










































This is an open access article under the terms of a license that permits non-commercial use, provided the original work is properly cited.  
© 2021 The Authors. Société Internationale d'Urologie Journal, published by the Société Internationale d'Urologie, Canada.

Urine Biomarkers for Prostate Cancer  
Diagnosis and Progression

Jeremy Clark,1 Rachel Hurst,1 Mark Simon Winterbone,1 Hardev Pandha,2 Antoinette Perry,3 Sophie 
McGrath,4,5 Richard Morgan,6 Adele E. Connor,3,7 Asia C. Jordan,3,7 Deirdre Winrow,3,7 Colin Cooper1

1 Norwich Medical School, University of East Anglia, Norwich Research Park, Norwich, United Kingdom 2 Professor of Medical Oncology, Faculty of Health and Medical 
Sciences, University of Surrey, Guildford, United Kingdom 3 Cancer Biology and Therapeutics Laboratory, School of Biomolecular and Biomedical Science, Conway 
Institute, University College Dublin, Ireland4  The Royal Marsden NHS Foundation Trust, Downs Road, Sutton, United Kingdom 5 Kingston Hospital NHS Foundation Trust, 
Galsworthy Road, Kingston-upon-Thames, United Kingdom 6 The Institute of Cancer Therapeutics, School of Pharmacy and Medical Sciences, University of Bradford, 
United Kingdom 7 School of Biology and Environmental Science, University College Dublin, Ireland  

Abstract

Prostate cancer (PCa) can be highly heterogeneous and multifocal, and accurate assessment of the volume, grade, 
and stage of PCa in situ is not a simple task. Urine has been investigated as a source of PCa biomarkers for over 70 
years, and there is now strong evidence that analysis of urine could provide more accurate diagnosis and a better risk 
stratification that could aid clinical decisions regarding disease surveillance and treatment. Urine diagnostics is a 
developing area, moving towards multi-omic biomarker integration for improved diagnostic performance. Urine 
tests developed by strong collaborations between scientists and clinicians have the potential to provide targeted and 
meaningful data that can guide treatment and improve men’s lives.

1. Introduction: Urine as a Source of Prostate Cancer Biomarkers

Prostate cancers (PCa) can be highly heterogeneous[1,2] and multifocal[2,3]. Accurate assessment of the volume, 
grade, and stage of prostate cancer in situ is not a simple task. Significant amounts of biopsy results can be upgraded or 
downgraded on prostatectomy analysis[4,5]. Multi-parametric MRI has improved enormously but has inter-operator 
inconsistencies[6], can miss significant cancers (Gleason > 4), and has a false positive rate of around 50%[7]. Urine 
has been investigated as a source of PCa biomarkers for over 70 years[8–10], and there is now strong evidence that 
urine analysis could provide a better assessment of disease diagnosis and prognosis that could aid clinical decisions 
regarding disease surveillance and treatment.

Prostatic secretions make up 30% of the volume of semen, and its composition can reflect pre-neoplastic or 
malignant changes[11]. The prostate is continually secreting, and these secretions flow from all areas of the prostate 
where PCa is found[12,13]. These secretions flow into the urethra whence they are flushed out of the body on 
urination[12]. When a cancer is present, tiny bits of tumour (cells, extracellular vesicles, and molecules) can also be 
carried in the secretions and these can be detected in urine[8,9]. Urine is advantageous as a source for liquid biopsy 
because it can be collected at low cost, is completely non-invasively, and has the potential to sample all secretory areas 
of the prostate at the same time. 

Key Words Competing Interests Article Information

Urine, biomarkers, prostate cancer Dr Clark and Professor Cooper have a patent 
GB1905111.9 issued in relation to the PUR 
(prostate urine risk) signatures discussed in 
this review. Professor Pandha and Professor 
Morgan have a patent issued for EN2 as a 
diagnostic marker. Dr Perry reports grants 
from Enterprise Ireland, Movember, Prostate 
Cancer Foundation, and Science Foundation 
Ireland during the conduct of the study. Dr 
Perry has a patent EP15831140.7 issued, and 
a patent 15/538928 pending. The remaining 
authors declare no competing interests.

Received on January 5, 2021 
Accepted on March 14, 2021

Soc Int Urol J.2021;2(3):159–170

DOI: https://doi 10.48083/SAWC9585 

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mailto:Jeremy.clark%40uea.ac.uk?subject=SIUJ
https://doi 10.48083/SAWC9585
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Urine samples have been analysed for promising 
cancer biomarkers in the form of cells, DNA, RNA, 
proteins, and metabolites. The relative proportions of 
biomarkers vary between whole urine, cell sediment, 
and supernatant which will be discussed separately. 
The majority of the research presented here has been 
performed on small cohorts from which limited 
conclusions can be made. The current state and future 
directions of urine analysis for prostate cancer diagnosis 
and prognosis are described herein. Table 1 provides an 
overview of the biomarkers discussed in this review.

2. Analysis of Whole Unfractionated Urine
Elevated levels of C3, C4, and transferrin proteins were 
found in prostatic fluid from PCa patients by Greyhack 
et al. in 1979[11], and in 1982 PCA-1 (prostate cancer 
antigen-1) protein was detected in urine from PCa 
patients but not in urine from age-matched non-PCa 
men[10]. However, it was not until 2002, when PCA3 
(prostate cancer antigen 3) RNA transcripts in urine 
were found that the potential for urine molecular 
diagnostics in clinical urological practice was realised. 

PCA3 is a prostate-specific long non-coding RNA 
overexpressed in ≥ 95% of prostate cancers that was first 
investigated as a urinary PCa marker by de Kok et al. in 
2002[14]. In a multicentre validation study[15,16] it was 
shown to predict Gleason score ≥ 7 cancer with an 80% 
negative predictive value. 

The FDA-approved Progensa PCA3 urine test was 
approved in 2012. Whole urine for this test is collected 
after prostate massage with the intent of predicting 
the likelihood of detecting PCa on repeat prostate 
biopsy[17,18]. The PCA3 score is calculated as the ratio 
of 2 mRNAs: PCA3/KLK3 x1000[17]. A threshold score 
of 35 provided a sensitivity and specificity of 58% and 
72%, respectively for presence of significant PCa on 
rebiopsy[19,20]. Investigations into a direct relationship 
between the PCA3 test and PCa volume or Gleason 
pattern have been unclear, yielding opposing results 

in different studies[14,21,22]. Metanalysis by Luo et al. 
found great heterogeneity among published data sets 
with PCA3 test sensitivity ranging from 47% to 82%[23]. 
The reasons for this were unknown, and they may 
underlie the poor uptake of the PCA3 test in the clinic. 
However, the PCA3 test is important as it was first to 
demonstrate that collection, transport, and centralised 
laboratory analysis of urine was a viable means of PCa 
biomarker analysis.

The TMPRSS2:ERG fusion gene is found in ~50% 
of PCa foci; however, as TMPRSS2:ERG-positive 
and negative tumour foci can be found in individual 
prostates[24], a TMPRSS2:ERG may be present in ~70% 
of PCa-radical prostatectomies[25], making its detection 
more useful than was initially apparent. Urine transcript 
levels of TMPRSS2:ERG correlated with ERG expression 
in PCa tissue and aided prediction of PCa by PCA3. The 
Mi-Prostate score (MiPS) combined detection of PCA3, 
TMPRSS2:ERG and serum PSA levels[26], providing 
significantly improved detection of any PCa and 
Gleason score (Gs) ≥ 7 on biopsy compared with PSA 
or the prostate cancer prevention trial risk calculator 
(PCPT-RC)[27]. 

