Grade Bladder Cancer Research Articles

Precise grading of non-muscle invasive bladder cancer with multi-scale pyramidal CNN

The grading of non-muscle invasive bladder cancer (NMIBC) continues to face challenges due to subjective interpretations, which affect the assessment of its severity. To address this challenge, we are developing an innovative artificial intelligence (AI) system aimed at objectively grading NMIBC. This system uses a novel convolutional neural network (CNN) architecture called the multi-scale pyramidal pretrained CNN to analyze both local and global pathology markers extracted from digital pathology images. The proposed CNN structure takes as input three levels of patches, ranging from small patches (e.g., 128×128\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$128 \ imes 128$$\\end{document}) to the largest size patches (512×512\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$512 \ imes 512$$\\end{document}). These levels are then fused by random forest (RF) to estimate the severity grade of NMIBC. The optimal patch sizes and other model hyperparameters are determined using a grid search algorithm. For each patch size, the proposed system has been trained on 32K patches (comprising 16K low-grade and 16K high-grade samples) and subsequently tested on 8K patches (consisting of 4K low-grade and 4K high-grade samples), all annotated by two pathologists. Incorporating light and efficient processing, defining new benchmarks in the application of AI to histopathology, the ShuffleNet-based AI system achieved notable metrics on the testing data, including 94.25% ± 0.70% accuracy, 94.47% ± 0.93% sensitivity, 94.03% ± 0.95% specificity, and a 94.29% ± 0.70% F1-score. These results highlight its superior performance over traditional models like ResNet-18. The proposed system’s robustness in accurately grading pathology demonstrates its potential as an advanced AI tool for diagnosing human diseases in the domain of digital pathology.

NMGrad: Advancing Histopathological Bladder Cancer Grading with Weakly Supervised Deep Learning.

The most prevalent form of bladder cancer is urothelial carcinoma, characterized by a high recurrence rate and substantial lifetime treatment costs for patients. Grading is a prime factor for patient risk stratification, although it suffers from inconsistencies and variations among pathologists. Moreover, absence of annotations in medical imaging renders it difficult to train deep learning models. To address these challenges, we introduce a pipeline designed for bladder cancer grading using histological slides. First, it extracts urothelium tissue tiles at different magnification levels, employing a convolutional neural network for processing for feature extraction. Then, it engages in the slide-level prediction process. It employs a nested multiple-instance learning approach with attention to predict the grade. To distinguish different levels of malignancy within specific regions of the slide, we include the origins of the tiles in our analysis. The attention scores at region level are shown to correlate with verified high-grade regions, giving some explainability to the model. Clinical evaluations demonstrate that our model consistently outperforms previous state-of-the-art methods, achieving an F1 score of 0.85.

Do we need a re-TUR after en bloc resection of T1 stage bladder cancer?

BackgroundA second look trans-urethral resection of the bladder (re-TUR) is recommended after the diagnosis of T1 high grade (T1HG) bladder cancer. Few studies have evaluated the results of re-TUR after a first en bloc resection (EBR) and none of them have specifically reported the pathological results on the field of previous T1 disease.ObjectiveTo report the rate of upstaging and the rate of residual disease (RD) on the field of T1HG lesions resected with EBR.Materials and methodsBetween 01/2014 and 06/2022, patients from 2 centers who had a re-TUR after an EBR for T1HG urothelial carcinoma were retrospectively included. Primary endpoint was the rate of RD including the rate of upstaging to T2 disease on the scar of the primary resection. Secondary endpoints were the rate of any residual disease outside the field.ResultsSeventy-five patients were included. No muscle invasive bladder cancer lesions were found after re-TUR. Among the 16 patients who had a RD, 4 were on the resection scar. All of these lesions were papillary and high grade. RD outside the field of the first EBR was observed in 12 patients.ConclusionAfter EBR of T1HG disease, none of our patients had an upstaging to MIBC. However, the rate of RD either on and outside the field of the EBR remains quite significant. We suggested that predictive factors of residual papillary disease (number of tumors at the initial TUR and concomitant CIS) might be suitable to select patient who will benefit of the re-TUR.

Deep learning identifies histopathologic changes in bladder cancers associated with smoke exposure status.

