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Review

SIU-ICUD: Clinical Application of Liquid and Tissue-Based Biomarkers in Prostate Cancer

by
Tamás Fazekas
1,2,3,
Pawel Rajwa
3,4,5,
Renu S. Eapen
6 and
Derya Tilki
7,8,9,*
1
Department of Urology, Semmelweis University, 1082 Budapest, Hungary
2
Centre for Translational Medicine, Semmelweis University, 1082 Budapest, Hungary
3
Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, 1090 Vienna, Austria
4
Division of Surgery and Interventional Science, University College London, London WC1E 6BT, UK
5
Second Department of Urology, Centre of Postgraduate Medical Education, 01-813 Warsaw, Poland
6
Department of Genitourinary Oncology, Peter MacCallum Cancer Centre, Melbourne, VIC 3000, Australia
7
Martini-Klinik Prostate Cancer Center, University Hospital Hamburg Eppendorf, 20246 Hamburg, Germany
8
Department of Urology, University Hospital Hamburg Eppendorf, 20246 Hamburg, Germany
9
Department of Urology, Koc University Hospital, Istanbul 34010, Turkey
*
Author to whom correspondence should be addressed.
Soc. Int. Urol. J. 2025, 6(6), 68; https://doi.org/10.3390/siuj6060068
Submission received: 30 April 2025 / Revised: 16 October 2025 / Accepted: 27 October 2025 / Published: 10 December 2025
Versions Notes

Abstract

Several liquid-, and tissue-based markers are available to guide primary diagnosis-, active surveillance-, and treatment-related decision-making for patients with prostate cancer. Most of these tests can improve the balance of harms and benefits associated with early detection, and aid patient selection for treatment intensification. However, the costs of these tests can make their integration in routine clinical practice challenging. To date, prostate-specific antigen (PSA) is still one of the most well-known and widely utilized tumor markers worldwide, with a unique facility ranging from the diagnosis to the treatment-related follow-up of patients with prostate cancer. Future research efforts are needed to integrate biomarkers and novel imaging techniques, such as prostate magnetic resonance imaging, in the decision-making pathways. Despite the growing body of knowledge and evidence, considerable challenges remain in optimizing risk-stratification, improving patient selection and cost-efficacy in different prostate cancer (PCa)-related settings.

1. Introduction

Prostate cancer (PCa) is the second most prevalent malignancy, and the sixth leading cause of cancer-related death among men, placing a significant socioeconomical burden on health care systems [1]. Consequently, since the beginning of modern medicine, the development of predictive and prognostic biomarkers aiming to optimize and guide early detection and disease management of PCa have been in the focus of translational research. As a result, several commercially available liquid-, or tissue-based markers have been introduced in clinical practice aiming to guide primary diagnosis-, active-surveillance-, and treatment-related decision-making. However, despite the evolving number of biomarkers, most of them never get translated to everyday clinical practice, due to their poor efficacy, lack of validation, or unfavorable cost-effectiveness. The aim of this narrative review is to summarize the most important clinically validated liquid, and tissue-based biomarkers aiding decision-making in various stages of localized PCa (Table 1).

