Simeon Springer1, Yuxuan Wang1, Marco Dal Molin2, David L Masica3, Yuchen Jiao1, Isaac Kinde1, Amanda Blackford4, Siva P Raman5, Christopher L Wolfgang6, Tyler Tomita7, Noushin Niknafs7, Christopher Douville7, Janine Ptak1, Lisa Dobbyn1, Peter J Allen8, David S Klimstra9, Mark A Schattner10, C Max Schmidt11, Michele Yip-Schneider12, Oscar W Cummings12, Randall E Brand13, Herbert J Zeh14, Aatur D Singhi15, Aldo Scarpa16, Roberto Salvia17, Giuseppe Malleo17, Giuseppe Zamboni18, Massimo Falconi19, Jin-Young Jang20, Sun-Whe Kim20, Wooil Kwon20, Seung-Mo Hong21, Ki-Byung Song22, Song Cheol Kim22, Niall Swan23, Jean Murphy23, Justin Geoghegan24, William Brugge25, Carlos Fernandez-Del Castillo26, Mari Mino-Kenudson27, Richard Schulick28, Barish H Edil28, Volkan Adsay29, Jorge Paulino30, Jeanin van Hooft31, Shinichi Yachida32, Satoshi Nara32, Nobuyoshi Hiraoka32, Kenji Yamao33, Susuma Hijioka33, Schalk van der Merwe34, Michael Goggins35, Marcia Irene Canto36, Nita Ahuja37, Kenzo Hirose37, Martin Makary37, Matthew J Weiss37, John Cameron37, Meredith Pittman2, James R Eshleman1, Luis A Diaz38, Nickolas Papadopoulos1, Kenneth W Kinzler1, Rachel Karchin39, Ralph H Hruban40, Bert Vogelstein1, Anne Marie Lennon41. 1. The Ludwig Center and Howard Hughes Medical Institute at the Sidney Kimmel Cancer Center, The Johns Hopkins University, Baltimore, Maryland; The Sol Goldman Pancreatic Cancer Research Center, The Johns Hopkins University, Baltimore, Maryland. 2. The Sol Goldman Pancreatic Cancer Research Center, The Johns Hopkins University, Baltimore, Maryland; Department of Pathology, The Johns Hopkins University, Baltimore, Maryland. 3. The Sol Goldman Pancreatic Cancer Research Center, The Johns Hopkins University, Baltimore, Maryland; Department of Biomedical Engineering, The Johns Hopkins University, Baltimore, Maryland; The Johns Hopkins Medical Institutions and the Institute for Computational Medicine, The Johns Hopkins University, Baltimore, Maryland. 4. Department of Biostatistics and Bioinformatics, The Johns Hopkins University, Baltimore, Maryland. 5. Department of Radiology, The Johns Hopkins University, Baltimore, Maryland. 6. The Sol Goldman Pancreatic Cancer Research Center, The Johns Hopkins University, Baltimore, Maryland; Department of Surgery, The Johns Hopkins University, Baltimore, Maryland; Department of Oncology, The Johns Hopkins University, Baltimore, Maryland. 7. Department of Biomedical Engineering, The Johns Hopkins University, Baltimore, Maryland; The Johns Hopkins Medical Institutions and the Institute for Computational Medicine, The Johns Hopkins University, Baltimore, Maryland. 8. Department of Surgery, Memorial Sloan-Kettering Cancer Center, New York, New York. 9. Department of Pathology, Memorial Sloan-Kettering Cancer Center, New York, New York. 10. Department of Gastroenterology, Memorial Sloan-Kettering Cancer Center, New York, New York. 11. Department of Surgery, University of Indiana, Bloomington, Indiana. 12. Department of Pathology, University of Indiana, Bloomington, Indiana. 13. Department of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania. 14. Department of Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania. 15. Department of Pathology, University of Pittsburgh, Pittsburgh, Pennsylvania. 16. ARC-Net Research Centre, Department of Pathology and Diagnostics, University and Hospital Trust of Verona, Verona, Italy; Department of Pathology, General Surgery B, University and Hospital Trust of Verona, Verona, Italy. 17. Department of Surgery, University and Hospital Trust of Verona, Verona, Italy. 18. Department of Pathology, General Surgery B, University and Hospital Trust of Verona, Verona, Italy; Department of Pathology, Ospedale Sacro Cuore-Don Calabraia, Negrar, Italy. 19. Division of Pancreatic Surgery, Department of Surgery, IRCCS San Raffaele Scientific Institute, Milan, Italy. 20. Department of Surgery and Cancer Research Institute, Seoul National University College of Medicine, Seoul, Korea. 21. Departments of Pathology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea. 22. Department of Hepatobiliary and Pancreas Surgery, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea. 23. Department of Histopathology, St Vincent's University Hospital, Dublin, Ireland. 24. Department of Surgery, St Vincent's University Hospital, Dublin, Ireland. 25. Department of Gastroenterology, Massachusetts General Hospital, Boston, Massachusetts. 26. Department of Surgery, Massachusetts General Hospital, Boston, Massachusetts. 27. Department of Histopathology, Massachusetts General Hospital, Boston, Massachusetts. 28. Department of Surgery, University of Colorado, Boulder, Colorado. 29. Department of Pathology, Emory University, Atlanta, Georgia. 30. Department of Pathology, Centro Hepatobiliopancreático e Transplantação, Hospital Curry Cabral, Lisbon, Portugal. 31. Department of Gastroenterology and Hepatology, Amsterdam Medical Center, The Netherlands. 32. Department of Hepatobiliary and Pancreatic Surgery, Pathology and Cancer Genomics, National Cancer Center Hospital and National Cancer Center Research Institute, Tokyo, Japan. 33. Department of Gastroenterology, Aichi Cancer Center Hospital, Nagoya, Japan. 34. Department of Hepatology, University Hospitals KU Leuven, Leuven, Belgium. 