Clinical Biochemistry 47 (2014) 889–896

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Clinical Biochemistry journal homepage: www.elsevier.com/locate/clinbiochem

Review

Clinical use of novel urine and blood based prostate cancer biomarkers: A review S. Dijkstra 1, P.F.A. Mulders 1, J.A. Schalken ⁎ Radboud University Medical Center, Department of Urology, P.O. Box 9101, Geert-Grooteplein Zuid 10, 6500 HB Nijmegen, The Netherlands

a r t i c l e

i n f o

Article history: Received 25 July 2013 Received in revised form 8 October 2013 Accepted 20 October 2013 Available online 29 October 2013 Keywords: Prostate cancer Biomarkers PSA PCA3 TMPRSS2–ERG MicroRNA miRNA Circulating tumour cells CTC Exosomes

a b s t r a c t In the era of upcoming techniques for molecular profiling, breakthroughs led to new discoveries in the field of prostate cancer (PCa) biomarkers. Since the early 1990s a tremendous increase in PCa incidence is seen, dedicated to the introduction of prostate specific antigen (PSA) testing. However, due to its lack of specificity many men undergo unnecessary biopsies, resulting in a rising incidence of clinically insignificant PCa. To overcome this drawback, cancer specific biomarkers are needed to identify patients who are at high risk of harbouring PCa and to distinguish patients with aggressive disease from patients with insignificant cancer. The most noninvasive, easy to obtain substrate for biomarker measurement is urine. The most promising markers to date are PCA3 and TMPRSS2–ERG. Both markers demonstrate to have a higher specificity and diagnostic accuracy for PCa outcome compared to serum PSA. This might better predict the presence of PCa and therefore reduce the number of unnecessary biopsies. Combining both markers in a panel might result in an even higher diagnostic accuracy, given the heterogeneity of the disease. In PCa management, circulating tumour cells (CTCs) detected in the blood seem a promising tool to predict treatment response and survival benefit. Although results appear to be encouraging, the biggest challenge about new markers in PCa is to validate them in large clinical trials and subsequently implement these markers into clinical practice. In this review we discuss the clinical usefulness of novel, noninvasive tests in PCa management. © 2013 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Novel urinary prostate cancer biomarkers . . . . . . . . . . . . . . . . . Prostate Cancer Antigen 3 (PCA3) . . . . . . . . . . . . . . . . . . . Identification of the PCA3 gene . . . . . . . . . . . . . . . . . Translation to a transcription-mediated amplification assay . . . . Clinical implication; diagnostic utility in the prostate biopsy setting PCA3 as a prognostic tool . . . . . . . . . . . . . . . . . . . Transmembrane Protease, Serine 2–ETS fusion (TMPRSS2–ERG) . . . . . TMPRSS2–ERG fusion as a prognostic tool in PCa management . . PCA3 + TMPRSS2–ERG combined biomarker panel . . . . . . . . . . . MicroRNA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Exosomes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Novel blood-based prostate cancer biomarkers . . . . . . . . . . . . . . . Circulating tumour cells (CTCs) . . . . . . . . . . . . . . . . . . . . Molecular profiling of peripheral blood mononuclear cells (PBMCs) . . . . Tissue markers for prostate cancer . . . . . . . . . . . . . . . . . . . . . Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abbreviations: PCa, prostate cancer; PSA, prostate specific antigen; DRE, digital rectal examination; TRUS, transrectal ultrasound; PCA3, Prostate Cancer Antigen 3; TMPRSS2, Transmembrane Protease, Serine 2; CTC, circulating tumour cell; mRNA, messenger RNA; PPV, positive predictive value; NPV, negative predictive value; FDA, Food and Drug Administration; RP, radical prostatectomy; CRPC, castration resistant prostate cancer. ⁎ Corresponding author. Fax: +31 24 35 41 222. E-mail address: [email protected] (J.A. Schalken). 1 Fax: +31 24 35 41 222. 0009-9120/$ – see front matter © 2013 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.clinbiochem.2013.10.023

