Reducing unnecessary biopsy during prostate cancer screening using a four-kallikrein panel: an independent replication

Methylated DNA Markers in Voided Urine for the Identification of Clinically Significant Prostate Cancer

INTRODUCTION

Non-invasive assays are needed to better discriminate patients with prostate cancer (PCa) to avoid over-treatment of indolent disease. We analyzed 14 methylated DNA markers (MDMs) from urine samples of patients with biopsy-proven PCa relative to healthy controls and further studied discrimination of clinically significant PCa (csPCa) from healthy controls and Gleason 6 cancers.

METHODS

To evaluate the panel, urine from 24 healthy male volunteers with no clinical suspicion for PCa and 24 men with biopsy-confirmed disease across all Gleason scores was collected. Blinded to clinical status, DNA from the supernatant was analyzed for methylation signal within specific DNA sequences across 14 genes (HES5, ZNF655, ITPRIPL1, MAX.chr3.6187, SLCO3A1, CHST11, SERPINB9, WNT3A, KCNB2, GAS6, AKR1B1, MAX.chr3.8028, GRASP, ST6GALNAC2) by target enrichment long-probe quantitative-amplified signal assays.

RESULTS

Utilizing an overall specificity cut-off of 100% for discriminating normal controls from PCa cases across the MDM panel resulted in 71% sensitivity (95% CI: 49-87%) for PCa detection (4/7 Gleason 6, 8/12 Gleason 7, 5/5 Gleason 8+) and 76% (50-92%) for csPCa (Gleason ≥ 7). At 100% specificity for controls and Gleason 6 patients combined, MDM panel sensitivity was 59% (33-81%) for csPCa (5/12 Gleason 7, 5/5 Gleason 8+).

CONCLUSIONS

MDMs assayed in urine offer high sensitivity and specificity for detection of clinically significant prostate cancer. Prospective evaluation is necessary to estimate discrimination of patients as first-line screening and as an adjunct to prostate-specific antigen (PSA) testing.

Diagnostic Accuracy of Liquid Biomarkers for Clinically Significant Prostate Cancer Detection: A Systematic Review and Diagnostic Meta-analysis of Multiple Thresholds

CONTEXT

Many liquid biomarkers have entered clinical practice with the praise to improve the detection of clinically significant prostate cancer (csPCa), helping avoid unnecessary prostate biopsies.

OBJECTIVE

We aimed to assess the diagnostic accuracy of multianalyte biomarkers for csPCa detection using multiple thresholds.

EVIDENCE ACQUISITION

A comprehensive literature search was done through PubMed, Web of Science, and Scopus in March 2023 for prospective and retrospective studies reporting the diagnostic performance of liquid biomarkers for detecting csPCa. The outcomes of interest were the diagnostic performance of liquid biomarkers for csPCa detection and identification of optimal thresholds for each biomarker.

EVIDENCE SYNTHESIS

Overall, 49 studies were eligible for this meta-analysis. Using each representative threshold based on the Youden Index, the pooled sensitivity and specificity for detecting csPCa were 0.85 and 0.37 for prostate cancer gene 3 (PCA3), 0.85 and 0.52 for prostate health index (PHI), 0.87 and 0.58 for four kallikrein (4K), 0.82 and 0.56 for SelectMDx, 0.85 and 0.54 for ExoDx, and 0.82 and 0.59 for mi prostate score (MPS), respectively. The diagnostic odds ratio was highest for 4K (8.84), followed by MPS (7.0) and PHI (6.28). According to the meta-analysis incorporating multiple thresholds, the corresponding sensitivity was 0.77 for 4K, 0.69 for PHI, and 0.63 for PCA3; specificity was 0.72 for PHI, 0.70 for 4K, and 0.69 for PCA3.

CONCLUSIONS

Regarding the detection of csPCa, 4K had the highest diagnostic performance among the commercial liquid biomarkers. Based on the optimal thresholds calculated by the present meta-analysis, 4K had the highest sensitivity and PHI had the highest specificity for detecting csPCa. Nevertheless, clinical decision-making requires combination strategies between liquid and imaging biomarkers.

PATIENT SUMMARY

Novel biomarkers for prostate cancer detection were useful for more accurate diagnosis of clinically significant prostate cancer to avoid unnecessary biopsies.

Predicting the Diagnosis of Prostate Cancer with a Novel Blood-Based Biomarker: Comparison of Its Performance with Prostate-Specific Antigen

The purpose of this study was to assess the efficacy, specificity, and predictive value of a newly discovered biomarker, Zinc finger-like1 protein (referred to as neuroendocrine marker, NEM) for the detection of prostate cancer (PCa). We retrospectively analyzed banked plasma samples from 508 men, with a median age of 67 years (range 48-97), to compare the performance of NEM and PSA in predicting subsequent histologic PCa. The cohort consisted of four groups of patients visiting a urology clinic: (1) patients not diagnosed with either benign prostatic disease or prostate cancer (PCa) were defined as normal; (2) patients diagnosed with benign hyperplasia (BPH) but not PCa; (3) patients with confirmed PCa; and (4) patients with cancer other than PCa. The normal men displayed a mean NEM plasma level of 0.948 ± 0.051 ng/mL, which increased to 1.813 ± 0.315 ng/mL in men with BPH, 86.49 ± 15.51 ng/mL in men with PCa, and 10.47 ± 1.029 ng/mL in men with other Ca. The corresponding concentrations of prostate-specific antigen (PSA) in these subjects were 1.787 ± 0.135, 5.405 ± 0.699, 35.77 ± 11.48 ng/mL, and 8.036 ± 0.518, respectively. Receiver operating characteristic (ROC) curve analysis was performed to compare NEM and PSA performance, and the Jouden Index for each biomarker was calculated to determine cut-off points for each biomarker. The area under the ROC curve to predict PCa was 0.99 for NEM and 0.81 for PSA (p < 0.0001). The cut-off for NEM was at 1.9 ng/mL, with sensitivity of 98% and specificity of 97%. The corresponding PSA values were 4.4 ng/mL, with sensitivity of 76% and specificity of 95%. The predictive value of each biomarker in a patient was matched with his pathologic data to determine the accuracy of each biomarker. NEM was more accurate than PSA in differentiating cancer from benign conditions, such as BPH or prostatitis. In conclusion, NEM was a better predictor of PCa than PSA in patients visiting urology clinics. NEM tests, either alone or in conjunction with other biomarkers, provide a reliable, non-invasive, and inexpensive test to remarkably reduce false positives and thereby reduce the number of diagnostic biopsies and associated painful procedures and the loss of quality of life.

Established and emerging liquid biomarkers for prostate cancer detection: A review

Prostate cancer remains one of the most frequently diagnosed cancers among men in the world today. Since its introduction in 1987 and FDA approval in 1994, prostate specific antigen (PSA) has reduced prostate cancer specific mortality considerably. However, the positive and negative predictive value of PSA is less than ideal and can lead to the over-detection of clinically insignificant prostate cancer. In the search for better screening measures to identify this cohort, liquid biomarkers for prostate cancer have emerged. In this review we will explore the commonly used urine and blood based prostate cancer liquid biomarkers. We detail the mechanism of each test and the validation studies that underscore their efficacy. Additionally, we will examine each test's effect on shared decision making as well as their cost efficacy in clinical practice.

Lectin-nanoparticle concept for free PSA glycovariant providing superior cancer specificity

BACKGROUND

Using lectins to target cancer-associated modifications of PSA glycostructure for identification of clinically significant prostate cancers, e.g., Gleason score (GS) ≥ 7, from benign and indolent cancers (GS 6), is highly promising yet technically challenging. From previous findings to quantify increased PSA fucosylation in urine, we set out to construct a robust, specific test concept suitable for plasma samples.

METHODS

Macrophage galactose-binding lectin (MGL) coupled to 100 nm Eu3 + -nanoparticles was used to probe PSA captured from cancer cell lines, seminal plasma, and plasma samples from 249 patients with a clinical suspicion of prostate cancer onto 3 mm dense spots of free PSA antibody fab fragments. Results were compared to four kallikrein tests: tPSA, fPSA, iPSA and hK2.

