How shall we use the proteomics toolbox for biomarker discovery?

Proteomic analysis of serum extracellular vesicles reveals Fibulin-3 as a new marker predicting liver-related events in MASLD

BACKGROUND

There is a need for novel noninvasive markers for metabolic dysfunction-associated steatotic liver disease (MASLD) to stratify patients at high risk for liver-related events including liver cancer and decompensation. In the present study, we used proteomic analysis of proteins in extracellular vesicles (EVs) to identify new biomarkers that change with fibrosis progression and can predict the development of liver-related events.

METHODS

We analyzed serum EVs from 50 patients with MASLD assessed for liver fibrosis by biopsy and identified proteins that altered with advanced fibrosis. A further evaluation was conducted on another cohort of 463 patients with MASLD with biopsy.

RESULTS

Eight candidate proteins were identified by proteomic analysis of serum EVs. Among them, serum levels of Fibulin-3, Fibulin-1, and Ficolin 1 correlated with their EV levels. In addition, serum Fibulin-3 and serum Fibulin-1 levels changed significantly with advanced fibrosis. Using another cohort with biopsy, we found that the serum Fibulin-3 concentration was significantly greater in those with advanced fibrosis but that the serum Fibulin-1 concentration was not significantly different. Multivariate Cox proportional hazards analysis revealed that a higher Fibrosis-4 (FIB-4) index and higher serum Fibulin-3 concentration were independent risk factors for liver-related events. When the cutoff value for the serum Fibulin-3 concentration was 6.0 µg/mL according to the Youden index of AUROCs, patients with high serum Fibulin-3 significantly more frequently developed liver-related events than did other patients. Validation using another cohort of 226 patients with clinically diagnosed MASLD confirmed that high serum Fibulin-3 levels are associated with a greater frequency of liver-related events.

CONCLUSIONS

Serum Fibulin-3 was identified as a biomarker for predicting liver-related events in patients with MASLD.

Frontiers in Plasma Proteome Profiling Platforms: Innovations and Applications

Biomarkers play a crucial role in advancing precision medicine by enabling more targeted and individualized approaches to diagnosis and treatment. Various biofluids, including serum, plasma, cerebrospinal fluid (CSF), saliva, tears, pancreatic cyst fluids, and urine, have been identified as rich sources of potential for the early detection of disease biomarkers in conditions such as cancer, cardiovascular diseases, and neurodegenerative disorders. The analysis of plasma and serum in proteomics research encounters challenges due to their high complexity and the wide dynamic range of protein abundance. These factors impede the sensitivity, coverage, and precision of protein detection when employing mass spectrometry, a widely utilized technology in discovery proteomics. Conventional approaches such as neat plasma workflow are inefficient in accurately quantifying low-abundant proteins, including those associated with tissue leakage, immune response molecules, interleukins, cytokines, and interferons. Moreover, the manual nature of the workflow poses a significant hurdle in conducting large cohort studies. In this study, our focus is on comparing workflows for plasma proteomic profiling to establish a methodology that is not only sensitive and reproducible but also applicable for large cohort studies in biomarker discovery. Our investigation revealed that the SeerProteographXT workflow outperforms other workflows in terms of plasma proteome depth, quantitative accuracy, and reproducibility while offering complete automation of sample preparation. Notably, SeerProteographXT demonstrates versatility by applying it to various types of biofluids. Additionally, the proteins quantified widely cover secretory proteins in peripheral blood, and the pathway analysis enriched with relevant components such as interleukins, tissue necrosis factors, chemokines, and B and T cell receptors provides valuable insights. These proteins, often challenging to quantify in complex biological samples, hold potential as early detection markers for various diseases, thereby contributing to the improvement of patient care quality.

Proteomic Serum Profiling of Holstein Friesian Cows with Different Pathological Forms of Bovine Paratuberculosis Reveals Changes in the Acute-Phase Response and Lipid Metabolism

The lack of sensitive diagnostic methods to detect Mycobacterium avium subsp. paratuberculosis (Map) subclinical infections has hindered the control of paratuberculosis (PTB). The serum proteomic profiles of naturally infected cows presenting focal and diffuse pathological forms of PTB and negative controls (n = 4 per group) were analyzed using TMT-6plex quantitative proteomics. Focal and diffuse are the most frequent pathological forms in subclinical and clinical stages of PTB, respectively. One (focal versus (vs.) control), eight (diffuse vs. control), and four (focal vs. diffuse) differentially abundant (DA) proteins (q-value < 0.05) were identified. Ingenuity pathway analysis of the DA proteins revealed changes in the acute-phase response and lipid metabolism. Six candidate biomarkers were selected for further validation by specific ELISA using serum from animals with focal, multifocal, and diffuse PTB-associated lesions (n = 108) and controls (n = 56). Overall, the trends of the serum expression levels of the selected proteins were consistent with the proteomic results. Alpha-1-acid glycoprotein (ORM1)-based ELISA, insulin-like growth factor-binding protein 2 (IGFBP2)-based ELISA, and the anti-Map ELISA had the best diagnostic performance for detection of animals with focal, multifocal, and diffuse lesions, respectively. Our findings identify potential biomarkers that improve diagnostic sensitivity of PTB and help to elucidate the mechanisms involved in PTB pathogenesis.

