Urinary Biomarkers for Prostate Cancer

Unveiling the potential of SLURP1 protein as a biomarker for prostate cancer screening

Background

Prostate cancer (PCa) develops slowly and lacks obvious symptoms in the early stage, which makes early screening and diagnosis difficult. Urine collection is simple and is an ideal source of biomarkers. In this study, we performed urinary proteomic studies in PCa patients to screen proteins and apply them to the non-invasive early diagnosis of PCa.

Method

Urine samples from PCa patients, benign prostatic hyperplasia (BPH) patients and normal control group were collected. Mass spectrometry was used for proteomic analysis and screening target proteins. Western blot and enzyme-linked immunosorbent assay (ELISA) were used to verify the results. Correlations with clinical indicators were explored, and receiver operating characteristic (ROC) curves were drawn to evaluate the value of target proteins in PCa.

Result

A total of 1065 proteins were identified. Urinary SLURP1 protein was significantly elevated in patients with PCa compared with normal controls and patients with BPH patients. Western blot and ELISA further verified the expression changes of SLURP1. The immunohistochemical staining results revealed a substantial increase in positive SLURP1 expression within PCa tumor tissue. Correlation analysis showed a positive correlation between the expression level of urine SLURP1 protein and serum PSA. ROC curve analysis of the SLURP1 protein in the urine of both normal individuals and PCa patients is determined to be 0.853 (95% CI=0.754 to 0.954).

Conclusion

The concentration of SLURP1 protein in urine of PCa patients is increased, which can serve as a biomarker for screening 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.

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.

Use of the MyProstateScore Test to Rule Out Clinically Significant Cancer: Validation of a Straightforward Clinical Testing Approach

PURPOSE

The MyProstateScore test was validated for improved detection of clinically significant (grade group ≥2) prostate cancer relative to prostate specific antigen based risk calculators. We sought to validate an optimal MyProstateScore threshold for clinical use in ruling out grade group ≥2 cancer in men referred for biopsy.

MATERIALS AND METHODS

Biopsy naïve men provided post-digital rectal examination urine prior to biopsy. MyProstateScore was calculated using the validated, locked multivariable model including only serum prostate specific antigen, urinary prostate cancer antigen 3 and urinary TMPRSS2:ERG. The MyProstateScore threshold approximating 95% sensitivity for grade group ≥2 cancer was identified in a training cohort, and performance was measured in 2 external validation cohorts. We assessed the 1) overall biopsy referral population and 2) population meeting guideline based testing criteria (ie, prostate specific antigen 3-10, or <3 with suspicious digital rectal examination).

RESULTS

Validation cohorts were prospectively enrolled from academic (977 patients, median prostate specific antigen 4.5, IQR 3.1-6.0) and community (548, median prostate specific antigen 4.9, IQR 3.7-6.8) settings. In the overall validation population (1,525 patients), 338 men (22%) had grade group ≥2 cancer on biopsy. The MyProstateScore threshold of 10 provided 97% sensitivity and 98% negative predictive value for grade group ≥2 cancer. MyProstateScore testing would have prevented 387 unnecessary biopsies (33%), while missing only 10 grade group ≥2 cancers (3.0%). In 1,242 patients meeting guideline based criteria, MyProstateScore ≤10 provided 96% sensitivity and 97% negative predictive value, and would have prevented 32% of unnecessary biopsies, missing 3.7% of grade group ≥2 cancers.

CONCLUSIONS

In a large, clinically pertinent biopsy referral population, MyProstateScore ≤10 provided exceptional sensitivity and negative predictive value for ruling out grade group ≥2 cancer. This straightforward secondary testing approach would reduce the use of more costly and invasive procedures after screening with prostate specific antigen.

Precision Medicine Approach in Prostate Cancer

Prostate cancer is the most prevalent type of cancer and the second cause of death in men worldwide. Various diagnostic and treatment procedures are available for this type of malignancy, but High-grade or locally advanced prostate cancers showed the potential to develop to lethal phase that can be causing dead. Therefore, new approaches are needed to prolong patients' survival and to improve their quality of life. Precision medicine is a novel emerging field that plays an essential role in identifying new sub-classifications of diseases and in providing guidance in treatment that is based on individual multi-omics data. Multi-omics approaches include the use of genomics, transcriptomics, proteomics, metabolomics, epigenomics and phenomics data to unravel the complexity of a disease-associated biological network, to predict prognostic biomarkers, and to identify new targeted drugs for individual cancer patients. We review the impact of multi-omics data in the framework of systems biology in the era of precision medicine, emphasising the combination of molecular imaging modalities with highthroughput techniques and the new treatments that target metabolic pathways involved in prostate cancer.