Further gene transcripts have been investigated for 
additional improvements. van Neste et al. combined 
RT-PCR data from HOXC4, HOXC6, TDRD1, DLX1, 
KLK3, and PCA3 with clinical information from 2  
independent mu lticentre prospective collections 
(n = 906)[28].An optimal model (SelectMDX) required 
only a combination of PSAD, DRE result, HOXC6 
and DLX1, with KLK3 used for relative biomarker 
quantitation[28]. SelectMDX had a strong net benefit, 
potentially reducing unnecessary biopsies over the PCA3 
test, PSA and the PCPT-RC with a validation cohort 
AUROC of 0.9 for detection of Gs ≥ 7 cancer. SelectMDX 
has been reported to be able to reduce diagnostic costs 
in a study covering 5 European countries, the degree 
of benefit varying with the amount of overtreatment in 
each country’s clinical procedures[29].

3. Analysis of Urine Cell Sediment
3.1 PCa cells in urine
Urine can contain many different cell types, including 
bladder urothelial cells, squamous cells, seminal vesicle 
cells, prostate cells, red blood cells, and white blood 
cells[30], up to 80% of which can originate from the 
prostate[31,32]. Prostate cancer cells were first detected 
in urine samples by microscopy in 1947[9] and are 
associated with higher risk and advanced cancers[31]. 
The relative proportions of the different cell types in 
urine can alter with a DRE[31,33] or disease state such 
as prostatitis[34], prostate/urinary tract problems, or 
PCa[30,35]. 

Abbreviations 
DRE digital rectal examination
EVs extracellular vesicles 
Gs Gleason score 
MiPS Mi-Prostate score
PCa prostate cancer 
PCA3 prostate cancer antigen 3
PCPT-RC prostate cancer prevention trial risk calculator 
PUR prostate urine risk 
VIP vasoactive intestinal peptide 

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Urine cell pellet staining for AMACR, Nk x3.1, 
nucleolin, ERG, and prostein[35,36] can detect prostate 
cancer cells but overall lacked sensitivity compared with 
biopsy[36]. Two f luorescent approaches have shown 
promise: OligoFISH probes to detect alterations in 
chromosomes 7, 16, 18, and 20 has been shown to have 
an 80% specificity compared with biopsy data[32], while 
a f luorescent peptide detected VPAC receptors with 
> 98% sensitivity and specificity[37]—VPAC receptors 
bind VIP, a neuropeptide linked to development, 
growth, immune system and cancer.

3.2 RNA in urine sediment 
A disadvantage with urine sediment analysis is that 
the cell transcriptome is likely to alter on becoming 
detached and/or on contact with urine[38,39]. However, 
urine cell sediment has been found to be useful for PCa 
diagnosis.

PCA3 has a reported sensitivity of detection of PCa 
in urinary sediment of 62%, boosted to 73% by co-
detection of TMPRSS2:ERG[40,41]. Other combination 
markers used with PCA3 have been found to aid PCa 

detection in cell sediment: (1) AMACR, TRPM8, 
MSMB[42], (2) TMPRSS2:ERG, GOLPH, SPINK1[43], 
and (3) HIST1H2B, SPP1, ELF3[44]. However, Leyten 
et al. found that PCA3 was unnecessary when HOXC6, 
DLX1, and TDRD1 were used[45], TDRD1 being a direct 
target of ERG and co-expressed with ERG in PCa[46]. In 
combination with the European Randomised Study of 
Screening for PCa (ERSPC) risk calculator[47], Leyten 
et al. noted that TMPRSS2:ERG added significant 
predictive value to the ERSPC calculator to predict 
biopsy Gleason whereas PCA3 did not. TMPRSS2:ERG 
has been reported to be less common in Chinese 
populations[48], and detection of TTTY15:USP9Y gene 
fusion transcripts found in 35% of Chinese patients 
PCa[48] has improved PCa detection in urine sediments 
in that population (n = 226, AUROC 0.83)[49]. Other 
probe combinations excluding PCA3 include a panel of 
6 genes overexpressed in PCa tissue (CCND1, LMTK2, 
FN1, GSTP1, HPN, and MYO6), used in the analysis of 
156 PCa patients’ urine sediments (n = 67), which had 
a sensitivity of 80.6% and specificity of 62.9% for PCa 
detection (AUROC of 0.80)[50]. 

TABLE 1. 

Overview of relevant biomarkers

Biomarker type Use of test
Urine 

fraction or 
source

Detection method
Largest 
cohort 

size
Results References

PCa cells

AMACR, Nkx3.1, 
nucleolin, ERG and 

prostein
PCa 

Urine 
sediment 

Antibody, microscopy 63
Sensitivity 64%, specificity 

69%
35, 36*

Chromosome 
alterations 

PCa 
Urine 

sediment
FISH microscopy 100 AUROC 0.83, 81% accuracy 32

VPAC receptors PCa 
Urine 

sediment
Fluorescent peptide, 

microscopy
176

> 98% sensitivity and 
specificity

37

Protein

C3, C4 transferrin PCa Prostatic fluid
Immunoelectrophoresis, 
radial immunodiffusion

10 Significantly elevated in PCa 11

PCa-1 PCa Whole urine 2D gel electrophoresis 17 16/17 PCa positive 10

ITGA3, ITGB1 Metastasis Supernatant
Mass spectrometry, 

Western blot
13

More abundant in 3 urines 
from metastatic patients

92

EN2
PCa, higher 

tumour stage  
(T1 v T2)

Supernatant
Antibody, ELISA, 
graphene-based 

biosensor
184

PCa AUROC 0.8, sensitivity 
66%, specificity 88%

99*–101, 104

AS: active surveillance; AUROC: area under receiver operating characteristic curve; FISH: fluorescent in situ hybridisation.

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TABLE 1. 

Overview of relevant biomarkers

Biomarker type Use of test
Urine 

fraction or 
source

Detection method
Largest 
cohort 

size
Results References

RNA

PCA3
PCa on repeat 
biopsy Gs≥7

Whole urine, 
supernatant

qRT-PCR, NanoString, 
quantitative nucleic acid 

amplification
809

AUROC 0.66-0.8.  
Sensitivity 47%–82%

15, 16*–23, 69, 
80–84, 97, 105

PCA3, TMPRSS2:ERG  
fusion gene

PCa detection 
Gs≥7, higher vol 

PCa

Whole 
urine, urine 
sediment, 

supernatant

qRT-PCR, quantitative 
nucleic acid amplification

497 AUROC 0.77-0.8. 
26, 40, 41, 47*, 
69, 80–84, 105

 HOXC6, DLX1 
(SelectMDx)

PCa detection 
Gs≥7

Whole urine qRT-PCR 358 AUROC 0.77 29, 45*

KLK3
Control probe in 

analyses

Whole urine, 
sediment, 

supernatant

qRT-PCR, NanoString 
linear amplification

NA NA
14-23, 28, 29, 
40, 41, 43, 69, 

80–84, 87

AMACR, TRPM8, 
MSMB

PCa Cell sediment qRT-PCR 104 AUROC 0.74 42

GOLPH, SPINK1 PCa Cell sediment qRT-PCR 235
AUROC 0.76, sensitivity 

66%, specificity 76%
43

HIST1H2B, SPP1,  
ELF3, PCA3

PCa Cell sediment qRT-PCR 224
AUROC 0.76, sensitivity 

77%, specificity 67%
44

TTTY15:USP9Y PCa Cell sediment qRT-PCR 226 AUROC 0.83 49

CCND1, LMTK2, FN1, 
GSTP1, HPN and MYO

PCa Cell sediment qRT-PCR 67 AUROC of 0.80 50

AGR2 PCa Supernatant qRT-PCR 32 AUROC 0.96 85

Birc5 PCa Supernatant qRT-PCR 207 AUROC 0.67 81

CDH3 PCa Supernatant qRT-PCR 53
Significantly decreased in 

PCa, sensitivity 0.69
86

PUR signatures 39 
gene probes

High risk, AS 
monitoring 

to treatment 
intervention

Supernatant NanoString 535
AUROC 0.77 for high risk, HR 

8.2 for AS monitoring
70

AS: active surveillance; AUROC: area under receiver operating characteristic curve; HR: hazard ratio; qRT-PCR: quantitative reverse transcribed and 
polymerase chain reaction.

