Equipping computational pathology systems with artifact processing pipelines: a showcase for computation and performance trade-offs.

BACKGROUND: Histopathology is a gold standard for cancer diagnosis. It involves extracting tissue specimens from suspicious areas to prepare a glass slide for a microscopic examination. However, histological tissue processing procedures result in the introduction of artifacts, which are ultimately transferred to the digitized version of glass slides, known as whole slide images (WSIs). Artifacts are diagnostically irrelevant areas and may result in wrong predictions from deep learning (DL) algorithms. Therefore, detecting and excluding artifacts in the computational pathology (CPATH) system is essential for reliable automated diagnosis. METHODS: In this paper, we propose a mixture of experts (MoE) scheme for detecting five notable artifacts, including damaged tissue, blur, folded tissue, air bubbles, and histologically irrelevant blood from WSIs. First, we train independent binary DL models as experts to capture particular artifact morphology. Then, we ensemble their predictions using a fusion mechanism. We apply probabilistic thresholding over the final probability distribution to improve the sensitivity of the MoE. We developed four DL pipelines to evaluate computational and performance trade-offs. These include two MoEs and two multiclass models of state-of-the-art deep convolutional neural networks (DCNNs) and vision transformers (ViTs). These DL pipelines are quantitatively and qualitatively evaluated on external and out-of-distribution (OoD) data to assess generalizability and robustness for artifact detection application. RESULTS: We extensively evaluated the proposed MoE and multiclass models. DCNNs-based MoE and ViTs-based MoE schemes outperformed simpler multiclass models and were tested on datasets from different hospitals and cancer types, where MoE using (MobileNet) DCNNs yielded the best results. The proposed MoE yields 86.15 % F1 and 97.93% sensitivity scores on unseen data, retaining less computational cost for inference than MoE using ViTs. This best performance of MoEs comes with relatively higher computational trade-offs than multiclass models. Furthermore, we apply post-processing to create an artifact segmentation mask, a potential artifact-free RoI map, a quality report, and an artifact-refined WSI for further computational analysis. During the qualitative evaluation, field experts assessed the predictive performance of MoEs over OoD WSIs. They rated artifact detection and artifact-free area preservation, where the highest agreement translated to a Cohen Kappa of 0.82, indicating substantial agreement for the overall diagnostic usability of the DCNN-based MoE scheme. CONCLUSIONS: The proposed artifact detection pipeline will not only ensure reliable CPATH predictions but may also provide quality control. In this work, the best-performing pipeline for artifact detection is MoE with DCNNs. Our detailed experiments show that there is always a trade-off between performance and computational complexity, and no straightforward DL solution equally suits all types of data and applications. The code and HistoArtifacts dataset can be found online at Github and Zenodo , respectively.

Characterization of Fibroblast Growth Factor Receptor Alterations and Activation in Patients with High-Risk Non-Muscle Invasive Bladder Cancer.

PURPOSE: The GARNER study investigated fibroblast growth factor receptor (FGFR) alteration (ALT) frequency and the clinical outcome relationship with Bacillus Calmette-Guérin (BCG) treatment in high-risk non-muscle invasive bladder cancer (HR-NMIBC). An FGFR predictive response signature (FGFR-PRS) was discovered that identifies patients with an activated FGFR pathway who could potentially benefit from FGFR-targeted therapy beyond those who are FGFR ALT (+). EXPERIMENTAL DESIGN: Pre-treatment tumor samples and clinical data were analyzed from 582 BCG-treated HR-NMIBC patients. FGFR-PRS was discovered using a separate BC dataset and applied to the GARNER and other BC cohorts. FGFR-PRS was also applied to in vitro data from UC cell lines treated with FGFR-active agents. RESULTS: 31% of pre-treatment GARNER HR-NMIBC tumors were FGFR ALT (+) but this was not significantly associated with BCG response. For the subset of patients with paired pre- and post-BCG treatment samples, nearly one-third pre-treatment ALT (+) patients were ALT (-) post-treatment. FGFR-PRS identified patients with an activated FGFR pathway and identified approximately 2-fold additional patients compared to ALT status alone, and this increase was similar across tumor stage. A positive relationship between tumor growth inhibition and FGFR-PRS score was shown in BC in vitro models treated with FGFR-active agents. CONCLUSIONS: These data provide support for FGFR-targeted therapy use in FGFR ALT (+) HR-NMIBC and describe tumors with shared FGFR pathway-activated biology that are FGFR ALT (-) but FGFR-PRS (+). The latter suggests a broader potential patient population for FGFR-targeted therapy, which will require subsequent validation in patients treated with FGFR-targeted therapy.

