Construction of Molecular Diagnostic Marker Model for Pancreatic Cystic Tumors Based on Pancreatic Cystic Fluid Samples

Pancreatic Neoplasms Clinical Trial

Official title:

Construction of Molecular Diagnostic Marker Models for Pancreatic Cystic Tumors Based on cfDNA Methylation Sequencing and Proteomic Analysis of Pancreatic Cystic Fluid Samples

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT05737953
• Other study ID #: WKX2023-02
• Status: Recruiting
• Start date: July 13, 2022
• Est. completion date: June 30, 2024

Study information

• Verified date: February 2023
• Source: Changhai Hospital
• Contact: Kaixuan Wang
• Phone: 021-31166666
• Email: lizfish[@]126.com
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

The goal of this observational study is to test in patients with cystic tumor of pancreas. The main questions it aims to answer are:

Screening of molecular diagnostic markers for pancreatic cystic tumors by cfDNA methylation sequencing of pancreatic cystic fluid and proteomic assays to distinguish benign from malignant and mucinous/non-mucinous, correlate with pathological features, and find molecular features associated with the degree of malignancy.

Participants will Provide post-operative cyst fluid specimens.

Description:

Patients with pancreatic cystic tumors were divided into control, mucinous tumor and non-mucinous tumor groups, and cfDNA molecules and protein molecules that were significantly altered between different groups were found by cfDNA methylation sequencing of pancreatic cystic fluid and proteomic detection techniques. Multi-omics analysis was performed to construct a more efficient molecular diagnostic marker model. Correlating models with pathological features to find molecular features associated with the degree of malignancy.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 100
• Est. completion date: June 30, 2024
• Est. primary completion date: December 31, 2023
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years and older

Eligibility

Inclusion Criteria:

• Subjects are = 18 years old, regardless of gender;

• Preoperative imaging examination (EUS, CT, MRI) diagnosed cystic mass of pancreas and suspected cystic tumor;

• Subjects voluntarily accepted radical resection of pancreatic cystic tumors;

• Subjects or family members voluntarily sign the informed consent form for clinical research.

Exclusion Criteria:

• The excised sample does not contain cystic components, or the cystic fluid cannot be collected;

• Receive tumor-related treatment (radiotherapy, chemotherapy, immunotherapy, etc.) before operation;

• Receive antibiotic treatment within 1 week before operation;

• Subjects refused to accept radical resection of pancreatic cystic tumor, or had any situation that they could not accept radical resection of pancreatic cystic tumor;

• The subjects or their families refused to sign the informed consent form for clinical research.

Related Conditions & MeSH terms

• DNA Methylation
• Pancreatic Neoplasms

Intervention

Diagnostic Test:
• cfDNA methylation sequencing and proteome analysis
Sequencing of cfDNA methylation and proteomic analysis of two sets of capsular fluid samples

Locations

Country	Name	City	State
China	Changhai Hospital	Shanghai	Shanghai

Sponsors (1)

Lead Sponsor	Collaborator
Zhaoshen Li

Country where clinical trial is conducted

China, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Types and concentrations of cfDNA and proteins contained in the vesicular fluid	Identification of protein and circulating gene methylation species in cyst fluid and quantification of their concentrations using mass spectrometry. Characterize cfDNA methylation and proteomics of cyst fluid in patients with pancreatic cystic neoplasm (PCN).	2023-11-31
Secondary	Establishment of a diagnostic model for cystic tumors of the pancreas	A machine learning approach was used to further screen for characteristically methylated cfDNA and proteins in PCN patients.Establishment of a diagnostic model for pancreatic cystic tumors.	2023-11-31
Secondary	Establishing a model for the identification of mucus and non-mucus	A machine learning approach was used to further screen for characteristically methylated cfDNA and proteins in PCN patients.To establish a model for the identification of mucinous and non-mucinous.	2023-11-31
Secondary	Development of a progressive benign malignancy prediction model	A machine learning approach was used to further screen for characteristically methylated cfDNA and proteins in PCN patients.Development of a progression benign malignancy prediction model.	2023-11-31