Treatment Of Bladder Cancer Patients Research Articles

Novel intravesical therapies and delivery systems for the management of bladder cancer.

Bladder cancer is a substantial burden for public health worldwide. A risk-adapted treatment strategy is required for non muscle-invasive (NMIBC) and muscle-invasive bladder cancer (MIBC). To date, treatment includes surgery with or without peri-operative local or systemic treatment. The aim of this review was to explore novel intravesical therapies and delivery systems emerging in NMIBC and MIBC. Several novel intravesical therapies and delivery systems for NMIBC and MIBC treatment recently emerged. Hyperthermic intravesical chemotherapy (HIVEC) allows a reasonable cancer control in selected high-risk NMIBC. Novel intravesical drugs such as nadofaragene firadenovec, Oncofid-P-B or Nogapendekin alfa-inbakicept seem to be safe and well tolerated. However, their efficacy in high-risk NMIBC should be further investigated. Hydrogels appear to be safe, well tolerated and potentially efficient in primary chemoablation in selected cases of low-grade intermediate-risk NMIBC tumors. Drug-releasing intravesical systems (drug-RIS) such as TAR-200 are safe and well tolerated, providing high partial and complete response rate in both NMIBC and MIBC patients. The armamentarium for the treatment of bladder cancer patients is expanding, notably with HIVEC, hydrogels, drug-RIS and novel therapies. However, accurate patients' selection is key to prevent disease progression in any bladder-sparing strategy, and radical cystectomy remains the gold-standard to date.

Cuproptosis-related signature predicts prognosis and indicates tumor immune infiltration in bladder cancer.

Cuproptosis is a newly identified form of cell death that is dependent on copper (Cu) ions, termed Cu-dependent cytotoxicity. This process is distinct from other forms of cell death such as apoptosis, necrosis, and ferroptosis. The accumulation of copper is known to play a significant role in various biological processes, including angiogenesis (the formation of new blood vessels) and metastasis (the spread of cancer cells to different parts of the body). These processes are crucial for tumor growth and progression, indicating that copper and the cuproptosis-related genes (CPRGs) might be indispensable in the context of cancer development and progression. Given this background, we aimed to explore the relationship between CPRGs and both prognostic predictions and tumor microenvironment (TME) infiltration in bladder cancer (BLCA). For this study, we utilized data from The Cancer Genome Atlas (TCGA) to identify CPRGs and subsequently divided BLCA patients into three distinct molecular clusters based on these genes. To assess the proportions of various immune cell types within the TME, we employed single-sample gene set enrichment analysis (ssGSEA) and the Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) method. These computational techniques allowed us to quantify the infiltration of different immune cells, providing insights into the immune landscape of the tumors. Furthermore, we developed a risk score model using CPRGs to predict the survival prospects of BLCA patients. Our analysis identified three molecular clusters of BLCA patients, each exhibiting unique clinical features and patterns of TME infiltration. Among these clusters, cluster 1 was associated with a poor prognosis. Interestingly, this cluster also showed significant infiltration of activated CD4+ (ssGSEA P<0.001) and CD8+ T (ssGSEA P<0.05) cells, which are crucial components of the immune response against tumors. This finding suggests a complex interaction between the immune system and the tumor, where a high presence of T cells does not necessarily correlate with better outcomes. Additionally, our risk score model revealed that the high-risk group, characterized by a specific expression pattern of CPRGs, also had enhanced infiltration of CD4+ and CD8+ T cells. This indicates that the cuproptosis-based risk model has a robust ability to predict patient prognosis and can guide immunotherapy decisions. Our study sheds light on the biological functions of CPRGs within the TME of BLCA and their correlations with clinical parameters and patient prognosis. The identification of distinct molecular clusters with varying prognoses and immune cell infiltrations highlights the heterogeneity of BLCA and underscores the potential of CPRGs as biomarkers for prognosis and therapeutic targets. These findings offer new perspectives for the development of immunotherapeutic strategies in the treatment of BLCA patients, potentially leading to more personalized and effective cancer therapies.