Molecular biomarkers of progression in non-muscle-invasive bladder cancer - beyond conventional risk stratification.

The global incidence of bladder cancer is more than half a million diagnoses each year. Bladder cancer can be categorized into non-muscle-invasive bladder cancer (NMIBC), which accounts for ~75% of diagnoses, and muscle-invasive bladder cancer (MIBC). Up to 45% of patients with NMIBC develop disease progression to MIBC, which is associated with a poor outcome, highlighting a clinical need to identify these patients. Current risk stratification has a prognostic value, but relies solely on clinicopathological parameters that might not fully capture the complexity of disease progression. Molecular research has led to identification of multiple crucial players involved in NMIBC progression. Identified biomarkers of progression are related to cell cycle, MAPK pathways, apoptosis, tumour microenvironment, chromatin stability and DNA-damage response. However, none of these biomarkers has been prospectively validated. Reported gene signatures of progression do not improve NMIBC risk stratification. Molecular subtypes of NMIBC have improved our understanding of NMIBC progression, but these subtypes are currently unsuitable for clinical implementation owing to a lack of prospective validation, limited predictive value as a result of intratumour subtype heterogeneity, technical challenges, costs and turnaround time. Future steps include the development of consensus molecular NMIBC subtypes that might improve conventional clinicopathological risk stratification. Prospective implementation studies of biomarkers and the design of biomarker-guided clinical trials are required for the integration of molecular biomarkers into clinical practice.

Multi-Center Assessment of Lymph-Node Density and Nodal-Stage to Predict Disease-Specific Survival in Patients with Bladder Cancer Treated by Radical Cystectomy.

BACKGROUND: Prognostic tools in pathological-node (pN) patients after radical cystectomy (RC) are needed. OBJECTIVES: To evaluate the prognostic impact of lymph node (LN)-density on disease-specific survival (DSS) in patients with bladder cancer (BC) undergoing RC with pelvic lymph node dissection. METHODS: We analyzed a multi-institutional cohort of 1169 patients treated with upfront RC for cT1-4aN0M0 urothelial BCat nine centers. LN-densitywas calculated as the ratio of the number of positive LNs×100% to the number of LNs removed. The optimal LN-density cut-off value was defined by creating a time-dependent receiver operating characteristic (ROC) curve in pN patients. Univariable and multivariable Cox' regression analyses were used to assess the effect of conventional Tumor Nodes Metastasis (TNM) nodal staging system, LN-density and other LN-related variables on DSS in the pN-positive cohort. RESULTS: Of the 1169 patients, 463 (39.6%) patients had LN-involvement. The area under the ROC curve was 0.60 and the cut-off for LN-density was set at 20%, 223 of the pN-positive patients (48.2%) had a LN-density ≥ 20%. In multivariable models, the number of LN-metastases (HR 1.03, p = 0.005) and LN-density, either as continuous (HR 1.01, p = 0.013) or as categorical variable (HR 1.37, p = 0.014), were independently associated with worse DSS, whereas pN-stage was not. CONCLUSIONS: LN-density ≥ 20% was an independent predictor of worse DSS in BC patients with LN-involvement at RC. The integration of LN-density and other LN-parameters rather than only conventional pN-stage may contribute to a more refined risk-stratification in BC patients with nodal involvement.