RESULTS

The fPSAMGLglycovariant provided superior discrimination of the GS ≥ 7 and benign + GS 6 groups (p 0.0003) compared to fPSA (NS). The corresponding AUC in ROC analysis was 0.70 compared to 0.66 for tPSA. In contrast to all four kallikrein tests, the fPSAMGLGV was independent of prostate gland volume. Using a logistic regression analysis the fPSAMGLGV significantly improved on the four-kallikrein model.

CONCLUSIONS

Due to Eu-nanoparticles and a dense fPSA capture spot, the fPSAMGL glycovariant identifies an fPSA subform with the highest cancer specificity compared to the four conventional kallikreins.

Cancer-specific risk prediction with a serum microRNA signature

We recently derived and validated a serum-based microRNA risk score (miR-score) that predicted colorectal cancer (CRC) occurrence with very high accuracy within 14 years of follow-up in a population-based cohort study from Germany (ESTHER cohort). Here, we aimed to evaluate associations of the CRC-specific miR-score with the risk of developing other common cancers, including female breast cancer (BC), lung cancer (LC), and prostate cancer (PC), in the ESTHER cohort. MicroRNAs (miRNAs) were profiled by quantitative real-time PCR in serum samples collected at baseline from randomly selected incident cases of BC (n = 90), LC (n = 88), and PC (n = 93) and participants without diagnosis of CRC, LC, BC, or PC (controls, n = 181) until the end of the 17-year follow-up. Multivariate logistic regression models were used to evaluate the associations of the miR-score with BC, LC, and PC incidence. The miR-score showed strong inverse associations with BC and LC incidence [odds ratio per 1 standard deviation increase: 0.60 (95% confidence interval [CI] 0.43-0.82), p = 0.0017, and 0.64 (95% CI 0.48-0.84),p = 0.0015, respectively]. Associations with PC were not statistically significant but pointed in the positive direction. Our study highlights the potential of serum-based miRNA biomarkers for cancer-specific risk prediction. Further large cohort studies aiming to investigate, validate, and optimize the use of circulating miRNA signatures for cancer risk assessment are warranted.

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.

Development and evaluation of the MiCheck® Prostate test for clinically significant prostate cancer

BACKGROUND

There is a clinical need to identify patients with an elevated PSA who would benefit from prostate biopsy due to the presence of clinically significant prostate cancer (CSCaP). We have previously reported the development of the MiCheck® Test for clinically significant prostate cancer. Here, we report MiCheck's further development and incorporation of the Roche Cobas standard clinical chemistry analyzer.

OBJECTIVES

To further develop and adapt the MiCheck® Prostate test so it can be performed using a standard clinical chemistry analyzer and characterize its performance using the MiCheck-01 clinical trial sample set.

DESIGN, SETTINGS, AND PARTICIPANTS

About 358 patient samples from the MiCheck-01 US clinical trial were used for the development of the MiCheck® Prostate test. These consisted of 46 controls, 137 non-CaP, 62 non-CSCaP, and 113 CSCaP.

METHODS

Serum analyte concentrations for cellular growth factors were determined using custom-made Luminex-based R&D Systems multi-analyte kits. Analytes that can also be measured using standard chemistry analyzers were examined for their ability to contribute to an algorithm with high sensitivity for the detection of clinically significant prostate cancer. Samples were then re-measured using a Roche Cobas analyzer for development of the final algorithm.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Logistic regression modeling with Monte Carlo cross-validation was used to identify Human Epidydimal Protein 4 (HE4) as an analyte able to significantly improve the algorithm specificity at 95% sensitivity. A final model was developed using analyte measurements from the Cobas analzyer.

RESULTS

The MiCheck® logistic regression model was developed and consisted of PSA, %free PSA, DRE, and HE4. The model differentiated clinically significant cancer from no cancer or not-clinically significant cancer with AUC of 0.85, sensitivity of 95%, and specificity of 50%. Applying the MiCheck® test to all evaluable 358 patients from the MiCheck-01 study demonstrated that up to 50% of unnecessary biopsies could be avoided while delaying diagnosis of only 5.3% of Gleason Score (GS) ≥3+4 cancers, 1.8% of GS≥4+3 cancers and no cancers of GS 8 to 10.

CONCLUSIONS

The MiCheck® Prostate test identifies clinically significant prostate cancer with high sensitivity and negative predictive value (NPV). It can be performed in a clinical laboratory using a Roche Cobas clinical chemistry analyzer. The MiCheck® Prostate test could assist in reducing unnecessary prostate biopsies with a marginal number of patients experiencing a delayed diagnosis.

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.

Implementation of 4Kscore as a Secondary Test Before Prostate Biopsy: Impact on US Population Trends for Prostate Cancer

Prostate cancer screening using prostate-specific antigen (PSA) reduces prostate cancer mortality at the cost of unnecessary prostate biopsy, overdiagnosis, and overtreatment. Several secondary tests have been developed to restrict biopsy to men at the greatest risk of high-grade disease. 4Kscore is a widely used secondary test that has been shown to reduce biopsy rates by approximately two-thirds in routine clinical practice. We estimated how 4Kscore implementation has affected cancer trends in the US population. We combined data from the US validation study of 4Kscore with data from the diagnostic test impact study, using a basis of 70 000 on-label 4Kscore tests performed annually. We estimate that each year, 4Kscore leads to 45 200 fewer biopsies and 9400 fewer overdiagnoses of low-grade cancer, at the cost of delayed diagnosis of high-grade prostate cancer for 3450 patients, of whom two-thirds have International Society of Urological Pathology grade group 2 disease. These findings need to be taken into consideration when studying epidemiologic trends in prostate cancer. They also suggest that high levels of overdiagnosis and overtreatment are not inevitable characteristics of PSA screening, but can be mitigated by additional tests.

Patient summary

We estimate that use of a test called 4Kscore to predict the probability that a patient has high-grade prostate cancer has significantly reduced the number of unnecessary biopsies and overdiagnosis of low-grade cancer in the USA. These decisions may result in delayed diagnosis of high-grade cancer in some patients. 4Kscore is a useful additional test in the management of prostate cancer.

Systematic review of methods used to improve the efficacy of magnetic resonance in early detection of clinically significant prostate cancer

BACKGROUND AND OBJECTIVE

Prostate cancer (PC) is the malignant neoplasm with the highest incidence after lung cancer worldwide. The objective of this study is to review the literature on the methods that improve the efficacy of the current strategy for the early diagnosis of clinically significant PC (csPC), based on the performance of magnetic resonance imaging (RM) and targeted biopsies when suspicious lesions are detected, in addition to systematic biopsy.

EVIDENCE ACQUISITION

A systematic literature review was performed in PubMed, Web of Science and Cochrane according to the PRISMA criteria (Preferred Reporting Items for Systematic Reviews and Meta-Analyses), using the search terms: multiparametric magnetic resonance imaging, biparametric magnetic resonance imaging, biomarkers in prostate cancer, prostate cancer y early diagnosis. A total of 297 references were identified and, using the PICO selection criteria, 21 publications were finally selected to synthesize the evidence.

EVIDENCE SYNTHESIS

With the consolidation of MRI as the test of choice for the diagnosis of prostate cancer, the role of PSA density (PSAD) becomes relevant as a predictive tool included in prediction nomograms, without added cost. PSAD and diagnostic markers, combined with MRI, offer a high diagnostic power with an area under curve (AUC) above 0.7. Only the SHTLM3 model integrates markers in the creation of a nomogram. Prediction models also offer consistent efficacy with an AUC greater than 0.8 when associating MRI.

CONCLUSIONS

The efficacy of MRI in clinically significant prostate cancer detection can be improved with different parameters in order to generate predictive models that support decision making.

Development of a Whole-urine, Multiplexed, Next-generation RNA-sequencing Assay for Early Detection of Aggressive Prostate Cancer

BACKGROUND

Despite biomarker development advances, early detection of aggressive prostate cancer (PCa) remains challenging. We previously developed a clinical-grade urine test (Michigan Prostate Score [MiPS]) for individualized aggressive PCa risk prediction. MiPS combines serum prostate-specific antigen (PSA), the TMPRSS2:ERG (T2:ERG) gene fusion, and PCA3 lncRNA in whole urine after digital rectal examination (DRE).

OBJECTIVE

To improve on MiPS with a novel next-generation sequencing (NGS) multibiomarker urine assay for early detection of aggressive PCa.

