Background: Circular RNA (circRNA) is a novel class noncoding RNA (ncRNA) that plays a critical role in various cancers, including prostate cancer (PCa). However, the clinical significance, biological function, and molecular mechanisms of circRNAs in prostate cancer remain to be elucidated.Methods: A circRNA array was performed to identified the differentially expressed circRNAs. circPDE5A was identified as a novel circRNA which downregulated in clinical samples. Functionally, the in vitro and in vivo assays were applied to explore the role of circPDE5A in PCa metastasis. Mechanistically, the interaction between circPDE5A and WTAP was verified using RNA pulldown followed by mass spectrometry, RNA Immunoprecipitation (RIP) assays. m⁶A methylated RNA immunoprecipitation sequencing (MeRIP-seq) was then used to identified the downstream target of circPDE5A. Chromatin immunoprecipitation assay (ChIP) and dual-luciferase reporter assay were used to identified transcriptional factor which regulated circPDE5A expression.Results: circPDE5A was identified downregulated in PCa tissues compared to adjacent normal tissue and was negatively correlated with gleason score of PCa patients. circPDE5A inhibits PCa cells migration and invasion both in vitro and in vivo. circPDE5A blocks the WTAP-dependent N6-methyladenisine (m⁶A) methylation of eukaryotic translation initiation factor 3c (EIF3C) mRNA by forming the circPDE5A-WTAP complex, and finally disrupts the translation of EIF3C. Moreover, the circPDE5A-dependent decrease in EIF3C expression inactivates the MAPK pathway and then restrains PCa progression.Conclusions: Our findings demonstrate that FOXO4-mediated upregulation of circPDE5A controls PCa metastasis via the circPDE5A-WTAP-EIF3C-MAPK signaling pathway and could serve as a potential therapeutic targer for PCa.

Prostate cancer (PC) is one of the most common male cancers worldwide. Until now, there is no consensus about using urinary metabolomic profiling as novel biomarkers to identify PC. In this study, urine samples from 50 PC patients and 50 non-cancerous individuals (control group) were collected. Based on ¹H nuclear magnetic resonance (¹H-NMR) analysis, 20 metabolites were identified. Subsequently, principal component analysis (PCA), partial least squares-differential analysis (PLS-DA) and ortho-PLS-DA (OPLS-DA) were applied to find metabolites to distinguish PC from the control group. Furthermore, Wilcoxon test was used to find significant differences between the two groups in metabolite urine levels. Guanidinoacetate, phenylacetylglycine, and glycine were significantly increased in PC, while L-lactate and L-alanine were significantly decreased. The receiver operating characteristics (ROC) analysis revealed that the combination of guanidinoacetate, phenylacetylglycine, and glycine was able to accurately differentiate 77% of the PC patients with sensitivity = 80% and a specificity = 64%. In addition, those three metabolites showed significant differences in patients stratified for Gleason score 6 and Gleason score ≥7, indicating potential use to detect significant prostate cancer. Pathway enrichment analysis using the KEGG (Kyoto Encyclopedia of Genes and Genomes) and the SMPDB (The Small Molecule Pathway Database) revealed potential involvement of KEGG “Glycine, Serine, and Threonine metabolism” in PC. The present study highlights that guanidinoacetate, phenylacetylglycine, and glycine are potential candidate biomarkers of PC. To the best knowledge of the authors, this is the first study identifying guanidinoacetate, and phenylacetylglycine as potential novel biomarkers in PC.

Background: Mediterranean dietary pattern has attracted great attention in terms of its effect on human health. However, whether Mediterranean dietary pattern is an independent protective factor for prostate cancer remains controversial. Our goal was to evaluate this association by conducting a meta-analysis of observational studies. Methods: We searched the PubMed and EMBASE database through February 2019 for relevant studies that examined the association between Mediterranean Diet and prostate cancer risk. The combined risk estimates were computed using a DerSimonian random-effects model. Results: A total of 10 eligible studies were included in this meta-analysis. The pooled risk estimates and 95% confidence interval (CI) in relation to Mediterranean diet pattern were 0.95 (95% CI: 0.90 to 1.01) for total prostate cancer, 0.93 (95% CI: 0.75 to 1.14) for advanced prostate cancer, 0.96 (95% CI: 0.81 to 1.14) for localized prostate cancer, and 0.92 (95% CI: 0.76 to 1.11) for fatal prostate cancer. There was no evidence of heterogeneity for total (P = .326, I² = 12.7%), localized (P = .706, I² = 0.0%) and fatal prostate cancer (P = .282, I² = 13.0%), but not for advanced prostate cancer (P = .018, I² = 63.4%). Conclusion: This large meta-analysis of observational studies suggests that Mediterranean dietary pattern has no relationship with prostate cancer risk.