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Conflict of interest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Introduction Prostate cancer (PCa) is the most common malignancy in men, with an estimated incidence of 382,000 new cases in Europe and 239,000 in the United States [1,2]. Incidence is highest in Western society and worldwide estimates for new PCa cases and deaths in 2008 are 899.000 and 258.000, respectively [3]. The tremendous increase over the past decades can mainly be assigned to the widespread use of serum prostate specific antigen (PSA) testing, introduced in the late 1980s. PSA, a kallikrein serine protease encoded by the KLK3 gene, is secreted almost exclusively by the epithelial cells of the prostate. This biomarker is organ-specific and small quantities are present in blood serum of healthy men. However, PSA is not cancer-specific and various non-malignant circumstances can cause a rise in PSA blood levels, e.g. benign prostatic hyperplasia and prostatitis. Despite its low specificity for the diagnosis of PCa upon prostate biopsies, PSA is currently, in combination with a digital rectal examination (DRE) and transrectal ultrasound (TRUS), the most commonly used diagnostic method for PCa. PSA is measured as a continuous parameter and therein also lies the pitfall. Although increased PSA levels are associated with a higher risk of harbouring PCa, there is no optimal threshold value for the presence of PCa. Moreover, a study by Thompson et al. demonstrated a risk of approximately 9% to have PCa, in men with a PSA ≤ 1.0 ng/mL [4]. The widespread use of PSA has led to an increase in diagnostic prostate biopsies, which in turn resulted in the diagnosis of more insignificant tumours. A fraction of these screen-detected tumours might not have become clinically significant during lifetime. Patients that have these tumours are therefore overdiagnosed, leading to unnecessary treatment, exposure to potential side effects, an increase in healthcare costs for the community and bringing psychological burden to the patient [5,6]. In a European screening study involving 182,160 men, the authors demonstrated that to prevent one PCa death at 11 years of follow-up, 1055 men needed to be invited for screening and 37 cancers needed to be detected [7]. Therefore, PCa screening based on PSA levels remains controversial, despite it reduces PCa mortality. Several PSA modifications have been described and evaluated in the attempt to improve diagnostic accuracy for early PCa detection and to use as a prognostic tool in the follow-up of PCa patients. These derivatives include PSA density, PSA velocity and PSA doubling time, free/total PSA ratio and PSA isoforms. Although a study demonstrated that a lower percentage of free PSA was associated with a higher risk of PCa at biopsy in men who have total PSA levels between 4 and 10 ng/mL, these results must be used with caution as several preanalytical and clinical factors may influence this ratio [8,9]. PSA velocity and PSA doubling time are correlated with PCa diagnosis at biopsy, however, there is little evidence that both provide additional value to absolute total PSA level alone [10]. There are different perspectives on the fact whether PSA kinetics can predict outcome in PCa patients, although it seems that PSA doubling time has a high sensitivity for predicting recurrence after radical prostatectomy and radiotherapy [11–13]. A specific PSA isoform called [−2]proenzyme PSA (p2PSA) and its derivatives; %p2PSA and the commercially available Beckman Coulter Prostate Health Index (phi: (p2PSA / free PSA) × √PSA) improve the predictive accuracy for PCa detection compared to total PSA and percentage free PSA [14,15]. In a study including 646 men, phi significantly outperformed total PSA (AUC of 0.67 versus 0.50, respectively) for the diagnosis of PCa upon initial biopsy [14]. Another study assessed

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phi and PCA3 in an initial biopsy cohort consisting of 300 eligible men. Both phi and PCA3 were independent predictors of PCa and they showed comparable diagnostic performance (AUC 0.77 and 0.73, respectively) [16]. This diagnostic tool therefore might increase the ability to detect PCa and lower the rate of unnecessary biopsies. However, these findings have to be further validated before implementation in clinical practice. As a consequence of the limitations of the PSA test, together with the technological improvement, enormous progress has been made in the field of molecular profiling and biomarker detection techniques (mass spectrometry, high throughput screening, cell and tissue based microarrays etcetera). This resulted in the discovery of novel biomarkers which could potentially contribute to more accurate prediction of biological behaviour in a non-invasive way. In this review we discuss the role of these novel, urinary biomarkers in PCa diagnosis and treatment. Novel urinary prostate cancer biomarkers The definition of a biological marker (biomarker) has a broad prospect. In general, a biomarker can be defined as a characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention [17]. In order to make a biomarker an ideal marker for general use in PCa management, it should be able to differentiate tumour tissue from benign tissue, and aggressive tumours from insignificant tumours, with a high specificity and sensitivity. Furthermore, it should be a non-invasive test and be as inexpensive as possible to encourage widespread use. Present-day study designs with diagnostic accuracy as endpoint need to be conducted in accordance with the Standards for Reporting of Diagnostic Accuracy (STARD) criteria in order to improve accuracy and completeness of these studies [18]. Biomarkers can be measured in several distinct substrates, e.g. blood, urine and tissue. However, since the latter substrate cannot be obtained non-invasively, tissue is less suitable to serve as a screening tool in contrast to urine and blood, which can be gained in a more non-invasive manner and could therefore serve as a promising substrate for biomarker measurement. Hypothetically, due to the anatomical localisation of the prostate in relation to the urethra, urine could serve as an easy to obtain substrate to represent biochemical processes within the prostate. Therefore, there might be a potential role for urinary biomarkers in PCa management. By performing pressure to the prostate, as is done with a DRE, biomarker expression in the first-catch urine is increased [19,20]. Prostate Cancer Antigen 3 (PCA3) Identification of the PCA3 gene Prostate Cancer Antigen 3 (PCA3) was first described as the Differential Display clone 3 (DD3) gene in 1999 as a prostate specific non-coding messenger RNA (mRNA) found to be highly overexpressed in PCa tissue compared to non-neoplastic prostate tissue. PCA3 overexpression was seen in 95% of prostate cancers, with a median 66-fold upregulation and no expression in non-prostate tissue (e.g. various benign tissues, malignant breast, ovary and testis tissue and cell lines originating from bladder, breast, kidney, and ovarian cancer) [21]. Two studies showed an improvement of diagnostic accuracy and specificity of the reverse transcription polymerase chain reaction (RT-PCR) PCA3 assay over serum PSA. The first study, including 108 men undergoing prostate biopsies, showed an area under the curve (AUC) of 0.72 (95% confidence interval (CI) 0.58–0.85) for

S. Dijkstra et al. / Clinical Biochemistry 47 (2014) 889–896

PCa outcome and a sensitivity and specificity of 67% and 83%, respectively [19]. In another multicenter study involving 583 men, the urinary PCA3 assay had an AUC of 0.66 (95% CI 0.61–0.71) compared to 0.57 (95% CI 0.52–0.63) for serum PSA, with a PCA3 sensitivity and specificity of 65% and 66%, respectively. In comparison, serum PSA (between 3 and 15 ng/mL) had a sensitivity of 65% and a specificity of 47% [22].