Smoke exposure is associated with bladder cancer (BC). However, little is known about whether the histologic changes of BC can predict the status of smoke exposure. Given this knowledge gap, the current study investigated the potential association between histology images and smoke exposure status. A total of 483 whole-slide histology images of 285 unique cases of BC were available from multiple centers for BC diagnosis. A deep learning model was developed to predict the smoke exposure status and externally validated on BC cases. The development set consisted of 66 cases from two centers. The external validation consisted of 94 cases from remaining centers for patients who either never smoked cigarettes or were active smokers at the time of diagnosis. The threshold for binary categorization was fixed to the median confidence score (65) of the development set. On external validation, AUC was used to assess the randomness of predicted smoke status; we utilized latent feature presentation to determine common histologic patterns for smoke exposure status and mixed effect logistic regression models determined the parameter independence from BC grade, gender, time to diagnosis, and age at diagnosis. We used 2,000-times bootstrap resampling to estimate the 95% Confidence Interval (CI) on the external validation set. The results showed an AUC of 0.67 (95% CI: 0.58-0.76), indicating non-randomness of model classification, with a specificity of 51.2% and sensitivity of 82.2%. Multivariate analyses revealed that our model provided an independent predictor for smoke exposure status derived from histology images, with an odds ratio of 1.710 (95% CI: 1.148-2.54). Common histologic patterns of BC were found in active or never smokers. In conclusion, deep learning reveals histopathologic features of BC that are predictive of smoke exposure and, therefore, may provide valuable information regarding smoke exposure status.

Advanced optical imaging techniques for bladder cancer detection and diagnosis: a systematic review.

To systematically assess the current available literature concerning advanced optical imaging methods for the detection and diagnosis of bladder cancer (BCa), focusing particularly on the sensitivity and specificity of these techniques. First a scoping search was performed to identify all available optical techniques for BCa detection and diagnosis. The optical imaging techniques used for detecting BCa are: the Storz professional image enhancement system (IMAGE1 S), narrow-band imaging (NBI), photoacoustic imaging (PAI), autofluorescence imaging (AFI), photodynamic diagnosis (PDD), and scanning fibre endoscopy (SFE). The staging and grading techniques for BCa are: optical coherence tomography (OCT), confocal laser endomicroscopy (CLE), Raman spectroscopy, endocytoscopy, and non-linear optical microscopy (NLO). Then a systematic literature search was conducted using MEDLINE, EMBASE and Web of Science from inception to 21 November 2023. Articles were screened and selected by two independent reviewers. Inclusion criteria were: reporting on both the sensitivity and specificity of a particular technique and comparison to histopathology, and in the case of a detection technique comparison to white light cystoscopy (WLC). Out of 6707 articles, 189 underwent full-text review, resulting in 52 inclusions. No articles met criteria for IMAGE1 S, PAI, SFE, Raman spectroscopy, and endocytoscopy. All detection techniques showed higher sensitivity than WLC, with NBI leading (87.8-100%). Overall, detection technique specificity was comparable to WLC, with PDD being most specific (23.3-100%). CLE and OCT varied in sensitivity and specificity, with OCT showing higher specificity for BCa diagnosis, notably for carcinoma in situ (97-99%) compared to CLE (62.5-81.3%). NLO demonstrated high sensitivity and specificity (90-97% and 77-100%, respectively) based on limited data from two small ex vivo studies. Optical techniques with the most potential are PDD for detecting and OCT for staging and grading BCa. Further research is crucial to validate their integration into routine practice and explore the value of other imaging techniques.

CircPGM5 regulates Foxo3a phosphorylation via MiR-21-5p/MAPK10 axis to inhibit bladder cancer progression

