Single-Cell Analysis Identifies Distinct Populations of Cytotoxic CD4+ T Cells Linked to the Therapeutic Efficacy of Immune Checkpoint Inhibitors in Metastatic Renal Cell Carcinoma

Abstract

Background: The involvement of cytotoxic CD4⁺ T cells (CD4⁺ CTLs) and their potential role in dictating the response to immune checkpoint inhibitors (ICIs) in patients with metastatic renal cell carcinoma (mRCC) remains an unexplored area of research.

Methods: Utilizing single-cell RNA sequencing, we analyzed the immunophenotype and expression patterns of CD4⁺ T lymphocyte subtypes in mRCC patients, followed by preliminary validation via multi-immunofluorescent staining. In addition, we obtained a comprehensive immunotherapy dataset encompassing single-cell RNA sequencing datasets and bulk RNA-seq cohorts from the European Genome-Phenome Archive and ArrayExpress database. Utilizing the CIBERSORTx deconvolution algorithms, we derived a signature score for CD4⁺ CTLs from the bulk-RNA-seq datasets of the CheckMate 009/025 clinical trials.

Results: Single-cell analysis of CD4⁺ T lymphocytes in mRCC reveals several cancer-specific states, including diverse phenotypes of regulatory T cells. Remarkably, we observe that CD4⁺ CTLs cells constitute a substantial proportion of all CD4⁺ T lymphocyte sub-clusters in mRCC patients, highlighting their potential significance in the disease. Furthermore, within mRCC patients, we identify two distinct cytotoxic states of CD4⁺ T cells: CD4⁺GZMK⁺ T cells, which exhibit a weaker cytotoxic potential, and CD4⁺GZMB⁺ T cells, which demonstrate robust cytotoxic activity. Both regulatory T cells and CD4⁺ CTLs originate from proliferating CD4⁺ T cells within mRCC tissues. Intriguingly, our trajectory analysis indicates that the weakly cytotoxic CD4⁺GZMK⁺ T cells differentiate from their more cytotoxic CD4⁺GZMB⁺ counterparts. In comparing patients with lower CD4⁺ CTLs levels to those with higher CD4⁺ CTLs abundance in the CheckMate 009 and 25 immunotherapy cohorts, the latter group exhibited significantly improved OS and PFS probability.

Conclusion: Our study underscores the pivotal role that intratumoral CD4⁺ CTLs may play in bolstering anti-tumor immunity, suggesting their potential as a promising biomarker for predicting response to ICIs in patients with mRCC.

Keywords: cytotoxic CD4+ T cells; granzyme K and granzyme B; immune checkpoint inhibitors; renal cell carcinoma; single-cell analysis.

Figure 1

CD4+ T cells encompass cytotoxic and regulatory states that are enriched in the environment of metastatic renal cell carcinoma. (A) Uniform Manifold Approximation and Projection (UMAP) visualization along with cell marker gene analysis of single-cell RNA sequencing data from metastatic renal cell carcinoma. Each dot represents a single cell and is colored according to its respective cluster. Specifically, MKI67 identifies the CD4_PROLIFERATION cell cluster, CCR7 marks the CD4_naive cell cluster, FOXP3 represents the CD4_Regulatory cell cluster, and GZMs designate the CD4_CYTOTOXIC cell cluster; (B–E) Differentially expressed genes were identified between each cell cluster, including the CD4_CYTOTOXIC, CD4_PROLIFERATION, CD4_Regulatory, and CD4_naive clusters. CD4_CYTOTOXIC versus other cell clusters (B); CD4_Regulatory versus other cell clusters (C); CD4_naive versus other cell clusters (D); CD4_PROLIFERATION versus other cell clusters (E); The CD4_CYTOTOXIC cluster was enriched in pathways pertaining to T cell cytotoxicity (F). Conversely, the CD4_Regulatory cluster was enriched in pathways that promote T cell tolerance induction (G). The CD4_naive cell cluster was associated with cell differentiation processes, including T cell differentiation (H). Finally, the CD4_PROLIFERATION signature exhibited a pronounced mitotic nuclear division and cell proliferation (I).

Figure 2

Renal cell carcinoma exhibits heterogeneous proliferation and cytotoxic CD4+ T cell states. (A) Gene set enrichment analysis revealed that the CD4_CYTOTOXIC cluster was significantly enriched in immune activation pathways; (B) A higher-resolution clustering analysis further elucidated the heterogeneous nature of renal cell carcinoma, demonstrating diverse proliferation, regulatory, and cytotoxic CD4+ T cell states; (C) Notably, the CD4_PROLIFERATION cluster comprised distinct cell groups that co-expressed either cytotoxic or regulatory genes, but not both simultaneously; (D) Within the CD4_CYTOTOXIC cluster, two distinct cytotoxic states were identified: CD4_GZMK CTLs and CD4_GZMB CTLs. These findings were visualized using the Uniform Manifold Approximation and Projection (UMAP) method, where each dot represents a single cell and is colored according to its respective cluster. CTLs refer to Cytotoxic CD4+ T Cells.