2. Biomarkers Aiding Primary Diagnosis

2.1. Blood-Based Markers

2.1.1. Prostate-Specific Antigen

Prostate-specific antigen (PSA) is a serine protease enzyme and is secreted by both prostate epithelial cells and malignant prostatic tissue into blood, urine and semen [2]. It was approved by the Food and Drug Administration (FDA) for the purpose of disease monitoring and as a diagnostic tool in 1986 and 1994, respectively, [3]. Since then, it has been one of the most widely used biomarkers worldwide.
Importantly, PSA is not tumor specific; many benign processes such as inflammation, benign prostatic hyperplasia (BPH), trauma, sexual intercourse may lead to elevated PSA levels. It is strongly associated with prostate size and age of the patient and affected by hormonal agents such as finasteride and dutasteride [4]. Moreover, due to the variety and instability of its isoforms in the serum, reliably measuring the analyte can be challenging [5]. Considering these challenges, it is not surprising that defining a clear, generalizable cut-off value, capable of predicting PCa is not possible, which can make the interpretation of a PSA value complicated. The sensitivity and specificity of PSA depend on the population (screening-like or symptomatic patients) and the applied cut-off for biopsy indication among others. In a systematic review and meta-analysis of 14,489 symptomatic patients, the pooled sensitivity and specificity of PSA for PCa detection was 0.93 (95% Confidence Interval [CI] 0.88–0.96) and 0.20 (95% CI 0.12–0.33), respectively. Historically, a PSA level of 4 ng/mL was widely accepted as the cut-off to predict the presence of PCa [6,7,8]. However, 20% of PCa patients have a PSA lower than 4 ng/mL and applying this PSA cut-off in PCa screening leads to unnecessary biopsies, overdetection and overtreatment [9,10]. Based on the results of the European Randomized Screening for Prostate Cancer (ERSPC) trial, discrimination at PSA level of 3 ng/mL is the most widespread cut-off and therefore recommended in early-detection by the European Association of Urology (EAU) guidelines [11]. Considering the strong correlation of PSA with age, age-specific PSA cut-offs can also help clinical decision-making such as biopsy selection and re-invitation for screening [12]. Based on EAU guidelines, men with a PSA level of >1 ng/mL at 40 years and with a PSA level of >2 ng/mL at 60 years are considered at-risk, therefore should be offered a 2-year follow-up interval for screening. Contemporary PCa screening strategies use PSA as a primary screening tool, although followed by a reflex test, such as prostate magnetic resonance imaging, other biomarkers, or risk-calculators to refine patient selection for prostate biopsy [13]. However, the use of PSA in the early detection of PCa is unquestionable.
To overcome the inherent limitations of PSA, several other PSA-based metrics were employed, with prostate-specific antigen density (PSAD) being the most useful in clinical practice. PSAD is the ratio of serum PSA level and the prostate volume, and a strong predictor of clinically significant disease (above 0.15 ng/mL/cc) [14,15]. Therefore, PSAD is extensively used in PCa risk calculators. Moreover, elevated values indicate prostate biopsy even in the case of negative magnetic resonance imaging (MRI) results; however, precisely measuring the prostate volume can be challenging [16].

2.1.2. Prostate Health Index (PHI)

The PHI is a three kallikrein-based immunoassay, combining total PSA, free PSA and [-2]proPSA into a single score aiming to lower biopsy indications and improve clinically significant PCa detection. It was approved by the FDA in 2012 for men over 50, with normal rectal exams and PSA level between 2 and 10 ng/mL. PHI has been proven to offer better diagnostic accuracy than total PSA or free to total ratio [17,18]. Moreover, PHI has shown to be able to predict high grade disease, and a strong ability to avoid unnecessary biopsies, overdetection and overtreatment [17,18]. Notably, PHI does not depend on age or prostate volume, highlighting its value in PCa detection [17]. In the study by Tosoian et al., by using PHI, up to 38% of unnecessary biopsies could be avoided while missing 2% of significant cancers [19].
Integrating PHI in predictive models and nomograms in combination with MRI results is a promising option to enhance the accuracy of detecting PCa, especially in patients considering repeat biopsies [20].

2.1.3. 4K Score

Similarly to the PHI, the 4K score comprises four kallikrein assays including free PSA, intact PSA, total PSA, and human kallikrein 2 (hK2) and additionally integrating clinical variables (age, digital rectal exam [DRE], previous biopsy) to predict clinically significant PCa. Several studies have shown its utility in improving PCa diagnostics with reducing unnecessary biopsies and overdiagnosis [21,22,23]. In the ERSPC cohort, incorporating the 4K score to PSA and age significantly improved predictive accuracy (area under the curve [AUC] 0.78 vs. 0.70) [21]. A comparative analysis of the 4K score and PHI was conducted in a population-based cohort study of 531 men with PSA 3–15 ng/mL by Nordström et al. [24]. The two tests performed similarly in predicting both any (4K score AUC 69, PHI AUC 70.4) and high grade (4k score AUC 71.8, PHI AUC 71.1) PCa [24]. The 4K score has been evaluated in the repeat biopsy setting as well [25]. In an ERSPC cohort of 925 men, Gupta et al. found higher accuracy of the 4K score than either PSA and DRE alone (AUC 0.68 vs. 0.58, p < 0.001) in detecting PCa on repeat biopsy [25].
Despite the weak level of evidence, both the PHI and 4Kscore are mentioned by EAU, the American Association of Urology (AUA), and the National Comprehensive Cancer Network (NCCN), as promising markers in the early detection.