Bladder cancer (BC) is one of the most prevalent malignant tumors worldwide, and the incidence is especially higher in males. Extensive evidence has demonstrated the pivotal role of circular RNAs (circRNAs) in BC progression. However, the exact regulatory mechanism of circRNAs in BC remains incompletely elucidated and warrants further exploration. This study screened a novel circRNA-circPGM5 from thousands of circRNAs by high-throughput sequencing. We found that circPGM5, originating from the PGM5 gene, was significantly lower expressed in BC tissues. Quantitative real-time PCR (qRT-PCR) verified that circPGM5 showed relatively low expression in 50 pairs of BC tissues and EJ and T24 cells. Notably, circPGM5 expression was correlated with stage, grade, and lymphatic metastasis of BC. Through RNA-FISH assay, we confirmed that circPGM5 predominantly localized in the cytoplasm. Functionally, overexpression of circPGM5 inhibited the proliferation, migration, and invasion of BC cells in vitro. Remarkably, circPGM5 demonstrated markedly significant tumor growth and metastasis suppression in vivo. Mechanistically, we discovered that circPGM5 upregulated the mitogen-activated protein kinase 10 (MAPK10) expression by influencing the oncogenic miR-21-5p activity through miR-21-5p absorption. This modulation of MAPK10 impacted the phosphorylation of the tumor suppressor Foxo3a in BC. In conclusion, our findings uncovered the tumor-suppressing role of circPGM5 in BC via the miR-21-5p/MAPK10/Foxo3a axis.

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.

1121 High Grade Bladder Cancer in A 28-Year-Old Male: The Burden Of Recurrence

1121 High Grade Bladder Cancer in A 28-Year-Old Male: The Burden Of Recurrence

Contrast-enhanced ultrasound (CEUS): applications from the kidneys to the bladder.

Contrast-enhanced ultrasound (CEUS) is an advanced ultrasound (US) technique utilizing ultrasound contrast agents (UCAs) to provide detailed visualization of anatomic and vascular architecture, including the depiction of microcirculation. CEUS has been well-established in echocardiography and imaging of focal hepatic lesions and recent studies have also shown the utility of CEUS in non-hepatic applications like the urinary system. The updated guidelines by the European Federation of Societies for Ultrasound in Medicine and Biology (EFSUMB) from 2018 describe the use of CEUS for non-hepatic applications. CEUS' excellent safety profile and spatial resolution make it a superior modality to conventional US and is often comparable and even superior to CECT in some instances. In comparison to other cross-sectional imaging modalities such as CECT or MRI, CEUS offers a safe (by virtue of non-nephrotoxic US contrast agents), accurate, cost-efficient, readily available, and a quick means of evaluation of multiple pathologies of the urinary system. CEUS also has the potential to reduce the overall economic burden on patients requiring long-term follow-up due to its low cost as compared to CT or MRI techniques. This comprehensive review focuses on the applications of CEUS in evaluating the urinary system from the kidneys to the urinary bladder. CEUS can be utilized in the kidney to evaluate complex cystic lesions, indeterminate lesions, pseudotumors (vs solid renal tumors), renal infections, and renal ischemic disorders. Additionally, CEUS has also been utilized in evaluating renal transplants. In the urinary bladder, CEUS is extremely useful in differentiating a bladder hematoma and bladder cancer when conventional US techniques show equivocal results. Quantitative parameters of time-intensity curves (TICs) of CEUS examinations have also been studied to stage and grade bladder cancers. Although promising, further research is needed to definitively stage bladder cancers and classify them as muscle-invasive or non-muscle invasive using quantitative CEUS to guide appropriate intervention. CEUS has been very effective in the classification of cystic renal lesions, however, further research is needed in differentiating benign from malignant renal masses.

Non-Gaussian diffusion metrics with whole-tumor histogram analysis for bladder cancer diagnosis: muscle invasion and histological grade

