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.
iScience. 2024 Jun 20*** epublish ***
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
Early Cancer Institute, Department of Oncology, University of Cambridge, Cambridge CB2 0XZ, UK., University Hospital Heidelberg, 69120 Heidelberg, Germany., Division of Cancer Genome Research, German Cancer Research Center (DKFZ), National Center for Tumor Diseases (NCT), 69120 Heidelberg, Germany., Department of Engineering, University of Cambridge, Cambridge, UK., School of Mathematics and Statistics, University of St Andrews, St Andrews KY16 9SS, UK., Department of Surgery, University of Cambridge, Addenbrooke's Hospital Site, Cambridge, UK.