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

Deciphering Cancer Complexity: Integrative Proteogenomics and Proteomics Approaches for Biomarker Discovery

Proteomics has revolutionized the field of cancer biology because the use of a large number of in vivo (SILAC), in vitro (iTRAQ, ICAT, TMT, stable-isotope Dimethyl, and 18O) labeling techniques or label-free methods (spectral counting or peak intensities) coupled with mass spectrometry enables us to profile and identify dysregulated proteins in diseases such as cancer. These proteome and genome studies have led to many challenges, such as the lack of consistency or correlation between copy numbers, RNA, and protein-level data. This review covers solely mass spectrometry-based approaches used for cancer biomarker discovery. It also touches on the emerging role of oncoproteogenomics or proteogenomics in cancer biomarker discovery and how this new area is attracting the integration of genomics and proteomics areas to address some of the important questions to help impinge on the biology and pathophysiology of different malignancies to make these mass spectrometry-based studies more realistic and relevant to clinical settings.

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.

Development of a predictive model to distinguish prostate cancer from benign prostatic hyperplasia by integrating serum glycoproteomics and clinical variables

BACKGROUND

Prostate Cancer (PCa) represents the second leading cause of cancer-related death in men. Prostate-specific antigen (PSA) serum testing, currently used for PCa screening, lacks the necessary sensitivity and specificity. New non-invasive diagnostic tools able to discriminate tumoral from benign conditions and aggressive (AG-PCa) from indolent forms of PCa (NAG-PCa) are required to avoid unnecessary biopsies.

METHODS

In this work, 32 formerly N-glycosylated peptides were quantified by PRM (parallel reaction monitoring) in 163 serum samples (79 from PCa patients and 84 from individuals affected by benign prostatic hyperplasia (BPH)) in two technical replicates. These potential biomarker candidates were prioritized through a multi-stage biomarker discovery pipeline articulated in: discovery, LC-PRM assay development and verification phases. Because of the well-established involvement of glycoproteins in cancer development and progression, the proteomic analysis was focused on glycoproteins enriched by TiO2 (titanium dioxide) strategy.

RESULTS

Machine learning algorithms have been applied to the combined matrix comprising proteomic and clinical variables, resulting in a predictive model based on six proteomic variables (RNASE1, LAMP2, LUM, MASP1, NCAM1, GPLD1) and five clinical variables (prostate dimension, proPSA, free-PSA, total-PSA, free/total-PSA) able to distinguish PCa from BPH with an area under the Receiver Operating Characteristic (ROC) curve of 0.93. This model outperformed PSA alone which, on the same sample set, was able to discriminate PCa from BPH with an AUC of 0.79. To improve the clinical managing of PCa patients, an explorative small-scale analysis (79 samples) aimed at distinguishing AG-PCa from NAG-PCa was conducted. A predictor of PCa aggressiveness based on the combination of 7 proteomic variables (FCN3, LGALS3BP, AZU1, C6, LAMB1, CHL1, POSTN) and proPSA was developed (AUC of 0.69).

CONCLUSIONS

To address the impelling need of more sensitive and specific serum diagnostic tests, a predictive model combining proteomic and clinical variables was developed. A preliminary evaluation to build a new tool able to discriminate aggressive presentations of PCa from tumors with benign behavior was exploited. This predictor displayed moderate performances, but no conclusions can be drawn due to the limited number of the sample cohort. Data are available via ProteomeXchange with identifier PXD035935.

The Controversy of Pepsinogen A/Pepsin A in Detecting Extra-Gastroesophageal Reflux

BACKGROUND

Pepsinogen A (PGA)/pepsin A is often used as a diagnostic marker of extra-gastroesophageal reflux. We aimed to explore whether its positivity in upper aerodigestive tract (UADT) was specific enough to diagnose reflux.

METHODS

PGA/pepsin A protein levels were examined in 10 types of tissues and 10 types of body fluid by immunological staining, western blot or Elisa, using three different commercially available brands simultaneously. Liquid chromatography-tandem mass spectrometry parallel reaction monitoring (LC-MS/MS PRM) served as a gold reference for the detection of PGA/pepsin A proteins. PGA gene expression was analyzed by reverse transcriptase sequencing methods for tissue samples. Specifically, 24 hour pH monitoring technique was conducted for patients who donated saliva samples.

