Lysine (K)-specific demethylase 6B (KDM6B), a stress-inducible H3K27me3 demethylase, plays oncogenic or antitumoral roles in malignant tumors depending on the type of tumor cell. However, how this histone modifier affects the progression of prostate cancer (PCa) is still unknown. Here we analyzed sequenced gene expression data and tissue microarray to explore the expression features and prognostic value of KDM6B in PCa. Further, we performed in vitro cell biological experiments and in vivo nude mouse models to reveal the biological function, upstream and downstream regulation mechanism of KDM6B. In addition, we investigated the effects of a KDM6B inhibitor, GSK-J4, on PCa cells. We showed that KDM6B overexpression was observed in PCa, and elevated KDM6B expression was associated with high Gleason Score, low serum prostate-specific antigen level and shorted recurrence-free survival. Moreover, KDM6B prompted proliferation, migration, invasion and cell cycle progression and suppressed apoptosis in PCa cells. GSK-J4 administration could significantly suppress the biological function of KDM6B in PCa cells. KDM6B is involved in the development of castration-resistant prostate cancer (CRPC), and combination of MDV3100 plus GSK-J4 is effective for CRPC and MDV3100-resistant CRPC. Mechanism exploration revealed that androgen receptor can decrease the transcription of KDM6B and that KDM6B demethylates H3K27me3 at the cyclin D1 promoter and cooperates with smad2/3 to prompt the expression of cyclin D1. In conclusion, our study demonstrates that KDM6B is an androgen receptor regulated gene and plays oncogenic roles by promoting cyclin D1 transcription in PCa and GSK-J4 has the potential to be a promising agent for the treatment of PCa.

Objective To investigate the application of virtual reality training in vesicourethral anastomosis during robot-assisted radical prostatectomy (RARP). Methods Three certified robotic urologists who underwent virtual reality training were enrolled in the study group. The other three without training were enrolled in the control group. Parameters were recorded before and after the training. Then a total of 18 patients undergoing RARP were enrolled and randomized assigned to receive anastomosis procedures with certified urologists who either obtained or did not obtain training. The quality of the anastomosis was evaluated. Results For the virtual training evaluation, the overall score was significantly improved from 65.0±10.8 to 92.7±3.5 ( p =0.014); the time of anastomosis was shortened; the economy of motion improved; instrument collisions decreased after training ( p <0.05). Besides, the effectiveness of the virtual training was evaluated in the 18 real anastomosis procedures which were completed either by three urologists with training or three urologists without training. Most intriguingly, the average time of anastomosis was shortened from 40.0±12.4 min to 25.1±7.1 min ( p =0.015). The parameters including time of operation, creatinine level of drainage, postoperative hospital stay and duration of catheter drainage were comparable before and after training. Two leakages, which were observed in procedures by doctors without training, needed salvage sutures by a senior doctor. Conclusions Virtual reality training enabled surgeons to become quickly familiar with robotic system manipulation, improved their skills for vesicourethral anastomosis and shortened the learning curve, thus helping them operate with high efficacy and quality.

The landscape and characteristics of circulating exosomal messenger RNAs (emRNAs) are poorly understood, which hampered the accurate detection of circulating emRNAs. Through comparing RNA sequencing data of circulating exosomes with the corresponding data in tissues, we illustrated the different characteristics of emRNAs compared to tissue mRNAs. We then developed an improved strategy for emRNA detection based on the features of circulating emRNAs. Using the optimized detection strategy, we further validated prostate cancer (PCa) associated emRNAs discovered by emRNA-seq in a large cohort of patients and identified emRNA signatures for PCa screening and diagnosis using logistic regression analysis. The receiver operating characteristic curve (ROC) analysis showed that the circulating emRNA-based screening signature yielded an area under the ROC curve (AUC) of 0.948 in distinguishing PCa patients from healthy controls. The circulating emRNA-based diagnostic signature also showed a great performance in predicting prostate biopsy results (AUC: 0.851). In conclusion, our study developed an optimized emRNA detection strategy and identified novel emRNA signatures for the detection of PCa.