A multicenter study of [-2]pro-prostate specific antigen combined with prostate specific antigen and free prostate specific antigen for prostate cancer detection in the 2.0 to 10.0 ng/ml prostate specific antigen range

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.

Prostate cancer biomarkers: from early diagnosis to precision treatment

Prostate cancer (PCa) is the second most prevalent cancer in men. In 2020, approximately 1,414,259 new cases were reported that accounted for 3,75,324 deaths (Sung et al. in CA 71:209-249, 2021). PCa is often asymptomatic at early stages; hence, routine screening and monitoring based on reliable biomarkers is crucial for early detection and assessment of cancer progression. Early diagnosis of disease is key step in reducing PCa-induced mortality. Biomarkers such as PSA have played vital role in reducing recent PCa deaths. Recent research has identified many other biomarkers and also refined PSA-based tests for non-invasive diagnosis of PCa in patients. Despite progress in screening methods, an important issue that influences treatment is heterogeneity of the cancer in different individuals, necessitating personalized treatment. Currently, focus is to identify biomarkers that can accurately diagnose PCa at early stage, indicate the stage of the disease, metastatic nature and chances of survival based on individual patient profile (Fig. 1). Fig. 1 Graphical abstract.

A west African ancestry-associated SNP on 8q24 predicts a positive biopsy in African American men with suspected prostate cancer following PSA screening

BACKGROUND

African American (AA) men have the highest incidence and mortality rates of prostate cancer (PCa) among all racial groups in the United States. While race is a social construct, for AA men, this overlaps with west African ancestry. Many of the PCa susceptibility variants exhibit distinct allele frequencies and risk estimates across different races and contribute substantially to the large disparities of PCa incidence among races. We previously reported that a single-nucleotide polymorphism (SNP) in 8q24, rs7824364, was strongly associated with west African ancestry and increased risks of PCa in both AA and Puerto Rican men. In this study, we determined whether this SNP can predict biopsy positivity and detection of clinically significant disease (Gleason score [GS] ≥ 7) in a cohort of AA men with suspected PCa.

METHODS

SNP rs7824364 was genotyped in 199 AA men with elevated total prostate-specific antigen (PSA) (>2.5 ng/mL) or abnormal digital rectal exam (DRE) and the associations of different genotypes with biopsy positivity and clinically significant disease were analyzed.

RESULTS

The variant allele carriers were significantly over-represented in the biopsy-positive group compared to the biopsy-negative group (44% vs. 25.7%, p = 0.011). In the multivariate logistic regression analyses, variant allele carriers were at a more than a twofold increased risk of a positive biopsy (odds ratio [OR] = 2.14, 95% confidence interval [CI] = 1.06-4.32). Moreover, the variant allele was a predictor (OR = 2.26, 95% CI = 1.06-4.84) of a positive biopsy in the subgroup of patients with PSA < 10 ng/mL and normal DRE. The variant allele carriers were also more prevalent in cases with GS ≥ 7 compared to cases with GS < 7 and benign biopsy.

CONCLUSIONS

This study demonstrated that the west African ancestry-specific SNP rs7824364 on 8q24 independently predicted a positive prostate biopsy in AA men who were candidates for prostate biopsy subsequent to PCa screening.

Blood-Based DNA Methylation Analysis by Multiplexed OBBPA-ddPCR to Verify Indications for Prostate Biopsies in Suspected Prostate Cancer Patients

Current prostate carcinoma (PCa) biomarkers, including total prostate-specific antigen (tPSA), have unsatisfactory diagnostic sensitivity and specificity resulting in overdiagnosis and overtreatment. Previously, we described an optimised bias-based preamplification-digital droplet PCR (OBBPA-ddPCR) technique, which detects tumour DNA in blood-derived cell-free DNA (cfDNA) of cancer patients. The current study investigated the performance of newly developed OBBPA-ddPCR-based biomarkers. Blood plasma samples from healthy individuals (n = 90, controls) and PCa (n = 39) and benign prostatic hyperplasia patients (BPH, n = 40) were analysed. PCa and BPH patients had tPSA values within a diagnostic grey area of 2-15 ng/mL, for whom further diagnostic validation is most crucial. Methylation levels of biomarkers RASSF1A, MIR129-2, NRIP3, and SOX8 were found significantly increased in PCa patients compared to controls. By combining classical PCa risk factors (percentage of free PSA compared to tPSA (QfPSA) and patient's age) with cfDNA-based biomarkers, we developed PCa risk scores with improved sensitivity and specificity compared to established tPSA and QfPSA single-marker analyses. The diagnostic specificity was increased to 70% with 100% sensitivity for clinically significant PCa patients. Thus, prostate biopsies could be avoided for 28 out of 40 BPH patients. In conclusion, the newly developed risk scores may help to confirm the clinical decision and prevent unnecessary prostate biopsy.

VOC-based detection of prostate cancer using an electronic nose and ion mobility spectrometry: A novel urine-based approach

BACKGROUND

Many diseases leave behind specific metabolites which can be detected from breath and urine as volatile organic compounds (VOC). Our group previously described VOC-based methods for the detection of bladder cancer and urinary tract infections. This study investigated whether prostate cancer can be diagnosed from VOCs in urine headspace.

METHODS

For this pilot study, mid-stream urine samples were collected from 56 patients with histologically confirmed prostate cancer. A control group was formed with 53 healthy male volunteers matched for age who had recently undergone a negative screening by prostate-specific antigen (PSA) and digital rectal exam. Headspace measurements were performed with the electronic nose Cyranose 320TM . Statistical comparison was performed using principal component analysis, calculating Mahalanobis distance, and linear discriminant analysis. Further measurements were carried out with ion mobility spectrometry (IMS) to compare detection accuracy and to identify potential individual analytes. Bonferroni correction was applied for multiple testing.

RESULTS

The electronic nose yielded a sensitivity of 77% and specificity of 62%. Mahalanobis distance was 0.964, which is indicative of limited group separation. IMS identified a total of 38 individual analytical peaks, two of which showed significant differences between groups (p < 0.05). To discriminate between tumor and controls, a decision tree with nine steps was generated. This model led to a sensitivity of 98% and specificity of 100%.

CONCLUSIONS

VOC-based detection of prostate cancer seems feasible in principle. While the first results with an electronic nose show some limitations, the approach can compete with other urine-based marker systems. However, it seems less reliable than PSA testing. IMS is more accurate than the electronic nose with promising sensitivity and specificity, which warrants further research. The individual relevant metabolites identified by IMS should further be characterized using gas chromatography/mass spectrometry to facilitate potential targeted rapid testing.

Opportunistic Prostate Cancer Screening with Biparametric Magnetic Resonance Imaging (VISIONING)

BACKGROUND

This study investigates the use of biparametric magnetic resonance imaging (bpMRI) as primary opportunistic screening for prostate cancer (PCa) without using a prostate-specific antigen (PSA) cut-off.

OBJECTIVE

The primary endpoint was to assess the efforts and effectiveness of identifying 20 participants with clinically significant prostate cancer (csPCa) using bpMRI.

DESIGN, SETTING, AND PARTICIPANTS

Biopsy-naïve men aged over 45 yr were included. All participants underwent 3 Tesla bpMRI, PSA, and digital rectal examination (DRE). Targeted-only biopsy was performed in participants with Prostate Imaging Reporting and Data System (PI-RADS) ≥3. Men with negative bpMRI but suspicious DRE or elevated PSA/PSA density had template biopsies. Preintended protocol adjustments were made after an interim analysis for PI-RADS 3 lesions: no biopsy and follow-up MRI after 6 mo and biopsy only if lesions persisted or upgraded.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Biopsy results underwent a comparison using Fisher's exact test and univariable logistic regression to identify prognostic factors for positive biopsy.

RESULTS AND LIMITATIONS

A total of 229 men were enrolled in this study, of whom 79 underwent biopsy. Among these men, 77 displayed suspicious PI-RADS lesions. PCa was detected in 29 participants (12.7%), of whom 21 had csPCa (9.2%). Biparametric MRI detected 21 csPCa cases, while PSA and DRE would have missed 38.1%. Protocol adjustment led to a 54.6% biopsy reduction in PI-RADS 3 lesions. Overall, in this cohort of men with a median PSA value of 1.26 ng/ml, 10.9 bpMRI scans were needed to identify one participant with csPCa. A major limitation of the study is the lack of a control cohort undergoing systematic biopsies.