RESULTS

Eight out of ten types of human tissue samples (stomach, esophagus, lung, kidney, colon, parotid gland, nasal turbinate and nasal polyps) were confirmed positive for PGA/pepsin A gene and protein by genetic and PRM technique, respectively. Two out of ten types of body fluid samples (gastric fluid, urine) were confirmed positive for PGA/pepsin A protein by PRM technique. The consistence rates of PGA/pepsin A positivity among three commercial antibody brands and Elisa kit were poor, and Elisa results of salivary did not match with 24-hour pH monitoring.

CONCLUSIONS

Multiple tissues and body fluid could be detected baseline expression levels of PGA/pepsin A gene and protein. However, those commercially available PGA/pepsin A antibodies achieved poor sensitivity and specificity, therefore, relying on the detection of PGA/pepsin A in UADT by single antibodies to diagnose extra-gastroesophageal reflux without a specific positive cut-off value is unreliable.

The Latest Developments in Using Proteomic Biomarkers from Urine and Serum for Non-Invasive Disease Diagnosis and Prognosis

Due to diagnostic improvements, medical diagnostics is demanding non-invasive or minimally invasive methods. Non-invasively obtained body fluids (eg., Urine, serum) can replace cerebral fluid, amniotic fluid, synovial fluid, bronchoalveolar lavage fluid, and others for diagnostic reasons. Many illnesses are induced by perturbations of cellular signaling pathways and associated pathway networks as a result of genetic abnormalities. These disturbances are represented by a shift in the protein composition of the fluids surrounding the tissues and organs that is, tissue interstitial fluid (TIF). These variant proteins may serve as diagnostic "signatures" for a variety of disorders. This review provides a concise summary of urine and serum biomarkers that may be used for the diagnosis and prognosis of a variety of disorders, including cancer, brain diseases, kidney diseases, and other system diseases. The studies reviewed in this article suggest that serum and urine biomarkers of various illnesses may be therapeutically useful for future diagnostics. Correct illness management is crucial for disease prognosis, hence non-invasive serum and urine biomarkers have been extensively studied for diagnosis, subclassification, monitoring disease activity, and predicting treatment results and consequences.

Mucins as contrast agent targets for fluorescence-guided surgery of pancreatic cancer

Pancreatic cancer is difficult to resect due to its unique challenges, often leading to incomplete tumor resections. Fluorescence-guided surgery (FGS), also known as intraoperative molecular imaging and optical surgical navigation, is an intraoperative tool that can aid surgeons in complete tumor resection through an increased ability to detect the tumor. To target the tumor, FGS contrast agents rely on biomarkers aberrantly expressed in malignant tissue compared to normal tissue. These biomarkers allow clinicians to identify the tumor and its stage before surgical resection and provide a contrast agent target for intraoperative imaging. Mucins, a family of glycoproteins, are upregulated in malignant tissue compared to normal tissue. Therefore, these proteins may serve as biomarkers for surgical resection. Intraoperative imaging of mucin expression in pancreatic cancer can potentially increase the number of complete resections. While some mucins have been studied for FGS, the potential ability to function as a biomarker target extends to the entire mucin family. Therefore, mucins are attractive proteins to investigate more broadly as FGS biomarkers. This review summarizes the biomarker traits of mucins and their potential use in FGS for pancreatic cancer.

Proteomic Discovery of Noninvasive Biomarkers Associated With Sport-Related Concussions

BACKGROUND AND OBJECTIVES

Sport-related concussions affect millions of individuals across the United States each year, and current techniques to diagnose and monitor them rely largely on subjective measures. Our goal was to discover and validate objective, quantifiable noninvasive biomarkers with the potential to be used in sport-related concussion diagnosis.

METHODS

Urine samples from a convenience series of healthy control collegiate athletes who had not sustained a concussion and athletes who sustained a concussion as diagnosed by a sports medicine physician within 7 days were collected prospectively and studied. Participants also completed an instrumented single-task gait analysis as a functional measure. Participants were recruited from a single collegiate athletic program and were ≥18 years of age and were excluded if they had a concomitant injury, active psychiatric conditions, or preexisting neurologic disorders. Using Tandem Mass Tags (TMT) mass spectroscopy and ELISA, we identified and validated urinary biomarkers of concussion.

