The present and future of prostate cancer urine biomarkers

Metabolomics and Proteomics in Prostate Cancer Research: Overview, Analytical Techniques, Data Analysis, and Recent Clinical Applications

Prostate cancer (PCa) is a significant global contributor to mortality, predominantly affecting males aged 65 and above. The field of omics has recently gained traction due to its capacity to provide profound insights into the biochemical mechanisms underlying conditions like prostate cancer. This involves the identification and quantification of low-molecular-weight metabolites and proteins acting as crucial biochemical signals for early detection, therapy assessment, and target identification. A spectrum of analytical methods is employed to discern and measure these molecules, revealing their altered biological pathways within diseased contexts. Metabolomics and proteomics generate refined data subjected to detailed statistical analysis through sophisticated software, yielding substantive insights. This review aims to underscore the major contributions of multi-omics to PCa research, covering its core principles, its role in tumor biology characterization, biomarker discovery, prognostic studies, various analytical technologies such as mass spectrometry and Nuclear Magnetic Resonance, data processing, and recent clinical applications made possible by an integrative "omics" approach. This approach seeks to address the challenges associated with current PCa treatments. Hence, our research endeavors to demonstrate the valuable applications of these potent tools in investigations, offering significant potential for understanding the complex biochemical environment of prostate cancer and advancing tailored therapeutic approaches for further development.

Early Detection of Prostate Cancer: The Role of Scent

Prostate cancer (PCa) represents the cause of the second highest number of cancer-related deaths worldwide, and its clinical presentation can range from slow-growing to rapidly spreading metastatic disease. As the characteristics of most cases of PCa remains incompletely understood, it is crucial to identify new biomarkers that can aid in early detection. Despite the prostate-specific antigen serum (PSA) levels, prostate biopsy, and imaging representing the actual gold-standard for diagnosing PCa, analyzing volatile organic compounds (VOCs) has emerged as a promising new frontier. We and other authors have reported that highly trained dogs can recognize specific VOCs associated with PCa with high accuracy. However, using dogs in clinical practice has several limitations. To exploit the potential of VOCs, an electronic nose (eNose) that mimics the dog olfactory system and can potentially be used in clinical practice was designed. To explore the eNose as an alternative to dogs in diagnosing PCa, we conducted a systematic literature review and meta-analysis of available studies. PRISMA guidelines were used for the identification, screening, eligibility, and selection process. We included six studies that employed trained dogs and found that the pooled diagnostic sensitivity was 0.87 (95% CI 0.86–0.89; I2, 98.6%), the diagnostic specificity was 0.83 (95% CI 0.80–0.85; I2, 98.1%), and the area under the summary receiver operating characteristic curve (sROC) was 0.64 (standard error, 0.25). We also analyzed five studies that used an eNose to diagnose PCa and found that the pooled diagnostic sensitivity was 0.84 (95% CI, 0.80–0.88; I2, 57.1%), the diagnostic specificity was 0.88 (95% CI, 0.84–0.91; I2, 66%), and the area under the sROC was 0.93 (standard error, 0.03). These pooled results suggest that while highly trained dogs have the potentiality to diagnose PCa, the ability is primarily related to olfactory physiology and training methodology. The adoption of advanced analytical techniques, such as eNose, poses a significant challenge in the field of clinical practice due to their growing effectiveness. Nevertheless, the presence of limitations and the requirement for meticulous study design continue to present challenges when employing eNoses for the diagnosis of PCa.

Potential Diagnostic Biomarker Detection for Prostate Cancer Using Untargeted and Targeted Metabolomic Profiling

Prostate cancer (PCa) remains one of the leading causes of cancer mortality in men worldwide, currently lacking specific, early detection and staging biomarkers. In this regard, modern research focuses efforts on the discovery of novel molecules that could represent potential future non-invasive biomarkers for the diagnosis of PCa, as well as therapeutic targets. Mounting evidence shows that cancer cells express an altered metabolism in their early stages, making metabolomics a promising tool for the discovery of altered pathways and potential biomarker molecules. In this study, we first performed untargeted metabolomic profiling on 48 PCa plasma samples and 23 healthy controls using ultra-high-performance liquid chromatography coupled with electrospray ionization quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-[ESI+]-MS) for the discovery of metabolites with altered profiles. Secondly, we selected five molecules (L-proline, L-tryptophan, acetylcarnitine, lysophosphatidylcholine C18:2 and spermine) for the downstream targeted metabolomics and found out that all the molecules, regardless of the PCa stage, were decreased in the PCa plasma samples when compared to the controls, making them potential biomarkers for PCa detection. Moreover, spermine, acetylcarnitine and L-tryptophan had very high diagnostic accuracy, with AUC values of 0.992, 0.923 and 0.981, respectively. Consistent with other literature findings, these altered metabolites could represent future specific and non-invasive candidate biomarkers for PCa detection, which opens novel horizons in the field of metabolomics.

Research of Prostate Cancer Urinary Diagnostic Biomarkers by Proteomics: The Noteworthy Influence of Inflammation

Nowadays, in the case of suspected prostate cancer (PCa), tissue needle biopsy remains the benchmark for diagnosis despite its invasiveness and poor tolerability, as serum prostate-specific antigen (PSA) is limited by low specificity. The aim of this proteomic study was to identify new diagnostic biomarkers in urine, an easily and non-invasively available sample, able to selectively discriminate cancer from benign prostatic hyperplasia (BPH), evaluating whether the presence of inflammation may be a confounding parameter. The analysis was performed by two-dimensional gel electrophoresis (2-DE), mass spectrometry (LC-MS/MS) and Enzyme-Linked Immunosorbent Assay (ELISA) on urine samples from PCa and BPH patients, divided into subgroups based on the presence or absence of inflammation. Significant quantitative and qualitative differences were found in the urinary proteomic profile of PCa and BPH groups. Of the nine differentially expressed proteins, only five can properly be considered potential biomarkers of PCa able to discriminate the two diseases, as they were not affected by the inflammatory process. Therefore, the proteomic research of novel and reliable urinary biomarkers of PCa should be conducted considering the presence of inflammation as a realistic interfering element, as it could hinder the detection of important protein targets.

Circulating metabolite biomarkers: a game changer in the human prostate cancer diagnosis

PURPOSE

Prostate cancer (PCa) is the second most commonly diagnosed cancer in men in Western and Asian countries. Serum prostate-specific antigen (PSA) test has been the routine diagnostic method despite the tremendous research in diagnostic markers for early detection of PCa. A shift towards a promising and potential biomarker for PCa detection is through metabolomic profiling of biofluids, particularly the blood and urine samples. Finding reliable, routinely usable circulating metabolite biomarkers may not be a distant reality.

METHODS

We performed a PubMed-based literature search of metabolite biomarkers in blood and urine for the early detection of prostate cancer. The timeline of these searches was limited between 2007 and 2022 and the following keywords were used: 'metabolomics', 'liquid biopsy', 'circulating metabolites', 'serum metabolite', 'plasma metabolite', and 'urine metabolite' with respect to 'prostate cancer'. We focussed only on diagnosis-based studies with only the subject-relevant articles published in the English language and excluded all of the other irrelevant publications that included prostate tissue biomarkers and cell line biomarkers.

