Serum and urine biomarkers for detecting clinically significant prostate cancer

Prostate Extracellular Vesicles and Prognostic Biomarkers of Clinically Significant Prostate Cancer: A Prospective Single-Institution Pilot Study

BACKGROUND

Commercial biomarkers and multiparametric MRI (mpMRI) have been utilized to triage men with elevated prostate specific antigen (PSA) and determine patients most likely to harbor clinically-significant prostate cancer (csPCa). We studied combinations of mpMRI, PSA-based and novel extracellular vesicle (EV)-based biomarkers to determine the optimal pre-biopsy testing to predict csPCa at biopsy.

METHODS

Men presenting with elevated PSA (≥ 2 ng/mL) were prospectively enrolled and all men underwent clinically indicated mpMRI and blinded study blood draws to determine PSA, prostate health index (PHI) scoring, and EV serum levels. MRI-fusion transperineal prostate biopsy was performed in all patients. Sensitivity, specificity, positive predictive value, and negative predictive value were calculated, and receiver operator characteristic (ROC) curves were constructed. Bootstrapping analysis was performed to provide more accurate assessment of predictive abilities.

RESULTS

Ultimately, 175 consecutive men were prospectively enrolled. Median age in the study population was 65 years. Combinations of biomarkers and MRI demonstrated better predictive ability for csPCa on biopsy than individual modalities. Predictive ability was greatest for PHI density (PHID)-mpMRI with an AUC of 0.86 (95% CI: 0.80-0.92) while combinations of PSA density -mpMRI (AUC: 0.81; 95% CI: 0.73-0.89) and STEAP1-mpMRI (AUC: 0.77; 95% CI: 0.70-0.86) demonstrated similar ability to predict csPCa. The study is limited by small, predominantly white patient cohort and requires external validation.

CONCLUSIONS

Inclusion of prostate density with biomarkers increases prognostic ability for detecting csPCa. EV density can refine prediction of csPCa and in combination with PHID-mpMRI leads to superior specificity, thereby decreasing unnecessary biopsies.

Personalised Prostate Cancer Diagnosis: Evaluating Biomarker-based Approaches to Reduce Unnecessary Magnetic Resonance Imaging and Biopsy Procedures

Background and objective

Efforts made over the last decade for the detection of prostate cancer (PCa) have revolutionised disease diagnostics, and implementation of prebiopsy magnetic resonance imaging (MRI) has received widespread acceptance. However, universal adoption of prebiopsy MRI and the benefits achieved have been limited by availability and equivocal MRI findings. This review aims to evaluate the latest evidence on the role of existing PCa risk calculators (RCs), and blood and urinary biomarkers as part of the diagnostic algorithm to improve the diagnosis of clinically significant PCa (csPCa) and reduce unnecessary MRI procedures and biopsies. We will also evaluate the potential of prostate-specific membrane antigen (PSMA) positron emission tomography (PET) to enhance sensitivity and specificity for PCa diagnosis, complement MRI, and refine biopsy strategies within the diagnostic pathway.

Methods

We performed a narrative review using the PubMed/MEDLINE database, which included papers published between January 2014 and June 2024. The outcome measures included rates of reduced diagnoses of nonsignificant PCa (defined as International Society of Urological Pathology [ISUP] grade group 1) cases, diagnoses of csPCa (defined as ISUP grade group ≥2) cases missed, and MRI scans and prostate biopsies avoided.

Key findings and limitations

In men with abnormal prostate-specific antigen (PSA) levels, further risk stratification using RCs, or blood or urine biomarkers can reduce up to 16-51% MRI scans, while missing 1-16% csPCa cases. In case of equivocal MRI results or Prostate Imaging Reporting and Data System 3 lesions, RCs or biomarkers could reduce up to 72% of biopsies, while missing only 3-13% csPCa cases. PSMA PET has emerging potential to improve csPCa prediction in combination with MRI and may further reduce unnecessary biopsies. A limitation of this study is that this is a narrative but not a systematic review.

Conclusions and clinical implications

RCs and biomarkers have been demonstrated to enhance the performance and efficiency of MRI in detecting csPCa in men with elevated PSA levels. PSMA PET shows promise in detecting csPCa, complementing MRI and refining biopsy indications.

Patient summary

In men with a suspicion of prostate cancer, magnetic resonance imaging prostate scans are effective in predicting clinically relevant cancer, but challenges including availability and equivocal scans exist. A personalised approach by adding one or more of clinical risk calculators, blood or urine biomarkers, or even novel imaging techniques such as positron emission tomography scans may improve cancer prediction further and reduce unnecessary scans and biopsies.

Fourier transform InfraRed spectra analyzed by multivariate and machine learning methods in determination spectroscopy marker of prostate cancer in dried serum

Prostate cancer represents the second most prevalent form of cancer in males globally. In the diagnosis of prostate cancer, the most commonly utilised biomarker is prostate-specific antigen (PSA). It is unfortunate that approximately 25 % of men with elevated PSA levels do not have cancer, and that approximately 20 % of patients with prostate cancer have normal serum PSA levels. Accordingly, a more sensitive methodology must still be identified. It is imperative that new diagnostic methods should be non-invasive, cost-effective, rapid, and highly sensitive. Fourier transform infrared spectroscopy (FTIR) is a technique that fulfils all of the aforementioned criteria. Consequently, the present study used FTIR to assess dried serum samples obtained from a cohort of prostate cancer patients (n = 53) and a control group of healthy individuals (n = 40). Furthermore, this study proposes FTIR markers of prostate cancer obtained from serum. For this purpose, FTIR spectra of dried serum were measured and analysed using statistical, chemometric and machine learning (ML) algorithms including decision trees C5.0, Random Forest (RF), k-Nearest Neighbours (kNN) and Support Vector Machine (SVM). The FTIR spectra of serum collected from patients suffering from prostate cancer exhibited a reduced absorbance values of peaks derived from phospholipids, amides, and lipids. However, these differences were not statistically significant. Furthermore, principal component analysis (PCA) demonstrated that it is challenging to distinguish serum samples from healthy and non-healthy patients. The ML algorithms demonstrated that FTIR was capable of differentiating serum collected from both analysed groups of patients with high accuracy (values between 0.74 and 0.93 for the range from 800 cm-1 to 1800 cm-1 and around 0.70 and 1 for the range from 2800 cm-1 to 3000 cm-1), depending on the ML algorithms used. The results demonstrated that the peaks at 1637 cm-1 and 2851 cm-1 could serve as a FTIR marker for prostate cancer in serum samples. Furthermore, the correlation test indicated a clear correlation between these two wavenumbers and four of the five clinical parameters associated with prostate cancer. However, the relatively small number of samples collected only from patients over the age of 60 indicated that the results should be further investigated using a larger number of serum samples collected from a mean age range. In conclusion, this study demonstrated the potential of FTIR for the detection of prostate cancer in serum samples, highlighting the presence of distinctive spectroscopic markers associated with the analysed cancer type.

