A novel microfluidic-based assay to determine high-risk pancreatic cysts for surgery utilizing pancreatic cyst fluid: an international multicenter study

Abstract

Presenter: Ajay Maker MD | University of California San Francisco Background: Pancreatic cysts are increasingly diagnosed in the general population. We previously reported that the majority of cysts resected in the country are low risk lesions on final pathology, despite multiple established clinical guidelines. Thus, selecting which patients harbor a cyst at high-risk of occult malignancy or malignant degeneration for operative resection remains a clinical dilemma. The aim of the current study is to develop a high-throughout molecular diagnostic platform to identify pancreatic cysts at high risk of malignancy or high-grade dysplasia. Methods: Pancreatic cyst fluid from an international multi-center patient cohort were analyzed on a newly constructed microfluidic TaqMan low density array that was customized with our gene target panel of five miRNAs and seven mRNAs. Signatures were validated utilizing a machine learning random forest model for the optimal accuracy to determine high-risk cysts (high-grade dysplasia or invasive cancer) from low risk cysts for operative intervention. Results: Of 358 pancreatic cyst fluids analyzed, 157 cysts were intraductal papillary mucinous neoplasms (IPMNs), 62 were mucinous cystic neoplasms (MCNs), and the remainder were of various non-mucinous histologies. Of the 219 mucinous cysts, 60 (27%) were found to harbor high-grade dysplasia (HGD) or invasive cancer on final pathological examination. The models were established and then internally validated revealing a maximal accuracy of 87% to determine benign from potentially malignant cysts with an out-of-bag error of 8-12%. Further, the assay performed with an accuracy of 81% to identify high-risk from low-risk mucinous lesions (IPMN+MCN) for operative intervention. Conclusion: A high-throughput, cost-effective microfluidics-based molecular diagnostic assay has been developed that identifies high-risk cystic lesions of the pancreas for surgical evaluation. In this large, international, multi-center study, robust validation sets were performed. Performance of the biosignatures are currently being enhanced with clinical and radiographic features.