RESULTS

We have consolidated all the blood and urine-based potential metabolite candidates in individual as well as panels, including lipid classes, fatty acids, amino acids, and volatile organic compounds which may become useful for PCa diagnosis.

CONCLUSION

All these metabolome findings unveil the impact of different dimensions of PCa development, giving a promising strategy to diagnose the disease since suspected individuals can be subjected to repeated and largescale blood and urine testing.

Underlying Features of Prostate Cancer-Statistics, Risk Factors, and Emerging Methods for Its Diagnosis

Prostate cancer (PCa) is the most frequently occurring type of malignant tumor and a leading cause of oncological death in men. PCa is very heterogeneous in terms of grade, phenotypes, and genetics, displaying complex features. This tumor often has indolent growth, not compromising the patient's quality of life, while its more aggressive forms can manifest rapid growth with progression to adjacent organs and spread to lymph nodes and bones. Nevertheless, the overtreatment of PCa patients leads to important physical, mental, and economic burdens, which can be avoided with careful monitoring. Early detection, even in the cases of locally advanced and metastatic tumors, provides a higher chance of cure, and patients can thus go through less aggressive treatments with fewer side effects. Furthermore, it is important to offer knowledge about how modifiable risk factors can be an effective method for reducing cancer risk. Innovations in PCa diagnostics and therapy are still required to overcome some of the limitations of the current screening techniques, in terms of specificity and sensitivity. In this context, this review provides a brief overview of PCa statistics, reporting its incidence and mortality rates worldwide, risk factors, and emerging screening strategies.

Locus-Specific Bisulfate NGS Sequencing of GSTP1, RNF219, and KIAA1539 Genes in the Total Pool of Cell-Free and Cell-Surface-Bound DNA in Prostate Cancer: A Novel Approach for Prostate Cancer Diagnostics

The locus-specific methylation of three genes (GSTP1, RNF219, and KIAA1539, also known as FAM214B) in the total pool of blood cell-free DNA, including cell-free DNA from plasma and cell-surface-bound DNA, of patients with prostate cancer and healthy donors was studied on the MiSeq platform. Our study found a higher methylation index of loci for total cell-free DNA compared with cell-free DNA. For total cell-free DNA, the methylation of GSTP1 in each of the 11 positions provided a complete separation of cancer patients from healthy donors, whereas for cell-free DNA, there were no positions in the three genes allowing for such separation. Among the prostate cancer patients, the minimum proportion of GSTP1 genes methylated in any of the 17 positions was 12.1% of the total circulated DNA fragments, and the minimum proportion of GSTP1 genes methylated in any of the 11 diagnostically specific positions was 8.4%. Total cell-free DNA was shown to be more convenient and informative as a source of methylated DNA molecules circulating in the blood than cell-free DNA.

On an Affordable Approach towards the Diagnosis and Care for Prostate Cancer Patients Using Urine, FTIR and Prediction Machines

Prostate cancer is a widespread form of cancer that affects patients globally and is challenging to diagnose, especially in its early stages. The common means of diagnosing cancer involve mostly invasive methods, such as the use of patient’s blood as well as digital biopsies, which are relatively expensive and require a considerable amount of expertise. Studies have shown that various cancer biomarkers can be present in urine samples from patients who have prostate cancers; this paper aimed to leverage this information and investigate this further by using urine samples from a group of patients alongside FTIR analysis for the prediction of prostate cancer. This investigation was carried out using three sets of data where all spectra were preprocessed with the linear series decomposition learner (LSDL) and post-processed using signal processing methods alongside a contrast across nine machine-learning models, the results of which showcased that the proposed modeling approach carries potential to be used for clinical prediction of prostate cancer. This would allow for a much more affordable and high-throughput means for active prediction and associated care for patients with prostate cancer. Further investigations on the prediction of cancer stage (i.e., early or late stage) were carried out, where high prediction accuracy was obtained across the various metrics that were investigated, further showing the promise and capability of urine sample analysis alongside the proposed and presented modeling approaches.

Delineating the role of extracellular vesicles in cancer metastasis: A comprehensive review

Extracellular vesicles (EVs) are subcellular messengers that aid in the formation and spread of cancer by enabling tumor-stroma communication. EVs develop from the very porous structure of late endosomes and hold information on both the intrinsic “status” of the cell and the extracellular signals absorbed by the cells from their surroundings. These EVs contain physiologically useful components, including as nucleic acids, lipids, and proteins, which have been found to activate important signaling pathways in tumor and tumor microenvironment (TME) cells, aggravating tumor growth. We highlight critical cell biology mechanisms that link EVS formation to cargo sorting in cancer cells in this review.Sorting out the signals that control EVs creation, cargo, and delivery will aid our understanding of carcinogenesis. Furthermore, we reviewed how cancer development and spreading behaviors are affected by coordinated communication between malignant and non-malignant cells. Herein, we studied the reciprocal exchanges via EVs in various cancer types. Further research into the pathophysiological functions of various EVs in tumor growth is likely to lead to the discovery of new biomarkers in liquid biopsy and the development of tumor-specific therapies.

Blood-based liquid biopsies for prostate cancer: clinical opportunities and challenges

Liquid biopsy has been established as a powerful, minimally invasive, tool to detect clinically actionable aberrations across numerous cancer types in real-time. With the development of new therapeutic agents in prostate cancer (PC) including DNA repair targeted therapies, this is especially attractive. However, there is unclarity on how best to screen for PC, improve risk stratification and ultimately how to treat advanced disease. Therefore, there is an urgent need to develop better biomarkers to help guide oncologists' decisions in these settings. Circulating tumour cells (CTCs), exosomes and cell-free DNA/RNA (cfDNA/cfRNA) analysis, including epigenetic features such as methylation, have all shown potential in prognostication, treatment response assessment and detection of emerging mechanisms of resistance. However, there are still challenges to overcome prior to implementing liquid biopsies in routine clinical practice such as preanalytical considerations including blood collection and storage, the cost of CTC isolation and enrichment, low-circulating tumour content as a limitation for genomic analysis and how to better interpret the sequencing data generated. In this review, we describe an overview of the up-to-date clinical opportunities in the management of PC through blood-based liquid biopsies and the next steps for its implementation in personalised treatment guidance.

A novel platform using homobifunctional hydrazide for enrichment and isolation of urinary circulating RNAs

Changes in specific circulating RNA (circRNA) expressions can serve as diagnostic noninvasive biomarkers for prostate cancer (PCa). However, there are still unmet needs, such as unclear types and roles of circRNAs, PCa detection in benign prostatic hyperplasia (BPH) by unstandardized methods, and limitations of sample volume capacity and low circRNA concentrations. This study reports a simple and rapid circRNA enrichment and isolation technique named "HAZIS-CirR" for the analysis of urinary circRNAs. The method utilizes homobifunctional hydrazides with amine-modified zeolite and polyvinylidene fluoride (PVDF) syringe filtration for combining electrostatic and covalent coupling and size-based filtration, and it offers instrument-free isolation of circRNAs in 20 min without volume limitation, thermoregulation, and lysis. HAZIS-CirR has high capture efficiency (82.03%-92.38%) and a 10-fold more sensitive detection limit (20 fM) than before enrichment (200 fM). The clinical utility of HAZIS-CirR is confirmed by analyzing circulating mRNAs and circulating miRNAs in 89 urine samples. Furthermore, three miRNA panels that differentiate PCa from BPH and control, PCa from control, and BPH from control, respectively, are established by comparing miRNA levels. HAZIS-CirR will be used as an optimal and established method for the enrichment and isolation of circRNAs as diagnostic, prognostic, and predictive biomarkers in human cancers.