RESULTS

Forty-eight control and 47 age- and sex-matched athletes with concussion were included in the study (51.6% female, 48.4% male, average age 19.6 years). Participants represented both contact and noncontact sports. All but 1 of the postconcussion participants reported experiencing symptoms at the time of data collection. Insulin-like growth factor 1 (IGF-1) and IGF binding protein 5 (IGFBP5) were downregulated in the urine of athletes with concussions compared to healthy controls. Multivariable risk algorithms developed to predict the probability of sport-related concussion showed that IGF-1 multiplexed with single-task gait velocity predicts concussion risk across a range of postinjury time points (area under the curve [AUC] 0.786, 95% confidence interval [CI] 0.690-0.884). When IGF-1 and IGFBP5 are multiplexed with single-task gait velocity, they accurately distinguish between healthy controls and individuals with concussion at acute time points (AUC 0.835, 95% CI 0.701-0.968, p < 0.001).

DISCUSSION

These noninvasive biomarkers, discovered in an objective and validated manner, may be useful in diagnosing and monitoring sport-related concussions in both acute phases of injury and several days after injury.

TRIAL REGISTRATION INFORMATION

ClinicalTrials.gov Identifier: NCT02354469 (submitted February 2015, first patient enrolled August 2015).

CLASSIFICATION OF EVIDENCE

This study provides Class III evidence that urinary IGF-1 and IGFBP5 multiplexed with single-task gait velocity may be useful in diagnosing sport-related concussion.

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

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

Proteomic discovery of non-invasive biomarkers of localized prostate cancer using mass spectrometry

Prostate cancer is the second most frequently diagnosed non-skin cancer in men worldwide. Patient outcomes are remarkably heterogeneous and the best existing clinical prognostic tools such as International Society of Urological Pathology Grade Group, pretreatment serum PSA concentration and T-category, do not accurately predict disease outcome for individual patients. Thus, patients newly diagnosed with prostate cancer are often overtreated or undertreated, reducing quality of life and increasing disease-specific mortality. Biomarkers that can improve the risk stratification of these patients are, therefore, urgently needed. The ideal biomarker in this setting will be non-invasive and affordable, enabling longitudinal evaluation of disease status. Prostatic secretions, urine and blood can be sources of biomarker discovery, validation and clinical implementation, and mass spectrometry can be used to detect and quantify proteins in these fluids. Protein biomarkers currently in use for diagnosis, prognosis and relapse-monitoring of localized prostate cancer in fluids remain centred around PSA and its variants, and opportunities exist for clinically validating novel and complimentary candidate protein biomarkers and deploying them into the clinic.

High mortality risk of prostate cancer patients in Asia and West Africa: A systematic review

Globally, prostate cancer (PCa) is the second most preponderant cancer in men. It contributes to the high mortality-to-incidence ratio reported in West Africa and Asia largely due to low screening. The mortality risk is determined or predicted based on the prevalence of high-risk or aggressive PCa using a scoring or grading system such as Gleason score (GS), Gleason grade (GG), and prostate-specific antigen (PSA) level. In this review, peer-reviewed articles found on databases such as Google Scholar, Scopus, Web of Science, PubMed Central and, EMBASE were selected based on adherence to clinical guidelines for the classification of PCa. In West Africa and Asia, the result revealed that the frequency of high-risk PCa was 42% and 51.2% based on GS, 48.8% and 25.3% based on GG pattern, and 87.5% and 44.3% based on PSA level >10 ng/mL, respectively. Data revealed a high prevalence of high-risk PCa both in West Africa and Asia when compared with developed countries. However, the prevalence of high-risk PCa is higher in West Africa than in Asia. Studies have shown that high-risk PCas are associated with germline mutations and such mutations are prevalent in blacks and Asians than in whites. Thus, testing for germline mutations in patients with GS of ≥ 7, GG ≥ 3, high prostate density, low prostate volume, and PSA levels of >4.0 ng/mL may identify those at risk of developing lethal PCa and could reduce the mortality rates in Asia and West Africa.