PurposeTo investigate the performance of histogram features of non-Gaussian diffusion metrics for diagnosing muscle invasion and histological grade in bladder cancer (BCa).MethodsPatients were prospectively allocated to MR scanner1 (training cohort) or MR2 (testing cohort) for conventional diffusion-weighted imaging (DWIconv) and multi-b-value DWI. Metrics of continuous time random walk (CTRW), diffusion kurtosis imaging (DKI), fractional-order calculus (FROC), intravoxel incoherent motion (IVIM), and stretched exponential model (SEM) were simultaneously calculated using multi-b-value DWI. Whole-tumor histogram features were extracted from DWIconv and non-Gaussian diffusion metrics for logistic regression analysis to develop diffusion models diagnosing muscle invasion and histological grade. The models’ performances were quantified by area under the receiver operating characteristic curve (AUC).ResultsMR1 included 267 pathologically-confirmed BCa patients (median age, 67 years [IQR, 46–82], 222 men) and MR2 included 83 (median age, 65 years [IQR, 31–82], 73 men). For discriminating muscle invasion, CTRW achieved the highest testing AUC of 0.915, higher than DWIconv’s 0.805 (p = 0.014), and similar to the combined diffusion model’s AUC of 0.885 (p = 0.076). For differentiating histological grade of non-muscle-invasion bladder cancer, IVIM outperformed a testing AUC of 0.897, higher than DWIconv’s 0.694 (p = 0.020), and similar to the combined diffusion model’s AUC of 0.917 (p = 0.650). In both tasks, DKI, FROC, and SEM failed to show diagnostic superiority over DWIconv (p > 0.05).ConclusionCTRW and IVIM are two potential non-Gaussian diffusion models to improve the MRI application in assessing muscle invasion and histological grade of BCa, respectively.Critical relevance statementOur study validates non-Gaussian diffusion imaging as a reliable, non-invasive technique for early assessment of muscle invasion and histological grade in BCa, enhancing accuracy in diagnosis and improving MRI application in BCa diagnostic procedures.Key PointsMuscular invasion largely determines bladder salvageability in bladder cancer patients.Evaluated non-Gaussian diffusion metrics surpassed DWIconv in BCa muscle invasion and histological grade diagnosis.Non-Gaussian diffusion imaging improved MRI application in preoperative diagnosis of BCa.Graphical

Automatic analysis of nuclear features reveals a non-tumoral predictor of tumor grade in bladder cancer

Background & objectivesTumor grade determines prognosis in urothelial carcinoma. The classification of low and high grade is based on nuclear morphological features that include nuclear size, hyperchromasia and pleomorphism. These features are subjectively assessed by the pathologists and are not numerically measured, which leads to high rates of interobserver variability. The purpose of this study is to assess the value of a computer-based image analysis tool for identifying predictors of tumor grade in bladder cancer.MethodsFour hundred images of urothelial tumors were graded by five pathologists and two expert genitourinary pathologists using a scale of 1 (lowest grade) to 5 (highest grade). A computer algorithm was used to automatically segment the nuclei and to provide morphometric parameters for each nucleus, which were used to establish the grading algorithm. Grading algorithm was compared to pathologists’ agreement.ResultsComparison of the grading scores of the five pathologists with the expert genitourinary pathologists score showed agreement rates between 88.5% and 97.5%.The agreement rate between the two expert genitourinary pathologists was 99.5%. The quantified algorithm based conventional parameters that determine the grade (nuclear size, pleomorphism and hyperchromasia) showed > 85% agreement with the expert genitourinary pathologists. Surprisingly, the parameter that was most associated with tumor grade was the 10th percentile of the nuclear area, and high grade was associated with lower 10th percentile nuclei, caused by the presence of more inflammatory cells in the high-grade tumors.ConclusionQuantitative nuclear features could be applied to determine urothelial carcinoma grade and explore new biologically explainable parameters with better correlation to grade than those currently used.

Quantitative CT Morphometrics: A Novel Approach for Predicting the Bladder Cancer Grade.

Background and objective Bladder cancer (BC) is a common urothelial neoplasm, with non-muscle invasive formscomprising about 75% of cases and generally having better outcomes than muscle-invasive types. Accurate preoperative grading and staging of BC are essential for appropriate treatment planning. This study investigates the efficacy of computerized tomography (CT) in correlating the morphological features of tumors to predict the histopathological grades of BC. Materials and methods This retrospective cohort involved 100 patients diagnosed with non-muscle invasive BC, who underwent transurethral resection of bladder tumor (TUR-BT) between January 2010 and August 2021. CT imaging, utilizing a 128-slice CT scanner, was employed to measure the tumor height (H) and contact length (CL). The study considered morphometric parameters across axial, coronal, and sagittal planes. Statistical analyses were conducted, comparing radiological findings with histopathological evaluations. Tumor grading was determined according to the 2004/2016 WHO classification. Results Among the 100 patients with primary bladder tumors, 15 were female and 85 were male, with a mean age of 65.28 ± 7.11 years. Furthermore, 58 had high-grade bladder tumors, while 42 had low-grade bladder tumors. Across all planes, high-grade tumors exhibited higher values for the tumor H, CL, and the tumor height-to-contact length (H/CL) ratio compared to low-grade tumors (p<0.05). Notably, the specificity, sensitivity, and diagnostic accuracy of the tumor CL were higher than those of the tumor H and the tumor H/CL ratio. A tumor CL exceeding 19.1mm measured in the axial plane demonstrated 83% sensitivity and specificity for high-grade tumors. Conclusion The measured CL of the tumor in the axial plane on computerized tomography urography has high sensitivity and specificity in detecting high-grade tumors.

