ArticleMolecular cancer2024
Discrimination of pancreato-biliary cancer and pancreatitis patients by non-invasive liquid biopsy.
Article in Molecular cancer, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 22 citations in OpenAlex.
- Machine learning and artificial intelligence in liquid biopsy-based early detection of pancreatic cancer: a scoping review.BJC reports · 2026Review
- Recent Advances in Non-Invasive Blood Markers for Intraductal Papillary Mucinous Neoplasm Grading.Oncology research · 2026Review
- Review
- Exosomal CD40, CD25, and Serum CA19-9 as Combinatory Novel Liquid Biopsy Biomarker for the Diagnosis and Prognosis of Patients with Pancreatic Ductal Adenocarcinoma.International journal of molecular sciences · 2025Article
- Lessons (to be) learned from liquid biopsies: assessment of circulating cells and cell-free DNA in cancer and pregnancy-acquired microchimerism.Seminars in immunopathology · 2025Review
- Blood-based biomarkers in pancreatic ductal adenocarcinoma: developments over the last decade and what holds for the future- a review.Frontiers in oncology · 2025Review
- Detection and characterization of pancreatic and biliary tract cancers using cell-free DNA fragmentomics.Journal of experimental & clinical cancer research : CR · 2024Article
- Development of liquid biopsy in detection and screening of pancreatic cancer.Frontiers in oncology · 2024Review
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Authors and funding
17 authors at 4 institutions in 2 countries.
Funding
Abstract
backgroundCurrent diagnostics for the detection of pancreato-biliary cancers (PBCs) need to be optimized. We therefore propose that methylated cell-free DNA (cfDNA) derived from non-invasive liquid biopsies serves as a novel biomarker with the ability to discriminate pancreato-biliary cancers from non-cancer pancreatitis patients.
methodsDifferentially methylated regions (DMRs) from plasma cfDNA between PBCs, pancreatitis and clinical control samples conditions were identified by next-generation sequencing after enrichment using methyl-binding domains and database searches to generate a discriminatory panel for a hybridization and capture assay with subsequent targeted high throughput sequencing.
resultsThe hybridization and capture panel, covering around 74 kb in total, was applied to sequence a cohort of 25 PBCs, 25 pancreatitis patients, 25 clinical controls, and seven cases of Intraductal Papillary Mucinous Neoplasia (IPMN). An unbiased machine learning approach identified the 50 most discriminatory methylation markers for the discrimination of PBC from pancreatitis and controls resulting in an AUROC of 0.85 and 0.88 for a training (n = 45) and a validation (n = 37) data set, respectively. The panel was also able to distinguish high grade from low grade IPMN samples.
conclusionsWe present a proof of concept for a methylation biomarker panel with better performance and improved discriminatory power than the current clinical marker CA19-9 for the discrimination of pancreato-biliary cancers from non-cancerous pancreatitis patients and clinical controls. This workflow might be used in future diagnostics for the detection of precancerous lesions, e.g. the identification of high grade IPMNs vs. low grade IPMNs.
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