From prostate specific antigen to genomic signatures: Advances in biomarkers for prostate cancer diagnosis and prognosis

Highlight

• •Provides a comprehensive update on traditional and emerging biomarkers for prostate cancer detection and prognosis.
• •Highlights advanced molecular and genomic tools (PCA3, 4Kscore, PHI, GPS, Decipher, CTCs) that improve diagnostic precision.
• •Discusses key genetic alterations (BRCA1/2, PTEN, HOXB13, ERG fusion) driving prostate carcinogenesis and disease progression.
• •Emphasizes the role of biomarkers in enabling earlier diagnosis and personalized management of prostate cancer.

Abstract

Prostate cancer is one of the most prevalent malignancies affecting men worldwide. It arises from the uncontrolled proliferation of abnormal cells within the prostate gland, an essential component of the male reproductive system, and exhibits highly variable clinical behaviour, ranging from indolent, localised tumours to aggressive, metastatic disease. Early detection significantly improves treatment outcomes and survival rates, emphasising the urgent need for more sensitive and specific diagnostic approaches.

This review provides a comprehensive overview of diagnostic and prognostic biomarkers associated with prostate cancer, highlighting their potential in early detection and disease monitoring. Traditional biomarkers such as digital rectal examination (DRE), prostate-specific antigen (PSA), prostatic acid phosphatase (PAP), and alkaline phosphatase (ALP) are discussed alongside emerging molecular markers that offer enhanced accuracy and predictive value. These include PCA3, SelectMDx, ExoDx Prostate (EPI), bone-specific ALP (BALP), 4Kscore, circulating tumour cells (CTCs), prostate health index (PHI), Oncotype DX Genomic Prostate Score (GPS), Decipher test, and ERG gene fusion.

Additionally, the review addresses key genetic alterations implicated in prostate carcinogenesis, including mutations in BRCA1/2, HOXB13, and PTEN deletions, as well as changes in the androgen receptor pathway. By evaluating recent advancements and applications of these biomarkers, this review aims to enhance understanding of their role in improving early diagnosis, prognosis, and personalised management of prostate cancer.

Graphical abstract

Introduction

Prostate cancer is one of the most common cancers among men, ranking second globally in prevalence, with approximately 1.1 million new cases diagnosed in 2012 [1]. In some cases, the disease may progress slowly, making it easily manageable, while in others, it may be aggressive and rapidly spreading. Although traditional diagnosis relies on the prostate-specific antigen (PSA) test, clinical examination, and tissue biopsies, these methods often fail to distinguish between aggressive and low-risk tumours accurately, highlighting the urgent need for more precise and analytical biomarkers [2].

In recent years, the effectiveness of the PSA test in the early detection of prostate cancer has been the subject of much debate [3], with several studies indicating that it often leads to overdiagnosis and unnecessary treatment. This underscores the importance of developing biomarkers capable of differentiating between low- and high-risk cases, reducing the number of unnecessary biopsies and the psychological impact of low-risk diagnoses [4]. While several biomarkers are available, including urinary (PCA3, SelectMDx), haematological (4Kscore, PHI), and tissue (ConfirmMDx) tests, clinical research comparing these biomarkers and evaluating their clinical utility remains limited.

Furthermore, most studies show racial disparities, with African American men comprising less than 10 % of participants despite having a 1.7 times higher incidence rate and a 2.1 times higher mortality rate compared to white men [5,6]. This is a significant gap that must be taken into account when evaluating the reliability of biomarkers across diverse populations.

Biomarkers play a crucial role in the diagnosis and management of prostate cancer, aiding in detection, prognosis prediction, and disease progression monitoring. These biomarkers can be categorised as traditional and emerging [7]. Traditional biomarkers particularly PSA have been the cornerstone of early detection, but they often lack the precision to differentiate between aggressive and non-aggressive cancer. This has led to increased interest in developing new biomarkers that offer higher accuracy and selectivity, particularly in low-risk cases or for differentiating between benign and malignant conditions [8].

Emerging biomarkers, which include genetic signatures, molecular assays, protein markers, and advanced imaging techniques, represent the next generation of precision oncology tools. These biomarkers have the potential to support personalised disease risk assessment and guide treatment decisions. With the rapid advancements in genomics, proteomics, and molecular biology, these tests are expected to contribute even more to improved clinical decision-making and more accurate prognostic prediction [9].

This review aims to provide a comprehensive analysis of the evolution of biomarkers in prostate cancer, from traditional markers to the most advanced molecular and genetic approaches. Unlike descriptive reviews, this work focuses on comparing biomarkers, evaluating their clinical utility, and highlighting current challenges, including racial disparities, overdiagnosis, economic challenges, and the integration of biomarkers into clinical practice. By tracing the development of these tools and relating them to the clinical context, this review aims to illustrate how biomarkers can be integrated into early detection, risk assessment, and the development of personalised treatment strategies in prostate cancer.

Physical examination for prostate cancer

Digital rectal examination (DRE) is a simple, inexpensive, ancient, and familiar physical test that is routinely used for prostate cancer screening [10]. It was the most abundant technique in determining prostate problems. It is essential for providing a tactile assessment of the texture, size, and consistency of the prostate gland, as well as for distinguishing between benign prostatic enlargement, inflammation, and cancer. DRE remains critical for symptom assessment, patient triage, and disease staging within individualised diagnostic pathways [11].

The studies revealed that while DRE has a positive predictive value (PPV) of about 21 %, comparable to the roughly 22 % observed with Prostate-Specific Antigen (PSA), its actual effectiveness in detecting cancer is significantly lower. In practice, DRE identifies cancer in only about 1 % of cases, whereas PSA detects it in approximately 3 % [12].

Even when both tests are administered together, there is no substantive improvement in detection. These findings are based on prospective studies, including randomised controlled trials and diagnostic accuracy studies, which, despite their rigorous design, are not immune to limitations such as inter-observer variability and the inherent challenges in comparing a subjective physical examination with an objective laboratory test [13].

For many men, the thought of undergoing a DRE can evoke discomfort and sensitivity. Given its limited benefit, especially in individuals without symptoms, this new evidence encourages us to reassess whether DRE should continue to play a central role in screening practices [14]. Studies indicate that digital rectal examinations do not reduce mortality. Conversely, it may lead to numerous false-positive results, resulting in unnecessary diagnostic testing. Furthermore, DRE has low sensitivity in detecting PCa, and it can cause various adverse effects, including pain, erectile dysfunction, urinary incontinence, and overuse of prostate cancer treatments [15,16].

Classification based on clinical Scenario and utility

Biomarker for initial detection

Blood-based biomarker

• ➢Prostate Specific Antigen (PSA):

Prostate Specific Antigen (PSA) is a Serine Proteas encoded by Kallikrein 3 gene located on chromosome 19q13.3-13.4. PSA, which was first identified as a marker for human semen, received FDA approval in 1994 for use in the diagnostic screening of prostate cancer [17].

Since the 1980s, the PSA test has helped in detecting many cases of prostate cancer in their early stages, giving men the opportunity for rapid intervention and treatment [18]. It is one of the most crucial cancer biomarkers because it is widely accessible, inexpensive, and clinically simple to interpret, and it can be used in risk stratification and monitoring. All phases of prostate cancer treatment, including screening, recurrence risk classification, post-diagnosis surveillance, and therapy monitoring, use PSA [19,20].

Other biomarkers that increase PSA accuracy include the Prostate Health Index (PHI), the 4K score, and multigene signatures [18].

The PSA test has many drawbacks despite its advantages, as not all raised PSA values are a sign of cancer; some men may feel excessively anxious because of elevated levels that are caused by benign illnesses like prostatitis or an enlarged prostate. So it can lead to false-positive results [21].

PSA is not accurate in diagnosis because PSA levels may be normal even in advanced cases of prostate cancer, which delays diagnosis and treatment. A slow-growing, low-risk tumor cannot be accurately distinguished from an aggressive, high-risk tumor with the PSA test alone. The issue of overdiagnosis and overtreatment is directly influenced by this inability [22].

• ➢Prostatic Acid Phosphatase test (PAP):

It is an enzyme that is mostly present in prostate cells, and it is an official mark of differentiation unique to the prostate. It was first discovered in semen at high levels. Studies have shown that individuals diagnosed with prostate cancer, especially those with metastatic spread to the bones, had noticeably higher blood levels of it [23].