Early Cancer Biomarker Discovery Using DIA-MS Proteomic Analysis of EVs from Peripheral Blood

One of the cornerstones of effective cancer treatment is early diagnosis. In this context, the identification of proteins that can serve as cancer biomarkers in bodily fluids ("liquid biopsies") has gained attention over the last decade. Plasma and serum fractions of blood are the most commonly investigated sources of potential cancer liquid biopsy biomarkers. However, the high complexity and dynamic range typical of these fluids hinders the sensitivity of protein detection by the most commonly used mass spectrometry technology (data-dependent acquisition mass spectrometry (DDA-MS)). Recently, data-independent acquisition mass spectrometry (DIA-MS) techniques have overcome the limitations of DDA-MS, increasing sensitivity and proteome coverage. In addition to DIA-MS, isolating extracellular vesicles (EVs) can help to increase the depth of serum/plasma proteome coverage by improving the identification of low-abundance proteins which are a potential treasure trove of diagnostic molecules. EVs, the nano-sized membrane-enclosed vesicles present in most bodily fluids, contain proteins which may serve as potential biomarkers for various cancers. Here, we describe a detailed protocol that combines DIA-MS and EV methodologies for discovering and validating early cancer biomarkers using blood serum. The pipeline includes size exclusion chromatography methods to isolate serum-derived extracellular vesicles and subsequent EV sample preparation for liquid chromatography and mass spectrometry analysis. Procedures for spectral library generation by DDA-MS incorporate methods for off-line peptide separation by microflow HPLC with automated fraction concatenation. Analysis of the samples by DIA-MS includes recommended protocols for data processing and statistical methods. This pipeline will provide a guide to discovering and validating EV-associated proteins that can serve as sensitive and specific biomarkers for early cancer detection and other diseases.

Extracellular Vesicle Membrane Protein Profiling and Targeted Mass Spectrometry Unveil CD59 and Tetraspanin 9 as Novel Plasma Biomarkers for Detection of Colorectal Cancer

Extracellular vesicles (EVs) are valuable sources for the discovery of useful cancer biomarkers. This study explores the potential usefulness of tumor cell-derived EV membrane proteins as plasma biomarkers for early detection of colorectal cancer (CRC). EVs were isolated from the culture supernatants of four CRC cell lines by ultracentrifugation, and their protein profiles were analyzed by LC-MS/MS. Bioinformatics analysis of identified proteins revealed 518 EV membrane proteins in common among at least three CRC cell lines. We next used accurate inclusion mass screening (AIMS) in parallel with iTRAQ-based quantitative proteomic analysis to highlight candidate proteins and validated their presence in pooled plasma-generated EVs from 30 healthy controls and 30 CRC patients. From these, we chose 14 potential EV-derived targets for further quantification by targeted MS assay in a separate individual cohort comprising of 73 CRC and 80 healthy subjects. Quantitative analyses revealed significant increases in ADAM10, CD59 and TSPAN9 levels (2.19- to 5.26-fold, p < 0.0001) in plasma EVs from CRC patients, with AUC values of 0.83, 0.95 and 0.87, respectively. Higher EV CD59 levels were significantly correlated with distant metastasis (p = 0.0475), and higher EV TSPAN9 levels were significantly associated with lymph node metastasis (p = 0.0011), distant metastasis at diagnosis (p = 0.0104) and higher TNM stage (p = 0.0065). A two-marker panel consisting of CD59 and TSPAN9 outperformed the conventional marker CEA in discriminating CRC and stage I/II CRC patients from healthy controls, with AUC values of 0.98 and 0.99, respectively. Our results identify EV membrane proteins in common among CRC cell lines and altered plasma EV protein profiles in CRC patients and suggest plasma EV CD59 and TSPAN9 as a novel biomarker panel for detecting early-stage CRC.

New advances in quantitative proteomics research and current applications in asthma

INTRODUCTION

Asthma is the most common chronic respiratory disease and has been declared a global public health problem by the World Health Organization. Due to the high heterogeneity and complexity, asthma can be classified into different 'phenotypes' and it is still difficult to assess the phenotypes and stages of asthma by traditional methods. In recent years, mass spectrometry-based proteomics studies have made significant progress in sensitivity and accuracy of protein identification and quantitation, and are able to obtain differences in protein expression across samples, which provides new insights into the mechanisms and classification of asthma.

AREAS COVERED

In this article, we summarize research strategies in quantitative proteomics, including labeled, label-free and targeted quantification, and highlight the advantages and disadvantages of each. In addition, new applications of quantitative proteomics and the current status of research in asthma have also been discussed. In this study, online resources such as PubMed and Google Scholar were used for literature retrieval.

EXPERT OPINION

The application of quantitative proteomics in asthma has an important role in identifying asthma subphenotypes, revealing potential pathogenesis and therapeutic targets. But the proteomic studies on asthma are not sufficient, as most of them are in the phase of biomarker discovery.

The Role of Neurophysiological Biomarkers in Obsessive-Compulsive Disorder

BACKGROUND

Obsessive-compulsive disorder is a highly debilitating psychiatric disorder with a high rate of treatment resistance. Biomarkers for obsessive-compulsive disorder may assist clinicians by predicting response to treatments and prognosis.

OBJECTIVE

To review the literature with regards to two of the more easily ascertainable and relatively inexpensive physiological biomarkers, i.e. heart rate variability and electroencephalography.

METHODS

Narrative review of the literature.

