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In our study, 49 key genes significantly associated with renal cell carcinoma (RCC) stemness were obtained. Next, we developed a molecular prognostic signature associated with stemness features of pan-RCC. The difference in overall survival (OS) between the high- and low-risk groups was statistically significant (p < .05). The area under the receiver operating characteristic curve for 1-year OS, 5-year OS, and 10-year OS was 0.759, 0.712, and 0.918, respectively. The results of validation in The Cancer Genome Atlas cohort and International Cancer Genome Consortium cohort revealed the predictive capability of this signature. Furthermore, we selected three genes and further validation showed that these three hub genes were potential hub biomarkers for pan-RCC stemness features.

Hai Cai,1,&ast; Shao-Ming Chen,2,&ast; Zhi-Bin Ke,1,&ast; Hang Chen,1,&ast; Jun-Ming Zhu,1 Ting-Ting Lin,1 Fei Huang,3,4 Yong Wei,1 Qing-Shui Zheng,1 Xue-Yi Xue,1 Xiong-Lin Sun,1 Ning Xu1,3 1Department of Urology, Urology Research Institute, The First Affiliated Hospital, Fujian Medical University, Fuzhou, 350005, People’s Republic of China; 2Department of Nuclear Medicine, First Affiliated Hospital of Fujian Medical University, Fuzhou, 350005, People’s Republic of China; 3Fujian Key Laboratory of Precision Medicine for Cancer, The First Affiliated Hospital, Fujian Medical University, Fuzhou, 350005, People’s Republic of China; 4Central Lab, The First Affiliated Hospital of Fujian Medical University, Fuzhou, 350005, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Ning Xu; Xiong-Lin Sun Tel +86-059187981687Email drxun@fjmu.edu.cn; sunxionglin@fjmu.edu.cnObjective: To develop and validate hub genes involving in the development and progression of primary aldosteronism (PA) and adrenal aldosterone-producing adenoma (APA).Materials and Methods: A total of four datasets of gene expression profiles related to APA were downloaded from GEO datasets. GSE60042 and GSE8514 were used to identify DEGs. Weighted gene co-expression network analysis (WGCNA) and protein–protein interaction (PPI) network module analysis were conducted. GO and KEGG enrichment analysis was performed. GSE10927 and GSE33371 were used for further external validation.Results: We identified a total of 892 DEGs from GSE60042 and 1167 DEGs from GSE8514. WGCNA analysis demonstrated that the blue module (255 genes) and turquoise module (303 genes) were significantly correlated with APA. PPI networks were then constructed. GO term enrichment analysis suggested that cellular divalent inorganic cation homeostasis, calcium ion homeostasis, collagen-containing extracellular matrix, transport vesicle and metal ion transmembrane transporter activity were the vital annotations. KEGG pathway analysis found that these genes were significantly enriched in neuroactive ligand−receptor interaction, calcium signaling pathway. Finally, we identified a total of 11 candidate genes involving in the development and progression of APA and PA. Besides, two independent datasets (GSE10927 and GSE33371) were used for external validation, and there were seven hub genes successfully verified, including C3, GRM3, AVPR1A, WFS1, PTGFR, NTSR2, and JUN.Conclusion: These newly identified genes could contribute to the understanding of potential mechanism in APA and PA and might be promising targets for the treatment of APA and PA.Keywords: aldosterone-producing adenoma, bioinformatics, primary aldosteronism, gene expression omnibus datasets

To explore whetherThe clinicopathologic data of 106 mCRPC cases receiving AA treatment were retrospectively analyzed. Logistic regression analysis was used to determine the independent predictors of biochemical response to AA treatment. Cox analyses were applied to investigate the independent prognostic factors for time to biochemical progression (TTBP) and radiological progression-free survival (rPFS). Survival analysis and ROC curve were also used.Multivariable Logistic analysis demonstrated that prior ADT duration ≥ 12 months, low prostate specific membrane antigen receptor-expressing tumor volume (PSMA-TV), low tumor to liver ratio (TLR) were independent predictors of biochemical response to AA treatment. Multivariate Cox analysis demonstrated that low PSMA-TV and low TLR were independent prognostic factors of longer TTBP and rPFS. The TTBP and rPFS of patients with higher PSMA-TV or TLR were significantly decreased compared with that of patients with lower PSMA-TV and TLR. The area under ROC curve (AUC) of combining ADT duration, PSMA-TV and TLR was 0.82 for predicting biochemical response to AA, which was significantly increased compared with that of otherLow PSMA-TV, low TLR were vital independent predictors of biochemical response to AA treatment and were associated with preferable prognosis in mCRPC patients. Combining ADT duration, PSMA-TV and TLR performed well in distinguishing AA responders from non-responders in mCRPC patients.

