Proteomic Insights into Osteoporosis: Unraveling Diagnostic Markers of and Therapeutic Targets for the Metabolic Bone Disease

Osteoporosis (OP), a prevalent skeletal disorder characterized by compromised bone strength and increased susceptibility to fractures, poses a significant public health concern. This review aims to provide a comprehensive analysis of the current state of research in the field, focusing on the application of proteomic techniques to elucidate diagnostic markers and therapeutic targets for OP. The integration of cutting-edge proteomic technologies has enabled the identification and quantification of proteins associated with bone metabolism, leading to a deeper understanding of the molecular mechanisms underlying OP. In this review, we systematically examine recent advancements in proteomic studies related to OP, emphasizing the identification of potential biomarkers for OP diagnosis and the discovery of novel therapeutic targets. Additionally, we discuss the challenges and future directions in the field, highlighting the potential impact of proteomic research in transforming the landscape of OP diagnosis and treatment.

Multitarget Potential Drug Candidates for High-Grade Gliomas Identified by Multiple Reaction Monitoring Coupled with In Silico Drug Repurposing

High-grade gliomas (HGGs) are extremely aggressive primary brain tumors with high mortality rates. Despite notable progress achieved by clinical research and biomarkers emerging from proteomics studies, efficacious drugs and therapeutic targets are limited. This study used targeted proteomics, in silico molecular docking, and simulation-based drug repurposing to identify potential drug candidates for HGGs. Importantly, we performed multiple reaction monitoring (MRM) on differentially expressed proteins with putative roles in the development and progression of HGGs based on our previous work and the published literature. Furthermore, in silico molecular docking-based drug repurposing was performed with a customized library of FDA-approved drugs to identify multitarget-directed ligands. The top drug candidates such as Pazopanib, Icotinib, Entrectinib, Regorafenib, and Cabozantinib were explored for their drug-likeness properties using the SwissADME. Pazopanib exhibited binding affinities with a maximum number of proteins and was considered for molecular dynamic simulations and cell toxicity assays. HGG cell lines showed enhanced cytotoxicity and cell proliferation inhibition with Pazopanib and Temozolomide combinatorial treatment compared to Temozolomide alone. To the best of our knowledge, this is the first study combining MRM with molecular docking and simulation-based drug repurposing to identify potential drug candidates for HGG. While the present study identified five multitarget-directed potential drug candidates, future clinical studies in larger cohorts are crucial to evaluate the efficacy of these molecular candidates. The research strategy and methodology used in the present study offer new avenues for innovation in drug discovery and development which may prove useful, particularly for cancers with low cure rates.

A large-scale targeted proteomics of serum and tissue shows the utility of classifying high grade and low grade meningioma tumors

BACKGROUND

Meningiomas are the most prevalent primary brain tumors. Due to their increasing burden on healthcare, meningiomas have become a pivot of translational research globally. Despite many studies in the field of discovery proteomics, the identification of grade-specific markers for meningioma is still a paradox and requires thorough investigation. The potential of the reported markers in different studies needs further verification in large and independent sample cohorts to identify the best set of markers with a better clinical perspective.

METHODS

A total of 53 fresh frozen tumor tissue and 51 serum samples were acquired from meningioma patients respectively along with healthy controls, to validate the prospect of reported differentially expressed proteins and claimed markers of Meningioma mined from numerous manuscripts and knowledgebases. A small subset of Glioma/Glioblastoma samples were also included to investigate inter-tumor segregation. Furthermore, a simple Machine Learning (ML) based analysis was performed to evaluate the classification accuracy of the list of proteins.

RESULTS

A list of 15 proteins from tissue and 12 proteins from serum were found to be the best segregator using a feature selection-based machine learning strategy with an accuracy of around 80% in predicting low grade (WHO grade I) and high grade (WHO grade II and WHO grade III) meningiomas. In addition, the discriminant analysis could also unveil the complexity of meningioma grading from a segregation pattern, which leads to the understanding of transition phases between the grades.

CONCLUSIONS

The identified list of validated markers could play an instrumental role in the classification of meningioma as well as provide novel clinical perspectives in regard to prognosis and therapeutic targets.

Mass spectrometry-based proteomics as an emerging tool in clinical laboratories

Mass spectrometry (MS)-based proteomics have been increasingly implemented in various disciplines of laboratory medicine to identify and quantify biomolecules in a variety of biological specimens. MS-based proteomics is continuously expanding and widely applied in biomarker discovery for early detection, prognosis and markers for treatment response prediction and monitoring. Furthermore, making these advanced tests more accessible and affordable will have the greatest healthcare benefit.This review article highlights the new paradigms MS-based clinical proteomics has created in microbiology laboratories, cancer research and diagnosis of metabolic disorders. The technique is preferred over conventional methods in disease detection and therapy monitoring for its combined advantages in multiplexing capacity, remarkable analytical specificity and sensitivity and low turnaround time.Despite the achievements in the development and adoption of a number of MS-based clinical proteomics practices, more are expected to undergo transition from bench to bedside in the near future. The review provides insights from early trials and recent progresses (mainly covering literature from the NCBI database) in the application of proteomics in clinical laboratories.