Usefulness of urinary biomarker-based risk score and multiparametric MRI for clinically significant prostate cancer detection in biopsy-naïve patients

OBJECTIVES

This study aimed to investigate the accuracy of multiparametric magnetic resonance imaging (mpMRI), genetic urinary test (GUT), and prostate cancer prevention trial risk calculator version 2.0 (PCPTRC2) for the clinically significant prostate cancer (csPCa) diagnostic in biopsy-naïve patients.

MATERIALS AND METHODS

In a single center study between 2021 and 2024 participants underwent prostate mpMRI, GUT, and ultrasound (US) guided biopsy. The csPCa risk was calculated using PCPTRC2. After conducting a digital rectal examination (DRE), a GUT was performed. It incorporated the RNA levels of prostate cancer antigen 3 (PCA3) and transmembrane serine protease 2 (TMPRSS2) gene and ETS-related gene (ERG) fusion genes (T: E), along with the patient's age and PSA density. The McNemar test compared detection rates between modalities.

RESULTS

208 (mean age 62.9 years +/- 8.2) men were included prospectively. A positive GUT score was found in 67.8% and PIRADS ≥3 in 81.7% of all cases. The combination of GUT with mpMRI showed significantly higher sensitivity (99.1%) than GUT and mpMRI alone, 84.4% and 93.8%, respectively (p ≤ 0.05). Similarly, very high sensitivity (99.0%) was achieved by combining mpMRI with PCPTCR2. Nevertheless, mpMRI plus GUT combination exceeded mpMRI plus PCPTCR2 by allowing to save a higher fraction of unnecessary biopsies, 25% and 2.4%, respectively.

CONCLUSION

GUT and mpMRI combination would allow saving a substantial fraction of unnecessary biopsies with minimal risk of missing csPCa cases.

Plasmon-Enhanced Fluorescence of Single Extracellular Vesicles Captured in Arrayed Aluminum Nanoholes

Extracellular vesicles (EVs) are nanoparticles encapsulated with a lipid bilayer, and they constitute an excellent source of biomarkers for multiple diseases. However, the heterogeneity in their molecular compositions constitutes a major challenge for their recognition and profiling, thereby limiting their application as an effective biomarker. A single-EV analysis technique is crucial to both the discovery and the detection of EV subpopulations that carry disease-specific signatures. Herein, a plasmonic nanohole array is designed for capturing single EVs and subsequently performing fluorescence detection of their membrane proteins by exploiting plasmonic amplification of the fluorescence signal. Unlike other reported methods, our design relies on an exclusive detection of single EVs captured inside nanoholes, thus allowing us to study only plasmonic effects and avoid other metal-induced phenomena while leveraging on the proximity of emitters to the plasmonic hotspots. The method is optimized through numerical simulations and verified by a combination of atomic force, scanning electron microscopy, and fluorescence microscopy. Fluorescence enhancement is then estimated by measuring the CD9 expression of small EVs derived from the human embryonic kidney (HEK293) cell line and carefully considering the spatial distribution of emission and excitation intensities. Fluorescence intensities of immunostained EVs show a moderate overall enhancement of intensity and follow the intensity trend predicted by simulation for nanohole arrays with different nanohole periods. Moreover, the number of observed EVs in the best-performing nanohole array increases by more than 12 times compared with EVs immobilized on a reference substrate, uncovering a vast amount of weakly fluorescent EVs that would remain undetected with the regular fluorescent method. Our nanohole array provides a basis for a future platform of single-EV analyses, also promising to capture the signature arising from low-expressing proteins.

Urinary MicroRNA-21 for Prostate Cancer Detection Using a Silver Nanoparticle Sensor: A Promising Diagnostic Tool

In this study, we detected the expression levels of miR-21 in 38 clinical urine samples, obtained from 10 patients with PCa (with each sample obtained at three time points: before surgery, 1 month after surgery, and 3 months after surgery), 3 patients with benign prostatic hypertrophy (BPH), and 5 healthy subjects (as a control group). All of the samples were examined using a silver nanoparticle-based biosensor, and the sensitivity of the biosensor was simultaneously confirmed via qRT-PCR. The results were further analyzed together with clinical data such as PSA values and cancer stages. The sensitivity of the biosensor ranged up to 100 fM, and it presented a rather high selectivity rate. Our results indicated a significantly decreased expression level of miR-21 in the patient cases at 3 months post-surgery when compared with pre-surgery levels (p-value < 0.001). In addition, when distinguishing the differences in the expression level of miR-21 between healthy subjects and patients with PCa or BPH, both groups showed highly significant differences (p = 0.008 and p < 0.001, respectively). The results strongly suggest that the proposed miR-21 biosensor can be used as an auxiliary screening tool for the early detection of PCa and may effectively facilitate tracking of the progression of PCa, thus enabling more accurate healthcare decision making.