CONCLUSIONS

Opportunistic screening utilising bpMRI as a primary tool has higher sensitivity in detecting csPCa than classical screening methods.

PATIENT SUMMARY

Screening with biparametric magnetic resonance imaging (bpMRI) and targeted biopsy identified clinically significant prostate cancer in every 11th man, regardless of the prostate-specific antigen (PSA) levels. Preselecting patients based on PSA >1 ng/ml and a positive family history of prostate cancer, as well as other potential blood tests may further improve the effectiveness of bpMRI in this setting.

Nomogram Using Prostate Health Index for Predicting Prostate Cancer in the Gray Zone: Prospective, Multicenter Study

PURPOSE

To create a nomogram that can predict the probability of prostate cancer using prostate health index (PHI) and clinical parameters of patients. And the optimal cut-off value of PHI for prostate cancer was also assessed.

MATERIALS AND METHODS

A prospective, multi-center study was conducted. PHI was evaluated prior to biopsy in patients requiring prostate biopsy due to high prostate-specific antigen (PSA). Among screened 1,010 patients, 626 patients with clinically suspected prostate cancer with aged 40 to 85 years, and with PSA levels ranging from 2.5 to 10 ng/mL were analyzed.

RESULTS

Among 626 patients, 38.82% (243/626) and 22.52% (141/626) were diagnosed with prostate cancer and clinically significant prostate cancer, respectively. In the PSA 2.5 to 4 ng/mL group, the areas under the curve (AUCs) of the nomograms for overall prostate cancer and clinically significant prostate cancer were 0.796 (0.727-0.866; p<0.001), and 0.697 (0.598-0.795; p=0.001), respectively. In the PSA 4 to 10 ng/mL group, the AUCs of nomograms for overall prostate cancer and clinically significant prostate cancer were 0.812 (0.783-0.842; p<0.001), and 0.839 (0.810-0.869; p<0.001), respectively.

CONCLUSIONS

Even though external validations are necessary, a nomogram using PHI might improve the prediction of prostate cancer, reducing the need for prostate biopsies.

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.

Baseline prostate health index risk category and risk category changes during active surveillance predict grade reclassification

BACKGROUND

It is not known whether baseline prostate health index (PHI) at the initiation of active surveillance (AS) or repeated PHI testing during AS is of clinical value after confirmatory biopsy in AS men followed with multiparametric magnetic resonance imaging (mpMRI).

METHODS

We identified 382 AS patients with no greater than Grade Group 1 (GG1) prostate cancer on diagnostic and confirmatory biopsy, at least one mpMRI and PHI test, of which 241 had at least 2 PHI tests. Grade reclassification (GR) was defined as ≥GG2 on surveillance biopsy. PHI risk categories 1 to 4 were as defined by the manufacturer. Associations between baseline PHI risk category or baseline PSA density (PSAD), change in PHI risk categories over time or PSAD changes over time and GR were evaluated with multivariable Cox proportional hazard regression models adjusted for age, Prostate Imaging-Reporting and Data System score and number of positive cores.

RESULTS

Men with baseline PHI scores in the highest risk categories had lower rates of GR-free survival (log-rank P < 0.001), as did those who increased in PHI risk category or remained in a high PHI risk category during surveillance (log-rank P = 0.032). On multivariable regression, baseline PHI risk category was a predictor of GR (risk category 4 [vs. 1] hazard ratio [HR] 2.74, 95% confidence interval [CI] 1.32-5.66, P = 0.002, model C-index 0.764, Akaike Information Criterion [AIC] 797), as were PHI risk category changes over time (risk category 4 [vs. 1] HR 4.20, 95% CI 1.76-10.05, P = 0.002, C-index 0.759, AIC 489). Separate models with baseline PSAD and PSAD changes over time yielded C-indices of 0.709 (AIC 809) and 0.733 (AIC 495) respectively.

CONCLUSIONS

Baseline PHI risk category and PHI changes over time were both independent predictors of GR after confirmatory biopsy, but the added benefit over PSAD seemed modest. However, baseline PHI and PHI risk category changes provided clinically useful risk stratification for time to GR, so further evaluation of PHI's ability to help reduce the frequency of mpMRI and/or surveillance biopsies with more PHI data points over time may be warranted.

The utility of the [-2]pro-prostate-specific antigen level as a prognostic marker in patients with castration-resistant prostate cancer treated with enzalutamide

BACKGROUND

The prostate health index (phi) derived using [-2]pro-prostate-specific antigen (p2PSA), a precursor of PSA, has been shown to predict cancer in the gray zone. However, the utility of p2PSA in predicting outcomes for castration-resistant prostate cancer (CRPC) patients remains unknown. Therefore, in this study, we aimed to evaluate the usefulness of p2PSA in predicting the efficacy and prognosis of enzalutamide treatment in CRPC patients.

METHODS

We conducted a prospective study of CRPC patients treated with enzalutamide at our institution, measuring p2PSA levels in 98 pre-treatment serum samples. All patients were divided into two groups based on the median values of each parameter. The PSA progression-free survival (PSA-PFS) and overall survival (OS) were compared using the Kaplan-Meier method. This study was approved by the Institutional Review Board of Gunma University Hospital (IRB No. 2021-092, 1983).

RESULTS

The median PSA level before enzalutamide treatment was 25.59 ng/mL, the median p2PSA level was 208.75 pg/mL, and the median phi was 187.95. PSA, p2PSA, and phi were not all predictors of PSA-PFS. However, the OS was significantly better in the low-value groups (log-rank p-values of PSA, p2PSA, and phi were 0.024, 0.034, and 0.018, respectively). In the docetaxel (DOC)-naive group (n = 58), PSA was not a predictor of OS, but p2PSA and phi were significantly associated with better OS in the low group. This relationship was not observed in the DOC-treated group.

CONCLUSIONS

Our study elucidates the usefulness of p2PSA in predicting outcomes for CRPC patients treated with enzalutamide. It suggests that p2PSA and phi may be prognostic markers after enzalutamide administration in CRPC patients.

Free PSA and Clinically Significant and Fatal Prostate Cancer in the PLCO Screening Trial

PURPOSE

We studied whether adding percent free PSA to total PSA improves prediction of clinically significant prostate cancer and fatal prostate cancer.

MATERIALS AND METHODS

A total of 6,727 men within the intervention arm of PLCO (Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial) had baseline percent free PSA. Of this cohort, 475 had clinically significant prostate cancer and 98 had fatal prostate cancer. Cumulative incidence and Cox analyses were conducted to evaluate the association between percent free PSA/PSA and clinically significant prostate cancer/fatal prostate cancer. Harrell's C index evaluated predictive ability. Kaplan-Meier analysis assessed survival.

RESULTS

Median follow-up was 19.7 years, median baseline PSA was 1.19 ng/mL, median percent free PSA was 18%. Cumulative incidence of fatal prostate cancer for men with baseline PSA ≥2 ng/mL and percent free PSA ≤10 was 3.2% and 6.1% at 15 and 25 years, respectively, compared to 0.03% and 1.1% for men with percent free PSA >25%. In younger men (55-64 years) with baseline PSA 2-10 ng/mL, C index improved from 0.56 to 0.60 for clinically significant prostate cancer and from 0.53 to 0.64 for fatal prostate cancer with addition of percent free PSA. In older men (65-74 years), C index improved for clinically significant prostate cancer from 0.60 to 0.66, with no improvement in fatal prostate cancer. Adjusting for age, digital rectal exam, family history of prostate cancer, and total PSA, percent free PSA was associated with clinically significant prostate cancer (HR 1.05, P < .001) per 1% decrease. Percent free PSA improved prediction of clinically significant prostate cancer and fatal prostate cancer for all race groups.

CONCLUSIONS

In a large U.S. screening trial, the addition of percent free PSA to total PSA in men with baseline PSA ≥2 ng/mL improved prediction of clinically significant prostate cancer and fatal prostate cancer. Free PSA should be used to risk-stratify screening and decrease unnecessary prostate biopsies.

