Clinical proteomics and OMICS clues useful in translational medicine research

Plasma Proteomic Analysis Reveals Age-Specific Changes in Platelet- and Endothelial Cell-Derived Proteins and Regulators of Plasma Coagulation and Fibrinolysis

This post hoc study of a plasma proteomic database investigated hemostatic proteins in the context of developmental hemostasis. Twenty-seven hemostatic proteins changed expression with age, and the hemostatic profile of neonates was unique. Appreciating developmental hemostasis through proteomics may lead to more personalized medicine for hospitalized children.

Differential proteome analysis of diabetes mellitus type 2 and its pathophysiological complications

The prevalence of Diabetes Mellitus Type 2 (DM 2) is increasing every passing year due to some global changes in lifestyles of people. The exact underlying mechanisms of the progression of this disease are not yet known. However recent advances in the combined omics more particularly in proteomics and genomics have opened a gateway towards the understanding of predetermined genetic factors, progression, complications and treatment of this disease. Here we shall review the recent advances in proteomics that have led to an early and better diagnostic approaches in controlling DM 2 more importantly the comparison of structural and functional protein biomarkers that are modified in the diseased state. By applying these advanced and promising proteomic strategies with bioinformatics applications and bio-statistical tools the prevalence of DM 2 and its associated disorders i-e nephropathy and retinopathy are expected to be controlled.

Ceruloplasmin, transferrin and apolipoprotein A-II play important role in treatment's follow-up of paracoccidioidomycosis patients

Paracoccidioidomycosis (PCM) is a systemic disease caused by thermodymorphic fungi of the Paracoccidioides brasiliensis complex, (Paracoccidioides spp.). Patients with PCM reveal specific cellular immune impairment. Despite the effective treatment, quiescent fungi can lead to relapse, usually late, the serological diagnosis of which has been deficient. The present study was carried out with the objective of investigating a biomarker for the identification of PCM relapse and another molecule behaving as an immunological recovery biomarker; therefore, it may be used as a cure criterion. In the evolutionary analysis of the proteins identified in PCM patients, comparing those that presented with those that did not reveal relapse, 29 proteins were identified. The interactions observed between the proteins, using transferrin and haptoglobin, as the main binding protein, were strong with all the others. Patient follow-up suggests that cerulosplamin may be a marker of relapse and that transferrin and apolipoprotein A-II may contribute to the evaluation of the treatment efficacy and avoiding a premature decision.

Blood Sampling and Preparation Procedures for Proteomic Biomarker Studies of Psychiatric Disorders

A major challenge in proteomic biomarker discovery and validation for psychiatric diseases is the inherent biological complexity underlying these conditions. There are also many technical issues which hinder this process such as the lack of standardization in sampling, processing and storage of bio-samples in preclinical and clinical settings. This chapter describes a reproducible procedure for sampling blood serum and plasma that is specifically designed for maximizing data quality output in two-dimensional gel electrophoresis, multiplex immunoassay and mass spectrometry profiling studies.

Blood Bio-Sampling Procedures for Multiplex Biomarkers Studies

A major challenge in single or panel of biomarker discovery and validation is the inherent biological complexity underlying disease heterogeneity and inconsistent responses to treatment. Moreover, the lack of standardization in the sampling, processing, and storage of biological fluids such as plasma and serum disrupts the discovery and validation of blood-based biomarker tests in preclinical and clinical settings. This chapter presents a reproducible sample collection and handling procedure that aims to enhance analyte stability and ensure compatibility with the corresponding multiplex biomarker profiling platforms. The importance of defining bio-sample acquisition and processing, study design, and profiling platform guidelines for blood-based biomarker measurements is paramount for the success of personalized healthcare strategy and development of companion diagnostics.

Study of phosphorylation events for cancer diagnoses and treatment

The activation of signaling cascades in response to extracellular and intracellular stimuli to control cell growth, proliferation and survival, is orchestrated by protein kinases via phosphorylation. A critical issue is the study of the mechanisms of cancer cells for the development of more effective drugs. With the application of the new proteomic technologies, together with the advancement in the sequencing of the human proteome, patients will therefore be benefited by the discovery of novel therapeutic and/or diagnostic protein targets. Furthermore, the advances in proteomic approaches and the Human Proteome Organization (HUPO) have opened a new door which is helpful in the identification of patients at risk and towards improving current therapies. Modification of the signaling-networks via mutations or abnormal protein expression underlies the cause or consequence of many diseases including cancer. Resulting data is used to reveal connections between genes proteins and compounds and the related molecular pathways for underlining disease states. As a delegate of HUPO, for human proteome on children assays and studies, we, at Hospital Universitario Niño Jesús, are seeking to support the human proteome in this context. Clinical goals have to be clearly established and proteomics experts have to set up the appropriate proteomic strategy, which coupled to bioinformatics will make it possible to achieve new therapies for patients with poor prognosis. We envision to combine our up-coming data to the HUPO organization in order to support international efforts to advance the cure of cancer disease.