, Cont’d

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TABLE 1. 

Overview of relevant biomarkers

Biomarker type Use of test
Urine 

fraction or 
source

Detection method
Largest 
cohort 

size
Results References

miRNA

miR-125b PCa, high risk Cell sediment
Exiqon miRNA RT-PCR 

platform
415 AUROC 0.76 53

miR-24, mir-30c PCA Cell sediment
Exiqon miRNA RT-PCR 

platform, miRCURY LNA 
miRNA SYBR Green PCR

415 AUROC 0.89 53,* 55

miR-148a, miR-375 PCA Cell sediment
Taqman low density 

array
72 AUROC 0.79 52

miR-3195, let-7b-5p, 
miR-144-3p, miR-
451a, miR-148a3p, 
miR-512-5p, miR-

431-5p

PCA Cell sediment NanoString 149 AUROC 0.74 54

DNA

c-Myc, BCAS1, 
HER2, AR, PTEN, 
TMPRSS2:ERG

PCa Supernatant 
qRT-PCR for copy 

number and mutations
10 AUROC 0.8 91

MethDNA

epiCaPture: GSTP1, 
SFRP2, IGFBP3, 

IGFBP7, APC, PTGS2
PCa Gs≥8 Cell sediment

Quantitative 
methylation-specific 

polymerase chain 
reaction 

463 AUROC 0.83 62

ProCUrE: HOXD3 and 
GSTP1

PCa Gs≥7 Cell sediment
Quantitative 
MethyLight

408 AUROC 0.8 63

APC, CRIP3, GSTP1, 
HOXD8

PCa Gs≥7 Cell sediment
Multiplex quantitative 

MethyLight
153 OR 2.6 64

AS: active surveillance; AUROC: area under receiver operating characteristic curve; MethDNA: methylated DNA

, Cont’d

3.3 miRNA in urine sediment
miR NA dysregulation is frequent ly obser ved in 
cancer[51], and a number of diagnostically useful 
miRNAs are detectable in urine[52–55]. miR-21 and  
miR-125b are controlled by the androgen receptor 
(AR), and are overexpressed in PCa and associated 
with apoptotic resistance[53,54]. In contrast, miR-205 
is a tumour suppressor miRNA, promoting apoptosis, 
and its loss is associated with the early stages of PCa 
development[56]. Despite miR-205 being dow n-
regulated in PCa, it is a constituent of several miRNA 
urinary biomarker panels. AUROCs vary from 0.6 to 
0.85 for detection of PCa using multiple combinations 
of miRNAs[52,53], and 0.74 for distinguishing low-risk 
from high-risk disease[54].

3.4 DNA-methylation in urine sediment
Epigenetic alterations are heritable changes in gene 
expression with no change to the DNA code. In cancer, 
DNA-hypermethylation silences tumour suppressors 
and other important regulatory genes[57]. It is easily 
detectable by PCR and it occurs early in tumorigenesis 
making it an ideal biomarker for early detection as well 
as disease progression monitoring and risk stratification 
of patients[58,59]. 

Pioneering work in the detection of PCa and 
significant PCa (Gs ≥ 7) was performed by Cairns et 
al. in 2001, who showed that methylation of the GSTP1 
gene was detectable in urine of men with PCa but at a 
low sensitivity (27%)[60]. GSTP1 is hypermethylated 
in > 90% of PCa[60] and is relatively PCa-specific, it 

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typically being overexpressed in most other cancers. 
For these reasons, it is a stalwart of PCa-methylation 
analysis. Gene panels improved performance, and a 
combination of APC, R ARbeta, R ASSF1A, PTGS2, 
ABCB1 methylation was detectable in > 85% of cases[61]. 
Notable examples include epiCaPture, a 6-gene DNA-
methylation panel (GSTP1, SFRP2, IGFBP3, IGFBP7, 
APC, PTGS2) that can detect 85% of aggressive PCa 
(Gs ≥ 8) with a 70% improvement in the specificity of 
PSA[62] and ProCUrE, a 2-gene DNA-methylation 
panel (HOXD3 and GSTP1) with a sensitivity of 57.1% 
and specificity of 97% for significant PCa[63]. Zhao et 
al. established a 4-gene panel (APC, CRIP3, GSTP1, 
HOXD8) with some ability to predict cancer progression 
in patients on active surveillance (OR 2.559; 95% 
CI 1.257 to 5.212) from post-DRE urine[64]. They 
subsequently incorporated microRNAs and reported 
that miR-24, miR-30c and CRIP3 methylation could 
predict reclassification of AS patients[55]. 

 Currently, no commercially available standardised 
DNA-methylation-based urine tests for PCa are 
available[60], which presents an obstacle to clinical 
uptake[65]. Sample storage conditions affect results as 
methylated-DNA is only stable for up to 28 days in urine 
stored at −20/−80⁰C and a preservative is required at 
room temperature[66]. Most urine assays use bisulfite 
conversion of unmethylated cytosines to uracil, leaving 
hypermethylated cytosines preserved for detection. 
However, a study of 12 different bisulfite kits discovered 
that conversion efficiency varied greatly[67], and storage 
of the less stable single-stranded bisulfite converted 
DNA may also be an issue[68]. Target sequence choice 
is critical, proximity to the transcription start site, 
transcription factor binding motifs, and DNase-
hypersensitivity are all factors that can affect sensitivity 
and specificity[59]. Large, multicentre, standardised 
urine collections and clinical follow-up are needed 
to reduce the unknowns and bring PCa methylation 
biomarkers to fruition. 

4. Urine Supernatant
4.1 RNA in urine extracellular vesicles
Large numbers of extracellular vesicles (EVs) can be 
found in urine[69], the majority of which in first-catch 
adult male urine originate from the prostate[69,70]. EVs 
are lipid-bound vesicles produced by a wide range of 
cell types[71]. EVs function as inter-cellular messengers 
that can bind to and influence the phenotype of cells 
they come into contact with[72,73]. Cancer cells 
produce EVs, which can enhance vasculature[74], 
increase metastasis[75], and inf luence the immune 
system[76] and can contain PCa-specific mRNAs such 
as TMPRSS2:ERG fusion gene transcripts[40]. EVs 
contain lipids, RNA, DNA, and proteins including 

membrane receptors[72,77,78] which are protected from 
degradation by, for example, RNAses by the EV lipid 
membrane[79].

The majority of publications refer to analysis of only 
small numbers of gene transcripts in EVs, namely PCA3, 
ERG, TMPRSS2:ERG, KLK3, which have been found to 
be useful in PCa diagnosis and detection of Gleason ≥ 
4 cancer[69,80–84]. Additional genes with diagnostic 
potential are AGR2 splice variants[85], Birc5[81], and 
decreased expression of CDH3[86]. In contrast, Connell 
et al. used a NanoString panel of 167 gene probes, mostly 
selected from published evidence of over-expression in 
PCa tissue[70]. Analysis of 535 urine EV samples from 
patients with and without PCa led to the prostate urine 
risk (PUR) signatures constructed from a subgroup of 
39 gene probes. In contrast to all other urine analyses, 
instead of a single cancer signature they constructed 
4 PUR signatures, which were built around samples 
categorised as non-cancer (PUR-1), plus the 3 D’Amico 
risk groups for cancer aggression, namely low-risk 
(PUR-2), intermediate-risk (PUR-3), and high-risk 
(PUR-4). Each sample could have representation from 
all 4 signatures and the sum of the 4 PUR signatures 
in each sample was ‘1’. Connell et al. found that PUR-
4 could predict the presence of significant cancer on 
TRUS biopsy (AUROC 0.77). On examination of an 
active surveillance cohort (n = 87) PUR-4 could be 
used to divide patients into 2 groups with rates of 
progression to treatment intervention of 10% and 60% 
up to 5 years after urine collection (HR 8.23). A strong 
PUR-1 signature correlated with stability of low-grade 
disease that did not progress in the 5-year follow-up. 
The PUR-2 and PUR-3 signatures had less utility but 
were hypothesised as integral to the creation of a clearer 
signature for higher grade Gleason cancer detectable by 
PUR-4.

