Incorporation of Urinary Prostate Cancer Antigen 3 and TMPRSS2:ERG into Prostate Cancer Prevention Trial Risk Calculator

Risk calculators for the detection of prostate cancer: a systematic review

BACKGROUND

Prostate cancer (PCa) (early) detection poses significant challenges, including unnecessary testing and the risk of potential overdiagnosis. The European Association of Urology therefore suggests an individual risk-adapted approach, incorporating risk calculators (RCs) into the PCa detection pathway. In the context of 'The PRostate Cancer Awareness and Initiative for Screening in the European Union' (PRAISE-U) project ( https://uroweb.org/praise-u ), we aim to provide an overview of the currently available clinical RCs applicable in an early PCa detection algorithm.

METHODS

We performed a systematic review to identify RCs predicting detection of clinically significant PCa at biopsy. A search was performed in the databases Medline ALL, Embase, Web of Science Core Collection, Cochrane Central Register of Controlled Trials and Google Scholar for publications between January 2010 and July 2023. We retrieved relevant literature by using the terms "prostate cancer", "screening/diagnosis" and "predictive model". Inclusion criteria included systematic reviews, meta-analyses, and clinical trials. Exclusion criteria applied to studies involving pre-targeted high-risk populations, diagnosed PCa patients, or a sample sizes under 50 men.

RESULTS

We identified 6474 articles, of which 140 were included after screening abstracts and full texts. In total, we identified 96 unique RCs. Among these, 45 underwent external validation, with 28 validated in multiple cohorts. Of the externally validated RCs, 17 are based on clinical factors, 19 incorporate clinical factors along with MRI details, 4 were based on blood biomarkers alone or in combination with clinical factors, and 5 included urinary biomarkers. The median AUC of externally validated RCs ranged from 0.63 to 0.93.

CONCLUSIONS

This systematic review offers an extensive analysis of currently available RCs, their variable utilization, and performance within validation cohorts. RCs have consistently demonstrated their capacity to mitigate the limitations associated with early detection and have been integrated into modern practice and screening trials. Nevertheless, the lack of external validation data raises concerns about numerous RCs, and it is crucial to factor in this omission when evaluating whether a specific RC is applicable to one's target population.

Liquid Biomarkers in Prostate Cancer Diagnosis: Current Status and Emerging Prospects

Prostate cancer (PCa) is a major health concern that necessitates appropriate diagnostic approaches for timely intervention. This review critically evaluates the role of liquid biopsy techniques, focusing on blood- and urine-based biomarkers, in overcoming the limitations of conventional diagnostic methods. The 4Kscore test and Prostate Health Index have demonstrated efficacy in distinguishing PCa from benign conditions. Urinary biomarker tests such as PCa antigen 3, MyProstateScore, SelectMDx, and ExoDx Prostate IntelliScore test have revolutionized risk stratification and minimized unnecessary biopsies. Emerging biomarkers, including non-coding RNAs, circulating tumor DNA, and prostate-specific antigen (PSA) glycosylation, offer valuable insights into PCa biology, enabling personalized treatment strategies. Advancements in non-invasive liquid biomarkers for PCa diagnosis may facilitate the stratification of patients and avoid unnecessary biopsies, particularly when PSA is in the gray area of 4 to 10 ng/mL.

How to Integrate Prostate Cancer Biomarkers in Urology Clinical Practice: An Update

Nowadays, the management of prostate cancer has become more and more challenging due to the increasing number of available treatment options, therapeutic agents, and our understanding of its carcinogenesis and disease progression. Moreover, currently available risk stratification systems used to facilitate clinical decision-making have limitations, particularly in providing a personalized and patient-centered management strategy. Although prognosis and prostate cancer-specific survival have improved in recent years, the heterogenous behavior of the disease among patients included in the same risk prognostic group negatively impacts not only our clinical decision-making but also oncological outcomes, irrespective of the treatment strategy. Several biomarkers, along with available tests, have been developed to help clinicians in difficult decision-making scenarios and guide management strategies. In this review article, we focus on the scientific evidence that supports the clinical use of several biomarkers considered by professional urological societies (and included in uro-oncological guidelines) in the diagnosis process and specific difficult management strategies for clinically localized or advanced prostate cancer.