Hormones such as androgens have been demonstrated to influence PAP. PAP expression is influenced by a few variables, including Epidermal Growth Factor (EGF) and TGF-β1, and it can be controlled without the help of androgens [24].

Especially when the illness is advanced and showing signs of resistance to hormonal treatment, PAP has an essential part in both diagnosing and tracking the course of prostate cancer [25].

In the 1940s, researchers found that there was a significant relationship between the dimensions of the prostate tumor and the blood level of PAP. PAP is still regarded as a significant biomarker and is used to predict chemotherapy failure and clinical recurrence of cancer, particularly following radical prostatectomy [26].

According to recent research, CPAP may be useful in treating prostate cancer. In animal models, it has been used to inject tumors, slowing their growth. To elicit an immune response against prostate cancer cells, a vaccination based on PAP has been developed [27]. One immunotherapy that targets PAP is the Sipuleucel-T vaccine (approved by the FDA), which has been demonstrated in tests to help people with treatment-resistant prostate cancer live longer and slow the course of their disease [28].

Despite its clinical benefits, PAP has low sensitivity in detecting prostate cancer in its early stages. It has low specificity because it is also expressed in other normal tissues and can be elevated in benign Prostatic hyperplasia or prostatitis, leading to false-positive results [29]. The sample should be collected before a biopsy, DRE, or massage, as they can cause elevated levels of serum PAcP [30].

• ➢The Prostate Health Index (PHI):

A blood-based diagnostic tool is used to estimate the probability of finding Gleason grade ≥2 (GG2) prostate cancer after a biopsy. The (-2) form of pro-PSA, free PSA (fPSA), and total PSA (tPSA) values are combined to provide a composite score [4].

Approved by the FDA in 2012 for men in their fifties or older with a normal DRE and serum PSA levels ranging from 4 to 10 ng/mL, PHI has shown moderate accuracy in detecting Gleason grade 2-5 PCa, including in black men with a cut-off score of ≥28.0 can help avoid unnecessary biopsies [31].

While PHI enhances the specificity of prostate cancer detection, studies report its sensitivity of 0.90 and specificity of 0.17 for identifying high-grade prostate cancer [4,17].

Preventing overtreatment and procedural problems is crucial for patients with prostate cancer. Depending on how advanced the prostate cancer is, treatment options include radiation therapy, radical prostatectomy, and active surveillance [32]. About 50 % of patients with clinically low-risk PCa have a Gleason score (GS) of ≥7 or prostate biopsy (TRUSP biopsy) [33,34].

Magnetic resonance imaging (MRI) has emerged as a substitute for prostate biopsy or MRI-targeted biopsy to more accurately identify clinically relevant cancer with a GS ≥7 [35]. However, due to the poor sensitivity of MRI in detecting extracapsular extension and seminal vesical invasion (SVI), its use has become limited in local cancer staging [44].

Consequently, for preoperatively predicting the undesirable pathological characteristics and identifying who may benefit from surgery, we need an easy and accurate biomarker to help doctors make decisions and predict prognosis before any intervention [36].

Complexed PSA and free PSA (fPSA) are components of total prostate-specific antigen (tPSA). One of the most notable and more cancer-associated biomarkers among fPSA forms is p2PSA, which is an isoform of proPSA [37]. In order to create a prostate health index (PHI), Beckman Coulter, Inc. combined three biomarkers into the following mathematical formula: (p2PSA/fPSA)×√tPSA. At the initial prostate biopsy, %p2PSA and PHI are considered the most accurate biomarkers of PCa [[38], [39], [40]].

PHI and %p2PSA can detect aggressive PCa with GS ≥7 before TRUSP biopsy and the prediction of unfavorable cancer features at the final pathology from RP [41,42]. However, the clinical value of %p2PSA and PHI is limited due to the lack of a reference range for predicting adverse pathological outcomes [43].

• ➢4Kscore test:

The 4Kscore test is a multivariable assay that quantifies four kallikrein markers: total PSA, free PSA, intact PSA, and human kallikrein 2 (hK2) [45]. These biological values are integrated with clinical variables, including age, DRE results, and prior biopsy history, to calculate the probability of high-grade PCa.

Multiple studies have demonstrated that the 4K score is more accurate than PHI in diagnosing PCa in general and high-grade PCa in particular when compared to PSA or the percentage of free PSA [[46], [47], [48], [49], [50]]. Like PHI and free PSA metrics, the primary clinical benefit of the 4Kscore is the reduction of unnecessary biopsies. The decrease in the 4K score-like the PHI- may miss a small percentage of clinically significant PCa [4].

A further problem is that different studies have varied cutoff values for the 4K score, which causes heterogeneity in PCa diagnosis. According to a recent meta-analysis, a 4K score below 7.5 % suggests low risk; however, cutoff values between 7.5 % and 10 % suggest high accuracy for a high-grade PCa diagnosis. However, we need more extensive research to validate this finding [51].

Urine-based biomarker

• The prostate excretes substances that can be identified and measured in the urine. New urine tests can detect changes in genes and biomarkers linked to prostate cancer. The results of these new assays can help determine whether a biopsy is necessary.

• ➢Prostate Cancer Antigen 3 (PCA3) test (also known as DD3) :

PCA3, a noncoding RNA, is the best clinically accessible marker for prostate cancer. PCA3 RNA is only expressed in the prostate gland; it is not found in any other healthy or tumor tissues [52]. In addition to its presence in prostate tissue specimens, PCA3 RNA can also be detected in urine and urine sediments after digital rectal examination (DRE), as cancerous cells with high PCA3 levels are expelled from the prostate into urine [53].

In contrast to normal or benign hyperplastic prostate tissue, 95 % of cancers have significantly higher levels of PCA3 RNA expression. A PCA3 score correlates with the likelihood of a positive biopsy as it helps clinicians in decision-making [54]. The greater the PCA3 score, the greater the probability of a positive biopsy. The PCA3 urine test has a relatively high average sensitivity and specificity of 66 % and 76 %, respectively, in contrast to serum PSA, which has a specificity of 47 % [55].

PCA3 is effective for assessing the need for a second biopsy (already approved by the FDA), but its results vary. After the DRE, the ratio of PCA3 mRNA to PSA mRNA in urine is determined. Where the cutoff score is typically 25 or 35, accordingly, a score above this cutoff might indicate a higher risk of prostate cancer and could help choose whether to have a second biopsy [56,57].

Its Sensitivity ranges between 58 % and 82 %, this indicates that while the test can accurately detect a significant percentage of people with prostate cancer, it may not detect all cases (false negatives). Knowing that the Specificity of this test ranges from 58 % to 76 % [4].

The ability of the test to distinguish between malignant and non-malignant patients is indicated by the Negative Predictive Value (NPV) of up to 87 % and the Area Under the Curve (AUC) range of 0.68–0.87. The PCA3 is reasonably excellent at differentiating between the two, and higher AUC values are preferable. So, the benefits of this test are that it is independent of prostate size, PSA level, and previous biopsies. While the drawback is that there is no unanimity on the best cut-off score [58].

• ➢The SelectMDx Test (DLX1, HOXC6 ) :

SelectMDx is a novel urine assay-based risk score that integrates two mRNA signatures, urinary homeobox C6 (HOXC6) and distal-less homeobox 1 (DLX1), with serum PSA, PSAD, and clinical factors such as age and previous negative biopsy [59,60]. It was included in the 2020 NCCN guidelines for early detection of prostate cancer [4].

To help select patients for prostate biopsies, they determined the mRNA levels of HOXC6 and DLX1 genes using KLK3 expression as an internal reference, which are known to be overexpressed in aggressive prostate cancer [61].

The chance of identifying prostate cancer at biopsy and the difference between high-grade and low-grade illness are provided by the assay of the Area Under Curve (AUC) which is 0.76 when measuring genes alone and 0.9 when combined with clinical risk factors [62]. Its sensitivity is ≥90 %, making it highly effective in accurately identifying patients with prostate cancer because of its high sensitivity; there won't be many false negative results [4].

Also, with a Negative Predictive Value (NPV) of 94 %, it gives it the advantage of very high accuracy, especially when taking clinical factors into account. And the disadvantages of being more sensitive and less specific than multiparametric magnetic resonance imaging (mpMRI) [58].