2.1.4. Stockholm3 (STHLM3)

The Stockholm3 test is a complex prediction model integrating several clinical variables, serum markers, and a polygenic risk score for predicting clinically significant PCa [26,27]. In combination with MRI, it has shown to decrease clinically insignificant PCa detection and the number of MRI scans in population-based screening [26,27]. The associated costs arising from the complexity of the test could limit its widespread use, although a microsimulation study has shown the test to be cost-effective in the Swedish health care system [28,29]

2.2. Urine-Based Markers

2.2.1. Progensa Prostate Cancer Antigen 3

Prostate Cancer Antigen 3 (PCA3) is a non-coding RNA molecule, overexpressed in PCa cells compared to benign epithelial tissue [30]. It can be measured in urine sediments collected after prostate massage during a digital rectal exam, using the Progensa assay, and its expression has shown to be unaffected by prostate size or PSA levels in the blood [30,31]. To date, Progensa is the only FDA-approved urine-based test to aid decision-making in the primary and repeat biopsy setting. A prospective validation trial of 859 patients by Wei et al. aimed to assess the diagnostic accuracy of PCA3 both in the initial and repeat biopsy setting [32]. The authors demonstrated a positive predictive value of 80% upon initial and a negative predictive value of 88% at repeat biopsy, respectively, [32].
Considering the favorable predictive utility of the test in various clinical settings, clinical practice guidelines support the use of urinary PCA3 to risk stratify patients both in the primary and repeat biopsy setting.

2.2.2. Select MDX

The Select MDX test is based on the combination of mRNA levels of two genes from the urine, obtained after prostate massage, and clinical parameters such as age, family history, previous negative biopsies and DRE findings [33]. The test is capable of predicting both the presence of PCa and high-risk disease [33]. It has shown to have similar performance to MRI in terms of clinically significant PCa detection and to be a valuable tool after an initial negative (Prostate Imaging Reporting and Data System [PI-RADS] 1-3) MRI, as it led to a 45.8% decrease in the number of biopsies [34]. However, the added value of SelectMDx in the MRI era remains unclear [35].

2.3. Tissue-Based Markers

ConfirmMDx (MDx Health, Irvine, CA, USA)

Epigenetic changes related to PCa are thought to have a “field effect”, therefore hints of PCa can be observed in otherwise morphologically normal tissue adjacent to tumor tissue [36]. This is utilized by ConfirmMDx, a molecular test using methylation profiling of three known epigenetic markers (GSPT1, APC, RASSF1) of PCa [37,38]. The assay was developed to aid the decision-making of patients with prior negative biopsy in the repeat-biopsy setting, and is based on formalin-fixed, paraffin-embedded (FFPE) prostate tissue obtained during biopsy [37]. The Detection of Cancer Using Methylated Events in Negative Tissue (DOCUMENT) and Methylation Analysis To Locate Occult Cancer (MATLOC) trials followed by two meta-analyses combining their cohorts by Partin and van Neste et al. validated ConfirmMDx in the repeat-biopsy setting [37,38,39,40]. Interestingly, despite NCCN guidelines considering ConfirmMDx as a useful tool in the repeat biopsy setting, current EAU guidelines do not mention the utility of the test at all [41,42].

3. Available Assays for Guiding Active Surveillance or Definitive Treatment

3.1. Prolaris

Prolaris® (Myriad Genetics, Inc., Salt Lake City, UT, USA), is a combination of Cancer of the Prostate Risk Assessment (CAPRA) risk score and a cell cycle progression score (CCP) (range: −3 to +3) based on an mRNA-based gene panel, consisting of 15 housekeeping, and 31 genes involved in proliferation [43]. The mathematical combination of CAPRA and CCP score results in the cell cycle risk score (CCR), with higher values conferring to more aggressive disease [44]. The assay is a robust prognosticator of biochemical recurrence, metastasis-free, and cancer-specific survival and has been validated in several studies [44,45,46,47,48]. In the study by Bishoff et al., the CCP score was found to be a strong predictor of both biochemical recurrence (BCR) (hazards ratio (HR)/CCP unit 1.47, 95% CI 1.23–1.76, p = 4.7 × 10−5) and metastatic disease (HR/CCP unit 4.19, 95% CI 2.08–8.45, p = 8.2 × 10−6) [45]. In a cohort of 1062 men who underwent definitive treatment for PCa, the CCP score was shown to be predictive of metastatic disease at 10 years (hazard ratio [HR]/CCP score  =  2.21; 95% CI 1.64, 2.98 p = 1.9 × 10−6) [46]. Recently, Tward et al., found the CCR score as a promising tool in patient selection for multimodal treatment in a cohort of 718 intermediate- and high-risk PCa patients [48]. Importantly, the Prolaris test with CCP score has shown to directly affect real-life clinical decision-making. In the study by Shore et al., utilizing Prolaris changed 47.8% of treatment decisions, with 72.1% and 26.9% reduction and intensification of treatment, respectively [49].
The assay is recommended by NCCN for low-, favorable- and unfavorable-intermediate, as well as high-risk patients with a 10-year life-expectancy as an initial risk stratification tool in the pre-treatment setting [42]. In contrast, the current EAU guideline does not recommend the routine use of the test for allcomers, but for selected men such as those with favorable intermediate-risk PCa who are candidates of active surveillance (AS) [41].

