Prospective single center trial of next-generation sequencing analysis in metastatic renal cell cancer: the MORE-TRIAL

Characterization of Molecular Heterogeneity Associated With Tumor Microenvironment in Clear Cell Renal Cell Carcinoma to Aid Immunotherapy

Clear cell renal cell carcinoma (ccRCC) is the most common type of kidney cancer and has strong immunogenicity. A systematically investigation of the tumor microenvironment (TME) in ccRCC could contribute to help clinicians develop personalized treatment and facilitate clinical decision-making. In this study, we analyzed the immune-related subtype of ccRCC on the basis of immune-related gene expression data in The Cancer Genome Atlas (TCGA, N = 512) and E-MTAB-1980 (N = 101) dataset, respectively. As a result, two subtypes (C1 and C2) were identified by performing non-negative matrix factorization clustering. Subtype C1 was characterized by increased advance ccRCC cases and immune-related pathways. A higher immune score, stromal score, TMB value, Tumor Immune Dysfunction and Exclusion (TIDE) prediction score, and immune checkpoint genes expression level were also observed in C1. In addition, the C1 subtype might benefit from chemotherapy and immunotherapy. The patients in subtype C2 had more metabolism-related pathways, higher tumor purity, and a better prognosis. Moreover, some small molecular compounds for the treatment of ccRCC were identified between the two subtypes by using the Connectivity Map (CMap) database. Finally, we constructed and validated an immune-related (IR) score to evaluate immune modification individually. A high IR score corresponded to a favorable prognosis compared to a low IR score, while more advanced tumor stage and grade cases were enriched in the low IR score group. The two IR score groups also showed a distinct divergence among immune status, TME, and chemotherapy. The external validation dataset (E-MTAB-1980) and another immunotherapy cohort (IMvigor 210) demonstrated that patients in the high IR score group had a significantly prolonged survival time and clinical benefits compared to the low IR score group. Together, characterization of molecular heterogeneity and IR signature may help develop new insights into the TME of ccRCC and provide new strategies for personalized treatment.

Identification of a four immune-related genes signature based on an immunogenomic landscape analysis of clear cell renal cell carcinoma

Renal clear cell carcinoma (ccRCC) is the most common type of renal cell carcinoma, which has strong immunogenicity. A comprehensive study of the role of immune-related genes (IRGs) in ccRCC is of great significance in finding ccRCC treatment targets and improving patient prognosis. In this study, we comprehensively analyzed the expression of IRGs in ccRCC based on The Cancer Genome Atlas datasets. The mechanism of differentially expressed IRGs in ccRCC was analyzed by bioinformatics. In addition, Cox regression analysis was used to screen prognostic related IRGs from differentially expressed IRGs. We also identified a four IRGs signature consisting of four IRGs (CXCL2, SEMA3G, PDGFD, and UCN) through lasso regression and multivariate Cox regression analysis. Further analysis results showed that the four IRGs signature could effectively predict the prognosis of patients with ccRCC, and its predictive power is independent of other clinical factors. In addition, the correlation analysis of immune cell infiltration showed that this four IRGs signature could effectively reflect the level of immune cell infiltration of ccRCC. We also found that the expression of immune checkpoint genes CTLA-4, LAG3, and PD-1 in the high-risk group was higher than that in the low-risk group. Our research revealed the role of IRGs in ccRCC, and developed a four IRGs signature that could be used to evaluate the prognosis of patients with ccRCC, which will help to develop personalized treatment strategies for patients with ccRCC and improve their prognosis. In addition, these four IRGs may be effective therapeutic targets for ccRCC.