Shotgun Proteomics of Co-Cultured Leukemic and Bone Marrow Stromal Cells from Different Species as a Preliminary Approach to Detect Intercellular Protein Transfer

Cellular interactions within the bone marrow microenvironment modulate the properties of subsets of leukemic cells leading to the development of drug-resistant phenotypes. The intercellular transfer of proteins and organelles contributes to this process but the set of transferred proteins and their effects in the receiving cells remain unclear. This study aimed to detect the intercellular protein transfer from mouse bone marrow stromal cells (OP9 cell line) to human T-lymphoblasts (CCRF-CEM cell line) using nanoLC-MS/MS-based shotgun proteomics in a 3D co-culture system. After 24 h of co-culture, 1513 and 67 proteins from human and mouse origin, respectively, were identified in CCRF-CEM cells. The presence of mouse proteins in the human cell line, detected by analyzing the differences in amino acid sequences of orthologous peptides, was interpreted as the result of intercellular transfer. The transferred proteins might have contributed to the observed resistance to vincristine, methotrexate, and hydrogen peroxide in the co-cultured leukemic cells. Our results suggest that shotgun proteomic analyses of co-cultured cells from different species could be a simple option to get a preliminary survey of the proteins exchanged among interacting cells.

Clinical application of serum-based proteomics technology in human tumor research

The rapid development of proteomics technology in the past decades has led to further human understanding of tumor research, and in some ways, the technology plays a very important supporting role in the early detection of tumors. Human serum has been shown to contain a variety of proteins closely related to life activities, and the dynamic change in proteins can often reflect the physiological and pathological conditions of the body. Serum has the advantage of easy extraction, so the application of proteomics technology in serum has become a hot spot and frontier area for the study of malignant tumors. However, there are still many difficulties in the standardized use of proteomic technologies, which inevitably limit the clinical application of proteomic technologies due to the heterogeneity of human proteins leading to incomplete whole proteome populations, in addition to most serum protein markers being now not highly specific in aiding the early detection of tumors. Nevertheless, further development of proteomics technologies will greatly increase our understanding of tumor biology and help discover more new tumor biomarkers with specificity that will enable medical technology.

Proteomics in Inherited Metabolic Disorders

Inherited metabolic disorders (IMD) are rare medical conditions caused by genetic defects that interfere with the body's metabolism. The clinical phenotype is highly variable and can present at any age, although it more often manifests in childhood. The number of treatable IMDs has increased in recent years, making early diagnosis and a better understanding of the natural history of the disease more important than ever. In this review, we discuss the main challenges faced in applying proteomics to the study of IMDs, and the key advances achieved in this field using tandem mass spectrometry (MS/MS). This technology enables the analysis of large numbers of proteins in different body fluids (serum, plasma, urine, saliva, tears) with a single analysis of each sample, and can even be applied to dried samples. MS/MS has thus emerged as the tool of choice for proteome characterization and has provided new insights into many diseases and biological systems. In the last 10 years, sequential window acquisition of all theoretical fragmentation spectra mass spectrometry (SWATH-MS) has emerged as an accurate, high-resolution technique for the identification and quantification of proteins differentially expressed between healthy controls and IMD patients. Proteomics is a particularly promising approach to help obtain more information on rare genetic diseases, including identification of biomarkers to aid early diagnosis and better understanding of the underlying pathophysiology to guide the development of new therapies. Here, we summarize new and emerging proteomic technologies and discuss current uses and limitations of this approach to identify and quantify proteins. Moreover, we describe the use of proteomics to identify the mechanisms regulating complex IMD phenotypes; an area of research essential to better understand these rare disorders and many other human diseases.

Surrogate peptide selection and internal standardization for accurate quantification of endogenous proteins

Relative quantification techniques have dominated the field of proteomics. However, biomarker discovery, mathematical model development and studies on transporter-mediated drug disposition still need absolute quantification of proteins. The quality of data of trace-level protein quantification is solely dependent on the specific selection of surrogate peptides. Selection of surrogate peptides has a major impact on the accuracy of the method. In this article, the advanced approaches for selection of surrogate peptides, which can provide absolute quantification of the proteins are discussed. In addition, internal standardization, which accounts for variations in the quantitation process to achieve absolute protein quantification is discussed.

Targeted Proteomics for Monitoring One-Carbon Metabolism in Liver Diseases

Liver diseases cause approximately 2 million deaths per year worldwide and had an increasing incidence during the last decade. Risk factors for liver diseases include alcohol consumption, obesity, diabetes, the intake of hepatotoxic substances like aflatoxin, viral infection, and genetic determinants. Liver cancer is the sixth most prevalent cancer and the third in mortality (second in males). The low survival rate (less than 20% in 5 years) is partially explained by the late diagnosis, which remarks the need for new early molecular biomarkers. One-carbon metabolism integrates folate and methionine cycles and participates in essential cell processes such as redox homeostasis maintenance and the regulation of methylation reactions through the production of intermediate metabolites such as cysteine and S-Adenosylmethionine. One-carbon metabolism has a tissue specific configuration, and in the liver, the participating enzymes are abundantly expressed—a requirement to maintain hepatocyte differentiation. Targeted proteomics studies have revealed significant differences in hepatocellular carcinoma and cirrhosis, suggesting that monitoring one-carbon metabolism enzymes can be useful for stratification of liver disease patients and to develop precision medicine strategies for their clinical management. Here, reprogramming of one-carbon metabolism in liver diseases is described and the role of mass spectrometry to follow-up these alterations is discussed.

