Landscape of immune cell infiltration in clear cell renal cell carcinoma to aid immunotherapy

Abstract

The tumor microenvironment, comprised of tumor cells and tumor-infiltrating immune cells, is closely associated with the clinical outcome of clear cell renal cell carcinoma (ccRCC) patients. However, the landscape of immune infiltration in ccRCC has not been fully elucidated. Herein, we applied multiple computational methods and various datasets to reveal the immune infiltrative landscape of ccRCC patients. The tumor immune infiltration (TII) levels of 525 ccRCC patients using a single-sample gene were examined and further categorized into immune infiltration subgroups. The TII score was characterized by distinct clinical traits and showed a significant divergence based on gender, grade, and stage. A high TII score was associated with the ERBB signaling pathway, the TGF-β signaling pathway, and the MTOR signaling pathway, as well as a better prognosis. Furthermore, patients with high TII scores exhibited greater sensitivity to pazopanib. The low TII score was characterized by a high immune infiltration level of CD8⁺ T cells, T follicular helper cells, and regulatory T cells (Tregs). Moreover, the immune check point genes, including CTLA-4, LAG3, PD-1, and IDO1, presented a high expression level in the low TII score group. Patients in the high TII score group demonstrated significant therapeutic advantages and clinical benefits. The findings in this study have the potential to assist in the strategic design of immunotherapeutic treatments for ccRCC.

Keywords: clear cell renal cell carcinoma; immune cell infiltration; immune check point; immunotherapy; tumor microenvironment.

FIGURE 1

The landscape of tumor immune infiltration in clear cell renal cell carcinoma (ccRCC) patients. (A) Cluster survival analysis of the five subgroups. (B) Principal component analysis supported the stratification into five subgroups of ccRCC. (C) Comparisons of the expression level of PD1 in five subgroups. (D) Comparisons of the expression level of PD‐L1 in five subgroups

FIGURE 2

The association between clinical traits and subgroups. (A) A heatmap including the clinical traits and 29 immune signatures. (B) Cluster survival analysis of subgroups C1&4 and C2&3&5

FIGURE 3

Consensus clustering of common differentially expressed genes among two subgroups (C1&4 and c2&3&5) to categorize patients into three gene clusters (A, B, and C)

FIGURE 4

Identification of gene cluster. (A) KM survival curve analysis of the three gene clusters. (B) Principal component analysis supported the stratification into three gene clusters of clear cell renal cell carcinoma (ccRCC). (C) Comparisons of expression level of PD1 in three gene clusters. (D) Comparisons of expression level of PD‐L1 in three gene clusters

FIGURE 5

Tumor immune infiltration in three gene clusters. (A) The 16 immune cell infiltration level in three gene clusters. (B) The 13 immune function level in three gene clusters (C) The immune score in three gene clusters. (D) The stromal score in three gene clusters

FIGURE 6

KEGG pathway enrichment analysis for the gene signature A (A) and signature B (B), respectively

FIGURE 7

Construction of the tumor immune infiltration (TII) score. (A) KM survival curve analysis between high TII score and low TII score groups. (B) Alluvial diagram of TII gene cluster distribution in groups with distinct gene clusters, TII scores, and survival status. (C) Gene set enrichment analysis (GSEA) for the high TII score group. (D) KM survival curve analysis between high TMB value and low TMB value groups. (E) KM survival curves analysis for clear cell renal cell carcinoma (ccRCC) patients stratified by both TMB and TII scores

FIGURE 8

Tumor immune infiltration in tumor immune infiltration (TII) score. (A) The 16 immune cell infiltration level in the two TII score groups. (B) The 13 immune function level in the two TII score groups

FIGURE 9

Expression level of immune check point (A) and sensitivity of four chemo drugs (B) evaluation in the two tumor immune infiltration (TII) score groups

FIGURE 10

Small molecular compounds identification based on the differentially expressed genes. (A) Volcano plot for the differentially expressed genes; green dots represent the downregulated genes, red dots represent the upregulated genes, and the gray dots represent the non‐significant genes. (B) Heatmap of the differentially expressed genes expression. (C) Small molecular compound identification through CMap analysis based on the differentially expressed genes

FIGURE 11

Clinical significance of the tumor immune infiltration (TII) score. (A) Clinical divergence of clinical traits (survival status, age, gender, stage, and grade) in the high TII score group and the low TII score group using the Fisher test or the χ²‐ test. (B) Multivariate Cox regression analysis for the clinical trait (age, gender, stage, and grade) and TII score in the overall survival and disease‐free survival of clear cell renal cell carcinoma (ccRCC) patients

FIGURE 12

Validation of the tumor immune infiltration (TII) score. (A) KM survival curve analysis of tumor immune infiltration (TII) score group in the disease‐free survival dataset. (B) KM survival curve analysis of the TII score group in the papillary renal cell carcinoma dataset. (C) KM survival curve analysis of TII score group in the IMvigor210 dataset. (D) Rate of clinical response (CR/PR and SD/PD) in TII score groups in the IMvigor210 cohort