Disulfidptosis and ferroptosis related genes define the immune microenvironment and NUBPL serves as a potential biomarker for predicting prognosis and immunotherapy response in bladder cancer

BackgroundFerroptosis and disulfidptosis are regulatory forms of cell death that play an important role in tumorigenesis and progression. However, few biomarkers about disulfidptosis and ferroptosis related genes (DFRGs) have been developed to predict the prognosis of bladder cancer (BC). MethodsWe conducted a bioinformatics analysis using public BC datasets to examine the prognostic significance of differentially expressed DFRGs. A Lasso regression was employed to create a prognostic prediction model from these DFRGs. Hub DFRGs that play a role in immunotherapy response and immunoregulation were pinpointed. Immunohistochemistry (IHC) experiment was performed to assess NUBPL and c-MYC expression in BC patients who underwent surgery or received immune checkpoint inhibitor (ICI) immunotherapy at Peking University Cancer Hospital. ResultsWe constructed a valid model to predict the prognosis of BC based on DFRGs and performed relevant validation, the results demonstrated that the model was an independent prognostic factor for BC. Further analysis indicated that the model score, combined with the expression of various immune factors and tumor mutation burden (TMB), could predict the prognosis for BC. In addition, we also found that NUBPL was strongly associated with prognosis and response to ICI treatment, and NUBPL may influence BC malignant progression through the c-MYC pathway. ConclusionsOur research findings highlight the satisfactory predictive value of DFRGs in the immune microenvironment and suggest that NUBPL may be a highly promising biomarker for predicting the prognosis and efficacy of ICI treatment in BC patients.

Prediction of HER2 Status Based on Deep Learning in H&E-Stained Histopathology Images of Bladder Cancer.

Epidermal growth factor receptor 2 (HER2) has been widely recognized as one of the targets for bladder cancer immunotherapy. The key to implementing personalized treatment for bladder cancer patients lies in achieving rapid and accurate diagnosis. To tackle this challenge, we have pioneered the application of deep learning techniques to predict HER2 expression status from H&E-stained pathological images of bladder cancer, bypassing the need for intricate IHC staining or high-throughput sequencing methods. Our model, when subjected to rigorous testing within the cohort from the People's Hospital of Wuhan University, which encompasses 106 cases, has exhibited commendable performance on both the validation and test datasets. Specifically, the validation set yielded an AUC of 0.92, an accuracy of 0.86, a sensitivity of 0.87, a specificity of 0.83, and an F1 score of 86.7%. The corresponding metrics for the test set were 0.88 for AUC, 0.67 for accuracy, 0.56 for sensitivity, 0.75 for specificity, and 77.8% for F1 score. Additionally, in a direct comparison with pathologists, our model demonstrated statistically superior performance, with a p-value less than 0.05, highlighting its potential as a powerful diagnostic tool.

Machine learning developed an intratumor heterogeneity signature for predicting clinical outcome and immunotherapy benefit in bladder cancer.

Bladder cancer is a common malignancy with high invasion and poor clinical outcome. Intratumor heterogeneity (ITH) is linked to cancer progression and metastasis and high ITH can accelerate tumor evolution. Our objective is to develop an ITH-related signature (IRS) for predicting clinical outcome and immunotherapy benefit in bladder cancer. Integrative procedure containing ten machine learning methods was applied to develop an IRS with The Cancer Genome Atlas (TCGA), gene series expression (GSE)13507, GSE31684, GSE32984 and GSE48276 datasets. To evaluate the performance of IRS in predicting the immunotherapy benefit, we also used several predicting scores and three immunotherapy datasets, including GSE91061, GSE78220 and IMvigor210. The predicting model constructed with Enet (alpha =0.2) algorithm had a highest average C-index of 0.69, which was suggested as the optimal IRS. As an independent risk factor for bladder cancer, IRS had a powerful performance in predicting the overall survival (OS) rate of patients, with an area under curve of 1-, 3- and 5-year receiver operating characteristic (ROC) curve being 0.744, 0.791 and 0.816 in TCGA dataset. Bladder cancer patients with low IRS score presented with a higher level of immune-activated cells, cytolytic function and T cell co-stimulation. We also found a lower tumor immune dysfunction and exclusion (TIDE) score, lower immune escape score, higher programmed cell death protein 1 (PD-1) & cytotoxic T-lymphocyte associated protein 4 immunophenoscore, higher tumor mutation burden (TMB) score, higher response rate and better prognosis in bladder cancer with low IRS score. Bladder cancer cases with high IRS score had a higher half maximal inhibitory concentration value of common chemotherapy and targeted therapy regimens. The current study developed an optimal IRS for bladder cancer patients, which acted as an indicator for predicting prognosis, stratifying risk and guiding treatment for bladder cancer patients. Further analysis should be focused on the exploration the differentially expressed genes (DEGs) and related underlying mechanism mediating the development of bladder cancer in different IRS score group.