DESIGN, SETTING, AND PARTICIPANTS

Preclinical development and validation of a post-DRE urine RNA NGS assay (Urine Prostate Seq [UPSeq]) assessing 84 PCa transcriptomic biomarkers, including T2:ERG, PCA3, additional PCa fusions/isoforms, mRNAs, lncRNAs, and expressed mutations. Our UPSeq model was trained on 73 patients and validated on a held-out set of 36 patients representing the spectrum of disease (benign to grade group [GG] 5 PCa).

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

The area under the receiver operating characteristic curve (AUC) of UPSeq was compared with PSA, MiPS, and other existing models/biomarkers for predicting GG ≥3 PCa.

RESULTS AND LIMITATIONS

UPSeq demonstrated high analytical accuracy and concordance with MiPS, and was able to detect expressed germline HOXB13 and somatic SPOP mutations. In an extreme design cohort (n = 109; benign/GG 1 vs GG ≥3 PCa, stratified to exclude GG 2 cancer in order to capture signal difference between extreme ends of disease), UPSeq showed differential expression for T2:ERG.T1E4 (1.2 vs 78.8 median normalized reads, p < 0.00001) and PCA3 (1024 vs 2521, p = 0.02), additional T2:ERG splice isoforms, and other candidate biomarkers. Using machine learning, we developed a 15-transcript model on the training set (n = 73) that outperformed serum PSA and sequencing-derived MiPS in predicting GG ≥3 PCa in the held-out validation set (n = 36; AUC 0.82 vs 0.69 and 0.69, respectively).

CONCLUSIONS

These results support the potential utility of our novel urine-based RNA NGS assay to supplement PSA for improved early detection of aggressive PCa.

PATIENT SUMMARY

We have developed a new urine-based test for the detection of aggressive prostate cancer, which promises improvement upon current biomarker tests.

Independent validation of a pre-specified four-kallikrein marker model for prediction of adverse pathology and biochemical recurrence

BACKGROUND

Accurate markers for prostate cancer (PC) risk stratification could aid decision-making for initial management strategies. The 4Kscore has an undefined role in predicting outcomes after radical prostatectomy (RP).

METHODS

We included 1476 patients with 4Kscore measured prior to RP at two institutions. The 4Kscore was assessed for prediction of adverse pathology at RP and biochemical recurrence (BCR) relative to a clinical model. We pre-specified that all analyses would be assessed in biopsy Grade Group 1 (GG1) or 2 (GG2) PC patients, separately.

RESULTS

The 4Kscore increased discrimination for adverse pathology in all patients (delta area under the receiver operative curve (AUC) 0.009, 95% confidence interval (CI) 0.002, 0.016; clinical model AUC 0.767), driven by GG1 (delta AUC 0.040, 95% CI 0.006, 0.073) rather than GG2 patients (delta AUC 0.005, 95% CI -0.012, 0.021). Adding 4Kscore improved prediction of BCR in all patients (delta C-index 0.014, 95% CI 0.007, 0.021; preop-BCR nomogram C-index 0.738), again with larger changes in GG1 than in GG2.

CONCLUSIONS

This study validates prior investigations on the use of 4Kscore in men with biopsy-confirmed PC. Men with GG1 PC and a high 4Kscore may benefit from additional testing to guide treatment selection. Further research is warranted regarding the value of the 4Kscore in men with biopsy GG2 PC.

Liquid biomarkers for early detection of prostate cancer and summary of available data for their use in African-American men

BACKGROUND

Several liquid biomarker tests have been developed to account for the limitations of prostate specific antigen (PSA) screening prior to prostate biopsy. African ancestry is an established risk factor for prostate cancer (PCa) and must be particularly considered when evaluating patients with liquid biomarkers. While multiple tests have been developed over decades of exploration, recent advances can help patients and physicians incorporate data into a broader clinical context.

METHODS

We sought to review currently available liquid biomarker tests in a practical, clinically directed fashion with particular focus on performance in men with African ancestry. We reviewed discovery and validation studies and highlight important considerations for each test.

RESULTS

We discuss the advantages and limitations of percent free PSA, Prostate Health Index, Progensa® PCA3, ExoDx® Prostate Test, SelectMDx®, 4Kscore® Test, and Mi-Prostate Score and summarize salient studies on their use. A literature review of evidence specifically for men with African ancestry was conducted and available studies were summarized.

CONCLUSIONS

Liquid biomarkers can be useful tools for aiding in risk stratification prior to prostate biopsy. Use of such tests should be individualized based on a thorough knowledge of supporting evidence and the goals of the patient and physician. Further study should prioritize evaluation of such biomarkers in men with African ancestry.

Prostate cancer biomarkers: a practical review based on different clinical scenarios

Traditionally, diagnosis and staging of prostate cancer (PCa) have been based on prostate-specific antigen (PSA) level, digital rectal examination (DRE), and transrectal ultrasound (TRUS) guided prostate biopsy. Biomarkers have been introduced into clinical practice to reduce the overdiagnosis and overtreatment of low-grade PCa and increase the success of personalized therapies for high-grade and high-stage PCa. The purpose of this review was to describe available PCa biomarkers and examine their use in clinical practice. A nonsystematic literature review was performed using PubMed and Scopus to retrieve papers related to PCa biomarkers. In addition, we manually searched websites of major urological associations for PCa guidelines to evaluate available evidence and recommendations on the role of biomarkers and their potential contribution to PCa decision-making. In addition to PSA and its derivates, thirteen blood, urine, and tissue biomarkers are mentioned in various PCa guidelines. Retrospective studies have shown their utility in three main clinical scenarios: (1) deciding whether to perform a biopsy, (2) distinguishing patients who require active treatment from those who can benefit from active surveillance, and (3) defining a subset of high-risk PCa patients who can benefit from additional therapies after RP. Several validated PCa biomarkers have become commercially available in recent years. Guidelines now recommend offering these tests in situations in which the assay result, when considered in combination with routine clinical factors, is likely to affect management. However, the lack of direct comparisons and the unproven benefits, in terms of long-term survival and cost-effectiveness, prevent these biomarkers from being integrated into routine clinical use.

The Autoantibodies against Tumor-Associated Antigens as Potential Blood-Based Biomarkers in Thyroid Neoplasia: Rationales, Opportunities and Challenges

The Autoantibodies targeting Tumor-Associated Antigens (TAA-AAbs) emerge as a result of a variety of tumor-related immunogenic stimuli and may be regarded as the eyewitnesses to the anti-tumor immune response. TAA-AAbs may be readily detected in peripheral blood to unveil the presence of a particular TAA-expressing tumor, and a fair number of TAAs eliciting the tumor-associated autoantibody response have been identified. The potential of TAA-AAbs as tumor biomarkers has been extensively studied in many human malignancies with a major influence on public health; however, tumors of the endocrine system, and, in particular, the well-differentiated follicular cell-derived thyroid neoplasms, remain understudied in this context. This review provides a detailed perspective on and legitimate rationales for the potential use of TAA-AAbs in thyroid neoplasia, with particular reference to the already established diagnostic implications of the TAA-AAbs in human cancer, to the windows for improvement and diagnostic niches in the current workup strategies in nodular thyroid disease and differentiated thyroid cancer that TAA-AAbs may successfully occupy, as well as to the proof-of-concept studies demonstrating the usefulness of TAA-AAbs in thyroid oncology, particularly for the pre-surgical discrimination between tumors of different malignant potential in the context of the indeterminate results of the fine-needle aspiration cytology.

Extracellular Vesicle Proteome in Prostate Cancer: A Comparative Analysis of Mass Spectrometry Studies

Molecular diagnostics based on discovery research holds the promise of improving screening methods for prostate cancer (PCa). Furthermore, the congregated information prompts the question whether the urinary extracellular vesicles (uEV) proteome has been thoroughly explored, especially at the proteome level. In fact, most extracellular vesicles (EV) based biomarker studies have mainly targeted plasma or serum. Therefore, in this study, we aim to inquire about possible strategies for urinary biomarker discovery particularly focused on the proteome of urine EVs. Proteomics data deposited in the PRIDE archive were reanalyzed to target identifications of potential PCa markers. Network analysis of the markers proposed by different prostate cancer studies revealed moderate overlap. The recent throughput improvements in mass spectrometry together with the network analysis performed in this study, suggest that a larger standardized cohort may provide potential biomarkers that are able to fully characterize the heterogeneity of PCa. According to our analysis PCa studies based on urinary EV proteome presents higher protein coverage compared to plasma, plasma EV, and voided urine proteome. This together with a direct interaction of the prostate gland and urethra makes uEVs an attractive option for protein biomarker studies. In addition, urinary proteome based PCa studies must also evaluate samples from bladder and renal cancers to assess specificity for PCa.

