The unique genomic landscape and prognostic mutational signature of Chinese clear cell renal cell carcinoma

The genomic background affects the occurrence and metastasis of cancers, including clear cell renal cell carcinoma (ccRCC). However, reports focusing on the prognostic mutational signature of Chinese ccRCC are lacking. Overall, 929 patients, including a training cohort with Chinese patients (n = 201), a testing cohort with Caucasian patients (n = 274), and a validation cohort (n = 454) were analyzed for the genomic landscape of ccRCC. Then, machine-learning algorithms were used to identify and evaluate the genomic mutational signature (GMS) in ccRCC. Analyses for prognosis, immune microenvironment, association with independent clinicopathological features, and predictive responses for immune checkpoint therapies (ICTs) were performed. The DNA variation data of 929 patients with ccRCC suggested markedly differential genomic mutational frequency of the most frequent genes, such as VHL, PBRM1, BAP1, SETD2, and KDM5C between the Chinese and Caucasian populations. PBRM1 showed significant co-occurrence with VHL and SETD2. We then successfully identified a seven-gene mutational signature (GMSMut) that included mutations in FBN1, SHPRH, CELSR1, COL6A6, DST, ABCA13, and BAP1. The GMSMut significantly predicted progressive progression (P < 0.0001, HR = 2.81) and poor prognosis (P < 0.0001, HR = 3.89) in the Chinese training cohort. Moreover, ccRCC patients with the GMSMut had poor survival rates in the testing cohort (P = 0.020) and poor outcomes were predicted for those treated with ICTs in the validation cohort (P = 0.036). Interestingly, a favorable clinical response to ICTs, elevated expression of immune checkpoints, and increased abundance of tumor-infiltrated lymphocytes, specifically CD8+ T cells, Tregs, and macrophages, were observed in the GMSMut cluster. This study described the pro-tumorigenic GMSMut cluster that improved the prognostic accuracy in Chinese patients with ccRCC. Our discovery of the novel independent prognostic signature highlights the relationship between tumor phenotype and genomic mutational characteristics of ccRCC.