Age-specific percentile-based prostate-specific antigen cutoff values predict the risk of prostate cancer: A single hospital observation

Background

Testing for prostate-specific antigen (PSA) is often recommended for men with a potential risk of prostate cancer (PCa) before requiring advanced examination. However, the best PSA cutoff value remains controversial.

Object

We compared the predictive performance of age-specific percentile-based PSA thresholds with a conventional cutoff of >4 ng/mL for the risk of PCa.

Methods

We included men who received PSA measurements between 2003 and 2017 in a medical center in Taiwan. Logistic regression modeling was used to assess the association between age-specific percentile-based PSA thresholds and PCa risk in age subgroups. We further applied C-statistic and decision curve analysis to compare the predictive performance of age-specific percentile-based PSA with that of a conventional cutoff PSA.

Results

We identified 626 patients with PCa and 40 836 patients without PCa. The slope of PSA in patients >60-year-old was almost 3 times that of those <60-year-old (0.713 vs 0.259). The risk effect sizes of the 75th percentile PSA cutoff (<60-year-old: 2.19; 60-70-year-old: 4.36; >70-year-old: 5.84 ng/mL) were comparable to those observed based on the conventional cutoff in all age groups. However, the discrimination performance of the 75th percentile PSA cutoff was better than that of the conventional cutoff among patients aged <60-year-old (C-statistic, 0.783 vs. 0.729, p < 0.05). The 75th percentile cutoffs also correctly identified an additional 2 patients with PCa for every 100 patients with PSA screening at the threshold probability of 20%.

Conclusions

Our data support the use of the 75th percentile PSA cutoff to facilitate individualized risk assessment, particularly for patients aged <60-year-old.

Prostate health index can stratify patients with Prostate Imaging Reporting and Data System score 3 lesions on magnetic resonance imaging to reduce prostate biopsies

We aim to evaluate prostate health index as an additional risk-stratification tool in patients with Prostate Imaging Reporting and Data System score 3 lesions on multiparametric magnetic resonance imaging. Men with biochemical or clinical suspicion of having prostate cancer who underwent multiparametric magnetic resonance imaging in two tertiary centers (Queen Mary Hospital and Princess Margaret Hospital, Hong Kong, China) between January 2017 and June 2022 were included. Ultrasound-magnetic resonance imaging fusion biopsies were performed after prostate health index testing. Those who only had Prostate Imaging Reporting and Data System score 3 lesions were further stratified into four prostate health index risk groups and the cancer detection rates were analyzed. Out of the 747 patients, 47.3% had Prostate Imaging Reporting and Data System score 3 lesions only. The detection rate of clinically significant prostate cancer in this group was 15.0%. The cancer detection rates of clinically significant prostate cancer had statistically significant differences: 5.3% in prostate health index <25.0, 7.4% in prostate health index 25.0-34.9, 17.9% in prostate health index 35.0-54.9, and 52.6% in prostate health index ≥55.0 (P < 0.01). Among the patients, 26.9% could have avoided a biopsy with a prostate health index <25.0, at the expense of a 5.3% risk of missing clinically significant prostate cancer. Prostate health index could be used as an additional risk stratification tool for patients with Prostate Imaging Reporting and Data System score 3 lesions. Biopsies could be avoided in patients with low prostate health index, with a small risk of missing clinically significant prostate cancer.

Relationship between Proclarix and the Aggressiveness of Prostate Cancer

INTRODUCTION

Proclarix is a CE-marked test that provides the risk of clinically significant prostate cancer (csPCa), ranging from 0% to 100%, based on the serum measurement of Thrombospondin-1, cathepsin D, prostate-specific antigen (PSA), and percentage of free PSA in addition to age. We hypothesize that Proclarix could be correlated with PCa aggressiveness. We analyzed the association of this new biomarker with four surrogates of aggressiveness: grade group (GG) in the biopsy, clinical stage, risk of biochemical recurrence after primary treatment of localized PCa, and pathology in the surgical specimen.

MATERIAL AND METHODS

This is a retrospective study from 606 men with suspicion of PCa [PSA of ≥ 3.0 ng/mL and/or abnormal digital rectal examination (DRE)], in whom Proclarix was assessed (0-100%). The GG was defined by the International Society of Urological Pathology categories. The TNM was used for clinical staging (cT based on DRE, whereas cN and cM were established with computed tomography and 99-technetium bone scintigraphy). The risk of biochemical recurrence of localized PCa after primary treatment was defined by combining PSA, GG, and cT. Finally, an unfavorable pathology in a surgical specimen was defined as GG > 2 or pT ≥ 3.

RESULTS

The median age of the cohort was 67 years old, with a median PSA of 7 ng/mL and a rate of abnormal DRE of 23.3%. CsPCa was detected in 254 men (41.9%), with a median Proclarix of 60.1% compared with 37.3% obtained in patients with insignificant PCa and 20.7% in men without PCa. Among patients with GG > 3, Proclarix was significantly higher (58.2%) than in those with GG of 3 or lower (33.1%, p < 0.001). Men with localized tumors exhibited a Proclarix median of 37.3% compared with those with advanced disease (60.1%, p < 0.001). Proclarix levels among 197 patients with low and intermediate risk of biochemical recurrence were 24.9% and 35.0%, respectively, significantly lower compared with patients with high-risk disease (58.7%, p < 0.001). Unfavorable pathology was observed in 35 patients out of the 79 who underwent radical prostatectomy, with a Proclarix median of 35.7% compared with 23.7% obtained in patients with favorable pathology (p = 0.013). Proclarix and magnetic resonance imaging were independent predictors of the four surrogates of aggressiveness analyzed.

CONCLUSION

There is a correlation between Proclarix and the aggressiveness of PCa.

A prospective study of the prostate health index density and multiparametric magnetic resonance imaging in diagnosing clinically significant prostate cancer

PURPOSE

To evaluate the predictive performance of the prostate health index (PHI) and PHI density (PHID), for clinically significant prostate cancer (csPCa) in patients with a PI-RADS score ≤3.

MATERIALS AND METHODS

Patients tested for total prostate-specific antigen (tPSA, ≤100 ng/mL), free PSA (fPSA), and p2PSA at Peking University First Hospital were prospectively enrolled. Possible predictive factors of csPCa were analyzed using the receiver operating characteristic (ROC) curve. Results were expressed as area under the curve (AUC) with 95% confidence intervals (CI). The cutoff values of PHI and PHID were determined.

RESULTS

We enrolled 222 patients in this study. The prevalence of csPCa in the PI-RADS ≤3 subgroup (n=89) was 22.47% (20/89). Age, tPSA, F/T, prostate volume, PSA density, PHI, PHID, and PI-RADS score were significantly associated with csPCa. PHID (AUC: 0.829 [95% CI: 0.717-0.941]) was the best predictor of csPCa. PHID >0.956 was set as the threshold of suspicious csPCa with a sensitivity of 85.00% and a specificity of 73.91%, avoiding 94.44% of unnecessary biopsies but missing 15.00% csPCa. A threshold of PHI ≥52.83 showed the same sensitivity but a rather lower specificity of 65.22% that avoided 93.75% of unnecessary biopsies.

CONCLUSIONS

PHI and PHID have the best predictive performance of csPCa in patients with PI-RADS score ≤3. A threshold value of PHID ≥0.956 may be used as the criterion for biopsy in these patients.

Management of Advanced Prostate Cancer in the Precision Oncology Era

Prostate cancer (PC) is the second leading cause of cancer death in men in the United States. While diversified and improved treatment options for aggressive PC have improved patient outcomes, metastatic castration-resistant prostate cancer (mCRPC) remains incurable and an area of investigative therapeutic interest. This review will cover the seminal clinical data supporting the indication of new precision oncology-based therapeutics and explore their limitations, present utility, and potential in the treatment of PC. Systemic therapies for high-risk and advanced PC have experienced significant development over the past ten years. Biomarker-driven therapies have brought the field closer to the goal of being able to implement precision oncology therapy for every patient. The tumor agnostic approval of pembrolizumab (a PD-1 inhibitor) marked an important advancement in this direction. There are also several PARP inhibitors indicated for patients with DNA damage repair deficiencies. Additionally, theranostic agents for both imaging and treatment have further revolutionized the treatment landscape for PC and represent another advancement in precision medicine. Radiolabeled prostate-specific membrane antigen (PSMA) PET/CT is rapidly becoming a standard of care for diagnosis, and PSMA-targeted radioligand therapies have gained recent FDA approval for metastatic prostate cancer. These advances in precision-based oncology are detailed in this review.