Despite its benefits in assessing prostate cancer risk, studies indicate that SelectMDx screening may fail to detect a small percentage of clinically significant, high-grade prostate cancers (csPCa). One study supports this concern, showing that applying a conditional strategy—which relies on performing multi-parameter magnetic resonance imaging (mpMRI) only upon a positive SelectMDx result—missed up to 13 % of high-grade prostate cancers [63].

• ➢The IntelliScore test (ExoDx Prostate) (EPI):

It is a standard urine (non-DRE) exosome-based test that uses SPDEF as an internal reference in addition to measuring ERG and PCA3. This assay is indicated for men over 50 years of age with a PSA range of 2-10 ng/ml who are being considered for an initial prostate biopsy [64]. It is used to assess the risk of Gleason 6, Gleason 7, and benign disease on initial biopsy, in combination with current standard of care (SOC) characteristics, such as age, race, family history, and PSA level. It analyzes urine exosomes without requiring a DRE [65]. So, we can determine the likelihood of high-grade prostate cancer (Gleason score ≥ 7) by using this method [4].

With a sensitivity of 92 %, the test can accurately detect prostate cancer, even high-grade disease (Gleason ≥ 7) [18]. The likelihood of false negative results is decreased because it is unlikely to overlook many cases of prostate cancer. The NPV, or negative predictive value, is 91 %, which shows the patient is most likely not suffering from prostate cancer [4].

For low-risk men, this helps prevent needless biopsies. Test Benefits include no DRE needed. And decreases needless biopsies by 26 percent [66]. ExoDx reduces needless biopsies while offering a non-invasive approach to risk assessment. While the drawback is when used alone without integrating with clinical criteria, it is less reliable in differentiating high-grade cases [67].

Tissue-based biomarker

• ➢ConfirmMDxL:

ConfirmMDx is a DNA methylation test performed on prostate tissue biopsy samples. Its purpose is to assess the methylation status of specific genes, which is often an indicator of the presence or progression of prostate cancer. This test is based on the concept of the "field effect," where a positive ConfirmMDx resulting in a cancer-negative biopsy sample suggests the presence of a latent or absent malignancy. This result has significant clinical value [4].

The National Comprehensive Cancer Network (NCCN) guidelines currently incorporate this test for the management of men with elevated PSA levels and a history of previous negative prostate biopsy results [17].

In a study evaluating 138 men with elevated PSA and a history of negative prostate biopsies, Wojno et al. reported that only 6.3 % of these patients underwent a subsequent prostate biopsy, and none showed signs of malignancy on the second procedure [68].

Furthermore, Stewart et al. ConfirmMDx has been shown to be a statistically significant independent predictor of which patients will be diagnosed with malignancy upon biopsy repeat, showing a strong negative predictive value (NPV) of 90 % [4,69].

Collectively to summarizes the principal biomarkers currently employed for the initial detection and risk stratification of prostate cancer, highlighting their sample sources, clinical utilities, and key performance characteristics as showed in Table 1. Traditional serum markers, such as PSA and PAP, remain widely used in screening and disease monitoring but are limited by suboptimal specificity and sensitivity. In contrast, newer blood and urine-based assays including PHI, 4Kscore, PCA3, SelectMDx, and ExoDx demonstrate improved discrimination of clinically significant disease and enhanced biopsy decision-making. Tissue-based assays such as ConfirmMDx further support post-biopsy risk assessment through detection of field effects. Together, these biomarkers reflect the evolving paradigm toward more accurate, minimally invasive, and clinically meaningful early detection strategies.

Table 1.

Initial-Detection Biomarkers.

Biomarker	Sample Type	Utility / Clinical Use	Key Performance / Notes	References
PSA (Prostate Specific Antigen)	Blood	Screening; early detection; monitoring; recurrence; post-diagnosis surveillance	Widely available; low cost; false positives with BPH/prostatitis; cannot distinguish low- vs high-risk tumors; may be normal in advanced cancer	[[17], [18], [19], [20], [21], [22]]
PAP (Prostatic Acid Phosphatase)	Blood	Advanced disease monitoring; correlates with metastasis; prognostic; therapeutic target (vaccine-based)	Low sensitivity in early disease; low specificity; influenced by androgens, EGF, TGF-β1; must be sampled before biopsy/DRE; may rise in benign conditions	[[23], [24], [25], [26], [27], [28], [29], [30]]
PHI (Prostate Health Index)	Blood	Detection of GG ≥2; biopsy decision; improves detection of GS ≥7	Sensitivity 0.90; specificity 0.17; based on p2PSA, fPSA, tPSA; strong predictor of adverse pathology; lacks universal reference range	[4,17,[31], [32], [33], [34], [35], [36], [37], [38], [39], [40], [41], [42], [43], [44]]
4Kscore	Blood	Predicts high-grade PCa; helps avoid unnecessary biopsies	Superior to PSA, %fPSA, and PHI; cut-off variability across studies; may miss small % of clinically significant PCa	[[45], [46], [47], [48], [49], [50],4,51]
PCA3 (DD3)	Urine (post-DRE)	Repeat-biopsy decision; improves specificity over PSA	Sensitivity 58–82 %; specificity 58–76 %; NPV up to 87 %; AUC 0.68–0.87; independent of gland size or PSA	[[52], [53], [54], [55], [56], [57],4,58]
SelectMDx (DLX1 + HOXC6)	Urine	Detection of aggressive PCa; biopsy stratification	AUC 0.76 (genes only) → 0.90 with clinical factors; sensitivity ≥90 %; NPV 94 %; may miss ∼13 % csPCa	[59,60,4,[61], [62], [63],58]
ExoDx / EPI (IntelliScore)	Urine (non-DRE)	Predicts GG ≥7; initial biopsy decision	Sensitivity 92 %; NPV 91 %; reduces unnecessary biopsies by 26 %; less accurate when used alone	[64,65,4,18,66,67]
ConfirmMDx	Tissue biopsy	Detects field effect; predicts latent/absent malignancy; guides repeat biopsy decisions	Strong NPV 90 %; significantly reduces unnecessary repeat biopsies; independent predictor for malignancy on repeat biopsy	[4,17,68,69]

Biomarker for risk stratification and prognosis:

Genomic signature :

• ➢Decipher test :

The Decipher genomic classifier is a tool designed to predict the likelihood of metastasis after radical prostatectomy (RP). While traditional risk assessment relies on factors such as PSA levels, clinical stage, and Gleason score to guide initial treatment decisions for PCa patients, these methods may not capture the patient's full potential for disease progression [[70], [71], [72]].

Consequently, there is a clear clinical need to optimize patient selection of different therapies, increasing the importance of molecular testing in clinical decision-making [72,73].

The Decipher classifier is a genome-based assessment that measures the expression levels of RNA in 22 genes. For high-risk males after radical prostatectomy, it calculates the 10-year prostate cancer mortality rate (PCSM) and the 5-year likelihood of clinical metastasis [17].

Higher scores on the genomic classifier (GC) scale, ranging from 0 to 1.0, indicate a higher likelihood of clinical metastasis [31,32]. It has also been validated for predicting PCSM after RP [72,74,75].

The Decipher test is offered as a "laboratory-developed test" (LDT) and is approved according to CLIA regulations. It is strongly listed in the National Comprehensive Cancer Network (NCCN) guidelines for guiding treatment decisions [76].

The Decipher classifier can be used on prostate needle biopsy tissue [77,78,72]. The effectiveness of this test has already been evaluated in a small cohort of 57 patients, mostly with low- and intermediate-risk cancer, from the Cleveland Clinic [79,72].

The current study aims to validate the performance of the biopsy-based Decipher test in predicting both metastasis and PCSM in a larger cohort of men from multiple institutions with low-, intermediate-, or high-risk disease who have received either radical resection (RP) or radiotherapy (RT) as initial treatment [80,81].

• ➢The Oncotype DX Genomic Prostate Score:

Genomic Health has developed a set of genetic tests called the Oncotype Assay. It relies on real-time PCR technology, which determines the genetic basis of the tumor to help identify the type of tumor. Since 2004, Oncotype DX has been widely used [[82], [83], [84]]. It is done by analyzing a tissue sample from the prostate covered with paraffin. The challenges of this test lie in the heterogeneous nature and the small number of available tissues. It involves comparing 5 reference genes and 12 cancer genes that play a role in cancer formation [82,85].

