Hypermethylated TAGMe as a universal-cancer-only methylation marker and its application in diagnosis and recurrence monitoring of urothelial carcinoma.

BACKGROUND: Urothelial carcinoma (UC) is the second most common urological malignancy. Despite numerous molecular markers have been evaluated during the past decades, no urothelial markers for diagnosis and recurrence monitoring have shown consistent clinical utility. METHODS: The methylation level of tissue samples from public database and clinical collected were analyzed. Patients with UC and benign diseases of the urinary system (BUD) were enrolled to establish TAGMe (TAG of Methylation) assessment in a training cohort (n = 567) using restriction enzyme-based bisulfite-free qPCR. The performance of TAGMe assessment was further verified in the validation cohort (n = 198). Urine samples from 57 UC patients undergoing postoperative surveillance were collected monthly for six months after surgery to assess the TAGMe methylation. RESULTS: We identified TAGMe as a potentially novel Universal-Cancer-Only Methylation (UCOM) marker was hypermethylated in multi-type cancers and investigated its application in UC. Restriction enzyme-based bisulfite-free qPCR was used for detection, and the results of which were consistent with gold standard pyrosequencing. Importantly, hypermethylated TAGMe showed excellent sensitivity of 88.9% (95% CI: 81.4-94.1%) and specificity of 90.0% (95% CI: 81.9-95.3%) in efficiently distinguishing UC from BUD patients in urine and also performed well in different clinical scenarios of UC. Moreover, the abnormality of TAGMe as an indicator of recurrence might precede clinical recurrence by three months to one year, which provided an invaluable time window for timely and effective intervention to prevent UC upstaging. CONCLUSION: TAGMe assessment based on a novel single target in urine is effective and easy to perform in UC diagnosis and recurrence monitoring, which may reduce the burden of cystoscopy. Trial registration ChiCTR2100052507. Registered on 30 October 2021.

Development and deployment of a histopathology-based deep learning algorithm for patient prescreening in a clinical trial.

Accurate identification of genetic alterations in tumors, such as Fibroblast Growth Factor Receptor, is crucial for treating with targeted therapies; however, molecular testing can delay patient care due to the time and tissue required. Successful development, validation, and deployment of an AI-based, biomarker-detection algorithm could reduce screening cost and accelerate patient recruitment. Here, we develop a deep-learning algorithm using >3000 H&E-stained whole slide images from patients with advanced urothelial cancers, optimized for high sensitivity to avoid ruling out trial-eligible patients. The algorithm is validated on a dataset of 350 patients, achieving an area under the curve of 0.75, specificity of 31.8% at 88.7% sensitivity, and projected 28.7% reduction in molecular testing. We successfully deploy the system in a non-interventional study comprising 89 global study clinical sites and demonstrate its potential to prioritize/deprioritize molecular testing resources and provide substantial cost savings in the drug development and clinical settings.

[Urinary cytology for the detection of urothelial lesions]. / Rôle de la cytologie urinaire dans le dépistage des lésions urothéliales.

Urine cytology is a long-used technique for the detection of high grade neoplastic urothelial lesions. Since 2016, «The Paris System¼ classification has revolutionized this field by introducing a standardized terminology widely adopted by cytopathologists and urologists. In this article, we explain this classification and discuss its impact on the clinical management of patients with urothelial lesions, as well as its role in the secondary prevention of these lesions.

La cytologie urinaire est une technique utilisée depuis longtemps dans la détection des lésions urothéliales tumorales de haut grade. Depuis 2016, la classification «The Paris System¼ a révolutionné ce domaine en introduisant une terminologie standardisée largement adoptée par les cytopathologistes et les urologues. Dans cet article, nous expliquons cette classification et discutons de son impact sur la prise en charge clinique des lésions urothéliales, ainsi que son rôle dans la prévention secondaire de ces lésions.

Molecular Pathology of Urothelial Carcinoma.