Ye-Hui Chen,1,&ast; Ru-Nan Dong,1,&ast; Jian Hou,1,&ast; Ting-Ting Lin,1,&ast; Shao-Hao Chen,1 Hang Chen,1 Jun-Ming Zhu,1 Jia-Yin Chen,1 Zhi-Bin Ke,1 Fei Lin,1 Xue-Yi Xue,1 Yong Wei,1 Ning Xu1,2 1Department of Urology, Urology Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou, 350005, People’s Republic of China; 2Fujian Key Laboratory of Precision Medicine for Cancer, the First Affiliated Hospital, Fujian Medical University, Fuzhou, 350005, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Ning Xu; Yong WeiDepartment of Urology, Urology Research Institute, the First Affiliated Hospital, Fujian Medical University, 20 Chazhong Road, Fuzhou, 350005, People’s Republic of ChinaTel +86-059187981687Email drxun@fjmu.edu.cn; weiyong2017@fjmu.edu.cnBackground: Urethral stricture is a clinical challenge for both patients and clinicians. Post-traumatic urethral stricture is associated with formation of scar tissue caused by excessive inflammation. The aim of this study is exploring potential therapeutic strategies for this condition.Methods: In vivo experiments on New Zealand rabbits and in vitro experiments on THP-1 monocytes and urethral fibroblasts were performed to investigate the effects on post-traumatic urethral stricture of exosomes isolated from IL-1β-treated mesenchymal stem cells (Exo-MSCsIL− 1β) and the role of macrophage M2 polarization in this process. Additionally, related signaling and mechanism behind were explored.Results: In a New Zealand rabbit model of post-traumatic urethral stricture, injection of Exo-MSCsIL− 1β significantly reduced urethral stricture and collagen fiber accumulation compared with Exo-MSCs. Addition of Exo-MSCsIL− 1β to THP-1 monocytes in vitro induced M2 macrophage polarization, which, in turn, inhibited activation of urethral fibroblasts and synthesis of collagen. Mechanistically, Exo-MSCsIL− 1β were found to contain high levels of the microRNA let-7c, and luciferase reporter assays showed that let-7c interacted with the 3′UTR of PAK1 mRNA. Transfection of THP-1 cells with a let-7c mimic downregulated PAK1 expression and inhibited activation of the NF-κB signaling pathway.Conclusion: These results support a role for let-7c-containing Exo-MSCsIL− 1β in reducing urethral stricture via inhibition of PAK1–NF-κB signaling, M2 macrophage polarization, and differentiation of urethral myofibroblasts.Keywords: urethral stricture, mesenchymal stem cells, polarization of macrophages, exosomes, let-7c

Pheochromocytoma and paraganglioma (PCPG) is a rare neuroendocrine tumor. This study aims to identify vital prognostic genes which were associated with PCPG tumor microenvironment (TME). We downloaded transcriptome data of PCPG from TCGA database and calculated the immune scores and stromal scores by using the ESTIMATE algorithm. DEGs related to TMB were then identified. We conducted WGCNA to further extract the TME-related modules. GO, KEGG pathway analysis, and PPI network were performed. Survival analysis was conducted to identify the hub genes associated with the prognosis of PCPG. A total of 150 PCPG samples were included in this study. We obtained 1507 and 2067 DEGs based on immune scores and stromal scores, respectively. WGCNA analysis identified the red module and brown module were correlated with immune sores while the turquoise module and red module were significantly associated with stromal scores. Functional enrichments analysis revealed that 307 TME-related genes were correlated with the inflammation or immune response. Survival analysis showed that three TME-relate genes (ADGRE1, CCL18, and LILRA6) were associated with PCPG prognosis. These three hub genes including ADGRE1, CCL18, and LILRA6 might be involved in the progression of PCPG and could serve as potential biomarkers and novel therapeutic targets.

The diverse tumor cell populations may be the critical roles in relapse and resistance to treatment in prostate cancer patients. This study aimed to identify new marker genes and cell subtypes among castration-resistant prostate cancer (CRPC) cells. We downloaded single-cell RNA seq profiles (GSE67980) from the Gene Expression Omnibus (GEO) database. Principal component (PC) analysis and t-Distributed Stochastic Neighbor Embedding (TSNE) analysis were performed to identify marker genes. CRPC cells were clustered and annotated. GO and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses among marker genes were performed. A total of 1500 genes with larger standardized variance were obtained. The top 20 genes were demonstrated in each identified 20 PCs. PC with P-value < 0.05 was selected, including PC1, PC7, PC8, and PC14. The TSNE analysis classified cells as two clusters. The top 6 genes in cluster 0 included HBB, CCL5, SLITRK4, GZMB, BBIP1, and PF4V1. Plus, the top 6 genes in cluster 1 included MLEC, CCT8, CCT3, EPCAM, TMPRSS2, EIF4G2. The GO analysis revealed that these marker genes were mainly enriched in RNA catabolic process, translational initiation, mitochondrial inner membrane, cytosolic part, ribosome, cell adhesion molecule binding, cadherin binding, and structural constituent of ribosome. The KEGG analysis showed that these marker genes mainly enriched in metabolism associated pathways, including carbon metabolism, cysteine and methionine metabolism, propanoate metabolism, pyruvate metabolism, and citrate cycle pathways. To conclude, our results provide essential insights into the spectrum of cellular heterogeneity within human CRPC cells. These marker genes, GO terms and pathways may be critical in the development and progression of human CRPC.

Objective To screen several immune-related long non-coding RNAs (lncRNAs) and construct a prognostic model for papillary renal cell carcinoma (pRCC). Methods Transcriptome-sequencing data of pRCC was downloaded and a prognostic model was constructed. Time-dependent receiver operating characteristic (ROC) curve was plotted and the area under curve (AUC) was calculated. We conducted quantitative reverse transcription polymerase chain reaction (RT-PCR) to verify the model. The gene set enrichment analysis (GSEA) was used to show the connection of our model with immune pathways. Result We identified four lncRNAs to constructed the model. The model was significantly associated with the survival time and survival state. The expression-levels of the four lncRNAs were measured and the prognosis of high-risk patients was significantly worse. The two immune-gene sets had an active performance in the high-risk patients. Conclusion We constructed a prognostic model in pRCC which provided more reference for treatment.