GPS is a genomic test based on biopsies that quantifies the mRNA expression of 17 genes involved in the growth and survival of tumor cells. Two studies, the Detection of Cancer Using Methylated Events in Negative Tissue (DOCUMENT) research and the Methylation Analysis to Locate Occult Cancer (MATLOC) trial, have validated the test, which was created and examined in 4500 individuals [10]. The Prostate Assay Specific Clinical Value at Launch (PASCUAL) research is underway and is anticipated to conclude in 2018 to assess the clinical value of the ConfirmMDx assay in US urologic practices [17,86].

The impact of GPS on patient and physician behaviour has been explored in numerous randomized and prospective studies [87]. reported that among patients with clinically low-risk prostate cancer, GPS resulted in a significant change in treatment decisions. The use of GPS led to a significant increase in the choice of Active Surveillance (AS) and a corresponding decrease in the choice of immediate radical treatment (surgery or radiation), particularly in men with low-text GPS scores.

Furthermore, physicians reported greater confidence and patients reported fewer conflicting decisions after using GPS [88]. Badani et al. also reported similar results, showing an increase in recommendations for AS and greater confidence among physicians due to the improved risk provided by the GPS system [84].

Conversely, the results of a randomized trial by Murphy et al. (2021), which included 200 patients with low- and intermediate-risk prostate cancer, showed that despite high baseline acceptance of Active Surveillance AS, GPS testing did not significantly increase AS acceptance, nor did it appear to enhance patients' perceived decision-making quality [87].

This highlights the complexity of the decision-making process in patients undergoing AS, which is often accompanied by psychological distress a condition described by Eymard et al. as characterized by disease awareness and anxiety about repeated examinations [89].

• ➢Prolaris test :

Prolaris is one of the most important predictive genomic tests for prostate cancer. It analyzes cell cycle gene activity using a panel of 31 genes obtained from prostate biopsies to assess disease progression risk and aggressiveness in patients [90]. The test's scientific basis lies in calculating the cell cycle progression score (CCP), which is closely linked to the likelihood of relapse, metastasis, and treatment resistance, making it particularly important for patients with intermediate or unclear risk [91].

To improve ease of use and reduce reliance on international reference centers, a new, simplified version of Prolaris was developed, analyzing only 16 genes. This version has demonstrated accuracy comparable to the original commercial version, which analyzed 46 genes [92,72]. The CCP score is combined with the clinical CAPRA score to generate a composite risk score (CCR), which is an important guideline in treatment decisions, whether regarding active follow-up, radical therapy, or the choice between monotherapy and combination therapy [[93], [94], [95], [96], [97]].

The test's application guidelines indicate that a CCR value less than 0.8 is associated with a significant reduction in the risk of death from the disease within ten years, making active follow-up a safe option for this patient population [93,94]. Due to this predictive capability, Prolaris has become widely used in Western countries within the personalized treatment decision-making pathways for prostate cancer patients [98].

Tissue-based marker

• ➢PTEN:

PTEN (Phosphatase and Tensin Homolog) is a tumor suppressor gene. It is important for the management of processes that occur in the cell , such as growth, proliferation, and differentiation. It also has a main role in PI3K/AKT/MTOR signaling pathways [99]. PTEN works by removing the phosphate group from PIP3 and turning it into PIP2. This reaction has an important role in the PI3K/AKT pathway [100].

PTEN reduces the level of PIP3 and inhibits cell growth. In this way, it acts as a tumor suppressor [101]. So loss of PTEN via deletion, mutation, and silencing disrupts the signaling pathway and commonly occurs in early prostate cancer [100]. PTEN suppressor can also happen by microRNA21 [102].

It has been documented at protein levels via Immunohistochemistry (IHC) and at the gene level via fluorescent in situ hybridization (FISH) [103]. Also using genomic assay as next-generation sequencing (NGS) to identify mutations [104].

Loss of PTEN has been associated with more aggressive pathological features in PCa.

Many studies have demonstrated the correlation between PTEN loss and higher Gleason score, indicating poor differentiation and malignant tumor [105]. Meta-analysis for patients shows that PTEN loss increases the risk of recurrence and lethal prostate cancer-specific mortality [106].

For localized prostate cancer, PTEN testing can identify patients at higher risk; IHC is the preferred first-line test, with FISH reserved for ambiguous or heterogeneous cases [107].

Also in postoperative risk stratification, PTEN testing can complement established clinical and pathological risk models, particularly in intermediate-risk patients, where additional molecular stratification can help in the decision of active follow-up and definitive treatment [106].

However, PTEN results should be interpreted in conjunction with other biomarkers and clinical factors.

• ➢ProMark:

ProMark is a tissue-based biomarker used to assess prostate cancer. It utilizes formalin-fixed, paraffin-embedded prostate tissue samples [108]. The test analyses eight specific proteins to estimate disease severity, with a score calculated based on the intensity of protein expression in the tumor tissue [109].

ProMark can contribute to the early detection of prostate cancer in asymptomatic patients and provides information about tumor molecular patterns, which helps classify patients for either active surveillance or alternative treatment options [110]. It can also be combined with other biomarkers to enhance accuracy and specificity, providing a comprehensive approach to monitoring disease progression and patient response to treatment [111,112].

Clinically, ProMark is used to assess prostate cancer severity in patients with Gleason scores of 3+3 and 3+4. The test has demonstrated high discriminatory power in predicting clinical cancer spread and associated mortality [17]. Therefore, this test is an important tool to support treatment decision-making, whether for active surveillance or radical intervention, taking into account the individual risks of each patient.

• ➢The TMPRSS2-ERG fusion:

The TMPRSS2-ERG fusion is an early genetic event in prostate cancer development. This fusion arises from the interaction between the androgen-regulated TMPRSS2 gene and the ERG transcription factor of the ETS family, while it is absent in normal prostate tissue and in cases of benign prostatic hyperplasia [[113], [114], [115], [116], [117], [118], [119]].

This fusion often involves exon 1 of TMPRSS2 with exon 4 or 5 of ERG, leading to increased ERG oncogene expression [[113], [114], [115]]. This fusion contributes to enhanced cell proliferation, invasion, and metastasis, and can interact with additional genetic alterations, such as PTEN loss, to accelerate disease progression [120].

Increased ERG expression activates genes associated with angiogenesis, cell migration, extracellular matrix remodeling, and the inflammatory response. It also promotes β-catenin activity and supports epithelial-mesenchymal transition (EMT), thereby increasing tumor aggressiveness [121].

Clinically, TMPRSS2-ERG represents a promising biomarker, as it can be easily and sensitively detected in urine samples, making it a reliable non-invasive diagnostic tool [88]. Furthermore, a novel transcriptional signature comprising five mRNA pairs has been developed to accurately identify TMPRSS2-ERG fusion status across different datasets, further enhancing its diagnostic capabilities [122].

The key molecular and genomic biomarkers currently utilized for prostate cancer risk stratification and prognostic assessment as in Table 2, unlike conventional screening markers, these assays provide deeper biological insight into tumor aggressiveness, metastatic potential, and disease-specific mortality. To summarize, tissue-based genomic classifiers such as Decipher, Oncotype DX, and Prolaris offer validated scores that guide critical management decisions, including active surveillance versus definitive treatment. Collectively, alterations such as PTEN loss and the presence of TMPRSS2–ERG fusion further enhance prognostic accuracy by refining molecular subtyping and identifying higher-risk disease phenotypes. Overall, this table highlights the growing integration of genomic and proteomic platforms into clinical practice, supporting more personalized and evidence-based therapeutic strategies for patients with prostate cancer.

Table 2.

Biomarkers for Risk Stratification and Prognosis.