Urothelial carcinoma is characterized by the presence of a wide spectrum of histopathologic features and molecular alterations that contribute to its morphologic and genomic heterogeneity. It typically harbors high rates of somatic mutations with considerable genomic and transcriptional complexity and heterogeneity that is reflective of its varied histomorphologic and clinical features. This review provides an update on the recent advances in the molecular characterization and novel molecular taxonomy of urothelial carcinoma and variant histologies.

Defining oligometastatic state in uro-oncological cancers.

PURPOSE OF REVIEW: Oligometastatic tumors illustrate a distinct state between localized and systematic disease and might harbor unique biologic features. Moreover, these tumors represent a different clinical entity, with a potential of long-term disease control or even cure, therefore they receive growing attention in the field of urologic oncology. RECENT FINDINGS: Currently, there is no consensus on the definition of oligometastatic prostate cancer, most experts limit it to a maximum of three to five lesions and involvement of no more than two organs, excluding visceral metastases. Quality data on oligometastatic bladder cancer is scarce, however, a consensus of experts defined it as a maximum of three metastatic lesions, either resectable or suitable for stereotactic therapy, without restrictions to the number of organs involved. As for kidney cancer, a maximum number of five metastases, without limitations to the location are defined as oligometastatic, with an important implication of timing of developing metastases since diagnosis of the primary tumor. SUMMARY: Defining oligometastatic state among urological tumors reflecting their distinct biological and clinical behavior is crucial to establish a sound framework for future clinical trials, and to facilitate guideline and policy formulation for improved patient care. Advancements in molecular imaging are expected to transform the field of oligometastatic urologic tumors in the future.

Multimodal Approach in the Diagnosis of Urologic Malignancies: Critical Assessment of ChatGPT-4V's Image-Reading Capabilities.

ChatGPT-4V model with image interpretation tested for distinguishing kidney & prostate tumors from normal tissue.

[What contribution can make artificial intelligence to urinary cytology?] / Quel apport de l'intelligence artificielle en cytologie urinaire ?

Urinary cytology using the Paris system is still the method of choice for screening high-grade urothelial carcinomas. However, the use of the objective criteria described in this terminology shows a lack of inter- and intra-observer reproducibility. Moreover, if its sensitivity is excellent on instrumented urine, it remains insufficient on voided urine samples. Urinary cytology appears to be an excellent model for the application of artificial intelligence to improve performance, since the objective criteria of the Paris system are defined at cellular level, and the resulting diagnostic approach is presented in a highly "algorithmic" way. Nevertheless, there is no commercially available morphological diagnostic aid, and very few predictive devices are still undergoing clinical validation. The analysis of different systems using artificial intelligence in urinary cytology rises clear prospects for mutual contributions.

Enhancing upper tract urothelial carcinoma diagnosis: Utility of cytokeratin 17 and CK20/CD44/p53 immunohistochemical panel.

Upper tract urothelial carcinoma (UTUC) presents diagnostic challenges due to small biopsy specimen size, poor orientation, and technical obstacles that can yield equivocal diagnoses. This uncertainty often mandates repeated biopsies to evaluate the necessity of nephroureterectomy. Prior studies have suggested cytokeratin 17 (CK17) immunostain as an adjunctive tool for diagnosing bladder urothelial neoplasia in both urine cytology and tissue biopsy specimens. We evaluated the utility of CK17 in differentiating UTUC from benign urothelium and its ability to stratify low-grade from high-grade neoplasia. Our study involved a cohort of previously diagnosed cytology (n = 29) and tissue specimens from biopsies and resections (n = 85). We evaluated CK17 staining percentage in cytology and tissue samples and localization patterns in biopsy/resection samples. Our findings showed a statistically significant distinction (p < 0.05) between UTUC and benign tissue specimens based on full thickness localization pattern (odds ratio 8.8 [95% CI 1.53-67.4]). The percentage of CK17 staining failed to significantly differentiate neoplastic from non-neoplastic cases in cytology or tissue samples. Additionally, based on prior research showing the efficacy of CK20/CD44/p53 triple panel in bladder urothelial neoplasia, we utilized tissue microarrays to evaluate if these markers could distinguish UTUC from benign urothelium. We found that CK20/CD44/p53, individually or in combination, could not distinguish urothelial neoplasia from non-neoplasia. Full thickness CK17 urothelial localization by immunohistochemistry was highly reproducible with excellent interobserver agreement and may play a supplementary role in distinguishing upper tract urothelial neoplasia from benign urothelium.