Towards Understanding the Role of the Glycosylation of Proteins Present in Extracellular Vesicles in Urinary Tract Diseases: Contributions to Cancer and Beyond

Extracellular vesicles (EVs) are a population of nanoscale particles surrounded by a phospholipid bilayer, enabling intercellular transfer of bioactive molecules. Once released from the parental cell, EVs can be found in most biological fluids in the human body and can be isolated from them. For this reason, EVs have significant diagnostic potential and can serve as an excellent source of circulating disease biomarkers. Protein glycosylation plays a key role in many biological processes, and aberrant glycosylation is a hallmark of various diseases. EVs have been shown to carry multiple glycoproteins, but little is known about the specific biological roles of these glycoproteins in the context of EVs. Moreover, specific changes in EV glycosylation have been described for several diseases, including cancers and metabolic, cardiovascular, neurological or kidney diseases. Urine is the richest source of EVs, providing almost unlimited (in terms of volume) opportunities for non-invasive EV isolation. Recent studies have also revealed a pathological link between urinary EV glycosylation and urological cancers, as well as other pathologies of the urinary tract. In this review, we discuss recent research advances in this field and the diagnostic/prognostic potential of urinary EV glycosylation. In addition, we summarize common methods for isolating EVs from urine and techniques used to study their glycosylation.

Prostate cancer theragnostics biomarkers: An update

Biomarkers are molecules such as proteins, genes, or other substances that may be tested to determine the stage of the tumor in a patient. The role of prostate cancer biomarkers is pivotal and the combination of prostate cancer immunotherapy with efficient biomarkers has emerged as a beneficial treatment strategy and its use has increased rapidly. The two primary objectives of this current prostate cancer early detection programs were recognizing non-symptomatic individuals with prostate cancer requiring prostatic core biopsy and identifying men with prostate cancer who might benefit from definitive medical treatment. The progress that has been made so far in the identification of the biomarkers that can be used for the classification, prediction and prognostication of prostate cancer, and as major targets for its clinical intervention has been well summarized in this review.

Diagnostic value and clinical significance of serum miR-4534 combined with transvaginal color Doppler ultrasound in cervical cancer

AIM

The purpose of the present study was to evaluate the diagnostic performance of serum miR-4534 combined with Transvaginal Color Doppler Ultrasound (TVCDS) in cervical cancer patients.

METHODS

Blood samples from 126 patients with cervical cancer and 83 patients with benign uterine lesions were retrospectively analyzed. Quantitative real time polymerase chain reaction (qRT-PCR) was applied to examine the relative abundances of serum miR-4534 in cervical cancer based on a case-control study. Chi-square test was adopted to analyze the association between serum miR-4534 and other clinicopathological factors. The blood flow of cervix was examined using TVCDS, and the blood flow resistance index (RI) of cervix was summarized. Receiver operating characteristic (ROC) curves were plotted to explore the diagnostic capacity of serum miR-4534 combined with blood flow RI. Logistic regression was employed to analyze the risk factors of cervical cancer.

RESULTS

Serum miR-4534 was distinctly increased in the study group compared with the control group (P < 0.05), while blood flow RI was dramatically decreased (P < 0.05). Moreover, increased miR-4534 was closely associated with lymph node metastasis (P = 0.010), FIGO stage (P = 0.007) and HR-HPV (P = 0.025). ROC curves demonstrated that the area under curve (AUC) of serum miR-4534 combined with the blood flow RI was 0.854, with the sensitivity and specificity of 88.9% and 73.5%, respectively, which displayed a better diagnostic capacity than serum miR-4534 and blood flow RI alone. Logistic regression analysis demonstrated that serum miR-4534 (OR = 8.805, 95% CI = 4.124-18.798; P < 0.001) was a risk factor related to the initiation and formation of cervical cancer, as well as blood flow RI (OR = 0.112; 95% CI = 0.054-0.235; P < 0.001).

CONCLUSION

Serum miR-4534 was highly expressed in cervical cancer, and associated with the development and metastasis of cervical cancer patients. MiR-4534 combined with TVCDS exhibited a considerable biomarker to detect cervical cancer patients.

Management of Patients With a Negative Multiparametric Prostate MRI Examination: AJR Expert Panel Narrative Review

Multiparametric MRI (mpMRI) of the prostate aids risk stratification of patients with elevated PSA levels. Although most clinically significant prostate cancers are detected by mpMRI, insignificant cancers are less evident. Thus, multiple international prostate cancer guidelines now endorse routine use of prostate MRI as a secondary screening test before prostate biopsy. Nonetheless, management of patients with negative mpMRI results (defined as PI-RADS category 1 or 2) remains unclear. This AJR Expert Panel Narrative Review summarizes the available literature on patients with an elevated screening PSA level and a negative prostate mpMRI result and provides guidance for these patients' management. Systematic biopsy should not be routinely performed after a negative mpMRI examination in patients at average risk but should be considered in patients at high risk. In patients who undergo PSA screening rather than systematic biopsy after negative mpMRI, clear triggers should be established for when to perform a repeat MRI examination. Patients with a negative MRI result followed by negative biopsy should follow their health care practitioners' preferred guidelines concerning subsequent PSA screening for the patient's risk level. Insufficient high-level data exist to support routine use of adjunctive serum or urine biomarkers, artificial intelligence, or PSMA PET to determine the need for prostate biopsy after a negative mpMRI examination.

Urinary PSA-ZINC biomarker outperforms standard of care in early detection of prostate cancer

BACKGROUND

Urine is a promising biological fluid for prostate cancer (PCa) diagnostics due to its non-invasive collection and wide range of biomarkers. The aim of this study was to assess the role of urinary PSA (uPSA) and urinary Zinc (uZinc) as biomarkers for the diagnosis of PCa in combination with routine parameters of standard of care (SOC - blood PSA, abnormal DRE, age) and MRI in patients candidates for prostate biopsy.

METHODS

Urine samples after prostatic massages were collected from men with suspected PCa scheduled for prostate biopsy. Quantification of uPSA was performed by ECLIA platform and confirmed by ELISA assay, while uZinc measurement was evaluated by ICP-MS and confirmed by colorimetric in vitro assay. Six multivariate logistic regression analysis were performed to assess diagnostic performance of uPSA and uZinc (urine), SOC and MRI alone, and combination of MRI+SOC, MRI+urine and SOC+MRI+urine. The discriminative power of the logistic models was assessed by calculating the area under the receiver operating characteristic (ROC) curves (AUC).

