1. A Combined DNA/RNA-based Next-Generation Sequencing Platform to Improve the Classification of Pancreatic Cysts and Early Detection of Pancreatic Cancer Arising From Pancreatic Cysts.
- Author
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Nikiforova MN, Wald AI, Spagnolo DM, Melan MA, Grupillo M, Lai YT, Brand RE, O'Broin-Lennon AM, McGrath K, Park WG, Pfau PR, Polanco PM, Kubiliun N, DeWitt J, Easler JJ, Dam A, Mok SR, Wallace MB, Kumbhari V, Boone BA, Marsh W, Thakkar S, Fairley KJ, Afghani E, Bhat Y, Ramrakhiani S, Nasr J, Skef W, Thiruvengadam NR, Khalid A, Fasanella K, Chennat J, Das R, Singh H, Sarkaria S, Slivka A, Gabbert C, Sawas T, Tielleman T, Vanderveldt HD, Tavakkoli A, Smith LM, Smith K, Bell PD, Hruban RH, Paniccia A, Zureikat A, Lee KK, Ongchin M, Zeh H, Minter R, He J, Nikiforov YE, and Singhi AD
- Subjects
- Humans, RNA, Early Detection of Cancer, DNA, High-Throughput Nucleotide Sequencing, Pancreatic Cyst diagnosis, Pancreatic Cyst genetics, Pancreatic Cyst pathology, Pancreatic Neoplasms diagnosis, Pancreatic Neoplasms genetics, Pancreatic Neoplasms metabolism
- Abstract
Objective: We report the development and validation of a combined DNA/RNA next-generation sequencing (NGS) platform to improve the evaluation of pancreatic cysts., Background and Aims: Despite a multidisciplinary approach, pancreatic cyst classification, such as a cystic precursor neoplasm, and the detection of high-grade dysplasia and early adenocarcinoma (advanced neoplasia) can be challenging. NGS of preoperative pancreatic cyst fluid improves the clinical evaluation of pancreatic cysts, but the recent identification of novel genomic alterations necessitates the creation of a comprehensive panel and the development of a genomic classifier to integrate the complex molecular results., Methods: An updated and unique 74-gene DNA/RNA-targeted NGS panel (PancreaSeq Genomic Classifier) was created to evaluate 5 classes of genomic alterations to include gene mutations (e.g., KRAS, GNAS, etc.), gene fusions and gene expression. Further, CEA mRNA ( CEACAM5 ) was integrated into the assay using RT-qPCR. Separate multi-institutional cohorts for training (n=108) and validation (n=77) were tested, and diagnostic performance was compared to clinical, imaging, cytopathologic, and guideline data., Results: Upon creation of a genomic classifier system, PancreaSeq GC yielded a 95% sensitivity and 100% specificity for a cystic precursor neoplasm, and the sensitivity and specificity for advanced neoplasia were 82% and 100%, respectively. Associated symptoms, cyst size, duct dilatation, a mural nodule, increasing cyst size, and malignant cytopathology had lower sensitivities (41-59%) and lower specificities (56-96%) for advanced neoplasia. This test also increased the sensitivity of current pancreatic cyst guidelines (IAP/Fukuoka and AGA) by >10% and maintained their inherent specificity., Conclusions: PancreaSeq GC was not only accurate in predicting pancreatic cyst type and advanced neoplasia but also improved the sensitivity of current pancreatic cyst guidelines., Competing Interests: A.D.S. has received an honorarium from Foundation Medicine Inc. M.N.N. and Y.E.N. own intellectual property related to the PancreaSeq technology and receive royalties from University of Pittsburgh. R.H.H. has the potential to receive royalty payments from Thrive Earlier Detection for the GNAS invention in an arrangement reviewed and approved by the Johns Hopkins University in accordance with its conflict-of-interest policies. The remaining authors report no conflicts of interest., (Copyright © 2023 The Author(s). Published by Wolters Kluwer Health, Inc.)
- Published
- 2023
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