Tumor hypoxia in immune infiltration and prognosis of bladder cancer.

Bladder cancer (BC) is the sixth most common cancer and the ninth leading cause of cancer death among men in the world. Previous studies have shown that tumor hypoxia plays an important role in the occurrence and development of BC, but the role of tumor hypoxia in the prognosis and immune infiltration of BC remains unclear. Our aim was to perform a bioinformatics analysis combined with a clinical analysis to explore the roles of hypoxia in BC. We acquired datasets (GSE13507, GSE5287, and GSE1827) containing mRNA expression information from BC cohorts from the Gene Expression Omnibus (GEO) and measured the Hypoxia score using the Gene Set Variation Analysis (GSVA). Then we used X-tile method and log-rank test and Pearson's correlation test to analyze the relation among the Hypoxia score and the clinicopathological and immunological characteristics of BC and used stepwise Cox regression analysis to establish a Prognostic model. Hypoxia was found to be closely associated with tumor grade, pathological type, invasion, and prognosis of BC in our study. Moreover, we determined that hypoxia was closely related to the infiltration abundance of multiple immune cells through a correlation analysis, and the tumor immune cell infiltration was further found to be significantly associated with the tumor grade and tumor type of BC. Furthermore, we constructed several models based on the Hypoxia score and tumor immune infiltration with C-indexes ranging from 0.703 and 0.888, which showed good performance in predicting the prognosis of BC. Our study showed that hypoxia plays an important role in the progression, prognosis, and tumor immune infiltration of BC. Our models based on hypoxia and tumor immune infiltration play a guiding role in the prognosis and treatment of BC patients.

Identification of bladder cancer subtypes and predictive signature for prognosis, immune features, and immunotherapy based on immune checkpoint genes

Immunotherapy based on immune checkpoint genes (ICGs) has recently made significant progress in the treatment of bladder cancer patients, but many patients still cannot benefit from it. In the present study, we aimed to perform a comprehensive analysis of ICGs in bladder cancer tissues with the aim of evaluating patient responsiveness to immunotherapy and prognosis. We scored ICGs in each BLCA patient from TCGA and GEO databases by using ssGSEA and selected genes that were significantly associated with ICGs scores by using the WCGNA algorithm. NMF clustering analysis was performed to identify different bladder cancer molecular subtypes based on the expression of ICGs-related genes. Based on the immune related genes differentially expressed among subgroups, we further constructed a novel stratified model containing nine genes by uni-COX regression, LASSO regression, SVM algorithm and multi-COX regression. The model and the nomogram constructed based on the model can accurately predict the prognosis of bladder cancer patients. Besides, the patients classified based on this model have large differences in sensitivity to immunotherapy and chemotherapy, which can provide a reference for individualized treatment of bladder cancer.

Abstract PO1-26-02: Enfortumab vedotin (EV): Correlation of estrogen receptor status and Nectin-4 expression with single agent efficacy in breast XPDX models

