Bladder cancer is a highly heterogeneous malignancy characterized by frequent genetic alterations that are closely associated with disease progression, recurrence risk, and treatment response. However, existing mutation detection approaches are often limited by high cost, complex workflows, or insufficient capacity for multiplex and low-frequency mutation analysis, which restricts their routine clinical application. The purpose of this study is to establish and clinically validate a multiplex mutation detection system for bladder cancer based on nucleic acid mass spectrometry. Using fresh tumor tissue and matched adjacent normal tissue samples collected from patients with bladder cancer, a targeted mutation panel comprising key functional mutations with demonstrated clinical relevance will be constructed. The matched normal tissues serve as germline references to enable accurate identification of somatic mutations. The analytical performance of the system, including sensitivity, specificity, and concordance with whole-genome sequencing, will be systematically evaluated. In addition, the clinical utility of the mutation panel in risk stratification and treatment decision support will be explored by comparing its predictive value with established clinical models and guideline-recommended tools. The ultimate goal is to develop a cost-effective, reproducible, and clinically applicable molecular testing strategy that can support precision diagnosis and individualized management of patients with bladder cancer.
Bladder cancer is a highly heterogeneous disease with complex genetic mutations that influence tumor behavior, treatment response, and patient outcomes. Current genetic testing methods often face limitations in simultaneously detecting multiple mutations with high sensitivity and low cost. This study aims to develop and clinically validate a novel multiplex mutation detection system for bladder cancer based on nucleic acid mass spectrometry. The study consists of two phases. In the first phase, a standardized detection panel targeting key bladder cancer-related genes and functional mutation sites will be established, selected based on mutation frequency, clinical significance, survival impact, and evidence from authoritative databases such as The Cancer Genome Atlas (TCGA), OncoKB, and ClinVar. The panel covers critical genes, including Fibroblast Growth Factor Receptor 3 (FGFR3), Tumor Protein P53 (TP53), and others involved in tumor progression, therapeutic response, and prognosis. In the second phase, the clinical utility of this system will be validated using 400 freshly collected bladder cancer tissue samples and paired adjacent normal tissue samples. This detection system offers several advantages: 1. High-throughput multiplexing - simultaneous detection of up to 30 mutation sites in a single run; 2. High sensitivity - capable of detecting low-frequency mutations (as low as 0.1% variant allele frequency); 3. Quantitative analysis - provides allele frequency information to assess tumor burden and monitor treatment response; 4. Cost-effectiveness and simplicity - lower cost and simpler workflow compared to next-generation sequencing, making it suitable for clinical implementation. The clinical value of this system will be rigorously evaluated by: 1. Comparing its risk stratification performance with established clinical tools, such as the European Organisation for Research and Treatment of Cancer (EORTC), European Association of Urology (EAU), and Vesical Imaging-Reporting and Data System (VI-RADS); 2. Assessing its treatment predictive value against current standards, such as the Spanish Bladder Cancer Group (CUETO) and immunohistochemical markers; 3. Validating its accuracy against whole-exome sequencing as the gold standard in paired samples of tumor and adjacent normal tissues. By providing a comprehensive, affordable, and clinically actionable mutation profiling tool, this study aims to improve precision risk stratification, guide individualized treatment decisions, and enable dynamic recurrence monitoring for bladder cancer patients. The ultimate goal is to establish a standardized molecular diagnostic framework that can be integrated into routine clinical practice.
Study Type
OBSERVATIONAL
Enrollment
400
This study uses a multiplex mutation detection system for bladder cancer based on nucleic acid mass spectrometry. The system is designed to identify genetic alterations in bladder cancer-related genes, including Fibroblast Growth Factor Receptor 3 (FGFR3), Tumor Protein P53 (TP53), and other relevant genes. The platform offers high-throughput, multiplex mutation detection with high analytical sensitivity and cost efficiency, suitable for potential clinical use. Tumor tissue samples will be prospectively collected from patients with bladder cancer who elect to undergo surgery. The study is observational, with no active intervention, therapeutic modification, or influence on clinical treatment decisions. Mutation status from tissue analysis will be evaluated for correlations with clinical outcomes, including recurrence, progression, and treatment response.
The Second Hospital of Lanzhou University
Lanzhou, Gansu, China
RECRUITINGSurvival Differences Between Mutated and Non-mutated Groups in Bladder Cancer Patients
This outcome measure aims to compare the survival rates between bladder cancer patients with mutations in key bladder cancer-related genes (as determined by the multiplex mutation detection panel) and those without mutations. The mutation status (any gene mutation versus no mutation) will be correlated with clinical outcomes, including recurrence-free survival (RFS), progression-free survival (PFS), and overall survival (OS), using Kaplan-Meier survival analysis. These survival metrics will be assessed to determine whether mutation status influences prognosis and to identify any significant survival differences between mutated and non-mutated groups.
Time frame: Survival will be assessed at post-surgical follow-up at 6 months, 1 year, 2 years, and 3 years, including recurrence, progression, and metastasis-free survival events over a 3-year period.
Development of Predictive Models for Post-surgical Recurrence, Progression, and Response to Intravesical Therapy
This secondary outcome measure focuses on identifying risk factors for post-surgical recurrence, progression, and response to intravesical therapy using a multivariable Cox proportional hazards regression analysis. Factors such as tumor stage, number of tumors, age, and mutation status will be included in the prediction model to assess the likelihood of recurrence and progression. The model will integrate the mutation panel to refine risk stratification and support clinical decision-making.
Time frame: The predictive model will be developed and evaluated during the 3-year follow-up period post-surgery, with data collected at key intervals: 6 months, 1 year, 2 year, and 3 years post-surgery.
Validation of Mutation Panel's Predictive Value in Risk Stratification Using Existing Clinical Models
This measure will assess the performance of the mutation panel in predicting patient outcomes compared to established clinical models, such as the European Association of Urology (EAU), the European Organisation for Research and Treatment of Cancer (EORTC), and the Spanish Urological Club for Oncological Treatment (CUETO). The mutation panel's predictive value will be compared with these models for risk stratification in different risk groups (extremely high, high, medium, low risk). The goal is to validate the effectiveness of the mutation panel as an additional tool for patient stratification and prediction of recurrence.
Time frame: Validation will occur after 3 years of patient follow-up, at the point of comparing the prediction models for their efficacy in risk stratification and recurrence prediction.
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