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.

Inclusion Criteria:

1. Histologically confirmed diagnosis of urothelial carcinoma of the bladder (any stage, including non-muscle invasive and muscle invasive).

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2. Availability of sufficient tumor tissue specimen (fresh frozen) for DNA extraction and mutation analysis.

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3. Age ≥ 18 years at time of diagnosis.

Exclusion Criteria:

1. History of other malignant tumors within the past 5 years, except adequately treated non-melanoma skin cancer or carcinoma in situ of the cervix.

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2. Inadequate quality or quantity of tumor tissue DNA for mutation panel analysis (e.g., severe DNA degradation, insufficient DNA yield).

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3. Pregnancy or breastfeeding.

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4. Serious uncontrolled intercurrent illness that would interfere with study follow-up or compliance, including but not limited to ongoing or active infection, symptomatic congestive heart failure, unstable angina pectoris, cardiac arrhythmia, or psychiatric illness/social situations that would limit compliance with study requirements.

This study will include adult patients aged 18 years or older with a histologically confirmed diagnosis of urothelial carcinoma of the bladder, including both non-muscle invasive bladder cancer and muscle invasive bladder cancer. Eligible participants must have sufficient fresh frozen tumor tissue samples available for DNA extraction and mutation analysis. Exclusion criteria include inadequate tumor tissue DNA quality for mutation analysis, pregnancy or breastfeeding, and serious uncontrolled intercurrent illnesses that may interfere with study participation. The study population will be representative of bladder cancer patients receiving standard clinical management, focusing on genetic mutation profiling for improved risk stratification and treatment prediction.

Protection of participant privacy and compliance with institutional ethics requirements will be ensured. The possibility of sharing de-identified individual participant data will be evaluated after study completion, taking into account the scope of informed consent, institutional policies, and the feasibility of establishing a secure data-sharing mechanism that safeguards participant confidentiality. Any future data sharing will be conducted under formal data use agreements and in accordance with applicable regulatory requirements.