Decoding the immune microenvironment in human clear cell renal carcinoma: Identification of key players and their correlation with clinical outcome

Immune cells within the tumor microenvironment (TME) play a critical role in regulating tumor development and response to targeted immunotherapy. T-cell infiltration in clear cell renal carcinoma is well studied. However, their tumor-specific targets, differential activity states and the role of other immunomodulatory cells remain relatively unknown. Here, we describe two approaches to bridge this gap in knowledge by firstly, investigating the potential tumor-specific targets that may be recognized by T-cells in patients with ccRCC. We performed whole exome sequencing and bulk RNA sequencing to screen for expression of tumor-specific frameshift mutations and endogenous retroviral proteins. We found that frameshift mutations are abundant within ccRCC and have a high impact on gene and protein function. Additionally, we identified 15 endogenous retroviral elements that are expressed in our cohort, with a novel discovery of a previously uncategorized gene, ERVMERK9-11. We also found tumor-specific endogenous retroviral elements which were only expressed in a subset of patients in our cohort, but didn’t correspond with tumor stage or grade, indicating their ability to be sources of tumor-specific neoantigens in ccRCC. Secondly, we implemented single cell gene expression analysis in conjunction with spectral flow cytometry on nephrectomy specimens to define immune cell subsets within the TME and identify novel differences between the immune landscape of tumor and tumor-adjacent tissue that may serve as therapeutic targets. We were able to infer protein activity based on gene expression by analyzing the master regulators and their interactions with downstream targets, affecting protein activity. Simultaneous analysis of transcriptome and inferred protein activity allowed us to identify a novel tumor-specific macrophage population co-expressing C1q, ApoE and TREM2, which also correlated with post-surgical disease recurrence. These data highlight the ability of inferential analyses to maximize the potential of scRNA-seq data, and identify TREM2/APOE/C1Q-positive macrophage infiltration as a potential biomarker for ccRCC recurrence and a therapeutic target