Proteomics in ocular fluids

The focus of this article is to review recent techniques in proteomic analysis of ocular fluids. These fluids include tears, aqueous humor, and vitreous, they will also be compared to serum analysis. Furthermore, we attempt to summarize some disease correlated biomarkers in ocular fluids that were discovered through different proteomic techniques in eye diseases like dry eye, glaucoma, age-related macular degeneration, uveitis, or diabetic retinopathy. This review is trying to point out the importance of these biomarkers for clinical applications.     

Proteomics as a research tool in clinical and experimental ophthalmology

It is estimated that 37 million people worldwide suffer from blindness and 124 million people have impaired vision. While the relatively recently developed therapies, antivascular endothelial growth factor inhibitors for the treatment of age-related macular degeneration, and prostaglandin analogues for the treatment of glaucoma are beneficial for some patients, there are many individuals with sight-threatening diseases for whom no effective pharmacological therapy is available. For many of these diseases, the molecular mechanisms remain to be comprehensively elucidated, thus precluding the design of successful therapies against specific pathological targets. The current review summarises recent attempts to elucidate molecular mechanisms of ocular diseases, including diabetic retinal disease, age-related macular degeneration and inherited blindness using proteomic methodologies. A novel hypothesis can be generated from global protein expression analysis of disease tissue, which can then be addressed with cellular and in vivo functional studies. For example, the identification of extracellular carbonic anhydrase from the vitreous of diabetic retinopathy patients using MS based proteomics led to the elucidation of a new pathway involved in intraretinal edema, which could be inhibited by a number of agents targeting different proteins in this pathway in relevant animal models. The potential of protein biomarkers for diagnosis and the identification of novel disease mechanisms are also discussed.     

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.     

Functional protease profiling for diagnosis of malignant disease

Clinical proteomic profiling by mass spectrometry (MS) aims at uncovering specific alterations within mass profiles of clinical specimens that are of diagnostic value for the detection and classification of various diseases including cancer. However, despite substantial progress in the field, the clinical proteomic profiling approaches have not matured into routine diagnostic applications so far. Their limitations are mainly related to high-abundance proteins and their complex processing by a multitude of endogenous proteases thus making rigorous standardization difficult. MS is biased towards the detection of low-molecular-weight peptides. Specifically, in serum specimens, the particular fragments of proteolytically degraded proteins are amenable to MS analysis. Proteases are known to be involved in tumour progression and tumour-specific proteases are released into the blood stream presumably as a result of invasive progression and metastasis. Thus, the determination of protease activity in clinical specimens from patients with malignant disease can offer diagnostic and also therapeutic options. The identification of specific substrates for tumour proteases in complex biological samples is challenging, but proteomic screens for proteases/substrate interactions are currently experiencing impressive progress. Such proteomic screens include peptide-based libraries, differential isotope labelling in combination with MS, quantitative degradomic analysis of proteolytically generated neo-N-termini, monitoring the degradation of exogenous reporter peptides with MS, and activity-based protein profiling. In the present article, we summarize and discuss the current status of proteomic techniques to identify tumour-specific protease-substrate interactions for functional protease profiling. Thereby, we focus on the potential diagnostic use of the respective approaches.     

Adipokines: a treasure trove for the discovery of biomarkers for metabolic disorders

Adipose tissue is a major endocrine organ, releasing signaling and mediator proteins, termed adipokines, via which adipose tissue communicates with other organs. Expansion of adipose tissue in obesity alters adipokine secretion which may contribute to the development of metabolic diseases. Consequently, this correlation has emphasized the importance to further characterize the adipocyte secretion profile, and several attempts have been made to characterize the complex nature of the adipose tissue secretome by utilizing diverse proteomic profiling approaches. Although the entirety of human adipokines is still incompletely characterized, to date more than 600 potentially secretory proteins were identified providing a rich source to identify putative novel biomarkers associated with metabolic diseases.     

