Identification of an Autophagy-Related Prognostic Signature for Clear Cell Renal Cell Carcinoma

Abstract

Abnormal autophagy is closely related to the development of cancer. Many studies have demonstrated that autophagy plays an important role in biological function in clear cell renal cell carcinoma (ccRCC). This study aimed to construct a prognostic signature for ccRCC based on autophagy-related genes (ARGs) to predict the prognosis of ccRCC. Differentially expressed ARGs were obtained from ccRCC RNA-seq data in The Cancer Genome Atlas (TCGA) database. ARGs were enriched by gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). The prognostic ARGs used to construct the risk score models for overall survival (OS) and disease-free survival (DFS) were identified by Cox regression analyses. According to the median value of the risk score, patients were divided into a high-risk group and a low-risk group. The OS and DFS were analyzed by the Kaplan-Meier method. The predictive accuracy was determined by a receiver operating characteristic (ROC) curve analysis. Additionally, we performed stratification analyses based on different clinical variables and evaluated the correlation between the risk score and the clinical variables. The differentially expressed ARGs were mainly enriched in the platinum drug resistance pathway. The prognostic signatures based on 11 ARGs for OS and 5 ARGs for DFS were constructed and showed that the survive time was significantly shorter in the high-risk group than in the low-risk group (P < 0.001). The ROC curve for OS exhibited good predictive accuracy, with an area under the curve value of 0.738. In the stratification analyses, the OS time of the high-risk group was shorter than that of the low-risk group stratified by different clinical variables. In conclusion, an autophagy-related signature for OS we constructed can independently predict the prognosis of ccRCC patient, and provide a deep understanding of the potential biological mechanisms of autophagy in ccRCC.