3.2. OncotypeDx Genomic Prostate Score

OncotypeDx Genomic Prostate Score® (Genomic Health, Redwood City, CA, USA), or shortly GPS (scaled 0–100), is intended for men with very low-, low-risk, and favorable intermediate-risk NCCN risk category PCa to help patient selection for immediate or deferred treatment [42]. It is based on the expression analysis of five housekeeping reference genes, and 12 genes involved in different biological pathways associated with PCa recurrence and metastatic potential [50].
In 2014, Klein et al., conducted a complex, three-stage study for predicting adverse pathology (primary Gleason pattern 4 or any pattern 5 and/or ≥pT3) in patients eligible for AS [51]. Using decision curve analysis, a greater net benefit was observed for a model composed of GPS and CAPRA, than for any single clinical variable [51]. In a study of 402 NCCN very low-, low-, and intermediate-risk patients by Cullen et al., the GPS increase per 20 units was associated with BCR [52]. In the two low-grade (3 + 3 and 3 + 4) cohorts, the GPS was validated and established as an independent predictor for adverse pathology [52]. Similarly, in the cohort of 215 men undergoing AS by Kornberg et al., a higher GPS (per 5 units) was associated with biochemical recurrence (HR 1.10, 95% CI 1.00–1.21 p = 0.04) and adverse pathology (HR 1.16, 95% CI 1.06–1.26 p < 0.01) [53]. Interestingly, in a multicenter study of 432 patients undergoing AS, Lin et al. did not find an association of GPS scores with either upgrading upon biopsy (p = 0.48) or adverse pathology (HR 1.85, 95% CI 0.99–4.19 p = 0.066) when adjusted for multiple clinical variables [54]. The impact of GPS-testing on decision-making was analyzed by Eure et al., in patients qualifying for both AS and immediate treatment [55]. Patients with—compared to without—GPS test results were more likely to undergo AS by 22% (55% relative difference) and stay on AS at 1 year (55% vs. 34%) [55]. Notably, 96% of doctors and 92% of patients confirmed the usefulness of the genomic assay [55].
A cost-effectiveness analysis in the US identified that utilization of GPS led to decreased aggregate health care costs (average USD 2286 per patient, including the cost of the GPS of USD 4520) for men with NCCN very low-risk and low-risk PCa in the first 180 days [56]. Moreover, GPS was considered useful and informative in decision-making in 90% of cases [56].
According to the NCCN guideline, OncotypeDx can be considered after positive biopsy for additional risk stratification of very low-, low-, and favorable intermediate-risk PCa patients with at least a 10-year life expectancy [42].

