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

• Published in: Journal of cellular and molecular medicine Vol. 24; no. 16; pp. 9012 - 9027
• Main Authors: Xu, Wen‐Hao, Xu, Yue, Tian, Xi, Anwaier, Aihetaimujiang, Liu, Wang‐Rui, Wang, Jun, Zhu, Wen‐Kai, Cao, Da‐Long, Wang, Hong‐Kai, Shi, Guo‐Hai, Qu, Yuan‐Yuan, Zhang, Hai‐Liang, Ye, Ding‐Wei
• Format: Journal Article
• Language: English
• Published: England John Wiley & Sons, Inc 01.08.2020; John Wiley and Sons Inc
• Subjects: Biomarkers, Tumor - genetics; Cancer therapies; Carcinoma, Renal Cell - genetics; Carcinoma, Renal Cell - pathology; clear cell renal cell carcinoma; Clear cell-type renal cell carcinoma; Cohort Studies; Confidence intervals; Consortia; Dendritic cells; Disease Progression; DNA methylation; Female; G6PC; Gene expression; Gene Expression Regulation, Neoplastic - genetics; Genes; Genomes; Glucose-6-Phosphatase - genetics; Humans; immune infiltration; Immunotherapy; Kidney - pathology; Kidney cancer; Kidney Neoplasms - genetics; Kidney Neoplasms - pathology; Kidneys; Lymphocytes T; Male; Medical prognosis; metabolic prediction models; Metabolism; Original; Prediction models; Prognosis; Proteins; Regression analysis; Risk assessment; Survival analysis; Transcriptome - genetics; Tumor Microenvironment - immunology; Tumors; tumour microenvironment; United States > US; metabolic prediction models; tumour microenvironment; G6PC; clear cell renal cell carcinoma; immune infiltration; prognosis
• ISSN: 1582-1838; 1582-4934; 1582-4934
• DOI: 10.1111/jcmm.15536

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 ccRCC patients from multiply cohorts. Next, G6Pase was detected high expressed in normal kidney tissues than ccRCC tissues. It suggested that low G6Pase expression significantly correlated with poor prognosis (P < 0.0001, HR = 0.316) and aggressive progression (P < 0.0001, HR = 0.414) in 322 ccRCC patients from FUSCC cohort. Meanwhile, promoter methylation level of G6PC was significantly higher in ccRCC samples with aggressive progression status. G6PC significantly participates in abnormal immune infiltration of ccRCC microenvironment, showing significantly negative association with check‐point immune signatures, dendritic cells, Th1 cells, etc. In conclusion, this study first provided the opportunity to comprehensively elucidate the prognostic MDEGs landscape, established novel prognostic model MPMs using large‐scale ccRCC transcriptome data and identified G6PC as potential prognostic target in 1,040 ccRCC patients from multiply cohorts. These finding could assist in managing risk assessment and shed valuable insights into treatment strategies of ccRCC.