Abstract
INTRODUCTION: Introduction. Renal cell carcinoma (RCC) is a common malignant tumor worldwide, and to explore, accurate prediction models are essential to the diagnosis and treatment. METHODS: In the present study, the profile expression of RCC patients for long non-coding RNAs (lncRNAs) were obtained from the database of The Cancer Genome Atlas (TCGA). The Gene Set Enrichment Analysis (GSEA) showed that the gene sets related to autophagy are significantly differentially expressed among the paired normal tissues and RCC. Multivariate and univariate Cox analyses were used to construct the gene signature related to prognosis. Receiver Operating Characteristic (ROC) dependent on the time factor and the Kaplan-Meier curves are used for evaluating identified signatures. For gene signature combination, a nomogram with associated clinical constraints was designed. RESULTS: Multivariate and Univariate Cox analyses presented seven autophagy-related lncRNAs were significantly correlated with Overall Survival (OS) for people with RCC. Risk scores of lncRNA prognostic signature, related to autophagy helped in distinguishing the patients accurately among the low-risk and high-risk RCC based on age, sex, grade of tumor, T, M, N, and AJCC stages. The RCC condition patients, as per their signature were put into the category of low and high-risk groups, having varying prognostic outcomes. Gene signature is an independent prognosticator for OS, accurately predicting 3-5 year survival time for RCC patients from either of the two groups. GSEA revealed that high-risk scores of the prognostic seven-long non-coding signature correlate with immune-regulatory and cancer, signaling pathways, whereas a low-risk score correlates with metabolism. The quantitative reverse chain reaction of transcription-polymerase verified differential expression of seven lncRNAs autophagy-related samples. CONCLUSION: The results depict that seven autophagy-related lncRNA prognostic signature helps in predicting the prognosis accurately among people with RCC.