A few studies have compared PCa mRNA transcripts 
in both cell and EV urine fractions. Prostatic transcripts 
appear to be higher in EV fractions[69,80,87], but may 
have better diagnostic utility in the cell sediment[88] 
with a caveat that ~10% of cell sediments may not 
be analysable. Hendriks et al. reported that PCA3 
transcripts were expressed significantly higher in PCa 
patients than in non-PCa patients in both the whole-
urine and cell-sediment fractions but not in the EV 
fraction[87]. Webb et al. compared RNA yields from 
cell sediment and EVs in 200 patients and found them 
to be highly variable with no apparent correlation. 
This observation suggests that examination of RNA 
biomarkers in whole urine could be obfuscated by the 
unknown relative contribution of transcripts from the 
different urine fractions and suggests that separate 
analysis of the 2 fractions is to be recommended[80].

4.2 Cell-free DNA in urine

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Cell-free urine DNA (cf DNA) has been found both 
inside EVs and bound outside EV membranes[79], 
the source of which has been hypothesised to be from 
apoptotic cells[79] and mitochondria[89]. cf DNA 
yields from EVs are low (18pg/mL urine[90]) but have 
been used to detect methylated GSTP1 in men with 
PCa that was not present in urine from men with 
BPH[78]. Casadio et al. used copy number analysis of 
c-Myc, BCAS1, and HER2 by qRTPCR to distinguish 
PCa from non-PCa men with an AUROC of 0.8, while 
copy number gains of AR, genomic deletions including 
PTEN, and TMPRSS2:ERG fusion sequences have been 
detected in a small cohort of men with castrate-resistant 
cancer (n = 10)[91]. 

4.3 Supernatant proteins
Thousands of proteins on or encapsulated within EVs 
have been identified by mass spectrometry analysis, 
with for example ITGA3 and ITGB1 being linked to 
metastasis[92]. For a thorough review see recent papers 
by Pang et al.[93] and Wu et al.[94].

Possibly the most thoroughly investigated urine 
protein biomarker is the transcriptional repressor 
EN2[95]. Unusually for a transcription factor, EN2 
can be secreted from normal and PCa cells and then 
be internalised by other cells to effect transcriptional 
cha nges i n, for ex a mple, st roma[96]. EN2 is 
involved with embryonic brain development and is 
inappropriately expressed in a range of cancers including 
bladder and prostate where EN2 may regulate androgen-
receptor activity in androgen-sensitive prostate cancer 
cells[97,98]. In a 2011 study by Morgan et al., men with 
prostate cancer had a 10-fold higher level of EN2 in 
their urine versus non-cancer controls, and EN2 was 
identified in 66% of urine samples from biopsy-proven 
PCa patients, some of whom had undetectable levels of 
serum PSA[99]. This was in contrast to < 15% positivity 
in control groups (some of whom would have been 
expected to harbour occult prostate cancer), giving a 
specificity of 88.2% (AUROC 0.8; P < 0.001). Higher EN2 
levels correlated with advancing tumour stage, eg, pT3a 
versus pT2b (P = 0.027), positive margins (P = 0.008), 
increasing tumour volume[100,101], and subsequent 
diagnosis of PCa in BRCA1/2 mutation carriers[102].

There have, however, been no large-scale EN2 trials 
because there is no robust commercially available test 
for EN2 protein in urine, which may be due to its very 
high net-charge causing non-specific attachment to 
some plastic surfaces (personal communication from 
H. Pandha [co-author], 2019). Indeed, a recent study 
looking at commercially available ELISA kits for EN2 

found no significant diagnostic value for urinary EN2 in 
PCa patients[103]. Novel approaches are in development, 
such as a graphene-based biosensor[104] and examining 
urine cfRNA EN2 transcripts[70]. 

5. Urine Biomarkers and the DRE
A problem with urine is the inconsistency in the 

amounts of prostatic material between samples. The 
digital rectal examination (DRE) of the prostate is one 
source of variation. When men present at a hospital, 
nerves very often mean that they would urinate before 
seeing the doctor and flush out all the prostatic secretions 
from the urethra. To replenish the prostatic biomarkers 
in the urethra, urine has usually been collected after a 
DRE whereby the doctor would stroke the prostate with 
a finger pushing prostate secretions into the urethra 
shortly before urination. However, urine cfRNA yields 
correlate with the clinician performing the DRE, with 
10-fold differences being found between clinicians, 
differences which were hypothesised as being linked to 
the clinician’s DRE technique, finger length and prostate 
position[80]. 

A number of studies indicate that RNA yields from 
urine collected in the clinic without a DRE are less 
than a tenth of post-DRE samples[69,80] and levels 
of prostate markers such as KLK3 were also reduced 
approx imately 10 -fold[87]. However, studies by 
Donovan et al. and McKiernan et al., using non-DRE 
urine found AUROCs of 0.8 and 0.77, respectively for 
detection of Gs >7 using PCA3 and ERG combined 
with clinical parameters[82,83,105], strongly suggesting 
that non-DRE urine has utility. Webb et al. took this 
one step further[80]: their hypothesis centred on the 
finding by Huggins et al. in 1945 that the prostate was 
constantly secreting[12], indicating that time since 
previous urination was key. Urine samples collected at 
home from the first urination of the day were found to 
have RNA yields comparable to samples collected post-
DRE from the same patients in the clinic a week earlier. 
Significantly, Webb et al. found that detection of PCA3 
and TMPRSS2:ERG by RT-PCR proved to be much 
more sensitive in these morning samples than in the 
post-DRE samples. While this study was limited by the 
low number of men (n = 14) it does suggest that urine 
collections could be performed by mail, could enable 
mass screening, and could simplify disease monitoring 
of, for example, active surveillance cohorts. Webb et al. 
also suggested that inter-sample consistency could be 
further improved by collecting a second urine sample at 
a fixed interval of 1-hour later.

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Conclusions
The extensive interconnecting luminal structures 

of the prostate that carry prostatic secretions to the 
urethra make urine a valuable non-invasive resource 
to examine all parts of the prostate where PCa arises. 
Urine has proven utility in predicting disease load and 
monitoring disease progression, and its use could result 
in the development of a PCa screening test. However, 
the translation of biomarkers from research to clinical 
practice is littered with failure[106]. The heterogeneity 
of PCa and analysis of cohorts with different ranges of 
disease severity make data difficult to inter-compare.  

A further layer of obfuscation is provided by variabilities 
in sample collection, extraction and specifics of analysis 
compounded by inaccurate estimates of PCa disease 
status by standard clinical means. However, urine 
diagnostics is a developing area, moving towards 
mu lti-omic biomarker integration for improved 
diagnostic performance. Urine tests developed by strong 
collaborations between scientists and clinicians have the 
potential to provide targeted and meaningful data that 
can guide treatment and truly improve men’s lives.

References

1. Arora R, Koch MO, Eble JN, Ulbright TM, Li L, Cheng L. Heterogeneity 
of Gleason grade in multifocal adenocarcinoma of the prostate. 
Cancer.2004 Jun 1;100(11):2362–6. 

2. Cooper CS, Eeles R, Wedge DC, Van Loo P, Gundem G, Alexandrov LB, 
et al. Analysis of the genetic phylogeny of multifocal prostate cancer 
identifies multiple independent clonal expansions in neoplastic and 
morphologically normal prostate tissue. Nat Genet.2015 Mar 2. 

