Abstract
Metabolic alterations play crucial roles in carcinogenesis, tumor progression, and prognosis in clear cell renal cell carcinoma (ccRCC). A risk score (RS) model for ccRCC consisting of disease-associated metabolic genes remains unidentified. Here, we utilized gene set enrichment analysis to analyze expression data from normal and tumor groups from the cancer genome atlas. Out of 70 KEGG metabolic pathways, we found seven and two pathways to be significantly enriched in our normal and tumor groups, respectively. We identified 113 genes enriched in these nine pathways. We further filtered 47 prognostic-related metabolic genes and used Least absolute shrinkage and selection operator (LASSO) analysis to construct a three-metabolic-genes RS model composed of ALDH3A2, B3GAT3, and CPT2. We further tested the RS by mapping Kaplan-Meier plots and receiver operating characteristic curves, the results were promising. Additionally, multivariate Cox analysis revealed the RS to be an independent prognostic factor. Thereafter, we considered all the independent factors and constructed a nomogram model, which manifested in better prediction capability. We validated our results using a dataset from ArrayExpress and through qRT-PCR. In summary, our study provided a metabolic gene-based RS model that can be used as a prognostic predictor for patients with ccRCC.
Highlights
Renal cell carcinoma (RCC) is a frequently diagnosed cancer and represents ∼5 and 3% of all cancers in men and women, respectively [1, 2]
Gene expression information (FPKM, fragments per kilobase per million, including 72 normal samples and 539 tumor samples) and corresponding clinicopathological data of clear cell renal cell carcinoma (ccRCC) patients were collected from The Cancer Genome Atlas (TCGA) as the training set
Gene Set Enrichment Analysis (GSEA) analysis was applied via expression data of TCGA-KIRC and the 70 gene sets correlated with metabolism
Summary
Renal cell carcinoma (RCC) is a frequently diagnosed cancer and represents ∼5 and 3% of all cancers in men and women, respectively [1, 2]. The incidence of RCC has increased annually over the past 20 years [3]. Among the histologic types of RCC, clear cell renal cell carcinoma (ccRCC) is the most common one (80–90%). Surgery is the gold standard for the treatment of localized ccRCC [4]. Around one third of patients with ccRCC relapse [5]. Over the past two decades, the development of ccRCC prognosis has only marginally improved [6]. Investigation of the molecular mechanisms involved in ccRCC would benefit the development of new therapeutic strategies
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