Selecting the right treatment: Health outcome priorities in older patients with bladder cancer.

INTRODUCTION: Selecting the appropriate treatment for older patients with non-muscle invasive (NMIBC) or muscle-invasive bladder cancer (MIBC) is challenging due to smoking-related comorbidities, treatment toxicity, and an increased risk of adverse health outcomes. Considering patient preferences prior to treatment is therefore crucial. Here, we aimed to identify the health outcome priorities of older patients with high-risk NMIBC (HR-NMIBC) or MIBC. MATERIALS AND METHODS: Patients aged 70 years or older or at risk for frailty, diagnosed with HR-NMIBC or MIBC without distant metastases, were referred for a comprehensive geriatric assessment (CGA). The CGA consisted of an interview, physical examination, and several tests to examine physical, cognitive, functional, and social status. Quality of life was assessed using EQ5D and EORTC QLQ-C30 questionnaires. Health outcome priorities were discussed using the Outcome Prioritization Tool (OPT) and associations between health outcome priorities and CGA-determinants and quality of life were studied. RESULTS: Of 146 patients (14 HR-NMIBC, 132 MIBC), OPT data was available for 139. Life extension was most often prioritized (44%), closely followed by preserving independence (40%). Reducing pain (7%) and other symptoms (9%) were less often prioritized. Patients prioritizing life extension had fewer musculoskeletal problems than patients prioritizing reducing pain or other symptoms (p = 0.02). Patients at risk of or suffering from malnutrition more frequently selected reducing pain or other symptoms as their health outcome priority (p = 0.004). For all other CGA-determinants and quality of life, there were no significant differences between groups based on health outcome priorities. DISCUSSION: In older patients with HR-NMIBC and MIBC, life extension and preserving independence are the most common health outcomes priorities. CGA-determinants and quality of life are generally not associated with the prioritization of health outcomes. As health outcome priorities cannot be predicted by CGA-determinants or quality of life, it is crucial to discuss health outcome priorities with patients to promote shared decision-making.

A Genomic Urine Assay for Surveillance of Patients with Bladder Cancer Treated with Radiotherapy.

Background: Patients with muscle-invasive bladder cancer (MIBC) who receive radiotherapy with curative intent are followed by imaging, cystoscopy, and urine cytology. However, interpretation of cytology and cystoscopy is hampered by the impact of ionizing radiation on cells. Objective: To assess the diagnostic performance of a genomic urine assay to detect urinary tract recurrences in patients with MIBC treated by (chemo)radiation. Design setting and participants: Patients with nonmetastatic MIBC who underwent (chemo)radiation with curative intent from 2016 to 2020 were prospectively included. Follow-up consisted of cystoscopy and upper tract imaging. Prior to cystoscopy, a urine sample was analyzed to assess mutations in the genes FGFR3, HRAS, and TERT and methylation of OTX1, TWIST1, and ONECUT2. The treating physician was blinded for the assay result. Outcome measurements and statistical analysis: The primary endpoint was a urinary tract recurrence. Cross-sectional sensitivity, specificity, and negative predictive value (NPV) were analyzed using a previously developed logistic regression model for the detection of bladder cancer with this assay. The secondary endpoint was the risk of a future urinary tract recurrence following a positive test and negative cystoscopy/imaging, using a time-dependent Cox proportional hazard analysis. Results and limitations: A total of 143 patients were included, and 503 urine samples were analyzed. The median study duration was 20 mo (interquartile range [IQR] 10-33), and the median time to a recurrence was 16 mo (IQR 12-26). In 27 patients, 32 urinary tract recurrences were diagnosed, including three upper tract tumors. Of 32 recurrences, 18 (56%) had a concomitant urine test available. The diagnostic model had an area under the curve of 0.80 (95% confidence interval [CI] 0.69-0.90) with corresponding sensitivity, specificity, and NPV of 78 (95% CI 52-94), 77% (95% CI 73-81), and 99% (95% CI 97-100). When taking into account the anticipatory effect of the test, 28/32 (88%) recurrences were detected. A Cox regression analysis showed a hazard ratio of 14.8 for the development of a future recurrence (p < 0.001). A major limitation was the lack of a concomitant urine test result in 14/32 (44%) recurrences. Conclusions: A genomic urine assay detected urinary tract recurrences after (chemo)radiation in patients with MIBC, and a positive test was strongly associated with future recurrences. Although validation in a large cohort is warranted, the test has the potential to limit frequent cystoscopies. Patient summary: Radiotherapy is a bladder-sparing treatment in patients with bladder cancer. After treatment, these patients undergo visual inspection of the bladder by cystoscopy to detect possible recurrences. However, interpretation of cystoscopy is difficult due to the effects of radiation on the bladder lining. Hence, we analyzed the diagnostic value of a molecular urine test to detect recurrent disease in bladder cancer patients treated by radiotherapy, and we showed that the urine test has the potential to limit the number of cystoscopies.