Translation to a transcription-mediated amplification assay In 2006 a transcription-mediated amplification assay was designed to translate the RT-PCR based urinary PCA3 assay into the commercially available PCA3 Progensa® test (Gen-Probe Inc.). In this test whole urine is used, in which a quantitative PCA3 score is calculated as a ratio between PCA3 and PSA mRNA ([PCA3 mRNA / PSA mRNA] × 1000) [23]. PSA mRNA concentrations are used in this calculation to normalise for the amount of prostate-specific mRNA in the molecular test samples, since KLK3, the gene that encodes for PSA, is not upregulated in PCa [23]. The PCA3 assay can be applied on first-catch urine obtained after performing a DRE (three strokes per lobe) that shed prostate (cancer) cells into the urethra. This method of urine collection provides higher informative rates compared to samples obtained without performing a DRE [24].

Clinical implication; diagnostic utility in the prostate biopsy setting The diagnostic performance of the PCA3 test has been extensively studied and gained USA Food and Drug Administration (FDA) approval in 2012 as an aid tool for decision making in the repeat biopsy setting, with a cut-off value of 25. The likelihood of harbouring PCa increases as the PCA3 score is higher [25,26]. Consequently, the most accurate and optimal cut-off value is still subject to discussion and is mostly based on a compromise between sensitivity and specificity. Various studies demonstrated an optimal balance between sensitivity and specificity using a PCA3 score of 35 [25,27–29], whereas others suggest lowering the cut-off to 25 [30,31]. The major drawback in these studies

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is the fact that prostate biopsy outcome is used as a golden standard, whereas the number of men who actually have PCa might be higher. To aid in the identification of men at risk for PCa and improve diagnostic accuracy, various PCa risk tables and nomograms have been developed. In a study described by Hansen et al., PCA3 was added to established clinical risk factors, to develop a nomogram for decision making in the initial prostate biopsy setting [32]. Adding PCA3 (with a cut-off value of 21) to this nomogram showed highest diagnostic accuracy with an AUC of 0.81; an increment of 7.1% in contrast to the base model consisting of age, serum PSA, prostate volume and DRE findings. Four other large clinical studies showed that PCA3 fulfils the criteria for a novel marker capable of increasing the predictive accuracy of multivariate biopsy models [33–36]. Hence, adding PCA3 to the developed nomograms may aid in guiding biopsy decision. An overview of the different clinical studies that evaluated the PCA3 score as a prediction tool for prostate biopsy outcome is represented in Table 1. PCA3 as a prognostic tool Several studies assessed the role of PCA3 as a useful marker to monitor PCa aggressiveness (e.g. clinical/pathological stage, Gleason score, tumour volume, extra prostatic extension) at prostate biopsies [19,25,28]. However, in these studies there was no significant correlation found. Moreover, various studies have been designed to assess PCA3 scores in relation to pathological features by using prostatectomy specimen as an outcome. In 2008 Van Gils et al. described a study including 62 men who underwent a radical prostatectomy and they assessed the PCA3 score in correlation with prognostic parameters [42]. No significant correlation was found between the PCA3 score and any of the investigated parameters. These findings were confirmed by a second study in which they assayed the same patient cohort, and by a recent study from the same research group who assessed a different patient population [41,43]. On the contrary, Durand et al. described a study in which they assessed the correlation between the PCA3 score and radical prostatectomy (RP) outcome in 160 patients. They found a significant correlation between PCA3 scores and tumour volume as

Table 1 Diagnostic performance of PCA3 with respect to prostate biopsy outcome. PCa %

PCA3 Cut-off value

AUC

Sensitivity %

Specificity %

PPV %

NPV %

Hessels et al. (2003) [19] Groskopf et al. (2006) [23] Van Gils et al. (2007) [22] Marks et al. (2007) [28]

References

108 68 534 226

22.2 22.9 32.6 26.5

0.72a 0.75 0.66a 0.68a

Ankerst et al. (2008) [35] Deras et al. (2008) [25]

443 570

27.8 36.1

Haese et al. (2008) [27]

463

27.6

Chun et al. (2009) [34]

809

39.1

Wang et al. (2009) [37] Auprich et al. (2010) [33]

187 621

46.5 41.1

Roobol et al. (2010) [38]

721

16.9

Adam et al. (2011) [39]

105

42.9

218 1913 443

33.5 41.9 44.2

Hansen et al. (2013) [32]

692

46.0

Ochiai et al. (2013) [26]

578

41.7

200 × 10−3 50 × 10−3 58 10 35 26 20 35 20 35 17 35 35 17 35 20 35 10 35 51 35 25 35 21 35 20 35

67 69 65 87 58 63 71 54 73 47 81 53 53 88 64 84 68 91 78 70 49 81 68 79 60 82 67

83 79 66 28 72 60 56 74 51 72 45 71 80 45 70 28 56 17 50 81 78 52 60 59 76 5 72

53 50 48 30 43 36 48 54 36 39 49 54 70 53 60 19 24 45 54 65 61 57 58 62 68 52 58

90 89 80 85 83 81 77 74 83 78 79 70 66 84 74 90 90 71 75 84 68 78 71 77 69 84 78

Perdona et al. (2011) [36] Crawford et al. (2012) [40] Leyten et al. (2012) [41]

Number of participants

0.67a 0.69a 0.66a 0.63 0.62 N/A 0.75b 0.74 0.64a 0.71a 0.83a 0.71a 0.72a 0.69 0.68 0.75a

Abbreviations: PCa, prostate cancer; AUC, area under the curve; PPV, positive predictive value; NPV, negative predictive value; N/A, not available. a PCA3 score as a continuous variable. b Implemented in the nomogram (age, PSA, DRE, prostate volume, previous biopsy).