Unravelling the Role of P300 and TMPRSS2 in Prostate Cancer: A Literature Review

Prostate cancer is one of the most common malignant diseases in men, and it contributes significantly to the increased mortality rate in men worldwide. This study aimed to review the roles of p300 and TMPRSS2 (transmembrane protease, serine 2) in the AR (androgen receptor) pathway as they are closely related to the development and progression of prostate cancer. This paper represents a library-based study conducted by selecting the most suitable, up-to-date scientific published articles from online journals. We focused on articles that use similar techniques, particularly those that use prostate cancer cell lines and immunohistochemical staining to study the molecular impact of p300 and TMPRSS2 in prostate cancer specimens. The TMPRSS2:ERG fusion is considered relevant to prostate cancer, but its association with the development and progression as well as its clinical significance have not been fully elucidated. On the other hand, high p300 levels in prostate cancer biopsies predict larger tumor volumes, extraprostatic extension of disease, and seminal vesicle involvement at prostatectomy, and may be associated with prostate cancer progression after surgery. The inhibition of p300 has been shown to reduce the proliferation of prostate cancer cells with TMPRSS2:ETS (E26 transformation-specific) fusions, and combining p300 inhibitors with other targeted therapies may increase their efficacy. Overall, the interplay between the p300 and TMPRSS2 pathways is an active area of research.

Clinical performance of magnetic resonance imaging and biomarkers for prostate cancer diagnosis in men at high genetic risk

OBJECTIVES

To evaluate different scenarios for the management of early diagnosis of cancer (PCa) in men at high genetic risk, using recently developed blood and urinary molecular biomarkers in combination with clinical information alongside multiparametric magnetic resonance imaging (mpMRI).

PATIENTS AND METHODS

A total of 322 patients with a high genetic risk (familial or personal history of cancers or a predisposing germline variant) were included in this study. The primary outcome was the detection rates of PCa (positive biopsy) or clinically significant PCa (biopsy with International Society of Urological Pathology [ISUP] grade >1). Clinical parameters included age, body mass index, ancestry, and germline mutational status, mpMRI, prostate-specific antigen density (PSAD), Prostate Health Index and urinary markers (Prostate Cancer Associated 3, SelectMdx™ and T2:ERG score) were assessed. Sensitivity (Se) and specificity (Sp) for each marker at their recommended cut-off for clinical practice were calculated. Comparison between diagnoses accuracy of each procedure and scenario was computed using mutual information based and direct effect contribution using a supervised Bayesian network approach.

RESULTS

A mpMRI Prostate Imaging-Reporting and Data System (PI-RADS) score ≥3 showed higher Se than mpMRI PI-RADS score ≥4 for detection of PCa (82% vs 61%) and for the detection of ISUP grade >1 lesions (96% vs 80%). mpMRI PI-RADS score ≥3 performed better than a PSA level of ≥3 ng/mL (Se 96%, Sp 53% vs Se 91%, Sp 8%) for detection of clinically significant PCa. In case of negative mpMRI results, the supervised Bayesian network approach showed that urinary markers (with the same accuracy for all) and PSAD of ≥0.10 ng/mL/mL were the most useful indicators of decision to biopsy.

CONCLUSIONS

We found that screening men at high genetic risk of PCa must be based on mpMRI without pre-screening based on a PSA level of >3 ng/mL, to avoid missing too many ISUP grade >1 tumours and to significantly reduce the number of unnecessary biopsies. However, urinary markers or a PSAD of ≥0.10 ng/mL/mL when mpMRI was negative increased the detection of ISUP grade >1 cancers. We suggest that a baseline mpMRI be discussed for men at high genetic risk from the age of 40 years.

The performance and limitations of PCA3, TMPRSS2:ERG, HOXC6 and DLX1 urinary markers combined in the improvement of prostate cancer diagnostics

BACKGROUND

Prostate cancer (PCa) is the second most commonly diagnosed cancer in men. To date, the role of the combined application of long non-coding RNAs (PCA3, DLX1, HOXC6, TMPRSS2:ERG) for obtaining the most accurate method of detection of PCa has not yet been comprehensively investigated.

METHODS

In total 240 persons were included in the retrospective study. Among them were 150 patients with confirmed PCa, 30 patients with benign prostatic hyperplasia, 30 patients with active chronic prostatitis and 30 healthy volunteers. In all patients, the urine samples were collected prior to biopsy or treatment. Polymerase chain reaction with reverse transcription was performed to detect the expression level of PCA3, HOXC6, DLX1 and the presence of the TMPRSS2:ERG transcript.

