Analysing DNA methylation and transcriptomic signatures to predict prostate cancer recurrence risk.

ABSTRACT: Prostate cancer (PCa) remains a significant global health challenge, with approximately 1.6 million new cases and 366,000 deaths annually. Despite high survival rates for localized prostate cancer, recurrence poses a substantial risk due to inherent biological factors and residual disease. Early detection and intervention are essential for enhancing patient outcomes and reducing mortality. However, traditional diagnostics such as PSA tests, digital rectal examinations, and biopsies often lack specificity resulting in overdiagnosis. There is a pressing need for novel biomarkers to enhance precision medicine approaches for PCa. This study employs a machine learning approach to identify DNA methylation and RNA expression biomarkers predictive of PCa recurrence using datasets from The Cancer G

SUBMITTER: Aldakheel FM 

PROVIDER: S-EPMC11787142 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature