How education level affects postoperative rehabilitation and follow-up: a single-center experience.

BACKGROUND: Radical prostatectomy remains the fundamental treatment for prostate cancer, and improving patients' compliance with postoperative follow-ups is essential for improving patients' quality of life. This study investigates the effect of education levels on patients' recovery and follow-up after radical prostatectomy. METHODS: Data from 1,112 patients undergoing radical prostatectomy between 2011 and 2020 were collected using medical records, and "pc-follow" systems were used to collect patients' baseline information, education level, pathological information, number of outpatient visits, the time interval between each visit, and PSA test data. RESULTS: Regarding postoperative outpatient data, there was no difference in the number of outpatient visits among the different education level groups in Shanghai (P = 0.063). A significant difference was found in the interval between outpatient visits among the groups (P < 0.001). Furthermore, significant differences were detected in the number and duration of outpatient clinic visits among the education level groups in all patients (P = 0.016, P = 0.0027). By contrast, no significant difference was found in the recovery time of urinary continence between all patients and those in Shanghai, grouped according to education level (P = 0.082, P = 0.68). For all patients and patients in the Shanghai area, the number of PSA follow-ups increased gradually with an increasing level of education (P < 0.001, P = 0.0029). CONCLUSIONS: Education level affected the number of postoperative clinic visits, compliance, and the number of PSA tests. However, no significant effect on the recovery of urinary continence was found. Further, clinicians must increase their focus on patients with low education levels to achieve equitable access to health services for all patients.

Multi-omics analysis of tumor angiogenesis characteristics and potential epigenetic regulation mechanisms in renal clear cell carcinoma.

BACKGROUND: Tumor angiogenesis, an essential process for cancer proliferation and metastasis, has a critical role in prognostic of kidney renal clear cell carcinoma (KIRC), as well as a target in guiding treatment with antiangiogenic agents. However, tumor angiogenesis subtypes and potential epigenetic regulation mechanisms in KIRC patient remains poorly characterized. System evaluation of angiogenesis subtypes in KIRC patient might help to reveal the mechanisms of KIRC and develop more target treatments for patients. METHOD: Ten independent tumor angiogenesis signatures were obtained from molecular signatures database (MSigDB) and gene set variation analysis was performed to calculate the angiogenesis score in silico using the Cancer Genome Atlas (TCGA) KIRC dataset. Tumor angiogenesis subtypes in 539 TCGA-KIRC patients were identified using consensus clustering analysis. The potential regulation mechanisms was studied using gene mutation, copy number variation, and differential methylation analysis (DMA). The master transcription factors (MTF) that cause the difference in tumor angiogenesis signals were completed by transcription factor enrichment analysis. RESULTS: The angiogenesis score of a prognosis related angiogenesis signature including 189 genes was significantly correlated with immune score, stroma score, hypoxia score, and vascular endothelial growth factor (VEGF) signal score in 539 TCGA KIRC patients. MMRN2, CLEC14A, ACVRL1, EFNB2, and TEK in candidate gene set showed highest correlation coefficient with angiogenesis score in TCGA-KIRC patients. In addition, all of them were associated with overall survival in both TCGA-KIRC and E-MTAB-1980 KIRC data. Clustering analysis based on 183 genes in angiogenesis signature identified two prognosis related angiogenesis subtypes in TCGA KIRC patients. Two clusters also showed different angiogenesis score, immune score, stroma score, hypoxia score, VEGF signal score, and microenvironment score. DMA identified 59,654 differential methylation sites between two clusters and part of these sites were correlated with tumor angiogenesis genes including CDH13, COL4A3, and RHOB. In addition, RFX2, SOX13, and THRA were identified as top three MTF in regulating angiogenesis signature in KIRC patients. CONCLUSION: Our study indicate that evaluation the angiogenesis subtypes of KIRC based on angiogenesis signature with 183 genes and potential epigenetic mechanisms may help to develop more target treatments for KIRC patients. Video Abstract.

Comprehensive analysis of macrophage-related genes in prostate cancer by integrated analysis of single-cell and bulk RNA sequencing.