Biomarkers That Differentiate Benign Prostatic Hyperplasia from Prostate Cancer: A Literature Review

Prediction of prostate cancer in primary care is typically based upon serum total prostate-specific antigen (tPSA) and digital rectal examination results. However, these tests lack sensitivity and specificity, leading to over-diagnosis of disease and unnecessary, invasive biopsies. Therefore, there is a clinical need for diagnostic tests that can differentiate between benign conditions and early-stage malignant disease in the prostate. In this review, we evaluate research papers published from 2009 to 2019 reporting biomarkers that identified or differentiated benign prostatic hyperplasia (BPH) from prostate cancer. Our review identifies hundreds of potential biomarkers in urine, serum, tissue, and semen proposed as useful targets for differentiating between prostate cancer and BPH patients. However, it is still not apparent which of these candidate biomarkers are most useful, and many will not progress beyond the discovery stage unless they are properly validated for clinical practice. We conclude that this validation will come through the use of multivariate panels which can assess the value of biomarker candidates in combination with clinical parameters as part of a risk prediction calculator. Implementation of such a model will help clinicians stratify patients with prostate cancer symptoms in primary care, with tangible benefits for both the patient and the health service.

Cdc42-Dependent Transfer of mir301 from Breast Cancer-Derived Extracellular Vesicles Regulates the Matrix Modulating Ability of Astrocytes at the Blood-Brain Barrier

Breast cancer brain metastasis is a major clinical challenge and is associated with a dismal prognosis. Understanding the mechanisms underlying the early stages of brain metastasis can provide opportunities to develop efficient diagnostics and therapeutics for this significant clinical challenge. We have previously reported that breast cancer-derived extracellular vesicles (EVs) breach the blood-brain barrier (BBB) via transcytosis and can promote brain metastasis. Here, we elucidate the functional consequences of EV transport across the BBB. We demonstrate that brain metastasis-promoting EVs can be internalized by astrocytes and modulate the behavior of these cells to promote extracellular matrix remodeling in vivo. We have identified protein and miRNA signatures in these EVs that can lead to the interaction of EVs with astrocytes and, as such, have the potential to serve as targets for development of diagnostics and therapeutics for early detection and therapeutic intervention in breast cancer brain metastasis.

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

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

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.

Distinct urinary glycoprotein signatures in prostate cancer patients

Novel biomarkers are needed to complement prostate specific antigen (PSA) in prostate cancer (PCa) diagnostic screening programs. Glycoproteins represent a hitherto largely untapped resource with a great potential as specific and sensitive tumor biomarkers due to their abundance in bodily fluids and their dynamic and cancer-associated glycosylation. However, quantitative glycoproteomics strategies to detect potential glycoprotein cancer markers from complex biospecimen are only just emerging. Here, we describe a glycoproteomics strategy for deep quantitative mapping of N- and O-glycoproteins in urine with a view to investigate the diagnostic value of the glycoproteome to discriminate PCa from benign prostatic hyperplasia (BPH), two conditions that remain difficult to clinically stratify. Total protein extracts were obtained, concentrated and digested from urine of six PCa patients (Gleason score 7) and six BPH patients. The resulting peptide mixtures were TMT-labeled and mixed prior to a multi-faceted sample processing including hydrophilic interaction liquid chromatography (HILIC) and titanium dioxide SPE based enrichment, endo-/exoglycosidase treatment and HILIC-HPLC pre-fractionation. The isolated N- and O-glycopeptides were detected and quantified using high resolution mass spectrometry. We accurately quantified 729 N-glycoproteins spanning 1,310 unique N-glycosylation sites and observed 954 and 965 unique intact N- and O-glycopeptides, respectively, across the two disease conditions. Importantly, a panel of 56 intact N-glycopeptides perfectly discriminated PCa and BPH (ROC: AUC = 1). This study has generated a panel of intact glycopeptides that has a potential for PCa detection.