Prognostic significance of circulating tumor DNA in urothelial carcinoma: a systematic review and meta-analysis.

BACKGROUND: Circulating tumor DNA (ctDNA) has emerged as a noninvasive technique that provides valuable insights into molecular profiles and tumor disease management. This study aimed to evaluate the prognostic significance of circulating tumor DNA (ctDNA) in urothelial carcinoma (UC) through a systematic review and meta-analysis. METHODS: A comprehensive search was conducted in MEDLINE, EMBASE, and the Cochrane Library from the inception to December 2023. Studies investigating the prognostic value of ctDNA in UC were included. Hazard ratios (HRs) of disease-free survival (DFS) and overall survival (OS) were extracted. Overall meta-analysis and subgroup exploration stratified by metastatic status, ctDNA sampling time, treatment type, and detection method was performed using the R software (version 4.2.2). RESULTS: A total of 16 studies with 1725 patients were included. Fourteen studies assessed the association between baseline ctDNA status and patient outcomes. Patients with elevated ctDNA levels exhibited significantly worse DFS (HR=6.26; 95% CI: 3.71-10.58, P <0.001) and OS (HR=4.23; 95% CI: 2.72-6.57, P <0.001) regardless of metastatic status, ctDNA sampling time, treatment type, and detection methods. Six studies evaluated the prognostic value of ctDNA dynamics in UC. Patients who showed a decrease or clearance in ctDNA levels during treatment or observation demonstrated more favorable DFS (HR=0.26, 95% CI: 0.17-0.41, P <0.001) and OS (HR=0.21, 95% CI: 0.11-0.38, P <0.001) compared to those who did not. The association remained consistent across the subgroup analysis based on metastatic status and detection methods. In the immune checkpoint inhibitor-treated setting, both lower baseline ctDNA level and ctDNA decrease during the treatment were significantly associated with more favorable oncologic outcomes. Furthermore, specific gene mutations such as FGFR3 identified in ctDNA also demonstrated predictive value in UC patients. CONCLUSION: This meta-analysis demonstrates a strong association of ctDNA status and its dynamic change with survival outcomes in UC, suggesting substantial clinical utility of ctDNA testing in prognosis prediction and decision making in this setting.

C-reactive protein (CRP) as a prognostic biomarker in patients with urothelial carcinoma: A systematic review and meta-analysis.

C-reactive protein (CRP) may reflect a pro-inflammatory tumor microenvironment and could represent a biomarker to select patients with urothelial carcinoma more likely to benefit from therapies directed at modulating tumor-promoting inflammation. We performed a systematic review to evaluate survival outcomes based on pre-treatment CRP values in urothelial carcinoma. The hazard ratios (HRs) of survival such as overall survival (OS) and progression-free survival (PFS) between groups with high versus low CRP values were pooled by the random-effect model meta-analyses. Overall, 28 studies comprising 6789 patients were identified for meta-analyses. High CRP levels were associated with shorter OS (HR=1.96 [95% CI: 1.64-2.33], p < 0.01), particularly in advanced disease treated with immune checkpoint blockade (ICB, HR=1.78 [1.47-2.15], p < 0.01). Similar findings were observed in ICB-treated patients with PFS. These findings suggest that CRP could be an attractive biomarker to select patients with urothelial carcinoma for strategies seeking to modulate tumor-promoting inflammation.

Comparing Preoperative Screening Tools for Elective Urologic Cancer Surgery: Insights from a Cluster Analysis.

