Performance benchmarking microplate-immunoassays for quantifying target-specific cysteine oxidation reveals their potential for understanding redox-regulation and oxidative stress.

The antibody-linked oxi-state assay (ALISA) for quantifying target-specific cysteine oxidation can benefit specialist and non-specialist users. Specialists can benefit from time-efficient analysis and high-throughput target and/or sample n-plex capacities. The simple and accessible "off-the-shelf" nature of ALISA brings the benefits of oxidative damage assays to non-specialists studying redox-regulation. Until performance benchmarking establishes confidence in the "unseen" microplate results, ALISA is unlikely to be widely adopted. Here, we implemented pre-set pass/fail criteria to benchmark ALISA by robustly evaluating immunoassay performance in diverse biological contexts. ELISA-mode ALISA assays were accurate, reliable, and sensitive. For example, the average inter-assay CV for detecting 20%- and 40%-oxidised PRDX2 or GAPDH standards was 4.6% (range: 3.6-7.4%). ALISA displayed target-specificity. Immunodepleting the target decreased the signal by ∼75%. Single-antibody formatted ALISA failed to quantify the matrix-facing alpha subunit of the mitochondrial ATP synthase. However, RedoxiFluor quantified the alpha subunit displaying exceptional performance in the single-antibody format. ALISA discovered that (1) monocyte-to-macrophage differentiation amplified PRDX2-specific cysteine oxidation in THP-1 cells and (2) exercise increased GAPDH-specific cysteine oxidation in human erythrocytes. The "unseen" microplate data were "seen-to-be-believed" via orthogonal visually displayed immunoassays like the dimer method. Finally, we established target (n = 3) and sample (n = 100) n-plex capacities in ∼4 h with 50-70 min hands-on time. Our work showcases the potential of ALISA to advance our understanding of redox-regulation and oxidative stress.

Gene Ontology (GO)-Driven Inference of Candidate Proteomic Markers Associated with Muscle Atrophy Conditions.

Skeletal muscle homeostasis is essential for the maintenance of a healthy and active lifestyle. Imbalance in muscle homeostasis has significant consequences such as atrophy, loss of muscle mass, and progressive loss of functions. Aging-related muscle wasting, sarcopenia, and atrophy as a consequence of disease, such as cachexia, reduce the quality of life, increase morbidity and result in an overall poor prognosis. Investigating the muscle proteome related to muscle atrophy diseases has a great potential for diagnostic medicine to identify (i) potential protein biomarkers, and (ii) biological processes and functions common or unique to muscle wasting, cachexia, sarcopenia, and aging alone. We conducted a meta-analysis using gene ontology (GO) analysis of 24 human proteomic studies using tissue samples (skeletal muscle and adipose biopsies) and/or biofluids (serum, plasma, urine). Whilst there were few similarities in protein directionality across studies, biological processes common to conditions were identified. Here we demonstrate that the GO analysis of published human proteomics data can identify processes not revealed by single studies. We recommend the integration of proteomics data from tissue samples and biofluids to yield a comprehensive overview of the human skeletal muscle proteome. This will facilitate the identification of biomarkers and potential pathways of muscle-wasting conditions for use in clinics.

Integrative OMICS Data-Driven Procedure Using a Derivatized Meta-Analysis Approach.

The wealth of high-throughput data has opened up new opportunities to analyze and describe biological processes at higher resolution, ultimately leading to a significant acceleration of scientific output using high-throughput data from the different omics layers and the generation of databases to store and report raw datasets. The great variability among the techniques and the heterogeneous methodologies used to produce this data have placed meta-analysis methods as one of the approaches of choice to correlate the resultant large-scale datasets from different research groups. Through multi-study meta-analyses, it is possible to generate results with greater statistical power compared to individual analyses. Gene signatures, biomarkers and pathways that provide new insights of a phenotype of interest have been identified by the analysis of large-scale datasets in several fields of science. However, despite all the efforts, a standardized regulation to report large-scale data and to identify the molecular targets and signaling networks is still lacking. Integrative analyses have also been introduced as complementation and augmentation for meta-analysis methodologies to generate novel hypotheses. Currently, there is no universal method established and the different methods available follow different purposes. Herein we describe a new unifying, scalable and straightforward methodology to meta-analyze different omics outputs, but also to integrate the significant outcomes into novel pathways describing biological processes of interest. The significance of using proper molecular identifiers is highlighted as well as the potential to further correlate molecules from different regulatory levels. To show the methodology's potential, a set of transcriptomic datasets are meta-analyzed as an example.