A novel method for detection of exfoliated prostate cancer cells in urine by RNA in situ hybridization

BACKGROUND

In the current study, we explore the feasibility of detecting exfoliated prostate cancer cells in urine using an RNA in situ hybridization (RISH) assay. We hypothesized that robust and specific labeling of prostate cancer cells could be achieved in post-digital rectal examination (DRE) urine samples using RISH.

METHODS

We focused on method development, optimization, and analytical evaluation of RISH-based detection of prostate cancer in urine. We optimized a sample collection, processing, and target detection workflow for urine cytology specimens in conjunction with RNA target detection by RISH. We screened a panel of 11 prostate-specific RNA targets, and selected NKX3-1 and PRAC1 as markers for cells of prostate origin and PCA3 as a marker of prostate malignancy. Following analytical validation of a multiplexed NKX3-1/PRAC1/PCA3 assay, we evaluated whether prostate cancer cells can be detected in a pilot cohort of 19 post-DRE specimens obtained from men diagnosed with prostate cancer.

RESULTS

Using cytology specimens prepared from spiked urine samples, we established the analytical validity of the RISH assay for detection and visualization of prostate cells in urine. Cells of prostate origin could be readily and specifically identified and separated into benign and malignant cell populations based on the multiplex test that consisted of markers specific for prostate cells (NKX3-1, PRAC1) and prostate cancer cells (PCA3). Upon evaluation of post-DRE urine from a pilot cohort of prostate cancer patients, we identified 11 samples in which prostate cells were present, 6 of which were also positive for prostate cancer cells.

CONCLUSIONS

Multiplex RISH enables the direct visualization and molecular characterization of individual exfoliated prostate cells in urine. This proof-of-principle study provides evidence supporting the application of RISH as a potential noninvasive tool for prostate cancer detection.

Urinary Exosomes from Bladder Cancer Patients Show a Residual Cancer Phenotype despite Complete Pathological Downstaging

Invasive urinary bladder cancer shows high recurrence rates after cystectomy even with apparent complete downstaging at cystectomy. Exosomes are nano-sized vesicles important in cell-cell communication, which have been hypothesized to contribute to cancer dissemination and recurrence. The aim of this study was to investigate if pro-carcinogenic exosomes could be detected in urine from histologically downstaged bladder cancer patients. 13 Patients were included in this study. Paired ureter and urine samples from nine patients underwent mass spectrometry, while samples from the remaining patients were used for exosome characterization. At cystectomy, exosomes were isolated from bladder and ureter urine, whereafter quantitative proteome profiling was performed. Urinary exosomes clustered based on whether they came from the bladder, with tumour contact, or the ureters, without tumour contact, even though all came from completely downstaged patients. Proteins overexpressed in exosomes derived from bladder urine contained several oncogenes and were mainly associated with tumour metabolism pathways. Although patients were histologically tumour-free at cystectomy, the bladder urine contained exosomes with a carcinogenic metabolic profile. This suggests a continuous release of exosomes from the bladder, which may promote recurrence at distant sites through metabolic rewiring, even after apparent complete downstaging. These exosomes, coming from either undetected cancer cells or partly transformed cells, are likely to increase the risk of metastasis and encourages cystectomy even in completely downstaged patients.

Establishment of reference intervals for serum [-2]proPSA (p2PSA), %p2PSA and prostate health index in healthy men

Background

Prostate cancer (PCa) is the second most common cancer among men worldwide. Recent research has identified [-2]proPSA (p2PSA), %p2PSA and prostate health index (phi) as new biomarkers for the early diagnosis and grading of PCa. However, few studies have used these parameters in a healthy population. In this study, we aimed to establish reference intervals (RIs) for p2PSA, %p2PSA and phi in healthy men based on age stratification.

Methods

Between April 2016 and March 2018, healthy subjects were recruited. Healthy men were then stratified into four age groups: <40 years, 40-49 years, 50-59 years and ≥60 years. Total PSA (tPSA), free PSA (fPSA), %fPSA, p2PSA, %p2PSA and phi were measured and RIs were established for p2PSA, %p2PSA and phi.

Results

In total, 732 healthy men were used for analysis. The RIs of phi were 9.77-48.44 for <40 years of age, 9.85-65.28 for 40-49 years of age, 9.98-39.72 for 50-59 years of age and 8.16-40.76 for ≥60 years of age. The reference values at the age of 40-49 years were generally higher than those at ≥60 years of age.

Conclusions

Age-specific RIs for p2PSA, %p2PSA and phi were established in this study. This first set of established RIs will be invaluable for physicians to make precise medical decisions and carry out appropriate medical interventions.

CE-MS-based urinary biomarkers to distinguish non-significant from significant prostate cancer

Background

Prostate cancer progresses slowly when present in low risk forms but can be lethal when it progresses to metastatic disease. A non-invasive test that can detect significant prostate cancer is needed to guide patient management.

Methods

Capillary electrophoresis/mass spectrometry has been employed to identify urinary peptides that may accurately detect significant prostate cancer. Urine samples from 823 patients with PSA (<15 ng/ml) were collected prior to biopsy. A case–control comparison was performed in a training set of 543 patients (n_Sig = 98; n_non-Sig = 445) and a validation set of 280 patients (n_Sig = 48, n_non-Sig = 232). Totally, 19 significant peptides were subsequently combined by a support vector machine algorithm.

Results

Independent validation of the 19-biomarker model in 280 patients resulted in a 90% sensitivity and 59% specificity, with an AUC of 0.81, outperforming PSA (AUC = 0.58) and the ERSPC-3/4 risk calculator (AUC = 0.69) in the validation set.

Conclusions

This multi-parametric model holds promise to improve the current diagnosis of significant prostate cancer. This test as a guide to biopsy could help to decrease the number of biopsies and guide intervention. Nevertheless, further prospective validation in an external clinical cohort is required to assess the exact performance characteristics.

GSTP1 methylation in cancer: a liquid biopsy biomarker?

The coding region of GSTP1 gene is preceded by a large CpG-rich region that is frequently affected by methylation. In many cancer types, GSTP1 is affected by hypermethylation and, as a consequence, it has a low expression. The aim of this review is to give an overview on GSTP1 methylation studies with a special focus on liquid biopsy, thus to summarize methods, results, sample types, different diseases, to have a complete information regarding this promising epigenetic biomarker. We used all the most valuable scientific search engines (PubMed, Medline, Scopus and Web of Science) searching the following keywords: GSTP1, methylation, cancer, urine, serum, plasma and blood. GSTP1 is a largely investigated tissue biomarker in several malignancies such as prostate, breast, lung and hepatocellular carcinoma with good performances especially for diagnostic purposes. As a liquid biopsy biomarker, it has been mainly investigated in prostate cancer (PCa) where it showed a high specificity but a low sensitivity; thus, it is recommended in combination with other biomarkers. Despite the large number of published papers and the promising results, GSTP1 has not yet entered the clinical practice even for PCa diagnosis. For this reason, further large and prospective studies are needed to validate this assay.

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

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

Searching for the Novel Specific Predictors of Prostate Cancer in Urine: The Analysis of 84 miRNA Expression

The aim of this study was to investigate miRNA profiles of clarified urine supernatant and combined urine vesicle fractions of healthy donors and patients with benign prostatic hyperplasia and prostate cancer (PCa). The comparative analysis of miRNA expression was conducted with a custom miRCURY LNA miRNA qPCR panel. Significant combinations of miRNA pairs were selected by the RandomForest-based feature selection algorithm Boruta; the difference of the medians between the groups and a 95% confidence interval was built using the bootstrap approach. The Asymptotic Wilcoxon-Mann-Whitney Test was performed for miRNA combinations to compare different groups of donors. Benjamini-Hochberg correction was used to adjust the statistical significance for multiple comparisons. The most diagnostically significant miRNAs pairs were miR-107-miR-26b.5p and miR-375.3p-miR-26b.5p in the urine supernatant fraction that discriminated the group of healthy patients and PCa patients, as well as miR-31.5p-miR-16.5p, miR-31.5p-miR-200b, miR-31.5p-miR-30e.3p and miR-31.5p-miR-660.5p in the fraction extracellular vesicles that were different between healthy men and benign prostate hyperplasia patients. Such statistical criteria as the occurrence of individual significant miRNA pairs in the total number of comparisons, median ΔCt difference, and confidence interval can be useful tools for determining reliable markers of PCa.

Urinary biomarkers of prostate cancer

The development of more specific biomarkers for prostate cancer and/or high-risk prostate cancer is necessary, because the prostate-specific antigen test lacks specificity for the detection of prostate cancer and can lead to unnecessary prostate biopsies. Urine is a promising source for the development of new biomarkers of prostate cancer. Biomarkers derived from prostate cancer cells are released into prostatic fluids and then into urine. Urine after manipulation of the prostate is enriched with prostate cancer biomarkers, which include prostate cancer cells, DNAs, RNAs, proteins and other small molecules. The urinary prostate cancer antigen 3 test is the first Food and Drug Administration-approved RNA-based urinary marker, and it helps in the detection of prostate cancer on repeat biopsy. The SelectMDx test is based on messenger RNA detection of DLX1 and HOXC6 in urine after prostate massage, and helps in the detection of high-risk prostate cancer on prostate biopsy. Exosomes are extracellular vesicles with a diameter of 30-200 nm that are secreted from various types of cells. Urinary prostate cancer-derived exosomes also contain RNAs and proteins specific for prostate cancer (e.g. PCA3 and TMPRSS2-ERG), and could be promising sources of novel biomarker discovery. The ExoDx Prostate test is a commercially available test based on the detection of three genes (PCA3, ERG and SPDEF) in urinary exosomes. Advancement of comprehensive analysis (microarray, mass spectrometry and next-generation sequencing) has resulted in the discovery of several urinary biomarkers. Non-invasive urinary markers can help in the decision to carry out prostate biopsy or in the design of a therapeutic strategy.