A proteomic approach to obesity and type 2 diabetes

The incidence of obesity and type diabetes 2 has increased dramatically resulting in an increased interest in its biomedical relevance. However, the mechanisms that trigger the development of diabetes type 2 in obese patients remain largely unknown. Scientific, clinical and pharmaceutical communities are dedicating vast resources to unravel this issue by applying different omics tools. During the last decade, the advances in proteomic approaches and the Human Proteome Organization have opened and are opening a new door that may be helpful in the identification of patients at risk and to improve current therapies. Here, we briefly review some of the advances in our understanding of type 2 diabetes that have occurred through the application of proteomics. We also review, in detail, the current improvements in proteomic methodologies and new strategies that could be employed to further advance our understanding of this pathology. By applying these new proteomic advances, novel therapeutic and/or diagnostic protein targets will be discovered in the obesity/Type 2 diabetes area.

Application of oncoproteomics to aberrant signalling networks in changing the treatment paradigm in acute lymphoblastic leukaemia

Oncoproteomics is an important innovation in the early diagnosis, management and development of personalized treatment of acute lymphoblastic leukaemia (ALL). As inherent factors are not completely known - e.g. age or family history, radiation exposure, benzene chemical exposure, certain viral exposures such as infection with the human T-cell lymphoma/leukaemia virus-1, as well as some inherited syndromes may raise the risk of ALL - each ALL patient may modify the susceptibility of therapy. Indeed, we consider these unknown inherent factors could be explained via coupling cytogenetics plus proteomics, especially when proteins are the ones which play function within cells. Innovative proteomics to ALL therapy may help to understand the mechanism of drug resistance and toxicities, which in turn will provide some leads to improve ALL management. Most important of these are shotgun proteomic strategies to unravel ALL aberrant signalling networks. Some shotgun proteomic innovations and bioinformatic tools for ALL therapies will be discussed. As network proteins are distinctive characteristics for ALL patients, unrevealed by cytogenetics, those network proteins are currently an important source of novel therapeutic targets that emerge from shotgun proteomics. Indeed, ALL evolution can be studied for each individual patient via oncoproteomics.

Combining bioinformatics and MS-based proteomics: clinical implications

Clinical proteomics research aims at i) discovery of protein biomarkers for screening, diagnosis and prognosis of disease, ii) discovery of protein therapeutic targets for improvement of disease prevention, treatment and follow-up, and iii) development of mass spectrometry (MS)-based assays that could be implemented in clinical chemistry, microbiology or hematology laboratories. MS has been increasingly applied in clinical proteomics studies for the identification and quantification of proteins. Bioinformatics plays a key role in the exploitation of MS data in several aspects such as the generation and curation of protein sequence databases, the development of appropriate software for MS data treatment and integration with other omics data and the establishment of adequate standard files for data sharing. In this article, we discuss the main MS approaches and bioinformatics solutions that are currently applied to accomplish the objectives of clinical proteomic research.

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.

The promise and challenge of systems biology in translational medicine

Abnormalities in clinical parameters and routine laboratory tests are frequently detected at late stages of many diseases (too late to cure or to prevent life-threatening complications). Hence earlier diagnostic and prognostic markers are needed for decision making and improving therapeutic outcome. In the present issue of Clinical Science, Rudiger and co-workers report findings from a transcriptomic study, which revealed that changes in transcripts involved in amino-sugar metabolism, p53-dependent cell-cycle arrest, β-adrenergic signalling and intracellular calcium cycling in cardiac tissue of rats with early sepsis could discriminate survivors from non-survivors. These findings underscore the great potential of systems biology in translational medicine. However, further investigations should be done to make the benchside results more feasible for routine clinical practice.

Prospective transcriptomic pathway analysis of human lymphatic vascular insufficiency: identification and validation of a circulating biomarker panel

BACKGROUND

In our previous transcriptional profiling of a murine model, we have identified a remarkably small number of specific pathways with altered expression in lymphedema. In this investigation, we utilized microarray-based transcriptomics of human skin for an unbiased a priori prospective candidate identification, with subsequent validation of these candidates through direct serum assay. The resulting multi-analyte biomarker panel sensitively should sensitively discriminate human lymphedema subjects from normal individuals.

