Bladder urothelial carcinoma (BLCA), a prevalent malignant neoplasm affecting the human urinary system, is frequently linked with an unfavorable prognosis in a significant proportion of individuals. More effective and sensitive markers are needed to provide a reference for prognostic judgment. We obtained RNA sequencing data and clinical information of individuals from TCGA, and 133 copper metabolism-related genes from literature. Prognostic genes were evaluated by univariate/multivariate Cox regression analysis and LASSO analysis, and a risk-scoring model was established and validated in the GEO dataset. The CIBERSORT method was utilized to explore immune cell infiltration in BLCA individuals. In addition, tumor immune dysfunction and exclusion (TIDE) and immunophenoscore (IPS) were utilized to verify whether the model can foretell the response of BLCA individuals to immunotherapy. We successfully constructed an 8-gene risk scoring model to foretell individuals\' overall survival, and the model performed well in TCGA training and GEO validation cohorts. Lastly, a nomogram containing clinical parameters and risk scores was constructed to help individualized result prediction for individuals. Calibration curves demonstrated a high degree of concordance between the observed and projected survival durations, attesting to its exceptional predictive accuracy. Analysis utilizing CIBERSORT unveiled elevated levels of immune cell infiltration in individuals classified as low risk. TIDE and IPS analyses substantiated that low-risk individuals exhibited a more favorable response to immunotherapy. In summary, the model held immense potential for stratifying the risk of survival and guiding tailored treatment approaches for individuals with BLCA, thereby offering valuable insights for personalized therapeutic interventions.

BACKGROUND: Bladder cancer is a common malignancy with high recurrence rate. Early diagnosis and recurrence surveillance are pivotal to patients\' outcomes, which require novel minimal-invasive diagnostic tools. The urinary microbiome is associated with bladder cancer and can be used as biomarkers, but the underlying mechanism is to be fully illustrated and diagnostic performance to be improved.
METHODS: A total of 23 treatment-naïve bladder cancer patients and 9 non-cancerous subjects were enrolled into the Before group and Control group. After surgery, 10 patients from the Before group were further assigned into After group. Void mid-stream urine samples were collected and sent for 16S rDNA sequencing, targeted metabolomic profiling, and flow cytometry. Next, correlations were analyzed between microbiota, metabolites, and cytokines. Finally, receiver operating characteristic (ROC) curves of the urinary biomarkers were plotted and compared.
RESULTS: Comparing to the Control group, levels of IL-6 (p < 0.01), IL-8 (p < 0.05), and IL-10 (p < 0.05) were remarkably elevated in the Before group. The α diversity of urine microbiome was also significantly higher, with the feature microbiota positively correlated to the level of IL-6 (r = 0.58, p < 0.01). Significant differences in metabolic composition were also observed between the Before and Control groups, with fatty acids and fatty acylcarnitines enriched in the Before group. After tumor resection, cytokine levels and the overall microbiome structure in the After group remained similar to that of the Before group, but fatty acylcarnitines were significantly reduced (p < 0.05). Pathway enrichment analysis revealed beta-oxidation of fatty acids was significantly involved (p < 0.001). ROC curves showed that the biomarker panel of Actinomycetaceae + arachidonic acid + IL-6 had superior diagnostic performance, with sensitivity of 0.94 and specificity of 1.00.
CONCLUSIONS: Microbiome dysbiosis, proinflammatory environment and altered fatty acids metabolism are involved in the pathogenesis of bladder cancer, which may throw light on novel noninvasive diagnostic tool development.

OBJECTIVE: To explore the clinical significance of OLC1 and cigarette smoking in bladder urothelial carcinoma (UBC).
METHODS: OLC1 mRNA expression was detected in 106 UBC samples by mRNA array or reverse real-time PCR. OLC1 protein expression in 114 UBC samples was detected by immunohistochemical staining. Wild-type C57BL/6J mice were injected with cigarette smoke condensate (n = 12) or exposed to cigarette smoke (n = 6) to investigate the correlations between cigarette smoking and OLC1 expression using mRNA array.
RESULTS: The mRNA and protein expression of OLC1 were higher in tumor samples (p < 0.01) and significantly correlated with tumor stage (p < 0.05). OLC1 protein expression and smoking history were correlated with disease-free survival (p < 0.05). OLC1 expression was significantly elevated in smoking patients with higher smoking intensity on both mRNA and protein levels (p < 0.05). Cigarette smoke exposure experiments revealed that OLC1 mRNA overexpressed in bladder uroepithelium of mice.
CONCLUSIONS: OLC1 could serve as a potential prognosis biomarker of UBC, especially for smoking patients.

