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Abstract A lack of advanced preclinical mouse tumor models impedes the progress in urothelial carcinoma research. We present here a novel fast, robust, reliable, and highly reproducible model for the genetic induction of bladder cancer in immunocompetent mice. Different sets of oncogenic transposons (Cmyc, Kras) and Cre drivers were transfected into the murine bladder wall of two different genetic backgrounds (Trp53 fl/fl and Braf V600E , Pten fl/fl , Ctnnb1 exon3-fl/fl). Transfection was carried out using in vivo electroporation of the bladder after surgical exploration and transmural or transurethral intravesical plasmid injection. Up to 100% of animals developed urothelial carcinomas of the bladder. Time to tumor onset ranged from 16 to 97 days with a median of approximately 23 days in the fastest groups. Histological examination identified orthotopic urothelial carcinomas in most cases, in some experimental groups up to 100%. The resulting tumors were highly invasive and often metastatic. Metastases were found in up to 100% of tumor bearing mice per group. Taken together, this study establishes the proof-of-principle that in vivo electroporation can be versatilely employed as a reliable, fast, and robust method for the highly reproducible induction of urothelial carcinomas in the murine bladder wall. This novel murine tumor model could pave the way towards more easily modelling subtype specific urothelial carcinomas in mice.

Abstract To determine whether Xpert bladder cancer monitor, a noninvasive PCR-based biomarker test, can predict the need for 2nd transurethral resection of the bladder (TURB) better than clinical assessment. Patients scheduled for TURB were prospectively screened. After initial TURB, patients were assigned to 2nd TURB or follow-up cystoscopy at 3 months (FU) by clinicians’ discretion. Central urine cytology and Xpert monitor tests were performed prior to the 1st TURB and 2nd TURB or FU, respectively. Statistical analysis to compare clinical assessment and Xpert monitor comprised sensitivity (SENS), specificity (SPEC), NPV and PPV. Of 756 screened patients, 171 were included (114 with 2nd TURB, 57 with FU). Residual tumors were detected in 34 patients who underwent 2nd TURB, and recurrent tumors were detected in 2 patients with FU. SENS and SPEC of Xpert monitor were 83.3% and 53.0%, respectively, PPV was 32.6% and NPV was 92.1%. Clinical risk assessment outperformed Xpert monitor. In patients with pTa disease at initial TURB, Xpert monitor revealed a NPV of 96%. Xpert monitor was not superior than clinical assessment in predicting the need for 2nd TURB. It might be an option to omit 2nd TURB for selected patients with pTa disease.

Abstract Background Shared decision-making is the gold standard for good clinical practice, and thus, psychometric instruments have been established to assess patients’ generic preference for participation (e.g., the Autonomy Preference Index, API). However, patients’ preferences may vary depending on the specific disease and with respect to the specific decision context. With a modified preference index (API-Uro), we assessed patients’ specific participation preference in preference-sensitive decisions pertaining to urological cancer treatments and compared this with their generic participation preference. Methods In Study 1, we recruited (N = 469) urological outpatients (43.1% urooncological) at a large university hospital. Participation preference was assessed with generic measures (API and API case vignettes) and with the disease-specific API-Uro (urooncological case vignettes describing medical decisions of variable difficulty). A polychoric exploratory factor analysis was used to establish factorial validity and reduce items. In Study 2, we collected data from N = 204 bladder cancer patients in a multicenter study to validate the factorial structure with confirmatory factor analysis. Differences between the participation preference for different decision contexts were analyzed. Results Study 1: Scores on the specific urooncological case vignettes (API-Uro) correlated with the generic measure (r = .44) but also provided incremental information. Among the disease-specific vignettes of the API-Uro, there were two factors with good internal consistency (α ≥ .8): treatment versus diagnostic decisions. Patients desired more participation for treatment decisions (77.8%) than for diagnostic decisions (22%), χ2(1) = 245.1, p ≤ .001. Study 2: Replicated the correlation of the API-Uro with the API (r = .39) and its factorial structure (SRMR = .08; CFI = .974). Bladder cancer patients also desired more participation for treatment decisions (57.4%) than for diagnostic decisions (13.3%), χ²(1) =84, p ≤ .001. Conclusions The desire to participate varies between treatment versus diagnostic decisions among urological patients. This underscores the importance of assessing participation preference for specific contexts. Overall, the new API-Uro has good psychometric properties and is well suited to assess patients’ preferences. In routine care, measures of participation preference for specific decision contexts may provide incremental, allowing clinicians to better address their patients’ individual needs.

