Quantitative proteomics in cardiovascular research: Global and targeted strategies

Extensive technical advances in the past decade have substantially expanded quantitative proteomics in cardiovascular research. This has great promise for elucidating the mechanisms of cardiovascular diseases and the discovery of cardiac biomarkers used for diagnosis and treatment evaluation. Global and targeted proteomics are the two major avenues of quantitative proteomics. While global approaches enable unbiased discovery of altered proteins via relative quantification at the proteome level, targeted techniques provide higher sensitivity and accuracy, and are capable of multiplexed absolute quantification in numerous clinical/biological samples. While promising, technical challenges need to be overcome to enable full utilization of these techniques in cardiovascular medicine. Here, we discuss recent advances in quantitative proteomics and summarize applications in cardiovascular research with an emphasis on biomarker discovery and elucidating molecular mechanisms of disease. We propose the integration of global and targeted strategies as a high-throughput pipeline for cardiovascular proteomics. Targeted approaches enable rapid, extensive validation of biomarker candidates discovered by global proteomics. These approaches provide a promising alternative to immunoassays and other low-throughput means currently used for limited validation.     

Targeted proteomics strategy applied to biomarker evaluation

The evaluation of biomarker candidates, involving quantitative measurement of a large number of proteins in bodily fluids, remains the main obstruction in the development of a biomarker validation pipeline. Although immunoassays are commonly used, high-throughput and multiplex-capable methods are required for expediting the evaluation process. MS-based approaches employing targeted proteomic strategies provide not only a sensitive, but in addition a precise quantification tool, which is versatile, systematic, and scalable. Its capability of multiplexing hundreds of targets facilitate a cost-effective and rapid evaluation and is especially useful during the early stage of the process where a large list of candidate biomarkers must be triaged before entering validation studies. The robustness requirement for the methods also mandates a high degree of selectivity to analyze complex clinical samples. Improvement in the selectivity of LC-MS methods has been achieved by adopting high-resolution and high-accuracy mass analyzers to perform quantitative analyses with a novel method called parallel reaction monitoring. This article discusses the design and performance of biomarker evaluation studies using targeted proteomics strategies and the implementation of recent technology developments.     

Application of quantitative proteomics technologies to the biomarker discovery pipeline for multiple sclerosis

Multiple sclerosis is an inflammatory-mediated demyelinating disorder most prevalent in young Caucasian adults. The various clinical manifestations of the disease present several challenges in the clinic in terms of diagnosis, monitoring disease progression and response to treatment. Advances in MS-based proteomic technologies have revolutionized the field of biomarker research and paved the way for the identification and validation of disease-specific markers. This review focuses on the novel candidates discovered by the application of quantitative proteomics to relevant disease-affected tissues in both the human context and within the animal model of the disease known as experimental autoimmune encephalomyelitis. The role of targeted MS approaches for biomarker validation studies, such as multiple reaction monitoring will also be discussed.     

Differential expression of serum/plasma proteins in various infectious diseases: Specific or nonspecific signatures

Apart from direct detection of the infecting organisms or biomarker of the pathogen itself, surrogate host markers are also useful for sensitive and early diagnosis of pathogenic infections. Early detection of pathogenic infections, discrimination among closely related diseases with overlapping clinical manifestations, and monitoring of disease progression can be achieved by analyzing blood biomarkers. Therefore, over the last decade large numbers of proteomics studies have been conducted to identify differentially expressed human serum/plasma proteins in different infectious diseases with the intent of discovering novel potential diagnostic/prognostic biomarkers. However, in-depth review of the literature indicates that many reported biomarkers are altered in the same way in multiple infectious diseases, regardless of the type of infection. This might be a consequence of generic acute phase reactions, while the uniquely modulated candidates in different pathogenic infections could be indicators of some specific responses. In this review article, we will provide a comprehensive analysis of differentially expressed serum/plasma proteins in various infectious diseases and categorize the protein markers associated with generic or specific responses. The challenges associated with the discovery, validation, and translational phases of serum/plasma biomarker establishment are also discussed.     

Urine proteomics in kidney and urogenital diseases: Moving towards clinical applications

To date, multiple biomarker discovery studies in urine have been conducted. Nevertheless, the rate of progression of these biomarkers to qualification and even more clinical application is extremely low. The scope of this article is to provide an overview of main clinically relevant proteomic findings from urine focusing on kidney diseases, bladder and prostate cancers. In addition, approaches for promoting the use of urine in clinical proteomics including potential means to facilitate the validation of existing promising findings (biomarker candidates identified from previous studies) and to increase the chances for success for the identification of new biomarkers are discussed.     