Promise and Implementation of Proteomic Prostate Cancer Biomarkers

Prostate cancer is one of the most commonly diagnosed malignancy and the fifth leading cause of cancer mortality in men. Despite the broad use of prostate-specific antigen test that resulted in an increase in number of diagnosed cases, disease management needs to be improved. Proteomic biomarkers alone and or in combination with clinical and pathological risk calculators are expected to improve on decreasing the unnecessary biopsies, stratify low risk patients, and predict response to treatment. To this end, significant efforts have been undertaken to identify novel biomarkers that can accurately discriminate between indolent and aggressive cancer forms and indicate those men at high risk for developing prostate cancer that require immediate treatment. In the era of “big data” and “personalized medicine” proteomics-based biomarkers hold great promise to provide clinically applicable tools, as proteins regulate all biological functions, and integrate genomic information with the environmental impact. In this review article, we aim to provide a critical assessment of the current proteomics-based biomarkers for prostate cancer and their actual clinical applicability. For that purpose, a systematic review of the literature published within the last 10 years was performed using the Web of Science Database. We specifically discuss the potential and prospects of use for diagnostic, prognostic and predictive proteomics-based biomarkers, including both body fluid- and tissue-based markers.

Approaches to the discovery of non-invasive urinary biomarkers of prostate cancer

Prostate cancer (PCa) continues to be one of the most common cancers in men worldwide. Prostate specific antigen (PSA) measured in blood has been used for decades as an aid for physicians to detect the presence of prostate cancer. However, the PSA test has limited sensitivity and specificity, leading to unnecessary biopsies, overdiagnosis and overtreatment of patients. For these reasons, there is an urgent need for more accurate PCa biomarkers that can detect PCa with high sensitivity and specificity. Urine is a unique source of potential protein biomarkers that can be measured in a non-invasive way. This review comprehensively summarizes state of the art approaches used in the discovery and validation of urinary biomarkers for PCa. Numerous strategies are currently being used in the discovery of urinary biomarkers for prostate cancer including gel-based separation techniques, mass spectrometry, activity-based proteomic assays and software approaches. Antibody-based approaches remain preferred method for validation of candidate biomarkers with rapidly advancing multiplex immunoassays and MS-based targeted approaches. In the last decade, there has been a dramatic acceleration in the development of new techniques and approaches in the discovery of protein biomarkers for prostate cancer including computational, statistical and data mining methods. Many urinary-based protein biomarkers have been identified and have shown significant promise in initial studies. Examples of these potential biomarkers and the methods utilized in their discovery are also discussed in this review.

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.

Prostate cancer proteomics: clinically useful protein biomarkers and future perspectives

INTRODUCTION

Although prostate cancer constitutes one of the most important, death-related diseases in the male population, there is still a need for identification of sensitive biomarkers that could precociously detect the disease and differentiate aggressive from indolent cancers, in order to decrease overtreatment. Proteomics research has improved understanding on mechanisms underlying tumorigenesis, cancer cells migration and invasion potential, and castration resistance. This review has focused on proteomic studies of prostate cancer published in the recent years, with a special emphasis on determination of biomarkers for cancer progression and diagnosis. Areas covered: Shotgun and targeted-proteomic studies of prostate cancer in different matrices are reviewed, i.e., prostate tissue, prostate cell lines, blood (serum and plasma), urine, seminal plasma, and exosomes. The most important biomarkers for cancer diagnosis and aggressiveness characterization are highlighted. Expert commentary: In general, results demonstrate alteration in cell cycle control, DNA repair, proteasomal degradation, and metabolic activity. However, these studies suffer from low reproducibility due to heterogeneity of the cancer itself, as well as to techniques utilized for protein identification/quantification. Downstream confirmatory studies in separate cohorts are warranted in order to demonstrate accuracy of these results.

Quantitative Mass Spectrometry-Based Proteomic Profiling for Precision Medicine in Prostate Cancer

Prostate cancer (PCa) is one of the most frequently diagnosed cancer among men in the western societies. Many PCa patients bear tumors that will not threat their lives if left untreated or if treatment is delayed. Our inability for early identification of these patients has resulted in massive overtreatment. Therefore, there is a great need of finding biomarkers for patient stratification according to prognostic risk; as well as there is a need for novel targets that can allow the development of effective treatments for patients that progress to castration-resistant PCa. Most biomarkers in cancer are proteins, including the widely-used prostate-specific antigen (PSA). Recent developments in mass spectrometry allow the identification and quantification of thousands of proteins and posttranslational modifications from small amounts of biological material, including formalin-fixed paraffin-embedded tissues, and biological fluids. Novel diagnostic and prognostic biomarkers have been identified in tissue, blood, urine, and seminal plasma of PCa patients, and new insights in the ethology and progression of this disease have been achieved using this technology. In this review, we summarize these findings and discuss the potential of this technology to pave the way toward the clinical implementation of precision medicine in PCa.

