| |  Online-Ressource |
|---|
| Verfasst von: | Lleshi, Ermira [VerfasserIn]  |
|---|
| | Milne-Clark, Toby [VerfasserIn] |
|---|
| | Lee Yu, Henson [VerfasserIn] |
|---|
| | Martin, Henno W. [VerfasserIn] |
|---|
| | Hanson, Robert [VerfasserIn] |
|---|
| | Lach, Radoslaw [VerfasserIn] |
|---|
| | Rossi, Sabrina H. [VerfasserIn] |
|---|
| | Riediger, Anja Lisa [VerfasserIn] |
|---|
| | Görtz, Magdalena [VerfasserIn] |
|---|
| | Sültmann, Holger [VerfasserIn] |
|---|
| | Flewitt, Andrew [VerfasserIn] |
|---|
| | Lynch, Andy G. [VerfasserIn] |
|---|
| | Gnanapragasam, Vincent J. [VerfasserIn] |
|---|
| | Massie, Charlie E. [VerfasserIn] |
|---|
| | Dev, Harveer S. [VerfasserIn] |
|---|
| Titel: | Prostate cancer detection through unbiased capture of methylated cell-free DNA |
|---|
| Verf.angabe: | Ermira Lleshi, Toby Milne-Clark, Henson Lee Yu, Henno W. Martin, Robert Hanson, Radoslaw Lach, Sabrina H. Rossi, Anja Lisa Riediger, Magdalena Görtz, Holger Sültmann, Andrew Flewitt, Andy G. Lynch, Vincent J. Gnanapragasam, Charlie E. Massie, and Harveer S. Dev |
|---|
| E-Jahr: | 2024 |
|---|
| Jahr: | 19 July 2024 |
|---|
| Umfang: | 17 S. |
|---|
| Illustrationen: | Illustrationen |
|---|
| Fussnoten: | Online verfügbar: 20. Juni 2024, Artikelversion: 4. Juli 2024 ; Gesehen am 03.01.2025 |
|---|
| Titel Quelle: | Enthalten in: iScience |
|---|
| Ort Quelle: | Amsterdam : Elsevier, 2018 |
|---|
| Jahr Quelle: | 2024 |
|---|
| Band/Heft Quelle: | 27(2024), 7 vom: Juli, Artikel-ID 110330, Seite 1-17 |
|---|
| ISSN Quelle: | 2589-0042 |
|---|
| Abstract: | Prostate cancer screening using prostate-specific antigen (PSA) has been shown to reduce mortality but with substantial overdiagnosis, leading to unnecessary biopsies. The identification of a highly specific biomarker using liquid biopsies, represents an unmet need in the diagnostic pathway for prostate cancer. In this study, we employed a method that enriches for methylated cell-free DNA fragments coupled with a machine learning algorithm which enabled the detection of metastatic and localized cancers with AUCs of 0.96 and 0.74, respectively. The model also detected 51.8% (14/27) of localized and 88.7% (79/89) of patients with metastatic cancer in an external dataset. Furthermore, we show that the differentially methylated regions reflect epigenetic and transcriptomic changes at the tissue level. Notably, these regions are significantly enriched for biologically relevant pathways associated with the regulation of cellular proliferation and TGF-beta signaling. This demonstrates the potential of circulating tumor DNA methylation for prostate cancer detection and prognostication. |
|---|
| DOI: | doi:10.1016/j.isci.2024.110330 |
|---|
| URL: | Bitte beachten Sie: Dies ist ein Bibliographieeintrag. Ein Volltextzugriff für Mitglieder der Universität besteht hier nur, falls für die entsprechende Zeitschrift/den entsprechenden Sammelband ein Abonnement besteht oder es sich um einen OpenAccess-Titel handelt.
kostenfrei: Volltext: https://doi.org/10.1016/j.isci.2024.110330 |
|---|
| | kostenfrei: Volltext: https://www.sciencedirect.com/science/article/pii/S2589004224015554 |
|---|
| | DOI: https://doi.org/10.1016/j.isci.2024.110330 |
|---|
| Datenträger: | Online-Ressource |
|---|
| Sprache: | eng |
|---|
| Sach-SW: | Cancer |
|---|
| | Machine learning |
|---|
| K10plus-PPN: | 1913491986 |
|---|
| Verknüpfungen: | → Zeitschrift |
|---|
Prostate cancer detection through unbiased capture of methylated cell-free DNA / Lleshi, Ermira [VerfasserIn]; 19 July 2024 (Online-Ressource)