Abstract A021: The role of MGAT5 in sex-dependent regulation of CD8+ T cells in muscle-invasive bladder cancer

Abstract Biological sex significantly affects bladder cancer incidence and outcome. Although men have much greater incidence of bladder cancer than women, females tend to be diagnosed with more advanced tumors and have worse outcomes. The mechanisms driving these differences are likely multifactorial, with biological factors playing an important role, however, much of the biology underlying these differences is unknown. The immune system is a critical regulator of cancer biology, and immune features have been associated with bladder cancer grade, stage, progression, and response to therapies. Sex dramatically affects the immune system including anti-tumor immunity. However, how sex and immunity intersect to affect clinical outcomes in bladder cancer patients remains unclear. CD8+ T cells are a key part of anti-tumor immune responses and the importance of inhibitory receptors such as programmed cell death-1 (PD-1), is now well established as a mechanism restricting T cell responses in MIBC. However, there are a variety of other regulatory pathways that restrict their anti-tumor function, which have yet to be investigated. One such pathway involves alterations in protein glycosylation, which can affect T cell function at many levels. The activity of the glycosyltransferase N-acetylglucosaminyltransferase V (MGAT5), responsible for complex N-glycan branching, has been shown to regulate T cell function in autoimmunity and chronic viral infections, however, its role in regulating anti-tumor CD8+ T cell responses has yet to be explored. We assessed the activity of MGAT5 in circulating and tumor-infiltrating CD8+ T cells in mice using a panel of cell lines in a syngeneic orthotopic model of muscle-invasive bladder cancer (MIBC). We found that in all tumor models, MGAT5 activity was upregulated in tumor infiltrating CD8+ T cells compared with circulating cells. Furthermore, using high parameter flow cytometry, we assessed the activity of MGAT5 in CD8+ T cells from mice with bladder cancer induced by the carcinogen N-butyl-N-(4-hydroxybutyl)nitrosamine (BBN), and in patients with MIBC. In both mice and humans, we found that sex affects MGAT5 activity in memory CD8+ T cells, with females exhibiting decreased MGAT5 activity in these cells compared to males. The functional significance of altering MGAT5 activity in T cells was also assessed in vivo. To do this, chimeric mice were generated by mixed bone-marrow transplant resulting in mice with loss of Mgat5 in T cells. Bladder cancer was then induced using BBN, and morbidity (defined as either 10% weight loss in one week, 10% weight loss post-BBN, or humane endpoint), as a proxy for mortality, was assessed over time. In this model, male mice were protected from BBN-induced morbidity compared to female mice, and this protection was abrogated by homozygous or heterozygous loss of Mgat5 in T cells. Overall, our data suggest that sex-dependent regulation of MGAT5 activity in CD8+ T cells may be an important underlying factor affecting outcomes in bladder cancer. Citation Format: Morgan E. Roberts, Igor Moskalev, Peter C. Black. The role of MGAT5 in sex-dependent regulation of CD8+ T cells in muscle-invasive bladder cancer [abstract]. In: Proceedings of the AACR Special Conference on Bladder Cancer: Transforming the Field; 2024 May 17-20; Charlotte, NC. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(10_Suppl):Abstract nr A021.

Abstract IA022: AI in bladder cancer pathology and research: What can we expect and what not?

