Objective: Prostate cancer (PCa) is one of the leading causes of death by solid tumors in men, and autophagy plays an important role in tumor progression and treatment. This study was designed to construct and evaluate an autophagy-related prognosis model of PCa with long noncoding RNAs (lncRNAs). Materials and Methods: RNA sequencing data and clinical features were obtained from The Cancer Genome Atlas (TCGA) prostate adenocarcinoma (PRAD) dataset. These data were analyzed by Pearson correlation and Lasso regression to enrich for six autophagy-related prognostic lncRNAs that were used to build a progressionfree interval (PFI) prognostic model. In addition, survival and receiver operating characteristic (ROC) curve analyses were performed to evaluate the PFI's prognostic effect. Moreover, we used a nomogram analysis combined with other clinical features to improve its accuracy. Finally, we verified the biological function of LINC00342 using cell-based assays. Results: Six differentially expressed autophagy-related lncRNAs (LINC00342, AC092171.4, PCAT7, AC048341.2, FGF14-AS2, and AC005180.2) were identified between PCa and adjacent noncancerous tissues from the TCGA-PRAD dataset. A novel risk score model was established based on these six autophagy-related lncRNAs. PCa patients were then stratified into high-or low-risk groups in terms of their PFI; and the area under the ROC curve (AUC) determined to be significant. Moreover, we developed a nomogram with other clinical features that could be used for clinical decision-making. Lastly, we verified the oncogenic role of LINC00342 in promoting autophagy. Conclusions: We developed a novel six autophagy-related lncRNA signature for prediction of PFI in PCa. These lncRNAs may help establish individualized biomarkers and therapeutic targets for patients with PCa. Moreover, we also found an oncogenic role for LINC00342 in autophagy in PCa.