3. Greene DR, Wheeler TM, Egawa S, Weaver RP, Scardino P T. 
Relationship between clinical stage and histological zone of origin 
in early prostate cancer: morphometric analysis. Br J Urol.1991 
Nov;68(5):499–509. 

4. Moussa AS, Li J, Soriano M, Klein EA, Dong F, Jones JS. Prostate 
biopsy clinical and pathological variables that predict significant 
grading changes in patients with intermediate and high grade prostate 
cancer. BJU Int.2009 Jan;103(1):43–8. 

5. Epstein JI, Feng Z, Trock BJ, Pierorazio PM. Upgrading and downgrading 
of prostate cancer from biopsy to radical prostatectomy: incidence and 
predictive factors using the modified Gleason grading system and 
factoring in tertiary grades. Eur Urol.2012 May;61(5):1019–24. 

6. Walz J. The “PROMIS” of magnetic resonance imaging cost 
ef fectiveness in prostate cancer diagnosis? Eur Urol. 2018 
Jan;73(1):31–2. 

7. Ahmed HU, El-Shater Bosaily A, Brown LC, Gabe R, Kaplan R, Parmar 
MK, et al. Diagnostic accuracy of multi-parametric MRI and TRUS 
biopsy in prostate cancer (PROMIS): a paired validating confirmatory 
study. Lancet.2017 Jan 19. 

8. PAPANICOL AOU GN. Diagnostic value of exfoliated cells from 
cancerous tissues. J Am Med Assoc.1946 Jun 1;131(5):372–8. 

9. Herbut PA, Lubin EN. Cancer cells in prostatic secretions. J Urol.1947 
Mar;57(3):542-51. doi: 10.1016/s0022-5347(17)69670-8.

10. Edwards JJ, Anderson NG, Tollaksen SL, Eschenbach von AC, Guevara 
J Jr. Proteins of human urine. II. Identification by two-dimensional 
electrophoresis of a new candidate marker for prostatic cancer. Clin 
Chem.1982 Jan 1;28(1):160–3. 

11. Grayhack JT, Wendel EF, Oliver L, Lee C. Analysis of specific proteins 
in prostatic fluid for detecting prostatic malignancy. J Urol.1979 
Mar;121(3):295-9. doi: 10.1016/s0022-5347(17)56760-9.

12. Huggins C. The Physiology of the Prostate Gland. Physiological 
Reviews. 1945;25(2):281–295. 

13. McNeal JE, Redwine EA, Freiha FS, Stamey TA. Zonal distribution of 
prostatic adenocarcinoma. Correlation with histologic pattern and 
direction of spread. Am J Surg Pathol.1988 Dec 1;12(12):897–906. 

14. de Kok JB, Verhaegh GW, Roelofs RW, Hessels D, Kiemeney LA, 
Aalders TW, et al. DD3(PCA3), a very sensitive and specific marker to 
detect prostate tumors. Cancer Res.2002 May 1;62(9):2695–8. 

15. van Gils MPMQ, Hessels D, van Hooij O, Jannink SA, Peelen WP, 
Hanssen SLJ, et al. The time-resolved fluorescence-based PCA3 
test on urinary sediments after digital rectal examination; a Dutch 
multicenter validation of the diagnostic performance. Clin Cancer 
Res.2007 Feb 1;13(3):939–943. 

16. Chun F, la Taille de A, Van Poppel H, Marberger M, Stenzl A, Mulders 
P, et al. Prostate cancer gene 3 (PCA3): development and internal 
validation of a novel biopsy nomogram. Eur Urol.2009 Mar;56(4):659-
667.DOI: 10.1016/j.eururo.2009.03.029.

17. Groskopf J, Aubin SMJ, Deras IL, Blase A, Bodrug S, Clark C, et al. 
APTIMA PCA3 molecular urine test: development of a method to aid in 
the diagnosis of prostate cancer. Clin Chem.2006 Jun 1;52(6):1089–95. 
doi: 10.1373/clinchem.2005.063289. Epub 2006 Apr 20.

18. Hessels D, Schalken JA. The use of PCA3 in the diagnosis of 
prostate cancer. Nat Rev Urol.2009 May;6(5):255-61. doi: 10.1038/
nrurol.2009.40.

19. Marks LS, Fradet Y, Deras IL, Blase A, Mathis J, Aubin SMJ, et al. PCA3 
molecular urine assay for prostate cancer in men undergoing repeat 
biopsy. Urology.2007 Mar 1;69(3):532–5. 

20. Haese A, la Taille de A, van Poppel H, Marberger M, Stenzl A, Mulders 
PFA, et al. Clinical utility of the PCA3 urine assay in European men 
scheduled for repeat biopsy. Eur Urol.2008 Nov 1;54(5):1081–8. 

166 SIUJ  •  Volume 2, Number 3  •  May 2021 SIUJ.ORG

REVIEW



21. Bostwick DG, Gould VE, Qian J, Susani M, Marberger M. Prostate 
cancer detected by uPM3: radical prostatectomy findings. Mod 
Pathol.2006 May;19(5):630–3. 

22. Filella X, Foj L, Milà M, Augé JM, Molina R, Jiménez W. PCA3 in the 
detection and management of early prostate cancer. Tumour Biol.2013 
Jun;34(3):1337–47. 

23. Luo Y, Gou X, Huang P, Mou C. The PCA3 test for guiding repeat biopsy 
of prostate cancer and its cut-off score: a systematic review and meta-
analysis. Asian J Androl.2014 May;16(3):487–492. 

24. Clark J, Attard G, Jhavar S, Flohr P, Reid A, de Bono J, et al. Complex 
patterns of ETS gene alteration arise during cancer development in the 
human prostate. Oncogene.2008 Mar 27;27(14):1993–2003. 

25. Mehra R, Han B, Tomlins SA, Wang L, Menon A, Wasco MJ, et al. 
Heterogeneity of TMPRSS2 gene rearrangements in multifocal 
prostate adenocarcinoma: molecular evidence for an independent 
group of diseases. Cancer Res.2007 Sep 1;67(17):7991–5. DOI: 
10.1158/0008-5472.CAN-07-2043

26. Tomlins SA, Groskopf J, Chinnaiyan AM. Reply to Carsten Stephan, 
Henning Cammann, and Klaus Jung’s Letter to the Editor re: Scott A. 
Tomlins, John R. Day, Robert J. Lonigro, et al. Urine TMPRSS2:ERG 
Plus PCA3 for Individualized Prostate Cancer Risk Assessment. Eur 
Urol. http://dx.doi.org/10.1016/j.eururo.2015.04.039. Eur Urol.2015 
Nov;68(5):e108. 

27. Young A, Palanisamy N, Siddiqui J, Wood DP, Wei JT, Chinnaiyan AM, 
et al. Correlation of urine TMPRSS2:ERG and PCA3 to ERG+ and total 
prostate cancer burden. Am J Clin Pathol.2012 Oct 18;138(5):685–696. 

28. Van Neste L, Partin AW, Stewart GD, Epstein JI, Harrison DJ, Van 
Criekinge W. Risk score predicts high-grade prostate cancer in 
DNA-methylation positive, histopathologically negative biopsies. 
Prostate.2016 Sep;76(12):1078–87. 

29. Govers TM, Hessels D, Vlaeminck-Guillem V, Schmitz-Dräger BJ, Stief 
CG, Martinez-Ballesteros C, et al. Cost-effectiveness of SelectMDx for 
prostate cancer in four European countries: a comparative modeling 
study. Prostate Cancer Prostatic Dis. 2019 Mar;22(1):101–109. doi: 
10.1038/s41391-018-0076-3. Epub 2018 Aug 20.