RESULTS

Decreased heart rate variability has been associated with increased symptom severity of obsessive-compulsive disorder. Findings from electroencephalography have also predicted response to pharmacotherapy and it is likely that biomarkers for OCD will have their greatest utility in predicting response to different pharmacological agents. However, the number of studies is small and results are inconsistent.

CONCLUSIONS

More research is required to determine whether heart rate variability and electrophysiological studies have a clinical role as biomarkers for obsessive-compulsive disorder.

Biological Behavior Regulation of Gold Nanoparticles via the Protein Corona

One of the difficulties in the translation of gold nanoparticles (GNPs) into clinical practice is the formation of the protein corona (PC) that causes the discrepancy between the in vitro and in vivo performance of GNPs. The PC formed on the surface of GNPs gives them a biological identity instead of an initial synthetic one. In most instances, this biological identity increases the particle size, leads to more clearance by the reticuloendothelial system, and causes less uptake by target cells. However, the performance of GNPs can still be improved by rewriting their original surface chemistry via the PC. This review specifically focuses on discussing the main influence factors, including the biological environment and physicochemical properties of GNPs, which affect the production and status of the PC. The status of the PC such as the amount, thickness, and composition subsequently influence the biological behavior of GNPs, especially their cellular uptake, cytotoxicity, biodistribution, and tumor targeting. Further understanding and revealing the impacts of the PC on the biological behavior of GNPs can be a promising and important strategy to regulate and improve the performance of GNP-based biosystems in the future.

Biomarkers in Psychiatry: Concept, Definition, Types and Relevance to the Clinical Reality

During the last years, an extraordinary effort has been made to identify biomarkers as potential tools for improving prevention, diagnosis, drug response and drug development in psychiatric disorders. Contrary to other diseases, mental illnesses are classified by diagnostic categories with a broad variety list of symptoms. Consequently, patients diagnosed from the same psychiatric illness present a great heterogeneity in their clinical presentation. This fact together with the incomplete knowledge of the neurochemical alterations underlying mental disorders, contribute to the limited efficacy of current pharmacological options. In this respect, the identification of biomarkers in psychiatry is becoming essential to facilitate diagnosis through the developing of markers that allow to stratify groups within the syndrome, which in turn may lead to more focused treatment options. In order to shed light on this issue, this review summarizes the concept and types of biomarkers including an operational definition for therapeutic development. Besides, the advances in this field were summarized and sorted into five categories, which include genetics, transcriptomics, proteomics, metabolomics, and epigenetics. While promising results were achieved, there is a lack of biomarker investigations especially related to treatment response to psychiatric conditions. This review includes a final conclusion remarking the future challenges required to reach the goal of developing valid, reliable and broadly-usable biomarkers for psychiatric disorders and their treatment. The identification of factors predicting treatment response will reduce trial-and-error switches of medications facilitating the discovery of new effective treatments, being a crucial step towards the establishment of greater personalized medicine.

Bottlenecks in Proteomics: An Update

Mass spectrometry (MS) is the core for advanced methods in proteomic experiments. When effectively used, proteomics may provide extensive information about proteins and their post-translational modifications, as well as their interaction partners. However, there are also many problems that one can encounter during a proteomic experiment, including, but not limited to sample preparation, sample fractionation, sample analysis, data analysis & interpretation and biological significance. Here we discuss some of the problems that researchers should be aware of when performing a proteomic experiment.

Personalized medicine: From diagnostic to adaptive

Personalized therapy has made great strides but suffers from the lack of companion diagnostics. With the dawn of extracellular vesicle (EV) based liquid biopsies fast approaching, this article proposes a novel approach to cancer treatment – adaptive therapy. Already being implemented in the field of radiation oncology, adaptive radiation therapy utilizes cutting-edge imaging techniques as a viable means to monitor a patient's tumor throughout the entire treatment cycle by adapting the dosage and alignment to match the dynamic tumor. Through an EV liquid biopsy, medical oncologists will also soon have the means to continuously monitor a patient's tumor as it changes over time. With this information, physicians will be able to “adapt” pre-planned therapies concurrently with the fluctuating tumor environment, thus creating a more precise personalized medicine. In this article, a theory for adaptive medicine and the current state of the field with an outlook on future challenges are discussed.

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.

Relative and Absolute Quantitation in Mass Spectrometry-Based Proteomics

Mass spectrometry-based quantitative proteomics is a powerful tool for gaining insights into function and dynamics of biological systems. However, peptides with different sequences have different ionization efficiencies, and their intensities in a mass spectrum are not correlated with their abundances. Therefore, various label-free or stable isotope label-based quantitation methods have emerged to assist mass spectrometry to perform comparative proteomic experiments, thus enabling nonbiased identification of thousands of proteins differentially expressed in healthy versus diseased cells. Here, we discuss the most widely used label-free and metabolic-, enzymatic-, and chemical labeling-based proteomic strategies for relative and absolute quantitation. We summarize the specific strengths and weaknesses of each technique in terms of quantification accuracy, proteome coverage, multiplexing capability, and robustness. Applications of each strategy for solving specific biological complexities are also presented.

