Integrated analysis of tertiary lymphoid structures and immune infiltration in ccRCC microenvironment revealed their clinical significances: a multicenter cohort study

Abstract

Background: Tertiary lymphoid structures (TLSs) serve as organized lymphoid aggregates that influence immune responses within the tumor microenvironment. This study aims to investigate the characteristics and clinical significance of TLSs and tumor-infiltrating lymphocytes (TILs) in clear cell renal cell carcinoma (ccRCC).

Methods: TLSs and TILs were analyzed comprehensively in 754 ccRCC patients from 6 academic centers and 532 patients from The Cancer Genome Atlas. Integrated analysis was performed based on single-cell RNA-sequencing datasets from 21 ccRCC patients to investigate TLS heterogeneity in ccRCC. Immunohistochemistry and multiplex immunofluorescence were applied. Cox regression and Kaplan-Meier analyses were used to reveal the prognostic significance.

Results: The study demonstrated the existence of TLSs and TILs heterogeneities in the ccRCC microenvironment. TLSs were identified in 16% of the tumor tissues in 113 patients. High density (>0.6/mm²) and maturation of TLSs predicted good overall survival (OS) (p<0.01) in ccRCC patients. However, high infiltration (>151) of scattered TILs was an independent risk factor of poor ccRCC prognosis (HR=14.818, p<0.001). The presence of TLSs was correlated with improved progression-free survival (p=0.002) and responsiveness to therapy (p<0.001). Interestingly, the combination of age and TLSs abundance had an impact on OS (p<0.001). Higher senescence scores were detected in individuals with immature TLSs (p=0.003).

Conclusions: The study revealed the contradictory features of intratumoral TLSs and TILs in the ccRCC microenvironment and their impact on clinical prognosis, suggesting that abundant and mature intratumoral TLSs were associated with decreased risks of postoperative ccRCC relapse and death as well as favorable therapeutic response. Distinct spatial distributions of immune infiltration could reflect effective antitumor or protumor immunity in ccRCC.

Keywords: Immunotherapy; Kidney Cancer; Tumor infiltrating lymphocyte - TIL; Tumor microenvironment - TME.

Figure 1

The expression characteristics of TLSs in retrospectively collected ccRCC tissue microarrays. (A) Thumbnail of tumor microarray, showing the expression of TLSs in ccRCC. Scale bar, 5 mm and 500 µm; (B) Representative figures of TLSs in ccRCC. Scale bar, 250 µm; (C) Number of TLSs in ccRCC cases; (D) Association between TLS density and OS (p=0.005); (E) Density of TLSs in non-relapse and relapse groups (p=0.022); (F) Proportion of B cells within TLSs in non-relapse and relapse groups (p=0.011); good and bad outcome groups (p=0.022); (G) Association between TLSs maturity and OS (p=0.005). ccRCC, clear cell renal cell carcinoma; OS, overall survival; TLSs, tertiary lymphoid structures.

Figure 2

Evaluation of TLSs in ccRCC using multiplex immunofluorescence. The staining images combining CD3 (red), CD8 (cyan), CD4 (yellow), CD21 (orange), CD56 (green) and CD20 (magenta) in one tissue session and CD3 (red), CD68 (cyan), CD31 (yellow), CD21 (orange), CD163 (green) and CD20 (magenta) in another serial section. TLSs are circled with dotted white lines. Scale bars, 50 µm. ccRCC, clear cell renal cell carcinoma; TLSs, tertiary lymphoid structures.

Figure 3

Distinct expression of TILs in ccRCC tissue samples. (A) Detection of TILs expression levels in ccRCC by CD3 and CD20 immunochemistry. Scale bar, 500 µm and 100 µm; (B) The representative figures of TILs expression in patients with different OS. Scale bar, 250 µm. ccRCC, clear cell renal cell carcinoma; OS, overall survival; TILs, tumor-infiltrating lymphocytes.

Figure 4

The correlation between TILs and clinical outcomes in ccRCC patients. (A) ROC curves of TIL-T (AUC=0.7702, cut-off=74.5) and TIL-B (AUC=0.7828, cut=off=59.5) in the training cohort; (B) ROC curve of TILs (AUC=0.798, cut-off=151) in the training cohort; (C) Kaplan-Meier survival curves of TIL-T (p=0.02) and TIL-B (p=0.009) in the testing cohort; (D) Kaplan-Meier survival curve of TILs in the testing cohort (p<0.001); (E) Violin plots of the IHC score of TIL-T (p<0.001), TIL-B (p<0.001), TIL (p<0.001) in different outcome groups; (F) The scatter diagram shows the correlation between TIL-T and TIL-B (r=0.742, p<0.001). AUC, area under curve; ccRCC, clear cell renal cell carcinoma; IHC, immunohistochemistry; ROC, receiver operation curve; TILs, tumor-infiltrating lymphocytes; TLSs, tertiary lymphoid structures.

Figure 5

The immune infiltration and clinical characteristics predict the OS of ccRCC patients. (A) Forest plot of the effect of patient characteristics on OS by subgroup; (B) Nomogram for predicting OS at 1, 3 or 5 years after surgery; (C) Calibration plots of the nomogram for predicted and actual results of 3 years and 5 years OS; (D) Kaplan-Meier survival curves of TLS-B cell density (p=0.037) and TLS-TIL density (p<0.001) with clinical outcome. *p<0.05; **p<0.01; ***p<0.001. ccRCC, clear cell renal cell carcinoma; OS, overall survival; TILs, tumor-infiltrating lymphocytes; TLSs, tertiary lymphoid structures.

Figure 6

The correlation between TLSs and response to first-line TKI+IO combination therapies of ccRCC. (A) Representative figures of distinct TLSs expression in responders and non-responders to treatment of ccRCC. Scale bar, 500 µm and 250 µm; (B) TLS maturity (p=0.02) and density (p<0.001) in response and non-response groups; (C) Kaplan-Meier survival curve shows progression-free survival in TLS+and TLS- patients (p=0.002). ccRCC, clear cell renal cell carcinoma; IO, immunotherapy; TKI, tyrosine kinase inhibitor; TLSs, tertiary lymphoid structures.

Figure 7

Age-related survival analysis and scRNA-seq analysis of TLS aging. (A) Kaplan-Meier survival curve of age-TLS density and clinical prognosis (p<0.001); (B) Kaplan-Meier survival curve of age-TLS maturity and clinical prognosis (p<0.001); (C) Kaplan-Meier survival curve of age-TLS density in TCGA dataset (p=0.005); (D) TLS expression level in young and old groups; (E) UMAP plot showing eight major cell clusters after Harmony treatment of the scRNA-seq datasets; (F) UMAP plot showing six major B cell subgroups; (G) UMAP plot showing senescence scores of B cells; (H) Heatmap showing the signature genes in B cell subgroups; (I) Volcano plot showing the differentially expressed genes between old and young groups in B cell cluster; (J) Statistics of senescence scores in young and old groups among all subsets; (K–L) Pathway activity scores of aging in young and old groups. UMAP, uniform manifold approximation and projection. *p<0.05; ***p<0.001. scRNA-seq, single cell RNA-sequencing; TCGA, The Cancer Genome Atlas; TLS, tertiary lymphoid structure; UMAP, uniform manifold approximation and projection.