Effective Diagnosis of Prostate Cancer Based on mRNAs From Urinary Exosomes

Background

Novel non-invasive biomarkers are urgently required to improve the diagnostic sensitivity and specificity of prostate cancer (PCa). Therefore, the diagnostic value of following candidate genes (ERG, PCA3, ARV7, PSMA, CK19, and EpCAM) were estimated by testing mRNAs from urinary exosomes of patients with primary PCa.

Methods

Exosomes were obtained using size-exclusion chromatography (SEC), out of which RNAs were extracted, then analyzed by quantitative reverse transcription-polymerase chain reaction according to manufacturer's protocol.

Results

The expression of urinary exosomal ERG, PCA3, PSMA, CK19, and EpCAM were significantly increased in patients with PCa compared with healthy males. In addition, the levels of urinary exosomal ERG, ARV7, and PSMA were intimately correlated with the Gleason score in PCa patients (P < 0.05). The receiver operating characteristic curves (ROCs) showed that urinary exosomal ERG, PCA3, PSMA, CK19, and EpCAM were able to distinguish patients with PCa from healthy individuals with the area under the curve (AUC) of 0.782, 0.783, 0.772, 0.731, and 0.739, respectively. Urinary exosomal PCA3 and PSMA distinguished PCa patients from healthy individuals with an AUC of 0.870. Combination of urinary exosomal PCA3, PSMA with serum PSA and PI-RADS achieved higher AUC compared with PSA alone (0.914 and 0.846, respectively). Kaplan-Meier curves demonstrated that PCA3, ARV7, and EpCAM were associated in androgen-deprivation therapy (ADT) failure time which is defined as from the initiation of ADT in hormone-sensitive stage to the development of castration-resistant prostate cancer.

Conclusion

These findings suggested that mRNAs from urinary exosomes have the potential in serving as novel and non-invasive indicators for PCa diagnosis and prediction.

Application of Proteomics in the Discovery of Radiosensitive Cancer Biomarkers

Radiation therapy remains an important component of cancer treatment. Gene-encoded proteins were the actual executors of cellular functions. Proteomic was a novel technology that can systematically analysis protein composition and measure their levels of change, this was a high throughput method, and were the import tools in the post genomic era. In recent years, rapid progress of proteomic have been made in the study of cancer mechanism, diagnosis, and treatment. This article elaborates current advances and future directions of proteomics in the discovery of radiosensitive cancer biomarkers.

Targeted liquid chromatography-tandem mass spectrometry analysis of proteins: Basic principles, applications, and perspectives

Liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) is now the main analytical method for the identification and quantification of peptides and proteins in biological samples. In modern research, identification of biomarkers and their quantitative comparison between samples are becoming increasingly important for discovery, validation, and monitoring. Such data can be obtained following specific signals after fragmentation of peptides using multiple reaction monitoring (MRM) and parallel reaction monitoring (PRM) methods, with high specificity, accuracy, and reproducibility. In addition, these methods allow measurement of the amount of post-translationally modified forms and isoforms of proteins. This review article describes the basic principles of MRM assays, guidelines for sample preparation, recent advanced MRM-based strategies, applications and illustrative perspectives of MRM/PRM methods in clinical research and molecular biology.

Development of a multiplex mass spectrometry method for simultaneous quantification of urinary proteins related to respiratory health

Respiratory health of children is a health priority. Club cell protein (CC16) is an interesting biomarker of lung diseases and adverse effects towards the airway epithelium integrity. Osteopontin (OPN) and nuclear factor-kappa B (NF-κB) also play a role in respiratory health. The use of urine as biomarker source is useful in studies involving children but necessitates proper adjustment for physiological confounders influencing the urinary excretion, potentially characterized with beta-2-microglobulin (β2M), retinol binding protein 4 (RBP4) or myoglobin (MYO), as well as adjustment for possible renal dysfunction, characterized by human serum albumin (HSA). The simultaneous quantification of all these proteins in urine could facilitate children's health monitoring. A multiple reaction monitoring method (MRM) was developed and validated for the relative quantification of the seven mentioned urinary proteins. A total of nine proteotypic peptides were selected and used for the relative quantification of the seven proteins. The MRM method was completely validated for all proteins and partially for OPN. LOQ's ranged from 0.3 to 42.8 ng/ml, a good reproducibility and a good linearity were obtained across the analytical measurement range (r² > 0.98). The method yielded varying correlations (r² of 0.78, 0.71, 0.34 and 0.15 for CC16, β2M, RBP4 and HSA respectively) with available immunoassay data. It also allowed the identification and successful quantification of β2M and RBP4 as a protein candidate for adjustment of renal handling and dysfunction. All proteins were detected in the urine samples except for MYO and NF-κB. Our validated MRM-method is able to simultaneously quantify in urine biomarkers of airway epithelium integrity and biomarkers of variation in renal function and urinary dilution. This will allow to investigate further in future studies if urine can be used as a good surrogate source for biomarkers of airway epithelium integrity, and to understand the complex relationship between cause and effect in children's respiratory health monitoring.