Background Clear cell renal cell carcinoma (ccRCC) is one of the most frequent malignancies; however, the present prognostic factors was deficient. This study aims to explore whether there is a relationship between tumor volume (TV) and oncological outcomes for localized ccRCC. Methods Seven hundred forty-nine localized ccRCC patients underwent surgery in our hospital. TV was outlined and calculated using a three-dimensional conformal radiotherapy planning system. We used receiver operating characteristic (ROC) curves to identified optimal cut-off value. Univariable and multivariable Cox regression models were performed to explore the association between TV and oncological outcomes. Kaplan-Meier method and log-rank test were used to estimate survival probabilities and determine the significance, respectively. Time-dependent ROC curve was utilized to assess the prognostic effect. Results Log rank test showed that higher Fuhrman grade, advanced pT classification and higher TV were associated with shortened OS, cancer-specific survival (CSS), freedom from metastasis (FFM) and freedom from local recurrence (FFLR). multivariable analysis showed higher Fuhrman grade and higher TV were predictors of adverse OS and CSS. The AUC of TV for FFLR was 0.822. The AUC of TV (0.864) for FFM was higher than that of pT classification (0.818) and Fuhrman grade (0.803). For OS and CSS, the AUC of TV was higher than that of Fuhrman grade (0.832 vs. 0.799; 0.829 vs 0.790). Conclusions High TV was an independent predictor of poor CSS, OS, FFLR and FFM of localized ccRCC. Compared with pT classification and Fuhrman grade, TV could be a new and better prognostic factor of oncological outcome of localized ccRCC, which might contribute to tailored follow-up or management strategies.

Purpose To identify the relevant factors, and create and validate a predictive scoring system for the duration of laparoscopic radical prostatectomy (LRP). Patients and methods We retrospectively analyzed clinicopathological data from 436 patients who underwent LRP between January 2014 and January 2019, of whom 304 cases were used as a model creation group and 132 were used as a validation group. Uni/multivariate linear regression analysis was performed to determine the predictors of the duration of the procedure and a novel scoring system was created using these predictors. External validation of the scoring system was performed. The Hosmer-Lemeshow test was used to determine the goodness-of-fit of the model and calibration plots were created for visual assessment. Results "Prolonged duration" was defined as a duration of the procedure that was longer than the mean (>150 min) duration. Multivariate analysis showed that body mass index (BMI), prostate volume, intravesicular protrusion of the prostate (IPP), the ratio of the cross-sectional areas of the prostate and the Retzius space (P/R), pelvic lymph node dissection, and neurovascular bundle (NVB) preservation were significant predictors of prolonged duration. A scoring system that included these six parameters was created and the area under the curve achieved during receiver operating characteristic analysis using this scoring system was 0.874 (95% confidence interval [CI]: 0.836-0.913). The Hosmer-Lemeshow test showed that the scoring system was well calibrated (X2=5.339, P=0.376). The external validation showed that the model had high predictive accuracy (AUC=0.835, 95% CI: 0.764-0.906) and goodness-of-fit (X2=4.401, P=0.493). Conclusion The following factors were significantly associated with prolonged duration of laparoscopic radical prostatectomy: BMI, prostate volume, IPP, P/R, pelvic lymph node dissection, and NVB preservation. The novel scoring system created can be used to accurately predict the duration of the procedure, assess the difficulty of surgery, and improve perioperative efficiency.

Background Bladder cancer (BCa) is one of the important tumors that have been proven to be treatable with immunotherapy. This study aims to identify and validate a molecular prognostic index of BCa based on immunogenomic landscape analysis. Methods The cancer genome atlas (TCGA) database and immunology database and analysis portal (ImmPort) database were used to identified differentially expressed immune-related genes (IRGs). Prognostic IRGs were screened and protein–protein interaction (PPI) network was constructed. Multivariate Cox analysis was performed to develop a molecular prognostic index of BCa. Internal and external validation were then performed in TCGA cohort and GEO cohort, respectively. Besides, we also explore the relationship between this index and clinical characteristics, immune cell infiltration and tumor microenvironment. Results A total of 61 prognostic IRGs were identified and a molecular prognostic index was developed. The top four hub genes included MMP9, IGF1, CXCL12 and PGF. The difference in overall survival between high-risk group and low-risk group was statistically significant. The area under curve of the receiver operating characteristic (ROC) curve was 0.757, suggesting the potential for this index. Besides, Internal validation using TCGA cohort and external validation using GEO cohort indicated that this index was of great performance in predicting outcome. T cells CD8, T cells CD4 memory activated, T cells follicular helper, macrophages M0, macrophages M2 and neutrophils were significantly associated with prognosis of BCa patients. Female, high grade, stage III&IV, N1-3 and T3-4 were associated significantly with higher risk score compared with male, low grade, stage I&II, N0 and T1-2, respectively. High risk score had a positive association with higher stromal score and ESTIMATE score while high risk score had a negative association with tumor purity. Conclusions This study identified several prognostic immune-related genes of clinical value. Besides, we developed and validated a molecular index based on immunogenomic landscape analysis, which performed well in predicting prognosis of BCa. Further researches are needed to verify the effectiveness of this index and these vital genes.

Objective: To explore the correlations among alternative splicing (AS), splicing factors (SF) and survival outcome in adrenocortical carcinoma (ACC) patients. Results: A total of 92 ACC patients were included. Univariate analysis identified 3919 AS events significantly associated with overall survival. Lasso method followed by multivariate analysis revealed that the prognostic capacity of these survival-related AS events is satisfactory. Interestingly, we found that the area under the curve (AUC) of AA, AD, AP and RI were more than 0.9, indicating that these four types of AS were of great significance. Independent prognostic analysis showed that only the risk score was the independent risk factor of ACC survival. Finally, we constructed an interesting interaction network between AS and SF. Conclusions: This is the first and most comprehensive study to explore the aberrant AS variants in ACC, which might provide novel insights into molecular mechanism of ACC. Methods: The transcriptome data, clinical information and Percent Spliced In (PSI) values of the ACC were obtained from TCGA database and TCGA SpliceSeq data portal. Lasso method and uni/multivariate Cox regression analysis were used to identify survival-related AS events and develop multi-AS-based signatures. The relationship between AS events and SFs was also investigated.