NPEPPS Is a Druggable Driver of Platinum Resistance.

There is an unmet need to improve the efficacy of platinum-based cancer chemotherapy, which is used in primary and metastatic settings in many cancer types. In bladder cancer, platinum-based chemotherapy leads to better outcomes in a subset of patients when used in the neoadjuvant setting or in combination with immunotherapy for advanced disease. Despite such promising results, extending the benefits of platinum drugs to a greater number of patients is highly desirable. Using the multiomic assessment of cisplatin-responsive and -resistant human bladder cancer cell lines and whole-genome CRISPR screens, we identified puromycin-sensitive aminopeptidase (NPEPPS) as a driver of cisplatin resistance. NPEPPS depletion sensitized resistant bladder cancer cells to cisplatin in vitro and in vivo. Conversely, overexpression of NPEPPS in sensitive cells increased cisplatin resistance. NPEPPS affected treatment response by regulating intracellular cisplatin concentrations. Patient-derived organoids (PDO) generated from bladder cancer samples before and after cisplatin-based treatment, and from patients who did not receive cisplatin, were evaluated for sensitivity to cisplatin, which was concordant with clinical response. In the PDOs, depletion or pharmacologic inhibition of NPEPPS increased cisplatin sensitivity, while NPEPPS overexpression conferred resistance. Our data present NPEPPS as a druggable driver of cisplatin resistance by regulating intracellular cisplatin concentrations. SIGNIFICANCE: Targeting NPEPPS, which induces cisplatin resistance by controlling intracellular drug concentrations, is a potential strategy to improve patient responses to platinum-based therapies and lower treatment-associated toxicities.

Are you sure it's an artifact? Artifact detection and uncertainty quantification in histological images.

Modern cancer diagnostics involves extracting tissue specimens from suspicious areas and conducting histotechnical procedures to prepare a digitized glass slide, called Whole Slide Image (WSI), for further examination. These procedures frequently introduce different types of artifacts in the obtained WSI, and histological artifacts might influence Computational Pathology (CPATH) systems further down to a diagnostic pipeline if not excluded or handled. Deep Convolutional Neural Networks (DCNNs) have achieved promising results for the detection of some WSI artifacts, however, they do not incorporate uncertainty in their predictions. This paper proposes an uncertainty-aware Deep Kernel Learning (DKL) model to detect blurry areas and folded tissues, two types of artifacts that can appear in WSIs. The proposed probabilistic model combines a CNN feature extractor and a sparse Gaussian Processes (GPs) classifier, which improves the performance of current state-of-the-art artifact detection DCNNs and provides uncertainty estimates. We achieved 0.996 and 0.938 F1 scores for blur and folded tissue detection on unseen data, respectively. In extensive experiments, we validated the DKL model on unseen data from external independent cohorts with different staining and tissue types, where it outperformed DCNNs. Interestingly, the DKL model is more confident in the correct predictions and less in the wrong ones. The proposed DKL model can be integrated into the preprocessing pipeline of CPATH systems to provide reliable predictions and possibly serve as a quality control tool.