Correlation of five secretory proteins with the nasopharyngeal carcinoma metastasis and the clinical applications

In our previous study, five different secretory proteins, including GSN, ADAMTSL4, CALR, PPIA and TXN, have been identified to be associated with the nasopharyngeal carcinoma (NPC) metastasis. In this work, the 5 proteins were further investigated. Bioinformatics analysis suggested that they might play an important role in the process of NPC development. Western blotting analysis showed that all of these 5 targets could be secreted into extracellular by both high metastatic NPC 5-8F cells and non-metastatic NPC 6-10B cells. Except for GSN, the expressions of ADAMTSL4, CALR, PPIA and TXN proteins in extracts of the 5-8F and 6-10B cells were significantly different (P < 0.05). Thus, the expressions of these 4 differentially expressed proteins were further tested in a cohort of NPC tissue specimens. The results indicated that the expression levels of ADAMTSL4 and TXN were highly correlated with the lymph node and distant metastasis (P<0.05) in NPC patients. Moreover, Enzyme-linked immunosorbent assay (ELISA) was used to investigate the concentrations of the ADAMTSL4 and TXN in serum specimens of NPC patients. The results revealed that serum ADAMTSL4 expression level was closely correlated with lymph node metastasis and clinical stage (P<0.05) in NPC patients, and it was able to discriminate metastasis NPC from non-metastasis NPC with a sensitivity of 75.6% and a specificity of 64.7%. The present data show for the first time that the ADAMTSL4 and TXN may be novel and potential biomarkers for predicting the NPC metastasis.Furthermore, the serum ADAMTSL4 could be a potential serum tumor biomarker for prognosis of NPC.

Nanoplasmonic Quantification of Tumor-derived Extracellular Vesicles in Plasma Microsamples for Diagnosis and Treatment Monitoring

Tumour-derived extracellular vesicles (EVs) are of increasing interest as a resource of diagnostic biomarkers. However, most EV assays require large samples, are time-consuming, low-throughput and costly, and thus impractical for clinical use. Here, we describe a rapid, ultrasensitive and inexpensive nanoplasmon-enhanced scattering (nPES) assay that directly quantifies tumor-derived EVs from as little as 1 μL of plasma. The assay uses the binding of antibody-conjugated gold nanospheres and nanorods to EVs captured by EV-specific antibodies on a sensor chip to produce a local plasmon effect that enhances tumour-derived EV detection sensitivity and specificity. We identified a pancreatic cancer EV biomarker, ephrin type-A receptor 2 (EphA2), and demonstrate that an nPES assay for EphA2-EVs distinguishes pancreatic cancer patients from pancreatitis patients and healthy subjects. EphA2-EVs were also informative in staging tumour progression and in detecting early responses to neoadjuvant therapy, with better performance than a conventional enzyme-linked immunosorbent assay. The nPES assay can be easily refined for clinical use, and readily adapted for diagnosis and monitoring of other conditions with disease-specific EV biomarkers.

Placental Proteomics Provides Insights into Pathophysiology of Pre-Eclampsia and Predicts Possible Markers in Plasma

Pre-eclampsia is a hypertensive disorder characterized by the new onset of hypertension >140/90 mmHg and proteinuria after the 20th week of gestation. The disorder is multifactorial and originates with abnormal placentation. Comparison of the placental proteome of normotensive (n = 25) and pre-eclamptic (n = 25) patients by gel-free proteomic techniques identified a total of 2145 proteins in the placenta of which 180 were differentially expressed (>1.3 fold, p < 0.05). Gene ontology enrichment analysis of biological process suggested that the differentially expressed proteins belonged to various physiological processes such as angiogenesis, apoptosis, oxidative stress, hypoxia, and placental development, which are implicated in the pathophysiology of pre-eclampsia. Some of the differentially expressed proteins were monitored in the plasma by multiple reaction monitoring analysis, which showed an increase in apolipoproteins A-I and A-II in gestational weeks 26-30 (2-fold, p < 0.01), while haptoglobin and hemopexin decreased in gestational weeks 26-30 and week 40/at delivery (1.8 fold, p < 0.01) in pre-eclamptic patients. This study provides a proteomic insight into the pathophysiology of pre-eclampsia. Identified candidate proteins can be evaluated further for the development of potential biomarkers associated with pre-eclampsia pathogenesis.

Discovery of nutritional biomarkers: future directions based on omics technologies

Understanding the interactions between food and human biology is of utmost importance to facilitate the development of more efficient nutritional interventions that might improve our wellness status and future health outcomes by reducing risk factors for non-transmittable chronic diseases, such as cardiovascular diseases, cancer, obesity and metabolic syndrome. Dissection of the molecular mechanisms that mediate the physiological effects of diets and bioactive compounds is one of the main goals of current nutritional investigation and the food industry as might lead to the discovery of novel biomarkers. It is widely recognized that the availability of robust nutritional biomarkers represents a bottleneck that delays the innovation process of the food industry. In this regard, omics sciences have opened up new avenues of research and opportunities in nutrition. Advances in mass spectrometry, nuclear magnetic resonance, next generation sequencing and microarray technologies allow massive genome, gene expression, proteomic and metabolomic profiling, obtaining a global and in-depth analysis of physiological/pathological scenarios. For this reason, omics platforms are most suitable for the discovery and characterization of novel nutritional markers that will define the nutritional status of both individuals and populations in the near future, and to identify the nutritional bioactive compounds responsible for the health outcomes.

