A cluster of metabolism-related genes predict prognosis and progression of clear cell renal cell carcinoma
Open Access
- 31 July 2020
- journal article
- research article
- Published by Springer Science and Business Media LLC in Scientific Reports
- Vol. 10 (1), 1-13
- https://doi.org/10.1038/s41598-020-67760-6
Abstract
Clear cell renal cell carcinoma (ccRCC) has long been considered as a metabolic disease characterized by metabolic reprogramming due to the abnormal accumulation of lipid droplets in the cytoplasm. However, the prognostic value of metabolism-related genes in ccRCC remains unclear. In our study, we investigated the associations between metabolism-related gene profile and prognosis of ccRCC patients in the Cancer Genome Atlas (TCGA) database. Importantly, we first constructed a metabolism-related prognostic model based on ten genes (ALDH6A1, FBP1, HAO2, TYMP, PSAT1, IL4I1, P4HA3, HK3, CPT1B, and CYP26A1) using Lasso cox regression analysis. The Kaplan–Meier analysis revealed that our model efficiently predicts prognosis in TCGA_KIRC Cohort and the clinical proteomic tumor analysis consortium (CPTAC_ccRCC) Cohort. Using time-dependent ROC analysis, we showed the model has optimal performance in predicting long-term survival. Besides, the multivariate Cox regression analysis demonstrated our model is an independent prognostic factor. The risk score calculated for each patient was significantly associated with various clinicopathological parameters. Notably, the gene set enrichment analysis indicated that fatty acid metabolism was enriched considerably in low-risk patients. In contrast, the high-risk patients were more associated with non-metabolic pathways. In summary, our study provides novel insight into metabolism-related genes’ roles in ccRCC.This publication has 39 references indexed in Scilit:
- HIF2α-Dependent Lipid Storage Promotes Endoplasmic Reticulum Homeostasis in Clear-Cell Renal Cell CarcinomaCancer Discovery, 2015
- limma powers differential expression analyses for RNA-sequencing and microarray studiesNucleic Acids Research, 2015
- Increased expression of the retinoic acid-metabolizing enzyme CYP26A1 during the progression of cervical squamous neoplasia and head and neck cancerBMC Research Notes, 2014
- External validation and comparison with other models of the International Metastatic Renal-Cell Carcinoma Database Consortium prognostic model: a population-based studyThe Lancet Oncology, 2013
- Metabolism of Kidney Cancer: From the Lab to Clinical PracticeEuropean Urology, 2012
- IL4I1: an inhibitor of the CD8+ antitumor T‐cell response in vivoEuropean Journal of Immunology, 2011
- The genetic basis of kidney cancer: a metabolic diseaseNature Reviews Urology, 2010
- edgeR: a Bioconductor package for differential expression analysis of digital gene expression dataBioinformatics, 2009
- Survival Model Predictive Accuracy and ROC CurvesBiometrics, 2005
- Identification and Characterization of HAOX1, HAOX2, and HAOX3, Three Human Peroxisomal 2-Hydroxy Acid OxidasesOnline Journal of Public Health Informatics, 2000