Abstract EV is a Nectin-4 targeting antibody-drug conjugate (ADC) with an MMAE payload, recently approved for treatment of bladder cancer patients. To better understand the potential for EV in treatment of breast cancer, we evaluated 175 breast XPDX models, including hormone receptor positive and negative cancer, some with actionable mutations, representing primary and metastatic disease from naïve or clinically treated patients. Each model was stained and scored for Nectin-4 protein and evaluated in vivo against single agent EV and activity correlated with ER status, Nectin-4 staining and known variants. 175 breast XPDX models were evaluated in this study, approximately 35% representing estrogen receptor positive and 20% clinically HER2+ cancers. Nectin-4 protein expression based on intensity and proportion was determined on a scale of 0+-3+, and models profiled using WES and RNAseq. For in vivo studies, models were evaluated against single agent EV administered by intravenous injection once weekly for three cycles at 3 mg/kg. Endpoints included tumor volume and time from treatment initiation with %T/C values and tumor regression reported at study completion; a T/C of ≤ 20% versus control was considered sensitive. Tumor regression (%T/C&amp;lt; 0%) versus Day 0 tumor volume was also reported. Overall, 40% of breast models stained positive for Nectin-4 including 50% of ER- and 20% of ER+ and 50% of HER2+ models. For ER- models, 50% were negative and 40% stained 1+ while 80% of ER+ models were negative and 15% stained 1+. In vivo, 25% of models were sensitive to EV, with 65% of these models ER- and &amp;lt; 10% HER2+. Nectin-4 staining did not directly correlate to model sensitivity although models with known drivers such as AKT1 and ESR1 were insensitive as were several models established from post CDK4/6i patients. We have characterized a panel of breast XPDX models based on Nectin-4 staining and in vivo sensitivity to EV and correlated activity with protein and receptor staining and known mutations. This data is a valuable tool in further developing EV and identifying its potential in treating breast cancer. Citation Format: Crystal Moreno, Johnnie Flores, Alyssa Simonson, Maci DeBoer, Natalia Banos, Armando Diaz III, Morgan Lynch, Jim Lund, Leonora Leykum, Tahmi Rouzbahan, Manuel Pedregal, Kyriakos P. Papadopoulos, Amy Lang, Arthur Rosenthal, Drew Rasco, Gladys Rodriguez, Luis Rodriguez, Nehal Lakhani, Muralidhar Beeram, Amita Patnaik, Maria De Miguel, Ronald Drengler, Steven Abbate, Bernard Doger de Speville Uribe, Michael Wick. Enfortumab vedotin (EV): Correlation of estrogen receptor status and Nectin-4 expression with single agent efficacy in breast XPDX models [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO1-26-02.

Abstract 5726: The potential anti-cancer activity of dual TTK/PLK1 inhibitor, BAL0891, in bladder cancer

Abstract Background: BAL0891 is a novel dual inhibitor of threonine tyrosine kinase (TTK) and polo-like kinase 1 (PLK1) which affects mitotic spindle assembly checkpoint integrity resulting in aberrant mitotic progression of cancer cells. Since unlike other organs, bladder urothelium is highly regenerative in certain circumstances, there are high chances of cell cycle inhibitors to have anti-cancer activity over bladder cancer. In this study, we investigated the therapeutic potential of BAL0891 in bladder cancer compared to single TTK or PLK1 inhibitor and discovered the best therapeutic combination partner for BAL0891. Methods: We performed meta-analysis of the mRNA expression levels of bladder cancer using Gene Expression Profiling Interactive Analysis 2 (GEPIA2). Representative bladder cancer cell lines (253J, 253J-BV, J82, RT4, T24, J82, HT1197, and HT1376) were treated with the dual protein kinase inhibitors, BAL0891, in comparison with TTK inhibitor (BAY1217389) or PLK1 inhibitor (onvansertib). BAL0891 was combined with CDK4/6 inhibitor, another cell cycle inhibitor working at different point from BAL0891. Cell viability was assessed using CCK-8 assay during 72 hours after treatment. Expression levels of TTK and PLK1 were measured by immunoblotting. Cell cycle analysis and cell apoptosis detection were performed on T24 cell. Results: The mRNA expression levels of both TTK (16.7 times) and PLK1 (10.0 times) were significantly upregulated only in bladder cancers compared to normal bladder tissues (P&amp;lt;0.05). Compared to TTK or PLK1 inhibitor, BAL0891 was sensitive in 75% of bladder cancer cell lines (IC50 &amp;lt;0.1 uM) and significantly reduced proliferation of bladder cancer cell lines depending on the dosage. TTK and PLK1 expression levels of cancer cells were associated with the sensitivity to BAL0891. BAL0891 significantly induced necrosis and increased in polyploidy and G2/M arrest in T24 cell. The anti-cancer activity of BAL0891 was further enhanced in certain cell lines (RT4, and J82) by combination of CDK4/6 inhibitor. Conclusion: This is the first study to suggest the potent anti-cancer activity of BAL0891 in bladder cancer. BAL0891 effectively worked on bladder cancer by two tracks which not only induced G2/M arrest but also increased in polyploidy. Furthermore, BAL0891 in combination with CDK4/6 inhibitor promoted anti-cancer effects. Lastly, this study suggests the use of TTK and PLK1 as the predictive biomarker for BAL0891. These data support further investigation of BAL0891 for the treatment of bladder cancer patients. Citation Format: Jee Soo Park, Ji-eun Lee, Myung Eun Lee, Jongchan Kim, Won Sik Jang, Jae Jung Lee, Jun Seung Lee, Minkyung Kang, Won Sik Ham. The potential anti-cancer activity of dual TTK/PLK1 inhibitor, BAL0891, in bladder cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5726.