RESULTS

PCA3 was detected in urine samples in all cases. Using a PCA3 score of 56 allowed the differentiation between PCa and all other cases with a sensitivity of 61% and specificity of 96% (p<0.001) while a PCA3 score threshold value of 50 resulted in a differentiation between clinically significant PCa (ISUP grades 2-5) and all other cases with a sensitivity of 93% and specificity of 93% (p<0.001). The TMPRSS2:ERG expression in urine was detected exclusively in the group of patients with PCa and only in 16% of all cases.

CONCLUSIONS

PCA3 score detected in urine demonstrated moderate sensitivity and good specificity in differentiation between PCa and non-PCa and high sensitivity and specificity in differentiation between clinically significant PCa and non-PCa.

Association of MyProstateScore (MPS) with prostate cancer grade in the radical prostatectomy specimen

BACKGROUND

To evaluate the association between urinary MyProstateScore (MPS) and pathologic grade group (GG) at surgery in men diagnosed with GG1 prostate cancer (PCa) on biopsy.

METHODS

Using an institutional biospecimen protocol, we identified men with GG1 PCa on biopsy and PSA ≤10 ng/ml who underwent radical prostatectomy (RP) at the University of Michigan. MPS was retrospectively calculated using prospectively collected, post-DRE urine samples. The primary outcome was upgrading on RP pathology, defined as GG ≥ 2. The associations of MPS, PSA, and PSA density (PSAD) with upgrading were assessed on univariable logistic regression, and the predictive accuracy of each marker was estimated by the area under the receiver operating characteristic curve (AUC).

RESULTS

There were 52 men with urinary specimens available that met study criteria, based on biopsy Gleason Grade and specimen collection. At RP, 17 men (33%) had GG1 cancer and 35 (67%) had GG ≥ 2 cancer. Preoperative MPS was significantly higher in patients with GG ≥ 2 cancer at surgery (median 37.8 [IQR, 22.2-52.4]) as compared to GG1 (19.3 [IQR, 9.2-29.4]; P = 0.001). On univariable logistic regression, increasing MPS values were significantly associated with upgrading (odds ratio 1.07 per one-unit MPS increase, 95% confidence interval 1.02-1.12, P = 0.004), while PSA and PSAD were not significantly associated with upgrading. Similarly, the discriminative ability of the MPS model (AUC 0.78) for upgrading at RP was higher compared to models based on PSA (AUC 0.52) and PSAD (AUC 0.62).

CONCLUSIONS

In men diagnosed with GG1 PCa who underwent surgery, MPS was significantly associated with RP cancer grade. In this limited cohort of men, these findings suggest that MPS could help identify patients with undetected high-grade cancer. Additional studies are needed to better characterize this association.

Diagnostic and prognostic potential of the proteomic profiling of serum-derived extracellular vesicles in prostate cancer

Extracellular vesicles (EVs) and their cargo represent an intriguing source of cancer biomarkers for developing robust and sensitive molecular tests by liquid biopsy. Prostate cancer (PCa) is still one of the most frequent and deadly tumor in men and analysis of EVs from biological fluids of PCa patients has proven the feasibility and the unprecedented potential of such an approach. Here, we exploited an antibody-based proteomic technology, i.e. the Reverse-Phase Protein microArrays (RPPA), to measure key antigens and activated signaling in EVs isolated from sera of PCa patients. Notably, we found tumor-specific protein profiles associated with clinical settings as well as candidate markers for EV-based tumor diagnosis. Among others, PD-L1, ERG, Integrin-β5, Survivin, TGF-β, phosphorylated-TSC2 as well as partners of the MAP-kinase and mTOR pathways emerged as differentially expressed endpoints in tumor-derived EVs. In addition, the retrospective analysis of EVs from a 15-year follow-up cohort generated a protein signature with prognostic significance. Our results confirm that serum-derived EV cargo may be exploited to improve the current diagnostic procedures while providing potential prognostic and predictive information. The approach proposed here has been already applied to tumor entities other than PCa, thus proving its value in translational medicine and paving the way to innovative, clinically meaningful tools.

