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Cell-free DNA end characteristics enable accurate and sensitive cancer diagnosis.
- Source :
-
Cell reports methods [Cell Rep Methods] 2024 Oct 21; Vol. 4 (10), pp. 100877. Date of Electronic Publication: 2024 Oct 14. - Publication Year :
- 2024
-
Abstract
- The fragmentation patterns of cell-free DNA (cfDNA) in plasma can potentially be utilized as diagnostic biomarkers in liquid biopsy. However, our knowledge of this biological process and the information encoded in fragmentation patterns remains preliminary. Here, we investigated the cfDNA fragmentomic characteristics against nucleosome positioning patterns in hematopoietic cells. cfDNA molecules with ends located within nucleosomes were relatively shorter with altered end motif patterns, demonstrating the feasibility of enriching tumor-derived cfDNA in patients with cancer through the selection of molecules possessing such ends. We then developed three cfDNA fragmentomic metrics after end selection, which showed significant alterations in patients with cancer and enabled cancer diagnosis. By incorporating machine learning, we further built high-performance diagnostic models, which achieved an overall area under the curve of 0.95 and 85.1% sensitivity at 95% specificity. Hence, our investigations explored the end characteristics of cfDNA fragmentomics and their merits in building accurate and sensitive cancer diagnostic models.<br />Competing Interests: Declaration of interests Y.A., J.J., and K.S. have filed patent applications based on the method developed in this work.<br /> (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)
- Subjects :
- Humans
Machine Learning
Liquid Biopsy methods
Nucleosomes genetics
Nucleosomes metabolism
Male
Female
Sensitivity and Specificity
Middle Aged
Cell-Free Nucleic Acids blood
Cell-Free Nucleic Acids genetics
Neoplasms genetics
Neoplasms diagnosis
Neoplasms blood
Biomarkers, Tumor blood
Biomarkers, Tumor genetics
Subjects
Details
- Language :
- English
- ISSN :
- 2667-2375
- Volume :
- 4
- Issue :
- 10
- Database :
- MEDLINE
- Journal :
- Cell reports methods
- Publication Type :
- Academic Journal
- Accession number :
- 39406232
- Full Text :
- https://doi.org/10.1016/j.crmeth.2024.100877