Prediction of Overall Survival by Thymidine Kinase 1 Combined with Prostate-Specific Antigen in Men with Prostate Cancer

Thymidine kinase 1 (TK1) is an intracellular enzyme involved in DNA-precursor synthesis. Increased serum TK1 levels are used as a biomarker in various malignancies. We combined serum TK1 with PSA and evaluated its capacity to predict overall survival (OS) in 175 men with prostate cancer (PCa), detected by screening in 1988-1989 (n = 52) and during follow-up (median 22.6 years) (n = 123). TK1 was measured in frozen serum, age was stratified into four groups, and dates of PCa diagnosis and dates of death were obtained from Swedish population-based registries. The median concentration of TK1 and PSA was 0.25 and 3.8 ng/ml. TK1 was an independent variable of OS. In the multivariate analysis, PSA was not statistically significant in combination with age whereas the significance remained for TK1 + PSA. Measured once, TK1 + PSA predicted a difference of up to 10 years (depending on patient subgroup) in OS at a median of 9 years before PCa diagnosis. The TK1 concentration in 193 controls without malignancies did not differ from that of the PCa patients, hence TK1 was likely not released from incidental PCa. Thus, TK1 in the blood circulation may indicate the release of TK1 from sources other than cancers, nonetheless associated with OS.

Targeted Mass Spectrometry Assays for Specific Quantification of Urinary proPSA Isoforms

Prostate cancer (PCa) is the second leading cause of male cancer-related deaths in the United States. The pre-mature forms of prostate-specific antigen (PSA), proPSA, were shown to be associated with PCa. However, there is a technical challenge in the development of antibody-based immunoassays for specific recognition of each individual proPSA isoform. Herein, we report the development of highly specific, antibody-free, targeted mass spectrometry assays for simultaneous quantification of [-2], [-4], [-5], and [-7] proPSA isoforms in voided urine. The newly developed proPSA assays capitalize on Lys-C digestion to generate surrogate peptides with appropriate length (9-16 amino acids) along with long-gradient liquid chromatography separation. The assay utility of these isoform markers was evaluated in a cohort of 30 well-established clinical urine samples for distinguishing PCa patients from healthy controls. Under the 95% confidence interval, the combination of [-2] and [-4] proPSA isoforms yields the area under curve (AUC) of 0.86, and the AUC value for the combined all four isoforms was calculated to be 0.85. We have further verified [-2]proPSA, the dominant isoform, in an independent cohort of 34 clinical urine samples. Validation of proPSA isoforms in large-scale cohorts is needed to demonstrate their potential clinical utility.

Re-thinking How We Use Prostate Health Index for African American Men

OBJECTIVE

To assess how the validated Prostate Health Index (PHI) risk stratifications perform with African American (AA) men and establish a threshold PHI value to potentially rule out the need for prostate biopsy.

MATERIALS AND METHODS

AA men meeting FDA-specified indications for PHI testing (>50 years old, PSA 4-10 and negative DRE) who underwent subsequent biopsy were included. Rates of clinically significant prostate cancer (csPCa, as defined by Gleason score ≥7) across accepted PHI stratifications were recorded. Receiver operator curve (ROC) analysis was undertaken to assess PHI performance to predict csPCa. A phi cutoff providing 90% sensitivity was identified. Among AA men with PSA 4-10 ng/mL, the proportion of men who proceeded to biopsy upon physician recommendation was determined.

RESULTS

Two hundred nine patients met primary criteria; 91 (43.5%) of which had csPCA. The area under the curve for PHI predicting csPCa was 0.68 (95% CI: 0.61-0.75). Using a phi threshold of <23.0 to avoid biopsy provided 98.9% sensitivity, 9.3% specificity, and would have avoided 4.7% of biopsies. The proportion of those who proceeded to biopsy upon physician recommendation was 81.8%.

CONCLUSIONS

PHI demonstrated limited performance in our cohort, with current stratifications featuring misleadingly low cancer detection rates for these men. Furthermore, PHI had limited use to avoid prostate biopsy, as the proposed threshold of 23.0 only allowed 4.7% of men to avoid biopsy. Further work is needed to assess and optimize PHI usage in AA men; nonetheless, it may still have use in increasing compliance with biopsy recommendation.

The Combined Effect of Polygenic Risk Score and Prostate Health Index in Chinese Men Undergoing Prostate Biopsy

To date, the combined effect of polygenic risk score (PRS) and prostate health index (phi) on PCa diagnosis in men undergoing prostate biopsy has never been investigated. A total of 3166 patients who underwent initial prostate biopsy in three tertiary medical centers from August 2013 to March 2019 were included. PRS was calculated on the basis of the genotype of 102 reported East-Asian-specific risk variants. It was then evaluated in the univariable or multivariable logistic regression models that were internally validated using repeated 10-fold cross-validation. Discriminative performance was assessed by area under the receiver operating curve (AUC) and net reclassification improvement (NRI) index. Compared with men in the first quintile of age and family history adjusted PRS, those in the second, third, fourth, and fifth quintiles were 1.86 (odds ratio, 95% confidence interval (CI): 1.34-2.56), 2.07 (95%CI: 1.50-2.84), 3.26 (95%CI: 2.36-4.48), and 5.06 (95%CI: 3.68-6.97) times as likely to develop PCa (all p < 0.001). Adjustment for other clinical parameters yielded similar results. Among patients with prostate-specific antigen (PSA) at 2-10 ng/mL or 2-20 ng/mL, PRS still had an observable ability to differentiate PCa in the group of prostate health index (phi) at 27-36 (P_trend < 0.05) or >36 (P_trend ≤ 0.001). Notably, men with moderate phi (27-36) but highest PRS (top 20% percentile) would have a comparable risk of PCa (positive rate: 26.7% or 31.3%) than men with high phi (>36) but lowest PRS (bottom 20% percentile positive rate: 27.4% or 34.2%). The combined model of PRS, phi, and other clinical risk factors provided significantly better performance (AUC: 0.904, 95%CI: 0.887-0.921) than models without PRS. Adding PRS to clinical risk models could provide significant net benefit (NRI, from 8.6% to 27.6%), especially in those early onset patients (NRI, from 29.2% to 44.9%). PRS may provide additional predictive value over phi for PCa. The combination of PRS and phi that effectively captured both clinical and genetic PCa risk is clinically practical, even in patients with gray-zone PSA.

Biomarkers of Aggressive Prostate Cancer at Diagnosis

In the United States, prostate cancer (CaP) remains the second leading cause of cancer deaths in men. CaP is predominantly indolent at diagnosis, with a small fraction (25-30%) representing an aggressive subtype (Gleason score 7-10) that is prone to metastatic progression. This fact, coupled with the criticism surrounding the role of prostate specific antigen in prostate cancer screening, demonstrates the current need for a biomarker(s) that can identify clinically significant CaP and avoid unnecessary biopsy procedures and psychological implications of being diagnosed with low-risk prostate cancer. Although several diagnostic biomarkers are available to clinicians, very few comparative trials have been performed to assess the clinical effectiveness of these biomarkers. It is of note, however, that a majority of these clinical trials have been over-represented by men of Caucasian origin, despite the fact that African American men have a 1.7 times higher incidence and 2.1 times higher rate of mortality from prostate cancer. Biomarkers for CaP diagnosis based on the tissue of origin include urine-based gene expression assays (PCA3, Select MDx, ExoDx Prostate IntelliScore, Mi-Prostate Score, PCA3-PCGEM1 gene panel), blood-based protein biomarkers (4K, PHI), and tissue-based DNA biomarker (Confirm MDx). Another potential direction that has emerged to aid in the CaP diagnosis include multi-parametric magnetic resonance imaging (mpMRI) and bi-parametric magnetic resonance imaging (bpMRI), which in conjunction with clinically validated biomarkers may provide a better approach to predict clinically significant CaP at diagnosis. In this review, we discuss some of the adjunctive biomarker tests along with newer imaging modalities that are currently available to help clinicians decide which patients are at risk of having high-grade CaP on prostate biopsy with the emphasis on clinical utility of the tests across African American (AA) and Caucasian (CA) men.