Colorectal cancer proteomics, molecular characterization and biomarker discovery

Colorectal cancer (CRC) is a widespread disease, whose major genetic changes and mutations have been well characterized in the sporadic form. Much less is known at the protein and proteome level. Still, CRC has been the subject of multiple proteomic studies due to the urgent necessity of finding clinically relevant markers and to elucidate the molecular mechanisms underlying the progression of the disease. These proteomic approaches have been limited by different technical issues, mainly related with sensitivity and reproducibility. However, recent advances in proteomic techniques and MS systems have rekindled the quest for new biomarkers in CRC and an improved molecular characterization. In this review, we will discuss the application of different proteomic approaches to the identification of differentially expressed proteins in CRC. In particular, we will make a critical assessment about the use of 2-D DIGE, MS and protein microarray technologies, in their different formats, to identify up- or downregulated proteins and/or autoantibodies profiles that could be useful for CRC characterization and diagnosis. Despite a wide list of potential biomarkers, it is clear that more scientific efforts and technical advances are still needed to cover the range of low-abundant proteins, which may play a key role in CRC diagnostics and progression.     

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.     

Identification of glial-cell-line-derived neurotrophic factor-regulated proteins of striatum in mouse model of Parkinson disease

Glial-cell-line-derived neurotrophic factor (GDNF) is a potent survival factor for dopaminergic neurons, and hence serves as a therapeutic candidate for the treatment of Parkinson's disease. However, despite the potential clinical and physiological importance of GDNF, its mechanism of action is unclear. Therefore, we employed a state-of-the-art proteomic technique, DIGE, along with MS and a bioinformatics tool called Database for Annotation, Visualization and Integrated Discovery (DAVID), to profile proteome changes in the parkinsonian mouse striatum after GDNF challenge. Forty-six unique differentially expressed proteins were successfully identified, which were found either up-regulated and/or down-regulated at the two time points 4 and 72 h compared with the control. Proteins involved in cell differentiation and system development formed the largest part of the proteins regulated under GDNF. Furthermore, the aberrant expression of HSPs and mitochondria-associated proteins were noticeable. Moreover, mitochondrial stress 70 protein and heat shock cognate 71 kDa protein, whose relative levels increased significantly in GDNF-treated striatum, were further evaluated with Western blot and RT-PCR, demonstrating a good agreement with quantitative proteomic data. These data will provide some clues for understanding the mechanisms by which GDNF promotes the survival of dopaminergic neurons.     

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.     

Type 2 diabetes: Gaining insight into the disease process using proteomics

The incidence of diabetes mellitus is growing rapidly, with an increasing disease related morbidity and mortality. This is caused by macro- and microvascular complications, as a consequence of the often late diagnosis of type 2 diabetes (T2D), but especially by the difficulties to control glucose homeostasis due to the progressive nature of the disease. T2D is moreover a dual disease, with components of beta-cell failure and components of insulin resistance in peripheral organs, such as liver, fat, and muscle. Understanding the pathogenesis of the disease by gaining insight into the molecular pathways involved in both phenomena is one of the major assets of proteomic approaches. Moreover, proteomics and peptidomics may provide us with robust biomarkers for beta-cell failure, insulin resistance in pheripheral organs, but also for the development of diabetic complications. This review focuses on the knowledge gained by use of proteomic and peptidomic techniques in the study of the pathophysiology of T2D and in the attempts to discover new therapeutic targets.     

Proteomics: A new perspective for the understanding of pterygia

Pterygia is a common ocular surface disease bothering both the patient because of its unsightly appearance and the surgeon because of its tendency to recur. The pathogenesis of pterygia is complex and the exact mechanism(s), especially at the molecular level, remains unknown. The use of modern proteomic techniques such as iTRAQ may yield new knowledge on the underlying pathogenesis of pterygia. In this issue of Proteomics Clinical Applications, Linghu et al. (article number 1600094) identified a total of 156 proteins that expressed differently between the pterygia and healthy conjunctiva using the isobaric tags for relative and absolute quantification based quantitative proteomic analysis. Most significantly, western blotting confirmed that two candidate proteins matrix metalloproteinase 10 (MMP‐10) and CD34 were significantly upregulated in pterygia, suggesting that they have potential roles in the pathogenesis of pterygia. The findings in Linhu's study may provide a new perspective for the understanding of pterygia and develop a new therapeutic target.     