3.3. Decipher (GenomeDx, Vancouver, Canada)—After Prostate Biopsy

The Decipher® (GenomeDx Biosciences, Inc., Vancouver, BC, Canada) is a 22-RNA genomic classifier (GC) test, which was initially developed to predict early metastasis after radical prostatectomy [57]. The GC risk score is a continuous value between 0 and 1, and is based on genes contributing to cellular differentiation, adhesion, motility, cell cycle, androgen signaling pathway, and immune modulation [58]. Every 0.1 increase in GC score represents a 10% increase in metastatic risk, and a score of >0.6 is considered high risk for disease progression [59]. The utility of biopsy as a source of tissue for the Decipher test was validated in a large, multicenter study by Nguyen et al., who confirmed the biopsy-based GC as an independent predictor of 5 yr metastasis irrespective of primary therapy (radical prostatectomy [RP] or external beam radiation therapy [EBRT]+/-Androgen Deprivation Therapy [ADT]) [60]. Low, intermediate, and high GC scores were associated with 0%, 0%, and 9.4% 5-year PCa-specific mortality, respectively, [60]. Herlemann et al. studied the association between a biopsy-based GC score in men with NCCN very low-, low- and favorable-intermediate risk and adverse pathology findings (grade group [GG] 3−5, ≥pT3b, lymph node invasion) upon radical prostatectomy [61]. Decipher results were found to be different in patients with and without adverse pathology findings upon radical prostatectomy (0.38 vs. 0.30, p = 0.016) [61]. The impact of Decipher on everyday practice has been evaluated by Zaorsky et al., in a study based on the Surveillance, Epidemiology, and End Results (SEER) database of men with PCa [62]. Clinical characteristics and outcomes of 8927 patients who underwent the GC test were studied [62]. In the real-world setting, the uptake of AS or WW was higher among patients tested with GC (odds ratio [OR] = 2.21, 95% CI 2.04–2.38 p < 0.001) [62]. Moreover, in patients with NCCN low- or favorable-intermediate risk, higher GC was associated with a higher likelihood of local treatment (OR = 4.79, 95% CI 3.51–6.55, p < 0.001) [62]. In the multicentric real-world cohort of 855 patients on AS, Vince et al. confirmed a strong correlation of higher Decipher scores with time to curative treatment (HR 2.51, 95% CI 1.52–4.13, p < 0.001) [63].
The assay is recommended for low-, favorable- and unfavorable-intermediate, as well as high-risk patients with a 10-year life-expectancy as an initial risk stratification tool in the pre-treatment setting by NCCN [42].

4. Available Assays for Guiding Adjuvant Therapy

4.1. Decipher (GenomeDx, Vancouver, Canada)—After Radical Prostatectomy

Decipher was initially developed to predict early metastasis after radical prostatectomy, based on tissue obtained during surgery by Erho et al. [58]. In the nested case–control study with a long follow-up (median 16.9 years), a high GC score (>0.5) was associated with shorter PCa-specific (median 2.9 years vs. 6.9 years) and overall survival (median 2.5 years vs. 4.98 years) after developing metastasis [58]. Cooperberg et al. analyzed the association between the post-RP GC, Cancer of the Prostate Risk Assessment Postsurgical (CAPRA-S) scores, and the PCa-specific mortality in 185 high-risk patients (median follow-up 6.44 years) [64]. Both the GC and CAPRA-S were identified as independent predictive factors [64]. A high GC (≥0.6) was associated with an estimated incidence of metastasis in 30% and a CAPRA-S score ≥ 6 was associated with a 13% incidence at 10 years, respectively, [64]. An important individual patient-level meta-analysis of 855 men undergoing radical prostatectomy by Spratt et al. confirmed the independent utility of GC in predicting metastasis (HR 1.30 95% CI 1.14–1.47 p < 0.001) [65].
Recently, several ancillary studies of high-quality trials tested the risk stratification capability of Decipher [66]. In the patient cohort of 226 patients after RP with biochemical recurrence from the SAKK 09/10 randomized controlled trial (RCT) (median follow-up 6.3 years), GC has been shown to be associated with both biochemical (HR 2.26 95% CI 1.32–3.98 p = 0.003) and clinical progression (HR 2.99 95% CI 1.55–5.76 p = 0.001) [66]. Moreover, in the ancillary study of the phase 3 RCT NRG/RTOG 9601, GC results (per 0.1 unit) were independently associated with distant metastases (HR 1.17 95% CI 1.05–1.32 p = 0.006), PCa-specific mortality (HR 1.39, 95% CI 1.20–1.63, p < 0.001) and OS (HR 1.17, 95% CI 1.06–1.29, p = 0.002) [67]. The effect of GC on decision-making has been evaluated in several studies, [68,69]. For example, adjuvant and salvage radiotherapy were modified by the results of GC in 43%, and 53% of cases, respectively, [70]. In the PRO-IMPACT study, a cohort of patients who underwent radical prostatectomy and were considered for either adjuvant (n = 150) or salvage (n = 114) radiotherapy, thirty-seven percent of high-risk PCa patients were advised to intensify their treatment, after obtaining their GC results, [68]. A recommendation to remain in the observational protocol was increased in the low-risk Decipher score group in the salvage arm (63% to 74%), [68]. In the study by Zaorsky et al., assessing the SEER database, high GC scores were associated with the use of radiation after prostatectomy (OR = 2.69, 95% CI 1.89–3.84) [62].
Based on the growing body of evidence on the outstanding prognostic and predictive utility of Decipher, current NCCN guidelines state that GC can be considered as part of counseling for risk stratification in patients with PCa after radical prostatectomy [42].