Abstract Introduction Certain sociodemographic characteristics (e.g., older age) have previously been identified as barriers to patients' participation preference in shared decision‐making (SDM). We aim to demonstrate that this relationship is mediated by the perceived power imbalance that manifests itself in patients' negative attitudes and beliefs about their role in decision‐making. Methods We recruited a large sample (N = 434) of outpatients with a range of urological diagnoses (42.2% urooncological). Before the medical consultation at a university hospital, patients completed the Patients' Attitudes and Beliefs Scale and the Autonomy Preference Index. We evaluated attitudes as a mediator between sociodemographic factors and participation preference in a path model. Results We replicated associations between relevant sociodemographic factors and participation preference. Importantly, attitudes and beliefs about one's own role as a patient mediated this relationship. The mediation path model explained a substantial proportion of the variance in participation preference (27.8%). Participation preferences and attitudes did not differ for oncological and nononcological patients. Conclusion Patients' attitudes and beliefs about their role determine whether they are willing to participate in medical decision‐making. Thus, inviting patients to participate in SDM should encompass an assessment of their attitudes and beliefs. Importantly, negative attitudes may be accessible to change. Unlike stable sociodemographic characteristics, such values are promising targets for interventions to foster more active participation in SDM. Patient or Public Contribution This study was part of a larger project on implementing SDM in urological practice. Several stakeholders were involved in the design, planning and conduction of this study, for example, three authors are practising urologists, and three are psychologists with experience in patient care. In addition, the survey was piloted with patients, and their feedback was integrated into the questionnaire. The data presented in this study is based on patients' responses. Results may help to empower our patients.

Abstract Objectives To assess the predictive and prognostic value of changes in longitudinal neutrophile-to-lymphocyte (NLR) ratios in men receiving taxane-based chemotherapy for metastatic prostate cancer (PC). Methods Retrospective, unicentric cohort study of patients treated with either docetaxel for metastatic hormone-sensitive PC (mHSPC) or docetaxel or cabazitaxel for metastatic castration-refractory PC (mCRPC) at a tertiary referral hospital between 2010 and 2019. NLR ratios were calculated for each cycle. Next, slopes over the first three (NLR3) and over six cycles (NLR6) were calculated and analysed for biochemical/radiologic response and survival. Results A total of 36 mHSPC (docetaxel), 118 mCRPC (docetaxel) and 38 mCRPC (cabazitaxel) patients were included. NLR3 was significantly associated with 1-year-survival, radiographic and biochemical response in mCRPC (docetaxel) in uni- and multivariable analyses. In mCRPC (docetaxel), positive NLR3s were associated with favourable 1-year-survival. Conclusion This study demonstrated NLR3 as a prognostic marker in men receiving docetaxel for mCRPC. NLR3 might be a clinical tool to reflect the individual’s response to taxane-based chemotherapy. Thereby, NLR3 could complement existing biomarkers and help to early identify treatment failure before complications arise. Further prospective and multicentric studies are needed to extend and confirm the presented results.