INTRODUCTION: The aim of this study was to evaluate the features and benefits of different geriatric screening tools for enhancing the perioperative care of patients who undergo elective cancer surgery using cluster analysis. METHODS: This study was a retrospective, observational analysis of 1,019 consecutive patients who had elective major cancer surgery in the urology department of our hospital from October 2019 to January 2023. Before the surgery, a trained nurse screened the patients using six tools: Eastern Clinical Oncology Group performance status (ECOG-PS), flemish version of the triage risk screening tool (fTRST), geriatric-8 (G8), instrumental activities of daily living, patient health questionnaire-2 (PHQ-2), and simple questionnaire to rapidly diagnose sarcopenia (SARC-F). The study grouped the patients into four clusters based on their scores on these tools and compared their outcomes after the surgery. The outcomes included overall survival, ambulation failure, delirium, and severe complications. The study also examined how each screening tool was associated with the outcomes. RESULTS: Based on their clinical data and screening results, we classified the patients into four groups: Healthy (73%), Depressive (11%), Intermediate (11%), and Unhealthy (5%). The Unhealthy group had the worst outcomes in overall survival (OS), ambulation failure, and delirium, followed by the Intermediate group. In addition, fTRST and SARC-F emerged as significant predictors of OS; ECOG-PS, fTRST, G8, and SARC-F of ambulation failure; ECOG-PS, fTRST, and G8 of delirium; and G8 of severe complications. CONCLUSION: Various geriatric screening tools were found to have the potential to forecast diverse postoperative outcomes.

A deep-learning workflow to predict upper tract urothelial carcinoma protein-based subtypes from H&E slides supporting the prioritization of patients for molecular testing.

Upper tract urothelial carcinoma (UTUC) is a rare and aggressive, yet understudied, urothelial carcinoma (UC). The more frequent UC of the bladder comprises several molecular subtypes, associated with different targeted therapies and overlapping with protein-based subtypes. However, if and how these findings extend to UTUC remains unclear. Artificial intelligence-based approaches could help elucidate UTUC's biology and extend access to targeted treatments to a wider patient audience. Here, UTUC protein-based subtypes were identified, and a deep-learning (DL) workflow was developed to predict them directly from routine histopathological H&E slides. Protein-based subtypes in a retrospective cohort of 163 invasive tumors were assigned by hierarchical clustering of the immunohistochemical expression of three luminal (FOXA1, GATA3, and CK20) and three basal (CD44, CK5, and CK14) markers. Cluster analysis identified distinctive luminal (N = 80) and basal (N = 42) subtypes. The luminal subtype mostly included pushing, papillary tumors, whereas the basal subtype diffusely infiltrating, non-papillary tumors. DL model building relied on a transfer-learning approach by fine-tuning a pre-trained ResNet50. Classification performance was measured via three-fold repeated cross-validation. A mean area under the receiver operating characteristic curve of 0.83 (95% CI: 0.67-0.99), 0.8 (95% CI: 0.62-0.99), and 0.81 (95% CI: 0.65-0.96) was reached in the three repetitions. High-confidence DL-based predicted subtypes showed significant associations (p < 0.001) with morphological features, i.e. tumor type, histological subtypes, and infiltration type. Furthermore, a significant association was found with programmed cell death ligand 1 (PD-L1) combined positive score (p < 0.001) and FGFR3 mutational status (p = 0.002), with high-confidence basal predictions containing a higher proportion of PD-L1 positive samples and high-confidence luminal predictions a higher proportion of FGFR3-mutated samples. Testing of the DL model on an independent cohort highlighted the importance to accommodate histological subtypes. Taken together, our DL workflow can predict protein-based UTUC subtypes, associated with the presence of targetable alterations, directly from H&E slides.

An artificial intelligence-powered PD-L1 combined positive score (CPS) analyser in urothelial carcinoma alleviating interobserver and intersite variability.

