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Next-generation sequencing (NGS) of pancreatic cyst fluid is a useful adjunct in the assessment of patients with pancreatic cyst. However, previous studies have been retrospective or single institutional experiences. The aim of this study was to prospectively evaluate NGS on a multi-institutional cohort of patients with pancreatic cyst in real time. The performance of a 22-gene NGS panel (PancreaSeq) was first retrospectively confirmed and then within a 2-year timeframe, PancreaSeq testing was prospectively used to evaluate endoscopic ultrasound–guided fine-needle aspiration pancreatic cyst fluid from 31 institutions. PancreaSeq results were correlated with endoscopic ultrasound findings, ancillary studies, current pancreatic cyst guidelines, follow-up, and expanded testing (Oncomine) of postoperative specimens. Among 1933 PCs prospectively tested, 1887 (98%) specimens from 1832 patients were satisfactory for PancreaSeq testing. Follow-up was available for 1216 (66%) patients (median, 23 months). Based on 251 (21%) patients with surgical pathology, mitogen-activated protein kinase/ GNAS mutations had 90% sensitivity and 100% specificity for a mucinous cyst (positive predictive value [PPV], 100%; negative predictive value [NPV], 77%). On exclusion of low-level variants, the combination of mitogen-activated protein kinase/ GNAS and TP53/SMAD4/CTNNB1/ mammalian target of rapamycin alterations had 88% sensitivity and 98% specificity for advanced neoplasia (PPV, 97%; NPV, 93%). Inclusion of cytopathologic evaluation to PancreaSeq testing improved the sensitivity to 93% and maintained a high specificity of 95% (PPV, 92%; NPV, 95%). In comparison, other modalities and current pancreatic cyst guidelines, such as the American Gastroenterology Association and International Association of Pancreatology/Fukuoka guidelines, show inferior diagnostic performance. The sensitivities and specificities of VHL and MEN1 /loss of heterozygosity alterations were 71% and 100% for serous cystadenomas (PPV, 100%; NPV, 98%), and 68% and 98% for pancreatic neuroendocrine tumors (PPV, 85%; NPV, 95%), respectively. On follow-up, serous cystadenomas with TP53 / TERT mutations exhibited interval growth, whereas pancreatic neuroendocrine tumors with loss of heterozygosity of ≥3 genes tended to have distant metastasis. None of the 965 patients who did not undergo surgery developed malignancy. Postoperative Oncomine testing identified mucinous cysts with BRAF fusions and ERBB2 amplification, and advanced neoplasia with CDKN2A alterations. PancreaSeq was not only sensitive and specific for various pancreatic cyst types and advanced neoplasia arising from mucinous cysts, but also reveals the diversity of genomic alterations seen in pancreatic cysts and their clinical significance. ▪ [ABSTRACT FROM AUTHOR]

Background: Pancreatic cysts are incidentally detected in up to 13% of patients undergoing radiographic imaging. Of the most frequently encountered types, mucin-producing (mucinous) pancreatic cystic lesions may develop into pancreatic cancer, while nonmucinous ones have little or no malignant potential. Accurate preoperative diagnosis is critical for optimal management, but has been difficult to achieve, resulting in unnecessary major surgery. Here, we aim to develop an algorithm based on biomarker risk scores to improve risk stratification.Study Design: Patients undergoing surgery and/or surveillance for a pancreatic cystic lesion, with diagnostic imaging and banked pancreatic cyst fluid, were enrolled in the study after informed consent (n = 163 surgical, 67 surveillance). Cyst fluid biomarkers with high specificity for distinguishing nonmucinous from mucinous pancreatic cysts (vascular endothelial growth factor [VEGF], glucose, carcinoembryonic antigen [CEA], amylase, cytology, and DNA mutation) were selected. Biomarker risk scores were used to design an algorithm to predict preoperative diagnosis. Performance was tested using surgical (retrospective) and surveillance (prospective) cohorts.Results: In the surgical cohort, the biomarker algorithm outperformed the preoperative clinical diagnosis in correctly predicting the final pathologic diagnosis (91% vs 73%; p < 0.000001). Specifically, nonmucinous serous cystic neoplasms (SCN) and mucinous cystic neoplasms (MCN) were correctly classified more frequently by the algorithm than clinical diagnosis (96% vs 30%; p < 0.000008 and 92% vs 69%; p = 0.04, respectively). In the surveillance cohort, the algorithm predicted a preoperative diagnosis with high confidence based on a high biomarker score and/or consistency with imaging from ≥1 follow-up visits.Conclusions: A biomarker risk score-based algorithm was able to correctly classify pancreatic cysts preoperatively. Importantly, this tool may improve initial and dynamic risk stratification, reducing overdiagnosis and underdiagnosis. [ABSTRACT FROM AUTHOR]