Combining Prostate Health Index density, magnetic resonance imaging and prior negative biopsy status to improve the detection of clinically significant prostate cancer

OBJECTIVES

To determine the performance of Prostate Health Index (PHI) density (PHID) combined with MRI and prior negative biopsy (PNB) status for the diagnosis of clinically significant prostate cancer (PCa).

PATIENTS AND METHODS

Patients without a prior diagnosis of PCa, with elevated prostate-specific antigen and a normal digital rectal examination who underwent PHI testing prospectively prior to prostate biopsy were included in this study. PHID was calculated retrospectively using prostate volume derived from transrectal ultrasonography at biopsy. Univariable and multivariable logistic regression modelling, along with receiver-operating characteristic (ROC) curve analysis, was used to determine the ability of serum biomarkers to predict clinically significant PCa (defined as either grade group [GG] ≥2 disease or GG1 PCa detected in >2 cores or >50% of any one core) on biopsy. Age, PNB status and Prostate Imaging Reporting and Data System (PI-RADS) score were incorporated into the regression models.

RESULTS

Of the 241 men who qualified for the study, 91 (37.8%) had clinically significant PCa on biopsy. The median (interquartile range) PHID was 0.74 (0.44-1.24); it was 1.18 (0.77-1.83) and 0.55 (0.38-0.89) in those with and without clinically significant PCa on biopsy, respectively (P < 0.001). On univariable logistic regression, age and PNB status were associated with clinically significant cancer. Of the tested biomarkers, PHID demonstrated the highest discriminative ability for clinically significant disease (area under the ROC curve [AUC] 0.78 for the univariable model). That continued to be the case in multivariable logistic regression models incorporating age and PNB status (AUC 0.82). At a threshold of 0.44, representing the 25th percentile of PHID in the cohort, PHID was 92.3% sensitive and 35.3% specific for clinically significant PCa; the sensitivity and specificity were 93.0% and 32.4% and 97.4% and 29.1% for GG ≥2 and GG ≥3 disease, respectively. In the 104 men who underwent MRI, PI-RADS score was complementary to PHID, with a PI-RADS score ≥3 or, if PI-RADS score ≤2, a PHID ≥0.44, detecting 100% of clinically significant disease. For that subgroup, of the biomarkers tested, PHID (AUC 0.90) demonstrated the highest discriminative ability for clinically significant disease on multivariable logistic regression incorporating age, PNB status and PI-RADS score.

CONCLUSIONS

In this contemporary cohort of men undergoing prostate biopsy for the diagnosis of PCa, PHID outperformed PHI and other PSA derivatives in the diagnosis of clinically significant cancer. Incorporating age, PNB status and PI-RADS score led to even further gains in the diagnostic performance of PHID. Furthermore, PI-RADS score was found to be complementary to PHID. Using 0.44 as a threshold for PHID, 35.3% of unnecessary biopsies could have been avoided at the cost of missing 7.7% of clinically significant cancers. Despite these encouraging results, prospective validation is needed.

Prostate Cancer Markers

Diagnostic biomarkers derived from blood, urine, or prostate tissue provide additional information beyond clinical calculators to determine the risk of detecting high-grade prostate cancer. Once diagnosed, multiple markers leverage prostate cancer biopsy tissue to prognosticate clinical outcomes, including adverse pathology at radical prostatectomy, disease recurrence, and prostate cancer mortality; however the clinical utility of some outcomes to patient decision making is unclear. Markers using tissue from radical prostatectomy specimens provide additional information about the risk of biochemical recurrence, development of metastatic disease, and subsequent mortality beyond existing multivariable clinical calculators (the use of a marker to simply sub-stratify risk groups such as the NCCN groups is of minimal value). No biomarkers currently available for prostate cancer have been prospectively validated to be predict an improved clinical outcome for a specific therapy based on the test result; however, further research and development of these tests may produce a truly predictive biomarker for prostate cancer treatment.

