Geospatial characterization of immune cell distributions and dynamics across the microenvironment in clear cell renal cell carcinoma.

INTRODUCTION: In clear cell renal cell carcinoma (ccRCC), tumor-associated macrophage (TAM) induction of CD8+T cells into a terminally exhausted state has been implicated as a major mechanism of immunotherapy resistance, but a deeper biological understanding is necessary. METHODS: Primary ccRCC tumor samples were obtained from 97 patients between 2004 and 2018. Multiplex immunofluorescence using lymphoid and myeloid markers was performed in seven regions of interest per patient across three predefined zones, and geospatial analysis was performed using Ripley's K analysis, a methodology adapted from ecology. RESULTS: Clustering of CD163+M2 like TAMs into the stromal compartment at the tumor-stroma interface was associated with worse clinical stage (tumor/CD163+nK(75): stage I/II: 4.4 (IQR -0.5 to 5.1); stage III: 1.4 (IQR -0.3 to 3.5); stage IV: 0.6 (IQR -2.1 to 2.1); p=0.04 between stage I/II and stage IV), and worse overall survival (OS) and cancer-specific survival (CSS) (tumor/CD163+nK(75): median OS-hi=149 months, lo=86 months, false-discovery rate (FDR)-adj. Cox p<0.001; median CSS-hi=174 months, lo=85 months; FDR-adj. Cox p<0.001). An RNA-seq differential gene expression score was developed using this geospatial metric, and was externally validated in multiple independent cohorts of patients with ccRCC including: TCGA KIRC, and the IMmotion151, IMmotion150, and JAVELIN Renal 101 clinical trials. In addition, this CD163+ geospatial pattern was found to be associated with a higher TIM-3+ proportion of CD8+T cells, indicative of terminal exhaustion (tumor-core: 0.07 (IQR 0.04-0.14) vs 0.40 (IQR 0.15-0.66), p=0.05). CONCLUSIONS: Geospatial clustering of CD163+M2 like TAMs into the stromal compartment at the tumor-stromal interface was associated with poor clinical outcomes and CD8+T cell terminal exhaustion.

Quantification of T- and B-cell Immune Receptor Distribution Diversity Characterizes Immune Cell Infiltration and Lymphocyte Heterogeneity in Clear Cell Renal Cell Carcinoma.

Immune-modulating systemic therapies are often used to treat advanced cancer such as metastatic clear cell renal cell carcinoma (ccRCC). Used alone, sequence-based biomarkers neither accurately capture patient dynamics nor the tumor immune microenvironment. To better understand the tumor ecology of this immune microenvironment, we quantified tumor infiltration across three distinct ccRCC patient tumor cohorts using complementarity determining region-3 (CDR3) sequence recovery counts in tumor-infiltrating lymphocytes and a generalized diversity index (GDI) for CDR3 sequence distributions. GDI can be understood as a curve over a continuum of diversity scales that allows sensitive characterization of distributions to capture sample richness, evenness, and subsampling uncertainty, along with other important metrics that characterize tumor heterogeneity. For example, richness quantified the total unique sequence count, while evenness quantified similarities across sequence frequencies. Significant differences in receptor sequence diversity across gender and race revealed that patients with larger and more clinically aggressive tumors had increased richness of recovered tumoral CDR3 sequences, specifically in those from T-cell receptor alpha and B-cell immunoglobulin lambda light chain. The GDI inflection point (IP) allowed for a novel and robust measure of distribution evenness. High IP values were associated with improved overall survival, suggesting that normal-like sequence distributions lead to better outcomes. These results propose a new quantitative tool that can be used to better characterize patient-specific differences related to immune cell infiltration, and to identify unique characteristics of tumor-infiltrating lymphocyte heterogeneity in ccRCC and other malignancies. SIGNIFICANCE: Assessment of tumor-infiltrating T-cell and B-cell diversity in renal cell carcinoma advances the understanding of tumor-immune system interactions, linking tumor immune ecology with tumor burden, aggressiveness, and patient survival. See related commentary by Krishna and Hakimi, p. 764.