Proteomics applications in biomarker discovery and pathogenesis for abdominal aortic aneurysm

Introduction: Abdominal aortic aneurysm (AAA) is a common, complex, and life-threatening disease. Currently, the pathogenesis of AAA is not well understood. No biomarkers or specific drugs are available for AAA in clinical applications. Proteomics is a powerful tool in biomarker discovery, exploration of pathogenesis, and drug target identification.Areas covered: We review the application of mass spectrometry-based proteome analysis in AAA patients within the last ten years. Differentially expressed proteins associated with AAA were identified in multiple sample sources, including vascular tissue, intraluminal thrombus, tissue secretome, blood, and cells. Some potential disease biomarkers, pathogenic mechanisms, or therapeutic targets for AAA were discovered using proteome analysis. The challenges and prospects of proteomics applied to AAA are also discussed.Expert opinion: Since most of the previous proteomic studies used relatively small sample sizes, some promising biomarkers need to be validated in multicenter cohorts to accelerate their clinical application. With the rapid development of mass spectrometry technology, modification-specific proteomics and multi-omics research in the future will enhance our understanding of the pathogenesis of AAA and promote biomarker discovery and drug development for clinical translation.

Application of Advanced Mass Spectrometry-Based Proteomics to Study Hypoxia Driven Cancer Progression

Cancer is one of the largest contributors to the burden of chronic disease in the world and is the second leading cause of death globally. It is associated with episodes of low-oxygen stress (hypoxia or ischemia/reperfusion) that promotes cancer progression and therapeutic resistance. Efforts have been made in the past using traditional proteomic approaches to decipher oxygen deprivation stress-related mechanisms of the disease initiation and progression and to identify key proteins as a therapeutic target for the treatment and prevention. Despite the potential benefits of proteomic in translational research for the discovery of new drugs, the therapeutic outcome with this approach has not met expectations in clinical trials. This is mainly due to the disease complexity which possess a multifaceted molecular pathology. Therefore, novel strategies to identify and characterize clinically important sets of modulators and molecular events for multi-target drug discovery are needed. Here, we review important past and current studies on proteomics in cancer with an emphasis on recent pioneered labeling approaches in mass spectrometry (MS)-based systematic quantitative analysis to improve clinical success. We also discuss the results of the selected innovative publications that integrate advanced proteomic technologies (e.g. MALDI-MSI, pSILAC/SILAC/iTRAQ/TMT-LC-MS/MS, MRM-MS) for comprehensive analysis of proteome dynamics in different biosystems, including cell type, cell species, and subcellular proteome (i.e. secretome and chromatome). Finally, we discuss the future direction and challenges in the application of these technological advancements in mass spectrometry within the context of cancer and hypoxia.

Novel biomarkers in cats with congestive heart failure due to primary cardiomyopathy

The pathogenesis of feline cardiomyopathy and congestive heart failure (CHF) requires further understanding. In this study, we assessed serum proteome change in feline CHF, aiming to identify novel biomarker for both research and clinical use. The study comprised 15 cats in CHF, 5 cats in preclinical cardiomyopathy and 15 cats as healthy controls. Serum proteome profiles were obtained by tandem mass tag labelling followed by mass spectrometry. Protein concentrations in CHF cats were compared with healthy controls. Western blot was performed for proteomic validation. Correlations were assessed between the altered proteins in CHF and clinical variables in cats with cardiomyopathy to evaluate protein-cardiac association. Bioinformatic analysis was employed to identify pathophysiological pathways involved in feline CHF. Sixteen serum proteins were significantly different between CHF and healthy control cats (P < .05). These included serine protease inhibitors, apolipoproteins and other proteins associated with inflammation and coagulation. Clinical parameters from cats with cardiomyopathy significantly correlated with the altered proteins (P < .05). Bioinformatic analysis identified 13 most relevant functional profiles in feline CHF, which mostly associated with extracellular matrix organization and metabolism. Data are available via ProteomeXchange with identifier PXD017761. SIGNIFICANCE: Cardiomyopathies affect both cats and humans, and they can cause serious consequence such as congestive heart failure (CHF). To date, the pathophysiological mechanism of CHF is not fully understood. In this study, for the first time, we used a proteomic approach combined with bioinformatic analysis to evaluate serum protein change in cats with CHF. Results indicate systemic inflammation, coagulation protein changes, innate immunity and extracellular matrix remodeling are involved in feline CHF, which are largely comparable with findings in previous human studies. Our study provides new insights into CHF and cardiomyopathy in cats, and the identified novel biomarkers and pathophysiological pathways provide valuable information for future studies.

Profiling tear proteomes of patients with unilateral relapsed Behcet's disease-associated uveitis using data-independent acquisition proteomics

Purpose

To explore whether unilateral relapse of Bechet’s disease-associated uveitis (BDU) causes differences in the tear proteome between the diseased and the contralateral quiescent eye and potential tear biomarkers for uveitis recurrence and disease monitoring.

Method

To minimize interindividual variations, bilateral tear samples were collected from the same patient (n = 15) with unilateral relapse of BDU. A data-independent acquisition (DIA) strategy was used to identify proteins that differed between active and quiescent eyes.