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well as positive margin risk on RP samples, considering a value of 35 as the most efficient value to predict tumour volumes N 0.5 mL and positive margins on RP [44]. Nakanishi et al. and Ploussard et al. also found a significant relationship between the PCA3 score and tumour volume as they evaluated 83 and 106 patients who underwent a RP, respectively [31,45]. In addition, in the study described by Nakanishi et al., higher PCA3 scores were also associated with a higher Gleason score. The largest study to date, published by Auprich et al., included 305 patients who underwent RP. In this study PCA3 was not found to be a significant predictor for extra prostatic extension, seminal vesicle invasion or high grade disease at RP specimen (Gleason score ≥7) [30]. In conclusion, several studies that have evaluated PCA3 as a potential prognostic marker showed controversial results. However, PCA3 seems most likely to be associated with low tumour volumes and its role in the prediction of aggressive tumours seems limited. It is assumed that lower Gleason score tumours are characterised by larger glandular lumina compared to higher Gleason score cancers, where glands appear to be fused. In this way, tumour cells might be easier shed into the glandular system in lower Gleason score tumours, resulting in higher PCA3 scores. Transmembrane Protease, Serine 2–ETS fusion (TMPRSS2–ERG) By using a method named cancer outlier profile analysis (COPA), genes that are differentially expressed in different PCas can be identified. With this technique Tomlins et al. described in 2005 that gene members of the ETS family (v-ets erythroblastosis virus E26 oncogene; ERG and ETS variant gene 1; ETV1) were markedly overexpressed in 57% of PCa cases. Furthermore, by using a combination of assays, they found fusion with the 5′ untranslated region of the androgen-regulated gene Transmembrane Protease, Serine 2 (TMPRSS2) in over 90% of cases that overexpressed ERG or ETV1, suggesting that the fusion is most likely the cause of the overexpression [46]. The existence of this androgen regulated gene fusion between TMPRSS2 and ERG may fulfil an important role in PCa diagnostics and management. In 2006 it was demonstrated that TMPRSS2–ERG fusion transcripts could be detected in urine samples of patients with PCa [47]. TMPRSS2–ERG gene fusion is highly PCa specific and has been found in approximately 50% of the PSA-screened prostate adenocarcinomas in the Caucasian population and with lower incidence in Asian cohorts [48,49]. This urine based assay was studied in a pre-biopsy cohort consisting of 108 patients. The TMPRSS2–ERG fusion had a sensitivity of 37%, a specificity of 93% and a positive predictive value (PPV) of 94% in post-DRE urine samples for the prediction of PCa upon biopsy [50]. Given this high specificity for PCa outcome with the urine TMPRSS2–ERG fusion assay, it suggests that this gene might potentially fulfil an important clinical role in determining whether PCa is present or absent. However, as most of the PCas have multiple tumour foci, TMPRSS2–ERG status is commonly heterogeneous between these foci within the same prostate [51]. Tomlins et al. suggested that due to this heterogeneous nature of the disease, a binary rendering (positive/ negative) of TMPRSS2–ERG expression in urine of men with PCa would not per definition reflect the extensiveness of the disease [51]. Despite TMPRSS2–ERG expression can be displayed as a continuous variable, using a certain cut-off, a balance between sensitivity and specificity could be gained, as is also the case with the PCA3 score. Another way to overcome the low sensitivity of TMPRSS2–ERG and reflect the heterogeneity of PCa is to combine several biomarkers in a panel. TMPRSS2–ERG fusion as a prognostic tool in PCa management Several studies aimed to investigate whether the TMPRSS2–ERG fusion is associated with a more aggressive PCa phenotype and therefore could predict worse prognosis. The largest study so far, assessed the association between ERG protein overexpression in tissue in a cohort including 1180 men treated with radical prostatectomy and found