Individual Patient Data Meta-analysis of Discrimination of the Four Kallikrein Panel Associated With the Inclusion of Prostate Volume

OBJECTIVE

To assess whether adding prostate volume to the kallikrein panel improves discrimination for ISUP Grade Group 2 or higher (GG2+) disease, as some men may have volume measurements available at the time of blood draw. While prostate volume predicts biopsy outcome, it requires an imaging procedure for measurement. The four kallikrein panel - commercially available as the 4Kscore - predicts risk of GG2+ disease and requires only a blood draw.

MATERIALS AND METHODS

A total of 9131 patients with available prostate volume and total PSA ≤25 ng/ml from 5 historical (sextant biopsy, pre-ISUP 2005 grading) and 4 contemporary cohorts (10+ cores, ISUP 2005 grading). Previously published kallikrein panel models were used to predict risk of GG2+. Volume was added to the model in each cohort and change in discrimination was meta-analyzed.

RESULTS

Increased prostate volume was associated with decreased risk of GG2+ disease after controlling for the kallikrein panel in 7/9 cohorts. However, kallikrein panel discrimination (0.817, 95% CI 0.802, 0.831) was not improved after including volume (AUC difference 0.002, 95% CI -0.003, 0.006). Heterogeneity (P <.0001) was driven by an AUC increase in 1 cohort of academic cancer centers (0.044, 95% CI 0.025, 0.064), with no evidence of heterogeneity after excluding this cohort (P = .15).

CONCLUSION

The kallikrein panel provides a non-invasive approach to assess the risk of high-grade prostate cancer. Our results do not justify the inclusion of prostate volume in the four kallikrein panel. There is some evidence that the predictive value of prostate volume is provider dependent: further research is needed to address this question.

Modified Predictive Model and Nomogram by Incorporating Prebiopsy Biparametric Magnetic Resonance Imaging With Clinical Indicators for Prostate Biopsy Decision Making

Purpose

The purpose of this study is to explore the value of combining bpMRI and clinical indicators in the diagnosis of clinically significant prostate cancer (csPCa), and developing a prediction model and Nomogram to guide clinical decision-making.

Methods

We retrospectively analyzed 530 patients who underwent prostate biopsy due to elevated serum prostate specific antigen (PSA) levels and/or suspicious digital rectal examination (DRE). Enrolled patients were randomly assigned to the training group (n = 371, 70%) and validation group (n = 159, 30%). All patients underwent prostate bpMRI examination, and T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI) sequences were collected before biopsy and were scored, which were respectively named T2WI score and DWI score according to Prostate Imaging Reporting and Data System version 2 (PI-RADS v.2) scoring protocol, and then PI-RADS scoring was performed. We defined a new bpMRI-based parameter named Total score (Total score = T2WI score + DWI score). PI-RADS score and Total score were separately included in the multivariate analysis of the training group to determine independent predictors for csPCa and establish prediction models. Then, prediction models and clinical indicators were compared by analyzing the area under the curve (AUC) and decision curves. A Nomogram for predicting csPCa was established using data from the training group.

Results

In the training group, 160 (43.1%) patients had prostate cancer (PCa), including 128 (34.5%) with csPCa. Multivariate regression analysis showed that the PI-RADS score, Total score, f/tPSA, and PSA density (PSAD) were independent predictors of csPCa. The prediction model that was defined by Total score, f/tPSA, and PSAD had the highest discriminatory power of csPCa (AUC = 0.931), and the diagnostic sensitivity and specificity were 85.1% and 87.5%, respectively. Decision curve analysis (DCA) showed that the prediction model achieved an optimal overall net benefit in both the training group and the validation group. In addition, the Nomogram predicted csPCa revealed good estimation when compared with clinical indicators.

Conclusion

The prediction model and Nomogram based on bpMRI and clinical indicators exhibit a satisfactory predictive value and improved risk stratification for csPCa, which could be used for clinical biopsy decision-making.

Tumour markers of prostate cancer: The post-PSA era

Although PSA-based prostate cancer (PCa) screening had a positive impact in reducing PCa mortality, it also led to overdiagnosis, overtreatment and to a significant number of unnecessary biopsies. In the post-PSA era, new biomarkers have emerged that can complement the information given by PSA, towards a better cancer diagnostic specificity, and also allow a better estimate of the aggressiveness of the disease and its clinical outcome. That means those markers have the potential to assist the clinician in the decision-making processes, such as whether or not to perform a biopsy, and to make the best treatment choice among the new therapeutic options available, including active surveillance (AS) in lower risk disease. In this article, we will review several of those more recent diagnostic markers (4Kscore®, [-2]proPSA and Prostate Health Index (PHI), SelectMDx®, ConfirmMDx®, Progensa® Prostate Cancer Antigen 3, Mi-Prostate Score, ExoDx™ Prostate Test, the Stockholm-3 test and ERSPC risk calculators) and prognostic markers (OncotypeDX® Genomic Prostate Score, Prolaris®, Decipher® and ProMark®). We will also address some new liquid biopsy approaches - circulating tumour cells and cell-free DNA (cfDNA) - with a potential role in metastatic castration-resistant PCa and will briefly give some future perspectives, mostly outlooking epigenetic markers.

Biomarkers for detection of clinically significant prostate cancer: contemporary clinical data and future directions

Use of serum prostate-specific antigen (PSA) testing for early detection of prostate cancer appears to reduce cancer-specific mortality. Due to the limited specificity of PSA for clinically significant [Grade Group (GG) ≥2] cancer, however, screening carries substantial risks, including frequent unnecessary prostate biopsies and overdetection of non-aggressive cancers. To that end, serum and urine biomarkers with improved specificity for GG ≥2 cancer have been proposed for clinical use following PSA. In the current article, we present clinical validation data for five such biomarkers: PHI, 4Kscore, SelectMDx, ExoDx, and MPS. For all studies, we specify the study population (overall biopsy referral vs. pre-specified PSA ranges), previous biopsy status (biopsy-naïve vs. previous negative biopsy), and the proportion of subjects diagnosed with GG ≥2 cancer. Outcomes include test performance characteristics: sensitivity, specificity, negative predictive value (NPV), and positive predictive value (PPV). Published data were used to compute the number of unnecessary biopsies avoided and number of GG ≥2 cancers missed if the biomarker had been used clinically to select for prostate biopsy. The evidence review is preceded by a primer on these and other clinically-relevant summary statistics.

Tissue- and Liquid-Based Biomarkers in Prostate Cancer Precision Medicine

Worldwide, prostate cancer (PC) is the second-most-frequently diagnosed male cancer and the fifth-most-common cause of all cancer-related deaths. Suspicion of PC in a patient is largely based upon clinical signs and the use of prostate-specific antigen (PSA) levels. Although PSA levels have been criticised for a lack of specificity, leading to PC over-diagnosis, it is still the most commonly used biomarker in PC management. Unfortunately, PC is extremely heterogeneous, and it can be difficult to stratify patients whose tumours are unlikely to progress from those that are aggressive and require treatment intensification. Although PC-specific biomarker research has previously focused on disease diagnosis, there is an unmet clinical need for novel prognostic, predictive and treatment response biomarkers that can be used to provide a precision medicine approach to PC management. In particular, the identification of biomarkers at the time of screening/diagnosis that can provide an indication of disease aggressiveness is perhaps the greatest current unmet clinical need in PC management. Largely through advances in genomic and proteomic techniques, exciting pre-clinical and clinical research is continuing to identify potential tissue, blood and urine-based PC-specific biomarkers that may in the future supplement or replace current standard practices. In this review, we describe how PC-specific biomarker research is progressing, including the evolution of PSA-based tests and those novel assays that have gained clinical approval. We also describe alternative diagnostic biomarkers to PSA, in addition to biomarkers that can predict PC aggressiveness and biomarkers that can predict response to certain therapies. We believe that novel biomarker research has the potential to make significant improvements to the clinical management of this disease in the near future.