ORA , FCS , and PT Strategies in Functional Enrichment Analysis.

Downstream analysis of OMICS data requires interpretation of many molecular components considering current biological knowledge. Most tools used at present for functional enrichment analysis workflows applied to the field of proteomics are either borrowed or have been modified from genomics workflows to accommodate proteomics data. While the field of proteomics data analytics is evolving, as is the case for molecular annotation coverage, one can expect the rise of enhanced databases with less redundant ontologies spanning many elements of the tree of life. The methodology described here shows in practical steps how to perform overrepresentation analysis, functional class scoring, and pathway-topology analysis using a preexisting neurological dataset of proteomic data.

Integrative Analysis of Incongruous Cancer Genomics and Proteomics Datasets.

Cancer is a complex disease characterized by molecular heterogeneity and the involvement of several cellular mechanisms throughout its evolution and pathogenesis. Despite the great efforts made to untangle these mechanisms, cancer pathophysiology remains far from clear. So far, panels of biomarkers have been reported from high-throughput data generated through different platforms. These biomarkers are primarily focused on one type of coding molecules such as transcripts or proteins, mainly due to the apparent heterogeneity of output data resulting from the use of various techniques specific to the molecular type. Hence, there is a major need to understand how these molecules interact and complement each other to be able to explain the deregulated processes involved. The breadth of large-scale data availability as well as the lack of in-depth analysis of publicly available data has raised concerns and enabled opportunities for new strategies to analyze "Big data" more comprehensively. Here, a new protocol to perform integrative analysis based on a systems biology approach is described. The foundation of the approach relies on groups of datasets from published studies compared within the original described groups and organized in a designated format to allow the integration and cross-comparison among different studies and different platforms. This approach follows an unbiased hypothesis-free methodology that will facilitate the identification of commonalities among different data-set sources, and ultimately map and characterize specific molecular pathways using significantly deregulated molecules. This in turn will generate novel insights about the mechanisms deregulated in complex diseases such as cancer.

Immunological Techniques to Assess Protein Thiol Redox State: Opportunities, Challenges and Solutions.

To understand oxidative stress, antioxidant defense, and redox signaling in health and disease it is essential to assess protein thiol redox state. Protein thiol redox state is seldom assessed immunologically because of the inability to distinguish reduced and reversibly oxidized thiols by Western blotting. An underappreciated opportunity exists to use Click PEGylation to realize the transformative power of simple, time and cost-efficient immunological techniques. Click PEGylation harnesses selective, bio-orthogonal Click chemistry to separate reduced and reversibly oxidized thiols by selectively ligating a low molecular weight polyethylene glycol moiety to the redox state of interest. The resultant ability to disambiguate reduced and reversibly oxidized species by Western blotting enables Click PEGylation to assess protein thiol redox state. In the present review, to enable investigators to effectively harness immunological techniques to assess protein thiol redox state we critique the chemistry, promise and challenges of Click PEGylation.

Reversible Thiol Oxidation Inhibits the Mitochondrial ATP Synthase in Xenopus Laevis Oocytes.

Oocytes are postulated to repress the proton pumps (e.g., complex IV) and ATP synthase to safeguard mitochondrial DNA homoplasmy by curtailing superoxide production. Whether the ATP synthase is inhibited is, however, unknown. Here we show that: oligomycin sensitive ATP synthase activity is significantly greater (~170 vs. 20 nmol/min-1/mg-1) in testes compared to oocytes in Xenopus laevis (X. laevis). Since ATP synthase activity is redox regulated, we explored a regulatory role for reversible thiol oxidation. If a protein thiol inhibits the ATP synthase, then constituent subunits must be reversibly oxidised. Catalyst-free trans-cyclooctene 6-methyltetrazine (TCO-Tz) immunocapture coupled to redox affinity blotting reveals several subunits in F1 (e.g., ATP-α-F1) and Fo (e.g., subunit c) are reversibly oxidised. Catalyst-free TCO-Tz Click PEGylation reveals significant (~60%) reversible ATP-α-F1 oxidation at two evolutionary conserved cysteine residues (C244 and C294) in oocytes. TCO-Tz Click PEGylation reveals ~20% of the total thiols in the ATP synthase are substantially oxidised. Chemically reversing thiol oxidation significantly increased oligomycin sensitive ATP synthase activity from ~12 to 100 nmol/min-1/mg-1 in oocytes. We conclude that reversible thiol oxidation inhibits the mitochondrial ATP synthase in X. laevis oocytes.