The Diagnostic Accuracy of Cystoscopy for Detecting Bladder Cancer in Adults Presenting with Haematuria: A Systematic Review from the European Association of Urology Guidelines Office.

CONTEXT: Haematuria can be macroscopic (visible haematuria [VH]) or microscopic (nonvisible haematuria [NVH]), and may be caused by a number of underlying aetiologies. Currently, in case of haematuria, cystoscopy is the standard diagnostic tool to screen the entire bladder for malignancy. OBJECTIVE: The objective of this systematic review is to determine the diagnostic test accuracy of cystoscopy (compared with other tests, eg, computed tomography, urine biomarkers, and urine cytology) for detecting bladder cancer in adults. EVIDENCE ACQUISITION: A systematic review of the literature was performed according to the Cochrane Handbook for Systematic Reviews of Diagnostic Test Accuracy and Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) extension for diagnostic test accuracy studies' checklist. The MEDLINE, Embase, Cochrane CENTRAL, and Cochrane CDSR databases (via Ovid) were searched up to July 13, 2022. The population comprises patients presenting with either VH or NVH, without previous urological cancers. Two reviewers independently screened all articles, searched reference lists of retrieved articles, and performed data extraction. The risk of bias was assessed using Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2). EVIDENCE SYNTHESIS: Overall, nine studies were included in the qualitative analysis. Seven out of nine included trials covered the use of cystoscopy in comparison with radiological imaging. Overall, sensitivity of cystoscopy ranged from 87% to 100%, specificity from 64% to 100%, positive predictive value from 79% to 98%, and negative predictive values between 98% and 100%. Two trials compared enhanced or air cystoscopy versus conventional cystoscopy. Overall sensitivity of conventional white light cystoscopy ranged from 47% to 100% and specificity from 93.4% to 100%. CONCLUSIONS: The true accuracy of cystoscopy for the detection of bladder cancer within the context of haematuria has not been studied extensively, resulting in inconsistent data regarding its performance for patients with haematuria. In comparison with imaging modalities, a few trials have prospectively assessed the diagnostic performance of cystoscopy, confirming very high accuracy for cystoscopy, exceeding the diagnostic value of any other imaging test. PATIENT SUMMARY: Evidence of tests for detecting bladder cancer in adults presenting with haematuria (blood in urine) was reviewed. The most common test used was cystoscopy, which remains the current standard for diagnosing bladder cancer.

Artificial Intelligence in Digital Pathology for Bladder Cancer: Hype or Hope? A Systematic Review.

Bladder cancer (BC) diagnosis and prediction of prognosis are hindered by subjective pathological evaluation, which may cause misdiagnosis and under-/over-treatment. Computational pathology (CPATH) can identify clinical outcome predictors, offering an objective approach to improve prognosis. However, a systematic review of CPATH in BC literature is lacking. Therefore, we present a comprehensive overview of studies that used CPATH in BC, analyzing 33 out of 2285 identified studies. Most studies analyzed regions of interest to distinguish normal versus tumor tissue and identify tumor grade/stage and tissue types (e.g., urothelium, stroma, and muscle). The cell's nuclear area, shape irregularity, and roundness were the most promising markers to predict recurrence and survival based on selected regions of interest, with >80% accuracy. CPATH identified molecular subtypes by detecting features, e.g., papillary structures, hyperchromatic, and pleomorphic nuclei. Combining clinicopathological and image-derived features improved recurrence and survival prediction. However, due to the lack of outcome interpretability and independent test datasets, robustness and clinical applicability could not be ensured. The current literature demonstrates that CPATH holds the potential to improve BC diagnosis and prediction of prognosis. However, more robust, interpretable, accurate models and larger datasets-representative of clinical scenarios-are needed to address artificial intelligence's reliability, robustness, and black box challenge.