Regulation of Macrophage Recognition through the Interplay of Nanoparticle Surface Functionality and Protein Corona

Using a family of cationic gold nanoparticles (NPs) with similar size and charge, we demonstrate that proper surface engineering can control the nature and identity of protein corona in physiological serum conditions. The protein coronas were highly dependent on the hydrophobicity and arrangement of chemical motifs on NP surface. The NPs were uptaken in macrophages in a corona-dependent manner, predominantly through recognition of specific complement proteins in the NP corona. Taken together, this study shows that surface functionality can be used to tune the protein corona formed on NP surface, dictating the interaction of NPs with macrophages.

Body fluid peptide and protein signatures in diabetic kidney diseases

Body fluid protein-based biomarkers carry the hope of improving patient management in diabetes by enabling more accurate and earlier detection of diabetic kidney disease (DKD), but also of defining the most suitable therapeutic targets. We present the data on some of the best studied individual protein markers in body fluids and conclude that their potential in clinical application for assessing DKD is moderate. Proteome-based approaches aiming at the identification of panels of body fluid biomarkers might be a valid alternative. We discuss the past (first) clinical proteomics studies in DKD, stressing their drawbacks but also the lessons that could be learned from them, as well as the more recent studies that have a potential for actual clinical implementation. We also highlight relevant issues and current problems associated with clinical proteomics from discovery towards application, and give suggestions for solutions that may help guiding proteomic studies, thereby removing some of the current hurdles for implementation of potentially beneficial results.

Novel biomarker pipeline to probe the oxidation sites and oxidation degrees of hemoglobin in bovine erythrocytes exposed to oxidative stress

Research on biomarkers for protein oxidation might give insight into the mechanistic mode of oxidative stress. In the work present here, a novel pipeline was established to probe the oxidation mechanism of bovine hemoglobin (Hb) with its oxidation products serving as the biomarkers. Reactive oxygen species generated by irradiation were used to mimic oxidative stress conditions to oxidize Hb in bovine erythrocytes. After Hb extraction and digestion, oxidized peptides in the tryptic fragments were assigned by comparison with the extracted ion chromatography spectra of native peptide from the control sample. Subsequent tandem mass spectrometry analysis of these peptides proved that oxidation was limited to partially exposed amino acid residues (α-Phe36 , β-Met1 , β-Trp14 , for instance) in Hb. Quantitation analysis on these oxidized peptides showed that oxidation degrees of target sites had positive correlations with the extended oxidation dose and the oxidation processes were also controlled by residues types. Compared with the conventional protein carbonyl assay, the identified oxidized products were feasibility biomarkers for Hb oxidation, indicating that the proposed biomarker pipeline was suitable to provide specific and valid information for protein oxidation. Copyright © 2015 John Wiley & Sons, Ltd.

New perspectives on bioactivity of olive oil: evidence from animal models, human interventions and the use of urinary proteomic biomarkers

Olive oil (OO) is the primary source of fat in the Mediterranean diet and has been associated with longevity and a lower incidence of chronic diseases, particularly CHD. Cardioprotective effects of OO consumption have been widely related with improved lipoprotein profile, endothelial function and inflammation, linked to health claims of oleic acid and phenolic content of OO. With CVD being a leading cause of death worldwide, a review of the potential mechanisms underpinning the impact of OO in the prevention of disease is warranted. The current body of evidence relies on mechanistic studies involving animal and cell-based models, epidemiological studies of OO intake and risk factor, small- and large-scale human interventions, and the emerging use of novel biomarker techniques associated with disease risk. Although model systems are important for mechanistic research nutrition, methodologies and experimental designs with strong translational value are still lacking. The present review critically appraises the available evidence to date, with particular focus on emerging novel biomarkers for disease risk assessment. New perspectives on OO research are outlined, especially those with scope to clarify key mechanisms by which OO consumption exerts health benefits. The use of urinary proteomic biomarkers, as highly specific disease biomarkers, is highlighted towards a higher translational approach involving OO in nutritional recommendations.

Aptamers: new arrows to target dendritic cells

Aptamers, as a novel class of molecular probes for diagnosis, imaging and targeting therapy, have attracted increasing attention in recent years. Aptamers are generated from libraries of single-stranded nucleic acids against different molecules via the "systematic evolution of ligands by exponential enrichment" (SELEX) method. SELEX is a repetitive process of a sequential selection procedure in which a DNA or RNA library pool is incubated separately with target and control molecules to select specific oligonucleotide aptamers with high affinities and specificities. Cell-SELEX is a modified version of the SELEX process in which whole living cells are used as targets for the aptamers. Dendritic cell (DC) targeting, as a new therapeutic approach, can improve the efficiency of immunotherapy in the treatment of allergies and cancers. DCs use various receptors to continuously induce adaptive immunity via capture and presentation of antigens to naïve T cells. DCs are considered as the best targets in modulating immune responses against cancer, autoimmunity, allergy and transplantation. Aptamers, as a new agent, can be applied in DC targeting. The purpose of this review is to present some general concepts of aptamer production and DC targeting by aptamer molecules.