Results

A total of 1,797 confident proteins were identified in the tear samples, of which 381 (21.2%) were also highly expressed in various tissues and organs. Fifty-one (2.8%) proteins differed in terms of expression between tears in active and quiescent eyes, 9 (17.6%) of which were functionally related to immunity or inflammation. Alpha-1-acid glycoprotein 1 (fold change = 3.2, p = 0.007) was increased and Annexin A1 (fold change = −1.7, p < 0.001) was decreased in the tears of the active BDU eye compared to the contralateral quiescent eye.

Conclusions

A substantial amount of confident proteins were detected in the tears of BDU patients, including proteins that were deferentially expressed in the uveitis-relapsed eyes and the contralateral quiescent eyes. Some of these identified tear proteins play important roles in immune and inflammatory processes. Tear proteome might be a good source of biomarkers for uveitis.

Multiplexed MRM-based protein quantification of putative prognostic biomarkers for chronic kidney disease progression in plasma

Current diagnostic measures for Chronic Kidney Disease (CKD) include detection of reduced estimated glomerular filtration rate (eGFR) and albuminuria, which have suboptimal accuracies in predicting disease progression. The disease complexity and heterogeneity underscore the need for multiplex quantification of different markers. The goal of this study was to determine the association of six previously reported CKD-associated plasma proteins [B2M (Beta-2-microglobulin), SERPINF1 (Pigment epithelium-derived factor), AMBP (Protein AMBP), LYZ (Lysozyme C), HBB (Hemoglobin subunit beta) and IGHA1 (Immunoglobulin heavy constant alpha 1)], as measured in a multiplex format, with kidney function, and outcome. Antibody-free, multiple reaction monitoring mass spectrometry (MRM) assays were developed, characterized for their analytical performance, and used for the analysis of 72 plasma samples from a patient cohort with longitudinal follow-up. The MRM significantly correlated (Rho = 0.5–0.9) with results from respective ELISA. Five proteins [AMBP, B2M, LYZ, HBB and SERPINF1] were significantly associated with eGFR, with the three former also associated with unfavorable outcome. The combination of these markers provided stronger associations with outcome (p < 0.0001) compared to individual markers. Collectively, our study describes a multiplex assay for absolute quantification and verification analysis of previously described putative CKD prognostic markers, laying the groundwork for further use in prospective validation studies.

Applications of multiple reaction monitoring targeted proteomics assays in human plasma

Introduction: Multiple (or selected) reaction monitoring-mass spectrometry (MRM/SRM) is a targeted proteomic method that can be used for relative and absolute quantification. Multiple reports exist supporting the potential of the approach in proteomic biomarker validation. Areas covered: To get an overview of the applications of MRM in protein quantification in plasma, a search in MedLine/PubMed was performed using the keywords: 'MRM/SRM plasma proteomic/proteomics/proteome'. The retrieved studies were further filtered to focus on disease biomarkers and the main results are summarized. Expert opinion: MRM is increasingly employed for the quantification of both well-established but also newly discovered putative biomarkers and occasionally their post-translationally modified forms in plasma. Fractionation is regularly required for the detection of low abundance proteins. Standardized procedures to facilitate assay establishment and marker quantification have been proposed and, in few cases, implemented. Nevertheless, in most cases, absolute quantification is not performed. To advance, multiple technical issues including the regular use of standard labeled peptides and appropriate quality controls to monitor assay performance should be considered. Additionally, clinical aspects involving careful study design to address biomarker clinical use should also be considered.

Development and Validation of Multiple Reaction Monitoring (MRM) Assays for Clinical Applications

Selected/multiple reaction monitoring-mass spectrometry (SRM/MRM) is an analytical method that is frequently combined to the use of stable isotope-labeled standard (SIS) peptides for absolute protein quantification. The application of SRM/MRM is a relatively recent development in the proteomics field for analysis of biological samples (plasma, urine, cell/tissue lysates) targeting to a large extent biomarker validation. Although MRM generally by-passes the use of antibodies (being linked to sub-optimal assay specificity in many cases), bioanalytical validation of MRM protocols has not been robustly applied because of sensitivity issues, in contrary to antibody-based methods. In this chapter, we will discuss the points that should be addressed for MRM method development in clinical proteomics applications.

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.

Clinical Proteomics: Closing the Gap from Discovery to Implementation

Clinical proteomics, the application of proteome analysis to serve a clinical purpose, represents a major field in the area of proteome research. Over 1000 manuscripts on this topic are published each year, with numbers continuously increasing. However, the anticipated outcome, the transformation of the reported findings into improvements in patient management, is not immediately evident. In this article, the value and validity of selected clinical proteomics findings are investigated, and it is assessed how far implementation has progressed. A main conclusion from this assessment is that to achieve implementation, well-powered clinical studies are required in the appropriate population, addressing a specific clinical need and with a clear context-of-use. Efforts toward implementation, to be feasible, must be supported by the key players in science: publishers and funders. The authors propose a change on objectives, from additional discovery studies toward studies aiming at validation of the plethora of potential biomarkers that have been described, to demonstrate practical value of clinical proteomics. All elements required, potential biomarkers, technologies, and bio-banked samples are available (based on today's literature), hence a change in focus from discovery toward validation and application is not only urgently necessary, but also possible based on resources available today.