RESULTS

Two hundred thirty-eight patients were included in the analysis; 145 of them were diagnosed with PCa. Urine test showed a better discrimination of HS from CP, in respect of uPSA and uZinc alone, both for PCa of any grade and Gleason Score ≥7 (4+3) (AUC 0.804 and 0.823 respectively). ROC curve combining SOC+MRI+urine showed an AUC=0.882, that is statistically different from SOC or MRI alone, or MRI+SOC (P=0.0001, P=0.0001, and P=0.008 respectively). PCa risk algorithm designed considering SOC+MRI+urine results in potential reduction of 57% of unnecessary biopsies compared to the current standard parameters.

CONCLUSIONS

The loss of uPSA and Zinc production and secretion during neoplastic transformation of the prostate could potentially represent a hallmark of PCa. Its combination with age, PSA and DRE, as well as with mpMRI could represent an interesting approach to improve the diagnostic accuracy of PCa.

Phage Biosensor for the Classification of Metastatic Urological Cancers from Urine

Most of the annual 10 million cancer-related deaths are caused by metastatic disease. Survival rates for cancer are strongly dependent on the type of cancer and its stage at detection. Early detection remains a challenge due to the lack of reliable biomarkers and cost-efficient screening methods. Phage biosensors can offer a solution for early detection using non-invasive liquid biopsies. Here, we report the first results of the bifunctional phage biosensor to detect metastatic urological cancers from urine. A dye-sensitized phage library was used to select metastasis-related phage binders. After selection rounds, the most promising phage candidate was used to classify metastatic cancer from controls. Additionally, we applied one chemical sensor (phenoxazine non-fluorescent dye) to classify cancer from urine. A statistical significance (p = 0.0002) was observed between metastatic and non-metastatic cancer, with sensitivity of 70% and specificity of 79%. Furthermore, the chemical sensor demonstrated significance in detecting cancer (p < 0.0001) with a sensitivity of 71% and a specificity of 75%. Our data suggest a new promising field for urine biomarker research, and further evaluation with prospectively collected samples is ongoing. In conclusion, we report, for the first time, the potential of a chemical- and phage-based biosensor method to detect metastatic cancer using urine.

The sensor applications for prostate and lung cancer biomarkers in terms of electrochemical analysis

Prostate and lung cancers are the most common types of cancer and affect a large part of the population around the world, causing deaths. Therefore, the rapid identification of cancer can profoundly impact reducing cancer-related death rates and protecting human lives. Significant resources have been dedicated to investigating new methods for early disease detection. Cancer biomarkers encompass various biochemical entities, including nucleic acids, proteins, sugars, small metabolites, cytogenetic and cytokinetic parameters, and whole tumor cells in bodily fluids. These tools can be utilized for various purposes, such as risk assessment, diagnosis, prognosis, treatment efficacy, toxicity evaluation, and predicting a return. Due to these versatile and critical purposes, there are widespread studies on the development of new, sensitive, and selective approaches for the determination of cancer biomarkers. This review illustrates the significant lung and prostate cancer biomarkers and their determination utilizing electrochemical sensors, which have the advantage of improved sensitivity, low cost, and simple analysis. Additionally, approaches such as improving sensitivity with nanomaterials and ensuring selectivity with MIPs are used to increase the performance of the sensor. This review aims to overview the most recent electrochemical biosensor applications for determining vital biomarkers of prostate and lung cancers in terms of nanobiosensors and molecularly imprinted polymer (MIP)-based biosensors.

High expression of Trop2 is associated with aggressive localized prostate cancer and is a candidate urinary biomarker

Distinguishing indolent from clinically significant localized prostate cancer is a major clinical challenge and influences clinical decision-making between treatment and active surveillance. The development of novel predictive biomarkers will help with risk stratification, and clinical decision-making, leading to a decrease in over or under-treatment of patients with prostate cancer. Here, we report that Trop2 is a prognostic tissue biomarker for clinically significant prostate cancer by utilizing the Canary Prostate Cancer Tissue Microarray (CPCTA) cohort composed of over 1100 patients from a multi-institutional study. We demonstrate that elevated Trop2 expression is correlated with worse clinical features including Gleason score, age, and pre-operative PSA levels. More importantly, we demonstrate that elevated Trop2 expression at radical prostatectomy predicts worse overall survival in men undergoing radical prostatectomy. Additionally, we detect shed Trop2 in urine from men with clinically significant prostate cancer. Our study identifies Trop2 as a novel tissue prognostic biomarker and a candidate non-invasive marker for prostate cancer.

Unveiling the Dichotomy of Urinary Proteins: Diagnostic Insights into Breast and Prostate Cancer and Their Roles

This review covers the diagnostic potential of urinary biomarkers, shedding light on their linkage to cancer progression. Urinary biomarkers offer non-invasive avenues for detecting cancers, potentially bypassing the invasiveness of biopsies. The investigation focuses primarily on breast and prostate cancers due to their prevalence among women and men, respectively. The intricate interplay of urinary proteins is explored, revealing a landscape where proteins exhibit context-dependent behaviors. The review highlights the potential impact of physical activity on urinary proteins, suggesting its influence on tumorigenic behaviors. Exercise-conditioned urine may emerge as a potential diagnostic biomarker source. Furthermore, treatment effects, notably after lumpectomy and prostatectomy, induce shifts in the urinary proteome, indicating therapeutic impacts rather than activating oncogenic signaling. The review suggests further investigations into the double-sided, context-dependent nature of urinary proteins, the potential role of post-translational modifications (PTM), and the integration of non-protein markers like mRNA and metabolites. It also discusses a linkage of urinary proteomes with secretomes from induced tumor-suppressing cells (iTSCs). Despite challenges like cancer heterogeneity and sample variability due to age, diet, and comorbidities, harnessing urinary proteins and proteoforms may hold promise for advancing our understanding of cancer progressions, as well as the diagnostic and therapeutic role of urinary proteins.

miRNA Expression Patterns in Early- and Late-Stage Prostate Cancer Patients: High-Throughput Analysis