Fibromodulin Gene Variants (FMOD) as Potential Biomarkers for Prostate Cancer and Benign Prostatic Hyperplasia

By the year 2050, the world's elderly population may increase exponentially, raising the rate of disease characteristic of this group, such as prostate cancer (PCa) and benign prostatic hyperplasia (BPH). Prostate disorders have a multifactorial etiology, especially age and genetic factors. Currently, PCa is the second most frequent neoplasm in the male population worldwide. The fibromodulin gene encodes a small leucine-rich proteoglycan (SLRP) which acts in the collagen fibrillogenesis pathway, cell adhesion, and modulation of TGF-β signaling pathways, which has been recently associated with PCa. The present study sequenced the coding region of the FMOD in a sample of 44 PCa, 90 BPH, and 82 controls from a Brazilian population, and the results identified 6 variants: 2 missenses (p.(Tyr42Ser) and p.(Pro24Ala)); 3 synonymous (p.(His253=), p.(Asn353=), and p.(Glu79=)); and 1 intronic (c.980-114A>G). Of these, p.(Tyr42Ser), p.(Pro24Ala), and p.(Asn353=) are rare variants, and p.(Tyr42Ser) was predicted as potential pathogenic by the algorithms used here, in addition to not being observed in controls, suggesting that may be a potential biomarker for development of PCa and BPH. In conclusion, we identified for the first time, in Brazilian individuals with PCa and BPH, a potentially pathogenic variant in the analysis of FMOD gene. Further studies are needed to investigate the deleterious effect of this variant on the structure and/or function of the FMOD protein.

Correlation between stage of prostate cancer and tyrosine and tryptophan in urine samples measured electrochemically

Prostate cancer (PCa) is the second most common cancer in men and one of the leading causes of cancer-related deaths. Early detection is the key to successful treatment and provides the greatest chance to cure the patient. Currently, early detection involves screening for prostate-specific antigen levels in blood, which is not a tumor-specific biomarker. There is a critical need to develop clinically useful methods for screening for more reliable biomarkers. Here, we introduce an electrochemical biosensor that measures the concentrations of the amino acids tyrosine and tryptophan, and propose it as a possible diagnostic and prognostic tool for PCa. The limits of detection of tyrosine and tryptophan using the electrochemical sensors were 1.15 and 1.13 μmol/L in 1:10 urine: PBS, respectively. This study is the first to present electrochemical measurements of tyrosine and tryptophan directly in patient urine samples. We demonstrated an inverse correlation between the measured electrochemical signals and the severity of PCa. The most notable observation was a significant difference between controls and metastatic PCa patients (P ≤ 0.001). This observation was further validated using Liquid-Chromatography-Mass Spectrometry. Our data provides the basis for further research with electrochemical measurements of tyrosine and tryptophan as potential biomarkers for PCa.

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.

Locus-Specific Methylation of GSTP1, RNF219, and KIAA1539 Genes with Single Molecule Resolution in Cell-Free DNA from Healthy Donors and Prostate Tumor Patients: Application in Diagnostics

Simple Summary

Prostate cancer (PCa) is the second most commonly diagnosed cancer in men, which is constantly accompanied by benign prostate hyperplasia (BPH). To reach a 100% 5-year survival rate in PCa, which is characteristic for PCa if it is diagnosed in early stages, efficient PCa diagnostics against the background of BPH are demanded. The article describes a liquid biopsy approach to differential PCa diagnostics based on the data on locus-specific methylation of the three genes (GSTP1, RNF219, and KIAA1539) obtained with NGS of cell-free DNA from blood plasma of PCa, BPH, and healthy individuals. We offered a diagnostic approach including the analysis of simultaneous methylation status of two CpGs in one cell-free DNA molecule, allowing the discrimination of all patients with absolute sensitivity and specificity.

Abstract

The locus-specific methylation of three genes (GSTP1, RNF219, and KIAA1539 (also known as FAM214B)) in the blood plasma cell-free DNA (cfDNA) of 20 patients with prostate cancer (PCa), 18 healthy donors (HDs), and 17 patients with benign prostatic hyperplasia (BPH) was studied via the MiSeq platform. The methylation status of two CpGs within the same loci were used as the diagnostic feature for discriminating the patient groups. Many variables had good diagnostic characteristics, e.g., each of the variables GSTP1.C3.C9, GSTP1.C9, and GSTP1.C9.T17 demonstrated an 80% sensitivity at a 100% specificity for PCa patients vs. the others comparison. The analysis of RNF219 gene loci methylation allowed discriminating BPH patients with absolute sensitivity and specificity. The data on the methylation of the genes GSTP1 and RNF219 allowed discriminating PCa patients, as well as HDs, with absolute sensitivity and specificity. Thus, the data on the locus-specific methylation of cfDNA (with single-molecule resolution) combined with a diagnostic approach considering the simultaneous methylation of several CpGs in one locus enabled the discrimination of HD, BPH, and PCa patients.

Metabolomics Profiling Discriminates Prostate Cancer From Benign Prostatic Hyperplasia Within the Prostate-Specific Antigen Gray Zone

Objective

Prostate cancer (PCa) is the second most common male malignancy globally. Prostate-specific antigen (PSA) is an important biomarker for PCa diagnosis. However, it is not accurate in the diagnostic gray zone of 4–10 ng/ml of PSA. In the current study, the performance of serum metabolomics profiling in discriminating PCa patients from benign prostatic hyperplasia (BPH) individuals with a PSA concentration in the range of 4–10 ng/ml was explored.

Methods

A total of 220 individuals, including patients diagnosed with PCa and BPH within PSA levels in the range of 4–10 ng/ml and healthy controls, were enrolled in the study. Liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS)-based non-targeted metabolomics method was utilized to characterize serum metabolic profiles of participants. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) methods were used for multivariate analysis. Receiver operating characteristic (ROC) curve analysis was performed to explore the diagnostic value of candidate metabolites in differentiating PCa from BPH. Correlation analysis was conducted to explore the relationship between serum metabolites and common clinically used fasting lipid profiles.

Results

Several differential metabolites were identified. The top enriched pathways in PCa subjects such as glycerophospholipid and glycerolipid metabolisms were associated with lipid metabolism. Lipids and lipid-like compounds were the predominant metabolites within the top 50 differential metabolites selected using fold-change threshold >1.5 or <2/3, variable importance in projection (VIP) > 1, and Student’s t-test threshold p < 0.05. Eighteen lipid or lipid-related metabolites were selected including 4-oxoretinol, anandamide, palmitic acid, glycerol 1-hexadecanoate, dl-dihydrosphingosine, 2-methoxy-6Z-hexadecenoic acid, 3-oxo-nonadecanoic acid, 2-hydroxy-nonadecanoic acid, N-palmitoyl glycine, 2-palmitoylglycerol, hexadecenal, d-erythro-sphingosine C-15, N-methyl arachidonoyl amine, 9-octadecenal, hexadecyl acetyl glycerol, 1-(9Z-pentadecenoyl)-2-eicosanoyl-glycero-3-phosphate, 3Z,6Z,9Z-octadecatriene, and glycidyl stearate. Selected metabolites effectively discriminated PCa from BPH when PSA levels were in the range of 4–10 ng/ml (area under the curve (AUC) > 0.80). Notably, the 18 identified metabolites were negatively corrected with total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), and Apo-B levels in PCa patients; and some were negatively correlated with high-density lipoprotein cholesterol (HDL-C) and Apo-A levels. However, the metabolites were not correlated with triglycerides (TG).