The influence of hypoxia on the prostate cancer proteome.

Prostate cancer accounts for around 15% of male deaths in Western Europe and is the second leading cause of cancer death in men after lung cancer. Mounting evidence suggests that prostate cancer deposits exist within a hypoxic environment and this contributes to radio-resistance thus hampering one of the major therapies for this cancer. Recent reports have shown that nitric oxide (NO) donating non-steroidal anti-inflammatory drugs (NSAIDs) reduced tumour hypoxia as well as maintaining a radio-sensitising/therapeutic effect on prostate cancer cells. The aim of this study was to evaluate the impact of hypoxia on the proteome of the prostate and to establish whether NO-NSAID treatment reverted the protein profiles back to their normoxic status. To this end an established hormone insensitive prostate cancer cell line, PC-3, was cultured under hypoxic and normoxic conditions before and following exposure to NO-NSAID in combination with selected other common prostate cancer treatment types. The extracted proteins were analysed by ion mobility-assisted data independent acquisition mass spectrometry (MS), combined with multivariate statistical analyses, to measure hypoxia-induced alterations in the proteome of these cells. The analyses demonstrated that under hypoxic conditions there were well-defined, significantly regulated/differentially expressed proteins primarily involved with structural and binding processes including, for example, TUBB4A, CIRP and PLOD1. Additionally, the exposure of hypoxic cells to NSAID and NO-NSAID agents, resulted in some of these proteins being differentially expressed; for example, both PCNA and HNRNPA1L were down-regulated, corresponding with disruption in the nucleocytoplasmic shuttling process.

Bile and urine peptide marker profiles: access keys to molecular pathways and biological processes in cholangiocarcinoma.

BACKGROUND: Detection of cholangiocarcinoma (CCA) remains a diagnostic challenge. We established diagnostic peptide biomarkers in bile and urine based on capillary electrophoresis coupled to mass spectrometry (CE-MS) to detect both local and systemic changes during CCA progression. In a prospective cohort study we recently demonstrated that combined bile and urine proteome analysis could further improve diagnostic accuracy of CCA diagnosis in patients with unknown biliary strictures. As a continuation of these investigations, the aim of the present study was to investigate the pathophysiological mechanisms behind the molecular determinants reflected by bile and urine peptide biomarkers. METHODS: Protease mapping and gene ontology cluster analysis were performed for the previously defined CE-MS based biomarkers in bile and urine. For that purpose, bile and urine peptide profiles (from samples both collected at the date of endoscopy) were investigated from a representative cohort of patients with benign (n = 76) or CCA-associated (n = 52) biliary strictures (verified during clinical follow-up). This was supplemented with a literature search for the association of the individual biomarkers included in the proteomic patterns with CCA or cancer progression. RESULTS: For most of the peptide markers, association to CCA has been described in literature. Protease mapping revealed ADAMTS4 activity in cleavage of both bile and urine CCA peptide biomarkers. Furthermore, increased chymase activity in bile points to mast cell activation at the tumor site. Gene ontology cluster analysis indicates cellular response to chemical stimuli and stress response as local and extracellular matrix reorganization by tissue destruction and repair as systemic events. The analysis further supports that the mapped proteases are drivers of local and systemic events. CONCLUSIONS: The study supports connection of the CCA-associated peptide biomarkers to the molecular pathophysiology and indicates an involvement in epithelial-to-mesenchymal transition, generation of cancer-associated fibroblasts and activation of residual immune cells. Proteases, extracellular matrix components, inflammatory cytokines, proangiogenic, growth and vasoactive factors released from the tumor microenvironment are drivers of systemic early events during CCA progression.