Molecular mechanism of anticancer effect of heat shock protein 90 inhibitor BIIB021 in human bladder cancer cell line

Bladder cancer is a type of urologic malignancy that exhibits significant morbidity, mortality, and treatment costs. Inhibition of heat shock protein 90 (HSP90) activity has been a promising pharmacological strategy for blocking of bladder cancer pathogenesis. BIIB021 is a next-generation HSP90 inhibitor which interrupts ATP hydrolysis process of HSP90 and inhibits the stabilization and correct folding of client proteins. In current study, we aimed to investigate the molecular mechanism of the anticancer activity of BIIB021 in human bladder cancer T24 cells. Our results revealed that nanomolar concentration of BIIB021 decreased viability of T24 cell. BIIB021 downregulated HSP90 expression in T24 cells and inhibited the refolding activity of luciferase in the presence of T24 cell lysate. PCR array data indicated a significant alteration in transcript levels of cancer-related genes involved in metastases, apoptotic cell death, cell cycle, cellular senescence, DNA damage and repair mechanisms, epithelial-to-mesenchymal transition, hypoxia, telomeres and telomerase, and cancer metabolism pathways in T24 cells. All findings hypothesize that BIIB021 could exhibit as effective HSP90 inhibitor in the future for treatment of bladder cancer patients.

Prediction of anticancer drug resistance using a 3D microfluidic bladder cancer model combined with convolutional neural network-based image analysis.

Bladder cancer is the most common urological malignancy worldwide, and its high recurrence rate leads to poor survival outcomes. The effect of anticancer drug treatment varies significantly depending on individual patients and the extent of drug resistance. In this study, we developed a validation system based on an organ-on-a-chip integrated with artificial intelligence technologies to predict resistance to anticancer drugs in bladder cancer. As a proof-of-concept, we utilized the gemcitabine-resistant bladder cancer cell line T24 with four distinct levels of drug resistance (parental, early, intermediate, and late). These cells were co-cultured with endothelial cells in a 3D microfluidic chip. A dataset comprising 2,674 cell images from the chips was analyzed using a convolutional neural network (CNN) to distinguish the extent of drug resistance among the four cell groups. The CNN achieved 95.2% accuracy upon employing data augmentation and a step decay learning rate with an initial value of 0.001. The average diagnostic sensitivity and specificity were 90.5% and 96.8%, respectively, and all area under the curve (AUC) values were over 0.988. Our proposed method demonstrated excellent performance in accurately identifying the extent of drug resistance, which can assist in the prediction of drug responses and in determining the appropriate treatment for bladder cancer patients.

Establishment of bladder cancer spheroids and cultured in microfluidic platform for predicting drug response.

Cisplatin-containing combination chemotherapy has been used as the standard treatment for bladder cancer patients at advanced stage. However, nearly 50% of patients are nonresponders. To guide the selection of more effective chemotherapeutic agents, a bladder cancer spheroids microfluidic drug sensitivity analysis system was established in this study. Bladder cancer spheroids were established and successfully cultured in a customized microfluidic device to assess their response to different chemotherapeutic agents. The in vitro drug sensitivity results were also compared to patient-derived xenograft (PDX) models and clinical responses of patients. As a result, bladder cancer spheroids faithfully recapitulate the histopathological and genetic features of their corresponding parental tumors. Furthermore, the in vitro drug sensitivity outcomes of spheroids (n = 8) demonstrated a high level of correlation with the PDX (n = 2) and clinical response in patients (n = 2). Our study highlights the potential of combining bladder cancer spheroids and microfluidic devices as an efficient and accurate platform for personalized selection of chemotherapeutic agents.

Transperitoneal vs extraperitoneal radical cystectomy: A systematic review and meta-analysis.