AIMS: Immune checkpoint inhibitors targeting programmed death-ligand 1 (PD-L1) have shown promising clinical outcomes in urothelial carcinoma (UC). The combined positive score (CPS) quantifies PD-L1 22C3 expression in UC, but it can vary between pathologists due to the consideration of both immune and tumour cell positivity. METHODS AND RESULTS: An artificial intelligence (AI)-powered PD-L1 CPS analyser was developed using 1,275,907 cells and 6175.42 mm2 of tissue annotated by pathologists, extracted from 400 PD-L1 22C3-stained whole slide images of UC. We validated the AI model on 543 UC PD-L1 22C3 cases collected from three institutions. There were 446 cases (82.1%) where the CPS results (CPS ≥10 or <10) were in complete agreement between three pathologists, and 486 cases (89.5%) where the AI-powered CPS results matched the consensus of two or more pathologists. In the pathologist's assessment of the CPS, statistically significant differences were noted depending on the source hospital (P = 0.003). Three pathologists reevaluated discrepancy cases with AI-powered CPS results. After using the AI as a guide and revising, the complete agreement increased to 93.9%. The AI model contributed to improving the concordance between pathologists across various factors including hospital, specimen type, pathologic T stage, histologic subtypes, and dominant PD-L1-positive cell type. In the revised results, the evaluation discordance among slides from different hospitals was mitigated. CONCLUSION: This study suggests that AI models can help pathologists to reduce discrepancies between pathologists in quantifying immunohistochemistry including PD-L1 22C3 CPS, especially when evaluating data from different institutions, such as in a telepathology setting.

Exosomal circRNAs: Novel biomarkers and therapeutic targets for urinary tumors.

Exosomal circRNAs have emerged as promising biomarkers and therapeutic targets for urinary tumors. In this review, we explored the intricate role of exosomal circRNAs in urological cancers, focusing on their biological functions, dysregulation in tumors, and potential clinical applications. The review delves into the mechanisms by which exosomal circRNAs contribute to tumor progression and highlights their diagnostic and therapeutic implications. By synthesizing current research findings, we present a compelling case for the significance of exosomal circRNAs in the context of urinary tumors. Furthermore, the review discusses the challenges and opportunities associated with utilizing exosomal circRNAs as diagnostic tools and targeted therapeutic agents. There is a need for further research to elucidate the specific mechanisms of exosomal circRNA secretion and delivery, as well as to enhance the detection methods for clinical translational applications. Overall, this comprehensive review underscores the pivotal role of exosomal circRNAs in urinary tumors and underscores their potential as valuable biomarkers and therapeutic tools in the management of urological cancers.

Utility of The Paris System (TPS) for upper urinary tract cytopathology: correlation with histology follow-up and UroVysion fluorescence in situ hybridization (FISH) analysis.

INTRODUCTION: The Paris System (TPS) provides a uniform reporting system of urine cytology based on well-defined cytologic criteria. Due to their rarity, there are limited data on the utility of TPS in upper urinary tract (UUT) lesions and follow-up histology of cases with abnormal cytology. We aimed to evaluate the utility of TPS for UUT lesions by correlating the cytologic diagnoses using TPS criteria with subsequent histology. Additionally, the diagnostic utility of UroVysion (Abbott) fluorescence in situ hybridization (FISH) was assessed. MATERIALS AND METHODS: A total of 148 UUT cytology specimens were retrospectively identified (2018-2022). Cytologic interpretation was performed using TPS, and then correlated with the findings of concurrent or subsequent histologic specimens. The performance of UroVysion FISH was analyzed. Sensitivity and specificity, positive predictive value (PPV) and negative predictive value (NPV) for detecting high-grade urothelial carcinoma (HGUC) were determined. RESULTS: Among 83 patients who had concurrent or subsequent histologic specimens, cyto-histologic discrepancy was seen in 7 cases (8.4%). The sensitivity, specificity, PPV, and NPV using TPS criteria for detecting HGUC were 87%, and 92%, 96.4%, and 73%, respectively. UroVysion FISH was performed in 21 patients with atypical cytologic findings. The sensitivity and specificity of UroVysion for detecting HGUC was 75% and 86%, respectively, while PPV and NPV were 86% and 75%, respectively. CONCLUSIONS: In our experience, the application of TPS criteria for reporting upper urinary cytology was reliable at detecting UUT lesions, especially HGUC. UroVysion FISH was a valuable ancillary test for detecting HGUC of UUT.

