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Cyst Fluid Biosignature to Predict Intraductal Papillary Mucinous Neoplasms of the Pancreas with High Malignant Potential.
BACKGROUND: Current standard-of-care technologies, such as imaging and cyst fluid analysis, are unable to consistently distinguish intraductal papillary mucinous neoplasms (IPMNs) of the pancreas at high risk of pancreatic cancer from low-risk IPMNs. The objective was to create a single-platform assay to identify IPMNs that are at high risk for malignant progression.
STUDY DESIGN: Building on the Verona International Consensus Conference branch duct IPMN biomarker review, additional protein, cytokine, mucin, DNA, and microRNA cyst fluid targets were identified for creation of a quantitative polymerase chain reaction-based assay. This included messenger RNA markers: ERBB2, GNAS, interleukin 1β, KRAS, MUCs1, 2, 4, 5AC, 7, prostaglandin E2R, PTGER2, prostaglandin E synthase 2, prostaglandin E synthase 1, TP63; microRNA 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 used in classification and regression analysis by a support vector machine training algorithm.
RESULTS: From cyst fluids of 59 IPMN patients, principal component analysis confirmed no institutional bias/clustering. Lasso (least absolute shrinkage and selection operator)-penalized logistic regression with binary classification and 5-fold cross-validation used area under the curve as the evaluation criterion to create the optimal signature to discriminate IPMNs as low risk (low/moderate dysplasia) or high risk (high-grade dysplasia/invasive cancer). The most predictive signature was achieved with interleukin 1β, MUC4, and prostaglandin E synthase 2 to accurately discriminate high-risk cysts from low-risk cysts with an area under the curve of up to 0.86 (p = 0.002).
CONCLUSIONS: We have identified a single-platform polymerase chain reaction-based assay of cyst fluid to accurately predict IPMNs with high malignant potential for additional studies.
STUDY DESIGN: Building on the Verona International Consensus Conference branch duct IPMN biomarker review, additional protein, cytokine, mucin, DNA, and microRNA cyst fluid targets were identified for creation of a quantitative polymerase chain reaction-based assay. This included messenger RNA markers: ERBB2, GNAS, interleukin 1β, KRAS, MUCs1, 2, 4, 5AC, 7, prostaglandin E2R, PTGER2, prostaglandin E synthase 2, prostaglandin E synthase 1, TP63; microRNA 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 used in classification and regression analysis by a support vector machine training algorithm.
RESULTS: From cyst fluids of 59 IPMN patients, principal component analysis confirmed no institutional bias/clustering. Lasso (least absolute shrinkage and selection operator)-penalized logistic regression with binary classification and 5-fold cross-validation used area under the curve as the evaluation criterion to create the optimal signature to discriminate IPMNs as low risk (low/moderate dysplasia) or high risk (high-grade dysplasia/invasive cancer). The most predictive signature was achieved with interleukin 1β, MUC4, and prostaglandin E synthase 2 to accurately discriminate high-risk cysts from low-risk cysts with an area under the curve of up to 0.86 (p = 0.002).
CONCLUSIONS: We have identified a single-platform polymerase chain reaction-based assay of cyst fluid to accurately predict IPMNs with high malignant potential for additional studies.
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