Figure 3

Multiplex immunofluorescent staining was performed to visualize CD4⁺GZMK⁺ and CD4⁺GZMB⁺ cytotoxic T cells in renal clear cell carcinoma tissues. (A) Nuclei were labeled with DAPI (blue). (B) CD4 expression was marked in red. (C) GZMK expression was indicated by green fluorescence. (D) GZMB expression was labeled in white. (E) The merged image shows the co-localization of DAPI, CD4, GZMK, and GZMB signals. CD4⁺ cells that concurrently expressed GZMK or GZMB were highlighted by arrowheads. Scale bar represents 200 μm.

Figure 4

The expression profile and phenotypic traits of cytotoxic CD4+ T cells in renal cell carcinoma (RCC). (A) CD4_GZMB cytotoxic T cells (CTLs) exhibited a heightened expression of cytotoxic lineage genes, such as GZMB, GNLY, PRF1, TBX1, and NKG7, in RCC samples; (B) In contrast, CD4_Regulatory cells displayed a greater abundance of regulatory lineage genes, including CTLA4 and TIGIT; (C) The proportion of CD4+ CTLs within RCC samples was evaluated, encompassing CD4_GZMK CTLs, CD4_GZMB CTLs, CD4_CTL_PROLIFERATION, Tn, Treg_PROLIF, Treg_LAYN_tex, and Treg_HSPA1A_ptex. CTLs refer to Cytotoxic CD4+ T Cells.

Figure 5

The CD4_GZMB CTLs cluster exhibited greater cytotoxicity than CD4_GZMK in the renal cell carcinoma (RCC) microenvironment. (A) High-resolution clustering analysis revealed that multiple active cytotoxic CD4⁺ T cell states, including CD4_GZMK, CD4_GZMB, and CD4_CTL_PROLIF, were enriched in RCC samples; (B) Gene set enrichment analysis demonstrated that the CD4_GZMB cluster was significantly enriched in pathways related to cytotoxicity; (C) Notably, the CD4_GZMB cluster showed higher AUC scores associated with T_CELL_MEDIATED_CYTOTOXICITY and GO_BP_CYTOLYSIS, indicating a stronger cytotoxic potential.

Figure 6

Both Regulatory T Cells And CD4+ CTLs Are Derives From Proliferating CD4+ T Cells In RCC Tissues. (A) According to CytoTRACE analysis, CD4_PROLIFERATION cells, comprising Treg_PROLIF and CD4_CTL_PROLIF, exhibited notably high stemness scores and a minimal degree of differentiation. Conversely, CD4_GZMK CTLs and Treg_LAYN displayed the lowest stemness scores and a pronounced level of differentiation in RCC tissues; (B) The cytotoxic linkage genes GZMK, TNFSF5, and the transcription factor FOS were found to correlate with a more differentiated state in CD4+ T cells; (C) Pseudotime trajectory analysis revealed that CD4_PROLIFERATION cells segregated into Treg_PROLIF and CD4_CTL_PROLIF groups, with each group aligning along distinct branches representing proliferating cytotoxic or regulatory CD4+ T lymphocytes; (D) Hierarchical clustering analysis highlighted the striking similarity in expression patterns between CD4_PROLIFERATION and CD4_Regulatory cells. Furthermore, when compared to CD4_GZMK CTLs, the expression patterns of CD4_GZMB CTLs and CD4_PROLIFERATION displayed a more consistent alignment.

Figure 7

Cytotoxic CD4+ T Cells Predicts Clinical Response To Immune Checkpoint Inhibitors. (A) Two distinct renal cell carcinoma patients were analyzed post-treatment with immune checkpoint inhibitors (9 weeks of Nivolumab), one demonstrating a responder status and the other a non-responder status; (B) A uniform manifold approximation and projection (UMAP) analysis revealed that CD8+ T cells accounted for a larger percentage compared to CD4+ T cells in both renal cell carcinoma patients; (C) The UMAP analysis further delineated the distribution of CD4+ T cells between the responder and non-responder patients following immune checkpoint inhibitor (ICI) treatment. CD4+ T cells from responder patients exhibited elevated expression levels of cytotoxic linkage genes and transcription factors, including GZMK and NR4A2. Conversely, CD4+ T cells from non-responder patients co-expressed high levels of regulatory and inhibitory linkage molecules, such as FOXP3 and CTLA4; (D) Among CD8+ T cells, those from responder patients displayed higher expression levels of GZMK and NR4A2. In contrast, non-responder patients exhibited a higher percentage of cells expressing PDCD1/PD1.

Figure 8

Cytotoxic CD4+ T Cells (CD4+ CTLs) improve Clinical Response To Immune Checkpoint Inhibitors. (A) Renal cell carcinoma (RCC) patients treated with immune checkpoint inhibitors (ICIs) exhibited an increased proportion of CD4+ cytotoxic T lymphocytes; (B) Analysis of the Checkmate 009 ICIs cohort revealed that patients with a higher proportion of CD4+ CTLs achieved improved overall survival and progression-free survival probabilities. (C) However, in the Checkmate 010 and Checkmate 025 cohorts, no significant difference in the proportion of CD4+ CTLs was observed between ICIs responders and non-responders; (D) Interestingly, a higher proportion of CD4+ CTLs in clear cell renal cell carcinoma (ccRCC) patients from the Checkmate 010 and Checkmate 025 ICIs cohorts was associated with a decreased progression-free survival probability; (E) The Checkmate 025 everolimus cohort demonstrated that the expression of CD4+ CTLs was not correlated with overall survival or progression-free survival probabilities.