The current value of histological findings in negative prostate biopsies to predict the future risk of clinically significant prostate cancer

BACKGROUND

Repeat prostate biopsy (PBx) is recommended under persistent suspicion of prostate cancer (PCa) or in the face of the following findings: atypical small acinar proliferation (ASAP); extense (≥3 biopsy sites) high-grade prostatic intraepithelial neoplasia (HGPIN); or HGPIN with atypical glands; suspicious for adenocarcinoma (PIN-ATYP). Nowadays; multiparametric magnetic resonance imaging (mpMRI) and mpMRI targeted PBx (MRI-TBx) are recommended in repeat PBx. Our objective was to analyze the current value of ASAP; mHGPIN; PIN-ATYP and other histological findings to predict clinically significant PCa (csPCa) risk.

METHODS

Retrospective analysis of 377 repeat PBxs. MRI-TBx was performed when Prostate Imaging-Reporting and Data System (PI-RADS) score >3 and 12-core transrectal ultrasound (TRUS) systematic PBx when ≤2. ASAP; HGPIN; mHGPIN; PIN-ATYP; and 8 other histological findings were prospectively reported in negative PBx. CsPCa was defined as ISUP group grade >2.

RESULTS

Incidence of ASAP; multifocal HGPIN (mHGPIN) and PINATYP was 4.2%; 39.7% and 3.7% respectively; and csPCa rate was statistically similar among men with these histological findings. However; the rate of csPCa was 22.2% when proliferative inflammatory atrophy (PIA) was present; and 36.1% when it was not. PIA was the only histological finding which predicted lower risk of csPCa; with an OR of 0.54 (95%CI: 0.308-0.945; P = .031). In addition; PIA was an independent predictor of a model combining clinical variables and mpMRI which reached area under de ROC curve of 0.86 (95%CI: 0.83-0.90).

CONCLUSION

PIA emerged as the only predictive histological finding of csPCa risk and can contribute to a predictive model. mHGPIN failed to predict csPCa risk. The low incidence of ASAP (4.2%) and PIN-ATYP (3.7%) prevented us from drawing conclusions.

Can serum endoglin be used to improve the diagnostic performance in prostate cancer?

PURPOSE

New biomarkers may contribute to avoid unnecessary biopsies resulting from the suboptimal performance of prostate-specific antigen (PSA) testing. This study aimed to assess serum endoglin as a prostate cancer (PCa) diagnostic tool among biopsy candidates.

METHODS

A total of 262 consecutive patients referred for prostate biopsy based on abnormal digital rectal examination and/or elevated total PSA (tPSA) who had serum endoglin assessed by solid-phase enzyme-linked immunosorbent assay were selected. Receiver operating characteristic curves were used to compare the predictive accuracy of different combinations of biomarkers to distinguish between PCa and benign prostatic conditions, and to identify cut-offs that maximize the ability of endoglin to rule out patients for biopsy (highest sensitivities).

RESULTS

Serum endoglin levels were higher in patients with PCa (median: 7.86 vs. 5.88 pg/mL, P < 0.001). Among patients with baseline tPSA ≤ 10 ng/mL the area under the curve was 0.69 for endoglin. Approximately one-quarter of the patients had serum endoglin < 4.92 ng/mL (sensitivity: 90.3%; specificity: 32.8%), and the probability of PCa varied from 37.7% before testing to 15.2% among those with low endoglin levels [negative predictive value (NPV) = 84.8%]. When restricting the analyses to patients with free/total PSA ratio > 0.25, the probability of cancer was less than 5% among those with serum endoglin < 6.04 ng/mL (sensitivity: 93.8%; specificity: 56.1%), corresponding to a NPV of 95.8%; this could allow sparing approximately 40% of patients from biopsy.

CONCLUSIONS

Serum endoglin may be useful in clinical practice to distinguish between PCa and non-cancer patients among prostatic biopsy candidates.

The current value of histological findings in negative prostate biopsies to predict the future risk of clinically significant prostate cancer

INTRODUCTION

Repeat prostate biopsy (PBx) is recommended under persistent suspicion of prostate cancer (PCa) or in the face of the following findings: atypical small acinar proliferation (ASAP), extense (≥3 biopsy sites) high-grade prostatic intraepithelial neoplasia (HGPIN), or HGPIN with atypical glands, suspicious for adenocarcinoma (PIN-ATYP). Nowadays, multiparametric magnetic resonance imaging (mpMRI) and mpMRI targeted PBx (MRI-TBx) are recommended in repeat PBx. Our objective was to analyze the current value of ASAP, mHGPIN, PIN-ATYP and other histological findings to predict clinically significant PCa (csPCa) risk.

METHODS

Retrospective analysis of 377 repeat PBxs. MRI-TBx was performed when Prostate Imaging-Reporting and Data System (PI-RADS) score>3 and 12-core transrectal ultrasound (TRUS) systematic PBx when≤2. ASAP, HGPIN, mHGPIN, PIN-ATYP, and 8 other histological findings were prospectively reported in negative PBx. CsPCa was defined as ISUP group grade>2.

RESULTS

Incidence of ASAP, multifocal HGPIN (mHGPIN) and PINATYP was 4.2%, 39.7% and 3.7% respectively, and csPCa rate was statistically similar among men with these histological findings. However, the rate of csPCa was 22.2% when proliferative inflammatory atrophy (PIA) was present, and 36.1% when it was not. PIA was the only histological finding which predicted lower risk of csPCa, with an OR of .54 (95% CI: .308-.945, P=.031). In addition, PIA was an independent predictor of a model combining clinical variables and mpMRI which reached area under de ROC curve of .86 (95% CI: .83-.90).

CONCLUSIONS

PIA emerged as the only predictive histological finding of csPCa risk and can contribute to a predictive model. mHGPIN failed to predict csPCa risk. The low incidence of ASAP (4.2%) and PIN-ATYP (3.7%) prevented us from drawing conclusions.

Biomarkers in Prostate Cancer Diagnosis: From Current Knowledge to the Role of Metabolomics and Exosomes

Early detection of prostate cancer (PC) is largely carried out using assessment of prostate-specific antigen (PSA) level; yet it cannot reliably discriminate between benign pathologies and clinically significant forms of PC. To overcome the current limitations of PSA, new urinary and serum biomarkers have been developed in recent years. Although several biomarkers have been explored in various scenarios and patient settings, to date, specific guidelines with a high level of evidence on the use of these markers are lacking. Recent advances in metabolomic, genomics, and proteomics have made new potential biomarkers available. A number of studies focused on the characterization of the specific PC metabolic phenotype using different experimental approaches has been recently reported; yet, to date, research on metabolomic application for PC has focused on a small group of metabolites that have been known to be related to the prostate gland. Exosomes are extracellular vesicles that are secreted from all mammalian cells and virtually detected in all bio-fluids, thus allowing their use as tumor biomarkers. Thanks to a general improvement of the technical equipment to analyze exosomes, we are able to obtain reliable quantitative and qualitative information useful for clinical application. Although some pilot clinical investigations have proposed potential PC biomarkers, data are still preliminary and non-conclusive.

Biomarkers for prostate cancer: prostate-specific antigen and beyond

In recent years, several new biomarkers supplementing the role of prostate-specific antigen (PSA) have become available for men with prostate cancer. Although widely used in an ad hoc manner, the role of PSA in screening asymptomatic men for prostate cancer is controversial. Several expert panels, however, have recently recommended limited PSA screening following informed consent in average-risk men, aged 55-69 years. As a screening test for prostate cancer however, PSA has limited specificity and leads to overdiagnosis which in turn results in overtreatment. To increase specificity and reduce the number of unnecessary biopsies, biomarkers such as percent free PSA, prostate health index (PHI) or the 4K score may be used, while Progensa PCA3 may be measured to reduce the number of repeat biopsies in men with a previously negative biopsy. In addition to its role in screening, PSA is also widely used in the management of patients with diagnosed prostate cancer such as in surveillance following diagnosis, monitoring response to therapy and in combination with both clinical and histological criteria in risk stratification for recurrence. For determining aggressiveness and predicting outcome, especially in low- or intermediate-risk men, tissue-based multigene tests such as Decipher, Oncotype DX (Prostate), Prolaris and ProMark, may be used. Emerging therapy predictive biomarkers include AR-V7 for predicting lack of response to specific anti-androgens (enzalutamide, abiraterone), BRAC1/2 mutations for predicting benefit from PARP inhibitor and PORTOS for predicting benefit from radiotherapy. With the increased availability of multiple biomarkers, personalised treatment for men with prostate cancer is finally on the horizon.