One of the most complex surgeries including radical cystectomy (RC) has a high rate of morbidity. The standard approach for the muscle-invasive bladder is conventional transperitoneal radical cystectomy. However, the procedure is associated with significant morbidities like ileus, urinary leak, bleeding, and infection. The aim of this study is to compare the transperitoneal RC approach with the extraperitoneal RC approach in the treatment of bladder cancer patients. The outcomes of this study are Operative time, Estimated Blood Loss, Hospital Stay, Post-Operative Ileus, Infection, and Major Complication (Clavien-Dindo Grade 3-5). PubMed, Cochrane Library, and Science Direct were systematically searched for different publications related to the meta-analysis. Keywords used for searching were Radical Cystectomy AND Extraperitoneal AND Transperitoneal up until 31st August 2022. The studies were screened for our eligibility criteria. Demographic parameters, perioperative variables, and postoperative complications were recorded and analyzed. The Newcastle-Ottawa Scale was used to evaluate the risk of bias in each study. The Review Manager (RevMan) software version 5.4.1 was used for statistical analysis. Eight studies (3 laparoscopic and 5 open methods) involving 1207 subjects (588 patients using the extraperitoneal approach and 619 using the transperitoneal approach) were included. The incidence of postoperative ileus is significantly lower after the extraperitoneal approach compared to the transperitoneal approach (p < 0.00001). The two techniques did not differ in operative time, estimated blood loss, duration of hospital stay, total infection, and major complication events. This meta-analysis shows that extraperitoneal radical cystectomy benefits in terms of reduced postoperative ileus.

Prediction of immune and targeted drug efficacy in pain-related risk subtypes for bladder cancer patients

Bladder cancer is a complex disease with high morbidity and mortality rates. At least 430,000 cases are diagnosed annually worldwide. Cancer pain is the most common and distressing symptom in cancer patients. Studies have reported depression, anxiety, and decreased quality of life in survivors of various cancers. The study of pain-related genes in cancer patients may provide a basis for developing targeted drugs for cancer therapy, which could reduce pain and improve quality of life of cancer patients. In this study, the mRNA expression and clinical data of bladder cancer patients were downloaded from public databases. A total of 103 pain-related genes were also downloaded from the public databases. Univariate Cox regression analysis identified 17 pain-related genes that were significantly associated with overall survival. We calculated a pain-related risk score for each patient, constructed a bladder cancer pain risk model, and categorized bladder cancer patients into two risk subtypes. Differences in prognosis, differential gene expression, immune cell signatures, hallmarks, metabolic pathways, and somatic mutations between the different risk subtypes were systematically investigated. Eight drugs associated with bladder cancer risk subtypes were identified. Their differences in the high- and low-risk subtypes of bladder cancer were examined. In addition, the response to immunotherapy was analyzed in patients with different pain-related subtypes. Results revealed significant differences in these characteristics. Finally, a predictive model for pain-related risk subtypes in patients with bladder cancer was established. The study findings provide a reference for prognostication and personalized medical treatment of bladder cancer patients.

Absence of detrusor muscle in TUR-BT specimen – can we predict who is at highest risk?

IntroductionAs a high-quality TUR-BT is important to ensure adequate treatment for bladder cancer patients, the aim of the current study is to investigate the impact of patient-related, surgical and tumor-specific parameters on detrusor muscle (DM) absence (primary objective) and to assess the impact of DM on the prognosis after a TUR-BT (secondary objective).Patients and methodsTransurethral resection of bladder tumors (TUR-BTs) between 2009 and 2021 were retrospectively screened (n = 3237). We included 2058 cases (1472 patients) for the primary and 472 patients for secondary objective. Clinicopathological variables including tumor size, localization, multifocality, configuration, operation time and skill-level of the urologist were assessed. We analyzed predictors for missing DM and prognostic factors for recurrence-free survival (RFS) for the complete cohort and subgroups.ResultsDM was present in 67.6% (n = 1371/2058). Surgery duration (continuous, minutes) was an independent predictor for absence of DM in the complete cohort (OR:0.98, r:0.012, 95%CI:0.98–0.99, p = 0.001). Other significant risk factors for missing DM were papillary tumors (OR:1.99, r:0.251, 95%CI:1.22–3.27, p = 0.006) in the complete cohort and bladder-roof and posterior-bladder-wall localization for re-resections. Absence of DM in high-grade BC correlated with reduced RFS (HR:1.96, 95%CI:1.0–3.79, p = 0.045).ConclusionSufficient time for a TUR-BT is mandatory to assure DM in the TUR-BT specimen. Also, cases with more difficult locations of bladder tumors should be performed with utmost surgical diligence and endourological training should incorporate how to perform such operations. Of note, DM correlates with improved oncological prognosis in high-grade BC.