Breaking the ice: urine proteomics of medullary sponge kidney disease

Urinary proteomics is a promising tool for biomarker investigation, particularly in complex kidney diseases. Fabris and colleagues report that urinary laminin subunit alpha-2 is a potential diagnostic marker of medullary sponge kidney (MSK) disease by using a label-free quantitative proteomics platform and a clinically compatible enzyme-linked immunosorbent assay. The neglected issue of stone pathogenesis was also evidenced. This commentary discusses several considerations in biomarker validation, and how urinary proteomics breaks new ground in MSK research.

Quantitation of peptides from non-invasive skin tapings using isotope dilution and tandem mass spectrometry

Previous work from our laboratories utilized a novel skin taping method and mass spectrometry-based proteomics to discover clinical biomarkers of skin conditions; these included atopic dermatitis, Staphylococcus aureus colonization, and eczema herpeticum. While suitable for discovery purposes, semi-quantitative proteomics is generally time-consuming and expensive. Furthermore, depending on the method used, discovery-based proteomics can result in high variation and inadequate sensitivity to detect low abundant peptides. Therefore, we strove to develop a rapid, sensitive, and reproducible method to quantitate disease-related proteins from skin tapings. We utilized isotopically-labeled peptides and tandem mass spectrometry to obtain absolute quantitation values on 14 peptides from 7 proteins; these proteins had shown previous importance in skin disease. The method demonstrated good reproducibility, dynamic range, and linearity (R² > 0.993) when n = 3 standards were analyzed across 0.05-2.5 pmol. The method was used to determine if differences exist between skin proteins in a small group of atopic versus non-atopic individuals (n = 12). While only minimal differences were found, peptides were detected in all samples and exhibited good correlation between peptides for 5 of the 7 proteins (R² = 0.71-0.98). This method can be applied to larger cohorts to further establish the relationships of these proteins to skin disease.

Needle lost in the haystack: multiple reaction monitoring fails to detect Treponema pallidum candidate protein biomarkers in plasma and urine samples from individuals with syphilis

Background: Current syphilis diagnostic strategies are lacking a sensitive manner of directly detecting Treponema pallidum antigens. A diagnostic test that could directly detect T. pallidum antigens in individuals with syphilis would be of considerable clinical utility, especially for the diagnosis of reinfections and for post-treatment serological follow-up.

Methods: In this study, 11 candidate T. pallidum biomarker proteins were chosen according to their physiochemical characteristics, T. pallidum specificity and predicted abundance. Thirty isotopically labelled proteotypic surrogate peptides (hPTPs) were synthesized and incorporated into a scheduled multiple reaction monitoring assay. Protein extracts from undepleted/unenriched plasma (N = 18) and urine (N = 4) samples from 18 individuals with syphilis in various clinical stages were tryptically digested, spiked with the hPTP mixture and analysed with a triple quadruple mass spectrometer.

Results: No endogenous PTPs corresponding to the eleven candidate biomarkers were detected in any samples analysed. To estimate the Limit of Detection (LOD) of a comparably sensitive mass spectrometer (LTQ-Orbitrap), two dilution series of rabbit cultured purified T. pallidum were prepared in PBS. Polyclonal anti- T. pallidum antibodies coupled to magnetic Dynabeads were used to enrich one sample series; no LOD improvement was found compared to the unenriched series. The estimated LOD of MS instruments is 300 T. pallidum/ml in PBS.

Conclusions: Biomarker protein detection likely failed due to the low (femtomoles/liter) predicted concentration of T. pallidum proteins. Alternative sample preparation strategies may improve the detectability of T. pallidum proteins in biofluids.

Biomarkers of Duchenne muscular dystrophy: current findings

Numerous biomarkers have been unveiled in the rapidly evolving biomarker discovery field, with an aim to improve the clinical management of disorders. In rare diseases, such as Duchenne muscular dystrophy, this endeavor has created a wealth of knowledge that, if effectively exploited, will benefit affected individuals, with respect to health care, therapy, improved quality of life and increased life expectancy. The most promising findings and molecular biomarkers are inspected in this review, with an aim to provide an overview of currently known biomarkers and the technological developments used. Biomarkers as cells, genetic variations, miRNAs, proteins, lipids and/or metabolites indicative of disease severity, progression and treatment response have the potential to improve development and approval of therapies, clinical management of DMD and patients’ life quality. We highlight the complexity of translating research results to clinical use, emphasizing the need for biomarkers, fit for purpose and describe the challenges associated with qualifying biomarkers for clinical applications.