Non-muscle-invasive bladder cancer molecular subtypes predict differential response to intravesical Bacillus Calmette-Guérin.

The recommended treatment for patients with high-risk non-muscle-invasive bladder cancer (HR-NMIBC) is tumor resection followed by adjuvant Bacillus Calmette-Guérin (BCG) bladder instillations. However, only 50% of patients benefit from this therapy. If progression to advanced disease occurs, then patients must undergo a radical cystectomy with risks of substantial morbidity and poor clinical outcome. Identifying tumors unlikely to respond to BCG can translate into alternative treatments, such as early radical cystectomy, targeted therapies, or immunotherapies. Here, we conducted molecular profiling of 132 patients with BCG-naive HR-NMIBC and 44 patients with recurrences after BCG (34 matched), which uncovered three distinct BCG response subtypes (BRS1, 2 and BRS3). Patients with BRS3 tumors had a reduced recurrence-free and progression-free survival compared with BRS1/2. BRS3 tumors expressed high epithelial-to-mesenchymal transition and basal markers and had an immunosuppressive profile, which was confirmed with spatial proteomics. Tumors that recurred after BCG were enriched for BRS3. BRS stratification was validated in a second cohort of 151 BCG-naive patients with HR-NMIBC, and the molecular subtypes outperformed guideline-recommended risk stratification based on clinicopathological variables. For clinical application, we confirmed that a commercially approved assay was able to predict BRS3 tumors with an area under the curve of 0.87. These BCG response subtypes will allow for improved identification of patients with HR-NMIBC at the highest risk of progression and have the potential to be used to select more appropriate treatments for patients unlikely to respond to BCG.

Intravesical BCG in patients with non-muscle invasive bladder cancer induces trained immunity and decreases respiratory infections.

BACKGROUND: BCG is recommended as intravesical immunotherapy to reduce the risk of tumor recurrence in patients with non-muscle invasive bladder cancer (NMIBC). Currently, it is unknown whether intravesical BCG application induces trained immunity. METHODS: The aim of this research was to determine whether BCG immunotherapy induces trained immunity in NMIBC patients. We conducted a prospective observational cohort study in 17 NMIBC patients scheduled for BCG therapy and measured trained immunity parameters at 9 time points before and during a 1-year BCG maintenance regimen. Ex vivo cytokine production by peripheral blood mononuclear cells, epigenetic modifications, and changes in the monocyte transcriptome were measured. The frequency of respiratory infections was investigated in two larger cohorts of BCG-treated and non-BCG treated NMIBC patients as a surrogate measurement of trained immunity. Gene-based association analysis of genetic variants in candidate trained immunity genes and their association with recurrence-free survival and progression-free survival after BCG therapy was performed to investigate the hypothesized link between trained immunity and clinical response. RESULTS: We found that intravesical BCG does induce trained immunity based on an increased production of TNF and IL-1ß after heterologous ex vivo stimulation of circulating monocytes 6-12 weeks after intravesical BCG treatment; and a 37% decreased risk (OR 0.63 (95% CI 0.40 to 1.01)) for respiratory infections in BCG-treated versus non-BCG-treated NMIBC patients. An epigenomics approach combining chromatin immuno precipitation-sequencing and RNA-sequencing with in vitro trained immunity experiments identified enhanced inflammasome activity in BCG-treated individuals. Finally, germline variation in genes that affect trained immunity was associated with recurrence and progression after BCG therapy in NMIBC. CONCLUSION: We conclude that BCG immunotherapy induces trained immunity in NMIBC patients and this may account for the protective effects against respiratory infections. The data of our gene-based association analysis suggest that a link between trained immunity and oncological outcome may exist. Future studies should further investigate how trained immunity affects the antitumor immune responses in BCG-treated NMIBC patients.

