Abstract 3873: Profiling the tumor microenvironment within clear cell renal cell carcinoma by single-nuclei RNA-Seq

Abstract

Abstract Clear cell renal carcinoma (ccRCC) appears as one of the most immune infiltrated tumors in pan-cancer comparisons. A systematic characterization of the immune microenvironment of ccRCC is important for understanding the disease progression and would be beneficial to predicting disease outcomes. To better understand the cellular components within the tumor microenvironment (TME), the interactions among different cell types, and the contribution to disease outcomes, we collected 34 ccRCC tumor samples for single-nuclei RNA-Seq (snRNASeq) profiling. We obtained 161312 cells in total, including 6791 stroma cells (endothelial cells, fibroblasts and myofibroblasts) and 38918 immune cells (lymphoid and myeloid populations).Analysis of cell-cell-interactions suggests tumor cells interact most frequently with stroma and immune cells. Of interest, we noticed some ligand-receptor pair interactions commonly found among all samples, such as VEGFA from tumor cells with VEGFR1/2 from endothelial cells, suggesting the presence of angiogenesis. Within endothelial populations, we found a common interaction between ANGPT2 and TEK, whose interaction scores are moderately correlated with lymphocyte percentages across samples, suggesting this interaction could contribute to endothelium leakage and lymphocytes recruitment. To better understand the immune cell subtype/states within each immune cell type, we further distinguished 14 different subpopulations within macrophages according to key marker expressions. The presence of the subpopulations suggest diverse states and heterogeneous functions within macrophages. Of note, the expression of iron uptake receptor TFRC is elevated in higher-grade tumors. Higher TFRC expression is associated with poorer prognosis, which is also validated by the CPTAC discovery cohort using bulk proteomics data. In summary, our study showcases the potential of using snRNA-Seq to profile the TME of ccRCC, in identifying important cell-cell interactions and predicting disease outcomes. Citation Format: Ruiyang Liu, Ilya Strunilin, Yige Wu, Alla Karpova, Siqi Chen, Chia-Kuei Mo, Yize Li, Feng Chen, Li Ding. Profiling the tumor microenvironment within clear cell renal cell carcinoma by single-nuclei RNA-Seq [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3873.