Nomograms Combining PHI and PI-RADS in Detecting Prostate Cancer: A Multicenter Prospective Study

(1) Background: The study aimed to construct nomograms to improve the detection rates of prostate cancer (PCa) and clinically significant prostate cancer (CSPCa) in the Asian population. (2) Methods: This multicenter prospective study included a group of 293 patients from three hospitals. Univariable and multivariable logistic regression analysis was performed to identify potential risk factors and construct nomograms. Discrimination, calibration, and clinical utility were used to assess the performance of the nomogram. The web-based dynamic nomograms were subsequently built based on multivariable logistic analysis. (3) Results: A total of 293 patients were included in our study with 201 negative and 92 positive results in PCa. Four independent predictive factors (age, prostate health index (PHI), prostate volume, and prostate imaging reporting and data system score (PI-RADS)) for PCa were included, and four factors (age, PHI, PI-RADS, and Log PSA Density) for CSPCa were included. The area under the ROC curve (AUC) for PCa was 0.902 in the training cohort and 0.869 in the validation cohort. The AUC for CSPCa was 0.896 in the training cohort and 0.890 in the validation cohort. (4) Conclusions: The combined diagnosis of PHI and PI-RADS can avoid more unnecessary biopsies and improve the detection rate of PCa and CSPCa. The nomogram with the combination of age, PHI, PV, and PI-RADS could improve the detection of PCa, and the nomogram with the combination of age, PHI, PI-RADS, and Log PSAD could improve the detection of CSPCa.

An overview of prostate cancer (PCa) diagnosis: Potential role of miRNAs

Prostate cancer is the second most frequently diagnosed cancer among men worldwide, with the estimated sixth leading cause of cancer death. Despite major advancements in clinical biology and imaging, digital rectal examination (DRE), prostate-specific antigen (PSA), and biopsies indication remain the keystone for screening. Several kits are used to detect genomic changes and non-coding RNAs in the sample. However, its indication remains controversial for screening purposes. There is an urged need for non-invasive biomarkers to implement precision medicine. Recent research shows that miRNAs have an important role in the diagnostic, prognostic, and therapeutic agents as non-invasive biomarkers. Though prostate cancer data remains controversial in other cancer types, such as breast cancer, miR-21 expression is upregulated. Here, we reported a prolonged revision of miRNAs as prostate cancer prognostic, diagnostic, and predictive tools, including data on androgen receptor (AR) signaling, epithelial-mesenchymal transition (EMT) process, and cancer stem cells (CSCs) regulation. The combined utilization of miRNAs with other tests will help patients and clinicians to select the most appropriate personalized treatment and to avoid overdiagnosis and unnecessary biopsies. Future clinical applications of our reported novel miRNAs have a substantial role in the primary diagnosis of prostate cancer to help treatment decisions.

Development of a novel nomogram for predicting clinically significant prostate cancer with the prostate health index and multiparametric MRI

INTRODUCTION

On prostate biopsy, multiparametric magnetic resonance imaging (mpMRI) and the Prostate Health Index (PHI) have allowed prediction of clinically significant prostate cancer (csPCa).

METHODS

To predict the likelihood of csPCa, we created a nomogram based on a multivariate model that included PHI and mpMRI. We assessed 315 males who were scheduled for prostate biopsies.

RESULTS

We used the Prostate Imaging Reporting and Data System version 2 (PI-RADS V2) to assess mpMRI and optimize PHI testing prior to biopsy. Univariate analysis showed that csPCa may be identified by PHI with a cut-off value of 77.77, PHID with 2.36, and PI-RADS with 3 as the best threshold. Multivariable logistic models for predicting csPCa were developed using PI-RADS, free PSA (fPSA), PHI, and prostate volume. A multivariate model that included PI-RADS, fPSA, PHI, and prostate volume had the best accuracy (AUC: 0.882). Decision curve analysis (DCA), which was carried out to verify the nomogram's clinical applicability, showed an ideal advantage (13.35% higher than the model that include PI-RADS only).

DISCUSSION

In conclusion, the nomogram based on PHI and mpMRI is a valuable tool for predicting csPCa while avoiding unnecessary biopsy as much as possible.

Phosphorylated Proteins from Serum: A Promising Potential Diagnostic Biomarker of Cancer

Cancer is a fatal disease worldwide. Each year ten million people are diagnosed around the world, and more than half of patients eventually die from it in many countries. A majority of cancer remains asymptomatic in the earlier stages, with specific symptoms appearing in the advanced stages when the chances of adequate treatment are low. Cancer screening is generally executed by different imaging techniques like ultrasonography (USG), mammography, CT-scan, and magnetic resonance imaging (MRI). Imaging techniques, however, fail to distinguish between cancerous and non-cancerous cells for early diagnosis. To confirm the imaging result, solid and liquid biopsies are done which have certain limitations such as invasive (in case of solid biopsy) or missed early diagnosis due to extremely low concentrations of circulating tumor DNA (in case of liquid biopsy). Therefore, it is essential to detect certain biomarkers by a noninvasive approach. One approach is a proteomic or glycoproteomic study which mostly identifies proteins and glycoproteins present in tissues and serum. Some of these studies are approved by the Food and Drug Administration (FDA). Another non-expensive and comparatively easier method to detect glycoprotein biomarkers is by ELISA, which uses lectins of diverse specificities. Several of the FDA approved proteins used as cancer biomarkers do not show optimal sensitivities for precise diagnosis of the diseases. In this regard, expression of phosphoproteins is associated with a more specific stage of a particular disease with high sensitivity and specificity. In this review, we discuss the expression of different serum phosphoproteins in various cancers. These phosphoproteins are detected either by phosphoprotein enrichment by immunoprecipitation using phosphospecific antibody and metal oxide affinity chromatography followed by LC-MS/MS or by 2D gel electrophoresis followed by MALDI-ToF/MS analysis. The updated knowledge on phosphorylated proteins in clinical samples from various cancer patients would help to develop these serum phophoproteins as potential diagnostic/prognostic biomarkers of cancer.

Ubiquitin-related lncRNAs: The new tool for prognosis prediction in prostate cancer

Objective

To establish a ubiquitin-related long noncoding ribonucleic acids (lncRNAs) prognosis prediction model for prostate cancer (Pca).

Methods

Data were acquired through The Cancer Genome Atlas (TCGA) database. Ubiquitin-related differentially expressed genes (DEGs) and lncRNAs in Pca were filtered out. UBE2S was selected as the representative gene and validated in vitro. Progression-free survival (PFS) predictive signature was established with ubiquitin-related lncRNAs screened by Cox regression analyses and internally validated. A nomogram was constructed to assess the prognosis of Pca patients. Gene enrichment analysis was performed to explore functional differences based on risk stratification. Between different risk groups, immune status and drug sensitivity were contrasted.

Results

A total of 254 ubiquitin-related genes were screened. UBE2S was shown to promote the proliferation of Pca cells in vitro. The predictive signature was established based on six ubiquitin-related lncRNAs and validated. The prognosis of Pca patients was worse with an increasing risk score. The area under the curve (AUC) of the signature was higher than that of clinicopathological variables (0.806 vs 0.504–0.701). The AUC was 0.811 for 1-year PFS, 0.807 for 3-year PFS, and 0.790 for 5-year PFS. The calibration curves of risk score-based nomogram demonstrated high consistency. By contrasting the expression of immune function, cells, and checkpoints, we found that the signature was closely related to immunity. The high-risk patients were more sensitive to gemcitabine, cisplatin, bortezomib, etc. and resistant to bicalutamide.

Conclusion

The ubiquitin-related lncRNAs can effectively predict the prognosis of Pca and may provide new treatment options for Pca.