Evaluating technical feasibility of a urine cell-free DNA (cfDNA) NGS assay for identifying biomarkers in bladder cancer.

565 Background: Bladder cancer is one of the most common cancers worldwide. In 2022, about 81,000 people were diagnosed with this disease and 17,000 died from it (www.cancer.org). Despite significant breakthroughs in targeted medicines (i.e., Erdafitinib, FGFR2/3 kinase inhibitor) and clinical care over the past decade, non-invasive molecular testing remains an unmet clinical need for the treatment of bladder cancer patients. By contrasting the results with those from the FDA-approved tissue-based CDx assay, we assess the clinical utility of a urine NGS assay for identifying biomarkers, including mutations from FGFR genes. Methods: Paired urine and tissue samples were collected from 107 (muscle and non-muscle invasive) bladder cancer patients from the Bladder BRIDGister clinical trial in Germany. Tissue specimens were analyzed using the FDA approved Qiagen therascreen FGFR RGQ RT-PCR kit while matched urine samples were processed using the PredicineCARE urine (cell-free DNA) cfDNA NGS assay with detection sensitivity of 0.3% (0.1% for hotspot mutations). One hundred seven bladder cancer urine cfDNA NGS and tissue RT-PCR results were analyzed to determine the concordance (PPA and NPA) between these two assays. A smaller sample set was also used to compare tissue NGS to therascreen RT-PCR and tissue NGS to urine cfDNA NGS. A subset of discordant mutations were additionally validated by ddPCR. Results: For the concordance analysis between PredicineCARE Urine cfDNA NGS and therascreen tissue RT-PCR assay of 107 samples, PPA was 100% (20/20, 95% CI: 83.2-100) and NPA was 94.1% (48/51, 95% CI: 83.8-98.8). Three discrepant samples (tissue FGFR negative but urine positive for FGFR genes) were further analyzed by independent orthogonal ddPCR (Bio-Rad ddPCR Mutation Detection Assay). All tissue FGFR negative but urine positive samples were confirmed positive by ddPCR. PPA and NPA between PredicineCARE Urine cfDNA and Tissue NGS were 100% (19/19, 95% CI: 82.4-100) and 94.2% (49/52, 95% CI: 84.1-98.8) respectively. PPA and NPA between PredicineCARE Tissue NGS and Therascreen FGFR RGQ RT-PCR kit were both &gt; 95%. Conclusions: High concordance between FGFR alterations detected with an FDA approved tissue CDx and urine cfDNA NGS assay demonstrates that the PredicineCARE urine cfDNA NGS assay may represent a novel, accurate, and non-invasive clinical application for molecular diagnostic testing to identify biomarkers in bladder cancer.

The Lund taxonomy for bladder cancer classification - from gene expression clustering to cancer cell molecular phenotypes, and back again.

Treatment of bladder cancer patients depends on precise diagnosis. Molecular subtyping by gene expression profiling may contribute substantially to subclassification of bladder cancer. Several classification systems have been proposed. Most of these base their classification on whole biopsy features, and molecular subtypes are therefore often defined by a combination of features from the cancer cells as well as infiltrating noncancer cells. This makes the link to what is seen at the cancer cell level unclear. The aim of the Lund taxonomy (LundTax) has been to align gene expression-level classification with immunohistochemical classification to identify cancer cell phenotypes independent of infiltration and proliferation. A systematic approach was used in which gene expression clusters were validated and adjusted by immunohistochemistry using markers expressed only by the cancer cells. This review provides a rationale for defining molecular subtypes and a step-by-step description of the development of the LundTax with motivations for each modification and extension. As the cancer cell phenotype defined by gene expression profiling corresponds with the immunohistochemistry of cancer cells, the LundTax represents a harmonization of the gene expression and immunohistochemical levels. Furthermore, the classification system is independent of pathological stage and is, thus, applicable to all urothelial carcinomas. A unified classification system relevant for both the molecular biologist and pathologist will facilitate systematization of current treatment practices, as well as the development of new treatments. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Prognosis Prediction of Disulfidptosis-Related Genes in Bladder Cancer and a Comprehensive Analysis of Immunotherapy.