Quantification of Cardiovascular Disease Biomarkers in Human Platelets by Targeted Mass Spectrometry

Platelets are known to be key players in thrombosis and hemostasis, contributing to the genesis and progression of cardiovascular diseases. Due to their pivotal role in human physiology and pathology, platelet function is regulated tightly by numerous factors which have either stimulatory or inhibitory effects. A variety of factors, e.g., collagen, fibrinogen, ADP, vWF, thrombin, and thromboxane promote platelet adhesion and aggregation by utilizing multiple intracellular signal cascades. To quantify platelet proteins for this work, a targeted proteomics workflow was applied. In detail, platelets are isolated and lyzed, followed by a tryptic protein digest. Subsequently, a mix of stable isotope-labeled peptides of interesting biomarker proteins in concentrations ranging from 0.1 to 100 fmol is added to 3 μg digest. These peptides are used as an internal calibration curve to accurately quantify endogenous peptides and corresponding proteins in a pooled platelet reference sample by nanoLC-MS/MS with parallel reaction monitoring. In order to assure a valid quantification, limit of detection (LOD) and limit of quantification (LOQ), as well as linear range, were determined. This quantification of platelet activation and proteins by targeted mass spectrometry may enable novel diagnostic strategies in the detection and prevention of cardiovascular diseases.

Identification of temperature regulated factors of Campylobacter jejuni and their potential roles in virulence

Campylobacter jejuni is the major cause of bacterial gastroenteritis in man, while it is generally regarded as a commensal of the avian gut. Consumption and handling of contaminated poultry meat products are major risk factors for human infection. The body temperature in man (37 °C) and chickens (42 °C) differ markedly, and differential gene regulation and protein expression at different temperatures may in part explain the behaviour in the two hosts. We performed proteomics analyses with C. jejuni cells grown at 37 °C and 42 °C. Time-of-flight mass spectrometry (Q-Tof) analysis was carried out after samples were digested with the Filter-Aided Sample Preparation (FASP) method and peptides were fractionated by strong anion exchanges. Differentially regulated proteins were identified by Mascot and Scaffold analyses. Triple quadrupole (QQQ) mass spectrometer analysis confirmed that a total of 33 proteins were differentially regulated between 37 °C and 42 °C. Several upregulated proteins were selected for their corresponding gene knock-out mutants to be tested for their virulence in the Galleria mellonella model. To correlate with other tissue/animal models, the GADH mutant was selected for its reduced ability to colonize chickens. At 37 °C, the mutants of outer membrane protein Omp50 and Chaperone GroEL significantly increased virulence; while at 42 °C, the mutants of YceI, Omp50, and GADH reduced virulence against Galleria mellonella compared with the wild type strains. The results of current and previous studies indicate that GADH is a virulent factor in G. mellonella and a colonization factor in chickens. The workflow of this study may prove a new way to identify stress related virulent factors. The implications of these findings are discussed for pathogenesis in the model and other hosts.

MiR-145 detection in urinary extracellular vesicles increase diagnostic efficiency of prostate cancer based on hydrostatic filtration dialysis method

BACKGROUND

Extracellular vesicles (EVs) can be detected in body fluids and may serve as disease biomarkers. Increasing evidence suggests that circulating miRNAs in serum and urine may be potential non-invasive biomarkers for prostate cancer (PCa). In the present study, we aimed to investigate whether hydrostatic filtration dialysis (HFD) is suitable for urinary EVs (UEVs) isolation and whether such reported PCa-related miRNAs can be detected in UEVs as PCa biomarkers.

METHODS

To analyze EVs miRNAs, we searched for an easy and economic method to enrich EVs from urine samples. We compared the efficiency of HFD method and conventional ultracentrifugation (UC) in isolating UEVs. Subsequently, UEVs were isolated from patients with PCa, patients with benign prostate hyperplasia (BPH) and healthy individuals. Differential expression of four PCa-related miRNAs (miR-572, miR-1290, miR-141, and miR-145) were measured in UEVs and paired serum EVs using SYBR Green-based quantitative reverse transcription-polymerase chain reaction (qRT-PCR).

RESULTS

The overall performance of HFD was similar to UC. In miRNA yield, both HFD and UC can meet the needs of further analysis. The level of miR-145 in UEVs was significantly increased in patients with PCa compared with the patients with BPH (P = 0.018). In addition, significant increase was observed in miR-145 levels when patients with Gleason score ≥8 tumors compared with Gleason score ≤7 (P = 0.020). Receiver-operating characteristic curve (ROC) revealed that miR-145 in UEVs combined with serum PSA could differentiate PCa from BPH better than PSA alone (AUC 0.863 and AUC 0.805, respectively). In serum EVs, four miRNAs were significantly higher in patients with PCa than with BPH.

CONCLUSION

HFD is appropriate for UEVs isolation and miRNA analysis when compared with conventional UC. miR-145 in UEVs is upregulated from PCa patients compared BPH patients and healthy controls. We suggest the potential use of UEVs miR-145 as a biomarker of PCa.

Current trends in quantitative proteomics - an update

Proteins can provide insights into biological processes at the functional level, so they are very promising biomarker candidates. The quantification of proteins in biological samples has been routinely used for the diagnosis of diseases and monitoring the treatment. Although large-scale protein quantification in complex samples is still a challenging task, a great amount of effort has been made to advance the technologies that enable quantitative proteomics. Seven years ago, in 2009, we wrote an article about the current trends in quantitative proteomics. In writing this current paper, we realized that, today, we have an even wider selection of potential tools for quantitative proteomics. These tools include new derivatization reagents, novel sampling formats, new types of analyzers and scanning techniques, and recently developed software to assist in assay development and data analysis. In this review article, we will discuss these innovative methods, and their current and potential applications in proteomics. Copyright © 2017 John Wiley & Sons, Ltd.