BACKGROUND: Lymph node metastasis (LNM) is associated with worse prognosis in bladder urothelial carcinoma (BUC) patients. This study aimed to develop and validate machine learning (ML) models to preoperatively predict LNM in BUC patients treated with radical cystectomy (RC).
METHODS: We retrospectively collected demographic, pathological, imaging, and laboratory information of BUC patients who underwent RC and bilateral lymphadenectomy in our institution. Patients were randomly categorized into training set and testing set. Five ML algorithms were utilized to establish prediction models. The performance of each model was assessed by the area under the receiver operating characteristic curve (AUC) and accuracy. Finally, we calculated the corresponding variable coefficients based on the optimal model to reveal the contribution of each variable to LNM.
RESULTS: A total of 524 and 131 BUC patients were finally enrolled into training set and testing set, respectively. We identified that the support vector machine (SVM) model had the best prediction ability with an AUC of 0.934 (95% confidence interval [CI]: 0.903-0.964) and accuracy of 0.916 in the training set, and an AUC of 0.855 (95%CI: 0.777-0.933) and accuracy of 0.809 in the testing set. The SVM model contained 14 predictors, and positive lymph node in imaging contributed the most to the prediction of LNM in BUC patients.
CONCLUSIONS: We developed and validated the ML models to preoperatively predict LNM in BUC patients treated with RC, and identified that the SVM model with 14 variables had the best performance and high levels of clinical applicability.

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BACKGROUND: Research has suggested significant correlations among ageing, immune microenvironment, inflammation and tumours. However, the relationships among ageing, immune microenvironment, cystitis and bladder urothelial carcinoma (BLCA) in the bladder have rarely been reported.
METHODS: Bladder single-cell and transcriptomic data from young and old mice were used for immune landscape analysis. Transcriptome, single-cell and The Cancer Genome Atlas Program datasets of BLCA and interstitial cystitis/bladder pain syndrome (IC/BPS) were used to analyse immune cell infiltration and molecular expression. Bladder tissues from mice, IC/BPS and BLCA were collected to validate the results.
RESULTS: Eight types of immune cells (macrophages, B-cells, dendritic cells, T-cells, monocytes, natural killer cells, γδ T-cells and ILC2) were identified in the bladder of mice. Aged mice bladder tissues had a significantly higher number of T-cells, γδ T-cells, ILC2 and B-cells than those in the young group (P < 0.05). Three types of T-cells (NK T-cells, γδ T-cells and naïve T-cells) and three types of B-cells (follicular B-cells, plasma and memory B-cells) were identified in aged mice bladder. Chemokine receptor 7 (CCR7) is highly expressed in aged bladder, IC/BPS and BLCA (P < 0.05). CCR7 is likely to be involved in T- and B-cell infiltration in aged bladder, IC/BPS and BLCA. Interestingly, the high CCR7 expression on BLCA cell membranes was a prognostic protective factor.
CONCLUSIONS: In this study, we characterised the expression profiles of immune cells in bladder tissues of aged and young mice and demonstrated that CCR7-mediated T- and B-cell filtration contributes to the development of bladder ageing, IC/BPS and BLCA.

OBJECTIVE: To investigate the diagnostic value of urine cyclic RNA-0071196 (circRNA-0071196) in the patients with bladder urothelial carcinoma (BUC).
METHODS: The expression of circRNA-0071196 was detected in the urine samples using qRT-PCR from 40 BUC patients and 30 non-UBC patients at our department from December 2018 to September 2021. The expression difference of circRNA-0071196 was compared between the two groups, and the relationship between the expression of circRNA-0071196 in the urine of UBC patients and the clinical pathological characteristics was analyzed.
RESULTS: (1) The expression of circRNA-0071196 in the urine of BUC group was significantly higher than that in the non-BUC group (P < 0.05). (2) The expression of circRNA-0071196 in the urine of BUC group was not related to age, sex, or lymph node metastasis (P > 0.05). (3) The expression of circRNA-0071196 in the urine of BUC group was related to tumor T stage, tumor grade and muscle invasion. (4) The urine circRNA-0071196 expression effectively distinguished BUC patients from non-BUC patients.
CONCLUSIONS: The elevated expression of urine circRNA-0071196 in BUC patients indicates that circRNA-0071196 has promising potential as a non-invasive urinary biomarker for detecting BUC.

OBJECTIVE: To investigate multiphase computed tomography (CT) radiomics-based combined with clinical factors to predict overall survival (OS) in patients with bladder urothelial carcinoma (BLCA) who underwent transurethral resection of bladder tumor (TURBT).
METHODS: Data were retrospectively collected from 114 patients with primary BLCA from February 2016 to February 2018. The regions of interest (ROIs) of the plain, arterial, and venous phase images were manually segmented. The Cox regression algorithm was used to establish 3 basic models for the plain phase (PP), arterial phase (AP), and venous phase (VP) and 2 combination models (AP + VP and PP + AP + VP). The highest-performing radiomics model was selected to calculate the radiomics score (Rad-score), and independent risk factors affecting patients\' OS were analyzed using Cox regression. The Rad-score and clinical risk factors were combined to construct a joint model and draw a visualized nomogram.
RESULTS: The combined model of PP + AP + VP showed the best performance with the Akaike Information Criterion (AIC) and Consistency Index (C-index) in the test group of 130.48 and 0.779, respectively. A combined model constructed with two independent risk factors (age and Ki-67 expression status) in combination with the Rad-score outperformed the radiomics model alone; AIC and C-index in the test group were 115.74 and 0.840, respectively. The calibration curves showed good agreement between the predicted probabilities of the joint model and the actual (p < 0.05). The decision curve showed that the joint model had good clinical application value within a large range of threshold probabilities.
CONCLUSIONS: This new model can be used to predict the OS of patients with BLCA who underwent TURBT.