Biomarker	Assay / Type	Sample	Key Metric Performance	Clinical Utility	Reference
Decipher	Genomic classifier (22-gene RNA)	Tissue biopsy	GC score 0–1.0; predicts 5-year metastasis & 10-year PCSM	Post-RP risk stratification; guides adjuvant therapy; NCCN listed	[17,31,32,[70], [71], [72], [73], [74], [75], [76], [77], [78], [79], [80], [81]]
Oncotype DX (GPS)	RT-PCR score (17 genes: 12 cancer + 5 reference)	FFPE biopsy tissue	Validated in >4500 pts; influences clinician/patient decision metrics	Supports AS vs radical therapy; mixed RCT impact	[10,17,[82], [83], [84], [85], [86], [87], [88], [89]]
Prolaris (CCP / CCR)	Cell-cycle gene panel (31 genes; 16-gene version)	Biopsy tissue	CCP + CAPRA → CCR; CCR < 0.8 = low 10-year mortality	Predicts recurrence, metastasis; guides AS vs definitive therapy	[72,[90], [91], [92], [93], [94], [95], [96], [97], [98]]
PTEN	Protein/gene loss (IHC, FISH, NGS)	FFPE tissue	Loss → higher Gleason, recurrence, lethal PCa	Improves stratification esp. intermediate risk; complements models	[[99], [100], [101], [102], [103], [104], [105], [106], [107]]
ProMark	Proteomic assay (8-protein panel)	FFPE biopsy tissue	Continuous severity score; high discriminatory power	Classifies Gleason 3+3 / 3+4; predicts spread & mortality	[17,[108], [109], [110], [111], [112]]
TMPRSS2-ERG Fusion	Genomic fusion (TMPRSS2::ERG)	urine (non-invasive)	Early oncogenic driver; interacts with PTEN loss	Diagnostic biomarker; defines molecular subtype	[88,[113], [114], [115], [116], [117], [118], [119], [120], [121], [122]]

Biomarker for advanced and Metastatic diseases.:

Blood-based biomarker

• ➢Circulating Tumor Cells (CTCs) and Cell-Free DNA (cfDNA / ctDNA)

The concept of "liquid biopsy" represents a significant shift towards less invasive methods than traditional tissue biopsy, used to monitor tumor burden and its genetic characteristics both before and after treatment [123]. In this context, both circulating tumor cells (CTCs) and cell-free DNA (cfDNA), specifically, circulating tumor DNA (ctDNA), emerge as promising tools for monitoring and diagnosis [124].

CTCs are cells that detach from the primary or secondary tumor and enter the peripheral bloodstream [125]. Their presence is a clear indicator of tumor spread and predicts a worse patient prognosis, even after adjusting for constant factors such as prostate-specific antigen (PSA) levels [126].

As a continuous variable, the circulating cell count has proven to be a strong predictor of survival, comparable to other factors such as PSA levels [127]. One of the most important advantages of circulating cells is their reliability as a marker of tumor spread, independent of androgen receptor-dependent pathways [126].

Circular cancer cell analysis can be monitored at multiple time points, providing an accurate and non-invasive indicator of disease that facilitates faster testing of future therapies [128].

The Cell Search™ platform is FDA-approved for predictive use in prostate cancer. CTC counts are strongly correlated with the prediction of overall survival and progression-free survival in metastatic prostate cancer [129]. These cells are used to differentiate between occult metastatic disease and actual localized prostate cancer, making them a promising tool for early metastasis detection.

Recent advances, such as testosterone receptor-dependent (AR) circular cancer cell detection, have demonstrated strong diagnostic efficacy, particularly within the "grey zone" of prostate-specific antigen (PSA) levels (between 4 and 10 ng/mL) [4].

Because PSA levels do not accurately reflect disease burden, PSA is not a suitable endpoint for clinical trials of castration-resistant prostate cancer (CRPC) [130]. This highlights the crucial role of CTCs and ctDNA. Current research focuses on the molecular characterization of CTCs to identify indicators of treatment response. This offers significant value for clinical decision-making by helping to determine the most appropriate treatment strategy for each individual patient [126].

In addition to cellular indicators, ctDNA (small fragments of DNA released by cancer cells) shows great potential as a potent biomarker in the blood plasma of prostate cancer patients [17,131,132]. These indicators, taken together, provide a solid foundation for integrating multi-molecular analyses and bio- imaging data to create more effective diagnostic algorithms, thus addressing the need for clear translational effects [133].

• ➢Total Alkaline Phosphatase (TALP) and Bone-specific alkaline phosphatase (BALP) :

Total alkaline phosphatase (TALP)

Total Alkaline Phosphatase (TALP) is a glycoprotein found in bones, kidneys, liver, gut, and placenta. It is commonly used as a low-cost and accessible marker for evaluating prostate cancer (PCa) bone metastasis (BM). ALP levels reflect osteoblastic and bone turnover activity, which helps indicate the degree of bone metastasis . Elevated ALP levels are typically observed in PCa patients with BM, and reductions in ALP levels can occur following treatments like radium-233 radionuclide therapy [132].

Clinical significance/ scenario

TALP is more suitable for predicting overall survival (OS) rather than diagnosing BM. Clinical studies investigating patients with metastatic castration-resistant prostate cancer (mCRPC) have shown that baseline ALP levels can predict OS regardless of the treatment [132]. High ALP levels in individuals with hormone-sensitive prostate cancer (HSPC) are associated with both a higher risk of death and the progression of the illness [133].

Limitations

TALP also correlates with non-neoplastic conditions, such as liver cancer and cholecystitis, which lowers its sensitivity in diagnosing PCa BM [133]. However, it is currently unclear if TALP can predict survival in individuals undergoing therapy for hormone-resistant cancer [135].

Bone-specific alkaline phosphatase (BALP)

Bone-specific alkaline phosphatase (BALP), an isoenzyme synthesized by osteoblasts, has emerged as a specific biomarker for detecting and monitoring metastases in prostate cancer (PCa) [134]. Elevated BALP levels typically reflect secondary bone resorption and enhanced osteoblastic activity. Unlike Total Alkaline phosphatase (TALP), BALP is less affected by renal function and food intake, making it a more reliable and accurate indication of bone metastases [134,135].

Diagnostic performance and prognosis

Comparative research indicates that BALP is 90 % more specific than TALP (57 %) for identifying bone metastases, with similar sensitivity (around 65 %). At a cutoff value of 18.4 ng/mL, BALP exhibits a 92 % specificity and sensitivity for diagnosing bone metastases [134].

Based on meta-analyses, BALP is a better biomarker for diagnosing and predicting the prognosis of prostate cancer metastases to bone (PCa BM) compared to TALP. This is due to the association of higher BALP levels with an increased risk of skeletal events (SREs) and disease progression [136]. Furthermore, lower BALP levels have been associated with improved overall survival (OS) in patients with Castration prostate Cancer (CRPC) [137].

Regard to specificity and sensitivity Table 3 provides a direct comparison between total alkaline phosphatase (TALP) and bone-specific alkaline phosphatase (BALP) in the context of prostate cancer–associated bone metastases. To summarize, although both markers demonstrate comparable sensitivity, BALP exhibits substantially higher specificity and is less influenced by confounding physiological factors such as renal function and dietary intake. Collectively, these characteristics make BALP a more reliable and accurate indicator of skeletal involvement. Taken together, its stronger association with skeletal-related events, disease progression, and overall survival underscores its superior prognostic value compared with TALP, highlighting BALP as the more clinically informative biomarker for monitoring bone metastasis in prostate cancer.

• ➢Bone-specific alkaline phosphatase (BALP):

Table 3.

Comparison between Total Alkaline Phosphatase (TALP) and Bone-specific alkaline phosphatase (BALP) :.

Feature	Bone Alkaline Phosphatase (BALP)	Total Alkaline Phosphatase (TALP)
Influence of factors	Less affected by renal function and food intake [134,137].	Affected by renal function and food intake [134,137].
Specificity (for bone metastases)
	High (90 %)	Low(57 %)
Sensitivity	∼65 % (similar to TALP) [134].	∼65 % (similar to BALP) [134].
Reliability & Accuracy
	More reliable and accurate indication of bone metastases [137].	Less reliable biomarker for this purpose [137].
Prognostic Value	High. Higher levels link to Skeletal-related events (SRE) and disease progression;lower levels link to Improve overall survival (OS) [134].	Less reliable for predicting the prognosis of Prostate Cancer Bone Metastases (PCa BM) [137].

Bone-specific alkaline phosphatase (BALP), an isoenzyme synthesized by osteoblasts, has emerged as a specific biomarker for detecting and monitoring metastases in prostate cancer ( PCa ) [134]. Elevated BALP levels typically reflect secondary bone resorption and enhanced osteoblastic activity [4].