Prostate cancer (PCa) is one of the most common types of cancer among men. To date, there have been no specific markers identified for the diagnosis and prognosis or response to treatment of this disease. Thus, there is an urgent need for promising markers, which may be fulfilled by small non-coding RNAs known as microRNAs (miRNAs). Therefore, the present study aimed to investigate the miRNA profile in tissue samples obtained from patients with PCa using microarrays, followed by reverse transcriptase quantitative PCRs (RT-qPCRs). In the discovery phase, 754 miRNAs were screened in tissues obtained from patients (n = 46) with PCa in early and late stages. Expression levels of miRNA-324-3p, miRNA-429, miRNA-570, and miRNA-616 were found to be downregulated, and miRNA-423-5p expression was upregulated in patients with early-stage cancer compared to the late-stage ones. These five miRNAs were further validated in an independent cohort of samples (n = 39) collected from patients with PCa using RT-qPCR-based assays. MiRNA-324-3p, miRNA-429, miRNA-570, and miRNA-616 expression levels remained significantly downregulated in early-stage cancer tissues compared to late-stage tissues. Remarkably, for a combination of three miRNAs, PSA levels and Gleason scores were able to discriminate between patients with early-stage PCa and late-stage PCa, with an AUC of 95%, a sensitivity of 86%, and a specificity close to 94%. Thus, the data obtained in this study suggest a possible involvement of the identified miRNAs in the pathogenesis of PCa, and they may also have the potential to be developed into diagnostic and prognostic tools for PCa. However, further studies with a larger cohort are needed.

Biomarkers for Prostate Cancer: From Diagnosis to Treatment

Prostate cancer (PCa) is a widespread malignancy with global significance, which substantially affects cancer-related mortality. Its spectrum varies widely, from slow-progressing cases to aggressive or even lethal forms. Effective patient stratification into risk groups is crucial to therapeutic decisions and clinical trials. This review examines a wide range of diagnostic and prognostic biomarkers, several of which are integrated into clinical guidelines, such as the PHI, the 4K score, PCA3, Decipher, and Prolaris. It also explores the emergence of novel biomarkers supported by robust preclinical evidence, including urinary miRNAs and isoprostanes. Genetic alterations frequently identified in PCa, including BRCA1/BRCA2, ETS gene fusions, and AR changes, are also discussed, offering insights into risk assessment and precision treatment strategies. By evaluating the latest developments and applications of PCa biomarkers, this review contributes to an enhanced understanding of their role in disease management.

Prostate Cancer Detection and Complications of Transperineal Versus Transrectal Magnetic Resonance Imaging-fusion Guided Prostate Biopsies

OBJECTIVE

To assess the rates of detection of clinically significant prostate cancer (csPCa) and complications associated with transperineal (TP) and transrectal (TR) biopsy approaches to magnetic resonance imaging (MRI)-fusion targeted biopsy.

MATERIALS AND METHODS

We retrospectively identified men who underwent TP or TR MRI-targeted biopsy with concurrent systematic random biopsy from August 2020 to August 2021. Primary outcomes were detection rates of csPCa and 30-day complication rates between the 2 MRI-biopsy groups. Data were additionally stratified by prior biopsy status.

RESULTS

A total of 361 patients were included in the analysis. No demographic differences were observed. No significant differences were observed between TP and TR approaches on any of the outcomes of interest. TR MRI-targeted biopsies identified csPCa in 47.2% of patients, and TP MRI-targeted biopsies identified csPCa in 48.6% of patients (P = .78). No significant differences were observed in csPCa detection between the 2 approaches for patients on active surveillance (P = .59), patients with prior negative biopsy (P = .34), and patients who were biopsy naïve (P = .19). Complication rates did not vary by approach (P = .45).

CONCLUSION

Neither the identification of csPCa by MRI-targeted biopsy nor rates of complications differed significantly based on a TR or TP approach. No differences were seen between MRI-targeted approaches based on prior biopsy or active surveillance status.

Screening for prostate cancer: evidence, ongoing trials, policies and knowledge gaps

Long-term screening with serum prostate-specific antigen (PSA) and systematic prostate biopsies can reduce prostate cancer mortality but leads to unacceptable overdiagnosis. Over the past decade, diagnostic methods have improved and the indolent nature of low-grade prostate cancer has been established. These advances now enable more selective detection of potentially lethal prostate cancer. This non-systematic review summarises relevant diagnostic advances, previous and ongoing screening trials, healthcare policies and important remaining knowledge gaps. Evidence synthesis and conclusions: The strong association between low serum PSA values and minimal long-term risk of prostate cancer death allows for adjusting screening intervals. Use of risk calculators, biomarkers and MRI to select men with a raised PSA value for biopsy and lesion-targeting rather than systematic prostate biopsies reduce the detection of low-grade cancer and thereby overdiagnosis. These improvements recently led the European Union to recommend its member states to evaluate the feasibility and effectiveness of organised screening programmes for prostate cancer. Nonetheless, important knowledge gaps remain such as the performance of modern diagnostic methods in long-term screening programmes and their impact on mortality. The knowledge gaps are currently being addressed in three large randomised screening trials. Population-based pilot programmes will contribute critical practical experience.

Adverse upgrading and/or upstaging in contemporary low-risk prostate cancer patients

BACKGROUND

Upgrading and/or upstaging in low-risk prostate cancer (PCa) patients may represent an indication for active treatment instead of active surveillance (AS). We addressed contemporary upgrading and/or upstaging rates in a large population based-cohort of low-risk PCa patients.

MATERIALS AND METHODS

Whitin the SEER database (2010-2015), NCCN low-risk PCa patients were identified across management modalities: radical prostatectomy (RP), radiotherapy (RT) and non-local treatment (NLT). In RP patients, upgrading and/or upstaging rates were assessed in logistic regression models.