BACKGROUND: Bladder urothelial carcinoma (BLCA) is the most common malignancy of the urinary tract, presenting with a wide range of clinical symptoms and prognosis. Disulfidptosis is a newly identified cell death method and closely associated with BLCA progression, prognosis, and treatment outcome. Currently, we need to construct a new prognostic model for disulfidptosis-related long noncoding RNAs (drlncRNAs) to improve the treatment strategy of BLCA.
METHODS: The data for BLCA samples were obtained from The Cancer Genome Atlas (TCGA), and then 10 unique genes related to disulfidoptosis (DRGs) were identified from research papers. The differences between the two groups showed in this study were used to create the \"disulfidptosis-related long noncoding RNAs score\" (disulfidptosis-score) prognostic model.
RESULTS: We identified two groups of drlncRNAs with high and low disulfidptosis scores in this study. Patients with low disulfidptosis scores had a better overall survival rate compared to those with high scores in bladder cancer, and the high disulfidptosis score subtype exhibited more active malignant pathways related to cancer than the low score subtype. We found that the low disulfidptosis-score subgroup had better prognosis than the high disulfidptosis-score subgroup. The expression of mutation burden was much higher in the low disulfidptosis-score group than in the high disulfidptosis-score group. The low disulfidptosis-score subgroup of patients exhibited significantly higher proportions of plasma cells, T cells CD8, and Tregs, while the high-risk subgroup had a greater abundance of Macrophages M0 and Macrophages M2. The disulfidptosis-score showed a strong correlation with the sensitivity of chemotherapeutic drugs, and patients in the low disulfidptosis-score group were more likely to exhibit an immune response and respond positively to immunotherapy. Additionally, we developed a nomogram to enhance the accuracy of the disulfidptosis-clinical score.
CONCLUSIONS: Based on our investigation of disulfidptosis-score in BLCA, disulfidptosis-score may have an important role in TME, prognosis, and drug sensitivity. We also investigated the significance of the disulfidoptosis-score in relation to immunotherapy and immune response, providing a basis for improving prognosis and responding to immunotherapy among patients with BLCA.

OBJECTIVE: To investigate the value of CT urography (CTU) indicators in the quantitative differential diagnosis of bladder urothelial carcinoma (BUC) and inverted papilloma of the bladder (IPB).
METHODS: The clinical and preoperative CTU imaging data of continuous 103 patients with histologically confirmed BUC or IPB were retrospectively analyzed. The imaging data included 6 qualitative indicators and 7 quantitative measures. The recorded clinical information and imaging features were subjected to univariate and multivariate logistic regression analysis to find independent risk factors for BUC, and a combined multi-indicator prediction model was constructed, and the prediction model was visualized using nomogram. ROC curve analysis was used to calculate and compare the predictive efficacy of independent risk factors and nomogram.
RESULTS: Junction smoothness, maximum longitudinal diameter, tumor-wall interface and arterial reinforcement rate were independent risk factors for distinguishing BUC from IPB. The AUC of the combined model was 0.934 (sensitivity = 0.808, specificity = 0.920, accuracy = 0.835), and its diagnostic efficiency was higher than that of junction smoothness (AUC=0.667, sensitivity = 0.654, specificity = 0.680, accuracy = 0.660), maximum longitudinal diameter (AUC=0.757, sensitivity = 0.833, specificity = 0.604, accuracy = 0.786), tumor-wall interface (AUC=0.888, sensitivity = 0.755, specificity = 0.808, accuracy = 0.816) and Arterial reinforcement rate (AUC=0.786, sensitivity = 0.936, specificity = 0.640, accuracy = 0.864).
CONCLUSIONS: Above qualitative and quantitative indicators based on CTU and the combination of them may be helpful to the differential diagnosis of BUC and IPB, thus better assisting in clinical decision-making.
CONCLUSIONS: 1. Bladder urothelial carcinoma (BUC) and inverted papilloma of the bladder (IPB) exhibit similar clinical symptoms and imaging presentations. 2. The diagnostic value of CT urography (CTU) in distinguishing between BUC and IPB has not been documented. 3. BUC and IPB differ in lesion size, growth pattern and blood supply. 4. The diagnostic efficiency is optimized by integrating multiple independent risk factors into the prediction model.