Sewage surveillance system using urological wastewater: Key to COVID-19 monitoring?

Since December 2019, the emergence of a new Severe Acute Respiratory Syndrome- coronavirus (SARS-CoV-2) has led to a global coronavirus pandemic disease (COVID-19), with devastating consequences for all healthcare worldwide, including urological care. COVID-19 has led to concern among urological healthcare workers about viral presence, detection and routes of transmission during routine clinical practice. The potential presence of (active) virus in bodily fluids of COVID-19 patients remains a continuing topic of debate. Therefore, we highlight viral detection methods and review the presence of SARS-CoV-2 in urine, feces, and semen. Finally, we discuss how excretion of virus particles through urological bodily fluids might be pivotal to epidemiologic monitoring and control of the disease.

RNA-based urinary assays for non-muscle invasive bladder cancer.

PURPOSE OF REVIEW: To provide an overview of the recent literature on RNA-based molecular urine assays for the diagnosis and surveillance of non-muscle invasive bladder cancer (NMIBC). RECENT FINDINGS: Articles were eligible for inclusion if performance metrics sensitivity, specificity, and negative-predictive value (NPV) were reported or could be calculated. Only prospective studies published between 2020-2022 were included. Five out of fourteen studies addressed the primary diagnostic setting; the proportion of gross hematuria patients in all study populations was >50%. Only one study reported performance metrics within a microscopic hematuria subgroup. This study evaluated Xpert Bladder and reported a sensitivity: 73%, specificity: 84%, NPV: 99%, and PPV: 12%. Ten studies assessed test performance during surveillance for NMIBC. For the detection of high-grade (HG) and high-risk (HR) NMIBC, sensitivity, specificity, NPV, and PPV varied between 78-100%, 64-89%, 97.0-99.7%, and 9.2-39%. SUMMARY: Multiple RNA-based urine assays have been investigated for the detection of urothelial cancer in the primary or surveillance setting. However, studies included within this review have important limitations, hampering the interpretation of study results. As such, performance metrics should be interpreted with caution and further research is required to evaluate the clinical impact of RNA-based urine assays in daily practice.

Prognostic markers in invasive bladder cancer: FGFR3 mutation status versus P53 and KI-67 expression: a multi-center, multi-laboratory analysis in 1058 radical cystectomy patients.

OBJECTIVES: To determine the association between the FGFR3 mutation status and immuno-histochemistry (IHC) markers (p53 and Ki-67) in invasive bladder cancer (BC), and to analyze their prognostic value in a multicenter, multi-laboratory radical cystectomy (RC) cohort. PATIENTS AND METHODS: We included 1058 cN0M0, chemotherapy-naive BC patients who underwent RC with pelvic lymph-node dissection at 8 hospitals. The specimens were reviewed by uro-pathologists. Mutations in the FGFR3 gene were examined using PCR-SNaPshot; p53 and Ki-67 expression were determined by standard IHC. FGFR3 mutation status as well as p53 (cut-off>10%) and Ki-67 (cut-off>20%) expression were correlated to clinicopathological parameters and disease specific survival (DSS). RESULTS: pT-stage was

Risk factors associated with positive surgical margins' location at radical cystectomy and their impact on bladder cancer survival.