Conclusion

The findings of the present study indicate that metabolic reprogramming, mainly lipid metabolism, is a key signature of PCa. The 18 lipid or lipid-associated metabolites identified in this study are potential diagnostic markers for differential diagnosis of PCa patients and BPH individuals within a PSA level in the gray zone of 4–10 ng/ml.

JPX and LINC00641 ncRNAs expression in prostate tissue: a case-control study

Background and purpose

Prostate cancer (PC) is the second most prevalent cancer in men. Prostate-specific antigen (PSA) is the main biomarker for screening PC. An increase in PSA could lead to false-positive results. Thus, more appropriate markers should be investigated. In the present study, JPX and LINC00641 expression levels were measured in tumoral prostate tissue compared with the non-tumor tissue.

Experimental approach

43 pairs of prostate tumoral and non-tumor tissue were prepared. The expression levels of JPX and LINC00641 were investigated by RT-qPCR.

Findings/Results

Significant upregulation of LINC00641 (2.47 ± 0.5 vs 1.41 ± 0.2) and downregulation of JPX (1.42 ± 0.6 vs 2.83 ± 1.0) were observed in PC tissues compared with the normal tissues (their adjacent non-tumoral tissues).

Conclusion and implications

Dysregulation of JPX and LINC00641 in PC patients could be used in the future as a prognostic biomarker in PC.

Multiplexed Prostate Cancer Companion Diagnostic Devices

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

Prostate Cancer Biomarkers: From diagnosis to prognosis and precision-guided therapeutics

Prostate cancer (PCa) is one of the most commonly diagnosed malignancies and among the leading causes of cancer-related death worldwide. It is a highly heterogeneous disease, ranging from remarkably slow progression or inertia to highly aggressive and fatal disease. As therapeutic decision-making, clinical trial design and outcome highly depend on the appropriate stratification of patients to risk groups, it is imperative to differentiate between benign versus more aggressive states. The incorporation of clinically valuable prognostic and predictive biomarkers is also potentially amenable in this process, in the timely prevention of metastatic disease and in the decision for therapy selection. This review summarizes the progress that has so far been made in the identification of the genomic events that can be used for the classification, prediction and prognostication of PCa, and as major targets for clinical intervention. We include an extensive list of emerging biomarkers for which there is enough preclinical evidence to suggest that they may constitute crucial targets for achieving significant advances in the management of the disease. Finally, we highlight the main challenges that are associated with the identification of clinically significant PCa biomarkers and recommend possible ways to overcome such limitations.

Urinary extracellular vesicles: A position paper by the Urine Task Force of the International Society for Extracellular Vesicles

Urine is commonly used for clinical diagnosis and biomedical research. The discovery of extracellular vesicles (EV) in urine opened a new fast-growing scientific field. In the last decade urinary extracellular vesicles (uEVs) were shown to mirror molecular processes as well as physiological and pathological conditions in kidney, urothelial and prostate tissue. Therefore, several methods to isolate and characterize uEVs have been developed. However, methodological aspects of EV separation and analysis, including normalization of results, need further optimization and standardization to foster scientific advances in uEV research and a subsequent successful translation into clinical practice. This position paper is written by the Urine Task Force of the Rigor and Standardization Subcommittee of ISEV consisting of nephrologists, urologists, cardiologists and biologists with active experience in uEV research. Our aim is to present the state of the art and identify challenges and gaps in current uEV-based analyses for clinical applications. Finally, recommendations for improved rigor, reproducibility and interoperability in uEV research are provided in order to facilitate advances in the field.

Blood-Derived Biomarkers of Diagnosis, Prognosis and Therapy Response in Prostate Cancer Patients

Prostate cancer is among the most frequent cancers in men worldwide. Despite the fact that multiple therapeutic alternatives are available for its treatment, it is often discovered in an advanced stage as a metastatic disease. Prostate cancer screening is based on physical examination of prostate size and prostate-specific antigen (PSA) level in the blood as well as biopsy in suspect cases. However, these markers often fail to correctly identify the presence of cancer, or their positivity might lead to overdiagnosis and consequent overtreatment of an otherwise silent non-progressing disease. Moreover, these markers have very limited if any predictive value regarding therapy response or individual risk for therapy-related toxicities. Therefore, novel, optimally liquid biopsy-based (blood-derived) markers or marker panels are needed, which have better prognostic and predictive value than the ones currently used in the everyday routine. In this review the role of circulating tumour cells, extracellular vesicles and their microRNA content, as well as cellular and soluble immunological and inflammation- related blood markers for prostate cancer diagnosis, prognosis and prediction of therapy response is discussed. A special emphasis is placed on markers predicting response to radiotherapy and radiotherapy-related late side effects.

Advances and Perspectives in Prostate Cancer Biomarker Discovery in the Last 5 Years through Tissue and Urine Metabolomics

Prostate cancer (PCa) is the second most diagnosed cancer in men worldwide. For its screening, serum prostate specific antigen (PSA) test has been largely performed over the past decade, despite its lack of accuracy and inability to distinguish indolent from aggressive disease. Metabolomics has been widely applied in cancer biomarker discovery due to the well-known metabolic reprogramming characteristic of cancer cells. Most of the metabolomic studies have reported alterations in urine of PCa patients due its noninvasive collection, but the analysis of prostate tissue metabolome is an ideal approach to disclose specific modifications in PCa development. This review aims to summarize and discuss the most recent findings from tissue and urine metabolomic studies applied to PCa biomarker discovery. Eighteen metabolites were found consistently altered in PCa tissue among different studies, including alanine, arginine, uracil, glutamate, fumarate, and citrate. Urine metabolomic studies also showed consistency in the dysregulation of 15 metabolites and, interestingly, alterations in the levels of valine, taurine, leucine and citrate were found in common between urine and tissue studies. These findings unveil that the impact of PCa development in human metabolome may offer a promising strategy to find novel biomarkers for PCa diagnosis.

The role of the voltage-gated potassium channel, Kv2.1 in prostate cancer cell migration

Voltage-gated potassium (Kv) channels are involved in many important cellular functions and play pivotal roles in cancer progression. The expression level of Kv2.1 was observed to be higher in the highly metastatic prostate cancer cells (PC-3), specifically in their membrane, than in immortalized prostate cells (WPMY-1 cells) and comparatively less metastatic prostate cancer cells (LNCaP and DU145 cells). However, Kv2.1 expression was significantly decreased when the cells were treated with anti-oxidants, such as N-acetylcysteine or ascorbic acid, implying that the highly expressed Kv2.1 could detect reactive oxygen species (ROS) in malignant prostate cancer cells. In addition, the blockade of Kv2.1 with stromatoxin-1 or siRNA targeting Kv2.1 significantly inhibited the migration of malignant prostate cancer cells. Our results suggested that Kv2.1 plays an important role as a ROS sensor and that it is a promising therapeutic molecular target in metastasis of prostate cancer.