Lymph node metastasis is one of the most important independent risk factors that can negatively affect the prognosis of prostate cancer (PCa); however, the exact mechanisms have not been well studied. This study aims to better understand the underlying mechanism of lymph node metastasis in PCa by bioinformatics analysis. We analysed a total of 367 PCa cases from the cancer genome atlas database and performed weighted gene co‐expression network analysis to explore some modules related to lymph node metastasis. Gene Ontology analysis and pathway enrichment analysis were conducted for functional annotation, and a protein‐protein interaction network was built. Samples from the International Cancer Genomics Consortium database were used as a validation set. The turquoise module showed the most relevance with lymph node metastasis. Functional annotation showed that biological processes and pathways were mainly related to activation of the processes of cell cycle and mitosis. Four hub genes were selected: CKAP2L, CDCA8, ERCC6L and ARPC1A. Further validation showed that the four hub genes well‐distinguished tumour and normal tissues, and they were good biomarkers for lymph node metastasis of PCa. In conclusion, the identified hub genes facilitate our knowledge of the underlying molecular mechanism for lymph node metastasis of PCa.

This study was to explore the risk factors for postoperative bladder neck contracture (BNC) after transurethral operation of prostate in patients with small-volume prostatic obstruction.Clinicopathologic data at our center from February 2016 to January 2020 were retrospectively collected and analyzed. Clinicopathological characteristics between patients with and without BNC were compared. Multivariate logistic regression was used to determine the risk factors for postoperative BNC.There were a total of 39 patients (8.53%) with postoperative BNC. Multivariate logistic regression analysis demonstrated that preoperative bladder neck diameter (BND), intravesical prostatic protrusion (IPP), surgical methods (transurethral resection of prostate (TURP)/anatomical endoscopic enucleation of the prostate (AEEP)), and postoperative urinary tract infection (UTI) were independent risk factors for postoperative BNC in patients with small-volume prostatic obstruction (P 0.05). The incidence of postoperative BNC in patients undergoing AEEP was significantly decreased compared with those undergoing TURP. The optimal cut-off value of preoperative IPP was 6.10 mm while the optimal cut-off value of preoperative BND was 2.52 cm.Larger preoperative bladder neck and higher preoperative IPP lead to decreased incidence of postoperative BNC in patients with small-volume prostatic obstruction. Active management of postoperative UTI could effectively prevent the occurrence of postoperative BNC. Compared with TURP, complete AEEP would contribute to reduce BNC in patients with small-volume prostatic obstruction.

Objective To explore the factors associated with improvement of lower urinary tract symptoms (LUTS) after transurethral plasmakinetic enucleation of the prostate (PKEP) and transurethral resection of the prostate (TURP) in patients with a small-volume prostate and bladder outlet obstruction (BOO). Methods The clinicopathologic data of 257 patients with BOO and a small-volume prostate from January 2013 to January 2018 were retrospectively collected preoperatively, 3 months postoperatively, and 12 months postoperatively. Patients were divided into postoperative success and failure groups based on the IPSS, IPSS-v, and IPSS-s. The relationship between each parameter and the improvement of postoperative LUTS was analyzed. Subgroup analysis was performed to compare the differences between the TURP and PKEP groups. Results Among patients followed up for 3 months postoperatively, multivariate analysis demonstrated that IPP, PUA, and post-PCB were significant predictors of postoperative IPSS improvement; TZI, IPP, and PUA were significant predictors of postoperative IPSS-v improvement; post-PCB and the surgical procedure were significant predictors of IPSS-s improvement; and IPP and PUA were significant predictors of postoperative Qmax improvement. Among patients followed up for 12 months postoperatively, multivariate analysis revealed that IPP, PUA, and post-PCB were significant predictors of postoperative IPSS improvement; PUA was a significant predictor of postoperative IPSS-v improvement; post-PCB was a significant predictor of IPSS-s improvement; and IPP and PUA were significant predictors of postoperative Qmax improvement. The post-PCB was significantly lower in the PKEP than the TURP group and the prostatic calculi removal rate was significantly higher in the PKEP than the TURP group. Conclusion Patients with a greater preoperative IPP and PUA and smaller post-PCB showed greater improvement of postoperative LUTS. PKEP might help to remove calculi from between the transitional and peripheral zones of prostate. Compared with conventional TURP, PKEP may improve the early postoperative storage symptoms of LUTS in patients with a small-volume prostate and BOO.

Objective: To develop and validate ubiquitination-related molecular subtypes and a novel prognostic index using ubiquitination-related genes (URGs) for patients with bladder cancer (BCa).Materials and Methods: We downloaded the clinical data and transcriptome data of BCa from TCGA and GEO database. Consensus clustering analysis was conducted to identify ubiquitination-related molecular subtypes for BCa. Besides, we performed univariate and multivariate Cox regression analysis to develop a novel prognostic URGs-related index for BCa. We conducted internal and external verification in TCGA cohort and GEO cohort, respectively. Furthermore, the associations of ubiquitination-related molecular subtypes and prognostic index with tumor immune environment were also investigated.Results: A total of four ubiquitination-related molecular subtypes of BCa were finally identified. These four molecular subtypes had significantly different clinical characteristics, prognosis, PD-L1 expression level and tumor microenvironment. Besides, we developed a novel prognostic index using six URGs (including HLA-A, TMEM129, UBE2D1, UBE2N, UBE2T and USP5). The difference in OS between high and low-risk group was statistically significant in training cohort, testing cohort, and validating cohort. The area under ROC curve (AUC) for OS prediction was 0.736, 0.723, and 0.683 in training cohort, testing cohort, and validating cohort, respectively. Multivariate survival analysis showed that this index was an independent predictor for OS. This prognostic index was especially suitable for subtype 1 and 3, older, male, high grade, AJCC stage III-IV, stage N0, stage T3-4 BCa patients.Conclusions: This study identified a total of four ubiquitination-related molecular subtypes with significantly different tumor microenvironment, prognosis, clinical characteristics and PD-L1 expression level. Besides, a novel ubiquitination-related prognostic index for BCa patients was developed and successfully verified, which performed well in predicting prognosis of BCa.