High-resolution biomarker discovery: Moving from large-scale proteome profiling to quantitative validation of lead candidates

Diverse proteomic techniques based on protein MS have been introduced to systematically characterize protein perturbations associated with disease. Progress in clinical proteomics is essential for personalized medicine, wherein treatments will be tailored to individual needs based on patient stratification using noninvasive disease monitoring procedures to reveal the most appropriate therapeutic targets. However, breakthroughs await the successful development and application of a robust proteomic pipeline capable of identifying and rigorously assessing the relevance of multiple candidate proteins as informative diagnostic and prognostic indicators or suitable drug targets involved in a pathological process. While steady progress has been made toward more comprehensive proteome profiling, the emphasis must now shift from in depth screening of reference samples to stringent quantitative validation of selected lead candidates in a broader clinical context. Here, we present an overview of the emerging proteomic strategies for high-throughput protein detection focused primarily on targeted MS/MS as the basis for biomarker verification in large clinical cohorts. We discuss the conceptual promise and practical pitfalls of these methods in terms of achieving higher dynamic range, higher throughput, and more reliable quantification, highlighting research avenues that merit additional inquiry.     

Quantitative proteomics for investigating psychiatric disorders

The underlying pathophysiology of psychiatric disorders remains elusive. The use of quantitative proteomics to investigate disease-specific protein signatures holds great promise to improve the understanding of psychiatric disorders and identify relevant biomarkers. In this review, we discuss quantitative proteomic approaches for elucidating molecular mechanisms of psychiatric disorders, i.e. anxiety, schizophrenia, bipolar disorder and depression, by studying specimens from animal models and patients. We present gel-based, label-free and stable isotope-labeling methodologies and evaluate their strengths and limitations in the context of psychiatric research, with a focus on (15)N metabolic labeling of live animals due to its increased accuracy and potential for future applications. We also review biomarker candidate validation methods and present quantitative proteomic studies from the literature that aim to disentangle the molecular pathobiology of psychiatric disorders and identify candidate biomarkers. Finally, we explore the applicability of implementing proteomic methods as a routine diagnostic tool in the clinical laboratory.     

Proteomic approach toward personalized sarcoma treatment: Lessons from prognostic biomarker discovery in gastrointestinal stromal tumor

Sarcomas range from curable tumors to those causing death via metastasis and recurrence. Thus, there is an urgent need for biomarker identification in order to assess the degree of malignancy, predict prognosis, and evaluate possible therapies. Various proteomic approaches and different clinical materials have been used to this end, and candidate biomarkers have been reported for the different types of sarcomas. However, the sample size used in these biomarker studies was generally insufficient, and thus far, no biomarker has been proved useful in clinics. Given that sarcomas are rare, biomarker validation in this setting is more challenging than in other malignancies. In gastrointestinal stromal tumor, adjuvant therapy has proven to be effective. However, only 40% patients experience metastasis after curative surgery alone, and the rest of the patients may not need adjuvant therapy. Using a proteomic approach, we identified pfetin (potassium channel tetramerization domain containing 12, KCTD 12) as a novel prognostic biomarker for sarcoma, and immunohistochemically confirmed its clinical usefulness by a multiinstitutional validation study. Here, we describe our experience and discuss the critical points in the discovery of this biomarker.     

Quantification of Biomarker Proteins Using Reverse‐Phase Protein Arrays

It is expected that antibody‐based proteomics will soon occupy a pivotal position in the discovery and validation of biomarkers and therapeutic targets. The reverse‐phase protein array (RPPA) is an antibody‐based proteomic method that can quantify the expression of multiple posttranslationally modified proteins (such as those that have been phosphorylated) across a large number of protein samples. RPPA is highly sensitive and requires only very small protein samples. This feature, in combination with large antibody libraries, makes RPPA ideal for clinical proteomics, as well as the fact that it is an expandable multiplex assay. In Volume 14, Issue 1 of Proteomics Clinical Applications, Suzuki and colleagues report for the first time a study comparing RPPA and immunohistochemistry for quantification of seven biomarker proteins used for subtyping of diffuse large B‐cell lymphoma. Such combination of multiple biomarkers is likely to increase diagnostic accuracy and can be used for precise classification of this heterogeneous disease.     

Biomarkers in pediatrics: children as biomarker orphans

Biomarkers have enormous potential to improve patient care by establishing tests of diagnosis, prognosis, and treatment effects. Successfully translating a biomarker from discovery to clinical application demands high-quality discovery research and high-quality clinical studies for biomarker validation; however, there are additional challenges that face biomarker research in pediatrics. There are also additional characteristics of pediatric medicine that make biomarker research especially needed. This review focuses on the fundamentals of biomarkers, the additional considerations needed for applying biomarker research to children, and recommendations for advancing pediatric biomarker research.     