The Role of Proteomics in Biomarker Development for Improved Patient Diagnosis and Clinical Decision Making in Prostate Cancer

Prostate Cancer (PCa) is the second most commonly diagnosed cancer in men worldwide. Although increased expression of prostate-specific antigen (PSA) is an effective indicator for the recurrence of PCa, its intended use as a screening marker for PCa is of considerable controversy. Recent research efforts in the field of PCa biomarkers have focused on the identification of tissue and fluid-based biomarkers that would be better able to stratify those individuals diagnosed with PCa who (i) might best receive no treatment (active surveillance of the disease); (ii) would benefit from existing treatments; or (iii) those who are likely to succumb to disease recurrence and/or have aggressive disease. The growing demand for better prostate cancer biomarkers has coincided with the development of improved discovery and evaluation technologies for multiplexed measurement of proteins in bio-fluids and tissues. This review aims to (i) provide an overview of these technologies as well as describe some of the candidate PCa protein biomarkers that have been discovered using them; (ii) address some of the general limitations in the clinical evaluation and validation of protein biomarkers; and (iii) make recommendations for strategies that could be adopted to improve the successful development of protein biomarkers to deliver improvements in personalized PCa patient decision making.

Site-specific characterization of N-linked glycosylation in human urinary glycoproteins and endogenous glycopeptides

Glycosylation is a very important post-translational modification involved in various cellular processes, such as cell adhesion, signal transduction and immune response. Urine is a rich source of glycoproteins and attractive biological fluid for biomarker discovery, owing to its availability, ease of collection, and correlation with pathophysiology of diseases. Although the urinary proteomics have been explored previously, the urinary glycoproteome characterization remains challenging requiring the development and optimization of analytical and bioinformatics methods for protein glycoprofiling. This study describes the high confident identification of 472 unique N-glycosylation sites covering 256 urinary glycoproteins. Besides, 202 unique N-glycosylation sites were identified in low molecular weight endogenous glycopeptides, which belong to 90 glycoproteins. Global site-specific characterization of the N-linked glycan heterogeneity was achieved by intact glycopeptide analysis, revealing 303 unique glycopeptides most of them displaying complex/hybrid glycans composed by sialic acid and fucose. These datasets consist in a valuable resource of glycoproteins and N-glycosylation sites found in healthy human urine that can be further explored in different disorders, in which the N-linked glycosylation may be aberrant.

Mining the Human Proteome: Biomarker Discovery for Human Cancer and Metastases

As our knowledge of the mechanisms underlying cancer development and progression has increased, so too have more effective, less toxic, and targeted therapies begun to reach the clinic. However, the full impact of these clinical advances and the practical success of the emerging field of precision medicine are dependent on the discovery and validation of sensitive and accurate biomarkers that can enable appropriate and rigorous sample type and patient selection, reliable longitudinal monitoring of therapeutic efficacy, and even risk assessment and early detection. Within the context of this review, we examine state-of-the-art approaches to the discovery and validation of noninvasive cancer biomarkers, with a specific emphasis on those that are protein or protein-associated ones. We also review sample selection strategies, currently utilized proteomic approaches for both discovery and validation requirements, and data analysis standards. Finally, we provide examples of these elements of biomarker discovery and validation from our own biomarker research.

Urinary proteomics and metabolomics studies to monitor bladder health and urological diseases

Background

Assays of molecular biomarkers in urine are non-invasive compared to other body fluids and can be easily repeated. Based on the hypothesis that the secreted markers from the diseased organs may locally release into the body fluid in the vicinity of the injury, urine-based assays have been considered beneficial to monitoring bladder health and urological diseases. The urine proteome is much less complex than the serum and tissues, but nevertheless can contain biomarkers for diagnosis and prognosis of diseases. The urine metabolome has a much higher number and concentration of low-molecular metabolites than the serum or tissues, with a far lower lipid concentration, yet informs directly about dietary and microbial metabolism.