Epidemiologic design and analysis for proteomic studies: a primer on -omic technologies

Proteome analysis is increasingly being used in investigations elucidating the molecular basis of disease, identifying diagnostic and prognostic markers, and ultimately improving patient care. We appraised the current status of proteomic investigations using human samples, including the state of the art in proteomic technologies, from sample preparation to data evaluation approaches, as well as key epidemiologic, statistical, and translational issues. We systematically reviewed the most highly cited clinical proteomic studies published between January 2009 and March 2014 that included a minimum of 100 samples, as well as strategies that have been successfully implemented to enhance the translational relevance of proteomic investigations. Limited comparability between studies and lack of specification of biomarker context of use are frequently observed. Nevertheless, there are initial examples of successful biomarker discovery in cross-sectional studies followed by validation in high-risk longitudinal cohorts. Translational potential is currently hindered, as limitations in proteomic investigations are not accounted for. Interdisciplinary communication between proteomics experts, basic researchers, epidemiologists, and clinicians, an orchestrated assimilation of required resources, and a more systematic translational outlook for accumulation of evidence may augment the public health impact of proteomic investigations.

Exosomes in bodily fluids are a highly stable resource of disease biomarkers

Biomarkers are measurable indicators of a biological state. As our understanding of diseases meliorates, it is generally accepted that early diagnosis renders the best chance to cure a disease. In the context of proteomics, the discovery phase of identifying bonafide biomarkers and the ensuing validation phase involving large cohort of patient samples are impeded by the complexity of bodily fluid samples. High abundant proteins found in blood plasma make it difficult for the detection of low abundant proteins that may be potential biomarkers. Extracellular vesicles (EVs) have reignited interest in the field of biomarker discovery. EVs contain a tissue-type signature wherein a rich cargo of proteins and RNA are selectively packaged. In addition, as EVs are membranous structures, the luminal contents are protected from degradation by extracellular proteases and are highly stable in storage conditions. Interestingly, an appealing feature of EV-based biomarker analysis is the significant reduction in the sample complexity compared to whole bodily fluids. With these prescribed attributes, which are the rate-limiting factors of traditional biomarker analysis, there is immense potential for the use of EVs for biomarker detection in clinical settings. This review will discuss the current issues with biomarker analysis and the potential use of EVs as reservoirs of disease biomarkers.

Explorative and targeted neuroproteomics in Alzheimer's disease

Alzheimer's disease (AD) is a progressive brain amyloidosis that injures brain regions involved in memory consolidation and other higher brain functions. Neuropathologically, the disease is characterized by accumulation of a 42 amino acid peptide called amyloid β (Aβ42) in extracellular senile plaques, intraneuronal inclusions of hyperphosphorylated tau protein in neurofibrillary tangles, and neuronal and axonal degeneration and loss. Biomarker assays capturing these pathologies have been developed for use on cerebrospinal fluid samples but there are additional molecular pathways that most likely contribute to the neurodegeneration and full clinical expression of AD. One way of learning more about AD pathogenesis is to identify novel biomarkers for these pathways and examine them in longitudinal studies of patients in different stages of the disease. Here, we discuss targeted proteomic approaches to study AD and AD-related pathologies in closer detail and explorative approaches to discover novel pathways that may contribute to the disease. This article is part of a Special Issue entitled: Neuroproteomics: Applications in neuroscience and neurology.

Comparative proteomic analyses of urine from rat urothelial carcinoma chemically induced by exposure to N-butyl-N-(4-hydroxybutyl)-nitrosamine

Bladder cancer is estimated to be the ninth most common malignancy with a high rate of recurrence and progression despite therapy, early diagnosis being crucial for timely intervention.

Clinical proteomic biomarkers: relevant issues on study design & technical considerations in biomarker development

Biomarker research is continuously expanding in the field of clinical proteomics. A combination of different proteomic-based methodologies can be applied depending on the specific clinical context of use. Moreover, current advancements in proteomic analytical platforms are leading to an expansion of biomarker candidates that can be identified. Specifically, mass spectrometric techniques could provide highly valuable tools for biomarker research. Ideally, these advances could provide with biomarkers that are clinically applicable for disease diagnosis and/ or prognosis. Unfortunately, in general the biomarker candidates fail to be implemented in clinical decision making. To improve on this current situation, a well-defined study design has to be established driven by a clear clinical need, while several checkpoints between the different phases of discovery, verification and validation have to be passed in order to increase the probability of establishing valid biomarkers. In this review, we summarize the technical proteomic platforms that are available along the different stages in the biomarker discovery pipeline, exemplified by clinical applications in the field of bladder cancer biomarker research.

Pursuing type 1 diabetes mellitus and related complications through urinary proteomics

Diabetes mellitus is a chronic metabolic disease with multiple complications, and its successful management requires early diagnosis, to allow timely interventions. Here, we have comprehensively analyzed the proteome changes in urine of type 1 diabetic subjects with and without complications such as retinopathy and nephropathy. gel electrophoresis combined to liquid chromatography-tandem mass spectrometry (GeLC-MS/MS) analysis of midstream urine highlighted the mechanisms involved in disease pathogenesis as, for instance wound healing and blood coagulation in all diabetics or altered ganglioside metabolism in retinopathy, and also some urinary proteins with potential diagnosis value. From these, gelsolin and antithrombin-III appear as promising diagnosis markers for type 1 diabetes mellitus (T1DM), whereas ephrin type-B receptor 4 and vitamin K-dependent protein Z seem to be promising markers for advanced T1DM disease state presenting retinopathy and nephropathy (T1DM-R + N). Data also suggest urinary ganglioside GM2 activator and beta-hexosaminidase subunit beta as potential urinary markers of retinopathy in diabetics. Taken together, the present exploratory urinary proteomic analysis might be seen as an important starting point for studies targeting specific urinary proteins aimed at the implementation of new biomarkers for the early detection of T1DM-related microvascular complications.