Biomarkers in Urological Cancers

Urological tumours have become one of the most common cancers in the last decade. It is important to apply an approach that evaluates many factors related to the patient and the disease carefully to minimize cancer-associated morbidity and mortality. The clinical use of cancer biomarkers is a valuable part of the clinical management of urological cancers. These biomarkers may lead to optimized detection, treatment, and follow-up of urological cancers. With the development of molecular research, newly developed biomarkers and next-generation sequencing have also contributed to patient management. In this chapter, we will present biomarkers in the most common urological cancers under subheadings of bladder cancer, prostate cancer, kidney cancer, and testicular cancer. Additionally, due to the development that occurred in the next-generation sequencing (NGS), all the above-mentioned malignancies are evaluated with regard to NGS.

Clinical Utility of Prostate Health Index for Diagnosis of Prostate Cancer in Patients with PI-RADS 3 Lesions

The risk of prostate cancer (PCa) in prostate imaging reporting and data system version 2 (PI-RADSv2) score-3 lesions is equivocal; it is regarded as an intermediate status of presented PCa. In this study, we evaluated the clinical utility of the prostate health index (PHI) for the diagnosis of PCa and clinically significant PCa (csPCa) in patients with PI-RADSv2 score-3 lesions. The study cohort included patients who underwent a transrectal ultrasound (TRUS)-guided, cognitive-targeted biopsy for PI-RADSv2 score-3 lesions between November 2018 and April 2021. Before prostate biopsy, the prostate-specific antigen (PSA) derivatives, such as total PSA (tPSA), [-2] proPSA (p2PSA) and free PSA (fPSA) were determined. The calculation equation of PHI is as follows: [(p2PSA/fPSA) × tPSA ½]. Using a receiver operating characteristic (ROC) curve analysis, the values of PSA derivatives measured by the area under the ROC curve (AUC) were compared. For this study, csPCa was defined as Gleason grade 2 or higher. Of the 392 patients with PI-RADSv2 score-3 lesions, PCa was confirmed in 121 (30.9%) patients, including 59 (15.1%) confirmed to have csPCa. Of all the PSA derivatives, PHI and PSA density (PSAD) showed better performance in predicting overall PCa and csPCa, compared with PSA (all p < 0.05). The AUC of the PHI for predicting overall PCa and csPCa were 0.807 (95% confidence interval (CI): 0.710−0.906, p = 0.001) and 0.819 (95% CI: 0.723−0.922, p < 0.001), respectively. By the threshold of 30, PHI was 91.7% sensitive and 46.1% specific for overall PCa, and was 100% sensitive for csPCa. Using 30 as a threshold for PHI, 34.4% of unnecessary biopsies could have been avoided, at the cost of 8.3% of overall PCa, but would include all csPCa.

Paradigm Shift in Prostate Cancer Diagnosis: Pre-Biopsy Prostate Magnetic Resonance Imaging and Targeted Biopsy

With regard to the indolent clinical characteristics of prostate cancer (PCa), the more selective detection of clinically significant PCa (CSC) has been emphasized in its diagnosis and management. Magnetic resonance imaging (MRI) has advanced technically, and recent international cooperation has provided a standardized imaging and reporting system for prostate MRI. Accordingly, prostate MRI has recently been investigated and utilized as a triage tool before biopsy to guide tissue sampling to increase the detection rate of CSC beyond the staging tool for patients in whom PCa was already confirmed on conventional systematic biopsy. Radiologists must understand the current paradigm shift for better PCa diagnosis and management. This article reviewed the recent literature, demonstrating the diagnostic value of pre-biopsy prostate MRI with targeted biopsy and discussed unsolved issues regarding the paradigm shift in the diagnosis of PCa.

Initial Prostate Health Index (phi) and phi density predicts future risk of clinically significant prostate cancer in men with initial negative prostate biopsy: a 6-year follow-up study

BACKGROUND

Men with elevated prostate-specific antigen (PSA) and initial negative prostate biopsy may have risk of prostate cancer (PCa) in the future. The role of Prostate Health Index (phi) in determining future PCa risk has not been studied before. This study aims to investigate the role of initial phi and phi density in predicting future PCa risk in men with initial negative biopsy.

METHODS

Five hundred sixty nine men with PSA 4-10 ng/mL were recruited between 2008 and 2015 for prostate biopsy with prior phi. Electronic clinical record of men with initial negative biopsy was reviewed. Patients and follow-up doctors were blinded to phi. Kaplan-Meier curves were used to analyze the PCa-free survival in different baseline phi and phi density groups.

RESULTS

Four hundred sixty-one men with complete follow-up data were included. Median follow-up is 77 months. PCa and HGPCa was diagnosed in 8.2% (38/461) and 4.8% (22/461) of cohort respectively. A higher baseline phi value was associated with PCa (p = 0.003) and HGPCa (p < 0.001). HGPCa was diagnosed in 0.6% (1/163) of phi < 25, 4.6% (9/195) of phi 25-34.9, and 11.7% (12/103) of phi ≥ 35 (p < 0.001). HGPCa was diagnosed in 0% (0/109) and 21.0% (13/62) with phi density of <0.4 and ≥1.2, respectively, (p < 0.001). Kaplan-Meier curves showed phi and phi density predicted PCa and HGPCa diagnoses (log-rank test, all p ≤ 0.002).

CONCLUSIONS

Initial phi or phi density predicted 6-year risk of PCa in men with initial negative prostate biopsy. Men with higher phi (≥35) or phi density (≥1.2) need closer follow-up and repeated investigation, while men with lower phi (<25) or phi density (<0.4) could have less frequent follow-up.

Reclassification prediction of first-year protocol biopsy on active surveillance of prostate cancer by p2PSA-related parameters: from PRIAS-JAPAN

BACKGROUND

There is no useful predictive marker for reclassification on active surveillance. Thus, we aimed to investigate thresholds of [-2] proPSA (p2PSA)-related parameters to predict reclassification of the first-year protocol biopsy (1-year PBx) and evaluate the influence of clinical decision-making.

METHODS

This was an observational, prospective cohort study conducted at 19 Japanese institutes. The inclusion criteria included clinical stage T1c/T2, prostate-specific antigen (PSA) levels ≤10 ng/mL, PSA density <0.2 ng/ml/cc, one or two positive biopsy cores, and Gleason score (GS) ≤6 (GS ≦7 for patients aged ≥70 years) at diagnostic biopsy. All participants were required to receive a blood-sampling test on a protocol visit at inclusion and at the 1-year PBx. PSA and PSA isoforms (free PSA, p2PSA) were measured, and parameters (%free PSA, %p2PSA, phi) were calculated. Multivariable logistic regression models were used to predict the reclassification risk. To assess the predictive power and thresholds for reclassification, we plotted Receiver Operating Characteristic (ROC) curves. Decision curve analysis (DCA) was used to evaluate the variables that yielded a net clinical benefit.

RESULTS

A total of 135 patients were included, and 36 patients were reclassified on the 1-year PBx. Multivariate analyses showed that %p2PSA and phi at inclusion and p2PSA, %p2PSA, and phi before the 1-year PBx were significant predictors of reclassification at the 1-year PBx. The ROC analysis showed an optimal cutoff point, sensitivity, and specificity of %p2PSA and phi before the 1-year PBx of 1.64, 86%, 49% and 35.92, 89%, 47%, respectively. The DCA showed that phi before the 1-year PBx had the highest net benefit. The study limitation was its single-arm observational design.

CONCLUSIONS

%p2PSA and phi before the 1-year PBx had a good prediction power. phi is the most useful indicator for clinical decision-making on active surveillance.

TRIAL REGISTRATION

This study is registered atthe Japan Trial Register with ID UMIN000009876 ( https://upload.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000011573 ).