Prospective Validation of Pentraxin-3 as a Novel Serum Biomarker to Predict the Risk of Prostate Cancer in Patients Scheduled for Prostate Biopsy

PURPOSE

To test and internally validate serum Pentraxin-3 (PTX3) levels as a potential PCa biomarker to predict prostate biopsy (PBx) results.

MATERIALS AND METHODS

Serum PSA and serum PTX3 were prospectively assessed in patients scheduled for PBx at our Institution due to increased serum PSA levels or abnormal digital rectal examination. Uni- and multivariable logistic regression analysis, area under the receiver operating characteristic curve (AUC), and decision curve analysis (DCA), were used to test the accuracy of serum PTX3 in predicting anyPCa and clinically significant PCa (csPCa) defined as Gleason Grade (GG) ≥ 2.

RESULTS

Among the 455 eligible patients, PCa was detected in 49% and csPCa in 25%. During univariate analysis, PTX3 outperformed other variables in predicting both anyPCa and csPCa. The addition of PTX3 to multivariable models based on standard clinical variables, significantly increased each model's predictive accuracy for anyPCa (AUC from 0.73 to 0.82; p < 0.001) and csPCa (AUC from 0.79 to 0.83; p < 0.001). At DCA, PTX3, and PTX3, density showed higher net benefit than PSA and PSA density and increased the net benefit of multivariable models in deciding when to perform PBx.

CONCLUSIONS

Serum PTX3 levels might be of clinical utility in predicting prostate biopsy results. Should our findings be confirmed, this novel reflex test could be used to reduce the number and burden of unnecessary prostate biopsies.

4Kscore diagnostic value in patients with high-grade prostate cancer using cutoff values of 7.5% to 10%: A meta-analysis

BACKGROUND

Reported 4Kscore thresholds used to differentiate between patients with and without high-grade prostate cancer (CaP) were variable. Patients with 4Kscore results <7.5% have been proven to be at low risk of carrying high-grade CaP. This study employed a meta-analysis approach in order to assess the diagnostic accuracy of the 4Kscore as a means of detecting high-grade CaP in prostate biopsy samples using cutoff values of 7.5% to 10%.

METHODS

Relevant studies published as of December 2019 were identified via searching PubMed, Embase, and Cochrane Library. Data pertaining to 4Kscore diagnostic accuracy were then extracted from these studies and utilized for the calculation of pooled sensitivity , specificity , diagnostic odds ratio , and area under the curve values relating to high-grade CaP diagnosis.

RESULTS

In total, 9 studies incorporating 1,689 high-grade CaP patients were included in our meta-analysis. Following the exclusion of 1 outlier study, the pooled sensitivity, specificity , diagnostic odds ratio , and area under the curve values for 4Kscore diagnostic accuracy with corresponding 95% confidence intervals (CIs) were 0.90 (95%CI: 0.86-0.92), 0.44 (95%CI: 0.36-0.52), 7 (95%CI: 5-8), and 0.81 (95%CI: 0.77-0.84), respectively.

CONCLUSION

These findings indicate that 4Kscore can be used as a model for the diagnosis of high-grade CaP. However, we detected significant heterogeneity among studies that was not explained by subgroup or meta-regression analysis, thus lowering our confidence in these results. It is therefore essential that future large, well-designed studies be conducted so as to confirm whether the 4Kscore can be used with cutoff values of 7.5% to 10% to reliably detect high-grade CaP.

Clinical utility of current biomarkers for prostate cancer detection

Although prostate-specific antigen (PSA) remains the most used test to detect prostate cancer (PCa), the limited specificity and an elevated rate of overdiagnosis are the main problems associated with PSA testing. Over the last three decades, a large body of evidence has indicated that PSA screening methods for PCa are problematic, although PSA screening significantly reduces PCa-specific mortality. A number of novel biomarkers have been introduced to overcome these limitations of PSA in the clinical setting. These biomarkers have demonstrated an increased ability to select patients for biopsy and identify men at risk for clinically significant PCa. Although a number of assays require further validation, initial data are promising. Forthcoming results will ultimately determine the clinical utility and commercial availability of these assays. Extensive efforts have recently been made to identify and commercialize novel PCa biomarkers for more effective detection of PCa, either alone or in combination with currently available clinical tools. This review highlights the role of existing and promising serum and urinary biomarkers for the detection and prognostication of PCa before prostate biopsy.

A review of current clinical biomarkers for prostate cancer: towards personalised and targeted therapy

Background:

Prostate cancer is the most commonly diagnosed cancer in men and it is responsible for about 10% of all cancer mortality in Canadian men. The current ‘gold standard’ for the diagnosis of prostate cancer is a prostate biopsy and the decision on when to biopsy a patient with non-suspicious Digital Rectal Examination (DRE) result and total prostate specific antigen (tPSA) of 4–10 ng/ml can be challenging. In order to shift the treatment paradigm of prostate cancer toward more personalised and targeted therapy, there is the need for a clear system that makes its detection binary so as to decrease the rate of inaccurate detections. Therefore in recent years, there have been several investigations into the development of various biomarkers with high sensitivity and specificity for screening, early detection and personalised patient-specific targeted medicine from diagnosis to treatment of the disease.

Materials and methods:

This paper reports on nine currently available clinical biomarkers used in screening for early detection and diagnosis, to reduce the number of unnecessary biopsies, in risk assessment of aggressive disease and in monitoring treatment response of prostate cancer.

Conclusion:

Current clinical prostate cancer biomarkers have the potential for a personalised risk assessment of aggressive disease and the risk of developing distant metastatic disease and have been proven to be useful tools to guide clinicians in personalised patient-specific targeted treatment and in the shared decision making between patients and their physicians regarding prostate biopsy and treatment. Using biomarkers to select patients with a significant probability of aggressive prostate cancer would potentially avoid premature death from the disease, while at the same time would safely preclude patients who do not require unnecessary invasive intervention.

Genetic testing for the clinician in prostate cancer

INTRODUCTION

Prostate cancer (PCa) is one of the most common cancers worldwide and a leading cause of cancer-related mortality. Although the diagnosis and treatment of prostate cancer has improved substantially in recent years, new molecular biomarkers are needed to further prolong survival and improve the quality of life in these patients.

AREAS COVERED

This review analyzes the current evidence for prognostic and predictive molecular biomarkers that can be applied across different clinical scenarios, ranging from localized disease to metastatic castration-resistant PCa, with a particular emphasis on the biomarkers likely to become available in routine clinical practice in the near future.

EXPERT OPINION

There is a growing need for molecular testing to identify the most indolent types of prostate cancer to help optimize treatment strategies and spare treatment in these patients when possible. Current trends in the treatment of prostate cancer underscore the unmet clinical need for biomarkers to improve decision-making in a challenging clinical setting.

Circular RNA and its potential as prostate cancer biomarkers

Advancing knowledge of the transcriptome has revealed that circular RNAs (circRNAs) are widely expressed and evolutionarily conserved molecules that may serve relevant biological roles. More interesting is the accumulating evidence which demonstrates the implication of circRNAs in diseases, especially cancers. This revelation has helped to form the rationale for many studies exploring their utility as clinical biomarkers. CircRNAs are highly stable due to their unique structures, exhibit some tissue specificity, and are enriched in exosomes, which facilitate their detection in a range of body fluids. These properties make circRNAs ideal candidates for biomarker development in many diseases. This review will outline the discovery, biogenesis, and proposed functions of circRNAs.

Added value of systematic biopsy in men with a clinical suspicion of prostate cancer undergoing biparametric MRI-targeted biopsy: multi-institutional external validation study

Purpose

We aimed to develop and externally validate a nomogram based on MRI volumetric parameters and clinical information for deciding when SBx should be performed in addition to TBx in man with suspicious prostate MRI.