Oral cancer secretome: identification of cancer-associated proteins

This study aims to identify cancer-associated proteins in the secretome of oral cancer cell lines. We have successfully established four primary cell cultures of normal cells with a limited lifespan without human telomerase reverse transcriptase (hTERT) immortalization. The secretome of these primary cell cultures were compared with that of oral cancer cell lines using 2DE. Thirty five protein spots were found to have changed in abundance. Unambiguous identification of these proteins was achieved by MALDI TOF/TOF. In silico analysis predicted that 24 of these proteins were secreted via classical or nonclassical mechanisms. The mRNA expression of six genes was found to correlate with the corresponding protein abundance. Ingenuity Pathway Analysis (IPA) core analysis revealed that the identified proteins were relevant in, and related to, cancer development with likely involvements in tumor growth, metastasis, hyperproliferation, tumorigenesis, neoplasia, hyperplasia, and cell transformation. In conclusion, we have demonstrated that a comparative study of the secretome of cancer versus normal cell lines can be used to identify cancer-associated proteins.

Mass spectrometry in cancer biomarker research: a case for immunodepletion of abundant blood-derived proteins from clinical tissue specimens

The discovery of clinically relevant cancer biomarkers using mass spectrometry (MS)-based proteomics has proven difficult, primarily because of the enormous dynamic range of blood-derived protein concentrations and the fact that the 22 most abundant blood-derived proteins constitute approximately 99% of the total plasma protein mass. Immunodepletion of clinical body fluid specimens (e.g., serum/plasma) for the removal of highly abundant proteins is a reasonable and reproducible solution. Often overlooked, clinical tissue specimens also contain a formidable amount of highly abundant blood-derived proteins present in tissue-embedded networks of blood/lymph capillaries and interstitial fluid. Hence, the dynamic range impediment to biomarker discovery remains a formidable obstacle, regardless of clinical sample type (solid tissue and/or body fluid). Thus, we optimized and applied simultaneous immunodepletion of blood-derived proteins from solid tissue and peripheral blood, using clear cell renal cell carcinoma as a model disease. Integrative analysis of data from this approach and genomic data obtained from the same type of tumor revealed concordant key pathways and protein targets germane to clear cell renal cell carcinoma. This includes the activation of the lipogenic pathway characterized by increased expression of adipophilin (PLIN2) along with 'cadherin switching', a phenomenon indicative of transcriptional reprogramming linked to renal epithelial dedifferentiation. We also applied immunodepletion of abundant blood-derived proteins to various tissue types (e.g., adipose tissue and breast tissue) showing unambiguously that the removal of abundant blood-derived proteins represents a powerful tool for the reproducible profiling of tissue proteomes. Herein, we show that the removal of abundant blood-derived proteins from solid tissue specimens is of equal importance to depletion of body fluids and recommend its routine use in the context of biological discovery and/or cancer biomarker research. Finally, this perspective presents the background, rationale and strategy for using tissue-directed high-resolution/accuracy MS-based shotgun proteomics to detect genuine tumor proteins in the peripheral blood of a patient diagnosed with nonmetastatic cancer, employing concurrent liquid chromatography-MS analysis of immunodepleted clinical tissue and blood specimens.

The added value of proteomics for toxicological studies

Proteomics has the potential to elucidate complex patterns of toxic action attributed to its unique holistic a posteriori approach. In the case of toxic compounds for which the mechanism of action is not completely understood, a proteomic approach may provide valuable mechanistic insight. This review provides an overview of currently available proteomic techniques, including examples of their application in toxicological in vivo and in vitro studies. Future perspectives for a wider application of state-of-the-art proteomic techniques in the field of toxicology are discussed. The examples concern experiments with dioxins, polychlorinated biphenyls, and polybrominated diphenyl ethers as model compounds, as they exhibit a plethora of sublethal effects, of which some mechanisms were revealed via successful proteomic studies. Generally, this review shows the added value of including proteomics in a modern tool box for toxicological studies.

Classical MALDI-MS versus CE-based ESI-MS proteomic profiling in urine for clinical applications

Human urine is an attractive and informative biofluid for medical diagnosis, which has been shown to reflect the (patho)-physiology of not only the urogenital system, but also others such as the cardiovascular system. For this reason, many studies have concentrated on the study of the urine proteome, aiming to find relevant biomarkers that could be applied in a clinical setting. However, this goal can only be achieved after reliable quantitative and qualitative analysis of the urinary proteome. In the last two decades, MS-based platforms have evolved to become indispensable tools for biomarker research. In this review, we will present and compare two of the most clinically relevant analytical platforms that have been used for the study of the urinary proteome, namely CE-based ESI-MS and classical MALDI-MS. These platforms, although not directly comparable, have been extensively used in proteomic profiling and therefore their comparison is fundamentally relevant to this field.

