DNA-methylation signature accurately differentiates pancreatic cancer from chronic pancreatitis in tissue and plasma

• Verfasst von: Wu, Yenan [VerfasserIn]
• Verfasst von: Seufert, Isabelle [VerfasserIn]
• Verfasst von: Al-Shaheri, Fawaz [VerfasserIn]
• Verfasst von: Kurilov, Roman [VerfasserIn]
• Verfasst von: Bauer, Andrea [VerfasserIn]
• Verfasst von: Manoochehri, Mehdi [VerfasserIn]
• Verfasst von: Moskalev, Evgeny A. [VerfasserIn]
• Verfasst von: Brors, Benedikt [VerfasserIn]
• Verfasst von: Tjaden, Christin [VerfasserIn]
• Verfasst von: Giese, Nathalia [VerfasserIn]
• Verfasst von: Hackert, Thilo [VerfasserIn]
• Verfasst von: Büchler, Markus W. [VerfasserIn]
• Verfasst von: Hoheisel, Jörg D. [VerfasserIn]
• Titel: DNA-methylation signature accurately differentiates pancreatic cancer from chronic pancreatitis in tissue and plasma
• Verf.angabe: Yenan Wu, Isabelle Seufert, Fawaz N. Al-Shaheri, Roman Kurilov, Andrea S. Bauer, Mehdi Manoochehri, Evgeny A. Moskalev, Benedikt Brors, Christin Tjaden, Nathalia A. Giese, Thilo Hackert, Markus W. Büchler, Jörg D. Hoheisel
• E-Jahr: 2023
• Jahr: 14 September 2023
• Umfang: 10 S.
• Illustrationen: Illustrationen
• Fussnoten: Gesehen am 14.11.2023
• Titel Quelle: Enthalten in: Gut
• Ort Quelle: London : BMJ Publishing Group, 1960
• Jahr Quelle: 2023
• Band/Heft Quelle: 72(2023), 12, Seite 2344-2353
• ISSN Quelle: 1468-3288
• DOI: doi:10.1136/gutjnl-2023-330155
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: chronic pancreatitis
• Sach-SW: pancreatic cancer
• K10plus-PPN: 187020803X

Abstract

Objective Pancreatic ductal adenocarcinoma (PDAC) is a lethal malignancy. Differentiation from chronic pancreatitis (CP) is currently inaccurate in about one-third of cases. Misdiagnoses in both directions, however, have severe consequences for patients. We set out to identify molecular markers for a clear distinction between PDAC and CP. - Design Genome-wide variations of DNA-methylation, messenger RNA and microRNA level as well as combinations thereof were analysed in 345 tissue samples for marker identification. To improve diagnostic performance, we established a random-forest machine-learning approach. Results were validated on another 48 samples and further corroborated in 16 liquid biopsy samples. - Results Machine-learning succeeded in defining markers to differentiate between patients with PDAC and CP, while low-dimensional embedding and cluster analysis failed to do so. DNA-methylation yielded the best diagnostic accuracy by far, dwarfing the importance of transcript levels. Identified changes were confirmed with data taken from public repositories and validated in independent sample sets. A signature of six DNA-methylation sites in a CpG-island of the protein kinase C beta type gene achieved a validated diagnostic accuracy of 100% in tissue and in circulating free DNA isolated from patient plasma. - Conclusion The success of machine-learning to identify an effective marker signature documents the power of this approach. The high diagnostic accuracy of discriminating PDAC from CP could have tremendous consequences for treatment success, once the result from still a limited number of liquid biopsy samples would be confirmed in a larger cohort of patients with suspected pancreatic cancer.