Hao Li,1,2 Lu Chen,1,2 Zhi-Bin Ke,3 Shao-Hao Chen,3 Xue-Yi Xue,3 Qing-Shui Zheng,3 Yong Wei,3 Kai Zeng,1,2 Ning Xu3,4 1Department of Anesthesiology, Anesthesiology Research Institute, The First Affiliated Hospital, Fujian Medical University, Fuzhou, 350005, People’s Republic of China; 2Department of Surgery, The First Affiliated Hospital, Fujian Medical University, Fuzhou, 350005, People’s Republic of China; 3Department of Urology, Urology Research Institute, The First Affiliated Hospital, Fujian Medical University, Fuzhou, 350005, People’s Republic of China; 4Fujian Key Laboratory of Precision Medicine for Cancer, The First Affiliated Hospital, Fujian Medical University, Fuzhou, 350005, People’s Republic of ChinaCorrespondence: Ning XuDepartment of Urology, Urology Research Institute, The First Affiliated Hospital, Fujian Medical University, 20 Chazhong Road, Fuzhou, 350005, People’s Republic of ChinaTel +86-59187981687Email drxun@fjmu.edu.cnKai ZengDepartment of Anesthesiology, Anesthesiology Research Institute, The First Affiliated Hospital, Fujian Medical University, 20 Chazhong Road, Fuzhou, 350005, People’s Republic of ChinaEmail zengkai6822@163.comBackground: This study aimed to develop and validate a novel angiogenesis-related gene (ARG) signature and molecular subtypes by bioinformatics analysis.Materials and Methods: The transcriptome data and clinical data were obtained from TCGA and ICGC database. We performed consensus clustering analysis to identify angiogenesis molecular subtypes for ccRCC. Univariate and multivariate Cox regression analyses were used to develop a novel ARG-related signature as a prognostic biomarker for ccRCC. Internal and external validation were then performed in TCGA and ICGC cohort, respectively.Results: We identified a total of two angiogenesis molecular subtypes of ccRCC. The overall survival (OS) of subtype 1 ccRCC was significantly decreased compared with that of subtype 2 ccRCC (P=0.001). These two molecular subtypes have significantly different tumor microenvironment and immune checkpoint inhibitor sensitivities (P< 0.05). Besides, we developed a novel signature based on three ARGs (including MSX1, TIMP1 and JAG2) for subtype 1 ccRCC. The difference in OS between high- and low-risk group was statistically significant in training cohort (P=0.009), test cohort (P=0.024), the whole type 1 cohort (P< 0.001), and validation cohort (P=0.041). The AUC for one-year OS prediction was 0.732, 0.710, 0.725, and 0.645 in training cohort, test cohort, the whole type 1 cohort, and validation cohort, respectively. Independent prognostic analysis showed that this signature was an independent predictor for OS of subtype 1 ccRCC (P=0.028914). The power of this prognostic signature was superior to other signatures reported in previous studies.Conclusion: We developed and successfully validated a novel ARG signature for predicting prognosis of subtype 1 ccRCC, which was superior to several previous signatures.Keywords: clear cell renal cell carcinoma, angiogenesis, molecular subtypes, signature, prognosis

Summary Objective To investigate the predictors of response to intravesical Bacillus Calmette-Guerin (BCG) immunotherapy for intermediate and high-risk non-muscle invasive bladder cancer (NMIBC) patients. Materials and methods We retrospectively analyzed the clinicopathological data of 184 intermediate and high risk NMIBC cases receiving transurethral resection of bladder tumor (TURBT) and intravesical BCG immunotherapy from December 2014 to April 2021 at our center. All patients were divided into BCG responders and non-responders. Multivariate Logistic regression analysis was performed to identify the independent predictors of response to intravesical BCG immunotherapy. Univariate and multivariate Cox regression analyses were applied to explore the independent prognostic factors of recurrence-free survival (RFS). Receiver operating characteristic (ROC) curve and Kaplan–Meier survival analysis were also utilized. Results The RFS of BCG responders was significantly increased compared with BCG non-responders. Multivariate Cox regression analysis demonstrated that low grade, pTa stage, non-CIS, lower relative visceral fat area (rVFA) and lower systemic immune inflammation index (SII) were independent prognostic factors of increased RFS after intravesical BCG immunotherapy. Multivariate Logistic regression analysis demonstrated that pTa stage, low grade, non-CIS, low rVFA, and low SII were independent predictors of response to intravesical BCG immunotherapy. Kaplan–Meier survival analysis indicated that the RFS of patients in low rVFA group or low SII group was significantly increased in comparison with those in high rVFA group or high SII group. ROC curve analysis showed that the area under ROC (AUC) of including SII and rVFA was significantly increased, indicating that the inclusion of preoperative SII and rVFA could significantly improve the predictive efficiency. Conclusions Low grade, pTa stage, non-CIS, preoperative lower rVFA and lower SII were vital independent predictors of response to intravesical BCG immunotherapy and were associated with preferable prognosis in NMIBC patients. The inclusion of preoperative SII and rVFA could significantly improve the predictive efficiency.

