The goal of the multicentric and interdisciplinary IMAGene project is to pursue early diagnosis for Pancreatic Cancers in high-risk asymptomatic subject groups, by developing and validating a comprehensive cancer risk prediction algorithm (CRPA) as a clinical support tool to calculate a personalized risk profile. The study is a longitudinal, non-randomized exploratory clinical study. A total of 170 asymptomatic first-degree relatives of PC patients.
The study is a longitudinal, non-randomized exploratory clinical study. A total of 170 asymptomatic first-degree relatives of PC patients. The study population consists of 170 first (1st) degree healthy/asymptomatic relatives of patients with exocrine pancreatic cancer, where the patient satisfies one OR more of the following conditions: * was diagnosed with pancreatobiliary cancer \<50 years of age; * was diagnosed with pancreatobiliary cancer \>50 years of age AND personal history of any solid cancers. The CRPA will be assessed in 170 first degree relatives of PC patients, in whom the development of pancreatic cysts will be assessed by WB-MRI at baseline and at one year.
Study Type
INTERVENTIONAL
Allocation
NA
Purpose
DIAGNOSTIC
Masking
NONE
Enrollment
170
Early diagnosis for Pancreatic Cancers in high-risk asymptomatic subject groups by developing and validating a comprehensive cancer risk prediction algorithm (CRPA) as a clinical support tool to calculate a personalized risk profile
Toulouse University Hospital
Toulouse, France
European Institute of Oncology
Milan, Italy
Oncological Institute "Prof. Dr. Ion Chiricuta"
Cluj-Napoca, Romania
Catalan Institute of Oncology
Barcelona, Spain
Observation of a two or three-fold enrichment in early detection of suspicious pancreatic lesion using the CRPA algorithm
Develop/calibrate/validate a comprehensive cancer risk prediction algorithm (CRPA) and observe a two or three-fold enrichment in early detection of suspicious pancreatic lesion in our sample of HR individuals (incidence about 24%), stratified through the application of the Machine Learning algorithm, the CRPA.
Time frame: 5 years
Identification of one or more abnormal methylation changes present in blood cells of participants with suspicious lesions versus methylation profiles of participants with no identified lesions
Provide evidence that the implementation of epigenetic biomarkers profiles in CRPA leads to a significant improvement of accuracy of cancer risk prediction models. This endpoint will be reached with the identification of a methylation profile referred to as a risk signature (defined as one or more abnormal methylation changes present in blood cells of participants) by analyzing blood cells methylation profiling data from participants with suspicious lesions vs methylation profiles of participants with no identified lesions;
Time frame: 5 years
Validation of igenetic biomarker testing in liquid biopsy followed by radiological exam as early cancer diagnostic tool
Validate whether the use of epigenetic biomarker testing in liquid biopsy followed by radiological exam can be an early cancer diagnostic tools for PC in High Risk (HR) subjects
Time frame: 5 years
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