Catalyst-free Click PEGylation reveals substantial mitochondrial ATP synthase sub-unit alpha oxidation before and after fertilisation.

Using non-reducing Western blotting to assess protein thiol redox state is challenging because most reduced and oxidised forms migrate at the same molecular weight and are, therefore, indistinguishable. While copper catalysed Click chemistry can be used to ligate a polyethylene glycol (PEG) moiety termed Click PEGylation to mass shift the reduced or oxidised form as desired, the potential for copper catalysed auto-oxidation is problematic. Here we define a catalyst-free trans-cyclooctene-methyltetrazine (TCO-Tz) inverse electron demand Diels Alder chemistry approach that affords rapid (k ~2000 M-1 s-1), selective and bio-orthogonal Click PEGylation. We used TCO-Tz Click PEGylation to investigate how fertilisation impacts reversible mitochondrial ATP synthase F1-Fo sub-unit alpha (ATP-α-F1) oxidation-an established molecular correlate of impaired enzyme activity-in Xenopus laevis. TCO-Tz Click PEGylation studies reveal substantial (~65%) reversible ATP-α-F1 oxidation at evolutionary conserved cysteine residues (i.e., C244 and C294) before and after fertilisation. A single thiol is, however, preferentially oxidised likely due to greater solvent exposure during the catalytic cycle. Selective reduction experiments show that: S-glutathionylation accounts for ~50-60% of the reversible oxidation observed, making it the dominant oxidative modification type. Intermolecular disulphide bonds may also contribute due to their relative stability. Substantial reversible ATP-α-F1 oxidation before and after fertilisation is biologically meaningful because it implies low mitochondrial F1-Fo ATP synthase activity. Catalyst-free TCO-Tz Click PEGylation is a valuable new tool to interrogate protein thiol redox state in health and disease.

Identification of diagnostic upper gastrointestinal cancer tissue type-specific urinary biomarkers.

Several potential urinary biomarkers exhibiting an association with upper gastrointestinal tumour growth have been previously identified, of which S100A6, S100A9, rabenosyn-5 and programmed cell death 6-interacting protein (PDCD6IP) were further validated and found to be upregulated in malignant tumours. The cancer cohort from our previous study was subclassified to assess whether distinct molecular markers can be identified for each individual cancer type using a similar approach. Urine samples from patients with cancers of the stomach, oesophagus, oesophagogastric junction or pancreas were analysed by surface-enhanced laser desorption/ionization-time-of-flight mass spectrometry using both CM10 and IMAC30 (Cu2+-complexed) chip types and LC-MS/MS-based mass spectrometry after chromatographic enrichment. This was followed by protein identification, pattern matching and validation by western blotting. We found 8 m/z peaks with statistical significance for the four cancer types investigated, of which m/z 2447 and 2577 were identified by pattern matching as fragments of cathepsin-B (CTSB) and cystatin-B (CSTB); both molecules are indicative of pancreatic cancer. Additionally, we observed a potential association of upregulated α-1-antichymotrypsin with pancreatic and gastric cancers, of PDCD6IP, vitelline membrane outer layer protein 1 homolog (VMO1) and triosephosphate isomerase (TPI1) with oesophagogastric junctional cancers, and of complement C4-A, prostatic acid phosphatase, azurocidin and histone-H1 with oesophageal cancer. Furthermore, the potential pancreatic cancer biomarkers CSTB and CTSB were validated independently by western blotting. Therefore, the present study identified two new potential urinary biomarkers that appear to be associated with pancreatic cancer. This may provide a simple, non-invasive screening test for use in the clinical setting.

Proteomics in Kidney Allograft Transplantation-Application of Molecular Pathway Analysis for Kidney Allograft Disease Phenotypic Biomarker Selection.

There is a need for accurate, robust, non-invasive methods to provide early diagnosis of graft lesions after kidney transplantation. A multitude of proteomic biomarkers for the major kidney allograft disease phenotypes defined by the BANFF classification criteria have been described in literature. None of these biomarkers have been established in the clinic. A key reason for this is the lack of clinical validation which is difficult, as even the gold standard of diagnosis, kidney biopsy, is often ambiguous. The semantic clustering by ReviGO on top of transcriptomic pathway analysis is evaluated to connect histological and transcriptomic kidney allograft disease characteristics with proteomic biomarker qualification. By using public data generated in microarray studies of kidney allograft tissue, biological processes and key molecules specifically associated with the different kidney allograft disease phenotypes are identified. Semantic clustering holds the promise to guide adaptation of proteomic marker panels to molecular pathology. This can support the development of noninvasive tests (e.g. in urine, by capillary electrophoresis mass spectrometry) that simultaneously detect diverse kidney allograft phenotypes with high accuracy and sensitivity.

