Although intraductal papillary mucinous neoplasms (IPMNs) represent potential precursors of pancreatic cancer, IPMNs with invasive cancer are rare. Based on current risk factors for malignancy, overtreatment (surgery) of benign IPMNs remains a critical issue, with its associated risk of postoperative and long-term complications. Identification of biomarkers that could predict malignancy in IPMNs is an unmet clinical need. Environmental, lifestyle, genetics and metabolic factors may play a role in IPMNs carcinogenesis. Aims of the study are: 1) to analyze exposome, somatic/germline genetic variability, metabolomics and transcriptome profile in order to identify new biomarkers; 2) to use nonparametric epidemiologic approaches and machine learning algorithms to compute a progression score to offer clinicians an innovative tool towards the goal of a personalized medicine approach. In order to perform all the analysis we will set up the Invasive Cyst biomarker detection (INCITE) consortium, between the participant centers in order to collectively enroll an adequate number of patients to fulfill the previous aims. The project is designed as an observational cross-sectional multicenter study with additional procedures. The analysis will be conducted on biological samples collected at a single time point. Some samples (500 patients: 160 surgical, 340 under surveillance) are already available in the consortium, having been collected in previous studies, while additional 300 (100 surgical and 200 under surveillance) patients will be prospectively enrolled during the first 12 months of the study. The sample collection will take place during outpatient visit/EUS procedure for the surveillance cohort, while in the surgical cohort all the material will be retrieved during the surgery. The patients samples will be divided in two cohorts, the first will be a discovery cohort and the second one a validation cohort. The first cohort will consist in patients already collected. The validation cohort will include patients enrolled prospectively during the first year of the study.
Age range
18 Years
Sex
ALL
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Analyzing exposome, metabolomics and transcriptome profile
Timeframe: All procedures on the patients will be carried out during their hospital stay for surgical patients and during the EUS procedure for the surveillance cohort.