30. Sullivan PS, Chan JB, Levin MR, Rao J. Urine cytology and adjunct 
markers for detection and surveillance of bladder cancer. Am J Transl 
Res.2010;2(4):412–440. Published online 2010 Jul 25.

31. Truong M, Yang B, Jarrard D. Towards the detection of prostate cancer 
in urine: a critical analysis. J Urol.2013 Feb;189(2):422–429. Published 
online 2012 Sep 24. doi: 10.1016/j.juro.2012.04.143. 

32. Tinawi-Aljundi R, Knuth ST, Gildea M, Khal J, Hafron J, Kernen K, et al. 
Minimally invasive prostate cancer detection test using FISH probes. 
Res Rep Urol.2016;8:105–111. 

33. Foot NC, Papanicolaou GN, Holmquist ND, Seybolt JF. Exfoliative 
cytology of urinary sediments; a review of 2,829 cases. Cancer.1958 
Jan;11(1):127–137. 

34. Thin RN. The diagnosis of prostatitis: a review. Genitourin Med.3rd 
ed. The Medical Society for the Study of Venereal Disease; 1991 
Aug;67(4):279–283. 

35. Fujita K, Pavlovich CP, Netto GJ, Konishi Y, Isaacs WB, Ali S, et al. 
Specific detection of prostate cancer cells in urine by multiplex 
immunofluorescence cytology. Hum Pathol.2009 Jul 1;40(7):924–933. 

36. Nickens KP, Ali A, Scoggin T, Tan S-H, Ravindranath L, Mcleod DG, et 
al. Prostate cancer marker panel with single cell sensitivity in urine. 
Prostate.2015 Mar 23;75(9):969–975. 

37. Trabulsi EJ, Tripathi SK, Gomella L, Solomides C, Wickstrom E, Thakur 
ML. Development of a voided urine assay for detecting prostate cancer 
non-invasively: a pilot study. BJU Int. 2017 Jun;119(6):885–895. 

38. Frisch SM, Screaton RA. Anoikis mechanisms. Curr Opin Cell Biol.2001 
Oct;13(5):555–562. 

39. Bella Della E, Stoddart MJ. Cell detachment rapidly induces changes 
in noncoding RNA expression in human mesenchymal stromal cells. 
BioTechniques.2019 Dec;67(6):286–293. doi: 10.2144/btn-2019-0038. 
Epub 2019 Oct 17.

40. Hessels D, Smit FP, Verhaegh GW, Alfred Witjes J, Cornel EB, Schalken 
JA. Detection of TMPRSS2-ERG fusion transcripts and prostate cancer 
antigen 3 in urinary sediments may improve diagnosis of prostate 
cancer. Clin Cancer Res.2007 Sep 1;13(17):5103–8. 

41. Salami SS, Schmidt F, Laxman B, Regan MM, Rickman DS, Scherr D, 
et al. Combining urinary detection of TMPRSS2:ERG and PCA3 with 
serum PSA to predict diagnosis of prostate cancer. Urol Oncol.2013 
Jul;31(5):566-71. doi: 10.1016/j.urolonc.2011.04.001. Epub 2011 May 
19.

42. Jamaspishvili T, Kral M, Khomeriki I, Vyhnankova V, Mgebrishvili G, 
Student V, et al. Quadriplex model enhances urine-based detection of 
prostate cancer. Prostate Cancer Prostatic Dis.2011 Dec;14(4):354–360. 
https://doi.org/10.1038/pcan.2011.32

43. Laxman B, Morris DS, Yu J, Siddiqui J, Cao J, Mehra R, et al. A 
first-generation multiplex biomarker analysis of urine for the early 
detection of prostate cancer. Cancer Res.2008 Feb 1;68(3):645–9. 
doi: 10.1158/0008-5472.CAN-07-3224.

44. Mengual L, Lozano JJ, Ingelmo-Torres M, Izquierdo L, Musquera M, 
Ribal MJ, et al. Using gene expression from urine sediment to diagnose 
prostate cancer: development of a new multiplex mRNA urine test and 
validation of current biomarkers. BMC Cancer.2016 Feb 9;16(1):76–8. 

45. Ley ten GHJM, Hessels D, Smit FP, Jannink SA, de Jong H, 
Melchers WJG, et al. Identification of a candidate gene panel for 
the early diagnosis of prostate cancer. Clin Cancer Res.2015 Mar 
18;21(13):3061–70. 

46. Boormans JL, Korsten H, Ziel-van der Made AJC, van Leenders 
GJLH, de Vos CV, Jenster G, et al. Identification of TDRD1as a direct 
target gene of ERGin primary prostate cancer. Int J Cancer.2013 Feb 
12;133(2):335–345. 

167SIUJ.ORG SIUJ  •  Volume 2, Number 3  •  May 2021

Urine Biomarkers for Prostate Cancer Diagnosis and Progression

http://dx.doi.org/10.1016/j.eururo.2015.04.039
http://siuj.org


47. Leyten GHJM, Hessels D, Jannink SA, Smit FP, de Jong H, Cornel EB, 
et al. Prospective multicentre evaluation of PCA3 and TMPRSS2-
ERG gene fusions as diagnostic and prognostic urinary biomarkers 
for prostate cancer. Eur Urol.2 014 Mar;65(3):534-42. doi: 10.1016/j.
eururo.2012.11.014. Epub 2012 Nov 15.

48. Ren S, Peng Z, Mao J-H, Yu Y, Yin C, Gao X, et al. RNA-seq analysis 
of prostate cancer in the Chinese population identifies recurrent 
gene fusions, cancer-associated long noncoding RNAs and aberrant 
alternative splicings. Cell Res.2012 May;22(5):806–821. 

49. Zhu Y, Ren S, Jing T, Cai X, Liu Y, Wang F, et al. Clinical utility of a novel 
urine-based gene fusion TTTY15-USP9Y in predicting prostate biopsy 
outcome. Urol Oncol.2015 Sep;33(9):384.e9–20. 

50. Guo J, Yang J, Zhang X, Feng X, Zhang H, Chen L, et al. A panel of 
biomarkers for diagnosis of prostate cancer using urine samples. 
Anticancer Res.2018 Mar;38(3):1471–7. 

51. Hata A, Lieberman J. Dysregulation of microRNA biogenesis and gene 
silencing in cancer. Sci Signal.2015 Mar 17;8(368):re3. doi: 10.1126/
scisignal.2005825.

52. Stuopelytė K, Daniūnaitė K, Bakavicius A, Lazutka JR, Jankevicius F, 
Jarmalaite S. The utility of urine-circulating miRNAs for detection of 
prostate cancer. Br J Cancer.2016 Aug 4;115(6):707–715. 

53. Fredsøe J, Rasmussen AKI, Thomsen AR, Mouritzen P, Høyer S, Borre 
M, et al. Diagnostic and prognostic microRNA biomarkers for prostate 
cancer in cell-free urine. Eur Urol Focus.2018 Dec;4(6):825–833. doi: 
10.1016/j.euf.2017.02.018. Epub 2017 Mar 9.

54. Jeon J, Olkhov-Mitsel E, Xie H, Yao CQ, Zhao F, Jahangiri S, et al. 
temporal stability and prognostic biomarker potential of the prostate 
cancer urine miRNA transcriptome. J Natl Cancer Inst.2020 Mar 
1;112(3):247–255. 

55. Zhao F, Vesprini D, Liu RSC, Olkhov-Mitsel E, Klotz LH, Loblaw A, 
et al. Combining urinary DNA methylation and cell-free microRNA 
biomarkers for improved monitoring of prostate cancer patients on 
active surveillance. Urol Oncol.2019 May;37(5):297.e9–297.e17. 

56. Boll K, Reiche K, Kasack K, Mörbt N, Kretzschmar AK, Tomm 
JM, et al. MiR-130a, miR-203 and miR-205 jointly repress key 
oncogenic pathways and are downregulated in prostate carcinoma. 
Oncogene.2013 Jan 17;32(3):277–285. 

