Translational andrology and urology最新文献

Background: Over the past few years, artificial intelligence (AI) platforms have rapidly gained popularity within medicine. While AI has been applied in various subspecialties of urology, its role in evaluating male factor infertility has not been explored. The objective of this study was to evaluate the diagnostic accuracy of two commonly used AI programs, Google's "Bard" and Bing. This study aimed to assess each program's accuracy in correctly diagnosing a sample patient's semen analysis results and recommending appropriate next steps following diagnosis.

Methods: Each respective AI program was given a set of data which included semen volume, pH, concentration, and sperm motility as a percentage along with a command to list the three most likely diagnoses and the next steps the patient should take. The data sets ranged from entirely normal to abnormal with clearly obstructive and non-obstructive azoospermia, teratozoospermia, oligospermia, or asthenospermia. Study personnel determined the clinical diagnostic accuracy of both Bard's and Bing's semen analysis interpretations. No patient data was utilized for this study.

Results: Bing resulted in only 29% accuracy of interpretation while 57% of results provided partially correct responses. First, second, and third, diagnoses provided resulted in 43%, 29% and 43% accuracy, respectively. Each analysis was 100% accurate in the next steps the patient should take and recommended discussing results with a physician 100% of the time. Bard was slightly more accurate regarding semen analysis with 50% accuracy. First, second, and third diagnoses provided resulted in 75%, 25%, and 25% accuracy, respectively. Bard had 75% accuracy regarding next steps but also had a 100% accuracy rating for recommending discussing results with a physician.

Conclusions: Overall, Bard was more accurate in providing correct analytical information regarding semen analysis (50% vs. 29%). Bard generated consistently accurate first diagnosis (75% vs. 43%). Bing resulted in increased accuracy regarding next steps (100% vs. 75%). Both programs recommended discussing semen analysis results with a physician. Overall, Bing and Bard are not capable of consistently providing patients with accurate analysis, diagnosis, or next steps when given a sample semen analysis. Specific training sets must be developed to provide with accurate interpretation of their urological results in a user-friendly format that can be further addressed with their physician.

Background: Recurrent ureteropelvic junction obstruction (UPJO) accompanied by long proximal ureteral obliteration presents significant challenges for conventional pyeloplasty, primarily due to the elevated tension at the surgical site. Additionally, previous surgeries often lead to scar tissue formation, complicating both the identification of healthy tissue and the success of reconstruction.

Case description: A 38-year-old patient with right UPJO successfully underwent robotic tubular pyeloureteroplasty using a flap and lingual mucosal graft (LMG). The surgical technique involved using the flap to form the posterior plate of the anastomosis, with the LMG serving as the anterior plate, resulting in a wide, tubularized, and well-vascularized ureteropelvic junction. Intraoperative blood loss was about 50 mL, and operative time was about 220 minutes. Follow-up ultrasound demonstrated sustained reduction in hydronephrosis, which was further confirmed by improved findings on computed tomography urography. Antegrade urography confirmed the absence of ureteral obstruction following removal of the Double-J stent, with no complications observed. During follow-up assessments, the patient reported no symptoms after surgery. By sixteen months postoperatively, the glomerular filtration rate of the right renal increased from 25.03 to 28.03 mL/min, and split renal function improved from 33.00% to 37.56%.

Conclusions: Robotic tubular pyeloureteroplasty using a flap and LMG is a safe and effective surgical option, offering a promising treatment for selected patients with UPJO. This technique serves as an alternative for those with complex anatomical challenges typically encountered in pyeloplasty.

Background: Androgen receptor signaling inhibitors (ARSIs) have become the standard of care for metastatic castration-sensitive prostate cancer (mCSPC). However, Japanese patients treated with apalutamide experience dermatologic adverse events at higher rates than Western populations. This study aimed to identify clinical determinants of apalutamide-induced rash and evaluate the impact of treatment modification on relative dose intensity (RDI) and oncological outcomes.

Methods: We retrospectively analyzed 95 patients with mCSPC treated with apalutamide plus androgen deprivation therapy (ADT) between February 2018 and April 2023. Patients who initiated therapy at reduced doses were excluded. The primary endpoint was the incidence of apalutamide-induced rash and its predictors. The secondary endpoint was the effect of RDI on progression-free survival (PFS), defined as time to castration-resistant prostate cancer (CRPC). Receiver operating characteristic analyses were used to identify risk factors for rash, and Cox proportional hazards models were used to assess predictors of progression.