RESULTS

Overall, of 27,901 low-risk PCa patients, 38% underwent RP vs 28% RT vs 34% NLT. RP patients were the youngest and harbored the highest percentage of positive cores and a higher rate of cT2a than NLT. At RP, 46.2% were upgraded to GGG ≥ 2, 6.0% to GGG ≥ 3 and 10.5% harbored nonorgan-confined stage (NOC, pT3-4 or pN1). Of NOC patients, 1.6% harbored GGG ≥ 3, 6.3% harbored GGG2 and 2.6% harbored GGG1. Of pT2 patients, 4.4% harbored GGG ≥ 3, 33.9% harbored GGG2 and 51.3% harbored GGG1. Age, PSA, percentage of positive cores and number of positive cores independently predicted the presence of NOC and/or GGG ≥ 3, but with low accuracy (63.9%).

CONCLUSIONS

In low-risk PCa, critical changes between tumor grade and stage at biopsy vs RP may be expected in very few patients: NOC with GGG ≥ 3 in 1.6% and NOC with GGG2 in 6.3%. Other patients with upgrading and/or upstaging combinations will invariably harbor either pT2 or GGG1 that far less critically affect PCa prognosis.

Magnetic Resonance Imaging-Based Predictive Models for Clinically Significant Prostate Cancer: A Systematic Review

Simple Summary

Magnetic resonance imaging (MRI) has allowed the early detection of PCa to evolve towards clinically significant PCa (csPCa), decreasing unnecessary prostate biopsies and overdetection of insignificant tumours. MRI identifies suspicious lesions of csPCa, predicting the semi-quantitative risk through the prostate imaging report and data system (PI-RADS), and enables guided biopsies, increasing the sensitivity of csPCa. Predictive models that individualise the risk of csPCa have also evolved adding PI-RADS score (MRI-PMs), improving the selection of candidates for prostate biopsy beyond the PI-RADS category. During the last five years, many MRI-PMs have been developed. Our objective is to analyse the current developed MRI-PMs and define their clinical usefulness through a systematic review. We have found high heterogeneity between MRI technique, PI-RADS versions, biopsy schemes and approaches, and csPCa definitions. MRI-PMs outperform the selection of candidates for prostate biopsy beyond MRI alone and PMs based on clinical predictors. However, few developed MRI-PMs are externally validated or have available risk calculators (RCs), which constitute the appropriate requirements used in routine clinical practice.

Abstract

MRI can identify suspicious lesions, providing the semi-quantitative risk of csPCa through the Prostate Imaging-Report and Data System (PI-RADS). Predictive models of clinical variables that individualise the risk of csPCa have been developed by adding PI-RADS score (MRI-PMs). Our objective is to analyse the current developed MRI-PMs and define their clinical usefulness. A systematic review was performed after a literature search performed by two independent investigators in PubMed, Cochrane, and Web of Science databases, with the Medical Subjects Headings (MESH): predictive model, nomogram, risk model, magnetic resonance imaging, PI-RADS, prostate cancer, and prostate biopsy. This review was made following the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) criteria and studied eligibility based on the Participants, Intervention, Comparator, and Outcomes (PICO) strategy. Among 723 initial identified registers, 18 studies were finally selected. Warp analysis of selected studies was performed with the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. Clinical predictors in addition to the PI-RADS score in developed MRI-PMs were age, PCa family history, digital rectal examination, biopsy status (initial vs. repeat), ethnicity, serum PSA, prostate volume measured by MRI, or calculated PSA density. All MRI-PMs improved the prediction of csPCa made by clinical predictors or imaging alone and achieved most areas under the curve between 0.78 and 0.92. Among 18 developed MRI-PMs, 7 had any external validation, and two RCs were available. The updated PI-RADS version 2 was exclusively used in 11 MRI-PMs. The performance of MRI-PMs according to PI-RADS was only analysed in a single study. We conclude that MRI-PMs improve the selection of candidates for prostate biopsy beyond the PI-RADS category. However, few developed MRI-PMs meet the appropriate requirements in routine clinical practice.

Pushing Fluids: A Case for Liquid Biomarkers Before Imaging in Pre-Prostate Biopsy Decision-making

For patients with clinical suspicion of prostate cancer, liquid biomarkers are the next best test because of their accessibility, objectiveness, and noninvasive nature. A highly sensitive cutoff for these biomarkers should be used to triage patients before use of magnetic resonance imaging.

From Omics to Multi-Omics Approaches for In-Depth Analysis of the Molecular Mechanisms of Prostate Cancer

Cancer arises following alterations at different cellular levels, including genetic and epigenetic modifications, transcription and translation dysregulation, as well as metabolic variations. High-throughput omics technologies that allow one to identify and quantify processes involved in these changes are now available and have been instrumental in generating a wealth of steadily increasing data from patient tumors, liquid biopsies, and from tumor models. Extensive investigation and integration of these data have led to new biological insights into the origin and development of multiple cancer types and helped to unravel the molecular networks underlying this complex pathology. The comprehensive and quantitative analysis of a molecule class in a biological sample is named omics and large-scale omics studies addressing different prostate cancer stages have been performed in recent years. Prostate tumors represent the second leading cancer type and a prevalent cause of cancer death in men worldwide. It is a very heterogenous disease so that evaluating inter- and intra-tumor differences will be essential for a precise insight into disease development and plasticity, but also for the development of personalized therapies. There is ample evidence for the key role of the androgen receptor, a steroid hormone-activated transcription factor, in driving early and late stages of the disease, and this led to the development and approval of drugs addressing diverse targets along this pathway. Early genomic and transcriptomic studies have allowed one to determine the genes involved in prostate cancer and regulated by androgen signaling or other tumor-relevant signaling pathways. More recently, they have been supplemented by epigenomic, cistromic, proteomic and metabolomic analyses, thus, increasing our knowledge on the intricate mechanisms involved, the various levels of regulation and their interplay. The comprehensive investigation of these omics approaches and their integration into multi-omics analyses have led to a much deeper understanding of the molecular pathways involved in prostate cancer progression, and in response and resistance to therapies. This brings the hope that novel vulnerabilities will be identified, that existing therapies will be more beneficial by targeting the patient population likely to respond best, and that bespoke treatments with increased efficacy will be available soon.