Perspective: a systems approach to diabetes research

We review here the status of human type 2 diabetes studies from a genetic, epidemiological, and clinical (intervention) perspective. Most studies limit analyses to one or a few omic technologies providing data of components of physiological processes. Since all chronic diseases are multifactorial and arise from complex interactions between genetic makeup and environment, type 2 diabetes mellitus (T2DM) is a collection of sub-phenotypes resulting in high fasting glucose. The underlying gene–environment interactions that produce these classes of T2DM are imperfectly characterized. Based on assessments of the complexity of T2DM, we propose a systems biology approach to advance the understanding of origin, onset, development, prevention, and treatment of this complex disease. This systems-based strategy is based on new study design principles and the integrated application of omics technologies: we pursue longitudinal studies in which each subject is analyzed at both homeostasis and after (healthy and safe) challenges. Each enrolled subject functions thereby as their own case and control and this design avoids assigning the subjects a priori to case and control groups based on limited phenotyping. Analyses at different time points along this longitudinal investigation are performed with a comprehensive set of omics platforms. These data sets are generated in a biological context, rather than biochemical compound class-driven manner, which we term “systems omics.”

Low-molecular-mass secretome profiling identifies C-C motif chemokine 5 as a potential plasma biomarker and therapeutic target for nasopharyngeal carcinoma

Cancer cell secretome profiling has been shown to be a promising strategy for identifying potential body fluid-accessible cancer biomarkers and therapeutic targets. However, very few reports have investigated low-molecular-mass (LMr) proteins (<15kDa) in the cancer cell secretome. In the present study, we applied tricine-SDS-gel-assisted fractionation in conjunction with LC-MS/MS to systemically identify LMr proteins in the secretomes of three nasopharyngeal carcinoma (NPC) cell lines. We examined two NPC tissue transcriptome datasets to identify LMr genes/proteins that are highly upregulated in NPC tissues and also secreted/released from NPC cells, obtaining 35 candidates. We verified the overexpression of four targets (LSM2, SUMO1, RPL22, and CCL5) in NPC tissues by immunohistochemistry and demonstrated elevated plasma levels of two targets (S100A2 and CCL5) in NPC patients by ELISA. Notably, plasma CCL5 showed good power (AUC 0.801) for discriminating NPC patients from healthy controls. Additionally, functional assays revealed that CCL5 promoted migration of NPC cells, an effect that was effectively blocked by CCL5-neutralizing antibodies and maraviroc, a CCL5 receptor antagonist. Collectively, our data indicate the feasibility of the tricine-SDS-gel/LC-MS/MS approach for efficient identification of LMr proteins from cancer cell secretomes, and suggest that CCL5 is a potential plasma biomarker and therapeutic target for NPC.

BIOLOGICAL SIGNIFICANCE

Both LMr proteome and cancer cell secretome represent attractive reservoirs for discovery of cancer biomarkers and therapeutic targets. Our present study provides evidence for the practicality of using the tricine-SDS-PAGE/LC-MS/MS approach for in-depth identification of LMr proteins from the NPC cell secretomes, leading to the discovery of CCL5 as a potential plasma biomarker and therapeutic target for NPC. We believe that the modified GeLC-MS/MS approach used here can be further applied to explore extremely low-abundance, extracellular LMr proteins with important biological functions in other cell lines and biospecimens.

Proteomic identification of biomarkers of skeletal muscle disorders

Disease-specific biomarkers play a central diagnostic and therapeutic role in muscle pathology. Serum levels of a variety of muscle-derived enzymes are routinely used for the detection of muscle damage in diagnostic procedures, as well as for the monitoring of physical training status in sports medicine. Over the last few years, the systematic application of mass spectrometry-based proteomics for studying skeletal muscle degeneration has greatly expanded the range of muscle biomarkers, including new fiber-associated proteins involved in muscle transformation, muscular atrophy, muscular dystrophy, motor neuron disease, inclusion body myositis, myotonia, hypoxia, diabetes, obesity and sarcopenia of old age. These mass spectrometric studies have clearly established skeletal muscle proteomics as a reliable method for the identification of novel indicators of neuromuscular diseases.

An omics strategy for discovering pulmonary biomarkers potentially relevant to the evaluation of tobacco products

Smoking is known to cause serious lung diseases including chronic bronchitis, chronic obstructive lung disease, obstruction of small airways, emphysema and cancer. Tobacco smoke is a complex chemical aerosol containing at least 8000 chemical constituents, either tobacco derived or added by tobacco product manufacturers. Identification of all of the toxic agents in tobacco smoke is challenging, and efforts to understand the mechanisms by which tobacco use causes disease will be informed by new biomarkers of exposure and harm. In 2009, President Obama signed into law the Family Smoking Prevention and Tobacco Control Act granting the US FDA the authority to regulate tobacco products to protect public health. This perspective article presents the background, rationale and strategy for using omics technologies to develop new biomarkers, which may be of interest to the FDA when implementing the Family Smoking Prevention and Tobacco Control Act.

Proteome-base biomarkers in diabetes mellitus: progress on biofluids' protein profiling using mass spectrometry

The worldwide number of individuals suffering from diabetes mellitus (DM) has been projected to rise from 171 million in 2000 to 366 million in 2030. Identification of specific biomarkers for prediction and monitoring of DM is needed not only for the adequate screening diagnosis but also to assist the design of interventions to prevent or delay progression of this pathology and its attendant complications. Proteomic methods based on MS hold special promise for the identification of novel biomarkers that might form the foundation for new clinical tests, but to date, their contribution has been somehow unfruitful. Indeed, from more than 300 proteins found differently modulated in body fluids from diabetic patients, approximately 50 were validated with other approaches like ELISA or Western blotting and the clinical trials are being initiated to employ biofluids' proteomics (specifically urinary proteomics) in clinical decision. This review provides an overview of MS-based applications in the identification of potential biomarkers for DM, emphasizing the methodological challenges involved.