Circular RNAs (circRNAs) have been recognized as important regulators in tumorigenesis. However, the specific role of circRNAs in prostate cancer is still largely unknown. Here, we identified that circPHF16 was downregulated in prostate cancer (PCa) tissues compared with normal tissues. Functionally, circPHF16 restrained prostate cancer metastasis both in vivo and in vitro. Mechanistically, circPHF16 directly interacted with miR-581, leading to the downregulation of ring finger protein 128 (RNF128) and inhibiting the metastatic ability of PCa. Furthermore, circPHF16-dependent upregulation of RNF128 inactivated Wnt/β-catenin signaling. In total, our findings revealed that circPHF16 suppressed prostate cancer metastasis through the circPHF16/miR-581/Wnt/β-catenin pathways.

Background: tRNA-derived RNA fragments (tRFs) are a novel class of small ncRNA that are derived from precursor or mature tRNAs. Recently, the general relevance of their roles and clinical values in tumorigenesis, metastasis, and recurrence have been increasingly highlighted. However, there has been no specific systematic study to elucidate any potential clinical significance for these tRFs in prostate adenocarcinoma (PRAD), one of the most common and malignant cancers that threatens male health worldwide. Here, we investigate the clinical value of 5′-tRFs in PRAD. Methods: Small RNA sequencing data were analyzed to discover new 5′-tRFs biomarkers for PRAD. Machine learning algorithms were used to identify 5′-tRF classifiers to distinguish PRAD tumors from normal tissues. LASSO and Cox regression analyses were used to construct 5′-tRF prognostic predictive models. NMF and consensus clustering analyses were performed on 5′-tRF profiles to identify molecular subtypes of PRAD. Results: The overall levels of 5′-tRFs were significantly upregulated in the PRAD tumor samples compared to their adjacent normal samples. tRF classifiers composed of 13 5′-tRFs achieved AUC values as high as 0.963, showing high sensitivity and specificity in distinguishing PRAD tumors from normal samples. Multiple 5′-tRFs were identified as being associated with the PRAD prognosis. The tRF score, defined by a set of eight 5′-tRFs, was highly predictive of survival in PRAD patients. The combination of tRF and Gleason scores showed a significantly better performance than the Gleason score alone, suggesting that 5′-tRFs can offer PRAD patients additional and improved prognostic information. Four molecular subtypes of the PRAD tumor were identified based on their 5′-tRF expression profiles. Genetically, these 5′-tRFs PRAD tumor subtypes exhibited distinct genomic landscapes in tumor cells. Clinically, they showed marked differences in survival and clinicopathological features. Conclusions: 5′-tRFs are potential clinical biomarkers for the diagnosis, prognosis, and classification of tumor subtypes on a molecular level. These can help clinicians formulate personalized treatment plans for PRAD patients and may have similar potential applications for other disease types.

Purpose: The clinical impacts of serum lipid levels on prostate cancer recurrence after radical prostatectomy have been evaluated by several observational studies with conflicting results. We performed the present meta-analysis to summarize the evidence evaluating the role of serum lipid profile in prostate cancer patients. Methods: We comprehensively searched the PubMed database for potentially relevant studies through January 2019. Pooled hazard ratios (HRs) with their corresponding 95% confidence intervals (CIs) for the highest versus the lowest level of serum lipid levels were calculated with the DerSimonian and Laird random-effects model. Results: A total of 12 eligible studies with 10,978 prostate cancer cases were included in this study. The pooled HRs of prostate cancer recurrence after racial prostatectomy were 0.92 (95% CI 0.73–1.16, P=0.462), 0.87 (95% CI 0.56–1.35, P=0.535), 1.09 (95% CI 0.92–1.30, P=0.320), and 1.01 (95% CI 0.78–1.31, P=0.938) for serum total cholesterol, low-density lipoprotein, high-density lipoprotein, and triglyceride, respectively. Sensitivity analysis was conducted by excluding each study sequentially and the results showed that all the summary risk estimates were stable and not influenced by any single study. Conclusion: The present meta-analysis indicated that serum lipid levels in patients undergoing radical prostatectomy were not associated with prostate cancer recurrence.