Comprehensive Landscape of HOXA2, HOXA9, and HOXA10 as Potential Biomarkers for Predicting Progression and Prognosis in Prostate Cancer

Prostate cancer (PCa) is recognized as a common malignancy in male patients. The homeobox A cluster (HOXA) family members have been confirmed to be implicated in the development of several types of tumors. However, the expression pattern and prognostic values of HOXA genes in PCa have not been investigated. In this study, we analyzed TCGA datasets and identified six HOXA family members which showed a dysregulated expression in PCa specimens compared with nontumor specimens. We also explored the potential mechanisms involved in the dysregulation of HOXA family members in PCa, and the results of Pearson's correlation revealed that most HOXA members were negatively related to the methylation degree. Moreover, we explored the prognostic values of HOXA family members and identified six survival-related HOXA members. Importantly, HOXA2, HOXA9, and HOXA10 were identified as critical PCa-related genes which were abnormally expressed in PCa and associated with clinical outcomes of PCa patients. Then, we explored the association between the above three genes and immune cell infiltration. We observed that the levels of HOXA2, HOXA9, and HOXA10 were associated with the levels of immune infiltration of several kinds of immune cells. Overall, our findings identified the potential values of the HOXA family for outcome prediction in PCa, which might facilitate personalized counselling and treatment in PCa.

The Barcelona Predictive Model of Clinically Significant Prostate Cancer

A new and externally validated MRI-PM for csPCa was developed in the metropolitan area of Barcelona, and a web-RC designed with the new option of selecting the csPCa probability threshold. The development cohort comprised 1486 men scheduled to undergo a 3-tesla multiparametric MRI (mpMRI) and guided and/or systematic biopsies in one academic institution of Barcelona. The external validation cohort comprised 946 men in whom the same diagnostic approach was carried out as in the development cohort, in two other academic institutions of the same metropolitan area. CsPCa was detected in 36.9% of men in the development cohort and 40.8% in the external validation cohort (p = 0.054). The area under the curve of mpMRI increased from 0.842 to 0.897 in the developed MRI-PM (p < 0.001), and from 0.743 to 0.858 in the external validation cohort (p < 0.001). A selected 15% threshold avoided 40.1% of prostate biopsies and missed 5.4% of the 36.9% csPCa detected in the development cohort. In men with PI-RADS <3, 4.3% would be biopsied and 32.3% of all existing 4.2% of csPCa would be detected. In men with PI-RADS 3, 62% of prostate biopsies would be avoided and 28% of all existing 12.4% of csPCa would be undetected. In men with PI-RADS 4, 4% of prostate biopsies would be avoided and 0.6% of all existing 43.1% of csPCa would be undetected. In men with PI-RADS 5, 0.6% of prostate biopsies would be avoided and none of the existing 42.0% of csPCa would be undetected. The Barcelona MRI-PM presented good performance on the overall population; however, its clinical usefulness varied regarding the PI-RADS category. The selection of csPCa probability thresholds in the designed RC may facilitate external validation and outperformance of MRI-PMs in specific PI-RADS categories.

Multiplexed Prostate Cancer Companion Diagnostic Devices

Prostate cancer (PCa) remains one of the most prominent forms of cancer for men. Since the early 1990s, Prostate-Specific Antigen (PSA) has been a commonly recognized PCa-associated protein biomarker. However, PSA testing has been shown to lack in specificity and sensitivity when needed to diagnose, monitor and/or treat PCa patients successfully. One enhancement could include the simultaneous detection of multiple PCa-associated protein biomarkers alongside PSA, also known as multiplexing. If conventional methods such as the enzyme-linked immunosorbent assay (ELISA) are used, multiplexed detection of such protein biomarkers can result in an increase in the required sample volume, in the complexity of the analytical procedures, and in adding to the cost. Using companion diagnostic devices such as biosensors, which can be portable and cost-effective with multiplexing capacities, may address these limitations. This review explores recent research for multiplexed PCa protein biomarker detection using optical and electrochemical biosensor platforms. Some of the novel and potential serum-based PCa protein biomarkers will be discussed in this review. In addition, this review discusses the importance of converting research protocols into multiplex point-of-care testing (xPOCT) devices to be used in near-patient settings, providing a more personalized approach to PCa patients’ diagnostic, surveillance and treatment management.

Low Levels of Urinary PSA Better Identify Prostate Cancer Patients

Simple Summary

Elevated PSA levels in blood tests are the gold standard for early prostate cancer detection, but its lack of specificity limits its clinical use as a mass screening test. The paradox is that it has long been known that advanced prostate cancers can lose PSA expression. We have observed that in the presence of tumors, the prostate produces and secretes less PSA than in healthy or benign conditions. Therefore, the PSA evaluation in urine provided more accurate information on the presence of prostate tumors than the blood test, representing a new method for the screening of prostate cancer.

Abstract

Serum prostatic specific antigen (PSA) has proven to have limited accuracy in early diagnosis and in making clinical decisions about different therapies for prostate cancer (PCa). This is partially due to the fact that an increase in PSA in the blood is due to the compromised architecture of the prostate, which is only observed in advanced cancer. On the contrary, PSA observed in the urine (uPSA) reflects the quantity produced by the prostate, and therefore can give more information about the presence of disease. We enrolled 574 men scheduled for prostate biopsy at the urology clinic, and levels of uPSA were evaluated. uPSA levels resulted lower among subjects with PCa when compared to patients with negative biopsies. An indirect correlation was observed between uPSA amount and the stage of disease. Loss of expression of PSA appears as a characteristic of prostate cancer development and its evaluation in urine represents an interesting approach for the early detection of the disease and the stratification of patients.

Health Economic Evidence for Liquid- and Tissue-based Molecular Tests that Inform Decisions on Prostate Biopsies and Treatment of Localised Prostate Cancer: A Systematic Review

CONTEXT

Several liquid- and tissue-based biomarker tests (LTBTs) are available to inform the need for prostate biopsies and treatment of localised prostate cancer (PCa) through risk stratification, but translation into routine practice requires evidence of their clinical utility and economic impact.

OBJECTIVE

To review and summarise the health economic evidence on the ability of LTBTs to inform decisions on prostate biopsies and treatment of localised PCa through risk stratification.