Background Risk factors of visceral metastases in prostate cancer (PCa) patients are unclear. The aim of this study is to investigate the risk factors of developing visceral metastases at diagnosis and the impact of these risk factors on the survival of patients with visceral metastatic PCa. Methods Patients with visceral metastases at the time of diagnosis of [2010–2015] PCa were identified using the Surveillance, Epidemiology, and End Results (SEER) database. Visceral metastatic distribution data were provided for liver, lung, and brain. The overall survival (OS) was calculated by the Kaplan-Meier method. Multivariable logistic and Cox regression models were performed to identify risk factors and analyze survival outcomes. Results A total of 13,092 eligible patients with stage IV PCa were identified from SEER database. A total of 598 patients developed visceral metastases at diagnosis among these patients. In multivariable analyses, patients with PSA >80 ng/mL had 1.545-fold higher risk of developing visceral metastases compared with those with PSA

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.

Background: Clear cell renal cell carcinoma (ccRCC) is one of the most frequent malignancies. Increasing evidence has highlighted the critical roles of autophagy-related genes and autophagy-related long non-coding RNA (lncRNA) in ccRCC development and progression. Therefore, it is necessary to identify novel biomarkers associated with autophagy in ccRCC.Methods: A total of 507 ccRCC patients were included in our study and then randomly divided into a training cohort (n=255) and testing cohort (n=252). Univariate Cox regression models, Lasso regression analyses and multivariate Cox regression models were successively used for constructing gene model and lncRNA model. Receiver-operating characteristic (ROC) curve analysis, Kaplan-Meier (K-M) analysis and more functional analyses were applied for verifying the accuracy of the two models.Results: The autophagy-related genes (ARGs) prognostic model was constructed based on the six ARGs (EIF4EBP1, IFNG, BID, BIRC5, CX3CL1 and RAB24) and five autophagy-related lncRNAs (AC093278.2, AC010326.3, AC099850.3, AC016773.1 and AC009549.1) and then ccRCC patients were significantly stratified into high- and low-risk groups in terms of overall survival (OS). K-M survival analyses indicated that low-risk group had a lower mortality rate than high-risk group in the six-gene prognostic risk model (training cohort: P=4.138e-07; testing cohort: P=1.125e-03) and the same results were obtained in the case of the five-lncRNA prognostic risk model (training cohort: P=4.564e-09; testing cohort: P=2.485e-03). The results of time-dependent ROC curves revealed six-gene prognostic risk model had a higher area under curve (AUC) of 0.765 than the five-lncRNA prognostic risk model at an AUC of 0.759. Therefore, the gene model is an indicator as good as the model constructed by lncRNAs. In addition, further functional analysis indicated these genes were functionally involved in regulation of endopeptidase activity, regulation of peptidase activity, autophagy, human cytomegalovirus infection, shigellosis, autophagy-animal and HIF-1 signaling pathway.Conclusions: A total of six OS-related ARGs and five autophagy-related lncRNA were identified in our current study. The two autophagy-related prediction models including genes and lncRNAs are reliable prognostic and predictive biomarkers for ccRCC.

Background The differential expression of miRNAs has played a significant role in bladder tumors. The aim of our study was to screen new biomarkers . Methods Through differential analysis of bladder cancer mRNA and miRNA expression data in the TCGA, differential genes and miRNAs were screened. Furthermore, Cox univariate analysis and multifactor analysis were used to establish a prognostic prediction model . The predictive ability of the prognostic model was then verified on the patient. The action mechanism of these miRNAs was analyzed.Results By the differential analysis and standardization of miRNA expression profiles. Differentially expressed miRNAs were screened, then all the patients were then randomly divided into train group and the test group. 23 miRNAs were revealed , then a Seven-miRNA signature prognostic biomarkers was constituting.Univariate cox regression and multivariate cox regression considering other clinical factors displayed that the seven-miRNA signature could serve as an independent prognostic factor.Target genes of these seven miRNAs were analyzed by KEGG signaling pathway and GO enrichment analysis. . Conclusion The prognostic model constructed by seven miRNAs has possessed certain degree of sensitivity and specificity for the prediction of the survival of bladder cancer patients, which can be used as a potential new clinical marker for bladder cancer patients.

Background Prostate cancer (PCa) is one of the most common malignant tumors worldwide. Accumulating evidence has suggested that circular RNAs (circRNAs) are involved in the development and progression of various cancers, and they show great potential as novel biomarkers. However, the underlying mechanisms and specific functions of most circRNAs in PCa remain unknown. Here, we aimed to identify circRNAs with potential roles in PCa from the PCa expression profile. Methods We used data downloaded from the Gene Expression Omnibus to identify circRNAs that were differentially expressed between PCa samples and adjacent non-tumor samples. Relative expression levels of identified circRNAs were validated by quantitative real-time PCR. Micro (mi)RNA response elements were predicted by the CircInteractome database, and miRNA target genes were predicted by miRDB, miRTarBase, and TargetScan databases. Gene ontology (GO) enrichment analysis and pathway analysis revealed the potential biological and functional roles of these target genes. A circRNA-miRNA-mRNA interaction network was constructed by Cytoscape. The interaction between circRNAs and miRNAs in PCa was thoroughly reviewed in the PubMed. Finally, the mRNA expression of these genes was validated by the Cancer Genome Atlas (TCGA) and Gene Expression Profiling Interactive Analysis (GEPIA) databases. The expression of proteins encoded by these genes was further validated by the Human protein Atlas (HPA) database. Results A total of 60 circRNAs that were differentially expressed between PCa and healthy samples were screened, of which 15 were annotated. Three circRNAs (hsa_circ_0024353, hsa_circ_0085494, hsa_circ_0031408) certified the criteria were studied. The results of quantitative real-time PCR demonstrated that the expression of hsa_circ_0024353 was significantly downregulated in PC-3 cells when compared with RWPE-1 cells, while the expression of hsa_circ_0031408 and hsa_circ_0085494 was significantly upregulated in PC-3 cells when compared with RWPE-1 cells. GO and Kyoto Encyclopedia of Genes and Genomes analyses found that target genes were mainly enriched in metabolic processes and pathways involving phosphoinositide 3-kinase-Akt signaling, hypoxia-inducible factor-1 signaling, p53 signaling, and the cell cycle. A total of 11 miRNA target genes showing differential expression between PCa and healthy samples were selected, and their mRNA and protein expression were validated by GEPIA and HPA databases, respectively. Of these, PDE7B, DMRT2, and TGFBR3 were identified as potentially playing a role in PCa progression. Finally, three circRNA-miRNA-mRNA interaction axes were predicted by bioinformatics: hsa_circ_0024353-hsa-miR-940-PDE7B, hsa_circ_0024353-hsa-miR-1253-DMRT2, and hsa_circ_0085494-hsa-miR-330-3p-TGFBR3. Conclusion This study identified three circRNA-miRNA-mRNA interaction axes that might provide novel insights into the potential mechanisms underlying PCa development.

