Background: Prostate cancer (PCa) remains the second leading cause of deaths due to cancer in the United States in men. The aim of this study was to perform an integrative epigenetic analysis of prostate adenocarcinoma to explore the epigenetic abnormalities involved in the development and progression of prostate adenocarcinoma. The key DNA methylation-driven genes were also identified.Methods: Methylation and RNA-seq data were downloaded for The Cancer Genome Atlas (TCGA). Methylation and gene expression data from TCGA were incorporated and analyzed using MethylMix package. Methylation data from the Gene Expression Omnibus (GEO) were assessed by R package limma to obtain differentially methylated genes. Pathway analysis was performed on genes identified by MethylMix criteria using ConsensusPathDB. Gene Ontology (GO) term enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were also applied for the identification of pathways in which DNA methylation-driven genes significantly enriched. The protein–protein interaction (PPI) network and module analysis in Cytoscape software were used to find the hub genes. Two methylation profile (GSE112047 and GSE76938) datasets were utilized to validate screened hub genes. Immunohistochemistry of these hub genes were evaluated by the Human Protein Atlas.Results: A total of 553 samples in TCGA database, 32 samples in GSE112047 and 136 samples in GSE76938 were included in this study. There were a total of 266 differentially methylated genes were identified by MethylMix. Plus, a total of 369 differentially methylated genes and 594 differentially methylated genes were identified by the R package limma in GSE112047 and GSE76938, respectively. GO term enrichment analysis suggested that DNA methylation-driven genes significantly enriched in oxidation–reduction process, extracellular exosome, electron carrier activity, response to reactive oxygen species, and aldehyde dehydrogenase [NAD(P)+] activity. KEGG pathway analysis found DNA methylation-driven genes significantly enriched in five pathways including drug metabolism—cytochrome P450, phenylalanine metabolism, histidine metabolism, glutathione metabolism, and tyrosine metabolism. The validated hub genes were MAOB and RTP4.Conclusions: Methylated hub genes, including MAOB and RTP4, can be regarded as novel biomarkers for accurate PCa diagnosis and treatment. Further studies are needed to draw more attention to the roles of these hub genes in the occurrence and development of PCa.

The tumor environment of prostate cancer (PCa) tissues of high Gleason score has been proved to be more immune suppressive and has higher extracellular matrix (ECM) stiffness, but whether ECM mechanical stiffness is the cause of higher ability of invasiveness and immune escape of PCa with high Gleason score remains uncertain. In this study, we showed that higher polyacrylamide hydrogels (PAAG) stiffness resulted in the progression and immune escape of PCa via integrin β1/FAK/YAP axis. The translocation of YAP into cell nucleus to bind to TEAD2 promoted the transcriptional activation of USP8. NBR1 could be ubiquitinated, and then degraded, via interacting with P62/SQSTM1 and through autophagy-lysosome pathway. Increased expression of USP8 promoted the abundance of NBR1 via K63-linked de-ubiquitination and PD-L1 via K48-linked de-ubiquitination in response to high PAAG stiffness. NBR1-mediated selective autophagy accelerated the degradation of MHC-1 of PCa. The USP8 inhibitor presented a potential application value in sensitizing immunotherapy of PCa. Taken together, we identified a USP8-mediated de-ubiquitination mechanism that involves in the process of high PAAG stiffness-mediated high expression of PD-L1 and low expression of MHC-1 of PCa cells, which provided a rationale of immunotherapy sensitization of PCa via USP8 inhibition.