Plasma Polyamine Biomarker Panels: Agmatine in Support of Prostate Cancer Diagnosis

Prostate cancer is the most frequent malignant tumour among males (19%), often clinically silent and of difficult prognosis. Although several studies have highlighted the diagnostic and prognostic role of circulating biomarkers, such as PSA, their measurement does not necessarily allow the detection of the disease. Within this context, many authors suggest that the evaluation of circulating polyamines could represent a valuable tool, although several analytical problems still counteract their clinical practice. In particular, agmatine seems particularly intriguing, being a potential inhibitor of polyamines commonly derived from arginine. The aim of the present work was to evaluate the potential role of agmatine as a suitable biomarker for the identification of different classes of patients with prostate cancer (PC). For this reason, three groups of human patients—benign prostatic hyperplasia (BPH), precancerous lesion (PL), and prostate cancer (PC)—were recruited from a cohort of patients with suspected prostate cancer (n = 170), and obtained plasma was tested using the LC-HRMS method. Statistics on the receiver operating characteristics curve (ROC), and multivariate analysis were used to examine the predictive value of markers for discrimination among the three patient groups. Statistical analysis models revealed good discrimination using polyamine levels to distinguish the three classes of patients. AUC above 0.8, sensitivity ranging from 67% to 89%, specificity ranging from 74% to 89% and accuracy from 73% to 86%, considering the validation set, were achieved. Agmatine plasma levels were measured in PC (39.9 ± 12.06 ng/mL), BPH (77.62 ± 15.05 ng/mL), and PL (53.31 ± 15.27 ng/mL) patients. ROC analysis of the agmatine panel showed an AUC of 0.959 and p ≤ 0.001. These results could represent a future tool able to discriminate patients belonging to the three different clinical groups.

Urothelial carcinoembryonic antigen 1 score for early detection of prostate cancer and risk prediction

UCA1 score appears useful in detecting nonhigh-risk (including very low-, low-, or intermediate-risk) prostate cancer. Combination of the PSA level and the UCA1 score may significantly reduce the burden of prostate biopsy.

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.

Development of the DNA-based biosensors for high performance in detection of molecular biomarkers: More rapid, sensitive, and universal

The molecular biomarkers are molecules that are closely related to specific physiological states. Numerous molecular biomarkers have been identified as targets for disease diagnosis and biological research. To date, developing highly efficient probes for the precise detection of biomarkers has become an attractive research field which is very important for biological and biochemical studies. During the past decades, not only the small chemical probe molecules but also the biomacromolecules such as enzymes, antibodies, and nucleic acids have been introduced to construct of biosensor platform to achieve the detection of biomarkers in a highly specific and highly efficient way. Nevertheless, improving the performance of the biosensors, especially in clinical applications, is still in urgent demand in this field. A noteworthy example is the Corona Virus Disease 2019 (COVID-19) that breaks out globally in a short time in 2020. The COVID-19 was caused by the virus called SARS-CoV-2. Early diagnosis is very important to block the infection of the virus. Therefore, during these months scientists have developed dozens of methods to achieve rapid and sensitive detection of the virus. Nowadays some of these new methods have been applied for producing the commercial detection kit and help people against the disease worldwide. DNA-based biosensors are useful tools that have been widely applied in the detection of molecular biomarkers. The good stability, high specificity, and excellent biocompatibility make the DNA-based biosensors versatile in application both in vitro and in vivo. In this paper, we will review the major methods that emerged in recent years on the design of DNA-based biosensors and their applications. Moreover, we will also briefly discuss the possible future direction of DNA-based biosensors design. We believe this is helpful for people interested in not only the biosensor field but also in the field of analytical chemistry, DNA nanotechnology, biology, and disease diagnosis.

[Clinical use and evolution of circulating biomarkers in the era of personalized oncology: From protein markers to bioclinical scores]

In oncology, the identification of targets that correlate with a type of cancer has led to a profound change in the notion of "tumor markers". Technological advances, in particular the development of high-throughput sequencing, have led to the emergence of a new generation of molecular biomarkers for tumors. Despite their limited utility for screening and diagnosis, conventional tumor markers remain interesting for evaluation of prognoses, the choice and optimization of treatments, as well as for monitoring the effectiveness of those treatments. In this article, we revisit the conventional serum markers that are enjoying a 'come back' thanks to the development of high-performance scores based on biological, cytological, clinical, or radiological criteria.

Beyond Prostate Specific Antigen: New Prostate Cancer Screening Options

Prostate specific antigen (PSA) is one of the best-known biomarkers for screening, diagnosis and follow-up of patients for prostate cancer. Owing to several inherent limitations with PSA, various newer blood and urinary based biomarkers have been evaluated in pursuit of better detection and risk stratification of prostate cancer cases. A combination of these different markers, in adjunct with clinical risk factors, and recent advances in imaging promises to offer better diagnostic performance with clearer risk stratification guiding therapeutics. We carried out an extensive literature search for the different biomarkers available for screening and diagnosis of prostate cancer, compared their performance with serum PSA to allow clinicians to draw meaningful conclusions to offer their patients a more personalized medical care.

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.

On the Road to Accurate Protein Biomarkers in Prostate Cancer Diagnosis and Prognosis: Current Status and Future Advances

Prostate cancer (PC) is a leading cause of morbidity and mortality among men worldwide. Molecular biomarkers work in conjunction with existing clinicopathologic tools to help physicians decide who to biopsy, re-biopsy, treat, or re-treat. The past decade has witnessed the commercialization of multiple PC protein biomarkers with improved performance, remarkable progress in proteomic technologies for global discovery and targeted validation of novel protein biomarkers from clinical specimens, and the emergence of novel, promising PC protein biomarkers. In this review, we summarize these advances and discuss the challenges and potential solutions for identifying and validating clinically useful protein biomarkers in PC diagnosis and prognosis. The identification of multi-protein biomarkers with high sensitivity and specificity, as well as their integration with clinicopathologic parameters, imaging, and other molecular biomarkers, bodes well for optimal personalized management of PC patients.

An analysis of three different prostate cancer risk calculators applied prior to prostate biopsy: A Turkish cohort validation study

The study aimed to investigate the best-performing of three risk calculators (RCs) for the Turkish population in predicting cancer-free status and high-risk prostate cancer (PCa) in patients undergoing transrectal ultrasound-guided prostate biopsy. The electronic medical records of 527 patients who underwent prostate biopsy for the first time due to PSA of 0.3-50 ng/dl and/or cancer suspicion at digital rectal examination (DRE) between January 2017 and December 2020 were retrieved retrospectively. The predictive power of the RCs in the biopsy and the surgical cohort was calculated by two urologists using European Randomised Study of Screening for Prostate Cancer (ERSPC) RC, the North American Prostate Cancer Prevention Trial-RC (PCPT-RC), and the Prostate Biopsy Collaborative Group (PBCG)-RC. All three RCs were successful in predicting PCa and high-risk disease at ROC analysis (p < 0.0001). Of these three nomograms, PBCG-RC outperformed PCPT-RC 2.0 and ERSPC-RH in predicting benign pathology outcomes at biopsy. A better performance of PBCG-RC was also observed in terms of prediction of high-risk disease at biopsy. Using any of the available RCs prior to biopsy is of greater assistance to prostate-specific antigen and DRE than examination alone. The study results show that PBCG-RC performed before biopsy has a higher predictive power than the other two RCs.

The Role and Significance of Bioumoral Markers in Prostate Cancer

The prostate is one of the most clinically accessible internal organs of the genitourinary tract in men. For decades, the only method of screening for prostate cancer (PCa) has been digital rectal examination of 1990s significantly increased the incidence and prevalence of PCa and consequently the morbidity and mortality associated with this disease. In addition, the different types of oncology treatment methods have been linked to specific complications and side effects, which would affect the patient's quality of life. In the first two decades of the 21st century, over-detection and over-treatment of PCa patients has generated enormous costs for health systems, especially in Europe and the United States. The Prostate Specific Antigen (PSA) is still the most common and accessible screening blood test for PCa, but with low sensibility and specificity at lower values (<10 ng/mL). Therefore, in order to avoid unnecessary biopsies, several screening tests (blood, urine, or genetic) have been developed. This review analyzes the most used bioumoral markers for PCa screening and also those that could predict the evolution of metastases of patients diagnosed with PCa.

Blood and urine biomarkers in prostate cancer: Are we ready for reflex testing in men with an elevated prostate-specific antigen?

Objective

There is no consensus on the role of biomarkers in determining the utility of prostate biopsy in men with elevated prostate-specific antigen (PSA). There are numerous biomarkers such as prostate health index, 4Kscore, prostate cancer antigen 3, ExoDX, SelectMDx, and Mi-Prostate Score that may be useful in this decision-making process. However, it is unclear whether any of these tests are accurate and cost-effective enough to warrant being a widespread reflex test following an elevated PSA. Our goal was to report on the clinical utility of these blood and urine biomarkers in prostate cancer screening.