Macrophages, as essential components of the tumor immune microenvironment (TIME), could promote growth and invasion in many cancers. However, the role of macrophages in tumor microenvironment (TME) and immunotherapy in PCa is largely unexplored at present. Here, we investigated the roles of macrophage-related genes in molecular stratification, prognosis, TME, and immunotherapeutic response in PCa. Public databases provided single-cell RNA sequencing (scRNA-seq) and bulk RNAseq data. Using the Seurat R package, scRNA-seq data was processed and macrophage clusters were identified automatically and manually. Using the CellChat R package, intercellular communication analysis revealed that tumor-associated macrophages (TAMs) interact with other cells in the PCa TME primarily through MIF - (CD74+CXCR4) and MIF - (CD74+CD44) ligand-receptor pairs. We constructed coexpression networks of macrophages using the WGCNA to identify macrophage-related genes. Using the R package ConsensusClusterPlus, unsupervised hierarchical clustering analysis identified two distinct macrophage-associated subtypes, which have significantly different pathway activation status, TIME, and immunotherapeutic efficacy. Next, an 8-gene macrophage-related risk signature (MRS) was established through the LASSO Cox regression analysis with 10-fold cross-validation, and the performance of the MRS was validated in eight external PCa cohorts. The high-risk group had more active immune-related functions, more infiltrating immune cells, higher HLA and immune checkpoint gene expression, higher immune scores, and lower TIDE scores. Finally, the NCF4 gene has been identified as the hub gene in MRS using the "mgeneSim" function.

UPCARE: Urinary Extracellular Vesicles-Derived Prostate Cancer Assessment for Risk Evaluation.

In the quest for efficient tumor diagnosis via liquid biopsy, extracellular vesicles (EVs) have shown promise as a source of potential biomarkers. This study addresses the gap in biomarker efficacy for predicting clinically significant prostate cancer (csPCa) between the Western and Chinese populations. We developed a urinary extracellular vesicles-based prostate score (EPS) model, utilizing the EXODUS technique for EV isolation from 598 patients and incorporating gene expressions of FOXA1, PCA3, and KLK3. Our findings reveal that the EPS model surpasses prostate-specific antigen (PSA) testing in diagnostic accuracy within a training cohort of 234 patients, achieving an area under the curve (AUC) of 0.730 compared to 0.659 for PSA (p = 0.018). Similarly, in a validation cohort of 101 men, the EPS model achieved an AUC of 0.749, which was significantly better than PSA's 0.577 (p < 0.001). Our model has demonstrated a potential reduction in unnecessary prostate biopsies by 26%, with only a 3% miss rate for csPCa cases, indicating its effectiveness in the Chinese population.

Integrated bioinformatics investigation of adenylyl cyclase family co-expression network in bladder cancer followed by preliminary validation of member 2 (ADCY2) in tumorigenesis and prognosis.

Background: The adenylyl cyclase (ADCY) gene family encodes enzymes responsible for the synthesis of cyclic adenosine monophosphate (cAMP) from adenosine triphosphate (ATP), which comprises nine transmembrane isoforms (ADCYs 1-9). Although ADCYs correlate with intracellular signalling and tumorigenesis in different malignancies, their roles in bladder cancer remain unclear. Methods: Utilizing the bladder urothelial carcinoma (BLCA) dataset from The Cancer Genome Atlas (TCGA), we employed the R package 'limma' to identify differential genes. Subsequent correlation analysis with corresponding clinical data was conducted. Prognostic significance of ADCY family genes was assessed through survival analysis. Univariate and multivariate Cox regression determined ADCY2 as a potential independent risk factor for BLCA. Validation was performed using immunohistochemistry results from independent cohorts. Additionally, we delved into the mechanism of genetic variations, methylation modifications, and signalling pathways of ADCY family genes. Evaluation of their role in the immune microenvironment was achieved through R packages single-sample gene set enrichment analysis (ssGSEA), CIBERPORT, and ESTIMATE. Results: Cases of bladder cancer were retrieved from TCGA, and the transcriptionally differentially expressed members of ADCY were identified (members 2, 4, and 5). Genomic alteration, epigenomic modification, clinicopathological characteristics and clinical survival were systematically investigated. A co-expression network was established based on the intersection of correlated genes, which was centred around ADCY2, ADCY4, and ADCY5. Enrichment analysis revealed that correlated genes were involved in epithelial-mesenchymal transition (EMT). The ADCY2 was selected as the most representative biomarker for prognosis in bladder cancer. Bladder tumour with higher ADCY2 expression had higher prognostic risk and worse survival outcomes. Moreover, ADCY2 was correlated with classic immune checkpoints, and a better responsiveness to immunotherapy was exhibited in high-expression subsets. To ameliorate universality of the conclusion, our study also included several real-world cohorts into the preliminary validation, using datasets from the Gene Expression Omnibus (GEO; GSE13507), tissue microarray (TMA) with 80 bladder cancer inclusion and clinical trial IMvigor210, which were associated with immunotherapy sensitivity, prognosis, and common biomarker presentation. Conclusions: Our study reveals that ADCY family has prognostic value in patients with bladder cancer; the ADCY2 is a prominent prognostic biomarker. The bioinformatics analyses and validation provide direction for further functional and mechanistic studies on the screened members of ADCY family.