Glycoproteomic strategies: From discovery to clinical application of cancer carbohydrate biomarkers

Carbohydrate antigens are the most frequently and traditionally used biomarkers for cancer, such as CA19–9, CA125, DUPAN-II, AFP-L3, and many others. The diagnostic potential of them was simply based on the cancer-specific alterations of glycan structures on particular glycoproteins in serum/plasma. In spite of the facts that glycosylation disorders are feasible for cancer biomarkers and glycomic analysis technologies to explore them have been rapidly developed, it remains difficult to sensitively screen glycan structure changes on cancer-associated glycoproteins from clinical specimens. Moreover, a lot of additional issues should be appropriately addressed for the clinical application of newly identified glycosylation biomarkers, including analytical throughput, quantitative confirmation of structural changes, and biological explanation for the alterations. In the last decade, significant improvement of mass spectrometric techniques is being made in the aspects of both hardware spec and preanalytical purification procedures for glycoprotein analysis. Here we review potential approaches to perform comprehensive analysis of glycoproteomic biomarker screening from serum/plasma and to realize high-throughput validation of site-specific oligosaccharide variations. The power and problems of mass spectrometric applications on the clinical use of carbohydrate biomarkers are also discussed in this review.     

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.     

Profiling the proteome in renal transplantation

Improved monitoring of transplanted solid organs is one of the next crucial steps leading to an increase in both patient and allograft survival. This can be facilitated through one or a set of surrogate biomarker molecules that accurately and precisely indicate the health status of the transplanted organ. Recent developments in the field of high throughput "omic" methods including genomics and proteomics have facilitated robust and comprehensive analysis of genes and proteins. This development has stimulated efforts in the identification of effective and clinically applicable gene and protein biomarkers in solid organ transplantation, including kidney transplantation. Some achievements have been made through proteomics in terms of profiling proteins and identification of potential biomarkers. However, the road to a successful biomarker discovery and its clinical implementation has proved to be challenging, requiring a number of key issues to be addressed. Such issues are: the lack of widely accepted protocols, difficulty in sample processing and transportation and a lack of collaborative efforts to achieve significant sample sizes in clinical studies. In this review using our area of expertise, we describe the current strategies used for proteomic-based biomarker discovery in renal transplantation, discuss inherent issues associated with these efforts and propose better strategies for successful biomarker discovery.     

Quantitative proteomic approaches for biomarker discovery

The rapid advances in proteomic technologies have made possible systematic analysis of hundreds to thousands of proteins in clinical samples with the promise of uncovering novel protein biomarkers for various disease conditions. We will discuss in this review article current MS and protein chip-based quantitative proteomic approaches and their application in biomarker discovery. The emphasis will be placed on new quantification strategies employing stable isotopic labeling coupled with MS/MS, and antibody-based protein chips and nanodevices. The strength and weakness of each technology are briefly highlighted.     

Network views for personalized medicine

Clinical Proteomics has traveled a long way pinpointing potential biomarkers for a variety of diseases. However, the absence of clinical implementation of proteomics findings has led to a frank evaluation and reconsideration of applied practices in biomarker discovery, recruitment of technological tools for biomarker verification and generation of new guidelines for data reporting. Nevertheless, considering the need for vast clinical resources for biomarker validation, the frequent lack of clear definitions of contexts of use, in combination to the biomarker “high offer,” progress toward biomarker implementation will even more require the adoption of an extensive open-minded approach: disease-focused networks are needed to ensure rapid exchange of information, initiation of appropriate studies, parallel validation of multiple biomarkers and sharing of valuable clinical resources. This viewpoint article targets to reflect on these issues and advocates the added value of multidisciplinary networks in biomarker development using bladder cancer as a paradigm.     

Applications of protein microarrays for biomarker discovery

The search for new biomarkers for diagnosis, prognosis, and therapeutic monitoring of diseases continues in earnest despite dwindling success at finding novel reliable markers. Some of the current markers in clinical use do not provide optimal sensitivity and specificity, with the prostate cancer antigen (PSA) being one of many such examples. The emergence of proteomic techniques and systems approaches to study disease pathophysiology has rekindled the quest for new biomarkers. In particular the use of protein microarrays has surged as a powerful tool for large-scale testing of biological samples. Approximately half the reports on protein microarrays have been published in the last two years especially in the area of biomarker discovery. In this review, we will discuss the application of protein microarray technologies that offer unique opportunities to find novel biomarkers.     