PCA3 in Prostate Cancer

Prostate cancer antigen 3 (PCA3) is a urinary biomarker for prostate cancer and has demonstrated a good specificity and sensitivity representing a minimally invasive test.PCA3 assay could be useful in combination with PSA to suggest an eventual rebiopsy in men who have had one or more previous negative prostate biopsies.Combination of multiple tumor biomarkers will be the trend in the near future to achieve the goal of evaluate the aggressiveness of cancer and at the same time reducing the number of unnecessary biopsies.

Prostate cancer biomarkers and multiparametric MRI: is there a role for both in prostate cancer management?

Several advancements have been made in recent years with regards to the detection and evaluation of prostate cancer (PCa). The low specificity of prostate specific antigen (PSA) has left much to be desired in a test, but a boom in novel biomarkers has made screening and surveillance more complicated. Several attempts at identifying a niche for these tests has helped somewhat, but much is still undetermined about the benefit that each test provides. In addition to laboratory tests, advancements in multiparametric magnetic resonance imaging (mpMRI) and PIRADSv.2 scoring have provided significant benefit to the evaluation of PCa. With the widespread use of prostate imaging, it is important to re-evaluate the impact of novel biomarkers in the context of furthering PCa screening and management. In this review, we aim to assess the influence mpMRI has on the role of nine different novel biomarkers in the detection and evaluation of PCa. We performed a review of current peer-reviewed literature to assess this question. Much data has been published on the role of these tests, allowing for their placement into one of three best-fit categories: tests for biopsy-naïve men (Prostate Health Index, Mi Prostate Score, 4K Score); tests for men with prior negative biopsies (ConfirmMDx, Progensa PCA3); and men on active surveillance (OncotypeDx, Prolaris, Decipher). Data on the role of these tests with the use of mpMRI have not been comprehensive and excludes several of the markers. More research is needed to determine the combined impact mpMRI and the novel biomarkers on the evaluation and management of PCa.

Prostate Cancer Biomarker Development: National Cancer Institute's Early Detection Research Network Prostate Cancer Collaborative Group Review

Prostate cancer remains the most common non-skin cancer and second leading cause of death among men in the United States. Although progress has been made in diagnosis and risk assessment, many clinical questions remain regarding early identification of prostate cancer and management. The early detection of aggressive disease continues to provide high curative rates if diagnosed in a localized state. Unfortunately, prostate cancer displays significant heterogeneity within the prostate organ and between individual patients making detection and treatment strategies complex. Although prostate cancer is common among men, the majority will not die from prostate cancer, introducing the issue of overtreatment as a major concern in clinical management of the disease. The focus of the future is to identify those at highest risk for aggressive prostate cancer and to develop prevention and screening strategies, as well as discerning the difference in malignant potential of diagnosed tumors. The Prostate Cancer Research Group of the National Cancer Institute's Early Detection Research Network has contributed to the progress in addressing these concerns. This summary is an overview of the activities of the group.See all articles in this CEBP Focus section, "NCI Early Detection Research Network: Making Cancer Detection Possible."

Adaptation of the prostate biopsy collaborative group risk calculator in patients with PSA less than 10 ng/ml improves its performance

PURPOSES

The prostate biopsy collaborative group risk calculator (PBCGRC) is a newly developed risk estimator for predicting prostate biopsy outcomes. However, its clinical usefulness is still unknown within the so-called gray area of PSA values. This study aimed to determine whether updating the PBCGRC improves its predictive performance for predicting any-grade and high-grade (HG), defined as biopsy Gleason score ≥ 7, prostate cancer (PCa) in patients with prostate-specific antigen (PSA) less than 10 ng/ml.

METHODS

The risk of any-grade and HGPCa was calculated using the PBCG risk calculation formulas updated by recalibration in the large, logistic recalibration and model revision. Predictive performances of the PBCGRC and the updated models were compared using discrimination, calibration, and clinical utility.

RESULTS

Within the study sample of 526 patients, PCa was detected in 193 (36.7%), and 78 (14.8%) of them had HGPCa. According to the calibration curves, the PBCGRC overestimated the risk of PCa. Predictive accuracy of the revised model was higher [the area under the receiver-operating characteristic curve (AUCs), 65.4% and 70.2%] than that of the PBCGRC (AUCs, 60.4% and 64.3%) for any-grade and HGPCa. The net benefit was greater for model revision in comparison with the original model.