Abstract Artificial intelligence (AI) applications are rapidly evolving, disruptive technologies that recently attracted tremendous public awareness including euphoria, bull runs at stock exchanges but also criticism and skepticism. Pathology, a crucial clinical diagnostic discipline, faces significant challenges despite its critical role and broad scope. A notable issue is the declining interest among medical graduates in pursuing further training in Surgical Pathology and Molecular Pathology. This disinterest is compounded by a trend towards part-time work and the aging demographic in Western industrial nations, which increases the demand for precise cancer diagnoses, molecular pathology and advanced oncological treatments. As the need for skilled pathologists grows, the availability of these professionals is steadily decreasing. Furthermore, political policies in heavily regulated healthcare systems (e.g., Germany) are exacerbating the shortage by limiting residency and specialist training positions despite the growing need. Adding to the reluctance among medical graduates to consider pathology as discipline is the looming “threat”” of replacing the field with Artificial Intelligence (AI) technologies. However, historical precedents suggest that necessity often spurs significant innovation. AI's role in pathology is expanding, reshaping the field with new technological advancements. AI, broadly encompassing various computational algorithms designed to perform tasks typically requiring human intelligence such as learning, reasoning, and pattern recognition, is now being applied extensively across different domains including medical diagnostics. Recent implementations in pathology include AI-driven algorithms that automate processes such as the Gleason grading of prostate biopsies, lymph node metastasis detection, detection of molecular bladder cancer subtypes or grading of kidney cancer showing high accuracy levels, speed and reproducibility in delivering results. These tools, while they do not replace pathologists, significantly reduce their workload by automating routine tasks, thus freeing up time for more complex diagnostic activities or simply dealing with the increasing workload. Despite the exciting possibilities, the use of AI in predicting molecular alterations, such as FGFR3 mutations in bladder cancer, faces limitations due to insufficient sensitivity and specificity, indicating that such technologies are not yet suitable for screening purposes. In conclusion, AI is increasingly vital in addressing the challenges of modern pathology, particularly in compensating for the shortage of pathologists. As technology advances, its integration into clinical practice offers promising solutions to enhance diagnostic accuracy and efficiency in uropathology, paving the way for more personalized and effective patient care. Citation Format: Markus Eckstein. AI in bladder cancer pathology and research: What can we expect and what not? [abstract]. In: Proceedings of the AACR Special Conference on Bladder Cancer: Transforming the Field; 2024 May 17-20; Charlotte, NC. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(10_Suppl):Abstract nr IA022.

Plasma metadherin mRNA expression in bladder cancer

Urinary bladder cancer (BC) is the ninth most common cancer worldwide. At present, the clinical diagnosis of BC depends on self-reported symptoms, tissue biopsy specimens by cystoscopy and from voided urine cytology. However, cystoscopy is an invasive examination and voided urine cytology has low sensitivity, which might provoke misdiagnosis. The search for cancer biomarkers in blood is worthy of intense attention due to patients' comfort and ease of sampling. This work aimed to study expression of mRNA metadherin (MTDH) in plasma, serum BC specific antigen 1 (BLCA-1) and cystatin C as biomarkers of BC and their relation to different disease stages. This study included 59 BC patients, 11 patients with benign bladder lesion and 18 subjects as normal controls. MTDH expression was assessed by real time polymerase chain reaction, BLCA-1, and cystatin C by the enzyme linked immunosorbent assay. The three biomarkers were elevated in BC patients than patients with benign bladder diseases and controls. Patients with BC grade 3 and 4 had higher cystatin C, BLCA-1 and MTDH in comparison to patients with grade 1 and grade 2 (p=0.000). The receiver operating characteristic curve analysis showed that BLCA-1 at a cutoff point of 32.5 ng/ml and area under the curve of 1.00, had 100% accuracy, 100% sensitivity, 100% specificity, 100% positive predictive values and 100% negative predictive value. In conclusion, BLCA-1 was a better biomarker than cystatin C and MTDH. Cystatin C, BLCA-1 and MTDH levels, can differentiate between benign bladder lesion and BC and correlated with tumor grades.