Ensembles of protein termini and specific proteolytic signatures as candidate biomarkers of disease

Early accurate diagnosis and personalized treatment are essential in order to treat complex or fatal diseases such as cancer and autoimmune, cardiovascular and neurodegenerative diseases. To realize this vision, new diagnostic and prognostic biomarkers are urgently required. MS-based proteomics is the most promising approach for protein biomarker identification, but suffers in clinical translation of biomarker candidates that show only quantitative differences from normal tissue. Indeed, success in translating proteomic data to biomarkers in the clinic has been disappointing. Here, we propose that protein termini provide a new opportunity for biomarker discovery due to qualitative differences in intact and new protein termini between diseased and normal tissues. Altered proteolysis occurs in most pathologies. Disease- and process-specific protein modifications, including proteolytic processing and subsequent modification of the terminal amino acids, frequently lead to altered protein activity that plays key roles in the disease process. Thus, mapping of ensembles of characteristic protein termini provides a proteolytic signature of high information content that shows both quantitative and most importantly qualitative differences in different diseases and stage of disease. These unique protein biomarkers have the added benefit of being mechanistically informative by revealing the activity state of the bioactive protein. Moreover, proteome-wide isolation of protein termini leads to generalized sample simplification, thereby enabling up to three orders of magnitude lower LODs compared to traditional shotgun proteomic approaches. We introduce the potential of protein termini for biomarker discovery, briefly review methods enabling large-scale studies of protein termini, and discuss how these may be integrated into a termini-oriented biomarker discovery pipeline from discovery to clinical application.     

Recent advances in targeted proteomics for clinical applications

MS-based approaches using targeted methods have been widely adopted by the proteomics community to study clinical questions such as the evaluation of biomarkers. At present, the most widely used targeted MS method is the SRM technique typically performed on a triple quadrupole instrument. However, the high analytical demands for performing clinical studies in combination with the extreme complexity of the samples involved are a serious challenge. The segmentation of the biomarker evaluation workflow has only partially alleviated these issues by differently balancing the analytical requirements and throughput at different stages of the process. The recent introduction of targeted high-resolution and accurate-mass analyses on fast sequencing mass spectrometers operated in parallel reaction monitoring (PRM) mode offers new avenues to conduct clinical studies and thus overcome some of the limitations of the triple quadrupole instrument. This article discusses the attributes and specificities of the PRM technique, in terms of experimental design, execution, and data analysis, and the implications for biomarker evaluation. The benefits of PRM on data quality and the impact on the consistency of results are highlighted and the definitive progress on the overall output of clinical studies, including high throughput, is discussed.     

Reconstructing the pipeline by introducing multiplexed multiple reaction monitoring mass spectrometry for cancer biomarker verification: an NCI-CPTC initiative perspective

Proteomics holds great promise in personalized medicine for cancer in the post-genomic era. In the past decade, clinical proteomics has significantly evolved in terms of technology development, optimization and standardization, as well as in advanced bioinformatics data integration and analysis. Great strides have been made for characterizing a large number of proteins qualitatively and quantitatively in a proteome, including the use of sample fractionation, protein microarrays and MS. It is believed that differential proteomic analysis of high-quality clinical biospecimen (tissue and biofluids) can potentially reveal protein/peptide biomarkers responsible for cancer by means of their altered levels of expression and/or PTMs. Multiple reaction monitoring, a multiplexed platform using stable isotope dilution-MS with sensitivity and reproducibility approaching that of traditional ELISAs commonly used in the clinical setting, has emerged as a potentially promising technique for next-generation high-throughput protein biomarker measurements for diagnostics and therapeutics.     

Implementation of Proteomics in Clinical Trials

The application of protein (or peptide) biomarkers in clinical studies is a dynamic, ever‐growing field. The introduction of clinical proteomics/peptidomics, such as mass spectrometry–based assays and multiplexed antibody–based protein arrays, has reshaped the landscape of biomarker identification and validation, allowing the discovery of novel biomarkers at an unprecedented rate and reliability. To reflect the current status with respect to implementation of protein/peptide biomarkers, an investigation of the most recent (last 6 years) clinical studies from clinicaltrials.gov is presented. Forty‐two clinical trials involving the direct use of protein or peptide biomarkers in patient stratification and/or disease diagnosis and prognosis are highlighted. Most of the clinical trials that include proteomics/protein assays are aiming toward implementation of non‐invasive diagnostic tools for early detection, while many of the clinical trials are targeting to correlate the protein abundance with the risk of a disease event. Less in number are the studies in which the protein biomarkers are applied to stratify the patients for intervention. All the above areas of application are considered of great importance for improving disease management, in an era where implementation toward precision medicine is the desired outcome of proteomics biomarker research.