Obesity is a known risk factor for prostate cancer progression and may contribute to poor treatment outcomes. However, little is known concerning the relationship between obesity (body mass index [BMI] ⩾ 30) and the urinary incontinence (UI) of patients after radical prostatectomy (RP). The goal of this study was to focus on the prevalence and duration of UI after RP with specific attention to the BMI. Subsequently, trials were identified in a literature search of PubMed, Embase, Cochrane Library, Web of Science, and Google Scholar using appropriate search terms. All comparative studies reporting BMI, study characteristics, and outcome data including the relationship between BMI and urinary incontinence data were included. Finally, four studies comprising 6 trials with 2890 participants were included. The results showed that obesity increased UI risk at 12 months in patients who underwent robotic-assisted laparoscopic radical prostatectomy (RLRP) (odds ratio [OR] 2.43, 95% confidence interval [CI] [1.21, 4.88], P=0.01). When stratified by the surgical methods, the pooled results showed that obesity increased UI risk at 24 months in patients who underwent RLRP (OR 2.00, 95% CI [1.57, 2.56], P<0.001). However, in patients who underwent laparoscopic radical prostatectomy (LRP), the pooled results showed that obesity does not increase UI risk at 24 months (OR 1.13, 95% CI [0.74, 1.72], P=0.58). This is the first study to include obesity as the primary independent variable. Outcomes indicate that obesity (BMI ≥ 30) may increase the UI risk at 12 and 24 months after RLRP. Well-designed randomized controlled trials with strict control of confounders are needed to make results comparable.

Expression of kinesin family member 18B (KIF18B), an ATPase with key roles in cell division, is deregulated in many cancers, but its involvement in prostate cancer (PCa) is unclear. Here, we investigated the expression and function of KIF18B in human PCa specimens and cell lines using bioinformatics analyses, immunohistochemical and immunofluorescence microscopy, and RT-qPCR and western blot analyses. KIF18B was overexpressed in PCa specimens compared with paracancerous tissues and was associated with poorer disease-free survival. In vitro, KIF18B knockdown in PCa cell lines promoted cell proliferation, migration, and invasion, and inhibited cell apoptosis, while KIF18B overexpression had the opposite effects. In a mouse xenograft model, KIF18B overexpression accelerated and promoted the growth of PCa tumors. Bioinformatics analysis of control and KIF18B-overexpressing PCa cells showed that genes involved in the PI3K–AKT–mTOR signaling pathway were significantly enriched among the differentially expressed genes. Consistent with this observation, we found that KIF18B overexpression activates the PI3K–AKT–mTOR signaling pathway in PCa cells both in vitro and in vivo. Collectively, our results suggest that KIF18B plays a crucial role in PCa via activation of the PI3K–AKT–mTOR signaling pathway, and raise the possibility that KIF18B could have utility as a novel biomarker for PCa.

Objective: To explore the risk factors for postoperatively pathological lymph node metastasis in patients with clinical T2N0M0 stage prostate cancer (PCa). Methods: We retrospectively analyzed clinicopathological data of 316 patients with clinical T2 stage PCa and preoperative negative lymph nodes [LN(−)] indicated by imaging (cT2N0M0) between January 2014 and May 2019. Multivariate logistic regression analysis was performed to determine risk factors for postoperatively pathological pLN(+) in patients with cT2N0M0 stage PCa. Spearman correlation analysis was used to explore the relationship between tumor burden and Prostate Imaging Reporting and Data System version 2 (PI-RADS v2) score. Results: A total of 45 patients (14.2%) were confirmed by postoperative pathology to have LN metastasis. Univariate analysis indicated that total prostate-specific antigen (tPSA), PI-RADS v2 score, postoperative Gleason grade group (GGG), intraductal carcinoma of the prostate (IDC-P), clinical T2 substaging, and postoperative pathological tumor burden were risk factors for pLN(+) in all patients. Multivariate analysis showed that tPSA and postoperative GGG were risk factors for pLN(+) in all patients. Univariate analysis revealed that tPSA, PIRADS v2 score, clinical T2 substaging, IDC-P, postoperative pathological tumor burden, and postoperative GGG were risk factors for pLN(+) in patients with GGG ≥ 3. Multivariate analysis suggested that tPSA, PI-RADS v2 score, clinical T2 substaging, postoperative pathological tumor burden, and GGG were risk factors for pLN (+) in patients with GGG ≥ 3. Spearman correlation analysis showed that PI-RADS v2 score was positively correlated with clinical T2 substaging and postoperative pathological tumor burden. Conclusion: There was a high risk of LN metastasis in patients with cT2 PCa if they had high preoperative tPSA or high postoperative GGG. Patients with cT2 PCa and GGG ≥ 3 had a high risk of LN metastasis if they had high PI-RADS v2 score, high preoperative clinical stage or high postoperative pathological tumor burden. PI-RADS v2 score predicted tumor burden well in patients with GGG ≥ 3.