ArticleJournal of experimental & clinical cancer research : CR2024
Detection and characterization of pancreatic and biliary tract cancers using cell-free DNA fragmentomics.
Article in Journal of experimental & clinical cancer research : CR, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Value of Machine Learning Models for Cell-Free DNA-Based Multi-Cancer Early Detection: A Systematic Review and Meta-Analysis.Technology in cancer research & treatmentPooled it
- Tumor-agnostic detection of circulating tumor DNA in patients with advanced pancreatic cancer using targeted DNA methylation sequencing and cell-free DNA fragmentomics.Molecular oncology · 2025Article
- Leveraging liquid biopsy to uncover resistance mechanisms and guide personalized immunotherapy.Translational oncology · 2025Review
- Enhanced anticancer efficacy of aluminum-curcumin complex compared to curcumin in colorectal cancer cells.Naunyn-Schmiedeberg's archives of pharmacology · 2025Article
- Chromosomal instability by low-coverage whole-genome sequencing assay predicts prognosis in bladder cancer patients underwent radical cystectomy.BMC medical genomics · 2025Article
- EM-DeepSD: A Deep Neural Network Model Based on Cell-Free DNA End-Motif Signal Decomposition for Cancer Diagnosis.Diagnostics (Basel, Switzerland) · 2025Article
- Blood-based biomarkers in pancreatic ductal adenocarcinoma: developments over the last decade and what holds for the future- a review.Frontiers in oncology · 2025Review
- The role of circulating tumor DNA in gynecological cancer management.Frontiers in oncology · 2025Review
- Liquid Biopsy in the Clinical Management of Cancers.International journal of molecular sciences · 2024Review
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Authors and funding
21 authors.
Funding
Abstract
backgroundPlasma cell-free DNA (cfDNA) fragmentomics has demonstrated significant differentiation power between cancer patients and healthy individuals, but little is known in pancreatic and biliary tract cancers. The aim of this study is to characterize the cfDNA fragmentomics in biliopancreatic cancers and develop an accurate method for cancer detection.
methodsOne hundred forty-seven patients with biliopancreatic cancers and 71 non-cancer volunteers were enrolled, including 55 patients with cholangiocarcinoma, 30 with gallbladder cancer, and 62 with pancreatic cancer. Low-coverage whole-genome sequencing (median coverage: 2.9 ×) was performed on plasma cfDNA. Three cfDNA fragmentomic features, including fragment size, end motif and nucleosome footprint, were subjected to construct a stacked machine learning model for cancer detection. Integration of carbohydrate antigen 19-9 (CA19-9) was explored to improve model performance.
resultsThe stacked model presented robust performance for cancer detection (area under curve (AUC) of 0.978 in the training cohort, and AUC of 0.941 in the validation cohort), and remained consistent even when using extremely low-coverage sequencing depth of 0.5 × (AUC: 0.905). Besides, our method could also help differentiate biliopancreatic cancer subtypes. By integrating the stacked model and CA19-9 to generate the final detection model, a high accuracy in distinguishing biliopancreatic cancers from non-cancer samples with an AUC of 0.995 was achieved.
conclusionsOur model demonstrated ultrasensitivity of plasma cfDNA fragementomics in detecting biliopancreatic cancers, fulfilling the unmet accuracy of widely-used serum biomarker CA19-9, and provided an affordable way for accurate noninvasive biliopancreatic cancer screening in clinical practice.
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