Comparative Proteomics Analysis of Urine Reveals Down-Regulation of Acute Phase Response Signaling and LXR/RXR Activation Pathways in Prostate Cancer

Detecting prostate cancer (PCa) using non-invasive diagnostic markers still remains a challenge. The aim of this study was the identification of urine proteins that are sufficiently sensitive and specific to detect PCa in the early stages. Comparative proteomics profiling of urine from patients with PCa, benign prostate hyperplasia, bladder cancer, and renal cancer, coupled with bioinformatics analysis, were performed. Statistically significant difference in abundance showed 20 and 85 proteins in the 2-D DIGE/MS and label-free LC-MS/MS experiments, respectively. In silico analysis indicated activation, binding, and cell movement of subset of immune cells as the top affected cellular functions in PCa, together with the down-regulation of Acute Phase Response Signaling and Liver X Receptor/ Retinoid X Receptor (LXR/RXR) activation pathways. The most promising biomarkers were 35, altered in PCa when compared to more than one group. Half of these have confirmed localization in normal or PCa tissues. Twenty proteins (CD14, AHSG, ENO1, ANXA1, CLU, COL6A1, C3, FGA, FGG, HPX, PTGDS, S100A9, LMAN2, ITIH4, ACTA2, GRN, HBB, PEBP1, CTSB, SPP1) are oncogenes, tumor suppressors, and multifunctional proteins with highly confirmed involvement in PCa, while 9 (AZU1, IGHG1, RNASE2, PZP, REG1A, AMY1A, AMY2A, ACTG2, COL18A1) have been associated with different cancers, but not with PCa so far, and may represent novel findings. LC-MS/MS data are available via ProteomeXchange with identifier PXD008407.

Current Management Strategy for Active Surveillance in Prostate Cancer

PURPOSE OF REVIEW

Active surveillance has been increasingly utilized as a strategy for the management of favorable-risk, localized prostate cancer. In this review, we describe contemporary management strategies of active surveillance, with a focus on traditional stratification schemes, new prognostic tools, and patient outcomes.

RECENT FINDINGS

Patient selection, follow-up strategy, and indication for delayed intervention for active surveillance remain centered around PSA, digital rectal exam, and biopsy findings. Novel tools which include imaging, biomarkers, and genetic assays have been investigated as potential prognostic adjuncts; however, their role in active surveillance remains institutionally dependent. Although 30-50% of patients on active surveillance ultimately undergo delayed treatment, the vast majority will remain free of metastasis with a low risk of dying from prostate cancer. The optimal method for patient selection into active surveillance is unknown; however, cancer-specific mortality rates remain excellent. New prognostication tools are promising, and long-term prospective, randomized data regarding their use in active surveillance will be beneficial.

Exosomes: A Novel Strategy for Treatment and Prevention of Diseases

An “exosome” is a nanoscale membrane vesicle derived from cell endocytosis that functions as an important intercellular communication mediator regulating the exchange of proteins and genetic materials between donor and surrounding cells. Exosomes secreted by normal and cancer cells participate in tumor initiation, progression, invasion, and metastasis. Furthermore, immune cells and cancer cells exert a two-way bidirectional regulatory effect on tumor immunity by exchanging exosomes. Current studies on exosomes have further expanded their known functions in physiological and pathological processes. The purpose of this review is to describe their discovery and biological functions in the context of their enormous potential in the clinical diagnosis, prevention, and treatment of cancer as well as bacterial and viral infectious diseases.

Longitudinal assessment of urinary PCA3 for predicting prostate cancer grade reclassification in favorable-risk men during active surveillance

Background

To assess the utility of urinary prostate cancer antigen 3 (PCA3) as both a one-time and longitudinal measure in men on active surveillance (AS).

Methods

The Johns Hopkins AS program monitors men with favorable-risk prostate cancer with serial PSA, digital rectal examination (DRE), prostate MRI, and prostate biopsy. Since 2007, post-DRE urinary specimens have also been routinely obtained. Men with multiple PCA3 measures obtained over ≥3 years of monitoring were included. Utility of first PCA3 score (fPCA3), subsequent PCA3 (sPCA3), and change in PCA3 were assessed for prediction of Gleason grade reclassification (GR, Gleason score>6) during follow-up.

Results

In total, 260 men met study criteria. Median time from enrollment to fPCA3 was 2 years (IQR 1–3) and from fPCA3 to sPCA3 was 5 years (IQR 4–6). During median follow-up of 6 years (IQR 5–8), 28 men (11%) underwent GR. Men with GR had higher median fPCA3 (48.0vs.24.5, p=0.007) and sPCA3 (63.5vs.36.0, p=0.002) than those without GR, while longitudinal change in PCA3 did not differ by GR status (log-normalized rate 0.07vs.0.06, p=0.53). In a multivariable model including age, risk-classification, and PSA density, fPCA3 remained significantly associated with GR (log[fPCA3] odds ratio=1.77, p=0.04).

