Tumor microenvironment immune subtypes for classification of novel clear cell renal cell carcinoma profiles with prognostic and therapeutic implications

Abstract

Currently, no effective prognostic model of clear cell renal cell carcinoma (ccRCC) based on immune cell infiltration has been developed. Recent studies have identified 6 immune groups (IS) in 33 solid tumors. We aimed to characterize the expression pattern of IS in ccRCC and evaluate the potential in predicting patient prognosis. The clinical information, immune subgroup, somatic mutation, copy number variation, and methylation score of patients with TCGA ccRCC cohort were downloaded from UCSC Xena for further analysis. The most dominant IS in ccRCC was the inflammatory subgroup (immune C3) (86.5%), regardless of different pathological stages, pathological grades, and genders. In the C3 subgroup, stage IV (69.1%) and grade 4 (69.9%) were the least presented. Survival analysis showed that the IS could effectively predict the overall survival (OS) (P < .0001) and disease-specific survival (DSS) (P < .0001) of ccRCC alone, of which group C3 (OS, HR = 2.3, P < .001; DSS, HR = 2.84, P < .001) exhibited the best prognosis. Among the most frequently mutated ccRCC genes, only VHL and PBRM1 were found to be common in the C3 group. The homologous recombination deficiency score was also lower. High heterogeneity was observed in immune cells and immunoregulatory genes of IS. Notably, CD4+ memory resting T cells were highly infiltrating, regulatory T cells (Treg) showed low infiltration, and most immunoregulatory genes (such as CX3CL1, IFNA2, TLR4, SELP, HMGB1, and TNFRSF14) were highly expressed in the C3 subgroup than in other subgroups. Enrichment analysis showed that adipogenesis, apical junction, hypoxia, IL2 STAT5 signaling, TGF-beta signaling, and UV response DN were activated, whereas E2F targets, G2M checkpoint, and MYC targets V2 were downregulated in the C3 group. Immune classification can more accurately classify ccRCC patients and predict OS and DSS. Thus, IS-based classification may be a valuable tool that enables individualized treatment of patients with ccRCC.