Prediction of histopathologic grades of bladder cancer with radiomics based on MRI: Comparison with traditional MRI

PurposeTo compare biparametric magnetic resonance imaging (bp-MRI) radiomics signatures and traditional MRI model for the preoperative prediction of bladder cancer (BCa) grade. Materials and methodsThis retrospective study included 255 consecutive patients with pathologically confirmed 113 low-grade and 142 high-grade BCa. The traditional MRI nomogram model was developed using univariate and multivariate logistic regression by the mean apparent diffusion coefficient (ADC), vesical imaging reporting and data system, tumor size, and the number of tumors. Volumes of interest were manually drawn on T2-weighted imaging (T2WI) and ADC maps by 2 radiologists. Using one-way analysis of variance, correlation, and least absolute shrinkage and selection operator methods to select features. Then, a logistic regression classifier was used to develop the radiomics signatures. Receiver operating characteristic (ROC) analysis was used to compare the diagnostic abilities of the radiomics and traditional MRI models by the DeLong test. Finally, decision curve analysis was performed by estimating the clinical usefulness of the 2 models. ResultsThe area under the ROC curves (AUCs) of the traditional MRI model were 0.841 in the training cohort and 0.806 in the validation cohort. The AUCs of the 3 groups of radiomics model [ADC, T2WI, bp-MRI (ADC and T2WI)] were 0.888, 0.875, and 0.899 in the training cohort and 0.863, 0.805, and 0.867 in the validation cohort, respectively. The combined radiomics model achieved higher AUCs than the traditional MRI model. decision curve analysis indicated that the radiomics model had higher net benefits than the traditional MRI model. ConclusionThe bp-MRI radiomics model may help distinguish high-grade and low-grade BCa and outperforming the traditional MRI model. Multicenter validation is needed to acquire high-level evidence for its clinical application.

Clinicopathologic characteristics and outcomes of prostate cancer incidentally discovered at the time of radical cystoprostatectomy: a population-based cohort study.

This study aimed to comprehensively analyze the clinical characteristics and prognosis of patients with concomitant bladder cancer (BCa) and prostate cancer (PCa) using a large population-based database. Within the Surveillance, Epidemiology, and End Results (SEER) database (2000-2019), we identified patient with concomitant PCa at the time of radical cystoprostatectomy (RCP). Logistic regression and propensity score matching (PSM) analyses were employed to identify risk factors and mitigate confounders, respectively. Kaplan-Meier survival curves were used to estimate cancer-specific survival (CSS). A total of 14,199 BCa patients undergoing RCP were identified, with 28.8% incidentally discovered to have concurrent PCa. Among them, 89.9% exhibited organ-confined (T1-2) PCa. An increased risk of concomitant tumors was observed among older age, white race, and high tumor grade of BCa. Survival analysis revealed no significant difference in CSS between patients with BCa alone and those with concurrent PCa (5-year CSS rate: 71.3% vs. 67.2%, P =0.076). Subgroup analysis and multivariable analysis, however, indicated that concurrent high-risk PCa adversely impacted survival (5-year CSS rate: 71.3% vs. 63.4%, HR 1.27, 95% CI 1.01-1.58, P =0.038) compared to solitary BCa. Notably, the presence of low/intermediate-risk PCa did not affect survival outcomes ( P =0.584). In conclusion, incidentally discovered PCa in RCP specimens is frequent and characterized by organ-confined presentation, lower PSA levels, and Gleason scores. Patients with concurrent high-risk PCa have a worse prognosis compared to those with solitary BCa, while the presence of low/intermediate-risk PCa does not influence oncological prognosis.

Abstract 7648: COL6A1 expression as a potential prognostic biomarker for risk stratification of T1HG bladder cancer: Unveiling the aggressive nature of a distinct non-muscle invasive subtype