35. The Sol Goldman Pancreatic Cancer Research Center, The Johns Hopkins University, Baltimore, Maryland; Department of Oncology, The Johns Hopkins University, Baltimore, Maryland; Department of Medicine, The Johns Hopkins University, Baltimore, Maryland. 36. Department of Medicine, The Johns Hopkins University, Baltimore, Maryland. 37. Department of Surgery, The Johns Hopkins University, Baltimore, Maryland. 38. The Ludwig Center and Howard Hughes Medical Institute at the Sidney Kimmel Cancer Center, The Johns Hopkins University, Baltimore, Maryland; The Sol Goldman Pancreatic Cancer Research Center, The Johns Hopkins University, Baltimore, Maryland; Department of Surgery, The Johns Hopkins University, Baltimore, Maryland. 39. The Sol Goldman Pancreatic Cancer Research Center, The Johns Hopkins University, Baltimore, Maryland; Department of Biomedical Engineering, The Johns Hopkins University, Baltimore, Maryland; The Johns Hopkins Medical Institutions and the Institute for Computational Medicine, The Johns Hopkins University, Baltimore, Maryland; Department of Oncology, The Johns Hopkins University, Baltimore, Maryland. 40. The Ludwig Center and Howard Hughes Medical Institute at the Sidney Kimmel Cancer Center, The Johns Hopkins University, Baltimore, Maryland; The Sol Goldman Pancreatic Cancer Research Center, The Johns Hopkins University, Baltimore, Maryland; Department of Pathology, The Johns Hopkins University, Baltimore, Maryland; Department of Oncology, The Johns Hopkins University, Baltimore, Maryland. 41. The Sol Goldman Pancreatic Cancer Research Center, The Johns Hopkins University, Baltimore, Maryland; Department of Surgery, The Johns Hopkins University, Baltimore, Maryland; Department of Medicine, The Johns Hopkins University, Baltimore, Maryland. Electronic address: amlennon@jhmi.edu.
Abstract
BACKGROUND & AIMS: The management of pancreatic cysts poses challenges to both patients and their physicians. We investigated whether a combination of molecular markers and clinical information could improve the classification of pancreatic cysts and management of patients. METHODS: We performed a multi-center, retrospective study of 130 patients with resected pancreatic cystic neoplasms (12 serous cystadenomas, 10 solid pseudopapillary neoplasms, 12 mucinous cystic neoplasms, and 96 intraductal papillary mucinous neoplasms). Cyst fluid was analyzed to identify subtle mutations in genes known to be mutated in pancreatic cysts (BRAF, CDKN2A, CTNNB1, GNAS, KRAS, NRAS, PIK3CA, RNF43, SMAD4, TP53, and VHL); to identify loss of heterozygozity at CDKN2A, RNF43, SMAD4, TP53, and VHL tumor suppressor loci; and to identify aneuploidy. The analyses were performed using specialized technologies for implementing and interpreting massively parallel sequencing data acquisition. An algorithm was used to select markers that could classify cyst type and grade. The accuracy of the molecular markers was compared with that of clinical markers and a combination of molecular and clinical markers. RESULTS: We identified molecular markers and clinical features that classified cyst type with 90%-100% sensitivity and 92%-98% specificity. The molecular marker panel correctly identified 67 of the 74 patients who did not require surgery and could, therefore, reduce the number of unnecessary operations by 91%. CONCLUSIONS: We identified a panel of molecular markers and clinical features that show promise for the accurate classification of cystic neoplasms of the pancreas and identification of cysts that require surgery.
BACKGROUND & AIMS: The management of pancreatic cysts poses challenges to both patients and their physicians. We investigated whether a combination of molecular markers and clinical information could improve the classification of pancreatic cysts and management of patients. METHODS: We performed a multi-center, retrospective study of 130 patients with resected pancreatic cystic neoplasms (12 serous cystadenomas, 10 solid pseudopapillary neoplasms, 12 mucinous cystic neoplasms, and 96 intraductal papillary mucinous neoplasms). Cyst fluid was analyzed to identify subtle mutations in genes known to be mutated in pancreatic cysts (BRAF, CDKN2A, CTNNB1, GNAS, KRAS, NRAS, PIK3CA, RNF43, SMAD4, TP53, and VHL); to identify loss of heterozygozity at CDKN2A, RNF43, SMAD4, TP53, and VHL tumor suppressor loci; and to identify aneuploidy. The analyses were performed using specialized technologies for implementing and interpreting massively parallel sequencing data acquisition. An algorithm was used to select markers that could classify cyst type and grade. The accuracy of the molecular markers was compared with that of clinical markers and a combination of molecular and clinical markers. RESULTS: We identified molecular markers and clinical features that classified cyst type with 90%-100% sensitivity and 92%-98% specificity. The molecular marker panel correctly identified 67 of the 74 patients who did not require surgery and could, therefore, reduce the number of unnecessary operations by 91%. CONCLUSIONS: We identified a panel of molecular markers and clinical features that show promise for the accurate classification of cystic neoplasms of the pancreas and identification of cysts that require surgery.
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