Unlike Total Alkaline phosphatase (TALP), BALP is less affected by renal function and food intake; it is a more reliable and accurate indication of bone metastases [134,135]. Comparative research indicates that when it comes to identifying bone metastases, BALP is 90 % more specific than TALP (57 %), with similar sensitivity (around 65 %) [134].

At a cutoff value of 18.4 ng/mL, BALP exhibits a 92 % specificity and sensitivity for diagnosing bone metastases.

Furthermore, lower BALP levels have been associated with improved overall survival (OS) in patients with Castration Resistant Prostate Cancer (CRPC) [136]. Based on meta-analyses, BALP is a better biomarker for diagnosing and predicting the prognosis of prostate cancer metastases to bone (PCa BM) compared to TALP. This is due to the association of higher BALP levels with an increased risk of skeletal events (SREs) and disease progression [137].

• ➢Androgen Receptors (AR):

The androgen receptor is a nuclear steroid receptor. It composed of three domains, (NTD )N-terminal domain that promote AR activity and transcription activity [138], ( DBD )DNA binding domain that verifies the specificity in gene regulation by recognizing the androgen response element [139], (LBD) ligand binding domain that bind to ligand as testosterone to enhance change in AR structure for being active [140].

AR regulates the development of normal and malignant prostate cells, it done by activating the signaling pathway of AR [141]. It also regulates cell growth, differentiation, and progression by regulating the expression of FOX family transcription factor [142].

Point mutations in AR occur primarily in LBD and NTD. The mutation alters receptor specificity, allowing activation by non-specific ligands [143], as the T878A mutation. Also increase resistance to androgen receptor-targeted therapies [144].

The T877A mutation is associated with resistance to the bicalutamide drug, while the F876L mutation leads to resistance to second-generation inhibitors such as enzalutamide and apalutamide [145].

Aberrant in the AR mRNA splicing produces active variant proteins lacking the hormone-binding domain (LBD) [146]. The AR-V7 variant is the most clinically significant because it produces a functional protein with transcriptional activity completely independent of hormone binding [147].

The isoform AR-V7 is detected in up to 75 %) of patients with mCRPC and is not common in early-stage disease. AR-targeted agent need an intact LBD to exert their effects.AR-V7 positivity is strongly associated with resistance to drugs such as enzalutamide and abiraterone [144].

The loss of the hinge region impairs the androgen receptor's binding to microtubules, contributing to reduced response to taxane chemotherapy such as Docetaxel and Cabazitaxel [148].

From a biomarker perspective, AR-V7 is an important prognostic indicator of treatment resistance in castration-resistant prostate cancer (mCRPC) [149]. Many clinical studies have demonstrated that AR-V7-positive patients exhibit significantly lower response rates to AR axis inhibitory therapy, with marked deterioration in progression-free survival and overall survival, while taxane therapy retains some efficacy despite the presence of the mutation [150,151].

AR gene amplification and Overexpression are hallmarks of castration-resistant prostate cancer (CRPC), with approximately 80 % of patients exhibiting elevated AR mRNA and protein levels [152], while about 18 % have an associated gene point mutation [144].

Overexpression correlates with earlier disease progression and poor clinical outcomes compared to normal levels expression. Mechanistically, oncogenes can enhance AR transcription, thereby increasing receptor levels [144].

Preclinical studies suggest that combining bromodamine (BET) inhibitors with enzalutamide can reduce AR expression, reduces tumor growth, and overcome resistance [153].

AR Co-factors play a pivotal role in prostate cancer development and metastasis by modulating receptor transcriptional activity. Among these, the SRC family (SRC-1, SRC-2, SRC-3) acts as key regulators; SRC-1 expression is strongly associated with tumorigenesis, while its inhibition impairs AR-related gene transcription [154].

SRC-2 is observed in primary and advanced tumors, promoting PI3K signaling and contributing to the emergence of CRPC development. In contrast, SRC-3 shows a negative correlation with PTEN expression and is associated with disease recurrence [155]. Other conjugate factors include Tip60, FHL2, and Hic-5/ARA55, which contribute to tumor growth [156].

Collectively, these alterations increase tumor aggressiveness, metastatic potential, and recurrence risk, highlighting their importance as potential predictive biomarkers, Table 4 [144].

Table 4.

Biomarkers for Advanced & Metastatic Prostate Cancer.

Biomarker Category	Biomarker / Alteration	Description / Function	Clinical / Prognostic Value	Advantages	Limitations	References
Blood-based biomarkers	Circulating Tumor Cells (CTCs)	Cells shed from primary/metastatic tumor into bloodstream; indicate tumor burden and spread	Strong predictor of OS & PFS; differentiates occult metastasis; useful in early metastasis detection	Non-invasive; serial monitoring; independent of AR pathway; FDA-approved CellSearch™ system	Sensitivity varies; technical variability; low abundance in early disease	[[123], [124], [125], [126], [127], [128], [129]]
	Circulating Tumor DNA (ctDNA / cfDNA)	Tumor-derived DNA fragments in plasma	Detects genomic alterations; guides therapy selection; complements CTCs	Non-invasive; allows repeated monitoring; integrates with multi-omic analyses	Sensitivity varies; standardization lacking	[17,[131], [132], [133]]
Bone Metastasis Biomarkers	Total Alkaline Phosphatase (TALP)	Glycoprotein from bone, liver, kidney; reflects osteoblastic activity	Predicts OS in mCRPC & HSPC; higher levels indicate higher risk of death and progression	Cheap; widely available	Low specificity; affected by non-neoplastic conditions; limited prognostic accuracy	[[132], [133], [134], [135]]
	Bone-Specific Alkaline Phosphatase (BALP)	Osteoblast-derived isoenzyme	Highly specific (90 %) for bone metastasis; sensitivity ∼65 %; cutoff 18.4 ng/mL; predicts SREs & OS	More reliable and accurate than TALP; less affected by renal function or food intake	Requires specific assay; slightly similar sensitivity to TALP	[[134], [135], [136], [137]]
Androgen Receptor (AR) Alterations	AR point mutations (T878A, F876L, etc.)	Mutations in LBD/NTD alter ligand specificity	Predict resistance to anti-androgens; associated with tumor progression	Identifies therapy-resistant patients early	Low abundance in early disease; requires sensitive molecular assays	[[138], [139], [140], [141], [142], [143], [144], [145]]
	AR-V7 splice variant	Lacks LBD → constitutively active AR	Strong predictor of resistance in mCRPC; detected in up to 75 % of patients	Non-hormone dependent activity; guides therapy selection	Variable detection; not common in early-stage disease	[[146], [147], [148], [149], [150], [151]]
	AR amplification / overexpression	Increased AR mRNA/protein (80 % of CRPC)	Associated with early progression & poor outcomes	Indicates aggressive disease; potential therapeutic target	Requires genomic testing; co-occurs with multiple alterations	[144,[152], [153]]
	AR Co-factors (SRC-1/2/3, Tip60, FHL2, Hic-5/ARA55)	Modulate AR transcriptional activity	Influence tumor aggressiveness, metastasis, recurrence	Potential experimental therapeutic targets	Research-based; not yet standardized clinically	[[154], [155], [156]]
Liquid biopsy for AR	CTCs, ctDNA, cfRNA	Non-invasive detection of AR alterations	Enables frequent patient monitoring; aids treatment decisions	Minimally invasive; repeatable	Platform sensitivity unstable; inter-study variability	[142,157]

In this context, the analysis of circulating tumor cells (CTCs), free tumor DNA in the blood (ctDNA), or free intraexosome RNA (cfRNA) allows for non-invasive detection of genetic alterations in the androgen receptor AR [142] . These techniques enable more frequent patient monitoring and more accurate treatment decisions, although the sensitivity and standardization of these platforms remain unstable and vary across studies [157].

Hereditary and familial risk biomarker

BRCA1/2

Mutation in BRCA 1/2 has an important role in discover and monitoring various types of cancer. Increased probability of developing cancer is related to different germline or somatic alterations in BRCA genes. BRCA1 is located on chromosome 17 and BRCA 2 on chromosome 13 [158]. BRCA 1 / 2 are important as tumor suppressor genes.

BRCA genes have many functions, but the main function is DNA double-strand repair by activating the homologous recombination [HR]. Any defect during this pathway leads to malignancies such as breast, pancreatic, and prostate cancer [159].