Novel Metabolic Signatures of Prostate Cancer Revealed by 1H-NMR Metabolomics of Urine

Prostate cancer (PC) is one of the most common male cancers worldwide. Until now, there is no consensus about using urinary metabolomic profiling as novel biomarkers to identify PC. In this study, urine samples from 50 PC patients and 50 non-cancerous individuals (control group) were collected. Based on 1H nuclear magnetic resonance (1H-NMR) analysis, 20 metabolites were identified. Subsequently, principal component analysis (PCA), partial least squares-differential analysis (PLS-DA) and ortho-PLS-DA (OPLS-DA) were applied to find metabolites to distinguish PC from the control group. Furthermore, Wilcoxon test was used to find significant differences between the two groups in metabolite urine levels. Guanidinoacetate, phenylacetylglycine, and glycine were significantly increased in PC, while L-lactate and L-alanine were significantly decreased. The receiver operating characteristics (ROC) analysis revealed that the combination of guanidinoacetate, phenylacetylglycine, and glycine was able to accurately differentiate 77% of the PC patients with sensitivity = 80% and a specificity = 64%. In addition, those three metabolites showed significant differences in patients stratified for Gleason score 6 and Gleason score ≥7, indicating potential use to detect significant prostate cancer. Pathway enrichment analysis using the KEGG (Kyoto Encyclopedia of Genes and Genomes) and the SMPDB (The Small Molecule Pathway Database) revealed potential involvement of KEGG "Glycine, Serine, and Threonine metabolism" in PC. The present study highlights that guanidinoacetate, phenylacetylglycine, and glycine are potential candidate biomarkers of PC. To the best knowledge of the authors, this is the first study identifying guanidinoacetate, and phenylacetylglycine as potential novel biomarkers in PC.

A novel urinary mRNA signature using the droplet digital polymerase chain reaction platform improves discrimination between prostate cancer and benign prostatic hyperplasia within the prostate-specific antigen gray zone

Purpose

The aim of this study was to identify a noninvasive urinary marker for prostate cancer (PCa) diagnosis and to validate the clinical performance of this novel urinary mRNA signature using the droplet digital polymerase chain reaction (ddPCR) approach.

Materials and Methods

A gene expression microarray (HT-12, Illumina Inc., USA) was used to identify genes differentially expressed between 16 PCa and 8 benign prostatic hyperplasia (BPH) tissues; ddPCR (QX200; Bio-Rad Laboratories, USA) was carried out to quantify the expression of selected genes in urine. The urinary molecular PCa risk score (UMPCaRS) was calculated by using the sum of three upregulated genes as the numerator and the sum of three downregulated genes as the denominator. The diagnostic utility of the UMPCaRS was validated by using a screening set (10 PCa and 10 BPH samples) and a validation set (131 PCa and 105 BPH samples).

Results

Three upregulated genes (PDLIM5, GDF-15, THBS4) and three downregulated genes (UPK1A, SSTR3, NPFFR2) were selected from the microarray and subjected to ddPCR. The UMPCaRS for PCa in the screening and validation sets was significantly higher than that for BPH. For the validation set, the diagnostic accuracy of the UMPCaRS was comparable with that of prostate-specific antigen (PSA). Importantly, in the "PSA gray zone" (3-10 ng/mL), the AUC for the UMPCaRS was 0.843 and that for PSA was 0.628 (p<0.001).

Conclusions

The data demonstrate that the UMPCaRS is useful for discriminating between PCa and BPH in the "PSA gray zone".

The auxiliary diagnostic value of prostate-specific antigen and α-methylacyl-CoA racemase in prostate cancer

Prostate cancer (PCa) is one of the most common types of malignant tumor, which places a major burden on the health of men, worldwide. A prerequisite to ensure good treatment outcomes for patients with PCa is an accurate diagnosis. The present study aimed to investigate the diagnostic value of prostate-specific antigen (PSA) and α-methylacyl-CoA racemase (P504S) in PCa, using the tumor-associated immunolabels. In total, clinical data was collected from 125 patients undergoing prostate biopsy or surgery between January 2015 and September 2019, and stratified into: PCa (45), benign prostatic hyperplasia (BPH) (60) and unconfirmed diagnosis (20). Immunohistochemistry analysis was performed to assess PSA and P504S expression levels in each group compared with that in the controls (the normal tissue in each group was the internal control). The results demonstrated that the expression level of P504S was significantly higher in the PCa group compared with that in the BPH group. Furthermore, no significant association was observed in the PCa group between PSA and P504S expression levels, and the Gleason grading groups. A total of 20 unconfirmed diagnoses was verified via PSA/P504S. Taken together, the results suggest that combination PSA and P504S have a positive effect in identifying prostate cancer. However, PSA and P504S still have limitations in their diagnosis and the final results need to be carefully and comprehensively analyzed, thus further studies are required to determine their diagnostic values.

Exosomal microRNAs as liquid biopsy biomarkers in prostate cancer

Prostate cancer (PCa) is the most commonly diagnosed solid-organ cancer in males. The PSA testing may cause overdiagnosis and overtreatment for PCa patients. There is an urgent need for new biomarkers with greater discriminative precision for diagnosis and risk-stratification, to select for prostate biopsy and treatment of PCa. Liquid biopsy is a promising field with the potential to provide comprehensive information on the genetic landscape at diagnosis and to track genomic evolution over time in order to tailor the therapeutic choices at all stages of PCa. Exosomes, containing RNAs, DNAs and proteins, have been shown to be involved in tumour progression and a rich potential source of tumour biomarkers, especially for profiling analysis of their miRNAs content. In this review, we summarise the exosomal miRNAs in PCa diagnosis, prognosis and management, and further discuss their possible technical challenges associated with isolating PCa-specific exosomes.

Review and Comparison of Cancer Biomarker Trends in Urine as a Basis for New Diagnostic Pathways

Cancer is one of the major causes of mortality worldwide and its already large burden is projected to increase significantly in the near future with a predicted 22 million new cancer cases and 13 million cancer-related deaths occurring annually by 2030. Unfortunately, current procedures for diagnosis are characterized by low diagnostic accuracies. Given the proved correlation between cancer presence and alterations of biological fluid composition, many researchers suggested their characterization to improve cancer detection at early stages. This paper reviews the information that can be found in the scientific literature, regarding the correlation of different cancer forms with the presence of specific metabolites in human urine, in a schematic and easily interpretable form, because of the huge amount of relevant literature. The originality of this paper relies on the attempt to point out the odor properties of such metabolites, and thus to highlight the correlation between urine odor alterations and cancer presence, which is proven by recent literature suggesting the analysis of urine odor for diagnostic purposes. This investigation aims to evaluate the possibility to compare the results of studies based on different approaches to be able in the future to identify those compounds responsible for urine odor alteration.