4.2. Decision-Making Tools Based on Artificial Intelligence

Artificial intelligence (AI) tools aiding clinical decision-making have been extensively studied recently [71,72]. The multimodal deep learning model by Esteva et al. was developed and trained on histopathologic data of 5654 patients (median follow-up 11.4 years) from five phase 3 RCTs assessing radiotherapy for localized PCa (NRG/RTOG-9202, 9408, 9413, 9910, and 0126) on six binary outcomes (5- and 10-year distant metastasis, biochemical failure-free survival, 10-year PCa-specific survival, 10-year overall survival) [72]. In a validation cohort of patients (20% of participants from each trial), the model outperformed NCCN risk stratification in terms of prediction of all the outcomes (relative improvement in AUC ranging from 9.2% to 14.6%) [72]. In a further study, Spratt et al. used an AI-based predictive model based on digitalized histology images and data from four phase 3 RCTs (NRG 9202, 9413, 9910, and 0126) [71]. The model was validated on the data of 1594 NCCN intermediate-risk PCa patients from the NRG/RTOG 9408 study (median follow-up 14.9 years). The AI-based prediction model was able to accurately discriminate between patients who can benefit from treatment intensification with androgen deprivation therapy [71]. These results underline the outstanding efficacy and abundant number of clinical implications of AI-based models in decision-making during the work-up of localized PCa; however, further prospective data and validation are required to enable widespread clinical implementation.

5. Conclusions and Future Perspectives

Several liquid-, or tissue-based markers are available to guide primary diagnosis-, active-surveillance-, and treatment-related decision-making for patients with PCa. Most of these tests are capable of improving the balance of harms and benefits associated with PCa early detection and aiding patient selection for treatment intensification. However, the costs of the tests can make their integration in routine clinical practice challenging. Moreover, most of the above-mentioned markers lack validation in men across different ethnicities limiting their wide-scale interpretability and utilization. Therefore, validation of diagnostic biomarkers in men with different ethnical background is of utmost importance. Further limitations include the following: (1) most of the biomarkers are based on retrospective studies or small cohorts, limiting their external validity; (2) the lack of standardization in the interpretation of some biomarkers can lead to clinical inconsistencies; (3) considering the scope and type of our study, selection may be affected by publication/selection bias.
To date, PSA is still one of the most well-known and widely utilized tumor markers worldwide, with a unique facility ranging from the diagnosis to the treatment-related follow-up of patients with PCa. Future research efforts are needed to integrate biomarkers and novel emerging imaging techniques, such as prostate MRI and prostate-specific membrane antigen-positron emission tomography/computed tomography (PSMA-PET/CT). Despite a growing body of knowledge and evidence, considerable challenges remain in optimizing risk-stratification and patient selection in different PCa-related settings.

Author Contributions

Conceptualization, T.F. and D.T.; methodology, T.F.; investigation, T.F. and R.S.E.; writing—original draft preparation, T.F., R.S.E., P.R. and D.T.; writing—review and editing, R.S.E. and D.T.; visualization, T.F.; supervision, D.T. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
GGGrade group
CAPRA-SCancer of the Prostate Risk Assessment Postsurgical
PCaProstate cancer
MRIMagnetic resonance imaging
PSMAProstate-specific membrane antigen
CTComputer tomography
HGHigh grade
GSGleason score
DREDigital rectal examination
EAUEuropean Association of Urology
NCCNNational Comprehensive Cancer Network
AUAAmerican Association of Urology
PSAProstate-specific antigen
BPHBenign prostatic hyperplasia
ERSPCEuropean Randomized Screening for Prostate Cancer
PHIProstate Health Index
hK2Human kallikrein 2
STHLM3Stockholm3
PCA3Prostate Cancer Antigen 3
FFPEFormalin-fixed, paraffin-embedded
CAPRACancer of the Prostate Risk Assessment
CCPCell cycle progression
CCRCell cycle risk
GPSGenomic Prostate Score®
GCGenomic classifier
SEERSurveillance, Epidemiology, and End Results
AIArtificial Intelligence
FDAFood and Drug Administration
CIConfidence interval
AUCArea under the curve
PI-RADSProstate Imaging Reporting and Data System
DOCUMENTDetection of Cancer Using Methylated Events in Negative Tissue
MATLOCMethylation Analysis To Locate Occult Cancer
BCRBiochemical recurrence
ASActive surveillance
RPRadical prostatectomy
EBRTExternal beam radiation therapy
ADTAndrogen Deprivation Therapy
HRHazards ratio
OROdds ratio
RCTRandomized controlled trial
PSMA-PET/CTProstate-specific membrane antigen-positron emission tomography/computed tomography

