms show the percentages of Cd31 in anti‐PD1‐responsive and non‐responsive groups; (H) multiplex immunofluorescence staining was performed for DAPI (blue), Cd4 (white), Pd1 (red), Cd200 (green) and Gas6 (yellow); each stain was shown separately and merged. Histograms show the percentages of Gas6 in anti‐PD1‐responsive and non‐responsive groups.

FIGURE 6

METTL3‐mediated m6A modification enhances GAS6 expression in BLCA cells: (A) the prediction of m6A RNA modification sites in GAS6; (B) GAS6 gene expression between the control and knockout‐METTL3 groups in three cohorts of knockout‐METTL3; (C) methylated RNA immunoprecipitation (RIP) and real‐time polymerase chain reaction analysis of the m6A levels of GAS6; (D and E) the protein levels and the relative mRNA levels of GAS6 after co‐transfection with METTL3 Knockdown (si‐METTL3) into UMUC3 (D) and T24 cells (E); (F) western blotting was performed with METTL3 antibodies to show immunoprecipitation efficiency; (G) RIP assay for the enrichment of GAS6 with METTL3.