Multiplex Mutation Detection Using Mass Spectrometry in Bladder Cancer

February 20, 2026 updated by: Zhilong Dong

Comprehensive Analysis of the Key Mutation Spectrum in Bladder Cancer: Establishment and Clinical Validation of a Multiplex Mutation Detection System Based on Nucleic Acid Mass Spectrometry

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.

Study Overview

Detailed Description

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 (Estimated)

400

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Locations

    • Gansu
      • Lanzhou, Gansu, China, 730030
        • Recruiting
        • The Second Hospital of Lanzhou University
        • Contact:

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Sampling Method

Probability Sample

Study Population

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.

Description

Inclusion Criteria:

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

    -

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

    -

  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.

    -

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

    -

  3. Pregnancy or breastfeeding.

    -

  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.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
NMIBC (Non-Muscle Invasive Bladder Cancer) Study Group
This cohort includes patients diagnosed with non-muscle invasive bladder cancer. Participants are categorized according to post-operative recurrence and progression status, as well as response to intravesical therapy (recurrence versus no recurrence; response versus non-response). Survival differences between mutation-positive and mutation-negative groups will be assessed using Kaplan-Meier survival analysis. Predictive models for post-surgical recurrence, progression, and treatment response will be developed using multivariable Cox proportional hazards regression analysis. Model performance will be validated in 30% of participants and compared with established risk models from the European Association of Urology and the European Organisation for Research and Treatment of Cancer.
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.
MIBC (Muscle Invasive Bladder Cancer) Study Group
This cohort includes patients diagnosed with muscle invasive bladder cancer. Participants are categorized according to recurrence after adjuvant therapy and the presence or absence of distant metastasis. Survival differences between mutation-positive and mutation-negative groups will be assessed using Kaplan-Meier survival analysis. A predictive model for recurrence and distant metastasis following adjuvant therapy will be developed using multivariable Cox proportional hazards regression analysis. Model performance will be validated in the remaining 30% of participants. Predictive accuracy will be compared with existing clinical assessment methods, including clinicopathological characteristics, single-gene mutation markers, and immunohistochemical biomarkers.
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.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Survival Differences Between Mutated and Non-mutated Groups in Bladder Cancer Patients
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.
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.
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.

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Development of Predictive Models for Post-surgical Recurrence, Progression, and Response to Intravesical Therapy
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.
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.
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
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.
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.
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.

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Investigators

  • Principal Investigator: Zhilong Dong, Doctor of Medicine, Lanzhou University Second Hospital

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Estimated)

February 25, 2026

Primary Completion (Estimated)

July 1, 2028

Study Completion (Estimated)

July 1, 2028

Study Registration Dates

First Submitted

February 14, 2026

First Submitted That Met QC Criteria

February 14, 2026

First Posted (Actual)

February 20, 2026

Study Record Updates

Last Update Posted (Actual)

February 24, 2026

Last Update Submitted That Met QC Criteria

February 20, 2026

Last Verified

February 1, 2026

More Information

Terms related to this study

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

UNDECIDED

IPD Plan Description

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.

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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