A Prospective, Multi-centre, Single-blinded Study of UCAD for Diagnosing Benign or Malignant Gallbladder Diseases and Follow-up
Overview
- Phase
- Not Applicable
- Intervention
- Not specified
- Conditions
- Gallbladder Cancer
- Sponsor
- Xinhua Hospital, Shanghai Jiao Tong University School of Medicine
- Enrollment
- 1
- Locations
- 1
- Primary Endpoint
- UCAD can be used as a diagnostic technology for gallbladder cancer with the sensitivity more than 90%
- Status
- Active, not recruiting
- Last Updated
- 2 years ago
Overview
Brief Summary
Copy number variation(CNV) refers to ongoing chromosome segregation errors throughout consecutive cell divisions. CNV is a hallmark of human cancer, and it is associated with poor prognosis, metastasis, and therapeutic resistance. Analyzing CNV of the DNA extracted from bile samples in gallbladder seems a promising method for diagnosing, monitoring, and predicting the prognosis of patients with gallbladder cancer. CNV can be assessed using experimental techniques such as bulk DNA sequencing, fluorescence in situ hybridization (FISH), or conventional karyotyping. However, these techniques are either time-consuming or non-specific. The investigators here intend to study whether a new method named Ultrasensitive Chromosomal Aneuploidy Detection (UCAD), which is based on low-coverage whole-genome sequencing, can be used to analyze CNV thus helping diagnose gallbladder cancer and assessing follow-up.
Investigators
Eligibility Criteria
Inclusion Criteria
- •Patients diagnosed with gallbladder disease and planned to undergo surgery.
- •Male or female patients aged \>= 18 years.
- •Participants signed informed consent form.
Exclusion Criteria
- •Participants had other tumor expect gallbladder cancer
Outcomes
Primary Outcomes
UCAD can be used as a diagnostic technology for gallbladder cancer with the sensitivity more than 90%
Time Frame: 2025
Ultrasensitive chromosomal aneuploidy detection (UCAD) uses low-coverage whole-genome sequencing technology to detect DNA chromosomal instability in samples. By detecting DNA extracted from patients' bile and blood, bioinformatics can be used to analyze the differences in CNV between benign and malignant gallbladder diseases, and a prediction model for gallbladder cancer.