Materials and methods

Retrospective analyses of single (IMPROD, NCT01864135) and multi-institution (MULTI-IMPROD, NCT02241122) clinical trials. All men underwent a unique rapid biparametric magnetic resonance imaging (IMPROD bpMRI) consisting of T2-weighted imaging and three separate DWI acquisitions. Men with IMPROD bpMRI Likert scores of 3–5 were included. Logistic regression models were developed using IMPROD trial (n = 122) and validated using MULTI-IMPROD trial (n = 262) data. The model’s performance was evaluated in the terms of PCa detection with Gleason Grade Group 1 (clinically insignificant prostate cancer, iPCa) and > 1 (clinically significant prostate cancer, csPCa). Net benefits and decision curve analyses (DCA) were compared. Combined biopsies were used for reference.

Results

The developed nomogram included age, PSA, prostate volume, MRI suspicion score (IMPROD bpMRI Likert or PIRADsv2.1 score), MRI-suspicion lesion volume percentage, and lesion location. All these variables were significant predictors of csPCa in SBx in multivariable analysis. In the validation cohort (n = 262) using different nomogram cutoffs, 19–43% of men would have avoided SBx while missing 1–4% of csPCa and avoiding detection of 9–20% of iPCa. Similar performance was found for nomograms using IMPROD bpMRI Likert score or v2.1.

Conclusions

The developed nomogram demonstrated potential to select men with a clinical suspicion of PCa who would benefit from performing SBx in addition to TBx. Public access to the nomogram is provided at:https://petiv.utu.fi/multiimprod/.

Electronic supplementary material

The online version of this article (10.1007/s00345-020-03393-8) contains supplementary material, which is available to authorized users.

The Movember Prostate Cancer Landscape Analysis: an assessment of unmet research needs

Prostate cancer is a heterogeneous cancer with widely varying levels of morbidity and mortality. Approaches to prostate cancer screening, diagnosis, surveillance, treatment and management differ around the world. To identify the highest priority research needs across the prostate cancer biomedical research domain, Movember conducted a landscape analysis with the aim of maximizing the effect of future research investment through global collaborative efforts and partnerships. A global Landscape Analysis Committee (LAC) was established to act as an independent group of experts across urology, medical oncology, radiation oncology, radiology, pathology, translational research, health economics and patient advocacy. Men with prostate cancer and thought leaders from a variety of disciplines provided a range of key insights through a range of interviews. Insights were prioritized against predetermined criteria to understand the areas of greatest unmet need. From these efforts, 17 research needs in prostate cancer were agreed on and prioritized, and 3 received the maximum prioritization score by the LAC: first, to establish more sensitive and specific tests to improve disease screening and diagnosis; second, to develop indicators to better stratify low-risk prostate cancer for determining which men should go on active surveillance; and third, to integrate companion diagnostics into randomized clinical trials to enable prediction of treatment response. On the basis of the findings from the landscape analysis, Movember will now have an increased focus on addressing the specific research needs that have been identified, with particular investment in research efforts that reduce disease progression and lead to improved therapies for advanced prostate cancer.

The Movember global Landscape Analysis Committee (LAC) was established to act as an independent group of experts across urology, medical oncology, radiation oncology, radiology, pathology, translational research, health economics and patient advocacy to identify the highest priority research needs across the prostate cancer biomedical research domain. Findings from the landscape analysis illustrate the research priorities in prostate cancer and will enable Movember to focus on specific needs, with particular investment in research to reduce disease progression and improve therapies for advanced prostate cancer.

Identification of genetic biomarkers in urine for early detection of prostate cancer

Prostate cancer screening is a challenging and vital issue in the aspects of the current tests and risk assessments. Prostate cancer risk assessments are currently carried out by using blood, urine and tissue biomarkers with radiological imaging methods. Here, we introduce a novel noninvasive screening tool for a further in-depth selection of eligible cases for prostate biopsies which is based on sequencing somatic and hereditary HOXB13 mutations in urine samples. This approach provides diagnostic information to the physician about the presence of prostate cancer while aiming to screen for specific prostate biopsies and save biopsies potentially when there are no mutations related to prostate cancer. Findings suggest that this method is reliable, cost-effective, and has a promising potential in prostate cancer screening.

1H NMR-Based Urine Metabolomics Reveals Signs of Enhanced Carbon and Nitrogen Recycling in Prostate Cancer

Prostate cancer is the second most common tumor and the fifth cause of cancer-related death among men worldwide. PC cells exhibit profound signaling and metabolic reprogramming that account for the acquisition of aggressive features. Although the metabolic understanding of this disease has increased in recent years, the analysis of such alterations through noninvasive methodologies in biofluids remains limited. Here, we used NMR-based metabolomics on a large cohort of urine samples (more than 650) from PC and benign prostate hyperplasia (BPH) patients to investigate the molecular basis of this disease. Multivariate analysis failed to distinguish between the two classes, highlighting the modest impact of prostate alterations on urine composition and the multifactorial nature of PC. However, univariate analysis of urine metabolites unveiled significant changes, discriminating PC from BPH. Metabolites with altered abundance in urine from PC patients revealed changes in pathways related to cancer biology, including glycolysis and the urea cycle. We found out that metabolites from such pathways were diminished in the urine from PC individuals, strongly supporting the notion that PC reduces nitrogen and carbon waste in order to maximize their usage in anabolic processes that support cancer cell growth.

A Gleason score-related outcome model for human prostate cancer: a comprehensive study based on weighted gene co-expression network analysis

BACKGROUND

Prostate cancer (PCa) is the second leading cause of cancer death in men in 2018. Thus, the evaluation of prognosis is crucial for clinical treatment decision of human PCa patients. We aim to establishing an effective and reliable model to predict the outcome of PCa patients.

METHODS

We first identified differentially expressed genes between prostate cancer and normal prostate in TCGA-PRAD and then performed WGCNA to initially identify the candidate Gleason score related genes. Then, the candidate genes were applied to construct a LASSO Cox regression analysis model. Numerous independent validation cohorts, time-dependent receiver operating characteristic (ROC), univariate cox regression analysis, nomogram were used to test the effectiveness, accuracy and clinical utility of the prognostic model. Furthermore, functional analysis and immune cells infiltration were performed.

RESULTS

Gleason score-related differentially expressed candidates were identified and used to build up the outcome model in TCGA-PRAD cohort and was validated in MSKCC cohort. We found the 3-gene outcome model (CDC45, ESPL1 and RAD54L) had good performance in predicting recurrence free survival, metastasis free survival and overall survival of PCa patients. Time-dependent ROC and nomogram indicated an ideal predictive accuracy and clinical utility of the outcome model. Moreover, outcome model was enriched in 28 pathways by GSVA and GSEA. In addition, the risk score was positively correlated with memory B cells, native CD4 T cells, activated CD4 memory T cells and eosinophil, and negatively correlated with plasma cells, resting CD4 memory T cells, resting mast cells and neutrophil.

CONCLUSIONS

In summary, our outcome model proves to be an effective prognostic model for predicting the risk of prognosis in PCa.

The Four-Kallikrein Panel Is Effective in Identifying Aggressive Prostate Cancer in a Multiethnic Population

BACKGROUND

The four-kallikrein (4K) panel has been demonstrated to improve prediction of aggressive prostate cancer compared with prostate-specific antigen (PSA) among men with moderately elevated PSA levels. However, the development and testing of the 4K panel has been conducted primarily in White men, with limited data in African Americans and no studies in other racial and ethnic groups.

METHODS

We evaluated the 4K panel in a nested case-control study among African American, Latino, Japanese, Native Hawaiian, and White men in the Multiethnic Cohort. Prediagnostic blood levels of free, intact, and total PSA and human kallikrein-related peptidase 2 were measured among 1,667 incident prostate cancer cases and 691 controls with PSA ≥2 ng/mL. We evaluated the discriminative ability of the 4K panel within and across all racial/ethnic groups.

RESULTS

The 4K panel enhanced discrimination of overall prostate cancer compared with free plus total PSA and total PSA alone (AUC 0.748 vs. 0.711 and 0.669, respectively). Discrimination was further enhanced for Gleason 8+ prostate cancer, aggressive prostate cancer, and death due to prostate cancer, and to a lesser degree for nonaggressive prostate cancer. Improvement of the 4K panel over PSA was observed in each population. Adding a prostate cancer polygenic risk score slightly improved upon the discriminative ability of the 4K panel.