METHODS AND FINDINGS

We enrolled 63 lymphedema subjects and 27 normals in our attempt to discover protein analytes that can distinguish diseased individuals from controls. To minimize technical and biologically irrelevant variation, we first identified potential candidates by performing transcriptional microarray analysis on paired diseased and normal skin specimens sampled from the same individuals. We focused our attention on genes with corresponding protein products that are secreted and took these candidates forward to a protein multiplex assay applied to diseased and normal subjects. We developed a logistic regression-based model on an eventual group of six proteins and validated our system on a separate cohort of study subjects. The area under the receiver operating characteristic curve was calculated to be 0.87 (95% CI : 0.75 to 0.97).

CONCLUSIONS

We have developed an accurate bioassay utilizing proteins representing four central pathogenetic modalities of the disease: lymphangiogenesis, inflammation, fibrosis, and lipid metabolism, suggesting that these proteins are directly related to the pathogenesis of the tissue pathology in lymphatic vascular insufficiency. Further studies are warranted to determine whether this newly-identified biomarker panel will possess utility as an instrument for in vitro diagnosis of early and latent disease; the ultimate applicability to risk stratification, quantitation of disease burden, and response to therapy can easily be envisioned.

Advances in proteomics of digestive juices for the diagnosis of digestive system malignancies

Body fluid proteomic analysis is a new technology and strategy for disease diagnosis and treatment. Blood is the most commonly used specimen in body fluid proteomics, but as a systemic fluid, it has limitations because of complex composition and low abundance of disease-related proteins. In contrast, local body fluids are closest to the lesions, contain more pathological information, and therefore are more valuable in clinical proteomics. In the digestive system, there are a variety of body fluids which are considered potential reservoirs of biomarkers for their quality and quantity of proteins will alter during lesions occurring in corresponding organs. In recent years, more and more clinical proteomic analyses of saliva, gastric juice, bile and pancreatic juice has been reported and the proteins related to digestive cancers have been found, and some proteins show application potentials in cancer diagnosis. However, the proteomic analyses of digestive juices are facing technical challenges in terms of the reproducibility of results and standardization of specimen handling.

Phosphoproteomics and lung cancer research

Massive evidence suggests that genetic abnormalities contribute to the development of lung cancer. These molecular abnormalities may serve as diagnostic, prognostic and predictive biomarkers for this deadly disease. It is imperative to search these biomarkers in different tumorigenesis pathways so as to provide the most appropriate therapy for each individual patient with lung malignancy. Phosphoproteomics is a promising technology for the identification of biomarkers and novel therapeutic targets for cancer. Thousands of proteins interact via physical and chemical association. Moreover, some proteins can covalently modify other proteins post-translationally. These post-translational modifications ultimately give rise to the emergent functions of cells in sequence, space and time. Phosphoproteomics clinical researches imply the comprehensive analysis of the proteins that are expressed in cells or tissues and can be employed at different stages. In addition, understanding the functions of phosphorylated proteins requires the study of proteomes as linked systems rather than collections of individual protein molecules. In fact, proteomics approaches coupled with affinity chromatography strategies followed by mass spectrometry have been used to elucidate relevant biological questions. This article will discuss the relevant clues of post-translational modifications, phosphorylated proteins, and useful proteomics approaches to identify molecular cancer signatures. The recent progress in phosphoproteomics research in lung cancer will be also discussed.

Functional phosphoproteomic mass spectrometry-based approaches

Mass Spectrometry (MS)-based phosphoproteomics tools are crucial for understanding the structure and dynamics of signaling networks. Approaches such as affinity purification followed by MS have also been used to elucidate relevant biological questions in health and disease.

The study of proteomes and phosphoproteomes as linked systems, rather than research studies of individual proteins, are necessary to understand the functions of phosphorylated and un-phosphorylated proteins under spatial and temporal conditions. Phosphoproteome studies also facilitate drug target protein identification which may be clinically useful in the near future.

Here, we provide an overview of general principles of signaling pathways versus phosphorylation. Likewise, we detail chemical phosphoproteomic tools, including pros and cons with examples where these methods have been applied. In addition, basic clues of electrospray ionization and collision induced dissociation fragmentation are detailed in a simple manner for successful phosphoproteomic clinical studies.