CONCLUSION

The performance accuracy of PBCGRC for the prediction of any and HGPC in men undergoing prostate biopsy with PSA levels below 10 ng/ml is suboptimal. The model revision resulted with significant improvement in model performance. However, external validation of the revised model is necessary before its routine use in clinical practice.

Performance of PCA3 and TMPRSS2:ERG urinary biomarkers in prediction of biopsy outcome in the Canary Prostate Active Surveillance Study (PASS)

BACKGROUND

For men on active surveillance for prostate cancer, biomarkers may improve prediction of reclassification to higher grade or volume cancer. This study examined the association of urinary PCA3 and TMPRSS2:ERG (T2:ERG) with biopsy-based reclassification.

METHODS

Urine was collected at baseline, 6, 12, and 24 months in the multi-institutional Canary Prostate Active Surveillance Study (PASS), and PCA3 and T2:ERG levels were quantitated. Reclassification was an increase in Gleason score or ratio of biopsy cores with cancer to ≥34%. The association of biomarker scores, adjusted for common clinical variables, with short- and long-term reclassification was evaluated. Discriminatory capacity of models with clinical variables alone or with biomarkers was assessed using receiver operating characteristic (ROC) curves and decision curve analysis (DCA).

RESULTS

Seven hundred and eighty-two men contributed 2069 urine specimens. After adjusting for PSA, prostate size, and ratio of biopsy cores with cancer, PCA3 but not T2:ERG was associated with short-term reclassification at the first surveillance biopsy (OR = 1.3; 95% CI 1.0-1.7, p = 0.02). The addition of PCA3 to a model with clinical variables improved area under the curve from 0.743 to 0.753 and increased net benefit minimally. After adjusting for clinical variables, neither marker nor marker kinetics was associated with time to reclassification in subsequent biopsies.

CONCLUSIONS

PCA3 but not T2:ERG was associated with cancer reclassification in the first surveillance biopsy but has negligible improvement over clinical variables alone in ROC or DCA analyses. Neither marker was associated with reclassification in subsequent biopsies.

Prediction Medicine: Biomarkers, Risk Calculators and Magnetic Resonance Imaging as Risk Stratification Tools in Prostate Cancer Diagnosis

This review discusses the most recent evidence for currently available risk stratification tools in the detection of clinically significant prostate cancer (csPCa), and evaluates diagnostic strategies that combine these tools. Novel blood biomarkers, such as the Prostate Health Index (PHI) and 4Kscore, show similar ability to predict csPCa. Prostate cancer antigen 3 (PCA3) is a urinary biomarker that has inferior prediction of csPCa compared to PHI, but may be combined with other markers like TMPRSS2-ERG to improve its performance. Original risk calculators (RCs) have the advantage of incorporating easy to retrieve clinical variables and being freely accessible as a web tool/mobile application. RCs perform similarly well as most novel biomarkers. New promising risk models including novel (genetic) markers are the SelectMDx and Stockholm-3 model (S3M). Prostate magnetic resonance imaging (MRI) has evolved as an appealing tool in the diagnostic arsenal with even stratifying abilities, including in the initial biopsy setting. Merging biomarkers, RCs and MRI results in higher performances than their use as standalone tests. In the current era of prostate MRI, the way forward seems to be multivariable risk assessment based on blood and clinical parameters, potentially extended with information from urine samples, as a triaging test for the selection of candidates for MRI and biopsy.

Long non-coding RNAs in prostate cancer: Biological and clinical implications

Prostate cancer (PCa) is a major health issue in the Western world. Current clinical imperatives for this disease include better stratification of indolent versus aggressive disease to enable improved patient management, as well as the identification of more effective therapies for the prevention and treatment of metastatic and therapy-resistant PCa. The advent of next-generation transcriptomics led to the identification of an important class of molecules, long non-coding RNAs (lncRNAs). LncRNAs have critical functions in normal physiology, but their dysregulation has also been implicated in the development and progression of a variety of cancers, including PCa. Importantly, a subset of lncRNAs are highly prostate-specific, suggesting potential for utility as both biomarkers and therapeutic targets. In this review, we summarise the biology of lncRNAs and their mechanisms of action in the development and progression of prostate cancer. Additionally, we cast a critical eye over the potential for this class of molecules to impact on clinical practice.