Identification of novel molecular subtypes and a signature to predict prognosis and therapeutic response based on cuproptosis-related genes in prostate cancer.

Background: Prostate cancer (PCa) is the most common malignant tumor of the male urinary system. Cuproptosis, as a novel regulated cell death, remains unclear in PCa. This study aimed to investigate the role of cuproptosis-related genes (CRGs) in molecular stratification, prognostic prediction, and clinical decision-making in PCa. Methods: Cuproptosis-related molecular subtypes were identified by consensus clustering analysis. A prognostic signature was constructed with LASSO cox regression analyses with 10-fold cross-validation. It was further validated in the internal validation cohort and eight external validation cohorts. The tumor microenvironment between the two risk groups was compared using the ssGSEA and ESTIMATE algorithms. Finally, qRT-PCR was used to explore the expression and regulation of these model genes at the cellular level. Furthermore, 4D Label-Free LC-MS/MS and RNAseq were used to investigate the changes in CRGs at protein and RNA levels after the knockdown of the key model gene B4GALNT4. Results: Two cuproptosis-related molecular subtypes with significant differences in prognoses, clinical features, and the immune microenvironment were identified. Immunosuppressive microenvironments were associated with poor prognosis. A prognostic signature comprised of five genes (B4GALNT4, FAM83D, COL1A, CHRM3, and MYBPC1) was constructed. The performance and generalizability of the signature were validated in eight completely independent datasets from multiple centers. Patients in the high-risk group had a poorer prognosis, more immune cell infiltration, more active immune-related functions, higher expression of human leukocyte antigen and immune checkpoint molecules, and higher immune scores. In addition, anti-PDL-1 immunotherapy prediction, somatic mutation, chemotherapy response prediction, and potential drug prediction were also analyzed based on the risk signature. The validation of five model genes' expression and regulation in qPCR was consistent with the results of bioinformatics analysis. Transcriptomics and proteomics analyses revealed that the key model gene B4GALNT4 might regulate CRGs through protein modification after transcription. Conclusion: The cuproptosis-related molecular subtypes and the prognostic signature identified in this study could be used to predict the prognosis and contribute to the clinical decision-making of PCa. Furthermore, we identified a potential cuproptosis-related oncogene B4GALNT4 in PCa, which could be used as a target to treat PCa in combination with cuproptosis.

A prognostic cuproptosis-related lncRNA predictive signature for bladder cancer patients.

Cuproptosis is a novel form of cell death in tumours. However, the clinical impact and mechanism of cuproptosis in bladder cancer (BC) remain unclear. This study aimed to explore the functions of long noncoding RNAs (lncRNAs) related to cuproptosis in BC and develop a prognostic predictive model. RNA sequencing and clinicopathological data were derived from The Cancer Genome Atlas and randomly divided into training and validation groups. Cuproptosis-related lncRNAs were identified by Cox regression analysis and least absolute shrinkage and selection operator, and the patients were divided into high- and low-risk groups according to the median value of the signature-based risk score. We established a signature of 17 cuproptosis-associated lncRNAs in the training set. In both sets, patients with higher signature-based risk scores had a notably higher probability of death (P ≤ 0.001) and a shorter survival duration. Cox regression analyses confirmed the risk score as an independent predictor of BC prognosis in the entire set. The area under the curve (AUC) values for 1-, 3-, and 5-year survival were 0.767, 0.734, and 0.764, respectively, confirming that the signature could determine the prognosis of BC. A signature-based nomogram was developed, and its prediction accuracy was validated using calibration curves. Several drugs, including Gemcitabine, Oxaliplatin, Mitoxantrone, Camptothecin, Cytarabine and Irinotecan may benefit low-risk BC patients more. Finally, in vitro experiments confirmed that the cuproptosis-related lncRNAs are highly expressed in bladder cancer cells after cuproptosis induced by exogenous copper ions. In conclusion, a cuproptosis-related lncRNA signature independently predicted prognosis in BC, indicating a possible mechanism and clinical treatment approach.