Ultrasensitive and Reversible Nanoplatform of Urinary Exosomes for Prostate Cancer Diagnosis

Prostate cancer cell-derived exosomes in urine have been extensively studied recently and regarded as novel biomarkers for cancer diagnosis and prognosis, which presents wide prospects in clinical applications. Sensitive detection and specific capture methods are essential for exosomes analysis. Herein, a dual functional platform composed of superparamagnetic conjunctions and molecular beacons (SMC-MB) is reported. The SMC-MB platform is designed based on aptamer immunoaffinity with ultrasensitive detection efficiency and reversible isolation capacity, which, respectively, profit from nonenzymatic amplification methods and magnetic separation along with restriction cleavage. It is noteworthy that exosomes quantification was exactly amplified and transformed into single strand DNA detection. Correlated measurements evidence that the limit of detection of SMC-MB is as low as ∼100 particles/μL in urine, and a linear relationship meets between the logarithmic concentration of exosomes and fluorescence intensity of the molecular beacon. Furthermore, employing prostate specific membrane antigen (PSMA) aptamer, the platform adapted to detect and capture PMSA-positive exosomes from urine samples provides excellent diagnostic efficiency for prostate cancer (PCa). The expression of typical biomarkers of PCa, i.e., PSA and PCA3 mRNA, is significantly higher in PSMA-positive exosomes. Altogether, the platform and strategy described in this paper are promising in urinary exosomes analysis and prostate cancer detection.

Epigenetic analysis identifies factors driving racial disparity in prostate cancer

BACKGROUND

Prostate cancer (PCa) is the second most leading cause of death in men worldwide. African-American men (AA) represent more aggressive form of the disease compared to Caucasian (CA) counterparts. Several lines of evidences suggest that biological factors are responsible for the observed racial disparity.

AIM

This study was aimed at identifying the epigenetic variation among AA and CA PCa patients and whether DNA methylation differences have an association with clinical outcomes in the two races.

METHODS AND RESULTS

The cancer genome atlas (TCGA) dataset (2015) was used to identify existing epigenetic variation in AA and CA PCa patients. Reduced Representation Bisulfite Sequencing (RRBS) was performed to identify global DNA methylation changes in a small cohort of AA and CA PCa patients. The RRBS data were then used to identify survival and recurrence outcomes in AA and CA PCa patients using publicly available datasets. The TCGA data analysis revealed epigenetic heterogeneity, which could be categorized into four classes. AA associated primarily to methylation cluster 1 (p = 0.048), and CA associated to methylation cluster 3 (p = 0.000146). Enrichment of the Wnt signaling pathway was identified in both the races; however, they were differentially activated in terms of canonical and non-canonical Wnt signaling. This was further validated using the Decipher Genomics Resource Information Database (GRID). The RRBS data also identified discrete methylation patterns in AA compared with CA and, in part, validated our TCGA findings. Survival analysis using the RRBS data suggested hypomethylated genes to be significantly associated with recurrence of PCa in CA (p = 6.07 × 10-6) as well as in AA (p = 0.0077).

CONCLUSION

Overall, we observed epigenetic-based racial disparity in PCa which could affect survival and should be considered during prognosis and treatment.

Approaches to urinary detection of prostate cancer

Background:

Prostate cancer is the most common cancer in American men that ranges from low risk states amenable to active surveillance to high risk states that can be lethal especially if untreated. There is a critical need to develop relatively non-invasive and clinically useful methods for screening, detection, prognosis, disease monitoring, and prediction of treatment efficacy. In this review, we focus on important advances as well as future efforts needed to drive clinical innovation in this area of urine biomarker research for prostate cancer detection and prognostication.

Methods:

We provide a review of current literature on urinary biomarkers for prostate cancer. We evaluate the strengths and limitations of a variety of approaches that vary in sampling strategies and targets measured; discuss reported urine tests for prostate cancer with respect to their technical, analytical, and clinical parameters; and provide our perspectives on critical considerations in approaches to developing a urine-based test for prostate cancer.

Results:

There has been an extensive history of exploring urine as a source of biomarkers for prostate cancer that has resulted in a variety of urine tests that are in current clinical use. Importantly, at least three tests have demonstrated high sensitivity (~90%) and negative predictive value (~95%) for clinically significant tumors; however, there has not been widespread adoption of these tests.

Conclusions:

Conceptual and methodological advances in the field will help to drive the development of novel urinary tests that in turn may lead to a shift in the clinical paradigm for prostate cancer diagnosis and management.

Spectrophotometric photodynamic diagnosis of prostate cancer cells excreted in voided urine using 5-aminolevulinic acid

To evaluate the feasibility of photodynamic diagnosis using 5-aminolevulinic acid (PDD-ALA) for detection of prostate cancer (PCa) cells in urine samples after prostate massage in patients who were suspected to have PCa. One hundred and eighty-nine patients with abnormal digital rectal examination and/or an elevated prostate-specific antigen (PSA) level who underwent initial prostate biopsy were recruited. After prostate massage, the first 60 mL of voided urine was collected. For PDD-ALA, 50 mL was used. The rest of collected urine was used for polymerase chain reaction (PCR) of PSA and glyceraldehyde 3-phosphate dehydrogenase (GAPDH). After incubation for 2 h, the intensity was measured at 635 nm under a 405-nm wavelength excitation. The results of PDD-ALA were compared with those of an initial transrectal ultrasound (TRUS)-guided prostate biopsy. Overall, 126/189 (67%) samples that showed bands of both PSA and GAPDH on PCR in urine samples were analyzed. The area under the curve, sensitivity, and specificity of PDD-ALA were 0.74, 77, and 67%, respectively. The value of PDD-ALA was significantly higher in patients with Gleason scores of 6 (p = 0.03), 7 (p = 0.005), and 8-10 (p = 0.0002) than in those with negative biopsy results. In the multivariate analysis, high PSA density, abnormal findings on TRUS, and a high value of PDD-ALA were significant markers for prediction of positive biopsy results. PDD-ALA was useful to predict positive biopsy results in patients who underwent initial prostate biopsy with suspected PCa. This PCa-detection method has potential for clinical use.

Innovative Diagnostic Methods for Early Prostate Cancer Detection through Urine Analysis: A Review

Prostate cancer is the second most common cause of cancer death among men. It is an asymptomatic and slow growing tumour, which starts occurring in young men, but can be detected only around the age of 40&ndash;50. Although its long latency period and potential curability make prostate cancer a perfect candidate for screening programs, the current procedure lacks in specificity. Researchers are rising to the challenge of developing innovative tools able of detecting the disease during its early stage that is the most curable. In recent years, the interest in characterisation of biological fluids aimed at the identification of tumour-specific compounds has increased significantly, since cell neoplastic transformation causes metabolic alterations leading to volatile organic compounds release. In the scientific literature, different approaches have been proposed. Many studies focus on the identification of a cancer-characteristic &ldquo;odour fingerprint&rdquo; emanated from biological samples through the application of sensorial or senso-instrumental analyses, others suggest a chemical characterisation of biological fluids with the aim of identifying prostate cancer (PCa)-specific biomarkers. This paper focuses on the review of literary studies in the field of prostate cancer diagnosis, in order to provide an overview of innovative methods based on the analysis of urine, thereby comparing them with the traditional diagnostic procedures.