57. Hoque MO. DNA methylation changes in prostate cancer: current 
developments and future clinical implementation. Expert Rev Mol 
Diagn.2009 Apr;9(3):243–257. 

58. Payne SR, Serth J, Schostak M, Kamradt J, Strauss A, Thelen P, et 
al. DNA methylation biomarkers of prostate cancer: confirmation of 
candidates and evidence urine is the most sensitive body fluid for 
non-invasive detection. Prostate.2009 Sep 1;69(12):1257–69. 

59. Larsen LK, Lind GE, Guldberg P, Dahl C. DNA-methylation-based 
detection of urological cancer in urine: overview of biomarkers and 
considerations on biomarker design, source of DNA, and detection 
technologies. Int J Mol Sci.2019 May 30;20(11):2657. Published online 
2019 May 30. doi: 10.3390/ijms20112657.

60. Cairns P, Esteller M, Herman JG, Schoenberg M, Jeronimo C, Sanchez-
Cespedes M, et al. Molecular detection of prostate cancer in urine by 
GSTP1 hypermethylation. Clin Cancer Res.2001 Sep 1;7(9):2727–30. 

61. Patel PG, Wessel T, Kawashima A, Okello JBA, Jamaspishvili 
T, Guérard K-P, et al. A three-gene DNA methylation biomarker 
accurately classifies early stage prostate cancer. Prostate.2019 
Oct;79(14):1705–14. 

62. O’Reilly E, Tuzova AV, Walsh AL, Russell NM, O’Brien O, Kelly S, et 
al. epiCaPture: A urine DNA methylation test for early detection of 
aggressive prostate cancer. JCO Precis Oncol.2019;3:1–18.Published 
online 2019 Jan 14. doi: 10.1200/PO.18.00134.

63. Zhao F, Olkhov-Mitsel E, Kamdar S, Jeyapala R, Garcia J, Hurst R, et al. 
A urine-based DNA methylation assay, ProCUrE, to identify clinically 
significant prostate cancer. Clin Epigenet.2018 Nov;10. https://doi.
org/10.1186/s13148-018-0575-z.

64. Zhao F, Olkhov-Mitsel E, van der Kwast T, Sykes J, Zdravic D, 
Venkateswaran V, et al. Urinary DNA Methylation Biomarkers for 
Noninvasive Prediction of Aggressive Disease in Patients with Prostate 
Cancer on Active Surveillance. J Urol.2017 Feb;197(2):335–341. 

65. Mikeska T, Bock C, Do H, Dobrovic A. DNA methylation biomarkers 
in cancer: progress towards clinical implementation. Expert Rev Mol 
Diagn.2012 Jun;12(5):473–487. 

66. Bosschieter J, Bach S, Bijnsdorp IV, Segerink LI, Rurup WF, van Splunter 
AP, et al. A protocol for urine collection and storage prior to DNA 
methylation analysis. PLoS One.2018;13(8):e0200906. Published online 
2018 Aug 24. doi: 10.1371/journal.pone.0200906.

67. Worm Ørntoft M-B, Jensen SØ, Hansen TB, Bramsen JB, Andersen 
CL. Comparative analysis of 12 different kits for bisulfite conversion 
of circulating cell-free DNA. Epigenetics.2017 Aug;12(8):626–636. 

68. Pharo HD, Honne H, Vedeld HM, Dahl C, Andresen K, Liestøl K, et al. 
Experimental factors affecting the robustness of DNA methylation 
analysis. Sci Rep.2016 Sep 27;6(1):33936. 

69. Pellegrini KL, Patil D, Douglas KJS, Lee G, Wehrmeyer K, Torlak M, et 
al. Detection of prostate cancer-specific transcripts in extracellular 
vesicles isolated from post-DRE urine. Prostate. 2017 Jun;77(9):990–9. 

70. Connell SP, Hanna M, McCarthy F, Hurst R, Webb M, Curley H, et al. 
A four-group urine risk classifier for predicting outcome in prostate 
cancer patients. BJU Int.2019 May 20;124(4):609-620. doi: 10.1111/
bju.14811. Online ahead of print.

71. Pan BT, Johnstone RM. Fate of the transferrin receptor during 
maturation of sheep reticulocytes in vitro: selective externalization 
of the receptor. Cell.1983 Jul 1;33(3):967–978. 

72. Zaborowski MP, Balaj L, Breakefield XO, Lai CP. Extracellular 
Vesicles: Composition, Biological Relevance, and Methods of Study. 
Bioscience.2015 Aug 1;65(8):783–797. 

73. Doyle L, Wang M. Overview of extracellular vesicles, their origin, 
composition, purpose, and methods for exosome isolation and analysis. 
Cells.2019 Jul 15;8(7):727. doi: 10.3390/cells8070727.

168 SIUJ  •  Volume 2, Number 3  •  May 2021 SIUJ.ORG

REVIEW

https://dx.doi.org/10.3390%2Fijms20112657
https://dx.doi.org/10.1200%2FPO.18.00134
https://dx.doi.org/10.1371%2Fjournal.pone.0200906


74. Chiba M, Kubota S, Sato K, Monzen S. Exosomes released from 
pancreatic cancer cells enhance angiogenic activities via dynamin-
dependent endocytosis in endothelial cells in vitro. Sci Rep.2018 Aug 
10;8(1):11972–9. 

75. Grange C, Tapparo M, Collino F, Vitillo L, Damasco C, Deregibus MC, 
et al. Microvesicles released from human renal cancer stem cells 
stimulate angiogenesis and formation of lung premetastatic niche. 
Cancer Res.2011 Aug 1;71(15):5346–56. 

76. Greening DW, Gopal SK, Xu R, Simpson RJ, Chen W. Exosomes and 
their roles in immune regulation and cancer. Semin Cell Dev Biol.2015 
Apr;40:72–81. 

77. Pisitkun T, Shen R-F, Knepper MA. Identification and proteomic 
profiling of exosomes in human urine. Proc Natl Acad Sci USA.2004 
Sep 7;101(36):13368–73. doi: 10.1073/pnas.0403453101. Epub 2004 
Aug 23.

78. Bryzgunova OE, Morozkin ES, Yarmoschuk SV, Vlassov VV, Laktionov 
PP. Methylation-specific sequencing of GSTP1 gene promoter 
in circulating/extracellular DNA from blood and urine of healthy 
donors and prostate cancer patients. Ann N Y Acad Sci.2008 Aug 
1;1137:222–5. 

79. Miranda KC, Bond DT, McKee M, Skog J, P ̆aunescu TG, Da Silva N, et 
al. Nucleic acids within urinary exosomes/microvesicles are potential 
biomarkers for renal disease. Kidney Int.2010 Jul;78(2):191–9. 

80. Webb M, Manley K, Olivan M, Guldvik I, Palczynska M, Hurst R, et al. 
Methodology for the at-home collection of urine samples for prostate 
cancer detection. BioTechniques.2020 Feb;68(2):65-71.doi: 10.2144/
btn-2019-0092. Epub 2019 Nov 29.

81. Motamedinia P, Scott AN, Bate KL, Sadeghi N, Salazar G, Shapiro E, 
et al. Urine exosomes for non-invasive assessment of gene expression 
and mutations of prostate cancer. Kyprianou N, editor. PLoS ONE.2016 
May 4;11(5):e0154507–15. 

82. McKiernan J, Donovan MJ, O’Neill V, Bentink S, Noerholm M, Belzer 
S, et al. A novel urine exosome gene expression assay to predict 
high-grade prostate cancer at initial biopsy. JAMA Oncol.2016 Jul 
1;2(7):882–8. 

