Identification and Validation of Two Prognostic Autophagy-related Models in Clear Cell Renal Cell Carcinoma

Abstract Background: Clear cell renal cell carcinoma (ccRCC) is one of the most frequent malignancies. Increasing evidence has highlighted the critical roles of autophagy-related genes and autophagy-related long non-coding RNA (lncRNA) in ccRCC development and progression. Therefore, it is necessary to identify novel biomarkers associated with autophagy in ccRCC.Methods: A total of 507 ccRCC patients were included in our study and then randomly divided into a training cohort (n=255) and testing cohort (n=252). Univariate Cox regression models, Lasso regression analyses and multivariate Cox regression models were successively used for constructing gene model and lncRNA model. Receiver-operating characteristic (ROC) curve analysis, Kaplan-Meier (K-M) analysis and more functional analyses were applied for verifying the accuracy of the two models.Results: The autophagy-related genes (ARGs) prognostic model was constructed based on the six ARGs (EIF4EBP1, IFNG, BID, BIRC5, CX3CL1 and RAB24) and five autophagy-related lncRNAs (AC093278.2, AC010326.3, AC099850.3, AC016773.1 and AC009549.1) and then ccRCC patients were significantly stratified into high- and low-risk groups in terms of overall survival (OS). K-M survival analyses indicated that low-risk group had a lower mortality rate than high-risk group in the six-gene prognostic risk model (training cohort: P=4.138e-07; testing cohort: P=1.125e-03) and the same results were obtained in the case of the five-lncRNA prognostic risk model (training cohort: P=4.564e-09; testing cohort: P=2.485e-03). The results of time-dependent ROC curves revealed six-gene prognostic risk model had a higher area under curve (AUC) of 0.765 than the five-lncRNA prognostic risk model at an AUC of 0.759. Therefore, the gene model is an indicator as good as the model constructed by lncRNAs. In addition, further functional analysis indicated these genes were functionally involved in regulation of endopeptidase activity, regulation of peptidase activity, autophagy, human cytomegalovirus infection, shigellosis, autophagy-animal and HIF-1 signaling pathway.Conclusions: A total of six OS-related ARGs and five autophagy-related lncRNA were identified in our current study. The two autophagy-related prediction models including genes and lncRNAs are reliable prognostic and predictive biomarkers for ccRCC.