GC-MS-Based Endometabolome Analysis Differentiates Prostate Cancer from Normal Prostate Cells

Prostate cancer (PCa) is an important health problem worldwide. Diagnosis and management of PCa is very complex because the detection of serum prostate specific antigen (PSA) has several drawbacks. Metabolomics brings promise for cancer biomarker discovery and for better understanding PCa biochemistry. In this study, a gas chromatography–mass spectrometry (GC-MS) based metabolomic profiling of PCa cell lines was performed. The cell lines include 22RV1 and LNCaP from PCa with androgen receptor (AR) expression, DU145 and PC3 (which lack AR expression), and one normal prostate cell line (PNT2). Regarding the metastatic potential, PC3 is from an adenocarcinoma grade IV with high metastatic potential, DU145 has a moderate metastatic potential, and LNCaP has a low metastatic potential. Using multivariate analysis, alterations in levels of several intracellular metabolites were detected, disclosing the capability of the endometabolome to discriminate all PCa cell lines from the normal prostate cell line. Discriminant metabolites included amino acids, fatty acids, steroids, and sugars. Six stood out for the separation of all the studied PCa cell lines from the normal prostate cell line: ethanolamine, lactic acid, β-Alanine, L-valine, L-leucine, and L-tyrosine.

Targeted proteomics in urinary extracellular vesicles identifies biomarkers for diagnosis and prognosis of prostate cancer

Rapid and reliable diagnosis of prostate cancer (PCa) is highly desirable as current used methods lack specificity. In addition, identification of PCa biomarkers that can classify patients into high- and low-risk groups for disease progression at early stage will improve treatment decision-making. Here, we describe a set of protein-combination panels in urinary extracellular vesicles (EVs), defined by targeted proteomics and immunoblotting techniques that improve early non-invasive detection and stratification of PCa patients.We report a two-protein combination in urinary EVs that classifies benign and PCa patients (ADSV-TGM4), and a combination of five proteins able to significantly distinguish between high- and low-grade PCa patients (CD63-GLPK5-SPHM-PSA-PAPP). Proteins composing the panels were validated by immunohistochemistry assays in tissue microarrays (TMAs) confirming a strong link between the urinary EVs proteome and alterations in PCa tissues. Moreover, ADSV and TGM4 abundance yielded a high diagnostic potential in tissue and promising TGM4 prognostic power. These results suggest that the proteins identified in urinary EVs distinguishing high- and low grade PCa are a reflection of histological changes that may be a consequence of their functional involvement in PCa development. In conclusion, our study resulted in the identification of protein-combination panels present in urinary EVs that exhibit high sensitivity and specificity for PCa detection and patient stratification. Moreover, our study highlights the potential of targeted proteomic approaches–such as selected reaction monitoring (SRM)–as diagnostic assay for liquid biopsies via urinary EVs to improve diagnosis and prognosis of suspected PCa patients.

Quantitative RNA Analysis from Urine Using Real Time PCR

Urine is emerging as a biological fluid suitable to perform liquid biopsy in a minimally invasive manner, a fundamental attribute for prevention and early detection of cancer. Urine biomarkers can be analyzed in voided urine, in urine sediment, and urine supernatant. In the case of urothelial carcinoma, in which tumor cells are in direct contact with urine, the assessment of the levels of biomarkers in the urinary cell fraction appears to be the most promising approach to identify diagnostic and prognostic biomarkers in a noninvasive way. Here, we describe a protocol to collect and process urine samples to obtain urinary exfoliated cells. Furthermore, we describe the methodology to isolate RNA from urinary cells and to quantify gene expression levels from these urinary cells.

Cutting Edge Methods for Non-Invasive Disease Diagnosis Using E-Tongue and E-Nose Devices

Biomimetic cross-reactive sensor arrays (B-CRSAs) have been used to detect and diagnose a wide variety of diseases including metabolic disorders, mental health diseases, and cancer by analyzing both vapor and liquid patient samples. Technological advancements over the past decade have made these systems selective, sensitive, and affordable. To date, devices for non-invasive and accurate disease diagnosis have seen rapid improvement, suggesting a feasible alternative to current standards for medical diagnostics. This review provides an overview of the most recent B-CRSAs for diagnostics (also referred to electronic noses and tongues in the literature) and an outlook for future technological development.

Amino Acid Profiles of Serum and Urine in Search for Prostate Cancer Biomarkers: a Pilot Study

There is a great interest in searching for diagnostic biomarkers in prostate cancer patients. The aim of the pilot study was to evaluate free amino acid profiles in their serum and urine. The presented paper shows the first comprehensive analysis of a wide panel of amino acids in two different physiological fluids obtained from the same groups of prostate cancer patients (n = 49) and healthy men (n = 40). The potential of free amino acids, both proteinogenic and non-proteinogenic, as prostate cancer biomarkers and their utility in classification of study participants have been assessed. Several metabolites, which deserve special attention in the further metabolomic investigations on searching for prostate cancer markers, were indicated. Moreover, free amino acid profiles enabled to classify samples to one of the studied groups with high sensitivity and specificity. The presented research provides a strong evidence that ethanolamine, arginine and branched-chain amino acids metabolic pathways can be a valuable source of markers for prostate cancer. The altered concentrations of the above-mentioned metabolites suggest their role in pathogenesis of prostate cancer and they should be further evaluated as clinically useful markers of prostate cancer.

Urinary Polyamines: A Pilot Study on Their Roles as Prostate Cancer Detection Biomarkers

Current screening methods towards prostate cancer (PCa) are not without limitations. Research work has been on-going to assess if there are other better tests suitable for primary or secondary screening of PCa to supplement the serum prostate specific antigen (PSA) test, which fails to work accurately in a grey zone of 4-10ng/ml. In this pilot study, the potential roles of urinary polyamines as prostate cancer biomarkers were evaluated. PCa, benign prostatic hyperplasia (BPH) patients and healthy controls (HC) showing PSA>4.0ng/ml were enrolled in the study. Their urine samples were obtained, and the urinary levels of putrescine (Put), spermidine (Spd) and spermine (Spm) were determined by ultra-high performance liquid chromatography coupled with triple quadrupole mass spectrometer (UPLC-MS/MS). Receiver operating characteristics (ROC) curve and Student’s t-test were used to evaluate their diagnostic accuracies. Among the three biogenic polyamines, Spm had demonstrated a good diagnostic performance when comparing their levels in PCa patients with BPH patients (1.47 in PCa vs 5.87 in BPH; p<0.0001). Results are in accordance with transrectal ultrasound prostatic biopsy (TRUSPB) results, with an area under curve (AUC) value of 0.83±0.03. Therefore urinary Spm shows potential to serve as a novel PCa diagnostic biomarker, which in turn can help to address the limited sensitivity and specificity problem of serum PSA test.

Biomarker Discovery in Human Prostate Cancer: an Update in Metabolomics Studies

Prostate cancer (PCa) is the most frequently diagnosed cancer and the second leading cause of cancer death among men in Western countries. Current screening techniques are based on the measurement of serum prostate specific antigen (PSA) levels and digital rectal examination. A decisive diagnosis of PCa is based on prostate biopsies; however, this approach can lead to false-positive and false-negative results. Therefore, it is important to discover new biomarkers for the diagnosis of PCa, preferably noninvasive ones. Metabolomics is an approach that allows the analysis of the entire metabolic profile of a biological system. As neoplastic cells have a unique metabolic phenotype related to cancer development and progression, the identification of dysfunctional metabolic pathways using metabolomics can be used to discover cancer biomarkers and therapeutic targets. In this study, we review several metabolomics studies performed in prostatic fluid, blood plasma/serum, urine, tissues and immortalized cultured cell lines with the objective of discovering alterations in the metabolic phenotype of PCa and thus discovering new biomarkers for the diagnosis of PCa. Encouraging results using metabolomics have been reported for PCa, with sarcosine being one of the most promising biomarkers identified to date. However, the use of sarcosine as a PCa biomarker in the clinic remains a controversial issue within the scientific community. Beyond sarcosine, other metabolites are considered to be biomarkers for PCa, but they still need clinical validation. Despite the lack of metabolomics biomarkers reaching clinical practice, metabolomics proved to be a powerful tool in the discovery of new biomarkers for PCa detection.