A recent meta-analysis (2023) found that BRCA2 gene mutations in germ cells occur in approximately 3.25 % of all prostate cancer cases, while BRCA2 somatic mutations occur in approximately 6.29 %. As for the BRCA1 gene, the incidence is lower 0.73 % in germ cells, and 1.20 % in somatic cells [160]

With advancing age, especially following the age of 75, the probability of developing PCa for people who have a defect in the BRCA1 gene is 20 percent, and for those who have a defect in the BRCA2 gene, it is about 30 percent. After the age of 85, the risk increases by 30 to 60 percent [158].

According to NCCN guidelines, BRCA2 germline mutations are associated with a significantly higher risk of prostate cancer, a more aggressive disease, and worse results, shorter survival for younger age [161]. The clinical significance of the BRCA genes includes:

Predictive (therapeutic) biomarker: Due to a mutation in DNA repair, BRCA1/2 gene mutations in prostate cancers are particularly sensitive to PARP inhibitors, a concept known as synthetic lethality [162].

BRCA1/2 mutations have become well-established as clinically viable biomarkers in metastatic castration-resistant prostate cancer (mCRPC). Several FDA approvals now require the presence of BRCA mutations to guide treatment selection. These include approvals for Rocaparib (2020) [163] and Olaparib (2020) for the treatment of mCRPC with BRCA1/2 mutations [164].

More recent approvals—Olaparib with Abiraterone and prednisone (2023) [165] and Niraparib with Abiraterone and Prednisone (2023)—target patients with BRCA-mutant mCRPC [166]. Taken together, these regulatory developments reinforce BRCA's position as a powerful prognostic biomarker that directly guides precise tumorigenesis strategies in prostate cancer.

Clinically, BRCA1/2 mutation screening is recommended for men with metastatic prostate cancer to provide genetic counseling and guide targeted therapy with PARP inhibitors [167]. Mutations can be detected using formalin-fixed, paraffin-embedded blood or tissue samples, usually via next-generation sequencing [161]. Thus, BRCA1/2 status is not only a diagnostic biomarker but also a predictive indicator of treatment response.

HOXB13

HOXOB13 is a transcription factor that belongs to the homeobox family. It forms a cluster region on chromosome 17. The function of all HOX genes is to regulate genes during cell division, but HOXB13 has a critical role in prostate gland normal development. It regulates secretory functions and anatomy of the prostate gland [168].

Mechanistically, HOXB13 interacts with the androgen receptor (AR) to regulate chromatin and gene expression. Overexpression of HOXB13 inhibits p21 and activates the RB–E2F pathway, promoting androgen-independent growth and driving the development of prostate cancer [169].

Genetically, HOXB13 has been identified as a pivotal hereditary determinant in prostate cancer risk. The G84E variant is the most relatively characterized, exhibiting a high prevalence in individuals of European descent [170]. Additional germline mutations, such as G135E in Chinese populations [171] and p. (Ala128Asp) and p.(Phe240Leu) in Portuguese cohorts [172], are also associated with a high risk of prostate cancer.

HOXB13 mutations are particularly higher in patients with a familial history or early-onset disease, highlighting their clinical utility for targeted genetic screening and risk stratification [173].

Germline analysis for the HOXB13 gene is recommended for men with a strong family history of prostate cancer or early-onset prostate cancer, as well as those with multiple first-degree relatives with the disease or a family history of hereditary cancers [174].

The HOXB13 gene is included in comprehensive germ cell assemblies alongside the BRCA1/2 genes, providing crucial information for genetic risk assessment, genetic counseling, and potential enrollment in enhanced surveillance programs [174].

Unlike BRCA1/2, there are no FDA-approved targeted therapies specifically for HOXB13-mutated prostate cancer, and its clinical utility remains primarily focused on risk stratification, Table 5. The results should be considered alongside other clinical and pathological factors, including age at diagnosis, PSA levels, Gleason score, and family history, to guide individualized patient management [175].

Table 5.

Hereditary and Familial Risk Biomarker.

Biomarker	Function/Mechanism	Clinical Relevance	Population/Equity Notes	FDA Approval/Therapeutic Implication	Reference
BRCA1/2	Tumor suppressor genes; DNA double-strand repair via homologous recombination; germline and somatic mutations increase cancer risk	High-risk hereditary prostate cancer; aggressive disease; shorter survival in younger age	Recommended for metastatic PCa screening; equitable enrollment needed across races	Predictive biomarker; PARP inhibitor sensitivity (Olaparib, Rucaparib, Niraparib)	[[158], [159], [160], [161], [162], [163], [164], [165], [166], [167]]
HOXB13	Homeobox transcription factor; interacts with androgen receptor; regulates chromatin and gene expression; variants promote androgen-independent growth	Hereditary determinant; high risk in familial or early-onset cases; guides genetic counseling	Included in germline panels; consider alongside age, PSA, Gleason score, family history	No FDA-approved targeted therapy; primarily for risk stratification	[[168], [169], [170], [171], [172], [173], [174], [175]]

Genetic signatures associated with HOXB13 have also been studied as potential indicators of tumor aggressiveness and disease progression [175].

Equity and racial disparities

A critical issue in translational oncology is the inadequate integration of health equity and racial disparities into prostate cancer biomarker research. For example, African American men face nearly twice the risk of death from prostate cancer compared to white men, yet they remain underrepresented in biomarker validation trials [176]. Recent analyses show that systemic barriers to accessing healthcare, socioeconomic factors, and underrepresentation in clinical studies all contribute to the persistence of these disparities [177]. Furthermore, growing evidence suggests that genetic and molecular differences may underlie the more aggressive nature of the disease in African American populations, potentially impacting the performance and predictive accuracy of biomarkers [178]. Despite these findings, most biomarker validation studies, such as PHI, 4Kscore, and genomic screening, have been conducted primarily in Caucasian populations, limiting the generalizability of the results [179]. Recent population studies also show rising rates of metastatic prostate cancer as racial disparities narrow, suggesting that improved screening strategies may help reduce these disparities if implemented equitably [180]. To ensure equity in precision medicine, future biomarker studies should prioritize enrolling diverse populations, assessing biomarker performance across racial groups, and incorporating health equity considerations into guideline development. Addressing these disparities is crucial to translating advances in biomarkers into improved outcomes for all patients across different racial and ethnic backgrounds.

Challenges associated with biomarkers in prostate cancer

1. Technical Barriers:

The selection of novel biomarkers involves several stages, beginning with initial discovery, followed by the development of a suitable screening method, early confirmation of their clinical utility, and culminating in a clinical trial to assess their true impact [181].

An ideal biomarker should be able to clearly differentiate between healthy and diseased tissues; however, most biomarkers exhibit overlapping numerical values, leading to confusion between the two conditions [182]. Initial results for discovered biomarkers are often not replicated due to variations in study design, analytical methods, or the limited availability of samples for evaluation [183]. Consequently, only a few new biomarkers succeed in providing additional benefits to traditional diagnostic methods such as cytology and histology [184].

Other challenges include the difficulty of comparing potential biomarkers, the challenge of developing biomarker combinations applicable to different clinical settings, and the need to reduce costs and increase accessibility, which necessitates rigorous and repeated validation processes [1873].

1. Clinical Barriers:

Biomarkers should provide additional and different information from current clinical and pathological criteria to improve diagnostic accuracy, predict disease course, and determine treatment response in prostate cancer patients [1]. However, randomized controlled trials evaluating the efficacy of molecular markers remain limited.

Future studies should therefore focus on the accuracy of these markers in treatment decision-making and their cost-effectiveness, as well as the need for clearer evidence on their ability to reduce the number of biopsies and decrease costs and complications [185]. Although molecular assays support progress toward precision medicine, their use faces several obstacles. Furthermore, somatic mutations may differ within the same patient when samples are taken from different metastatic sites [186].

While blood tests detect only inherited mutations, tissue samples can detect both somatic and inherited mutations [187]. Data indicate that inherited mutations are present in approximately 12 % of men with metastatic prostate cancer, while somatic mutations can exceed 30 % [188,189], potentially leading to 15–20 % of patients with undetected somatic mutations going untreated. Furthermore, the sensitivity of ctDNA assays is lower than that of tissue samples, with a concordance rate of approximately 80 % in some tumors [190]. Nevertheless, whole-gene sequencing and NGS techniques have improved the detection capabilities of both CTCs and ctDNA.

