Abstract
BackgroundThe application of advanced imaging technologies for identifying pancreatic cysts has become widespread. However, accurately differentiating between low-grade dysplasia (LGD), high-grade dysplasia (HGD), and invasive intraductal papillary mucinous neoplasms (IPMNs) remains a diagnostic challenge with current biomarkers, necessitating the development of novel biomarkers that can distinguish IPMN malignancy.MethodsCyst fluid samples were collected from nine IPMN patients (3 LGD, 3 HGD, and 3 invasive IPMN) during their pancreatectomies. An integrated proteomics approach that combines filter-aided sample preparation, stage tip-based high-pH fractionation, and high-resolution MS was applied to acquire in-depth proteomic data of pancreatic cyst fluid and discover marker candidates for IPMN malignancy. Biological processes of differentially expressed proteins that are related to pancreatic cysts and aggressive malignancy were analyzed using bioinformatics tools such as gene ontology analysis and Ingenuity pathway analysis. In order to confirm the validity of the marker candidates, 19 cyst fluid samples were analyzed by western blot.ResultsA dataset of 2992 proteins was constructed from pancreatic cyst fluid samples. A subsequent analysis found 2963 identified proteins in individual samples, 2837 of which were quantifiable. Differentially expressed proteins between histological grades of IPMN were associated with pancreatic diseases and malignancy according to ingenuity pathway analysis. Eighteen biomarker candidates that were differentially expressed across IPMN histological grades were discovered—7 DEPs that were upregulated and 11 that were downregulated in more malignant grades. HOOK1 and PTPN6 were validated by western blot in an independent cohort, the results of which were consistent with our proteomic data.ConclusionsThis study demonstrates that novel biomarker candidates for IPMN malignancy can be discovered through proteomic analysis of pancreatic cyst fluid.
Highlights
The application of advanced imaging technologies for identifying pancreatic cysts has become widespread
Clinical sample characterization Pancreatic cyst fluid samples from nine patients were classified into three groups: low-grade dysplasia (LGD) (n = 3), high-grade dysplasia (HGD) (n = 3), and invasive Intraductal papillary mucinous neoplasm (IPMN) (n = 3)
Our samples were consistent with several publications that have reported that malignant cysts tend to be larger, as evidenced by our invasive IPMN samples (6.63 ± 3.74 cm) being twice as large as LGD (2.93 ± 0.54 cm) and HGD (2.50 ± 0.41 cm) samples on average [5, 56,57,58,59]
Summary
The application of advanced imaging technologies for identifying pancreatic cysts has become widespread. Accurately differentiating between low-grade dysplasia (LGD), high-grade dysplasia (HGD), and invasive intraductal papillary mucinous neoplasms (IPMNs) remains a diagnostic challenge with current biomarkers, necessitating the development of novel biomarkers that can distinguish IPMN malignancy. Intraductal papillary mucinous neoplasms (IPMNs) are precancerous lesions that grow in the pancreatic ducts and are characterized by papillary growth of the ductal epithelium. IPMN is classified as low-grade dysplasia (LGD), intermediate-grade dysplasia (IGD), high-grade dysplasia (HGD), and invasive IPMN. According to the official guidelines for managing pancreatic IPMN, only patients with HGD or invasive IPMN require surgery, because they are at higher risk of their disease developing into cancer [5]. Milder forms of IPMN can be managed with active surveillance and do not warrant surgical intervention. Current methods for assessing the histological grades of IPMNs are unreliable, and as a result, patients with milder IPMN are often subjected to unnecessary operations [6,7,8,9,10]
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