Conclusions

PCA3 scores obtained during AS were higher in men who underwent GR, but the rate of change in PCA3 over time did not differ by GR status. PCA3 was a significant predictor of GR in a multivariable model including conventional risk factors, suggesting that PCA3 provides incremental prognostic information in the AS setting.

Two-Stage Biomarker Protocols for Improving the Precision of Early Detection of Prostate Cancer

Background. New cancer biomarkers are being discovered at a rapid pace; however, these tests vary in their predictive performance characteristics, and it is unclear how best to use them. Methods. We investigated 2-stage biomarker-based screening strategies in the context of prostate cancer using a partially observable Markov model to simulate patients’ progression through prostate cancer states to mortality from prostate cancer or other causes. Patients were screened every 2 years from ages 55 to 69. If the patient’s serum prostate-specific antigen (PSA) was over a specified threshold in the first stage, a second stage biomarker test was administered. We evaluated design characteristics for these 2-stage strategies using 7 newly discovered biomarkers as examples. Monte Carlo simulation was used to estimate the number of screening biopsies, prostate cancer deaths, and quality-adjusted life-years (QALYs) per 1000 men. Results. The all-cancer biomarkers significantly underperformed the high-grade cancer biomarkers in terms of QALYs. The screening strategy that used a PSA threshold of 2 ng/mL and a second biomarker test with high-grade sensitivity and specificity of 0.86 and 0.62, respectively, maximized QALYs. This strategy resulted in a prostate cancer death rate within 1% of using PSA alone with a threshold of 2 ng/mL, while reducing the number of biopsies by 20%. Sensitivity analysis suggests that the results are robust with respect to variation in model parameters. Conclusions. Two-stage biomarker screening strategies using new biomarkers with risk thresholds optimized for high-grade cancer detection may increase quality-adjusted survival and reduce unnecessary biopsies.

Long noncoding RNAs in prostate cancer: overview and clinical implications

Prostate cancer is the second most common cause of cancer mortality among men in the United States. While many prostate cancers are indolent, an important subset of patients experiences disease recurrence after conventional therapy and progresses to castration-resistant prostate cancer (CRPC), which is currently incurable. Thus, there is a critical need to identify biomarkers that will distinguish indolent from aggressive disease, as well as novel therapeutic targets for the prevention or treatment of CRPC. In recent years, long noncoding RNAs (lncRNAs) have emerged as an important class of biological molecules. LncRNAs are polyadenylated RNA species that share many similarities with protein-coding genes despite the fact that they are noncoding (not translated into proteins). They are usually transcribed by RNA polymerase II and exhibit the same epigenetic signatures as protein-coding genes. LncRNAs have also been implicated in the development and progression of variety of cancers, including prostate cancer. While a large number of lncRNAs exhibit tissue- and cancer-specific expression, their utility as diagnostic and prognostic biomarkers is just starting to be explored. In this review, we highlight recent findings on the functional role and molecular mechanisms of lncRNAs in the progression of prostate cancer and evaluate their use as potential biomarkers and therapeutic targets.

Prostate Health Index density improves detection of clinically significant prostate cancer

OBJECTIVES

To explore the utility of Prostate Health Index (PHI) density for the detection of clinically significant prostate cancer (PCa) in a contemporary cohort of men presenting for diagnostic evaluation of PCa.

PATIENTS AND METHODS

The study cohort included patients with elevated prostate-specific antigen (PSA; >2 ng/mL) and negative digital rectal examination who underwent PHI testing and prostate biopsy at our institution in 2015. Serum markers were prospectively measured per standard clinical pathway. PHI was calculated as ([{-2}proPSA/free PSA] × [PSA]^½ ), and density calculations were performed using prostate volume as determined by transrectal ultrasonography. Logistic regression was used to assess the ability of serum markers to predict clinically significant PCa, defined as any Gleason score ≥7 cancer or Gleason score 6 cancer in >2 cores or >50% of any positive core.

RESULTS

Of 118 men with PHI testing who underwent biopsy, 47 (39.8%) were found to have clinically significant PCa on biopsy. The median (interquartile range [IQR]) PHI density was 0.70 (0.43-1.21), and was 0.53 (0.36-0.75) in men with negative biopsy or clinically insignificant PCa and 1.21 (0.74-1.88) in men with clinically significant PCa (P < 0.001). Clinically significant PCa was detected in 3.6% of men in the first quartile of PHI density (<0.43), 36.7% of men in the IQR of PHI density (0.43-1.21), and 80.0% of men with PHI density >1.21 (P < 0.001). Using a threshold of 0.43, PHI density was 97.9% sensitive and 38.0% specific for clinically significant PCa, and 100% sensitive for Gleason score ≥7 disease. Compared with PSA (area under the curve [AUC] 0.52), PSA density (AUC 0.70), %free PSA (AUC 0.75), the product of %free PSA and prostate volume (AUC 0.79), and PHI (AUC 0.76), PHI density had the highest discriminative ability for clinically significant PCa (AUC 0.84).