overexpression in 49% [49]. This ERG overexpression was correlated with a higher tumour stage (p b 0.01). On the contrary no association was found between ERG overexpression and Gleason score (p = 0.58), lethal PCa (metastases to distant organs, bones and PCa death) (p = 0.99), biochemical recurrence after RP (p = 0.96) or all-cause mortality (p = 0.60) [49]. In a meta-analysis including 61 studies, men with fusion-positive cancers were somewhat more likely to have advanced stage tumours (≥ T3 versus ≤ T2). Fusion status was not associated with risk of Gleason 8–10 versus Gleason 2–6 (risk ratio (RR), 0.99; 95% CI 0.86–1.13) or Gleason 7 versus Gleason 2–6 (RR, 1.05; 95% CI 0.99–1.12) [49]. These results suggested that TMPRSS2–ERG is not a strong predictive marker of disease outcome among men treated with RP. Another study, not included in the meta-analysis, assessed the fusion transcript in urinary sediment of pre-biopsy patients. In 37% of the PCa patients TMPRSS2–ERG was detected in the urine. No correlation was found between the presence of TMPRSS2–ERG transcripts and Gleason score (p = 0.511) [50]. On the other hand, results from various previous studies suggest that the presence of the TMPRSS2–ERG fusion is associated with higher tumour stage and PCa specific death. In 2007 Demichelis et al. identified a statistically significant association between TMPRSS2–ERG fusion, higher Gleason scores (p = 0.01) and PCa specific death (p b 0.01) in a group of 111 men with low stage PCa (T1a–b Nx M0). However, in this cohort TMPRSS2–ERG fusion was detected in only 15% of the PCa patients, whereas other studies documented a positive TMPRSS2–ERG fusion rate of approximately 50% [52]. In agreement with these results, a study by Attard et al. found that men with a deletion based fusion had a higher clinical stage of disease, a higher Gleason score and a worse PCa specific survival [53]. Additionally, Leyten et al. described a significant higher TMPRSS2–ERG expression in urine samples from patients with a Gleason score ≥7 (p b 0.01) and clinical tumour stage T3–4 (p = 0.003) [41]. These results suggest that TMPRSS2–ERG fusion presence might be associated with tumour stage, however, correlation with Gleason score and PCa specific death shows contradictory results. PCA3 + TMPRSS2–ERG combined biomarker panel Since PCa is a heterogeneous disease with each tumour displaying its own characteristics, a panel of biomarkers would be more suitable to improve the diagnosis of PCa. Several studies have assessed the PCA3 score in combination with TMPRSS2–ERG expression to predict prostate biopsy outcome (Table 2). In 2007 Hessels et al. described a prospective study in which they collected post-DRE urine samples from 108 prebiopsy patients for biomarker analysis. In this cohort, 72% had PCa upon biopsy. When a cut-off value of 58 was used for PCA3, 48 (62%) PCas were detected. Combining both PCA3 and TMPRSS2–ERG the number of PCas diagnosed, increased with 11% to 57 patients (73%) [50]. Laxman et al. described a study using a multiplexed model with four putative biomarkers, including PCA3 and TMPRSS2–ERG. This combination panel showed a sensitivity and specificity for PCa detection of 65.9% and 76%, respectively [54]. Another study evaluated a model including PCA3, TMPRSS2–ERG, Annexin A3 and Sarcosine for PCa diagnosis. The diagnostic accuracy of this model outperformed any of the single biomarkers (AUC 0.856 versus PCA3: 0.739, TMPRSS2–ERG: 0.732, Annexin A3: 0.728 and Sarcosine: 0.665) [55]. Furthermore, a recent study by Leyten et al. assessed the combination of urinary PCA3 and TMPRSS2–ERG to improve diagnostic accuracy in a series of 443 men of which 44% had PCa upon biopsy. Predictive values were calculated in addition to the European Randomised Study of Screening for PCa (ERSPC) risk calculator (serum PSA level, DRE abnormal/normal, TRUS abnormal/normal and prostate volume). Using these parameters, the ERSPC risk calculator alone had an AUC of 0.799 to predict PCa. This increased to 0.833 when PCA3 was added and to 0.842 when both PCA3 and TMPRSS2–ERG were added [41]. For the

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Table 2 Diagnostic performance of the PCA3 + TMPRSS2–ERG panel. References

Biomarker

Number of participants

PCa %

Cut-off value

AUC

Sensitivity %

Specificity %

PPV %

NPV %

Hessels et al. (2007) [50]

T2E PCA3 PCA3 T2E PCA3 PCA3 T2E PCA3 PCA3 T2E PCA3 PCA3 T2E PCA3 PCA3 T2E PCA3 PCA3

108

72.2

45

33.3

– 58 58 –

– – – 0.77 0.65

443

44.2

387

79.6c

– 25 25 –

128

37.5

110

44.7

– 0.72b – 0.61 0.63b 0.66 – 0.90 – 0.53 0.77 0.78f

37 62 73 67 93 80 24 83 88 – – – 46 85 94 90 90 90

93 – 50 87 37 90 93 51 50 – – – 99 99 98 4 36 56

94 – 79 71 42 80 73 89 58 – – – 96 98 96 22 74 82

36 – 42 84 92 90 61 79 84 – – – 75 92 96 54 64 72

Salami et al. (2011) [56]

Leyten et al. (2012)a [41]

Lin et al. (2013) [57]

Robert et al.(2013)d [58]

Stephan et al. (2013)e [59]

+ T2E

+ T2E

+ T2E

+ T2E

+ T2E

2.71 19.6 As above –

+ T2E

Abbreviations: PCa, prostate cancer; T2E, TMPRSS2–ERG; AUC, area under the curve; PPV, positive predictive value; NPV, negative predictive value. a For the prediction of clinically significant PCa (clinical stage ≥ T2, Gleason score ≥7, PSA density N0.15, and N33% positive cores). b Scores as a continuous variable. c Percentage of patients with PCa at repeat biopsy in an active surveillance cohort. d TMPRSS2–ERG and PCA3 assays on tissue samples. e In a repeat biopsy cohort (n = 110). f In a model including PCA3, TMPRSS2–ERG, phi, age, PSA, %fPSA, prostate volume and DRE status.

prediction of clinically significant PCa (clinical stage ≥ T2, Gleason score ≥7, PSA density N0.15, and N 33% positive cores) PCA3 alone, with a cutoff value of 25, had a sensitivity and specificity of 81% and 51%, respectively. When combined with TMPRSS2–ERG sensitivity increased to 88% without comprising the specificity of PCA3. Noteworthy however, in this cohort the diagnostic accuracy of significant PCa almost equals that of any PCa, as 90% had significant PCa [41].

patient cohorts (b 200 men) [62]. Therefore, these promising results need further validation in larger prospective patient studies conducted according to standardised, robust methodology and standards for sampling the biological material and profiling the miRNAs [63].