PBRM1 Deficiency Sensitizes Renal Cancer Cells to DNMT Inhibitor 5-Fluoro-2'-Deoxycytidine.

PBRM1 is a tumor suppressor frequently mutated in clear cell renal cell carcinoma. However, no effective targeted therapies exist for ccRCC with PBRM1 loss. To identify novel therapeutic approaches to targeting PBRM1-deficient renal cancers, we employed a synthetic lethality compound screening in isogenic PBRM1+/+ and PBRM1-/- 786-O renal tumor cells and found that a DNMT inhibitor 5-Fluoro-2'-deoxycytidine (Fdcyd) selectively inhibit PBRM1-deficient tumor growth. RCC cells lacking PBRM1 show enhanced DNA damage response, which leads to sensitivity to DNA toxic drugs. Fdcyd treatment not only induces DNA damage, but also re-activated a pro-apoptotic factor XAF1 and further promotes the genotoxic stress-induced PBRM1-deficient cell death. This study shows a novel synthetic lethality interaction between PBRM1 loss and Fdcyd treatment and indicates that DNMT inhibitor represents a novel strategy for treating ccRCC with PBRM1 loss-of-function mutations.

Construction and validation of a novel cuproptosis-related long noncoding RNA signature for predicting the outcome of prostate cancer.

Background: Prostate cancer (PCa) is one of the most common tumors of the urinary system. Cuproptosis is a novel mode of controlled cell death that is related to the development of various tumor types. However, the functions of cuproptosis-related long noncoding RNAs (CRLs) in PCa have not yet been well studied. Methods: In this study, data of PCa patients were obtained from The Cancer Genome Atlas (TCGA) and from the Changhai Hospital. Univariate and multivariate Cox regression analyses and LASSO regression analysis were conducted to screen CRLs linked to the prognosis of PCa patients. A risk score model was constructed on the basis of CRLs to predict prognosis. PCa patients were categorized into high- and low-risk cohorts. The predictive value of the risk score was evaluated by Kaplan-Meier survival analysis, receiver operating characteristic curves, and nomograms. In addition, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were used to explore possible pathways involving CRLs in PCa. Immune function analysis confirmed the correlation between CRLs and immunity in PCa. Finally, we explored the tumor mutational burden and drug response in the high- and low-risk cohorts. Results: First, we identified seven CRLs (C1orf229, C9orf139, LIPE-AS1, MCPH1-AS1, PRR26, SGMS1-AS1, and SNHG1) that were closely related to prognosis in PCa. The risk score model based on the selected CRLs could accurately predict the prognosis of PCa patients. The high-risk cohort was associated with worse disease-free survival (DFS) time in PCa patients (p < 0.001). ROC curve analysis was performed to confirm the validity of the signature (area under the curve (AUC) at 1 year: 0.703). Nomograms were constructed based on the risk score and clinicopathological features and also exhibited great predictive efficiency for PCa. GO and KEGG analyses showed that the CRLs were mainly enriched in metabolism-related biological pathways in PCa. In addition, immune function analysis showed that patients in the high-risk cohort had higher TMB and were more sensitive to conventional chemotherapy and targeted drugs including doxorubicin, epothilone B, etoposide, and mitomycin C. Conclusion: We constructed a novel CRL-related risk score model to accurately predict the prognosis of PCa patients. Our results indicate that CRLs are potential targets for drug therapy in PCa and provide a possible new direction for personalized treatment of PCa patients.

Case Report: Dendritic Cells and Macrophages Capture Sperm in Chronically Inflamed Human Epididymis.

Chronic inflammation of the male genital tract is thought to be a primary etiological factor of male infertility. The abundance and activation of macrophages and dendritic cells in patients with chronic inflammation of genital tract were closely associated with oligozoospermia and asthenospermia. Chronic epididymitis appears to be more important than seminal vesiculitis or prostatitis due to the direct interaction between spermatozoa and epididymal inflammatory cells. In this study, we present a case report of a 41-year-old male with oligoasthenospermia and chronic epididymitis. Hematoxylin-eosin staining and immunofluorescence analyses showed that antigen presenting cells including macrophages and dendritic cells were found capturing spermatozoa in the lumen of cauda epididymis. To our knowledge, this is the first case report that directly observed dendritic cells capturing spermatozoa in the lumen of an inflamed epididymis. This finding directly explains chronic epididymitis as the possible cause of oligospermia in patients.