Biomimetic Cross-Reactive Sensor Arrays: Prospects in Biodiagnostics

Biomimetic cross-reactive sensor arrays have been used to detect and analyze a wide variety of vapour and liquid components in applications such as food science, public health and safety, and diagnostics. As technology has advanced over the past three decades, these systems have become selective, sensitive, and affordable. Currently, the need for non-invasive and accurate devices for early disease diagnosis remains a challenge. This review provides an overview of the various types of Biomimetic cross-reactive sensor arrays (also referred to as electronic noses and tongues in the literature), their current use and future directions, and an outlook for future technological development.

Diagnosis of prostate cancer via nanotechnological approach

Prostate cancer is one of the leading causes of cancer-related deaths among the Caucasian adult males in Europe and the USA. Currently available diagnostic strategies for patients with prostate cancer are invasive and unpleasant and have poor accuracy. Many patients have been overly or underly treated resulting in a controversy regarding the reliability of current conventional diagnostic approaches. This review discusses the state-of-the-art research in the development of novel noninvasive prostate cancer diagnostics using nanotechnology coupled with suggested diagnostic strategies for their clinical implication.

Novel non-invasive biomarkers that distinguish between benign prostate hyperplasia and prostate cancer

BACKGROUND

The objective of this study was to discover and to validate novel noninvasive biomarkers that distinguish between benign prostate hyperplasia (BPH) and localized prostate cancer (PCa), thereby helping to solve the diagnostic dilemma confronting clinicians who treat these patients.

METHODS

Quantitative iTRAQ LC/LC/MS/MS analysis was used to identify proteins that are differentially expressed in the urine of men with BPH compared with those who have localized PCa. These proteins were validated in 173 urine samples from patients diagnosed with BPH (N = 83) and PCa (N = 90). Multivariate logistic regression analysis was used to identify the predictive biomarkers.

RESULTS

Three proteins, β2M, PGA3, and MUC3 were identified by iTRAQ and validated by immunoblot analyses. Univariate analysis demonstrated significant elevations in urinary β2M (P < 0.001), PGA3 (P = 0.006), and MUC3 (P = 0.018) levels found in the urine of PCa patients. Multivariate logistic regression analysis revealed AUC values ranging from 0.618 for MUC3 (P = 0.009), 0.625 for PGA3 (P < 0.008), and 0.668 for β2M (P < 0.001). The combination of all three demonstrated an AUC of 0.710 (95% CI: 0.631 - 0.788, P < 0.001); diagnostic accuracy improved even more when these data were combined with PSA categories (AUC = 0.812, (95% CI: 0.740 - 0.885, P < 0.001).

CONCLUSIONS

Urinary β2M, PGA3, and MUC3, when analyzed alone or when multiplexed with clinically defined categories of PSA, may be clinically useful in noninvasively resolving the dilemma of effectively discriminating between BPH and localized PCa.

Analytical platform evaluation for quantification of ERG in prostate cancer using protein and mRNA detection methods

Background

The established methods for detecting prostate cancer (CaP) are based on tests using PSA (blood), PCA3 (urine), and AMACR (tissue) as biomarkers in patient samples. The demonstration of ERG oncoprotein overexpression due to gene fusion in CaP has thus provided ERG as an additional biomarker. Based on this, we hypothesized that ERG protein quantification methods can be of use in the diagnosis of prostate cancer.

Methods

An antibody-free assay for ERG3 protein detection was developed based on PRISM (high-pressure high-resolution separations with intelligent selection and multiplexing)-SRM (selected reaction monitoring) mass spectrometry. We utilized TMPRSS2-ERG positive VCaP and TMPRSS2-ERG negative LNCaP cells to simulate three different sample types (cells, tissue, and post-DRE urine sediment). Enzyme-linked immunosorbent assay (ELISA), western blot, NanoString, and qRT-PCR were also used in the analysis of these samples.

Results

Recombinant ERG3 protein spiked into LNCaP cell lysates could be detected at levels as low as 20 pg by PRISM-SRM analysis. The sensitivity of the PRISM-SRM assay was approximately 10,000 VCaP cells in a mixed cell population model of VCaP and LNCaP cells. Interestingly, ERG protein could be detected in as few as 600 VCaP cells spiked into female urine. The sensitivity of the in-house ELISA was similar to the PRISM-SRM assay, with detection of 30 pg of purified recombinant ERG3 protein and 10,000 VCaP cells. On the other hand, qRT-PCR exhibited a higher sensitivity, as TMPRSS2-ERG transcripts were detected in as few as 100 VCaP cells, in comparison to NanoString methodologies which detected ERG from 10,000 cells.

Conclusions

Based on this data, we propose that the detection of both ERG transcriptional products with RNA-based assays, as well as protein products of ERG using PRISM-SRM assays, may be of clinical value in developing diagnostic and prognostic assays for prostate cancer given their sensitivity, specificity, and reproducibility.

Microfluidic platforms for biomarker analysis

Biomarkers have been described as characteristics, most often molecular, that provide information about biological states, whether normal, pathological, or therapeutically modified. They hold great potential to assist diagnosis and prognosis, monitor disease, and assess therapeutic effectiveness. While a few biomarkers are routinely utilised clinically, these only reflect a very small percentage of all biomarkers discovered. Numerous factors contribute to the slow uptake of these new biomarkers, with challenges faced throughout the biomarker development pipeline. Microfluidics offers two important opportunities to the field of biomarkers: firstly, it can address some of these developmental obstacles, and secondly, it can provide the precise and complex platform required to bridge the gap between biomarker research and the biomarker-based analytical device market. Indeed, adoption of microfluidics has provided a new avenue for advancement, promoting clinical utilisation of both biomarkers and their analytical platforms. This review will discuss biomarkers and outline microfluidic platforms developed for biomarker analysis.

Prostate cancer risk after anti-androgen treatment for priapism

BACKGROUND

Patients with recurrent ischemic priapism have historically been treated with anti-androgen therapy due to the limited available evidence for more targeted therapies to treat the underlying pathophysiologic mechanisms of this condition. We report a case in which anti-androgen therapy caused significant adverse side effects and likely masked this patient's elevated prostate-specific antigen (PSA) levels, which adversely impacted the timely diagnosis and treatment of his prostate cancer.

CASE REPORT

A 69-year-old man treated with anti-androgens for priapism initially developed unwanted anti-androgenic side effects such as gynecomastia, erectile dysfunction, and decreased libido. After decreasing his anti-androgen dosage and starting a specified regimen of phosphodiesterase type 5 inhibitor therapy, his serum PSA levels were found to be elevated. He was subsequently diagnosed with adenocarcinoma of the prostate and underwent a radical prostatectomy with the pathologic finding of high-grade, locally progressive disease.

CONCLUSION

Anti-androgen therapy carries significant complication risks, including the potential to alter the diagnosis and treatment of prostate cancer. Clinicians administering this therapy for priapism management should be aware of these possible risks.