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dc.contributor.authorCalina, Teodor G.
dc.contributor.authorPerez, Eilís
dc.contributor.authorGrafenhorst, Elena
dc.contributor.authorBenhamida, Jamal
dc.contributor.authorSchallenberg, Simon
dc.contributor.authorPopescu, Adrian
dc.contributor.authorKoch, Ines
dc.contributor.authorJanik, Tobias
dc.contributor.authorChen, BaoQing
dc.contributor.authorIhlow, Jana
dc.contributor.authorRoessler, Stephanie
dc.contributor.authorGoeppert, Benjamin
dc.contributor.authorSinn, Bruno
dc.contributor.authorBahra, Marcus
dc.contributor.authorCalin, George A.
dc.contributor.authorTaube, Eliane T.
dc.contributor.authorPelzer, Uwe
dc.contributor.authorNeumann, Christopher C. M.
dc.contributor.authorHorst, David
dc.contributor.authorKnutsen, Erik
dc.contributor.authorCapper, David
dc.contributor.authorDragomir, Mihnea P.
dc.date.accessioned2024-12-12T14:32:38Z
dc.date.available2024-12-12T14:32:38Z
dc.date.issued2024-11-10
dc.description.abstractBackground - We have recently constructed a DNA methylation classifier that can discriminate between pancreatic ductal adenocarcinoma (PAAD) liver metastasis and intrahepatic cholangiocarcinoma (iCCA) with high accuracy (PAAD-iCCA-Classifier). PAAD is one of the leading causes of cancer of unknown primary and diagnosis is based on exclusion of other malignancies. Therefore, our focus was to investigate whether the PAAD-iCCA-Classifier can be used to diagnose PAAD metastases from other sites.<p> <p>Methods - For this scope, the anomaly detection filter of the initial classifier was expanded by 8 additional mimicker carcinomas, amounting to a total of 10 carcinomas in the negative class. We validated the updated version of the classifier on a validation set, which consisted of a biological cohort (n = 3579) and a technical one (n = 15). We then assessed the performance of the classifier on a test set, which included a positive control cohort of 16 PAAD metastases from various sites and a cohort of 124 negative control samples consisting of 96 breast cancer metastases from 18 anatomical sites and 28 carcinoma metastases to the brain.<p> <p>Results - The updated PAAD-iCCA-Classifier achieved 98.21% accuracy on the biological validation samples, and on the technical validation ones it reached 100%. The classifier also correctly identified 15/16 (93.75%) metastases of the positive control as PAAD, and on the negative control, it correctly classified 122/124 samples (98.39%) for a 97.85% overall accuracy on the test set. We used this DNA methylation dataset to explore the organotropism of PAAD metastases and observed that PAAD liver metastases are distinct from PAAD peritoneal carcinomatosis and primary PAAD, and are characterized by specific copy number alterations and hypomethylation of enhancers involved in epithelial-mesenchymal-transition.<p> <p>Conclusions - The updated PAAD-iCCA-Classifier (available at https://classifier.tgc-research.de/) can accurately classify PAAD samples from various metastatic sites and it can serve as a diagnostic aid.en_US
dc.identifier.citationCalina, Perez, Grafenhorst, Benhamida, Schallenberg, Popescu, Koch, Janik, Chen, Ihlow, Roessler, Goeppert, Sinn, Bahra, Calin, Taube, Pelzer, Neumann, Horst, Knutsen, Capper, Dragomir. DNA methylation classifier to diagnose pancreatic ductal adenocarcinoma metastases from different anatomical sites. Clinical Epigenetics. 2024;16(1)
dc.identifier.cristinIDFRIDAID 2327086
dc.identifier.doi10.1186/s13148-024-01768-x
dc.identifier.issn1868-7075
dc.identifier.issn1868-7083
dc.identifier.urihttps://hdl.handle.net/10037/35971
dc.language.isoengen_US
dc.publisherSpringer Natureen_US
dc.relation.journalClinical Epigenetics
dc.rights.holderCopyright 2024 The Author(s)en_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0en_US
dc.rightsAttribution 4.0 International (CC BY 4.0)en_US
dc.titleDNA methylation classifier to diagnose pancreatic ductal adenocarcinoma metastases from different anatomical sitesen_US
dc.type.versionpublishedVersionen_US
dc.typeJournal articleen_US
dc.typeTidsskriftartikkelen_US
dc.typePeer revieweden_US


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Attribution 4.0 International (CC BY 4.0)
Except where otherwise noted, this item's license is described as Attribution 4.0 International (CC BY 4.0)