MRI-Based Nomogram of Prostate Maximum Sectional Area and Its Zone Area for Prediction of Prostate Cancer.

OBJECTIVE: To reduce unnecessary prostate biopsies, we designed a magnetic resonance imaging (MRI)-based nomogram prediction model of prostate maximum sectional area (PA) and investigated its zone area for diagnosing prostate cancer (PCa). METHODS: MRI was administered to 691 consecutive patients before prostate biopsies from January 2012 to January 2020. PA, central gland sectional area (CGA), and peripheral zone sectional area (PZA) were measured on axial T2-weighted prostate MRI. Multivariate logistic regression analysis and area under the receiver operating characteristic (ROC) curve were performed to evaluate and integrate the predictors of PCa. Based on multivariate logistic regression coefficients after excluding combinations of collinear variables, three models and nomograms were generated and intercompared by Delong test, calibration curve, and decision curve analysis (DCA). RESULTS: The positive rate of PCa was 46.74% (323/691). Multivariate analysis revealed that age, PSA, MRI, transCGA, coroPZA, transPA, and transPAI (transverse PZA-to-CGA ratio) were independent predictors of PCa. Compared with no PCa patients, transCGA (AUC = 0.801) was significantly lower and transPAI (AUC = 0.749) was significantly higher in PCa patients. Both of them have a significantly higher AUC than PSA (AUC = 0.714) and PV (AUC = 0.725). Our best predictive model included the factors age, PSA, MRI, transCGA, and coroPZA with the AUC of 0.918 for predicting PCa status. Based on this predictive model, a novel nomogram for predicting PCa was conducted and internally validated (C-index = 0.913). CONCLUSIONS: We found the potential clinical utility of transCGA and transPAI in predicting PCa. Then, we firstly built the nomogram based on PA and its zone area to evaluate its diagnostic efficacy for PCa, which could reduce unnecessary prostate biopsies.

Evaluation of immune status in testis and macrophage polarization associated with testicular damage in patients with nonobstructive azoospermia.

OBJECTIVE: Immune cells residing in the testicular interstitial space form the immunological microenvironment of the testis. They are assumed to play a role in maintaining testicular homeostasis and immune privilege. However, the immune status and related cell polarization in patients with nonobstructive azoospermia (NOA) remains poorly characterized. System evaluation of the testis immunological microenvironment in NOA patients may help to reveal the mechanisms of idiopathic azoospermia. STUDY DESIGN: The gene expression patterns of immune cells in normal human testes were systematically analyzed by single-cell RNA sequencing (scRNA-seq) and preliminarily verification by the human protein atlas (HPA) online database. The immune cell infiltration profiles and immune status of patients with NOA was analyzed by single-sample gene set enrichment analysis (ssGSEA) and gene set variation analysis (GSVA) based on four independent public microarray datasets (GSE45885, GSE45887, GSE9210, and GSE145467), obtained from Gene Expression Omnibus (GEO) online database. The relationship between immune cells and spermatogenesis score was further analyzed by Spearman correlation analysis. Finally, immunohistochemistry (IHC) staining was performed to identify the main immune cell types and their polarization status in patients with NOA. RESULTS: Both scRNA-seq and HPA analysis showed that testicular macrophages represent the largest pool of immune cells in the normal testis, and also exhibit an attenuated inflammatory response by expressing high levels of tolerance proteins (CD163, IL-10, TGF-ß, and VEGF) and reduced expression of TLR signaling pathway-related genes. Correlation analysis revealed that the testicular immune score and macrophages including M1 and M2 macrophages were significantly negatively correlated with spermatogenesis score in patients with NOA (GSE45885 and GSE45887). In addition, the number of M1 and M2 macrophages was significantly higher in patients with NOA (GSE9210 and GSE145467) than in normal testis. GSVA analysis indicated that the immunological microenvironment in NOA tissues was manifested by activated immune system and pro-inflammatory status. IHC staining results showed that the number of M1 and M2 macrophages was significantly higher in NOA tissues than in normal testis and negatively correlated with the Johnson score. CONCLUSION: Testicular macrophage polarization may play a vital role in NOA development and is a promising potential therapeutic target.

S100A14 inhibits cell growth and epithelial-mesenchymal transition (EMT) in prostate cancer through FAT1-mediated Hippo signaling pathway.

