RESUMEN
LncRNAs involve in the autophagy to regulate prostate cancer (PCA) initiation and progression. Therefore, it urges to explore more significant AR-lncRNAs in PCa. mRNA data and clinical information of PCa were achieved from TCGA database, and ARGs were obtained from the HADb. AR-lncRNAs were identified by correlation analysis of DE ARGs and lncRNAs. Univariate Cox regression, LASSO regression, and multivariate Cox regression were used to identify the prognostic AR-lncRNA signature and constructed a risk model. GESA was used to biological function analysis between high- and low-risk score group. A nomogram was constructed and used to predicate the survival of PCa patients. A calibration curve was used to determine the accuracy of the predication model. AR-related ceRNA network was constructed by correlation analysis. Expression of six AR-related lncRNAs were detected by qRT-PCR. 222 ARGs and 385 AR-lncRNAs were screened from PCa and normal tissues, and 17 AR-lncRNAs were identified as prognostic signature for PCa. Based on the expression of prognostic signature, a risk score was calculated, and PCa samples were distributed into high- and low-risk score groups. The biological function and predicated value of the prognostic signature were also examined. Finally, based on the correlation between each ARG and its prognostic signature, three modules of AR-lncRNA-miRNA-mRNA regulatory networks were constructed based on 6 AR-lncRNAs, 17 miRNAs, and 12 ARGs. And we found that AC012085.2, UBXN10-AS1, LINC00261 downregulated, whereas AP004608.1, AC104667.2, AC008610.1 upregulated in PCa compared with BPH tissues. Our finding supplied the potential AR-lncRNAs prognostic signature for PCa.