Prostate cancer detection through unbiased capture of methylated cell-free DNA

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, Harveer S Dev*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Article number110330
Number of pages17
JournaliScience
Volume27
Issue number7
Early online date20 Jun 2024
DOIs
Publication statusE-pub ahead of print - 20 Jun 2024

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