Urinary biomarkers for renal tract malformations

INTRODUCTION

Renal tract malformations (RTMs) are congenital anomalies of the kidneys and urinary tract, which are the major cause of end-stage renal disease in children. Using immunoassay-based approaches (ELISA, western blot), individual urinary proteins including transforming growth factor β, tumor necrosis factor and monocyte attractant proteins 1 were found to be associated to RTMs. However, only mass spectrometry (MS) based methods leading to the identification of panels of protein-based markers composed of fragments of the extracellular matrix allowed the prediction of progression of RTMs and its complications. Areas covered: In this review, we summarized relevant studies identified in "Pubmed" using the keywords "urinary biomarkers" and "proteomics" and "renal tract malformations" or "hydronephrosis" or "ureteropelvic junction obstruction" or "posterior urethral valves" or "vesicoureteral reflux". These publications represent studies on potential protein-based biomarkers, either individually or combined in panels, of RTMs in human and animal models. Expert commentary: Successful use in the clinic of these protein-based biomarkers will need to involve larger scale studies to reach sufficient power. Improved performance will potentially come from combining immunoassay- and MS-based markers.

Exosomal proteins as prostate cancer biomarkers in urine: From mass spectrometry discovery to immunoassay-based validation

Exosomes have recently appeared as a novel source of non-invasive cancer biomarkers since tumor-specific molecules can be found in exosomes isolated from biological fluids. We have previously analyzed the proteome of urinary exosomes by mass spectrometry, and identified proteins differentially expressed in prostate cancer patients compared to healthy males. Since mass spectrometry is so far not commonly used in clinical laboratories, we have here investigated whether antibody-based methods such as Western blot or ELISA can be used to validate the use of the identified proteins as prostate cancer biomarkers. Western blot experiments designed to detect flotillin 2, TMEM256, Rab3B and LAMTOR1 showed that the level of these proteins was higher in urinary exosomes from prostate cancer patients compared to healthy males. Furthermore, a receiver operating characteristic curve of flotillin 2 in samples from 16 controls and 16 patients showed an area under the curve of 0.91, and 88% sensitivity at a threshold set to give 94% specificity. In addition, ELISA-based detection of flotillin 2 and PARK7 showed that the combination of these proteins was able to distinguish prostate cancer patients and healthy controls with 68% sensitivity and 93% specificity. Several promising biomarkers identified by mass spectrometry could not be evaluated by Western blot or ELISA due to their low exosomal amount and/or lack of good antibodies. In conclusion, our results show that several urinary exosomal proteins identified as prostate cancer biomarkers by mass spectrometry have a high diagnostic value also when analyzed by immunology-based methods, thus bringing these biomarkers closer to a potential clinical use.

Proteomics for prediction of disease progression and response to therapy in diabetic kidney disease

The past decade has resulted in multiple new findings of potential proteomic biomarkers of diabetic kidney disease (DKD). Many of these biomarkers reflect an important role in the (patho)physiology and biological processes of DKD. Situations in which proteomics could be applied in clinical practice include the identification of individuals at risk of progressive kidney disease and those who would respond well to treatment, in order to tailor therapy for those at highest risk. However, while many proteomic biomarkers have been discovered, and even found to be predictive, most lack rigorous external validation in sufficiently powered studies with renal endpoints. Moreover, studies assessing short-term changes in the proteome for therapy-monitoring purposes are lacking. Collaborations between academia and industry and enhanced interactions with regulatory agencies are needed to design new, sufficiently powered studies to implement proteomics in clinical practice.

Urine proteome analysis as a discovery tool in patients with deep vein thrombosis and pulmonary embolism

PURPOSE

Early and accurate detection of deep vein thrombosis (DVT) is an important clinical need. Based on the hypothesis that urinary peptides may hold information on DVT in conjunction with pulmonary embolism (PE), the study was aimed at identifying such peptide biomarkers using capillary electrophoresis coupled mass spectrometry.

EXPERIMENTAL DESIGN

Patients with symptoms of unprovoked/idiopathic DVT and/or PE were examined by doppler-sonography or angio-computed tomography. Urinary proteome analysis allowed for identification of respective peptide biomarkers. To confirm their biological relevance, we induced PE in mice and assessed human ex vivo thrombi.

RESULTS

We identified 62 urinary peptides as DVT-specific biomarkers, i.e. fragments of collagen type I and a fragment of fibrinogen β-chain. The presence of fibrinogen α/β in the acute thrombus, and collagen type I and osteopontin in the older, organized thrombus was demonstrated. The classifier DVT62 established through support vector machine (SVM) modeling based on the 62 identified peptides was validated in an independent cohort of 47 subjects (six cases and 41 controls) with a sensitivity of 100% and specificity of 83%.

CONCLUSIONS AND CLINICAL RELEVANCE

Urine proteome analysis enabled the detection of DVT-specific peptides, which were validated in human and mouse tissue. Furthermore, it allowed for the establishment of an urinary-proteome based classifier that is relatively specific for DVT. The data provide the basis for assessment of these biomarkers in a prospective clinical study.