MicroRNA

Recent findings revealed that small tissue-derived vesicles (30–100 nm in diameter), called exosomes, are secreted by various cell types, including tumour cells, and contain a wide variety of proteins and RNAs that represent their tissue origin [64]. These exosomes can be found in various body fluids (e.g. blood, urine, semen). The presence of exosomes in urine and the fact of carrying genetic information make it a promising non-invasive substrate for biomarkers. Moreover, exosomes lack essentially all of the ribosomal RNA and thus contain mainly mRNAs and miRNAs [65]. As exosomes are the internal vesicles of multivesicular bodies it is suggested that mRNA therefore is better preserved within the exosomes compared with whole cells isolated from urine [66]. Only a few studies have assessed the role of exosomes as a PCa biomarker substrate. In 2009 Nilsson et al. for the first time described the presence of PCA3 and TMPRSS2–ERG in exosomes isolated from the urine of PCa patients [65]. Urine samples were collected for biomarker analysis before and after DRE from nine PCa patients (four untreated patients, two treated with androgen-deprivation therapy (ADT), three with verified bone metastases). In all four untreated patients, positive PSA and PCA3 mRNA levels could be detected in the exosomes after DRE, and TMPRSS2–ERG mRNA was detected in 2/4 patients. Neither of the ADT patients nor the patients with verified bone metastases had detectable PSA, PCA3 or TMPRSS2–ERG mRNA levels [65]. The latter can be explained by the finding of Mitchell et al. who described a 2-fold decrease in urinary exosome content following ADT [67]. The results of detecting PCa specific biomarkers within exosomes are promising and this substrate may offer potential in future PCa management. However, more studies are needed to gain additional knowledge about the clinical value of exosomes. Furthermore, current methods for exosome isolation are comprehensive and time consuming. Future studies might gain methodological improvement in isolating exosomes.

MicroRNAs (miRNAs) are small, non-coding single-stranded RNAs, with a length of approximately 19–23 nucleotides that play a role in cell gene expression. miRNAs have specific functions in various biological processes through their interaction with cellular mRNA, such as apoptosis and cell cycle control. miRNAs can be detected in serum, plasma, saliva and urine, and have been show to be associated with various pathological conditions, including cancer [60]. Their presence in various body fluids makes it a potential approach to obtain information about cancerous conditions in a non-invasive manner. In PCa, several miRNAs appear to have important mechanistic roles with respect to apoptosis avoidance, proliferation, epithelial-to-mesenchymal transition and development of androgen independence [61]. The small size of miRNAs is suggested to protect them from RNAse as they are also secreted within protective exosomes. A recently published study described miRNA quantification in urine samples. In 118 PCa patients and 17 healthy controls it was feasible to successfully quantify five selected miRNAs, of which miR-107 and miR-574-3p were found to be present at significantly higher concentrations in the urine of men with cancer, compared with the controls [61]. They even appeared more accurate than PCA3 normalised to urinary PSA to identify the presence of PCa [61]. Since this is the only study on PCa miRNA detection in urine to date, most studies assessed miRNA in serum and plasma. Across these studies, two miRNAs (miR-141 and miR-375) were suggested as diagnostic and prognostic markers. Elevated serum level of miR-141 has been correlated with metastatic PCa compared to local PCa, and together with miR-375 it was also associated with higher Gleason score and positive lymph node status [62]. These findings suggest that miRNAs may assist in the diagnosis and prognosis of PCa. However, detection and validation of miRNAs as a urine and serum biomarker is still at an early stage of research, and the majority of studies to date used only small