Abstract Introduction and Objectives: T1 high grade (T1HG) bladder cancer (BC) is a type of non-muscle invasive BC (NMIBC) that is recognized as an aggressive subtype with a heightened propensity for progression. Current risk stratification methods for NMIBC rely on clinicopathological indicators; however, these approaches do not adequately capture the aggressive nature of T1HG BC. Thus, new, more accurate biomarkers for T1HG risk stratification are needed. Here, we enrolled three different patient cohorts and investigated expression of COL6A1, a key component of the extracellular matrix, at different stages and grades of BC, with a specific focus on T1HG BC. Materials and Methods: Samples from 298 BC patients were subjected to RNA sequencing and real-time PCR. Results: We found that T1HG BC and muscle invasive BC (MIBC) exhibited comparable expression of COL6A1, which was significantly higher than that by other NMIBC subtypes. In particular, T1HG patients who later progressed to MIBC had considerably higher expression of COL6A1 than Ta, T1 low-grade patients, and patients that did not progress, highlighting the aggressive nature and higher risk of progression associated with T1HG BC. Moreover, Cox and Kaplan-Meier survival analyses revealed a significant association between elevated expression of COL6A1 and poor progression-free survival of T1HG BC patients (multivariate Cox hazard ratio, 16.812; 95% confidence interval, 3.283-86.095; P=0.001 and P=0.0002 [log-rank test]). Conclusion: These findings suggest that COL6A1 may be a promising biomarker for risk stratification of T1HG BC, offering valuable insight into disease prognosis and guidance of personalized treatment decisions. Citation Format: Xuan-Mei Piao, Young Joon Byun, Chuang-Ming Zheng, Seon-Kyu Kim, Seong-Hwan Park, Kyungchan Min, Hansoo Park, Sungmin Moon, Kyeong Kim, Ho Won Kang, Won Tae Kim, Seok Joong Yun. COL6A1 expression as a potential prognostic biomarker for risk stratification of T1HG bladder cancer: Unveiling the aggressive nature of a distinct non-muscle invasive subtype [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 7648.

SMMF: a self-attention-based multi-parametric MRI feature fusion framework for the diagnosis of bladder cancer grading.

Multi-parametric magnetic resonance imaging (MP-MRI) may provide comprehensive information for graded diagnosis of bladder cancer (BCa). Nevertheless, existing methods ignore the complex correlation between these MRI sequences, failing to provide adequate information. Therefore, the main objective of this study is to enhance feature fusion and extract comprehensive features from MP-MRI using deep learning methods to achieve an accurate diagnosis of BCa grading. In this study, a self-attention-based MP-MRI feature fusion framework (SMMF) is proposed to enhance the performance of the model by extracting and fusing features of both T2-weighted imaging (T2WI) and dynamic contrast-enhanced imaging (DCE) sequences. A new multiscale attention (MA) model is designed to embed into the neural network (CNN) end to further extract rich features from T2WI and DCE. Finally, a self-attention feature fusion strategy (SAFF) was used to effectively capture and fuse the common and complementary features of patients' MP-MRIs. In a clinically collected sample of 138 BCa patients, the SMMF network demonstrated superior performance compared to the existing deep learning-based bladder cancer grading model, with accuracy, F1 value, and AUC values of 0.9488, 0.9426, and 0.9459, respectively. Our proposed SMMF framework combined with MP-MRI information can accurately predict the pathological grading of BCa and can better assist physicians in diagnosing BCa.

Comparing Clinical Efficacy of Different Bacillus Calmette-Guérin Strains in Patients With T1 High Grade Bladder Cancer.

This study aimed to compare the clinical efficacy of two different Bacillus Calmette-Guérin (BCG) strains, TICE strain (OncoTICE) and Connaught strain (ImmuCyst), as a first line intravesical instillation therapy in patients with T1 high grade bladder cancer. Patients with newly diagnosed T1 high-grade bladder cancer who underwent transurethral resection of bladder tumor (TURBT) followed by intravesical instillation therapy were enrolled. The effects of BCG strain on recurrence, progression, and side effects were analyzed using Kaplan-Meier and Cox proportional hazards models. Among 147 patients, 53 patients received Connaught strain and 94 patients received TICE strain. The completion rate of induction instillation was 92.45% in the Connaught group and 91.49% in the TICE group (p=1.00). The three-year recurrence-free survival rate was 71.7% in the Connaught group and 63.83% in the TICE group (p=0.33), whereas the three-year progression-free survival rate was 96.23% in the Connaught group and 89.36% in the TICE group (p=0.21). On Cox regression test, carcinoma in situ and ≥eight lesions were significant predictors for recurrence. No significant difference was observed in recurrence and progression between the two BCG regimens. The complication rates according to the Cleveland Clinic grading system showed no significant difference between the two groups (p=0.13). Both the Connaught and TICE strains of BCG demonstrated comparable three-year recurrence-free survival rates and three-year progression-free survival rates for T1 high grade bladder cancer, as well as comparable adverse events. Due to the global BCG shortage, further strain comparisons are essential for clinical validation.