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.     

Proteomic approaches to the analysis of atopic dermatitis and new insights from interactomics

In this review, we summarized the recent findings regarding atopic dermatitis (AD) skin disease based on proteomic studies. AD is a chronic relapsing inflammatory skin disease typically characterized by a distribution of eczematous skin lesions with lichenification, pruritic excoriations and dry skin with wide varieties of pathophysiological aspects. We summarized the alterations of the protein expressions in the primary cultured AD cells from the patients'-biopsy samples that were mostly analyzed by 2-D PAGE and MALDI-TOF. Further, we also conducted protein-protein interaction mapping according to the obtained candidate proteins. As a result, we found that several hub proteins, i.e. heat shock 70-kDa protein 2, heat shock 70-kDa protein 9, tumor rejection antigen-1 (gp96), spermatogenesis-associated factor, protein kinase C inhibitor 1, vimentin, tenascin, semaphorin 4f (SEMA4F), complement component C1r deficiency (C1R) and apolipoprotein A (LPA), respectively, could receive important consideration in future studies. Since the mechanism of AD disease has been shown to be complex, our results may provide new clues to aid understanding of AD.     

Review of methods for determination of total protein and peptide concentration in biological samples

Clinical proteomics can be defined as the use of proteomic technologies to identify and measure biomarkers in fluids and tissues. The current work is intended to review various methods used for the determination of the total concentration of protein or peptide in fluids and tissues and the application of such methods to clinical proteomics. Specifically, this article considers the approaches to the measurement of total protein concentration, not the measurement of the concentration of a specific protein or group of proteins in a larger mixture of proteins. The necessity of understanding various concepts such as fit-for-use, quality-by-design, and other regulatory elements is discussed, as is the significance of using suitable standards for the protein quality of various samples.     

Membrane Proteome of Invasive Retinoblastoma: Differential Proteins and Biomarkers

Purpose: Retinoblastoma (RB) is a pediatric ocular cancer which is caused due to the aberrations in the RB1 gene. The changes in the membrane proteomics would help in understanding the development of the retinoblastoma and could identify candidates for biomarkers and therapy. Experimental design: Quantitative proteomics is performed on the enriched membrane fractions from pooled normal retina (n = 5) and pooled retinoblastoma tissues (n = 5). The proteins are tryptic‐digested and tagged with iTRAQ labels. Orbitrap mass spectrometry is used to analyze and quantify the deregulated membrane proteins involved in the RB tumor progression. Immunohistochemistry (IHC) is used to further validate few of the differentially expressed proteins. Results: A total of 3122 proteins are identified of which, 663 proteins are found to be deregulated with ≥two fold change in the RB tumor compared to the retina. 282 proteins are upregulated and 381 are downregulated with ≥2 peptide identifications. Bioinformatic analysis revealed that, most of the proteins are involved in the transport, cellular communication, and growth. Overexpression of lamin B1 (LMNB1) and transferrin receptor (TFRC) are observed in RB tumors using IHC. Conclusion and clinical relevance: The present study, is the first comprehensive quantitative membrane proteomic atlas of the differentially regulated proteins in RB compared to the retina. LMNB1 and TFRC could be potential biomarkers for this childhood cancer.     

How can proteomics elucidate the complexity of multiple sclerosis?

Multiple sclerosis affects more than 2.5 million people worldwide. Although multiple sclerosis was described almost 150 years ago, there are many knowledge gaps regarding its etiology, diagnosis, prognosis, and pathogenesis. Multiple sclerosis is an inflammatory, demyelinating, neurodegenerative disease of the CNS. During the last several decades, experimental models of multiple sclerosis have contributed to our understanding of the inflammatory disease mechanisms and have aided drug testing and development. However, little is known about the neurodegenerative mechanisms that operate during the evolution of the disease. Currently, all therapeutic approaches are primarily based on the inflammatory aspect of the disease. During the last decade, proteomics has emerged as a promising tool for revealing molecular pathways as well as identifying and quantifying differentially expressed proteins. Therefore, proteomics may be used for the discovery of biomarkers, potential drug targets, and new regulatory mechanisms. To date, a considerable number of proteomics studies have been conducted on samples from experimental models and patients with multiple sclerosis. These data form a solid base for further careful analysis and validation.     

