Urinary DNA Methylation Profiling Improves Discrimination of Prostate Cancer Across PSA-Defined Risk Strata.

Area of Science:

• Oncology
• Genetics
• Biomarker Discovery

Background:

• Prostate-specific antigen (PSA) testing is crucial for prostate cancer (PCa) screening but suffers from low specificity, leading to unnecessary biopsies.
• Benign prostate conditions can elevate PSA levels, complicating accurate PCa diagnosis and patient management.

Purpose of the Study:

• To evaluate if combining DNA methylation signatures with PSA metrics can improve the discrimination between PCa and non-PCa cases.
• To assess the diagnostic performance of novel methylation markers in urine samples.

Main Methods:

• Targeted bisulfite sequencing of 74 CpG sites across 9 genes in urine sediment from 194 patients (89 PCa, 105 non-PCa).
• Patients were stratified using total PSA (tPSA) and free-to-total PSA ratio (%fPSA).
• Machine learning models (Random Forest, SVM, KNN, Bayesian) were developed and validated using identified methylation markers.

Main Results:

• PSA-based stratification alone resulted in a diagnostic "gray zone" for 26.80% of patients.
• Twenty CpG sites demonstrated significant differential methylation (p < 0.01) between PCa and non-PCa.
• Machine learning models incorporating methylation markers achieved high diagnostic accuracy (AUC > 0.95) and specificity (100%) with KNN, maintaining high sensitivity (>80%).

Conclusions:

• Urine-based DNA methylation profiling significantly enhances PCa diagnostic accuracy beyond conventional PSA testing.
• This approach shows particular promise for improving diagnosis in patients within the PSA "gray zone".
• Further validation in larger, independent cohorts is recommended to confirm clinical utility.