Summary: METTL3 is the major writer of N6-Methyladenosine (m6A) and has been associated with controversial roles in cancer. This is best illustrated in urothelial carcinoma of the bladder (UCB), where METTL3 was described to have both oncogenic and tumor-suppressive functions. Here, we reinvestigated the role of METTL3 in UCB. METTL3 knockout reduced the oncogenic phenotype and m6A levels of UCB cell lines. However, complete depletion of METTL3/m6A was not achieved due to selection of cells expressing alternative METTL3 isoforms. Systematic vulnerability and inhibitor response analyses suggested that uroepithelial cells depend on METTL3 for viability. Furthermore, expression and survival analyses of clinical data revealed a complex role for METTL3 in UCB, with decreased m6A mRNA levels in UCB tumors. Our results suggest that METTL3 expression may be a suitable diagnostic UCB biomarker, as the enzyme promotes UCB formation. However, the suitability of the enzyme as a therapeutic target should be evaluated carefully.

Abstract Objective Patient‐centered care and shared decision making (SDM) are generally recognized as the gold standard for medical consultations, especially for preference‐sensitive decisions. However, little is known about psychological patient characteristics that influence patient‐reported preferences. We set out to explore the role of personality and anxiety for a preference‐sensitive decision in bladder cancer patients (choice of urinary diversion, UD) and to determine if anxiety predicts patients' participation preferences. Methods We recruited a sample of bladder cancer patients (N = 180, primarily male, retired) who awaited a medical consultation on radical cystectomy and their choice of UD. We asked patients to fill in a set of self‐report questionnaires before this consultation, including measures of treatment preference, personality (BFI‐10), anxiety (STAI), and participation preference (API and API‐Uro), as well as sociodemographic characteristics. Results Most patients (79%) indicated a clear preference for one of the treatment options (44% continent UD, 34% incontinent UD). Patients who reported more conscientiousness were more likely to prefer more complex methods (continent UD). The majority (62%) preferred to delegate decision making to healthcare professionals. A substantial number of patients reported elevated anxiety (32%), and more anxiety was predictive of higher participation preference, specifically for uro‐oncological decisions (β = 0.207, p

Abstract Bladder cancer is one of the top 10 frequently occurring cancers and leads to most cancer deaths worldwide. Recently, blue light (BL) cystoscopy-based photodynamic diagnosis was introduced as a unique technology to enhance the detection of bladder cancer, particularly for the detection of flat and small lesions. Here, we aim to demonstrate a BL image-based artificial intelligence (AI) diagnostic platform using 216 BL images, that were acquired in four different urological departments and pathologically identified with respect to cancer malignancy, invasiveness, and grading. Thereafter, four pre-trained convolution neural networks were utilized to predict image malignancy, invasiveness, and grading. The results indicated that the classification sensitivity and specificity of malignant lesions are 95.77% and 87.84%, while the mean sensitivity and mean specificity of tumor invasiveness are 88% and 96.56%, respectively. This small multicenter clinical study clearly shows the potential of AI based classification of BL images allowing for better treatment decisions and potentially higher detection rates.

Abstract Renal cell carcinoma (RCC) is the deadliest primary genitourinary malignancy typically associated with asymptomatic initial presentation and poorly predictable survival. Next to established risk factors, tumor microenvironment may alter metastatic capacity and immune landscape. Due to their high concentrations, sulfoglycolipids (sulfatides) were among the first well-described antigens in RCC that are associated with worse prognosis. As sulfatide detection in routine diagnostics is not possible, we aimed to test the prognostic value of its protein counterpart, sulfatide-producing enzyme Gal3ST1. We performed retrospective long-term follow up analysis of Gal3ST1 expression as prognostic risk factor in a representative RCC patient cohort. We observed differentially regulated Gal3ST1 expression in all RCC types, being significantly more associated with clear cell RCC than to chromophobe RCC (p = 0.001). Surprisingly, in contrast to published observations from in vitro models, we could not confirm an association between Gal3ST1 expression and a malignant clinical behaviour of the RCC. In our cohort, Gal3ST1 did not significantly influence progression-free survival (Hazard Ratio (HR): 1.7 95% CI (0.6–4.9), p = 0.327). Particularly after adjusting for histology, T-stage, N-status and M-status at baseline, we observed no independent prognostic effect (HR = 1.0 95% CI (0.3–3.3), p = 0.96). The analysis of Gal3ST1 mRNA expression in a TCGA dataset supported the results of our cohort. Thus, Gal3ST1 might help to differentiate between chromophobe RCC and other frequent RCC entities but—despite previously published data from cell culture models—does not qualify as a prognostic marker for RCC. Further investigation of regulatory mechanisms of sulfatide metabolism in human RCC microenvironment is necessary to understand the role of this quantitatively prominent glycosphingolipid in RCC progression.