As a newly discovered mechanism of cell death, disulfidptosis is expected to help diagnose and treat bladder cancer patients. First, data obtained from public databases were analyzed using bioinformatics techniques. SVA packages were used to combine data from different databases to remove batch effects. Then, the differential analysis and COX regression analysis of ten disulfidptosis-related genes identified four prognostically relevant differentially expressed genes which were subjected to Lasso regression for further screening to obtain model-related genes and output model formulas. The predictive power of the prognostic model was verified and the immunohistochemistry of model-related genes was verified in the HPA database. Pathway enrichment analysis was performed to identify the mechanism of bladder cancer development and progression. The tumor microenvironment and immune cell infiltration of bladder cancer patients with different risk scores were analyzed to personalize treatment. Then, information from the IMvigor210 database was used to predict the responsiveness of different risk patients to immunotherapy. The oncoPredict package was used to predict the sensitivity of patients at different risk to chemotherapy drugs, and its results have some reference value for guiding clinical use. After confirming that our model could reliably predict the prognosis of bladder cancer patients, the risk scores were combined with clinical information to create a nomogram to accurately calculate the patient survival rate. A prognostic model containing three disulfidptosis-related genes (NDUFA11, RPN1, SLC3A2) was constructed. The functional enrichment analysis and immune-related analysis indicated patients in the high-risk group were candidates for immunotherapy. The results of drug susceptibility analysis can guide more accurate treatment for bladder cancer patients and the nomogram can accurately predict patient survival. NDUFA11, RPN1, and SLC3A2 are potential novel biomarkers for the diagnosis and treatment of bladder cancer. The comprehensive analysis of tumor immune profiles indicated that patients in the high-risk group are expected to benefit from immunotherapy.

The delay in the diagnosis and treatment of newly diagnosed bladder cancer patients during COVID 19 pandemic.

To evaluate the newly diagnosed bladder cancer(BC) patients during the pandemic period and compare them with the corresponding last4 years. To document the time schedules of BC patient evaluation and define the possible delays and investigate the reasons. Newly diagnosed BC patients who underwent transurethral resection of bladder tumour in the last5 years were retrospectively included to study. The patients were divided into 5 groups. Group-1 was composed of patients diagnosed betweenMarch, 1,2016 -March-1,2017. The patients who were diagnosed in the further corresponding years formed group 2,3 and 4. The last group(Group-5) was composed of patients who were diagnosed during the pandemic period which was between March,1,2020 and March,1,2021. The clinicodemographic properties and diagnostic time schedules of the patients were compared between the groups. There were56 patients in Group-1,60 patients in Group-2,61 patients in Group-3,68 patients in Group-4, and 58 patients inGroup-5. The mean hospital admission period was102.5±179.0days during the pandemic period which ranged between24.5± 32.0 and38.3±69.1days before thepandemic.(p=0.002)The diagnosis-anesthesia period was significantly higher during the pandemic pandemic period.(p=0.034). The pandemic period has caused some delays in the diagnosis and treatment of BC patients. Telemonitoring systems may be useful to prevent the possible diagnostic and treatment delays for newly diagnosed BC patients.

An immune‐related gene signature for the prognosis of human bladder cancer based on WGCNA

The innovation of immunotherapy was a milestone in the treatment of bladder cancer (BLCA). However, the treatment benefits varied by individual thus promoting the investigation of the biomarker of the patients. Unfortunately, there were not many effective predictive models, which were desired by clinicians, for BLCA that can predict the prognosis and benefit of immunotherapy. We constructed a three genes prognosis prediction model termed RiskScore based on the result of weighted correlation network analysis (WGCNA) from The Cancer Genome Atlas (TCGA) cohort (n = 406). We then validated the prediction accuracy with three validation cohort(GSE13507 (n = 165), GSE48075(n = 73), GSE32894(n = 224)). We compared the differences in gene expression, immune relate function, and immune infiltration between two groups divided by RiskScore. We further discovered the potential drug target and suitable compounds for high-risk groups. Our results suggested that the low-risk group may be more potential for immunotherapy for they have higher B cell infiltration, higher expression of immune checkpoints(PDCD1, CTLA4), and much more active immune-related pathways(B cell and T cell receptor signaling pathway). The RiskScore showed a well predictive accuracy for the prognosis of BLCA. After Spearman analysis, we found the suitable drug target and compounds for the patients in the high-risk group. The model we constructed is able to predict the prognosis of BLCA patients with ease and accuracy. PLK1 and gefitinib may be utilized for further treatment of BLCA patients.