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.

This study was to evaluate the impact of the symptoms of overactive bladder (OAB) syndrome on female sexual function. Seventy nine patients with OAB (OAB group) and 79 healthy women (control group) underwent physical examination at our center, and had their sexual function evaluated using the female sexual function index (FSFI). In accordance with the presence or absence of urge incontinence, the OAB group was further divided into the wet and dry groups. The sexual function was evaluated again after 3 months of pharmacotherapy. We investigate the difference of sexual function between OAB and control group. The effect of OAB severity and OAB pharmacotherapy on sexual function was also explored. There were no significant differences between OAB group and control group, including age, body mass index (BMI), education, occupation, fertility, parity, childbirth, and menopause. Compared with the control group, the OAB group had significantly lower FSFI scores. The respective mean ± standard error FSFI scores in the control group and the OAB group were 2.98 ± 1.07 and 2.27 ± 0.96 for desire, 3.48 ± 1.16 and 2.32 ± 1.44 for arousal, 4.60 ± 1.13 and 3.10 ± 1.95 for lubrication, 3.37 ± 0.87 and 2.63 ± 1.04 for orgasm, 3.58 ± 1.02 and 2.41 ± 1.35 for sexual satisfaction, 3.58 ± 1.02 and 2.41 ± 1.35 for sexual pain, and 22.24 ± 5.29 and 15.59 ± 7.47 for the total score (P

BACKGROUND Evidence indicates that there is an important role for long non-coding RNAs (lncRNA) in numerous cellular processes and that lncRNAs dysregulation contributes to tumor progression. Improved insight into the molecular characteristics of bladder cancer is required to predict outcomes and to develop a new rationale for targeted therapeutic strategies. Bioinformatics methods, including functional enrichment and network analysis combined with survival analysis, are required to process a large volume of data to obtain further information about differentially expressed genes (DEGs) in bladder cancer. This study aimed to explore the role of lncRNAs and their regulation network in bladder cancer. MATERIAL AND METHODS We analyzed bladder cancer data by The Cancer Genome Atlas profiling to identify differentially expressed lncRNAs in bladder cancer. The genes involved in the circlncRNAnet database were evaluated using Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO), evolutionary relationship analysis, and protein-protein interaction (PPI) networks. RESULTS Two new lncRNAs, ADAMTS9-AS1 and LINC00460, were shown to be differentially expressed in bladder cancer. Patients were divided into 2 groups (high expression and low expression) according to their median expression values. The overall survival and disease-free survival of patients with high ADAMTS9-AS1 bladder cancer were significantly shorter; the expression of LINC00460 had no significant correlation with survival. GO and KEGG analysis of the 2 lncRNA-related genes revealed that these lncRNAs played a vital role in tumorigenesis. Bioinformatics analysis showed that key genes related to LINC00460, including CXCL, CCL, and CSF2, may be related to the development of bladder cancer. The low expression of ADAMTS9-AS1 may influence the survival rate of bladder cancer with the hub gene as a target. CONCLUSIONS LncRNA, including LINC00460 and ADAMTS9-AS1, might play a crucial role in the biosynthesis network of bladder cancer. Differential expression results of ADAMTS9-AS1 suggests it may be correlated with a worse prognosis and a shorter survival time. We outlined the biosynthesis network that regulates lncRNAs in bladder cancer. Further experimental data is needed to validate our results.

Objective To identify hub genes and pathways involved in castrate-resistant prostate cancer (CRPC). Methods The gene expression profiles of GSE70768 were downloaded from Gene Expression Omnibus (GEO) datasets. A total of 13 CRPC samples and 110 tumor samples were identified. The differentially expressed genes (DEGs) were identified, and the gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analysis was performed. Protein-protein interaction (PPI) network module analysis was constructed and performed in Cytoscape software. Weighted correlation network analysis (WGCNA) was conducted to determine hub genes involved in the development and progression of CRPC. The gene expression profiles of GSE80609 were used for validation. Results A total of 1738 DEGs were identified, consisting of 962 significantly down-regulated DEGs and 776 significantly upregulated DEGs for the subsequent analysis. GO term enrichment analysis suggested that DEGs were mainly enriched in the extracellular matrix organization, extracellular exosome, extracellular matrix, and extracellular space. KEGG pathway analysis found DEGs significantly enriched in the focal adhesion pathway. PPI network demonstrated that the top 10 hub genes were ALB, ACACB, KLK3, CDH1, IL10, ALDH1A3, KLK2, ALDH3B2, HBA1, COL1A1. Also, WGCNA identified the top 5 hub genes in the turquoise module, including MBD4, BLZF1, PIP5K2B, ZNF486, LRRC37B2. Plus, the Venn diagram demonstrated that HBA1 was the key gene in both GSE70768 and GSE80609 datasets. Conclusions These newly identified genes and pathways could help urologists understand the differences in the mechanism between CRPC and PCa. Besides, it might be promising targets for the treatment of CRPC.