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Novel blood-based prostate cancer biomarkers With the current development and upcoming treatment options in advanced PCa, together with the fact that PSA levels may not accurately reflect disease status, the need for finding reliable indicators of disease status and predictors of therapy outcome is growing. A blood sample will be the most interesting substrate to detect these biomarkers in disseminated PCa patients. Circulating tumour cells (CTCs) The presence of circulating tumour cells (CTCs) in the peripheral blood and their role in distant metastases development have already been described in 1869, in a man with metastatic disease. More recently, a technology to enumerate CTCs from the blood received regulatory clearance from the FDA in 2004 for metastatic breast cancer patients. Subsequently, the clinical utility of the CellSearch System (Veridex LLC) has been further evaluated in patients with metastatic PCa since 2007. De Bono et al. described a correlation between the number of CTCs in 7.5 mL blood of castration-resistant prostate cancer (CRPC) patients and overall survival by using this CellSearch System [68]. They evaluated 231 patients with progressing CRPC and showed that the CTC number, defined as favourable (b5 CTCs) or unfavourable (≥5 CTCs), at different time points after treatment was the strongest independent predictor of overall survival [68]. It also showed to be more predictive than post-therapy changes in PSA. These results were confirmed in other studies by Olmos et al. and Scher et al. [69,70]. Another study however, found baseline CTCs, used as a continuous variable, to be predictive of survival, without a threshold effect [71]. To investigate treatment response, Danila et al. and Reid et al. incorporated CTC analysis within two phase II studies to assess abiraterone treatment in CRPC patients. In these studies, respectively, 34% and 41% showed conversion from unfavourable CTC count (≥5 CTCs) to favourable CTC count (b 5 CTCs) [72,73]. These findings might emphasise the CTC enumeration as a potential surrogate biomarker of therapy response and survival. Nevertheless, more trials will be required to proof their actual benefit. Molecular profiling of peripheral blood mononuclear cells (PBMCs) Through molecular profiling of CTCs, information about tumour characteristics can be gained and potentially contribute to a treatment decision. In 1994 Katz et al. already described the ability to detect PSA mRNA from the blood of PCa patients [74]. In the metastatic PCa patients 77.8% was positive for PSA mRNA and in the patients with clinically localised PCa, 38.5%. In addition, none of the 40 specimens from women or men without PCa was positive [74]. Furthermore, in 2008 Väänänen et al. examined the role of PCA3 in peripheral blood from 67 PCa patients, of which 9 had metastatic PCa. Two of the nine metastatic PCa patients had levels of PCA3 mRNA above the limit of quantification and four of the nine had positive levels of PSA mRNA [75]. A more recent study by Danila et al. assessed the role of TMPRSS2–ERG in CTCs of CRPC patients commencing abiraterone treatment. They found TMPRSS2–ERG expression in blood samples of 15 of 41 CRPC patients (37%) prior to treatment initiation. However, TMPRSS2–ERG fusion status by itself had a limited role as a predictive biomarker of sensitivity to abiraterone treatment in this cohort with post-chemotherapy treated CRPC patients [76]. Furthermore, several other genes and gene panels have been investigated in the blood of PCa patients. In a study by Liong et al. blood mRNA from North American and Malaysian PCa patients and controls was assessed to identify biomarkers for aggressive PCa. By microarray data mining and PCR data evaluation of the blood samples they were able to identify a panel consisting of seven biomarkers [77]. This panel improved PSA accuracy for the prediction of aggressive cancers.

However, results are preliminary and need validation in a multicenter clinical study containing a more extended population. Another recent study by Danila et al. described an analytic and clinical validation of a prostate cancer-enhanced mRNA detection assay in whole blood as a prognostic biomarker panel for survival. In this study they identified a 5-gene panel, consisting of KLK3, KLK2, HOXB13, GRHL2 and FOXA1, and measured these markers in blood samples from 97 metastatic CRPC patients with progressive disease [78]. The results showed that expression of at least two of the five genes was a strong prognostic factor for survival, comparable with the CellSearch System. Combining both the gene panel and the CellSearch resulted in an enhanced power to discriminate between low- and high-risk patients relative to CellSearch alone. Although the few studies that evaluated the presence of PCa specific biomarkers in peripheral blood samples used only small patient groups, results are encouraging and more extensive research is needed. Tissue markers for prostate cancer Tissue markers can be of value once prostate biopsies have been taken or prostatectomy specimen is available. Examples of markers which have been assessed for their prognostic role in PCa are Ki-67, PTEN, E-Cadherin and EZH2 [79–82]. Over the years also various other biomarkers have been identified in prostate tissue and these discoveries have led to the development of multiple commercially available genetic tests to predict PCa presence and/or PCa aggressiveness. Recent studies described the prognostic value of a predefined cell cycle progression score using the expression of 31 genes in prostate (cancer) tissue. This score was validated to have significant prognostic accuracy (pre- and postprostatectomy) and was subsequently developed into a commercial available test (Prolaris®) [83,84]. Another currently available test to identify which low-risk patients can be managed by active surveillance and which patients need immediate treatment is the Oncotype DX® PCa assay. This assay is based on a score derived from the expression of 17 genes that can predict the aggressiveness of PCa. By detecting an epigenetic field or “halo” associated with the cancerization process at the DNA level in cells adjacent to cancer foci, the commercial ConfirmMDx test can aid in the identification of highrisk men who may need to undergo repeat biopsies. Prior to the development of this test, Trock et al. evaluated the performance of DNA methylation biomarkers (APC and GSTP1) in 86 men with an initial histologically negative prostate biopsy session [85]. Since evidence so far is fairly marginal, but results seem promising, these tests and markers need further assessment. Another challenging step in this evolution will be to adapt these markers for testing and use in CRPC patients. Conclusions PSA is still the most widely used biomarker in PCa diagnosis, however, its lack of specificity has caused an increase in the number of diagnostic prostate biopsies worldwide and subsequently an increase in insignificant PCa incidence, resulting in potential overtreatment, a psychological burden to the patient and increasing health care costs. This major drawback of PSA testing and the tremendous progress that has been made in the field of molecular profiling the last decades have led to the discovery of various novel, promising biomarkers. Given the anatomical localisation of the prostate in relation to the urethra, and the fact that prostate cells can be released into the urethra by performing a DRE, urine can serve as an ideal, non-invasive, easy to obtain substrate to acquire information about biochemical processes within the prostate. Although genetic sequencing resulted in the identification of multiple promising markers, to date only few of these markers have shown to obtain characteristics to serve as a useful non-invasive urinary marker. In PCa diagnostics, two mRNA based biomarkers gained extraordinary