Prostate cancer (PCA) is an epithelial malignant tumor occurring in the prostate gland. It is the second most common male cancer in the world and one of the top five cancer deaths in men. To combat this disease, it is needed to identify important tumor suppressor genes and elucidate the molecular mechanisms. S100 calcium-binding protein A14 (S100A14), a member of the S100 family, is located on chromosome 1q21.3 and contains an EF-hand motif that binds calcium. S100A14 is involved in a variety of tumor biological processes in several types of cancers. Its expression level and related biological functions are tissue or tumor specific. However, its possible effects on prostate cancer are still unclear. Herein, we found the low expression of S100A14 in human prostate cancer tissues and cell lines. S100A14 suppressed the proliferation of prostate cancer cells and promoted cell apoptosis. Additionally, S100A14 suppressed the motility and EMT processes of prostate cancer cells. We further found S100A14 promoted the expression of FAT1 and activated the Hippo pathway, which, therefore, suppressed the prostate cancer progression. The in vivo assays confirmed that S100A14 suppressed tumor growth of prostate cancer cells through FAT1-mediated Hippo pathway in mice. In conclusion, we clarified the mechanism underlying S100A14 suppressing prostate cancer progression and, therefore, we thought S100A14 could serve as a tumor suppressor protein.

Establishment of an Individualized Predictive Model to Reduce the Core Number for Systematic Prostate Biopsy: A Dual Center Study Based on Stratification of the Disease Risk Score.

PURPOSE: To establish an individualized prostate biopsy model that reduces unnecessary biopsy cores based on multiparameter MRI (mpMRI). MATERIALS AND METHODS: This retrospective, non-inferiority dual-center study retrospectively included 609 patients from the Changhai Hospital from June 2017 to November 2020 and 431 patients from the Fujian Union Hospital between 2014 and 2019. Clinical, radiological, and pathological data were analyzed. Data from the Changhai Hospital were used for modeling by calculating the patients' disease risk scores. Data from the Fujian Union Hospital were used for external verification. RESULTS: Based on the data of 609 patients from the Changhai Hospital, we divided the patients evenly into five layers according to the disease risk score. The area under the receiver operating characteristic (ROC) curve (AUC) with 95% confidence intervals (CI) was analyzed. Twelve-core systemic biopsy (12-SBx) was used as the reference standard. The SBx cores from each layer were reduced to 9, 6, 5, 4, and 4. The data of 279 patients with benign pathological results from the Fujian Union Hospital were incorporated into the model. No patients were in the first layer. The accuracies of the models for the other layers were 88, 96.43, 94.87, and 94.59%. The accuracy of each layer would be increased to 96, 100, 100, and 97.30% if the diagnosis of non-clinically significant prostate cancer was excluded. CONCLUSIONS: In this study, we established an individualized biopsy model using data from a dual center. The results showed great accuracy of the model, indicating its future clinical application.

The roles of MRI-based prostate volume and associated zone-adjusted prostate-specific antigen concentrations in predicting prostate cancer and high-risk prostate cancer.

Prostate biopsies are frequently performed to screen for prostate cancer (PCa) with complications such as infections and bleeding. To reduce unnecessary biopsies, here we designed an improved predictive model of MRI-based prostate volume and associated zone-adjusted prostate-specific antigen (PSA) concentrations for diagnosing PCa and risk stratification. Multiparametric MRI administered to 422 consecutive patients before initial transrectal ultrasonography-guided 13-core prostate biopsies from January 2012 to March 2018 at Fujian Medical University Union Hospital. Univariate and multivariate logistic regression analyses and determination of the area under the curve (AUC) of the receiver operating characteristic (ROC) curve was performed to evaluate and integrate the predictors of PCa and high-risk prostate cancer (HR-PCa). The detection rates of PCa was 43.84% (185/422). And the detection rates of HR-PCa was 71.35% (132/185) in PCa patients. Multivariate analysis revealed that prostate volume(PV), PSA density(PSAD), transitional zone volume(TZV), PSA density of the transitional zone(PSADTZ), and MR were independent predictors of PCa and HR-PCa. PSA, peripheral zone volume(PZV) and PSA density of the peripheral zone(PSADPZ) were independent predictors of PCa but not HR-PCa. The AUC of our best predictive model including PSA + PV + PSAD + MR + TZV or PSA + PV + PSAD + MR + PZV was 0.906 for PCa. The AUC of the best predictive model of PV + PSAD + MR + TZV was 0.893 for HR-PCa. In conclusion, our results will likely improve the detection rate of prostate cancer, avoiding unnecessary prostate biopsies, and for evaluating risk stratification.