Cyst Fluid Biosignature to Predict Intraductal Papillary Mucinous Neoplasms of the Pancreas with High Malignant Potential

Abstract Background Current standard-of-care technologies such as imaging and cyst fluid analysis are unable to consistently distinguish intraductal papillary mucinous neoplasms of the pancreas (IPMN) at high-risk of pancreatic cancer from low-risk IPMN. The objective was to create a single-platform assay to identify IPMN that are at high-risk for malignant progression. Study Design Building on the Verona International Consensus Conference BD-IPMN biomarker study, specific protein, cytokine, mucin, DNA, and miRNA cyst fluid targets were identified for creation of a q-PCR based assay as we have previously published. This included mRNA markers: ERBB2, GNAS, IL1b, KRAS, MUCs1, 2, 4, 5AC, 7, PGE2R, PTGER2, PTGES2, PTGES1, TP63; miRNA targets: miRs 101, 106b, 10a, 142, 155, 17, 18a, 21, 217, 24, 30a, 342, 532, 92a, and 99b; and GNAS and KRAS mutational analysis. A multi-institutional international collaborative contributed IPMN cyst fluid samples to validate this platform. Cyst fluid gene expression levels were normalized, z-transformed, and utilized in classification and regression analysis by a support vector machine (SVM) training algorithm. Results From fifty-nine IPMN patient cyst fluids, principal component analysis confirmed no institutional bias/clustering. Lasso-penalized logistic regression with binary classification and 5-fold cross validation utilized AUC as evaluation criteria to create the optimal signature to discriminate IPMN into low-risk (low/moderate dysplasia) or high-risk (high-grade dysplasia/invasive cancer). The most predictive signature was achieved with IL1β, MUC4, and PTGES2 to accurately discriminate high from low-risk cysts with up to an AUC of 0.86, p=0.002. Conclusions We have identified a single-platform PCR-based assay of cyst fluid to accurately predict IPMN with high-malignant potential for further studies.