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Sequencing of cfDNA methylation and proteomic analysis of two sets of capsular fluid samples

cfDNA methylation sequencing and proteome analysis

Kaixuan Wang

Kaixuan Wang, MD

Shiyu Li

Chengye Pan

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.

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.

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

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

cfDNA methylation data and proteome analysis data

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).

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.

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.

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.

Study title	NCT ID	Conditions	Interventions	Eligibility	Organization	Link
Construction of Molecular Diagnostic Marker Model for Pancreatic Cystic Tumors Based on Pancreatic Cystic Fluid Samples	NCT05737953	Pancreatic Neop... DNA Methylation Proteome	cfDNA methylati...	18 Years -	Changhai Hospital
Construction of Molecular Diagnostic Marker Model for Pancreatic Cystic Tumors Based on Pancreatic Cystic Fluid Samples	NCT05737953	Pancreatic Neop... DNA Methylation Proteome	cfDNA methylati...	18 Years -	Changhai Hospital

Spots Global Cancer Trial Database for cfdna methylation sequencing and proteome analysis