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contrary, the NPV was confirmed to have high performance being 85% and 93%, for DRE and FV,
respectively. Both studies showed a significant increase in the area under the curve (AUC) values of the
Receiver Operating Characteristic (ROC) curves when compared to PSA. This finding demonstrates the
higher specificity and sensitivity of the number of methylated markers in urinary cfDNA compared to PSA
level. Notably, HOXD3 and HOXA7, both encoding members of the family of transcription factors, GPR62,
coding a signaling factor of the phosphoinositol pathway, and KLK10, coding a serine protease implicated
in carcinogenesis, were found in all PCa samples; however, HOXD8rc, encoding a member of the family of
transcription factors, CXCL14, encoding a protein involved in inflammatory and immunomodulatory
functions, SLC16A5rc, encoding a member of a family of carrier, and GRASP, encoding a scaffold protein
involved in phosphoinositide pathway, were more frequently present in highly aggressive PCa, thus
suggesting for the last ones a prognostic value for these markers.

Moreover, both studies evaluated the correlation between the number of methylated markers or the average
of methylation with the risk score University of California San Francisco Cancer of the Prostate Risk
Assessment. Overall, the results suggested a high performance of the methylation test to identify patients at
risk of PCa and the possibility to use these markers and their global status of methylation to stratify patients
for PCa aggressiveness. The 32-panel of biomarkers has improved the precision for patient stratification by
giving the indication for biopsy in those patients who did not reach the threshold in the 19-panel. Notably,
the possibility to determine the risk stratification was assigned to urine cfDNA after DRE, because of the
possibility to recover more cancer cells and to avoid dilution and degradation of DNA derived from urine at
FV specimens that may cause a higher sampling error. However, the authors underline that in 58 patients,
both DRE and FV samples were equivalent in the analysis results, thus suggesting that FV remains a useful
and simple source for cfDNA. These markers matched with the age of patients and others anamnestic
parameters could improve the sensitivity/specificity of the test. A future dedicated clinical trial will be able
to find the clinical correlations necessary for the validations of these markers.

Nekrasov et al. collected 31 urine samples from PCa patients and 33 samples in healthy patients as disease-
[6]
free control. The methylation status of 17 cancer‐associated genes was analyzed using a methylation-specific
polymerase chain reaction. They reported 13 genes with increased methylation frequency in patients with
PCa compared with the control group. In conclusion, the authors reported a 6‐gene panel (APC2, CDH1,
FOXP1, LRRC3B, WNT7A, and ZIC4) able to identify PCa with 78% sensitivity and 100% specificity.

Connel et al. , reported a multivariable risk model integrating urinary cell DNA methylation and cfRNA
[7]
data able to detect significant PCa. In their analysis, 207 post-digital rectal examination urine samples were
collected within a Movember cohort (GAP1 urine biomarker). ExoMeth was the name of the model created
for this study. Clinical variables (age and PSA) were integrated with methylation and transcript targets. The
model was subsequently tested and applied to a final cohort of 197 with available data. With an odds ratio
(OR) of 2.04 (95%CI: 1.78-2.35) per 0.1 ExoMeth increase, they were able to increase the likelihood high-
grade of the disease being detected on prostate biopsy. In the future, this can potentially avoid unnecessary
biopsies in patients on AS or to guide the necessity of mpMRI in patients with a clinically suspected PCa.

[8]
Similarly, Zhao et al. combined the urinary DNA methylation with cf-mRNA biomarkers in a series of 103
CaP patients on AS. The aim of the study was the identification of patients at risk of reclassification. Three
marker panels (miR-24, miR-30c and CRIP3 methylation) were identified in the post-DRE urinary sediment
using a qPCR-based MethyLight assay. With a NPV of 90% and an OR of 2.17 (95%CI: 1.22-3.85), the
authors were able to identify patients with a PCa progression. CRIP3 methylation was found to be a
significant predictor of AS reclassification (OR = 1.079, 95%CI: 1.013-1.15).