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interest as PCa specific markers, namely TMPRSS2–ERG and PCA3. The latter obtained FDA approval as a clinical aid tool regarding decision making in the repeat biopsy setting. Both markers showed higher specificity and diagnostic accuracy for PCa outcome compared to serum PSA, which, in clinical use, may lead to the reduction of unnecessary biopsies. Combining both markers as a urinary biomarker panel resulted in a higher diagnostic accuracy compared to the use of a single marker. Concerning the heterogeneity of the disease, the future prospect will have to be focused on the combination of biomarkers to improve the prediction of PCa upon biopsy. Another major challenge remains to accurately predict the risk of harbouring aggressive disease instead of insignificant cancer. Furthermore, finding a marker that can function as a non-invasive aid tool in the management of CRPC treatment is important. The detection of CTCs within the blood seems a promising method to predict treatment response and survival benefit. However, studies aiming to detect PCa specific biomarkers within peripheral blood mononuclear cells are also ongoing and more results in this field are to be expected. In summary, the gain of technical improvements in the last decades led to new breakthroughs in the world of PCa biomarkers and although results already seem promising so far, there are still major steps to be made. Conflict of interest All authors certify that there is no conflict of interest in relation to this manuscript. References [1] Ferlay J, Parkin DM, Steliarova-Foucher E. Estimates of cancer incidence and mortality in Europe in 2008. Eur J Cancer 2010;46:765–81. [2] Siegel R, Naishadham D, Jemal A. Cancer statistics, 2013. CA Cancer J Clin 2013;63:11–30. [3] Globocan. Prostate cancer incidence and mortality worldwide in 2008 — summary. Available at http://globocan.Iarc.Fr/factsheets/cancers/prostate.Asp. [4] Thompson IM, Pauler DK, Goodman PJ, Tangen CM, Lucia MS, Parnes HL, et al. Prevalence of prostate cancer among men with a prostate-specific antigen level b or =4.0 ng per milliliter. N Engl J Med 2004;350:2239–46. [5] Heijnsdijk EA, der Kinderen A, Wever EM, Draisma G, Roobol MJ, de Koning HJ. Overdetection, overtreatment and costs in prostate-specific antigen screening for prostate cancer. Br J Cancer 2009;101:1833–8. [6] Roobol MJ. Is prostate cancer screening bad or good? Summary of a debate at the innovation in urology meeting, September 17–19, 2010, Milan, Italy. Eur Urol 2011;59:359–62. [7] Schroder FH, Hugosson J, Roobol MJ, Tammela TL, Ciatto S, Nelen V, et al. Prostatecancer mortality at 11 years of follow-up. N Engl J Med 2012;366:981–90. [8] Catalona WJ, Partin AW, Slawin KM, Brawer MK, Flanigan RC, Patel A, et al. Use of the percentage of free prostate-specific antigen to enhance differentiation of prostate cancer from benign prostatic disease: a prospective multicenter clinical trial. JAMA 1998;279:1542–7. [9] Heidenreich A, Bellmunt J, Bolla M, Joniau S, Mason M, Matveev V, et al. EAU guidelines on prostate cancer. Part 1: screening, diagnosis, and treatment of clinically localised disease. Eur Urol 2011;59:61–71. [10] Vickers AJ, Savage C, O'Brien MF, Lilja H. Systematic review of pretreatment prostate-specific antigen velocity and doubling time as predictors for prostate cancer. J Clin Oncol Off J Am Soc Clin Oncol 2009;27:398–403. [11] D'Amico AV, Cote K, Loffredo M, Renshaw AA, Schultz D. Determinants of prostate cancer-specific survival after radiation therapy for patients with clinically localized prostate cancer. J Clin Oncol Off J Am Soc Clin Oncol 2002;20:4567–73. [12] Pound CR, Partin AW, Eisenberger MA, Chan DW, Pearson JD, Walsh PC. Natural history of progression after PSA elevation following radical prostatectomy. JAMA 1999;281:1591–7. [13] Vickers AJ, Brewster SF. PSA velocity and doubling time in diagnosis and prognosis of prostate cancer. Br J Med Psychol Surg Urol 2012;5:162–8. [14] Lazzeri M, Haese A, de la Taille A, Palou Redorta J, McNicholas T, Lughezzani G, et al. Serum isoform [−2]proPSA derivatives significantly improve prediction of prostate cancer at initial biopsy in a total PSA range of 2–10 ng/ml: a multicentric European study. Eur Urol 2013;63:986–94. [15] Le BV, Griffin CR, Loeb S, Carvalhal GF, Kan D, Baumann NA, et al. [−2]Proenzyme prostate specific antigen is more accurate than total and free prostate specific antigen in differentiating prostate cancer from benign disease in a prospective prostate cancer screening study. J Urol 2010;183:1355–9. [16] Ferro M, Bruzzese D, Perdona S, Marino A, Mazzarella C, Perruolo G, et al. Prostate health index (phi) and prostate cancer antigen 3 (PCA3) significantly improve prostate cancer detection at initial biopsy in a total PSA range of 2–10 ng/ml. PloS One 2013;8:e67687.

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