Methods

We performed a systematic review of studies published between January 2000 and October 2020 to report the available parameters and cost-effectiveness of the aforementioned diagnostic tests. We focus on the negative predictive value, the area under the curve, and the decision curve analysis in comparing reflexive tests due to their relevance in evaluating diagnostic screening tests.

Results

Overall, the biomarkers are roughly equivalent in predictive accuracy. Each test has additional clinical utility to the current diagnostic standard of care, but the added benefit is not substantial to justify using the test reflexively after an elevated PSA.

Conclusions

Our findings suggest these biomarkers should not be used in binary fashion and should be understood in the context of pre-existing risk predictors, patient's ethnicity, cost of the test, patient life-expectancy, and patient goals. There are more recent diagnostic tools such as multi-parametric magnetic resonance imaging, polygenic single-nucleotide panels, IsoPSA, and miR Sentinel tests that are promising in the realm of prostate cancer screening and need to be investigated further to be considered a consensus reflexive test in the setting of prostate cancer screening.

Prostate Health Index (phi) and its derivatives predict Gleason score upgrading after radical prostatectomy among patients with low-risk prostate cancer

To analyze the performance of the Prostate Health Index (phi) and its derivatives for predicting Gleason score (GS) upgrading between prostate biopsy and radical prostatectomy (RP) in the Chinese population, an observational, prospective RP cohort consisting of 351 patients from two medical centers was established from January 2017 to September 2020. Pathological reclassification was determined by the Gleason Grade Group (GG). The area under the receiver operating characteristic curve (AUC) and logistic regression (LR) models were used to evaluate the predictive performance of predictors. In clinically low-risk patients with biopsy GG ≤ 2, phi (odds ratio [OR] = 1.80, 95% confidence interval [95% CI]: 1.14–2.82, P = 0.01) and its derivative phi density (PHID; OR = 2.34, 95% CI: 1.30–4.20, P = 0.005) were significantly associated with upgrading to GG ≥3 after RP, and the results were confirmed by multivariable analysis. Similar results were observed in patients with biopsy GG of 1 for the prediction of upgrading to RP GG ≥2. Compared to the base model (AUC = 0.59), addition of the phi or PHID could provide additional predictive value for GS upgrading in low-risk patients (AUC = 0.69 and 0.71, respectively, both P < 0.05). In conclusion, phi and PHID could predict GS upgrading after RP in clinically low-risk patients.

A Germline Variant at 8q24 Contributes to the Serum p2PSA Level in a Chinese Prostate Biopsy Cohort

Introduction

The clinical performance of [-2]proPSA (p2PSA) and its derivatives in predicting the presence and aggressiveness of prostate cancer (PCa) has been well evaluated in prostate biopsy patients. However, no study has been performed to evaluate the common genetic determinants that affect serum level of p2PSA.

Materials and Methods

Here, we performed a two-stage genome-wide association study (GWAS) on the p2PSA level in Chinese men who underwent a transperineal ultrasound-guided prostate biopsy at Huashan Hospital, Shanghai Cancer Center, and Ruijin Hospital in Shanghai, China. Germline variants significantly associated with the p2PSA level in the first stage (n = 886) were replicated in the second stage (n = 1,128). Multivariate linear regression was used to assess the independent contribution of confirmed single nucleotide polymorphisms (SNPs) and known covariates, such as age, to the level of p2PSA.

Results

A novel non-synonymous SNP, rs72725879, in region 8q24.21 of the PRNCR1 gene was significantly associated with the serum level of p2PSA in this two-stage GWAS (p = 2.28 × 10^-9). Participants with homozygous "T" alleles at rs72725879 had higher p2PSA levels compared to allele "C" carriers. This variant was also nominally associated with PCa risk (p-combined = 3.44 × 10^-18). The association with serum level of p2PSA was still significant after adjusting for PCa risk and age (p = 0.017).

Conclusions

Our study shows that the genetic variants in the 8q24.21 region are associated with the serum level of p2PSA in a large-scale Chinese population. By taking inherited variations between individuals into account, the findings of these genetic variants may help improve the performance of p2PSA in predicting prostate cancer.

Usefulness of the prostate health index in predicting the presence and aggressiveness of prostate cancer among Korean men: a prospective observational study

Background

We aimed to evaluate the usefulness of the Beckman Coulter prostate health index (PHI) and to compare it with total prostate-specific antigen (PSA) levels and related derivatives in predicting the presence and aggressiveness of prostate cancer (PCa) in the Korean population.

Methods

A total of 140 men who underwent their first prostate biopsy for suspected PCa were included in this prospective observational study. The diagnostic performance of total PSA, free PSA, %free PSA, [–2] proPSA (p2PSA), %p2PSA, and PHI in detecting and predicting the aggressiveness of PCa was estimated using the receiver operating characteristic curve (ROC) and logistic multivariate regression analyses.

Results

Of 140 patients, PCa was detected in 63 (45%) of participants, and 48 (76.2%) of them had significant cancer with a Gleason score (GS) ≥ 7. In the whole group, the area under the curve (AUC) for ROC analysis of tPSA, free PSA, %fPSA, p2PSA, %p2PSA, and PHI were 0.63, 0.57, 0.69, 0.69, 0.72, and 0.76, respectively, and the AUC was significantly greater in the PHI group than in the tPSA group (p = 0.005). For PCa with GS ≥ 7, the AUCs for tPSA, free PSA, %fPSA, p2PSA, %p2PSA, and PHI were 0.62, 0.58, 0.41, 0.79, 0.86, and 0.87, respectively, and the AUC was significantly greater in the PHI group than in the tPSA group (p < 0.001). In the subgroup with tPSA 4–10 ng/mL, both %p2PSA and PHI were strong independent predictors for PCa (p = 0.007, p = 0.006) and significantly improved the predictive accuracy of a base multivariable model, including age, tPSA, fPSA and %fPSA, using multivariate logistic regression analysis. (p = 0.054, p = 0.048). Additionally, at a cutoff PHI value > 33.4, 22.9% (32/140) of biopsies could be avoided without missing any cases of aggressive cancer.

Conclusions

This study shows that %p2PSA and PHI are superior to total PSA and %fPSA in predicting the presence and aggressiveness (GS ≥ 7) of PCa among Korean men. Using PHI, a significant proportion of unnecessary biopsies can be avoided.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12894-021-00897-2.

Genetic polymorphisms at 19q13.33 are associated with [-2]proPSA (p2PSA) levels and provide additional predictive value to prostate health index for prostate cancer

BACKGROUND

Prostate health index (phi), a derivative of [-2]proPSA (p2PSA), has shown better accuracy than prostate-specific antigen (PSA) in prostate cancer (PCa) detection. The present study was to investigate whether previously identified PSA-associated single nucleotide polymorphisms (SNPs) influence p2PSA or phi levels and lead to potential clinical utility.

METHODS

We conducted an observational prospective study with 2268 consecutive patients who underwent prostate biopsy in three tertiary medical centers from August 2013 to March 2019. Genotyping data of the 46 candidate genes with a ± 100 kb window were tested for association with p2PSA and phi levels using linear regression. Multivariable logistic regression models were performed and internally validated using repeated tenfold cross-validation. We further calculated personalized phi cutoff values based on the significant genotypes. Discriminative performance was assessed using decision curve analysis and net reclassification improvement (NRI) index.

RESULTS

We detected 11 significant variants at 19q13.33 which were p2PSA-associated independent of PCa. The most significant SNP, rs198978 in KLK2 (P_combined  = 5.73 × 10^-9 ), was also associated with phi values (P_combined  = 3.20 × 10^-6 ). Compared to the two commonly used phi cutoffs of 27.0 and 36.0, the personalized phi cutoffs had a significant NRI for PCa ranged from 5.23% to 9.70% among men carrying variant types (all p < .01).

CONCLUSION

Rs198978, is independently associated with p2PSA values, and can improve the diagnostic ability of phi for PCa using personalized cutoff values.