CONCLUSIONS

Based on the present prospective single-centre experience, PHI density could be used to avoid 38% of unnecessary biopsies, while failing to detect only 2% of clinically significant cancers.

Characterization of Protein Content Present in Exosomes Isolated from Conditioned Media and Urine

Cells secrete biomolecules into the extracellular space as a way of intercellular communication. Secreted proteins can act as ligands that engage specific receptors-on the same cell, nearby cells, or distant cells-and induce defined signaling pathways. Proteins and other biomolecules can also be packaged as cargo molecules within vesicles that are released to the extracellular space (termed extracellular vesicles or EVs). A subclass of such EVs, exosomes have been shown to horizontally transfer information. In recent years, exosomes have sparked tremendous interest in biological research, both for the discovery of novel biomarkers and for the identification of signaling molecules, as part of their cargo. Although multiple methods have been described for the isolation of exosomes, described here is a simple differential centrifugation approach that is well suited for the isolation of exosomes from conditioned cell culture media and urine. Mass spectrometry provides an ideal method to comprehensively analyze the protein cargo of exosomes. © 2017 by John Wiley & Sons, Inc.

Use of the Prostate Health Index for detection of prostate cancer: results from a large academic practice

BACKGROUND

The Prostate Health Index (phi) outperforms PSA and other PSA derivatives for the diagnosis of prostate cancer (PCa). The impact of phi testing in the real-world clinical setting has not been previously assessed.

METHODS

In a single, large, academic center, phi was tested in 345 patients presenting for diagnostic evaluation for PCa. Findings on prostate biopsy (including Grade Group [GG], defined as GG1: Gleason score [GS] 6, GG2: GS 3+4=7, GG3: GS 4+3=7, GG4: GS 8, and GG5: GS 9-10), magnetic resonance imaging (MRI), and radical prostatectomy (RP) were prospectively recorded. Biopsy rates and outcomes were compared to a contemporary cohort that did not undergo phi testing (n=1318).

RESULTS

Overall, 39% of men with phi testing underwent prostate biopsy. No men with phi<19.6 were diagnosed with PCa, and only 3 men with phi<27 had cancer of GG≥2. Phi was superior to PSA for the prediction of any PCa (AUC 0.72 vs. 0.47) and GG≥2 PCa (AUC 0.77 vs. 0.53) on prostate biopsy. Among men undergoing MRI and phi, no men with phi<27 and PI-RADS≤3 had GG≥2 cancer. For those men proceeding to RP, increasing phi was associated with higher pathologic GG (p=0.002) and stage (p=0.001). Compared to patients who did not undergo phi testing, the use of phi was associated with a 9% reduction in the rate of prostate biopsy (39% vs. 48%; p<0.001). Importantly, the reduction in biopsy among the phi population was secondary to decreased incidence of negative (8%) and GG1 (1%) biopsies, while the proportion of biopsies detecting GG≥2 cancers remained unchanged.

CONCLUSIONS

In this large, real-time clinical experience, phi outperformed PSA alone, was associated with high-grade PCa, and provided complementary information to MRI. Incorporation of phi into clinical practice reduced the rate of unnecessary biopsies without changing the frequency of detection of higher grade cancers.

Metabolomics Identifies Multiple Candidate Biomarkers to Diagnose and Stage Human African Trypanosomiasis

Treatment for human African trypanosomiasis is dependent on the species of trypanosome causing the disease and the stage of the disease (stage 1 defined by parasites being present in blood and lymphatics whilst for stage 2, parasites are found beyond the blood-brain barrier in the cerebrospinal fluid (CSF)). Currently, staging relies upon detecting the very low number of parasites or elevated white blood cell numbers in CSF. Improved staging is desirable, as is the elimination of the need for lumbar puncture. Here we use metabolomics to probe samples of CSF, plasma and urine from 40 Angolan patients infected with Trypanosoma brucei gambiense, at different disease stages. Urine samples provided no robust markers indicative of infection or stage of infection due to inherent variability in urine concentrations. Biomarkers in CSF were able to distinguish patients at stage 1 or advanced stage 2 with absolute specificity. Eleven metabolites clearly distinguished the stage in most patients and two of these (neopterin and 5-hydroxytryptophan) showed 100% specificity and sensitivity between our stage 1 and advanced stage 2 samples. Neopterin is an inflammatory biomarker previously shown in CSF of stage 2 but not stage 1 patients. 5-hydroxytryptophan is an important metabolite in the serotonin synthetic pathway, the key pathway in determining somnolence, thus offering a possible link to the eponymous symptoms of “sleeping sickness”. Plasma also yielded several biomarkers clearly indicative of the presence (87% sensitivity and 95% specificity) and stage of disease (92% sensitivity and 81% specificity). A logistic regression model including these metabolites showed clear separation of patients being either at stage 1 or advanced stage 2 or indeed diseased (both stages) versus control.

