Large-scale transcriptome profiles reveal robust 20-signatures metabolic prediction models and novel role of G6PC in clear cell renal cell carcinoma.

ABSTRACT: Clear cell renal cell carcinoma (ccRCC) is the most common and highly malignant pathological type of kidney cancer. We sought to establish a metabolic signature to improve post-operative risk stratification and identify novel targets in the prediction models for ccRCC patients. A total of 58 metabolic differential expressed genes (MDEGs) were identified with significant prognostic value. LASSO regression analysis constructed 20-mRNA signatures models, metabolic prediction models (MPMs), in ccRCC patients from two cohorts. Risk score of MPMs significantly predicts prognosis for ccRCC patients in TCGA (P < 0.001, HR = 3.131, AUC = 0.768) and CPTAC cohorts (P = 0.046, HR = 2.893, AUC = 0.777). In addition, G6PC, a hub gene in PPI network of MPMs, shows significantly prognostic value in 718 cc

SUBMITTER: Xu WH 

PROVIDER: S-EPMC7417710 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature