Vitreous humor in the pathologic scope: Insights from proteomic approaches

The vitreous humor (VH) is the largest component of the eye. It is a colorless, gelatinous, highly hydrated matrix that fills the posterior segment of the eye between the lens and retina in vertebrates. In VH, a diversity of proteins that can influence retinal physiology is present, including growth factors, hormones, proteins with transporter activity, and enzymes. More importantly, the protein composition of VH has been described as being altered in a number of disease states. Therefore, attempts aiming at establishing a map of VH proteins and detecting putative biomarkers for ocular illness or protein fluctuations with putative physiologic significance were conducted over the last two decades, using proteomic approaches. Proteomic strategies often involve gel-based or LC techniques as sample fractioning approaches, subsequently coupled with MS procedures. This set of studies resulted in the proteomic characterization of a range of ocular disease samples, with particular incidence on diabetic retinopathy. However, practical therapeutic applications arising from these studies are scarce at the moment. A pertinent example of therapeutic targets arising from VH proteomics has emerged concerning vasoproliferative factors present in the vitreous, which should be involved in neovascularization and subsequent fibrovascular proliferation of the retina, in ocular disease context. Therefore, this review attempts to sum up the information acquired from the proteomic approaches to ocular disease conducted in VH samples, highlighting its clinical potential for disclosing ocular disease mechanisms and engendering pharmacological therapeutic treatments.     

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.     

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.     

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.     

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.     

Application of proteomic technologies to discover and identify biomarkers for periodontal diseases in gingival crevicular fluid: A review

Periodontal disease is a bacterial infection that destroys the gingiva and surrounding tissues of the oral cavity. In recent years, studies have shown a definite association between periodontal disease and other inflammatory conditions of the body. High-throughput analysis of proteins has become possible with the development of MS technology. This breakthrough in proteome technology enables comparative studies of comprehensive protein expression and identification of protein. In case of periodontal disease, proteome analysis using 2DE, as well as gel-free methods, has been reported. As a fluid lying in close proximity to periodontal tissue, the gingival crevicular fluid (GCF) is the principal target in the search for biomarkers of periodontal disease, because its protein composition may reflect the disease pathophysiology. Biochemical marker analysis of GCF is effective for objective diagnosis in the early and advanced stages of periodontal disease. Increasing numbers of recent reports have provided evidence that the proteomic approach is a promising tool for the discovery and identification of biochemical markers of periodontal disease. This search is of continuing interest in the field of experimental and clinical periodontal disease research. In this article, we summarize recent comprehensive proteomic studies aimed at discovering and identifying biomarkers of periodontal disease in GCF.     

Differential regulation of redox proteins and chaperones in HbEβ-thalassemia erythrocyte proteome

Purpose: In (hemoglobin, Hb) HbEβ‐thalassemia, HbE (β‐26 Glu→Lys) interacts with β‐thalassemia to produce clinical manifestation of varying severity. This is the first proteomic effort to study changes in protein levels of erythrocytes isolated from HbEβ‐thalassemic patients compared to normal. Experimental design: We have used 2‐DE and MALDI‐MS/MS‐based techniques to investigate the differential proteome profiling of membrane and Hb‐depleted fraction of cytosolic proteins of erythrocytes isolated from the peripheral blood samples of HbEβ‐thalassemia patients and normal volunteers. Results: Our study showed that redox regulators such as peroxiredoxin 2, Cu‐Zn superoxide dismutase and thioredoxin and chaperones such as α‐hemoglobin stabilizing protein and HSP‐70 were upregulated in HbEβ‐thalassemia. We have also observed larger amounts of membrane associated globin chains and indications of disruption of spectrin‐based junctional complex in the membrane skeleton of HbEβ‐thalassemic erythrocytes upon detection of low molecular weight fragments of β‐spectrin and decrease in β‐actin and dematin content. Conclusion and clinical relevance: We have observed interesting changes in the proteomic levels of redox regulators and chaperons in the thalassemic hemolysates and have observed strong correlation or association of the extent of such proteomic changes with HbE levels. This could be important in understanding the role of HbE in disease progression and pathophysiology.     

Biomarker discovery in asthma and COPD by proteomic approaches

Asthma and chronic obstructive pulmonary disease (COPD) are multifactorial respiratory diseases, characterized by reversible and irreversible airway obstruction, respectively. Even if the primary causes of these diseases remain unknown, inflammation is a central feature that leads to progressive and permanent pulmonary tissue damage (airway remodeling) up to the total loss of lung function. Therefore, the elucidation of the inflammation mechanisms and the characterization of the biological pathways, involved in asthma and COPD pathogenesis, are relevant in finding new possible diagnostic/prognostic biomarkers and for the validation of new drug targets. In this context, current advances in proteomic approaches, especially those based on MS, provide new tools to facilitate the discovery-driven studies of new biomarkers in respiratory diseases and improve the clinical reliability of the next generation of biomarkers for these diseases consisting of multiple phenotypes. This review will report an overview of the current proteomic methods applied to the discovery of candidate biomarkers for asthma and COPD, giving a special emphasis to emerging MS-based techniques.     

Proteomic approaches to the study of malignant lymphoma: Analyses on patient samples

We describe the application of proteomic techniques for protein profiling and biomarker discovery in malignant lymphoma. Hematologic malignancies are primarily characterized by their clinical, morphological, immunophenotypical, and molecular-genetic features. However, when based on these parameters, apparently identical lymphomas may show distinct clinical courses, suggesting underlying biological heterogeneity. Recent proteomic analyses have identified differences in protein expression both with regard to subclassification of the malignant lymphoma entities, as well as in correlation with clinical outcome. In this review, studies on quantification of differential protein expression in and between malignant lymphoma entities are included. Studies are included that are based on patient samples, that is, serum/plasma or cytological specimens, as well as intact tumor tissues, together with studies that focus on tumor cells alone, or in conjunction with the tumor microenvironment. For biomarker discovery in malignant lymphoma, these approaches are used to uncover the underlying biological mechanisms and identify proteins with potential diagnostic and prognostic utility, either as predictive biomarkers or as novel future treatment targets.     

Asthma and COPD proteomics: Current approaches and future directions

Although asthma and chronic obstructive pulmonary disease COPD represent the two most common chronic respiratory diseases worldwide, the mechanisms underlying their pathobiology need to be further elucidated. Presently, differentiation of asthma and COPD are largely based on clinical and lung function parameters. However, the complexity of these multifactorial diseases may lead to misclassification and to inappropriate management strategies. Recently, tremendous progress in MS has extended the sensitivity, accuracy, and speed of analysis, enabling the identification of thousands of proteins per experiment. Beyond identification, MS has also greatly implemented quantitation issues allowing to assess qualitative–quantitative differences in protein profiles of different samples, in particular diseased versus normal. Herein, we provide a summary of recent proteomics-based investigations in the field of asthma/COPD, highlighting major issues related to sampling and processing procedures for proteomic analyses of specific airway and parenchymal specimens (induced sputum, exhaled breath condensate, epithelial lining fluid, bronchoalveolar and nasal lavage fluid), as well as blood-derived specimen (plasma and serum). Within such a context, together with current difficulties and limitations mainly due to lack of general standardization in preanalytical sampling procedure, our discussion will focus on the challenges and possible benefits of proteomic studies in phenotypic stratification of asthma and COPD.     

Characterisation of tumoral markers correlated with ErbB2 (HER2/Neu) overexpression and metastasis in breast cancer

The receptor tyrosine kinase ErbB2 (HER2/neu) is overexpressed in ?30% of breast cancers and is associated with poor prognosis and an increased likelihood of metastasis. Clinical treatments such as trastuzumab are effective in less than 35% of women diagnosed as ErbB2‐positive, highlighting the necessity of searching for novel targets and alternative therapies. Herein, a proteomic screening strategy combining quantitative‐based gel electrophoresis and MS was used to compare the protein expression of 48 normal human breast and tumour tissues differing in ErbB2 expression and lymph node status. The aim was to identify proteins associated with the aggressive phenotype of ErbB2‐positive breast cancer which could be potential biomarkers of the disease as well as therapy targets. In total, 177 protein isoforms (107 gene products) differentially expressed between tissue groups were identified. Immunohistochemical staining of a tissue‐microarray was used for validation of selected protein candidates. We found that expression of HSP90α, laminin and GSTP1 significantly correlated with ErbB2 expression, while others such as AGR2, NM23H1 and Annexin 2 were overexpressed in greater than 40% of tumours. Finally, knocking‐down the expression by RNA interference of three candidates, AGR2, Transgelin2 and NM23H1 resulted in an enhanced invasive capacity of MDA‐MB435 cells. These data support the involvement of these targets in tumour progression and identify them as novel biomarkers of the disease.     

Clinical application of tear proteomics: Present and future prospects

Human tear fluid is charactered with very small volume and complex protein constitutes with a very large orders of magnitude. The tear proteome analysis provides a unique dataset (i.e., specific protein markers or protein patterns) that may be correlated to more effective diagnosis, prognosis, and response to therapy. Compared to less than 100 tear proteins obtained by the traditional methods, more than 400 proteins have been found in human tear fluid by current proteomic technologies. Many proteomics techniques, such as 2-DE, MALDI-TOF-MS, LC-MS, SELDI-TOF-MS, protein arrays, have been used to perform tear proteome analysis in healthy and/or disease subjects. The clinical application of tear proteomics needs suitable tear collection methods, standard tear handling procedures, and more sensitive and reliable proteomic technologies.     

How to get proteomics to the clinic? Issues in clinical proteomics,exemplified by CE‐MS

Clinical proteomics is defined as application of proteome analysis aiming at improving the current clinical situation. As such, the success of clinical proteomics should be assessed based on the clinical impact following implementation of the findings. While we have experienced significant technological advancements in mass spectrometry in the last years, based on the above measure, this has not at all resulted in similar advancements in clinical proteomics. Although a large number of proteomic biomarkers have been described, most of them were not subsequently validated, and certainly have had no impact in clinical decision making as yet. Under the current conditions, it appears likely that the situation will not change significantly: we will be flooded by reports on biomarkers, but not see any implementation. In this article, some key issues in proteomic biomarker research are pinpointed, based on the experience with CE‐MS, likely also holding true for biomarkers resulting from other analysis domains.     

Proteomics of a conundrum: Thoughts on addressing the aetiology versus progression of multiple sclerosis

Currently in the field of multiple sclerosis (MS) research there is an ongoing debate concerning the cause of the disease. MS is widely considered to begin with an autoimmune dysregulation. The disease does have a prominent autoimmune component however this may be representative of a secondary effect. There is growing evidence that the disease may be initiated by an underlying degeneration of oligodendrocytes. In our viewpoint, we discuss the potential differences between the aetiology and progression of MS. For the most part, proteomic analysis has focused on the autoimmune component of the disease. We suggest that proteomic analysis should be applied to investigating oligodendrocyte degeneration. We discuss the potential of the cuprizone animal model of demyelination and its usefulness in understanding oligodendrocyte degeneration. Immune suppressive therapies are effective at reducing clinical symptoms and improving quality of life. However, a cure is still lacking and as such the disease does still progress. We suggest that if the initiating cause is poorly understood, then curing MS is unlikely.     

Proteomic profiling of animal models mimicking skeletal muscle disorders

Over the last few decades of biomedical research, animal models of neuromuscular diseases have been widely used for determining pathological mechanisms and for testing new therapeutic strategies. With the emergence of high-throughput proteomics technology, the identification of novel protein factors involved in disease processes has been decisively improved. This review outlines the usefulness of the proteomic profiling of animal disease models for the discovery of new reliable biomarkers, for the optimization of diagnostic procedures and the development of new treatment options for skeletal muscle disorders. Since inbred animal strains show genetically much less interindividual differences as compared to human patients, considerably lower experimental repeats are capable of producing meaningful proteomic data. Thus, animal model proteomics can be conveniently employed for both studying basic mechanisms of molecular pathogenesis and the effects of drugs, genetic modifications or cell-based therapies on disease progression. Based on the results from comparative animal proteomics, a more informed decision on the design of clinical proteomics studies could be reached. Since no one animal model represents a perfect pathobiochemical replica of all of the symptoms seen in complex human disorders, the proteomic screening of novel animal models can also be employed for swift and enhanced protein biochemical phenotyping.     

Differentially expressed proteins of MCF-7 human breast cancer cells affected by Zilongjin, a complementary Chinese herbal medicine

Purpose : Zilongjin, a complementary Chinese herbal medicine, has been used to alleviate the adverse effects of chemotherapeutic drugs in cancer therapy. However, the mechanisms of anti‐cancer activity of Zilongjin are still largely unkonwn. Experimental design : First, the proteomic approach of combined 2‐DE and ESI‐MS/MS was used to investigate the effect of Zilongjin on the protein expression in MCF‐7 cells. Then, the differential expression of some proteins was confirmed by Western blot, cytoimmunofluoresecnce, and quantitative real‐time RT‐PCR analysis. Results : The identified proteins with differential expression, involved in such events as protein translation, cellular signal transduction, cytoskeleton formation and transportation, include seven downregulating proteins, such as Eukaryotic translation initiation factor 3 subunit I, Eukaryotic translation initiation factor 1A Y‐chromosomal, Ran‐specific GTPase‐activating protein, Ubiquitin‐conjugating enzyme E2 N, Tropomodulin‐3, Macrophage‐capping protein, and Tumor protein D52, as well as two upregulating proteins, HSP β‐1 and keratin18. Moreover, the differential expression of three proteins was confirmed. Conclusions and clinical relevance : (i) These results provide a new insight into the molecular mechanisms of Zilongjin on therapy for breast cancer. (ii) The application of the proteomic approaches will result in the more extended appreciation of Chinese medicine than those known at present.     

Proteomics in chronic kidney disease: The issues clinical nephrologists need an answer for

A growing number of patients are recognised to have chronic kidney disease (CKD). However, only a minority will progress to end-stage renal disease requiring dialysis or transplantation. Currently available diagnostic and staging tools frequently fail to identify those at higher risk of progression or death. Furthermore within specific disease entities there are shortcomings in the prediction of the need for therapeutic interventions or the response to different forms of therapy. Kidney and urine proteomic biomarkers are considered as promising diagnostic tools to predict CKD progression early in diabetic nephropathy, facilitating timely and selective intervention that may reduce the related health-care expenditures. However, independent groups have not validated these findings and the technique is not currently available for routine clinical care. Furthermore, there are gaps in our understanding of predictors of progression or need for therapy in non-diabetic CKD. Presumably, a combination of tissue and urine biomarkers will be more informative than individual markers. This review identifies clinical questions in need of an answer, summarises current information on proteomic biomarkers and CKD, and describes the European Kidney and Urine Proteomics initiative that has been launched to carry out a clinical study aimed at identifying urinary proteomic biomarkers distinguishing between fast and slow progressors among patients with biopsy-proven primary glomerulopathies.     

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.     

Autism spectrum disorder: An omics perspective

Current directions in autism spectrum disorder (ASD) research may require moving beyond genetic analysis alone, based on the complexity of the disorder, heterogeneity and convergence of genetic alterations at the cellular/functional level. Mass spectrometry (MS) has been increasingly used to study CNS disorders, including ASDs. Proteomic research using MS is directed at understanding endogenous protein changes that occur in ASD. This review focuses on how MS has been used to study ASDs, with particular focus on proteomic analysis. Other neurodevelopmental disorders have been investigated using MS, including fragile X syndrome (FXS) and Smith-Lemli-Opitz Syndrome (SLOS), genetic syndromes highly associated with ASD comorbidity.     

The pancreatic cancer proteome - recent advances and future promise

Of the common cancers, pancreatic ductal adenocarcinoma is one of the most lethal. The cancer's aggressive biology, leading to rapid dissemination, combined with a lack of clearly recognisable symptoms means that for many patients, the disease is at an advanced stage when diagnosed. The prognosis is consequently very poor, with as few as 3-5% of patients surviving 5?years. Recently, proteomic technologies have been employed in an effort to identify protein biomarkers, therapeutic targets and disease response markers for pancreatic cancer. Research has primarily relied upon pancreatic tissue samples, and body fluids such as pancreatic juice and blood serum. In this article, we will highlight the current proteomic techniques, qualitative and quantitative, employed in the field of pancreatic cancer research. We will review both the progress made and the challenges ahead, in elaborating the biology of pancreatic cancer and identifying novel biomarkers.