83. Donovan MJ, Noerholm M, Bentink S, Belzer S, Skog J, Neill VOA, et al. 
A molecular signature of PCA3 and ERG exosomal RNA from non-DRE 
urine is predictive of initial prostate biopsy result. Prostate Cancer 
Prostatic Dis.2015 Dec;18(4):370-5.doi: 10.1038/pcan.2015.40. Epub 
2015 Sep 8.

84. Lin DW, Newcomb LF, Brown EC, Brooks JD, Carroll PR, Feng Z, 
et al. Urinary TMPRSS2:ERG and PCA3 in an active surveillance 
cohort: results from a baseline analysis in the canary prostate active 
surveillance study. Clin Cancer Res.2013 Apr 30;19(9):2442–50. 

85. Neeb A, Hefele S, Bormann S, Parson W, Adams F, Wolf P, et al. Splice 
variant transcripts of the anterior gradient 2 gene as a marker of 
prostate cancer. Oncotarget.2014 Sep 30;5(18):8681–9. 

86. Royo F, Zuñiga-Garcia P, Torrano V, Loizaga A, Sanchez-Mosquera 
P, Ugalde-Olano A, et al. Transcriptomic profiling of urine 
extracellular vesicles reveals alterations of CDH3 in prostate cancer. 
Oncotarget.2016 Feb 9;7(6):6835–46. 

87. Hendriks RJ, Dijkstra S, Jannink SA, Steffens MG, van Oort IM, 
Mulders PFA, et al. Comparative analysis of prostate cancer specific 
biomarkers PCA3 and ERG in whole urine, urinary sediments and 
exosomes. Clin Chem Lab Med.2016 Mar;54(3):483-92.doi: 10.1515/
cclm-2015-0599.

88. Dijkstra S, Birker IL, Smit FP, Leyten GHJM, de Reijke TM, van Oort 
IM, et al. Prostate cancer biomarker profiles in urinary sediments and 
exosomes. J Urol.2014 Apr;191(4):1132–8. 

89. Guescini M, Genedani S, Stocchi V, Agnati LF. Astrocytes and 
glioblastoma cells release exosomes carrying mtDNA. J Neural 
Transm.2010;117(1):1–4. 

90. Bryzgunova OE, Zaripov MM, Skvortsova TE, Lekchnov EA, Grigor’eva 
AE, Zaporozhchenko IA, et al. Comparative study of extracellular 
vesicles from the urine of healthy individuals and prostate cancer 
patients. PLoS One.2016 Jun 15;11(6):e0157566–17. doi: 10.1371/
journal.pone.0157566. 

91. Xia Y, Huang C-C, Dittmar R, Du M, Wang Y, Liu H, et al. Copy number 
variations in urine cell free DNA as biomarkers in advanced prostate 
cancer. Oncotarget.2016 Jun 14; 7(24): 35818–35831. Published online 
2016 Apr 26. doi: 10.18632/oncotarget.9027.

92. Bijnsdorp IV, Geldof AA, Lavaei M, Piersma SR, van Moorselaar RJA, 
Jimenez CR. Exosomal ITGA3 interferes with non-cancerous prostate 
cell functions and is increased in urine exosomes of metastatic 
prostate cancer patients. J Extracell Vesicles.2013;2. doi: 10.3402/
jev.v2i0.22097. eCollection 2013.

93. Pang B, Zhu Y, Ni J, Thompson J, Malouf D, Bucci J, et al. Extracellular 
vesicles: the next generation of biomarkers for liquid biopsy-based 
prostate cancer diagnosis. Theranostics.2020 Jan 18;10(5):2309–26. 

94. Wu Z, Zhang Z, Xia W, Cai J, Li Y, Wu S. Extracellular vesicles in 
urologic malignancies-Implementations for future cancer care. 
Cell Prolif.2019 Nov;52(6):e12659. Published online 2019 Aug 
30. doi: 10.1111/cpr.12659.

95. Tolkunova EN, Fujioka M, Kobayashi M, Deka D, Jaynes JB. Two 
distinct types of repression domain in Engrailed: one interacts with 
the groucho corepressor and is preferentially active on integrated 
target genes. Mol Cell Biol.1998 May;18(5):2804–14.  doi: 10.1128/
mcb.18.5.2804. 

96. Punia N, Primon M, Simpson GR, Pandha HS, Morgan R. Membrane 
insertion and secretion of the Engrailed-2 (EN2) transcription factor 
by prostate cancer cells may induce antiviral activity in the stroma. 
Sci Rep.2019 Mar 26;9(1):5138. 

97. Shah CA, Bei L, Wang H, Altman JK, Platanias LC, Eklund EA. 
Cooperation between AlphavBeta3 integrin and the fibroblast growth 
factor receptor enhances proliferation of Hox-overexpressing acute 
myeloid leukemia cells. Oncotarget. 2016 Aug 23;7(34):54782–94. 

98. Gómez-Gómez E, Jiménez-Vacas JM, Pedraza-Arévalo S, López-López 
F, Herrero-Aguayo V, Hormaechea-Agulla D, et al. Oncogenic role 
of secreted Engrailed homeobox 2 (EN2) in prostate cancer. J Clin 
Med.2019 Sep 6;8(9):1400. 

169SIUJ.ORG SIUJ  •  Volume 2, Number 3  •  May 2021

Urine Biomarkers for Prostate Cancer Diagnosis and Progression

https://dx.doi.org/10.18632%2Foncotarget.9027
https://dx.doi.org/10.1111%2Fcpr.12659
http://siuj.org


99. Morgan R, Boxall A, Bhatt A, Bailey M, Hindley R, Langley S, et al. 
Engrailed-2 (EN2): a tumor specific urinary biomarker for the early 
diagnosis of prostate cancer. Clin Cancer Res.2011 Mar 1;17(5):1090–8. 

100. Pandha H, Sorensen KD, Orntoft TF, Langley S, Høyer S, Borre M, et 
al. Urinary Engrailed-2 (EN2) levels predict tumour volume in men 
undergoing radical prostatectomy for prostate cancer. BJU Int.2012 
May 15;110(6b):E287–92. 

101. Pandha H, Javed S, Sooriakumaran P, Bott S, Montgomery B, Hutton 
A, et al. Correlation of urinary Engrailed-2 levels to tumour volume and 
pathological stage in men undergoing radical prostatectomy. J Cancer 
Ther.2013;04(03):726–733. doi: 10.4236/jct.2013.43089.

102. Mitra AV, Bancroft EK, Barbachano Y, Page EC, Foster CS, Jameson C, et 
al. Targeted prostate cancer screening in men with mutations in BRCA1 
and BRCA2 detects aggressive prostate cancer: preliminary analysis 
of the results of the IMPACT study. BJU Int.2011 Jan;107(1):28–39. 

103. Do Carmo Silva J, Vesely S, Novak V, Luksanova H, Prusa R, Babjuk 
M. Is Engrailed-2 (EN2) a truly promising biomarker in prostate cancer 
detection? Biomarkers.2020 Feb;25(1):34–9. 

104. Settu K, Liu J-T, Chen C-J, Tsai J-Z. Development of carbon-
graphene-based aptamer biosensor for EN2 protein detection. Anal 
Biochem.2017 Oct 1;534:99–107. doi: 10.1016/j.ab.2017.07.012. Epub 
2017 Jul 11.

105. McKiernan J, Donovan MJ, Margolis E, Partin A, Carter B, Brown G, 
et al. A Prospective adaptive utility trial to validate performance of 
a novel urine exosome gene expression assay to predict high-grade 
prostate cancer in patients with prostate-specific antigen 2–10ng/
ml at initial biopsy. Eur Urol.2018 Dec;74(6):731-738. doi: 10.1016/j.
eururo.2018.08.019. Epub 2018 Sep 17.

106. Locke WJ, Guanzon D, Ma C, Liew YJ, Duesing KR, Fung KYC, et al. 
DNA Methylation Cancer Biomarkers: Translation to the Clinic. Front 
Genet. 2019;10:1150. 

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