CONCLUSIONS

The superior discriminative ability of the 4K panel over PSA for overall and aggressive prostate cancer across multiethnic populations indicates the broad clinical applicability of the 4K panel.

IMPACT

Our multiethnic investigation suggests potential for the 4K panel to improve current prostate cancer screening practices.

microRNAs identified in prostate cancer: Correlative studies on response to ionizing radiation

As the most frequently diagnosed non-skin cancer in men and a leading cause of cancer-related death, understanding the molecular mechanisms that drive treatment resistance in prostate cancer poses a significant clinical need. Radiotherapy is one of the most widely used treatments for prostate cancer, along with surgery, hormone therapy, and chemotherapy. However, inherent radioresistance of tumor cells can reduce local control and ultimately lead to poor patient outcomes, such as recurrence, metastasis and death. The underlying mechanisms of radioresistance have not been fully elucidated, but it has been suggested that miRNAs play a critical role. miRNAs are small non-coding RNAs that regulate gene expression in every signaling pathway of the cell, with one miRNA often having multiple targets. By fine-tuning gene expression, miRNAs are important players in modulating DNA damage response, cell death, tumor aggression and the tumor microenvironment, and can ultimately affect a tumor's response to radiotherapy. Furthermore, much interest has focused on miRNAs found in biofluids and their potential utility in various clinical applications. In this review, we summarize the current knowledge on miRNA deregulation after irradiation and the associated functional outcomes, with a focus on prostate cancer. In addition, we discuss the utility of circulating miRNAs as non-invasive biomarkers to diagnose, predict response to treatment, and prognosticate patient outcomes.

A predictive model for prostate cancer incorporating PSA molecular forms and age

The diagnostic specificity of prostate specific antigen (PSA) is limited. We aimed to characterize eight anti-PSA monoclonal antibodies (mAbs) to assess the prostate cancer (PCa) diagnostic utility of different PSA molecular forms, total (t) and free (f) PSA and PSA complexed to α₁-antichymotrypsin (complexed PSA). MAbs were obtained by immunization with PSA and characterized by competition studies, ELISAs and immunoblotting. With them, we developed sensitive and specific ELISAs for these PSA molecular forms and measured them in 301 PCa patients and 764 patients with benign prostate hyperplasia, and analyzed their effectiveness to discriminate both groups using ROC curves. The free-to-total (FPR) and the complexed-to-total PSA (CPR) ratios significantly increased the diagnostic yield of tPSA. Moreover, based on model selection, we constructed a multivariable logistic regression model to predictive PCa that includes tPSA, fPSA, and age as predictors, which reached an optimism-corrected area under the ROC curve (AUC) of 0.86. Our model outperforms the predictive ability of tPSA (AUC 0.71), used in clinical practice. In conclusion, The FPR and CPR showed better diagnostic yield than tPSA. In addition, the PCa predictive model including age, fPSA and complexed PSA, outperformed tPSA detection efficacy. Our model may avoid unnecessary biopsies, preventing harmful side effects and reducing health expenses.

Merging new-age biomarkers and nanodiagnostics for precision prostate cancer management

The accurate identification and stratified treatment of clinically significant early-stage prostate cancer have been ongoing concerns since the outcomes of large international prostate cancer screening trials were reported. The controversy surrounding clinical and cost benefits of prostate cancer screening has highlighted the lack of strategies for discriminating high-risk disease (that requires early treatment) from low-risk disease (that could be managed using watchful waiting or active surveillance). Advances in molecular subtyping and multiomics nanotechnology-based prostate cancer risk delineation can enable refinement of prostate cancer molecular taxonomy into clinically meaningful and treatable subtypes. Furthermore, the presence of intertumoural and intratumoural heterogeneity in prostate cancer warrants the development of novel nanodiagnostic technologies to identify clinically significant prostate cancer in a rapid, cost-effective and accurate manner. Circulating and urinary next-generation prostate cancer biomarkers for disease molecular subtyping and the newest complementary nanodiagnostic platforms for enhanced biomarker detection are promising tools for precision prostate cancer management. However, challenges in merging both aspects and clinical translation still need to be overcome.

Practical Molecular Testing in a Clinical Genitourinary Service

CONTEXT.—

Molecular testing is increasingly playing a key role in the diagnosis, prognosis, and treatment of neoplasms of the genitourinary system.

OBJECTIVE.—

To provide a general overview of the clinically relevant molecular tests available for neoplasms of the genitourinary tract.

DATA SOURCES.—

Relevant medical literature indexed on PubMed.

CONCLUSIONS.—

Understanding of the molecular oncology of genitourinary neoplasms is rapidly advancing, and the pathologist must be aware of the practical implications of molecular testing. While many genomic abnormalities are not yet clinically relevant, there is an increasing library of ancillary tests that may guide diagnosis, prognosis, and/or treatment of many neoplasms. Recurrent genomic abnormalities have been identified in many types of renal cell carcinoma, and some types of renal cell carcinoma are specifically defined by the molecular abnormality. Two major routes of developing urothelial carcinoma have been molecularly described. Recurrent translocations involving ETS family genes are found in approximately half of prostate cancer cases. Testicular germ cell tumors typically harbor i(12p). Penile neoplasms are often high-risk human papillomavirus-driven cancers. Nonetheless, even as genitourinary neoplasms are increasingly better understood at the molecular level, further research with eventual clinical validation is needed for optimal diagnosis, prognosis, and treatment of aggressive malignancies in the genitourinary tract.

Novel Diagnostic Biomarkers of Prostate Cancer: An Update

OBJECTIVE

In recent years, several biomarkers alternative to standard prostate specific antigen (PSA) for prostate cancer (PCa) diagnosis have become available. The aim of this systematic review is to assess the current knowledge about alternative serum and urinary biomarkers for the diagnosis of PCa.

MATERIAL AND METHODS

A research was conducted in Medline, restricted to English language articles published between December 2014 and June 2018 with the aim to update previously published series on PCa biomarkers. The preferred reporting items for systematic reviews and meta-analyses (PRISMA) criteria were used for selecting studies with the lowest risk of bias.

RESULTS

Emerging role and actual controversies on serum and urine alternative biomarkers to standard PSA for PCa diagnosis, staging and prognosis assessment, such as prostate health index (PHI), PCA3, ConfirmMDx, Aberrant PSA glycosylation, MiPS, miRNAs are critically presented in the current review.

CONCLUSION

Although the use of several biomarkers has been recommended or questioned by different international guidelines, larger prospective randomized studies are still necessary to validate their efficacy in PCa detection, discrimination, prognosis and treatment effectiveness. To date, only PHI and 4Kscore have shown clinical relevance for discriminating more aggressive PCa. Furthermore, a new grading classification based on molecular features relevant for PCa risk-stratification and tailoring treatment is still needed.

Assessment of men's risk thresholds to proceed with prostate biopsy for the early detection of prostate cancer

PURPOSE

To delineate the range of "risk thresholds" for prostate biopsy to determine how improved prostate cancer (CaP) risk prediction tools may impact shared decision-making (SDM).

METHODS

We conducted a cross-sectional survey study involving men 45-75 years old attending a multispecialty urology clinic. Data included demographics, personal and family prostate cancer history, and prostate biopsy history. Respondents were presented with a summary of the details, risks, and benefits of prostate biopsy, then asked to indicate the specific risk threshold (% chance) of high-grade CaP at which they would proceed with prostate biopsy.

RESULTS

Of a total of 103 respondents, 18 men (17%) had a personal history of CaP, and 31 (30%) had undergone prostate biopsy. The median risk threshold to proceed with prostate biopsy was 25% (interquartile range 10-50%). Risk thresholds did not vary by race, education, or employment. Personal history of CaP or prostate biopsy was significantly associated with lower mean risk thresholds (19% vs. 32% [P = 0.02] and 23% vs. 33% [P = 0.04], respectively). In the lowest versus highest risk threshold quartiles, there were significantly higher rates of CaP (36% vs. 1%, P = 0.01) and prior prostate biopsy (46% vs. 17%, P < 0.01).

CONCLUSIONS

Men have a wide range of risk thresholds for high-grade CaP to proceed with prostate biopsy. Men with a prior history of CaP or biopsy reported lower risk thresholds, which may reflect their greater concern for this disease. The extent to which refined risk prediction tools will improve SDM warrants further study.