Results: Rash occurred in 38 patients (40%), including 13 (13.7%) with grade 3 events, with a median onset of 2 months. Older age [odds ratio (OR) =1.07, P=0.048] and lower body mass index (BMI; OR =0.89, P=0.049) were independent predictors. Cutoff values of age ≥ 68 years and BMI ≤19.7 kg/m² were identified, with cumulative rash incidence increasing stepwise with the number of risk factors (7.7%, 38.1%, and 68.4% for no, one, and two factors, respectively). During follow-up, 37.7% of patients were able to continue apalutamide at the full dose, whereas the remainder required dose reduction or discontinuation. Despite dose modifications, reduced RDI was not associated with inferior PFS, and multivariable analysis confirmed that RDI was not an independent predictor of progression.

Conclusions: Advanced age and low BMI are significant risk factors for apalutamide-induced rash in patients with mCSPC. Importantly, decreased RDI resulting from dose reduction or interruption did not compromise PFS, implying that timely dose modification may be a safe and effective strategy to manage adverse events without impairing oncological efficacy.

Background: Clear cell renal cell carcinoma (ccRCC) represents the most common histological subtype of kidney cancer and constitutes a major global health burden. Despite increasing recognition of the roles of migrasome-related long non-coding RNAs (MRLs) in tumor biology, their prognostic relevance in ccRCC remains largely undefined. Therefore, this study aimed to systematically identify MRLs associated with ccRCC prognosis and construct a robust prognostic model to improve risk stratification and guide potential therapeutic strategies.

Methods: To identify MRLs, we initially performed a correlation analysis integrating transcriptomic profiles with clinical parameters of ccRCC patients from The Cancer Genome Atlas (TCGA). Leveraging the expression matrix of MRLs, we subsequently employed the least absolute shrinkage and selection operator (LASSO) regression to construct a prognostic signature. A comprehensive assessment was carried out to determine the model's predictive robustness. At single-cell resolution, we delineated the cellular composition of ccRCC, capturing transcriptional heterogeneity across distinct cell populations. Ultimately, long non-coding RNAs (lncRNAs) derived from the prognostic model were experimentally validated in clinical specimens through reverse transcription-quantitative polymerase chain reaction (RT-qPCR), and the landscape of migrasome-related genes (MRGs) was further defined using single-cell RNA sequencing (scRNA-seq) data.

Results: A prognostic signature comprising five MRLs-EMX2OS, AC106897.1, AC087645.2, AC121338.2, and C5orf66-was established to stratify patient risk. The derived risk score was subsequently validated as an independent predictor of overall survival (OS) in ccRCC patients. A nomogram integrating this score exhibited strong predictive capability. Immune landscape analysis uncovered marked differences in functional immune features between high- and low-risk cohorts defined by the lncRNA-based model. Notably, the high-risk group displayed enrichment of immune-related processes, whereas the low-risk group demonstrated enhanced predicted responsiveness to a spectrum of therapeutic compounds. scRNA-seq identified 17 distinct cellular subpopulations and highlighted the involvement of tumor cell-intrinsic vascular endothelial growth factor (VEGF) signaling in modulating migrasome-associated molecular programs.

Conclusions: This study emphasizes the prognostic utility of a signature comprising five MRLs for ccRCC, offering valuable insights for clinical risk stratification and therapeutic decision-making. Additionally, modulation of tumor cell migration and migrasome function via the VEGF signaling pathway offers a mechanistic basis for targeted intervention.

Background: Bladder cancer (BC) is a prevalent urinary tract malignancy with high morbidity and mortality. Despite advances in therapeutic modalities, early diagnosis and precise treatment remain challenging, highlighting the need for reliable biomarkers and therapeutic targets. This study aims to identify molecular targets and drug candidates for BC by integrating cross-omics quantitative trait loci (xQTLs), OLINK proteomics (a high-throughput plasma protein measurement platform), and transcriptomics data, alongside prospective cohort studies and multi-omics analyses.

Methods: We utilized data from the UK Biobank Pharma Proteomics Project (UKB-PPP), deCODE Genetics, and the Atherosclerosis Risk in Communities study (ARIC). Protein quantitative trait loci (pQTLs) associated with BC were screened via Summary-data-based Mendelian Randomization (SMR). Associations between proteins and BC risk were evaluated using Cox regression and a random survival forest (RSF) model. Drug targets were identified through genome-wide association studies (GWAS) and co-localization, while expression quantitative trait loci (eQTLs) analyses and single-cell RNA sequencing investigated gene expression and cellular heterogeneity. Methylation quantitative trait loci (mQTLs) analysis provided insights into epigenetic mechanisms.