Human African trypanosomiasis, also known as sleeping sickness, is a parasitic disease that affects people in sub-Saharan Africa. There are two stages of the infection. The first stage involves parasites proliferating in the bloodstream following introduction via the bite of an infected tsetse fly. The second, more serious stage, involves parasite invasion and proliferation within the central nervous system causing characteristic disturbances to the patients’ sleep wake patterns and progressive appearance of other neurological signs, including walking disabilities behaviour changes, abnormal movements, incontinence, then ultimately coma and death. Drugs are available to treat both stages of the disease, but the drugs for stage 2 disease have serious side effects and must be administered in hospital settings. Stage determination is thus a key element for disease management. Currently staging involves microscopic evaluation of CSF following a lumbar puncture. Here, we have analysed the metabolome of CSF, blood and urine of patients to seek biomarkers to stage the disease based on these biofluids. CSF and blood fluids were found to have distinctive metabolic biomarkers and when several of these metabolites are combined, a sensitive and robust discriminatory staging test can be developed. Some CSF metabolic markers relate to brain inflammation, whilst others may be related to somnolence associated with the disease in stage 2 patients, which may also help in understanding disease progression. Interestingly, distinctive biomarkers were also found in plasma, potentially abrogating the need for diagnostic lumbar punctures in the future.

Tumour biomarkers: homeostasis as a novel prognostic indicator

The term 'personalized medicine' refers to a medical procedure that consists in the grouping of patients based on their predicted individual response to therapy or risk of disease. In oncologic patients, a 'tailored' therapeutic approach may potentially improve their survival and well-being by not only reducing the tumour, but also enhancing therapeutic response and minimizing the adverse effects. Diagnostic tests are often used to select appropriate and optimal therapies that rely both on patient genome and other molecular/cellular analysis. Several studies have shown that lifestyle and environmental factors can influence the epigenome and that epigenetic events may be involved in carcinogenesis. Thus, in addition to traditional biomarkers, epigenetic factors are raising considerable interest, because they could potentially be used as an excellent tool for cancer diagnosis and prognosis. In this review, we summarize the role of conventional cancer genetic biomarkers and their association with epigenomics. Furthermore, we will focus on the so-called 'homeostatic biomarkers' that result from the physiological response to cancer, emphasizing the concept that an altered 'new' homeostasis influence not only tumour environment, but also the whole organism.

Elevated Prostate Health Index (phi) and Biopsy Reclassification During Active Surveillance of Prostate Cancer

The Prostate Health Index (phi) has been FDA approved for decision-making regarding prostate biopsy. Phi has additionally been shown to positively correlate with tumor volume, extraprostatic disease and higher Gleason grade tumors. Here we describe a case in which an elevated phi encouraged biopsy of a gentleman undergoing active surveillance leading to reclassification of his disease as high risk prostate cancer.

Influence of age on seven putative prostate tumor markers: a cohort study in Chinese men

The accuracy and sensitivity of prostate-specific antigen (PSA) for prostate cancer diagnosis is often poor; however, the reasons for its inaccuracy have rarely been investigated, especially with respect to age. In this study, 476 healthy males, aged 10-89 years, were stratified into eight age groups, and levels of seven markers were determined: total PSA (tPSA), free PSA (fPSA), %fPSA, isoform [-2]proPSA (p2PSA), p2PSA/tPSA, %p2PSA, and the prostate health index (PHI). Both tPSA and fPSA levels increased with age. The tPSA level was highest (1.39 ng ml-1) at 70-79 years; %fPSA was highest (0.57 ng ml-1) at 10-19 years; and %p2PSA was lowest (18.33 ng ml-1) at 40-49 years. Both p2PSA and p2PSA/tPSA had relatively flat curves and showed no correlation with age (P = 0.222). PHI was a sensitive age-associated marker (P < 0.05), with two peaks and one trough. The coverage rates and radiance graphs of PHI and %p2PSA were more distinctive than those of tPSA and the other markers. In subjects older than 69 years, PHI and %p2PSA both began to decrease, approximately 10 years earlier than the decrease in tPSA. Our results suggest that the clinical diagnosis of prostate cancer using PSA should be investigated more comprehensively based on patient age. Moreover, %p2PSA and PHI could be considered as earlier markers that may be more suitable than PSA alone.