2. Economic Barriers:

The high cost of some prostate cancer diagnostic biomarkers presents a significant obstacle, leading to continued reliance on traditional methods despite their limited efficacy, particularly in low-income countries. This can result in misdiagnosis or delayed diagnosis, impacting treatment effectiveness [191].

Furthermore, molecular analyses are often expensive and require genetic counseling when heritable mutations are detected, thus limiting the global applicability of biomarker-based therapies. While obtaining tissue samples can be costly and challenging, liquid biopsies offer a practical and easier option for sample collection and expand their use in molecular diagnostics [192].

Future direction

The multi-omics approach, which integrates data from different layers such as genomics, proteomics, metabolomics, and microbiome [[193], [194], [195]], represents a powerful tool for understanding the complex biological systems in prostate cancer, where genetic and metabolic factors intertwine in disease progression [196].

Clinical studies have demonstrated the importance of data integration in discovering novel genes, mutations, metabolites, and biomarkers with greater precision than PSA [4,[197], [198], [199]]. Notable recent applications include microbiome and metabolomics analysis for assessing radiotherapy-associated toxicity [195], as well as mRNA, miRNA, and DNA methylation-based models for classifying disease recurrence risk [200]. Additionally, serological tests have been developed for predicting relapse [201].

The combination of different omics and network pharmacology has also helped identify novel therapeutic targets, such as N-methylglycerol [202], and elucidate the role of natural compounds, including quercetin and ursolic acid [203].

In parallel, single-cell omics techniques, such as scRNA-seq, have provided detailed insights into cellular heterogeneity and the tumour microenvironment [[204], [205], [206], [207]] and have contributed to the identification of tumour suppressor genes and prognostic markers [198]. This comprehensive integration presents opportunities for enhancing diagnostic and therapeutic precision in prostate cancer [204,208,209].

Artificial intelligence (AI) plays a crucial role in improving the screening and diagnosis of early prostate cancer. The traditional PSA-based approach suffers from low biopsy positivity (25 %) and frequent overdiagnosis, with a specificity that varies between 6 % and 66 % [210,211].

AI applications of micro-US have demonstrated clear superiority; the model achieved a sensitivity of 92.5 % and a specificity of 68.1 % compared to the traditional clinical model (96.2 % sensitivity but 27.3 % specificity), with an accuracy of 81.4 % versus 64.8 % [212].

Multimodal models also outperformed routine MRI scans, achieving a specificity of 88 % versus 78 % and an AUC of 0.90 versus 0.79 [213]. Meanwhile, liquid biopsy using ctDNA is evolving as a non-invasive approach, employing AI to interpret complex genomic signals [[214], [215], [216]].

The FateAI platform has demonstrated early capability for multiple cancer detection [217,218]. Furthermore, the integration of genomic markers with machine learning enhances risk assessment beyond PSA [[218], [219]]. Finally, a 25-gene mRNA panel-based blood test (GeneVerify) has shown strong performance in early diagnosis (AUC 0.906; sensitivity 90 %; specificity 91 %) [220,221].

• •New Radio traces for enhanced PCa detection:

The future perspectives for the diagnosis and management of prostate cancer (PCa) are centred on active research into novel radiotracers and advanced imaging techniques. To overcome the limitations of choline tracers 11C-choline and 18F-choline, the radiolabeled leucine analogue 18F-FACBC (1-amino-3-fluorocyclobutane-1-carboxylic acid) has shown favourable imaging characteristics due to its low early urinary excretion [222,223]. Preliminary data suggest its superiority for identifying disease recurrence in biochemical failure [224]. Significant efforts have also focused on developing 68Ga-labelled PSMA ligands targeting the overexpressed Prostate-Specific Membrane Antigen. These ligands offer a better signal-to-background ratio than choline, thereby improving contrast and sensitivity for detecting small metastases, even at low PSA levels [225]. Notably, 68Ga does not require a cyclotron, as it can be extracted from a commercial 68Ge/68Ga generator.

• •The Rise of PET/MRI:

Concurrent PET/MRI, which combines high-resolution magnetic resonance imaging (MRI) with metabolic/molecular imaging, is the most promising of the new techniques [226,227]. PET/MRI can be particularly valuable in identifying high-yield biopsy sites to reduce false-negative results [228] and improving salvage radiotherapy (RT) planning by enabling precise target identification [229].

Preliminary results using PET/MRI are encouraging for detecting and staging the primary tumour [230]. However, lower uniform uptake values (SUVs) have been observed compared to choline PET/CT, which is attributed to the different attenuation correction methods [226,227].PET/MRI, particularly when combined with alternative tracers such as 68Ga-labelled PSMA, is an innovative tool that enables the assessment of multiple tumour parameters to enhance detection, characterisation, and personalised treatment guidance [229].

Conclusion

Prostate cancer (PCa) biomarkers are pivotal tools for diagnosing the disease, predicting its course, and making appropriate treatment decisions. This review highlights the most prominent biomarkers included in current clinical guidelines, given their role in reducing overdiagnosis of low-risk cases, detecting aggressive phenotypes early, and supporting treatment decisions in patients with high genetic susceptibility. Current clinical trials are focused on identifying the optimal populations for utilising these biomarkers, paving the way for improved future applications.

Despite significant progress, the application of biomarkers remains challenging due to the complexity of their detection, the varying sensitivity and accuracy of each test, and the high cost, which limits their widespread adoption. This necessitates strengthening evaluation methodologies and improving study design to achieve accurate molecular risk assessment.

It is essential to note that the growing number of biomarkers associated with targeted therapies highlights the gradual shift toward precision medicine. Genetic information—such as BRCA mutations—guides the use of treatments like PARP inhibitors, leading to improved outcomes and longer survival times for patients with metastatic or treatment-resistant disease.

In the near future, diagnostic methods are expected to evolve towards less invasive and more precise tests, particularly new urinary and haematological markers such as PCA3, along with advanced imaging techniques. Treatment strategies will also be reshaped by more precise molecular classification of tumours, including the expanded use of tumour-specific targeted therapies.

However, a significant limitation in current clinical practice is the continued reliance on the PSA test, despite its limitations in distinguishing between low- and high-risk tumours. Although more accurate tools are available, their integration into clinical practice remains slow, indicating a clear gap between research advancements and clinical application. This underscores the need for further validation studies, along with the application of a personalised medicine approach that considers the molecular characteristics of each patient.

It is also crucial to emphasise the importance of health equity and balanced representation in clinical trials, particularly since African American men who exhibit higher incidence and mortality rates remain underrepresented in most studies. Bridging this gap is crucial for ensuring the dissemination of research findings and providing optimal care for all populations.

Overall, the future of prostate cancer markers is moving toward multimodal systems that integrate genomics, proteomics, hematopoiesis, advanced imaging, and artificial intelligence. This integration will enhance diagnostic accuracy, improve the prediction of tumour biological behaviour, and guide treatment more effectively. As reliance on molecular assessment increases, standardising and expanding the application of these tools becomes essential for achieving better outcomes and reducing the burden of unnecessary diagnosis and treatment.

Ethical approval

This review has no ethical approval; thus, this is a collection of the author's studies.

Consent to participate

This review has no consent to participate; thus, this is a collection of the author's studies.

Human ethics

This review has no ethical approval; thus, this is a collection of the author's studies.

Consent for publication

This review has no consent for publication; thus, this is a collection of the author's studies.

Availability of supporting data

This review doesn't have supporting data; thus, this is a collection of the author's studies.

Funding

No funding.

Declaration of generative AI and AI-assisted technologies

During the preparation of this manuscript, the authors used AI-assisted tools (ChatGPT, Gemini, and Canva) for figure preparation, graphical abstract design, and improvement of language clarity. The authors reviewed and edited all content and take full responsibility for the accuracy, integrity, and originality of the manuscript.

CRediT authorship contribution statement

Nouran Walid Hamed: Formal analysis. Hasnaa Salman Elbeljihy: Software, Resources. Shifaa Atif Hussin: Writing – original draft, Validation. Rana Mohamed Fouda: Writing – original draft, Project administration. El-Khawaga OY: Visualization, Supervision. Raghda W․Magar: Methodology, Conceptualization.

Declaration of competing interest

This review has no competing interests; thus, this is a collection of author studies.