EVIDENCE ACQUISITION

A systematic search was performed in the EMBASE, MEDLINE, Health Technology Assessment, and National Health Service Health Economic Evaluation databases. Eligible publications were those presenting health economic evaluations of an LTBT to select individuals for biopsy or risk-stratify PCa patients for treatment. Data on the study objectives, context, methodology, clinical utility, and outcomes were extracted and summarised.

EVIDENCE SYNTHESIS

Of the 22 studies included, 14 were focused on test-informed biopsies and eight on treatment selection. Most studies performed cost-effectiveness analyses (n = 7), followed by costing (n = 4) or budget impact analyses (n = 3). Most (18 of 22) studies concluded that biomarker tests could decrease health care costs or would be cost-effective. However, downstream consequences and long-term outcomes were typically not included in studies that evaluated LTBT to inform biopsies. Long-term effectiveness was modelled by linking evidence from different sources instead of using data from prospective studies.

CONCLUSIONS

Although studies concluded that LTBTs would probably be cost-saving or -effective, the strength of this evidence is disputable because of concerns around the validity and transparency of the assumptions made. This warrants prospective interventional trials to inform health economic analyses to ensure collection of direct evidence of clinical outcomes based on LTBT use.

PATIENT SUMMARY

We reviewed studies that evaluated whether blood, urine, and tissue tests can reduce the health and economic burden of prostate cancer. Results indicate that these tests could be cost-effective, but clinical studies of long-term outcomes are needed to confirm the findings.

Identification of a novel non-invasive biological marker to overcome the shortcomings of PSA in diagnosis and risk stratification for prostate cancer: Initial prospective study of developmental endothelial locus-1 protein

Objective

This prospective study sought to clarify the developmental endothelial locus-1 (Del-1) protein as values of diagnosis and risk stratification of prostate cancer (PCa).

Design

From February 2017 to December 2019, a total 458 patients who underwent transrectal ultrasound guided prostate biopsy or surgery of benign prostatic hyperplasia agreed to research of Del-1 protein. We prospectively compared and analyzed the Del-1 protein and prostate specific antigen (PSA) in relation to the patients’ demographic and clinicopathological characteristics.

Results

Mean age was 68.86±8.55 years. Mean PSA and Del-1 protein was 21.72±89.37, 0.099±0.145, respectively. Two hundred seventy-six (60.3%) patients were diagnosed as PCa. Among them, 181 patients underwent radical prostatectomy (RP). There were significant differences in Del-1 protein between benign and PCa group (0.066±0.131 vs 0.121±0.149, respectively, p<0.001). When we set the cut-off value of del-1 protein as 0.120, in patients with 3≤PSA≤8, positive predictive value and specificity of Del-1 protein (≥0.120) for predicting PCa were 88.9% (56/63) and 93.5% (101/108), respectively. Among 181 patients who underwent RP, there were significant differences in Del-1 protein according to stage (pT2 vs pT3a vs ≥pT3b) (0.113±0.078, 0.171±0.121, 0.227±0.161, respectively, p<0.001) and to Gleason score (6 (3+3) or 7 (3+4) vs 7 (4+3) or 8 (4+4) vs 9 or 10) (0.134±0.103, 0.150±0.109, 0.212±0.178, respectively, P = 0.044). Multivariate analysis showed that PSA, Del-1 protein and high Gleason score (≥9) were the independent prognostic factors for predicting higher pT stage (≥3b). Furthermore, age, PSA and Del-1 protein were independent prognostic factors for predicting significant PCa.

Conclusion

Patients with PCa showed higher expression of Del-1 protein than benign patients. Del-1 protein increased with the stage and Gleason score of PCa. Collaboration with PSA, Del-1 protein can be a non-invasive useful marker for diagnosis and risk stratification of PCa.

Tumor Microenvironment in Prostate Cancer: Toward Identification of Novel Molecular Biomarkers for Diagnosis, Prognosis, and Therapy Development

Prostate cancer (PCa) is by far the most commonly diagnosed cancer in men worldwide. Despite sensitivity to androgen deprivation, patients with advanced disease eventually develop resistance to therapy and may die of metastatic castration-resistant prostate cancer (mCRPC). A key challenge in the management of PCa is the clinical heterogeneity that is hard to predict using existing biomarkers. Defining molecular biomarkers for PCa that can reliably aid in diagnosis and distinguishing patients who require aggressive therapy from those who should avoid overtreatment is a significant unmet need. Mechanisms underlying the development of PCa are not confined to cancer epithelial cells, but also involve the tumor microenvironment. The crosstalk between epithelial cells and stroma in PCa has been shown to play an integral role in disease progression and metastasis. A number of key markers of reactive stroma has been identified including stem/progenitor cell markers, stromal-derived mediators of inflammation, regulators of angiogenesis, connective tissue growth factors, wingless homologs (Wnts), and integrins. Here, we provide a synopsis of the stromal-epithelial crosstalk in PCa focusing on the relevant molecular biomarkers pertaining to the tumor microenvironment and their role in diagnosis, prognosis, and therapy development.

Incorporating Prognostic Biomarkers into Risk Assessment Models and TNM Staging for Prostate Cancer

In current practice, prostate cancer staging alone is not sufficient to adequately assess the patient's prognosis and plan the management strategies. Multiple clinicopathological parameters and risk tools for prostate cancer have been developed over the past decades to better characterize the disease and provide an enhanced assessment of prognosis. Herein, we review novel prognostic biomarkers and their integration into risk assessment models for prostate cancer focusing on their capability to help avoid unnecessary imaging studies, biopsies and diagnosis of low risk prostate cancers, to help in the decision-making process between active surveillance and treatment intervention, and to predict recurrence after radical prostatectomy. There is an imperative need of reliable biomarkers to stratify prostate cancer patients that may benefit from different management approaches. The integration of biomarkers panel with risk assessment models appears to improve prostate cancer diagnosis and management. However, integration of novel genomic biomarkers in future prognostic models requires further validation in their clinical efficacy, standardization, and cost-effectiveness in routine application.