Detection of potential markers of primary fibromyalgia syndrome in human saliva

In the last few years, many attempts have been carried out for the research of specific biological biomarkers in fibromyalgia (FM) since, so far, no laboratory tests have been appropriately validated for the diagnosis and the prognostic stratification of the disease. In our study for the first time, we carried out a proteomic analysis of the whole saliva of FM patients in order to evaluate salivary biomarkers. Twenty-two FM patients with all fulfilling the American College of Rheumathology diagnostic criteria for FM and 26 sex-and age-matched healthy subjects were enrolled in the study. Proteomic analysis was performed by combining 2-DE and MALDI-TOF-MS. The most relevant observation which emerged from the data analysis was the exclusive and significant over-expression of transaldolase and phosphoglycerate mutase I. These findings were validated by Western blot analysis and the total optical density confirmed the significant up-regulation of transaldolase and phosphoglycerate mutase I in FM samples with respect to healthy subjects. It was noteworthy that seven further salivary proteins resulted differentially expressed, namely: calgranulin A, calgranulin C, cyclophilin A, profilin 1, Rho GDP-dissociation inhibitor 2, proteasome subunit-α-type-2 and haptoglobin-related protein precursor. These preliminary results demonstrated the utility of salivary proteomic analysis in the identification of salivary biomarkers in FM patients and in clarifying some of the pathogenetic aspects of the disease.     

Anatomic site‐specific proteomic signatures of gastrointestinal stromal tumors

The gastrointestinal stromal tumor (GIST) is the most common mesenchymal malignancy of the gastrointestinal tract. Its clinical course ranges widely from a curable disorder to a highly malignant disease. Although its clinical and molecular characteristics depend on the anatomic site of origin, the molecular background of GIST arising in different anatomical site has not been studied yet. To investigate the proteomic background of GIST, we examined the proteomic features corresponding to the anatomic site of tumor origin. Comparison of the proteomic profile of gastric (23 cases) and small intestinal (9 cases) GIST by 2‐DE revealed 105 protein spots with significantly different intensity (p <0.01) between the two groups. Mass spectrometric study identified 68 distinct proteins for these 105 protein spots, including cancer‐associated ones such as prohibitin, pigment epithelium‐derived factor, and alpha‐actinin 4. The intensity of 37/105 (35.2%) protein spots was significantly concordant with the corresponding mRNA levels (p <0.01). Although both 2‐D DIGE and microarray experiments showed significant up‐regulation of vimentin expression in small intestinal GIST, Western blotting did not show a significant difference between the two groups. In conclusion, our study demonstrates the proteins specially expressed in GIST depending on their site of origin, as well as the unique advantage offered by use of proteomics to acquire such data. The identified proteins may provide clues to understanding the different characteristics of GIST depending on their site of origin.     

Impact of incomplete DNase I treatment on human macrophage proteome analysis

The aim of our study was to analyze the proteomic pattern of human macrophages obtained over a 4 year period from blood donors. The purpose was to simulate a long-term clinical study to assess the application of 2-D DIGE technique for differential proteomic analysis of these scarce samples. Bioinformatic analysis of 2-D DIGE gels of 19 different cultures of macrophages assessed whether they did or did not contain at least specific five spots identified by MS as being or containing bovine deoxyribonuclease I (DNase I). Bovine DNase I was used during sample treatment to remove nucleic acids from protein extracts. Macrophages were classified in two groups, which appeared to be differentiated by the completeness of DNase I treatment. Further detailed analysis revealed a different proteomic pattern of macrophage protein samples according to the completeness of this treatment. The major group of proteins affected, accounting for one third of the differentially expressed proteins, included proteins involved in cell motion and actin cytoskeleton reorganization. The use of DNase I for the removal of nucleic acids from protein samples must be avoided in proteomic studies since it can generate bias in the analysis of protein expression patterns.