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Table 1. Overview of biomarkers in prostate cancer.
Table 1. Overview of biomarkers in prostate cancer.
Clinical IndicationTestStage of ManagementDescriptionSample Used for Test
PrediagnosisProstate-specific Antigen (PSA)Initial and repeat biopsyTotal PSASerum
Prostate Health Index (PHI)Initial and repeat biopsyTotal and free PSA, [-2]proPSASerum
4K scoreInitial and repeat biopsytotal, free, and intact PSA, human kallikrein 2Serum
Stockholm3 (STHLM3)Initial biopsyTotal and free PSA, human kallikrein 2, macrophage inhibitory cytokine-1, microseminoprotein-β, polygenic risk scoreSerum
Progensa Prostate Cancer Antigen 3 (PCA3)Initial and repeat biopsyPCA3 non-coding RNAPost-Digital Rectal Exam (DRE) urine
Select MDXDetection of High grade (HG) prostate cancer (PCa) on initial and repeat biopsyHOXC6, DLX1, KLK3 mRNAPost-DRE urine
ConfirmMDxDetection of any- and HG (Gleason Score [GS] > 7) PCa on repeat biopsyMethylation intensity of GSTP1, APC and RASSF1, relative to ACTBNegative biopsy tissue
Active surveillance vs. TreatmentProlarisPost biopsy confirmed National Comprehensive Cancer Network (NCCN) low- to high-risk patients.46 gene mRNA assay (31 cell cycle progression, 15 housekeeper)
Cell Cycle Progression (CCP) score (−3 to +3)		Formalin-Fixed, Paraffin-Embedded (FFPE) from biopsy or radical prostatectomy tumor tissue
Oncotype DxPost biopsy confirmed NCCN low- to favorable intermediate-risk patients17 gene mRNA assay (12 PCa-related, 5 reference)
Genomic Prostate Score (GPS) (0 to 100)		FFPE from biopsy tumor tissue
Decipher—post biopsyPost biopsy confirmed NCCN low- to high-risk patients22 gene mRNA panel
(all PCa-related)
Genomic classifier (GC) score (0–1)		FFPE from biopsy tumor tissue
Adjuvant treatment intensificationDecipher—post radical prostatectomyPost radical prostatectomy risk stratification22 gene mRNA panel
(all PCa-related)
GC score (0–1)		FFPE from radical prostatectomy tumor tissue
Artificial intelligencePost biopsy risk stratification before radiationDeep learning-based model using histopathological data (digital image)FFPE from biopsy
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Fazekas, T.; Rajwa, P.; Eapen, R.S.; Tilki, D. SIU-ICUD: Clinical Application of Liquid and Tissue-Based Biomarkers in Prostate Cancer. Soc. Int. Urol. J. 2025, 6, 68. https://doi.org/10.3390/siuj6060068

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Fazekas T, Rajwa P, Eapen RS, Tilki D. SIU-ICUD: Clinical Application of Liquid and Tissue-Based Biomarkers in Prostate Cancer. Société Internationale d’Urologie Journal. 2025; 6(6):68. https://doi.org/10.3390/siuj6060068

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Fazekas, Tamás, Pawel Rajwa, Renu S. Eapen, and Derya Tilki. 2025. "SIU-ICUD: Clinical Application of Liquid and Tissue-Based Biomarkers in Prostate Cancer" Société Internationale d’Urologie Journal 6, no. 6: 68. https://doi.org/10.3390/siuj6060068

APA Style

Fazekas, T., Rajwa, P., Eapen, R. S., & Tilki, D. (2025). SIU-ICUD: Clinical Application of Liquid and Tissue-Based Biomarkers in Prostate Cancer. Société Internationale d’Urologie Journal, 6(6), 68. https://doi.org/10.3390/siuj6060068

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