Transurethral resection of the prostate (TURP) remains the 'gold standard' for surgical treatment of benign prostatic obstruction (BPO). Recently, anatomical endoscopic enucleation of the prostate (AEEP) using holmium laser, thulium laser and plasma, etc., is extensively applied in clinical practice. However, perioperative complications of AEEP are inevitable in spite of lower incidence compared with TURP. This study reviewed the literature related to the aetiology, prevention and treatment of common complications of AEEP, which would contribute to the diagnosis and treatment of BPO.

Testicular cancer is the most common solid malignancy among young men. We downloaded data of testicular cancer patients from The Cancer Genome Atlas database to find novel genes in the testicular cancer microenviroment based on ESTIMATE algorithm-derived immune scores. A total of 156 cases of testicular cancer were included in this study and 165 cases of normal testicular tissues were used. We divided the testicular cancer patients into high- and low-score groups based on their immune scores. We identified 1,226 differentially expressed genes (fold change > 2, false discovery rate < 0.05), including 688 downregulated genes and 538 upregulated genes, between these two groups. The top Gene Ontology terms were involved in the immune response-regulating cell surface receptor signaling pathway, immune response-activating cell surface receptor signaling pathway, external side of the plasma membrane, and receptor ligand activity. By performing the Kyoto Encyclopedia of Genes and Genomes analysis, we demonstrated that cAMP signaling pathway was highly enriched among these differentially expressed genes. High expression of LINC01564, LINC02208, ODAM, RNA5SP111, and RNU6-196P were found to be associated with poor overall survival. The expression of genes was further validated by the Human Protein Atlas and only ALB and IFNG were demonstrated to be differentially expressed between testis tissue and testicular cancer tissue.

Background. Patients with brain metastases (BM) from renal cell carcinoma (RCC) were considered to experience a poor prognosis. However, there is little knowledge on the risk factors for BM from RCC at diagnosis. This study was aimed at exploring the risk factors for patients with BM from RCC and the interaction among these risk factors. Methods. A total of 38759 cases of RCC were identified from the Surveillance, Epidemiology, and End Results (SEER) database. Risk factors for BM from RCC were evaluated by univariate and multivariate logistic regression analyses. Interaction effect between age and tumor size was tested. Results. There was a significant difference in univariate analysis, including T stage, tumor size, grades III and IV, lymph node metastasis, bone metastasis, liver metastasis, lung metastasis, and surgery. There was a significant difference in multivariate analysis, including age, T stage, tumor size<10 cm, grade IV, lymph node metastasis, bone metastasis, lung metastasis, and surgery. Patients older than 70 had 0.653-fold lower risk of developing BM compared with those younger than 70. Patients with tumor size≥4 cm and those<4 cm. The larger the tumor size, the higher the incidence of BM from RCC in those whose tumor size was less than 10 cm. An interaction test between the tumor size and age on brain metastasis was statistically significant in the crude analysis (P=0.0114) and model II analysis (P=0.0248) but not in model I analysis (P=0.1136). Although age significantly affected the risk of BM from RCC, impact of age on the risk of developing BM from RCC was limited to patients with tumor size≥7 cm. Conclusion. Both tumor size and age were independent risk factors for brain metastases in patients with RCC. The impact of age on the risk of developing BM from RCC was limited to patients with tumor size≥7 cm. Patients with a larger tumor size and younger age might have the higher risk of developing BM at diagnosis of RCC.

The mechanism of upper tract recurrence after local excision of bladder cancer remains unknown. This study was designed to identify risk factors for upper tract urothelial recurrence following local tumor excision of bladder cancer. To identify 76 597 bladder cancer patients, comprising 76 537 nonrecurrence and 60 recurrence patients, the Surveillance, Epidemiology, and End Results database was used. Kaplan‐Meier analysis and univariate and multivariate Cox proportional hazards regression models were used to determine the risk factors. Compared with the nonrecurrence group, the recurrence group was associated with older age, higher grade, high T stage, and higher proportional squamous cell carcinomas. Univariate Cox proportional hazards regression model showed that age, grades III and IV, T stage, and pathology were significantly associated with worse upper tract urothelial recurrence (UTUR) survival. However, after adjusting for prognostic factors, grade was no longer an independent prognostic factor in multivariate analysis. This study demonstrates that clinical prognosis of UTUR after local bladder tumor excision has significant independent risk factors that include age ≥60 years, T1 and T2 stage, and squamous cell carcinoma, and will require more careful consideration during follow‐up.

To explore the value of Prostate Imaging Reporting and Data System Version 2 (PI-RADS v2) for predicting prostate biopsy results in patients with prostate specific antigen (PSA) levels of 4–10 ng/ml. We retrospectively reviewed multi-parameter magnetic resonance images from 528 patients with PSA levels of 4–10 ng/ml who underwent transrectal ultrasound-guided prostate biopsies between May 2015 and May 2017. Among them, 137 were diagnosed with prostate cancer (PCa), and we further subdivided them according to pathological results into the significant PCa (S-PCa) and insignificant significant PCa (Ins-PCa) groups (121 cases were defined by surgical pathological specimen and 16 by biopsy). Age, PSA, percent free PSA, PSA density (PSAD), prostate volume (PV), and PI-RADS score were collected. Logistic regression analysis was performed to determine predictors of pathological results. Receiver operating characteristic curves were constructed to analyze the diagnostic value of PI-RADS v2 in PCa. Multivariate analysis indicated that age, PV, percent free PSA, and PI-RADS score were independent predictors of biopsy findings, while only PI-RADS score was an independent predictor of S-PCa (P