Abstract Comprehensive transcriptome expression analyses of bladder cancer revealed distinct lncRNA clusters with differential molecular and clinical characteristics. In this study, pivotal lncRNAs were assessed for their impact on survival and their differential expression between the molecular bladder cancer subtypes. FFPE samples from chemotherapy-naïve patients with muscle invasive bladder cancer (MIBC) were analyzed on the Nanostring nCounter platform for absolute quantification. An established 36-gene panel was used for molecular subtype classification into basal, luminal and infiltrated MIBC. In a second step, 14 pivotal lncRNAs were assessed for their molecular subtype attribution, and their predictive value in disease-specific survival. In silico validation was performed on a total of 487 MIBC patients (MDA, TGCA and Chungbuk cohort). Several pivotal lncRNAs showed a distinct molecular subtype attribution: e.g. MALAT1 showed a downregulation in the basal subtype (p = 0.009), TUG1 and CBR3AS1 showed an upregulation in the luminal subtype (p ≤ 0.001). High transcript levels of SNHG16, CBR3AS1 and H19 appeared to be predictive for a shorter disease-specific survival. Patients overexpressing putative oncogenes MALAT1 and TUG1 in MIBC tissue presented prolonged survival, suggesting tumor suppressive effects of both lncRNAs. The Nanostring nCounter proved to be a valid platform for the quantification of low-abundance transcripts including lncRNAs.

To date, only a single transcriptome-wide m6A sequencing study of clear cell renal cell carcinoma (ccRCC) has been reported, with no validation so far. Herein, by TCGA analysis of the KIRC cohort (n = 530 ccRCC; n = 72 normal), an external expression validation of 35 preidentified m6A targets was performed. Further in-depth expression stratification enabled assessment of m6A-driven key targets. Overall survival (OS) analysis and gene set enrichment analyses (GSEA) were conducted to assess their clinical and functional impact on ccRCC. In the hyper-up cluster significant upregulation was confirmed for NDUFA4L2, NXPH4, SAA1, and PLOD2 (40%) and in the hypo-up cluster for FCHSD1 (10%). Significant downregulation was observed for UMOD, ANK3, and CNTFR (27.3%) in the hypo-down cluster and for CHDH (25%) in the hyper-down cluster. In-depth expression stratification showed consistent dysregulation in ccRCC only for 11.67%: NDUFA4L2, NXPH4, and UMOD (NNU-panel). Patients with strong NNU panel dysregulation had significantly poorer OS (p = 0.0075). GSEA identified 13 associated and significantly upregulated gene sets (all p-values < 0.5; FDR < 0.25). External validation of the only available m6A sequencing in ccRCC consistently reduced dysregulated m6A-driven targets on the NNU panel with highly significant effects on OS. Epitranscriptomics are a promising target for developing novel therapies and for identifying prognostic markers for daily clinical practice.