Results: Among the 16 proteins associated with BC, seven exhibited a positive correlation: MFGE8, ROR1, CTSS, CLEC4G, PLAT, CD59, TNFRSF19. The RSF model demonstrated superior performance. Co-localization analyses identified WFDC1, GSTM4, and RHOC as potential drug targets. Molecular docking validated camptothecin and lycorine as promising therapeutic candidates. eQTLs analyses implicated MFGE8, CTSS, TNFRSF19, and IL1RAP in BC risk and prognosis. Methylation analyses indicated complex regulation of CTSS and TNFRSF19.

Conclusions: WFDC1, RHOC, and GSTM4 exhibit therapeutic potential, while MFGE8, CTSS, TNFRSF19, and IL1RAP predict risk and prognosis, providing insights for precision diagnosis and treatment.

Background: Renal cell carcinoma (RCC) is biologically heterogeneous, complicating prognosis and treatment. Our study aims to clarify prognostic factors and support evidence-based clinical decision-making in RCC management.

Methods: This study analyzed clinical data of RCC patients diagnosed between 2010 and 2021 from the Surveillance, Epidemiology, and End Results database. Prognostic factors associated with patient outcomes were selected using least absolute shrinkage and selection operator regression and Boruta. Seven machine learning algorithms were employed to construct predictive models for 5-year survival in RCC patients. Shapley Additive Explanations (SHAP) analysis was utilized to visually interpret the model's predictions. Model performance was evaluated using the following metrics: accuracy, sensitivity, specificity, positive predictive value, negative predictive value, F1 score, area under the receiver operating characteristic curve (AUC), Brier score, and estimated calibration index (ECI).

Results: In the realm of predicting 5-year survival for RCC patients, the gradient boosting machine (GBM) model achieved the best overall performance with an AUC of 0.841 [95% confidence interval (CI): 0.833-0.850], along with the lowest Brier score (0.127; 95% CI: 0.126-0.128) and ECI (0.005; 95% CI: 0.003-0.007). Furthermore, SHAP analysis highlighted key clinical factors influencing 5-year survival of RCC patients, reinforcing their prognostic significance in RCC.

Conclusions: This study developed an accurate predictive model for 5-year survival in RCC patients using machine learning, which may offer valuable support to clinicians in making informed clinical decisions.

Background: Chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS) represents a prevalent urological disorder characterized by an unfavorable prognosis. Accumulating evidence indicates that suppression of excessive reactive oxygen species (ROS) generation significantly ameliorates its inflammatory manifestations. 7,8-dihydroxyflavone (7,8-DHF), a specific TrkB receptor agonist, which could subsequently trigger downstream signaling pathways such as AKT, demonstrates antioxidant and anti-inflammatory properties across diverse pathological conditions. Nevertheless, its potential therapeutic efficacy against CP/CPPS remains undefined. The aim of this study is to investigate the effects of 7,8-DHF on CP/CPPS and elucidate the underlying mechanisms involved, thereby providing fundamental experimental data for the clinical research of pharmacological interventions for CP/CPPS.

Methods: CP/CPPS rat model was established via intraprostatic injection of complete Freund's adjuvant (CFA). Utilizing this experimental prostatitis model, we evaluated the effects of 7,8-DHF on prostate index, mechanical hyperalgesia, prostate histopathology, oxidative stress markers, pro-inflammatory cytokine expression, and immune cell infiltration. Molecular analyses further assessed TrkB/AKT/SIRT3 signaling pathways in RWPE-1 cells. We have cultivated human prostate epithelial cells RWPE-1. In vitro cell models were constructed through lipopolysaccharide (LPS) induction. The effects of 7,8-DHF on LPS-induced cellular damage and inflammatory responses were validated through Cell Counting Kit-8 (CCK-8) and enzyme-linked immunosorbent assay (ELISA) assays.

Results: At the animal level, 7,8-DHF administration concurrently suppressed CFA-induced elevations in prostate index, mechanical hyperalgesia, inflammatory cell infiltration, and pro-inflammatory cytokine levels, while significantly ameliorating histological damage. At the cellular level, 7,8-DHF attenuates LPS-induced cellular damage and inflammatory responses through mechanisms involving the activation of TrkB/AKT/SIRT3 signaling, augmented antioxidant enzyme activity, mitigated ROS overproduction and pro-inflammatory mediator expression, thus disrupting the "oxidative stress-inflammation" vicious cycle.

Conclusions: This study identifies 7,8-DHF as a novel therapeutic agent for CP/CPPS, and the potential role of the TrkB/AKT/SIRT3 pathway in the improvement of CP/CPPS by 7,8-DHF, thereby establishing a foundational basis for future CP/CPPS therapeutics.