Discussion

We here discuss the use of mass spectrometry-based proteomics and metabolomics for urine biomarker assays, specifically with respect to the underlying mechanisms that trigger the pathological condition.

Conclusion

Molecular biomarker profiles, based on proteomics and metabolomics studies, reliably distinguish patients from healthy controls, stratify sub-populations with respect to treatment options, and predict therapeutic response of patients with urological disease.

Wash-free magnetic immunoassay of the PSA cancer marker using SERS and droplet microfluidics

We report a novel wash-free magnetic immunoassay technique for prostate-specific antigen (PSA) that uses a surface-enhanced Raman scattering (SERS)-based microdroplet sensor. The magnetic bar embedded in a droplet-based microfluidic system segregates the free and bound SERS tags by splitting the droplets into two smaller parts. The presence of PSA targets leads more SERS tags to immunocomplex in one droplet so that fewer SERS tags remain in another supernatant solution droplet. Thus, SERS signal measurement enables the quantitative evaluation of PSA markers. This approach can provide a rapid and sensitive assay that is applicable for PSA cancer markers in serum without any washing. Specifically, SERS signals were measured at 174 droplets per minute and averaged for quantitative evaluation of PSA. The limit of detection (LOD) determined by our SERS-based microdroplet sensor was estimated to be below 0.1 ng mL(-1), which is significantly below the clinical cut-off value for the diagnosis of prostate cancer. In addition, because the entire assay can be carried out automatically, only a minimal amount of sample is needed. Accordingly, the approach is expected to be useful as a potential clinical tool for the early diagnosis of prostate cancer.

Bioinformatics analysis of differentially expressed proteins in prostate cancer based on proteomics data

We mined the literature for proteomics data to examine the occurrence and metastasis of prostate cancer (PCa) through a bioinformatics analysis. We divided the differentially expressed proteins (DEPs) into two groups: the group consisting of PCa and benign tissues (P&b) and the group presenting both high and low PCa metastatic tendencies (H&L). In the P&b group, we found 320 DEPs, 20 of which were reported more than three times, and DES was the most commonly reported. Among these DEPs, the expression levels of FGG, GSN, SERPINC1, TPM1, and TUBB4B have not yet been correlated with PCa. In the H&L group, we identified 353 DEPs, 13 of which were reported more than three times. Among these DEPs, MDH2 and MYH9 have not yet been correlated with PCa metastasis. We further confirmed that DES was differentially expressed between 30 cancer and 30 benign tissues. In addition, DEPs associated with protein transport, regulation of actin cytoskeleton, and the extracellular matrix (ECM)–receptor interaction pathway were prevalent in the H&L group and have not yet been studied in detail in this context. Proteins related to homeostasis, the wound-healing response, focal adhesions, and the complement and coagulation pathways were overrepresented in both groups. Our findings suggest that the repeatedly reported DEPs in the two groups may function as potential biomarkers for detecting PCa and predicting its aggressiveness. Furthermore, the implicated biological processes and signaling pathways may help elucidate the molecular mechanisms of PCa carcinogenesis and metastasis and provide new targets for clinical treatment.

Recent progress in urinary proteome analysis for prostate cancer diagnosis and management

Prostate cancer (PCa) is fifth leading cause of cancer-associated deaths in men worldwide. Although the application of the serum prostate-specific antigen (PSA) screening test resulted in an increase in the PCa diagnosed cases, it demonstrated a negligible benefit regarding the associated mortality. Treatment options vary, with active surveillance to be preferable for patients with low-risk PCa and therapy of advanced castration-resistant PCa to rely on α-emitters and cytotoxic chemotherapy. Although recent developments have led to the approval of novel drugs for the treatment of castration-resistant PCa, the optimal sequence and timing of medication have not been yet determined. New screening modalities could improve the discriminatory accuracy between tumors with favorable clinical prognosis. Implementation of proteomic-based biomarkers appears to be a promising improvement, which could enable a more accurate diagnosis, guide treatment and improve patient outcome. Reviewed here are urinary proteome-based approaches for detection of PCa and patient management.