BackgroundTo compare severe infectious complication rates after transrectal prostate biopsies between cephalosporins and fluoroquinolones for antibiotic monoprophylaxis.Material and MethodsIn the multi-institutional cohort, between November 2014 and July 2020 patients received either cefotaxime (single dose intravenously), cefpodoxime (multiple doses orally) or fluoroquinolones (multiple-doses orally or single dose intravenously) for transrectal prostate biopsy prophylaxis. Data were prospectively acquired and retrospectively analyzed. Severe infectious complications were evaluated within 30 days after biopsy. Logistic regression models predicted biopsy-related infectious complications according to antibiotic prophylaxis, application type and patient- and procedure-related risk factors.ResultsOf 793 patients, 132 (16.6%) received a single dose of intravenous cefotaxime and were compared to 119 (15%) who received multiple doses of oral cefpodoxime and 542 (68.3%) who received fluoroquinolones as monoprophylaxis. The overall incidence of severe infectious complications was 1.0% (n=8). No significant differences were observed between the three compared groups (0.8% vs. 0.8% vs. 1.1%, p=0.9). The overall rate of urosepsis was 0.3% and did not significantly differ between the three compared groups as well.ConclusionMonoprophylaxis with third generation cephalosporins was efficient in preventing severe infectious complications after prostate biopsy. Single intravenous dose of cefotaxime and multiday regimen of oral cefpodoxime showed a low incidence of infectious complications

Recent advances in mass spectrometry (MS)‐based technologies are now set to transform translational cancer proteomics from an idea to a practice. Here, we present a robust proteomic workflow for the analysis of clinically relevant human cancer tissues that allows quantitation of thousands of tumor proteins in several hours of measuring time and a total turnaround of a few days. We applied it to a chemorefractory metastatic case of the extremely rare urachal carcinoma. Quantitative comparison of lung metastases and surrounding tissue revealed several significantly upregulated proteins, among them lysine‐specific histone demethylase 1 (LSD1/KDM1A). LSD1 is an epigenetic regulator and the target of active development efforts in oncology. Thus, clinical cancer proteomics can rapidly and efficiently identify actionable therapeutic options. While currently described for a single case study, we envision that it can be applied broadly to other patients in a similar condition.

For clear cell renal cell carcinoma (ccRCC) risk-dependent diagnostic and therapeutic algorithms are routinely implemented in clinical practice. Artificial intelligence-based image analysis has the potential to improve outcome prediction and thereby risk stratification. Thus, we investigated whether a convolutional neural network (CNN) can extract relevant image features from a representative hematoxylin and eosin-stained slide to predict 5-year overall survival (5y-OS) in ccRCC. The CNN was trained to predict 5y-OS in a binary manner using slides from TCGA and validated using an independent in-house cohort. Multivariable logistic regression was used to combine of the CNNs prediction and clinicopathological parameters. A mean balanced accuracy of 72.0% (standard deviation [SD] = 7.9%), sensitivity of 72.4% (SD = 10.6%), specificity of 71.7% (SD = 11.9%) and area under receiver operating characteristics curve (AUROC) of 0.75 (SD = 0.07) was achieved on the TCGA training set (n = 254 patients / WSIs) using 10-fold cross-validation. On the external validation cohort (n = 99 patients / WSIs), mean accuracy, sensitivity, specificity and AUROC were 65.5% (95%-confidence interval [CI]: 62.9-68.1%), 86.2% (95%-CI: 81.8-90.5%), 44.9% (95%-CI: 40.2-49.6%), and 0.70 (95%-CI: 0.69-0.71). A multivariable model including age, tumor stage and metastasis yielded an AUROC of 0.75 on the TCGA cohort. The inclusion of the CNN-based classification (Odds ratio = 4.86, 95%-CI: 2.70-8.75, p < 0.01) raised the AUROC to 0.81. On the validation cohort, both models showed an AUROC of 0.88. In univariable Cox regression, the CNN showed a hazard ratio of 3.69 (95%-CI: 2.60-5.23, p < 0.01) on TCGA and 2.13 (95%-CI: 0.92-4.94, p = 0.08) on external validation. The results demonstrate that the CNN's image-based prediction of survival is promising and thus this widely applicable technique should be further investigated with the aim of improving existing risk stratification in ccRCC.