The significance of G8 and other geriatric assessments in urologic cancer management: A comprehensive review.

In urologic oncology, which often involves older patients, it is important to consider how to manage their care appropriately. Geriatric assessment (GA) is a method that can address the specific needs of older cancer patients. The GA encompasses various assessment domains, but these domains exhibit variations across the literature. Some of the common items include functional ability, nutrition, comorbidities, cognitive ability, psychosocial disorders, polypharmacy, social and financial support, falls/imbalance, and vision/hearing. Despite the diversity of domains, there is limited consensus on reliable measurement methods. This review discusses the role of GA in managing urologic cancer in unique scenarios, such as those necessitating temporary or permanent urinary catheters or stomas due to urinary diversion. A comprehensive GA is time and human-resource-intensive in real-world clinical practice. Hence, simpler tools such as the Geriatric-8 (G8), capable of identifying high-risk patients requiring a detailed GA, are also under investigation in various contexts. Therefore, we conducted a systematic literature review on the G8. Our findings indicate that patients with low G8 scores encounter difficulties with stoma self-care after urinary diversion and have higher risks of urinary tract infections and ileus after radical cystectomy. The utilization of G8 as a screening tool for urologic cancer patients may facilitate the delivery of appropriate and personalized treatment and care.

The National Health Service urgent cancer referral pathway for suspected urological cancers: early economic evaluation of a risk prediction test.

OBJECTIVES: In the UK, the number of patients urgently referred for suspected cancer is increasing, and providers are struggling to cope with demand. We explore the potential cost-effectiveness of a new risk prediction test - the PinPoint test - to triage and prioritize patients urgently referred with suspected urological cancers. METHODS: Two simulation models were developed to reflect the diagnostic pathways for patients with (i) suspected prostate cancer, and (ii) bladder or kidney cancer, comparing the PinPoint test to current practice. An early economic analysis was conducted from a UK National Health Service (NHS) perspective. The primary outcomes were the percentage of individuals seen within 2 weeks and health care costs. An exploratory analysis was conducted to understand the potential impact of the Pinpoint test on quality-adjusted life years gained. RESULTS: Across both models and applications, the PinPoint test led to more individuals with urological cancer being seen within 2 weeks. Using PinPoint only to prioritize patients led to increased costs overall, whereas using PinPoint to both triage and prioritize patients led to cost savings. The estimated impact on life years gained/lost was very small and highly uncertain. CONCLUSIONS: Using the PinPoint test to prioritize urgent referrals meant that more individuals with urological cancer were seen within 2 weeks, but at additional cost to the NHS. If used as a triage and prioritization tool, the PinPoint test shortens wait times for referred individuals and is cost saving. More data on the impact of short-term delays to diagnosis on health-related quality of life is needed.

[The Paris System, 2022 edition: What is new?] / La version 2022 du Système de Paris : quoi de neuf ?

The second version of the Paris System for reporting urine cytology was published in 2022. It follows the first version of 2016, which was very successful and widely adopted by many cytopathologists from different countries. Thus, numerous publications using the Paris System have made possible to refine the criteria as well as discussing the limits. The diagnostic accuracy of urinary cytology is high for detection of high-grade urothelial carcinoma, but not for low-grade carcinoma where there are few cytological abnormalities. So, the chapter individualizing low-grade urothelial neoplasms was deleted; the latter were included in the category "negative for high-grade urothelial carcinoma". Indeed, the risk of malignancy is replaced by the risk of high-grade urothelial carcinoma. A new chapter has been devoted to urothelial tumors of the upper tract. Finally, the pitfalls linked to cellular degeneration are discussed for each category. The risk of high-grade malignancy associated with each category will help communication with the clinician and help patient care.