PURPOSE: To evaluate the risk factors associated with positive surgical margins' (PSMs) location and their impact on disease-specific survival (DSS) in patients with bladder cancer (BCa) undergoing radical cystectomy (RC). METHODS: We analyzed a large multi-institutional cohort of patients treated with upfront RC for non-metastatic (cT1-4aN0M0) BCa. Multivariable binomial logistic regression analyses were used to assess the risk of PSMs at RC for each location after adjusting for clinicopathological covariates. The Kaplan-Meier method was used to estimate DSS stratified by margins' status and location. Log-rank statistics and Cox' regression models were used to determine significance. RESULTS: A total of 1058 patients were included and 108 (10.2%) patients had PSMs. PSMs were located at soft-tissue, ureter(s), and urethra in 57 (5.4%), 30 (2.8%) and 21 (2.0%) patients, respectively. At multivariable analysis, soft-tissue PSMs were independently associated with pathological stage T4 (pT4) (Odds ratio (OR) 6.20, p < 0.001) and lymph-node metastases (OR 1.86, p = 0.04). Concomitant carcinoma-in-situ (CIS) was an independent risk factor for ureteric PSMs (OR 6.31, p = 0.003). Finally, urethral PSMs were independently correlated with pT4-stage (OR 5.10, p = 0.01). The estimated 3-years DSS rates were 58.2%, 32.4%, 50.1%, and 40.3% for negative SMs, soft-tissue-, ureteric- and urethral PSMs, respectively (log-rank; p < 0.001). CONCLUSIONS: PSMs' location represents distinct risk factors' patterns. Concomitant CIS was associated with ureteric PSMs. Urethral and soft-tissue PSM showed worse DSS rates. Our results suggest that clinical decision-making paradigms on adjuvant treatment and surveillance might be adapted based on PSM and their location.

Improving Anti-PD-1/PD-L1 Therapy for Localized Bladder Cancer.

In high-risk non-muscle invasive bladder cancer (HR-NMIBC), patient outcome is negatively affected by lack of response to Bacillus-Calmette Guérin (BCG) treatment. Lack of response to cisplatin-based neoadjuvant chemotherapy and cisplatin ineligibility reduces successful treatment outcomes in muscle-invasive bladder cancer (MIBC) patients. The effectiveness of PD-1/PD-L1 immune checkpoint inhibitors (ICI) in metastatic disease has stimulated its evaluation as a treatment option in HR-NMIBC and MIBC patients. However, the observed responses, immune-related adverse events and high costs associated with ICI have provided impetus for the development of methods to improve patient stratification, enhance anti-tumorigenic effects and reduce toxicity. Here, we review the challenges and opportunities offered by PD-1/PD-L1 inhibition in HR-NMIBC and MIBC. We highlight the gaps in the field that need to be addressed to improve patient outcome including biomarkers for response stratification and potentially synergistic combination therapy regimens with PD-1/PD-L1 blockade.

Biomarker-Oriented Therapy in Bladder and Renal Cancer.

Treatment of patients with urothelial carcinoma (UC) of the bladder or renal cancer has changed significantly during recent years and efforts towards biomarker-directed therapy are being investigated. Immune checkpoint inhibition (ICI) or fibroblast growth factor receptor (FGFR) directed therapy are being evaluated for non-muscle invasive bladder cancer (NMIBC) patients, as well as muscle-invasive bladder cancer (MIBC) patients. Meanwhile, efforts to predict tumor response to neoadjuvant chemotherapy (NAC) are still ongoing, and genomic biomarkers are being evaluated in prospective clinical trials. Currently, patients with metastatic UC (mUC) are usually treated with second-line ICI, while cisplatin-ineligible patients with programmed death-ligand 1 (PD-L1) positive tumors can benefit from first-line ICI. Platinum-relapsed UC patients harboring FGFR2/3 mutations can be treated with erdafitinib, while enfortumab vedotin has emerged as a novel third-line treatment option for mUC. In metastatic (clear cell) renal cell carcinoma (RCC), ICI was first introduced as second-line treatment after vascular endothelial growth factor receptor-tyrosine kinase inhibition (VEGFR-TKI). Currently, ICIs have also been introduced as first-line treatment in metastatic RCC. Although there is no evidence up to now for beneficial adjuvant treatment after surgery with VEGFR-TKIs in high-risk non-metastatic RCC, several trials are underway investigating the potential beneficial effect of ICIs in this setting.