Acute stress alters the rates of degradation of cardiac muscle proteins.

Stressful experiences can have detrimental effects on many aspects of health and wellbeing. The zebrafish (Danio rerio) is a widely used model for stress research and a stress phenotype can be induced by manipulating the environmental conditions and social interactions. In this study we have combined a zebrafish stress model with the measurement of degradation rates of soluble cardiac muscle proteins. The results showed that the greater the stress response in the zebrafish the lower the level of overall protein degradation. On comparing the rates of degradation for individual proteins it was found that four main pathways were altered in response to stress conditions with decreased degradation for proteins involved in glucose metabolism, gluconeogenesis, the ubiquitin-proteasome system (UPS) and peroxisomal proliferator-activated receptor (PPAR) signalling pathways. Taken together, these data indicate that under stress conditions zebrafish preserve cardiac muscle proteins required for the 'fight or flight' response together with proteins that play a role in stress mitigation. SIGNIFICANCE: This study is the first to investigate the impact of stressful experiences on the dynamics of protein turnover in cardiac muscle. Using an established zebrafish model of human stress it has been possible to map key pathways at the protein level. The results show that the rates of degradation of cardiac proteins involved in glucose metabolism, UPS activity, hypoxia and PPAR signalling are decreased in stressed zebrafish. These findings indicate that proteins involved in the 'fight or flight' response to stress are conserved by the heart together with proteins that play a role in stress mitigation. This work provides the basis for more detailed investigations aimed at understanding the molecular effects of stress, which has implications for human health and disease.

Proteomic strategies to unravel age-related redox signalling defects in skeletal muscle.

Increased oxidative damage and disrupted redox signalling are consistently associated with age-related loss of skeletal muscle mass and function. Redox signalling can directly regulate biogenesis and degradation pathways and indirectly via activation of key transcription factors. Contracting skeletal muscle fibres endogenously generate free radicals (e.g. superoxide) and non-radical derivatives (e.g. hydrogen peroxide). Exercise induced redox signalling can promote beneficial adaptive responses that are disrupted by age-related redox changes. Identifying and quantifying the redox signalling pathways responsible for successful adaptation to exercise makes skeletal muscle an attractive physiological model for redox proteomic approaches. Site specific identification of the redox modification and quantification of site occupancy in the context of protein abundance remains a crucial concept for redox proteomics approaches. Notwithstanding, the technical limitations associated with skeletal muscle for proteomic analysis, we discuss current approaches for the identification and quantification of transient and stable redox modifications that have been employed to date in ageing research. We also discuss recent developments in proteomic approaches in skeletal muscle and potential implications and opportunities for investigating disrupted redox signalling in skeletal muscle ageing.

MAGE genes in the kidney: identification of MAGED2 as upregulated during kidney injury and in stressed tubular cells.

BACKGROUND: Mutations in Melanoma Antigen-encoding Gene D2 (MAGED2) promote tubular dysfunction, suggesting that MAGE proteins may play a role in kidney pathophysiology. We have characterized the expression and regulation of MAGE genes in normal kidneys and during kidney disease. METHODS: The expression of MAGE genes and their encoded proteins was explored by systems biology multi-omics (kidney transcriptomics and proteomics) in healthy adult murine kidneys and following induction of experimental acute kidney injury (AKI) by a folic acid overdose. Changes in kidney expression during nephrotoxic AKI were validated by quantitative reverse transcription-polymerase chain reaction (qRT-PCR), western blot and immunohistochemistry. Factors regulating gene expression were studied in cultured tubular cells. RESULTS: Five MAGE genes (MAGED1, MAGED2, MAGED3, MAGEH1, MAGEE1) were expressed at the mRNA level in healthy adult mouse kidneys, as assessed by RNA-Seq. Additionally, MAGED2 was significantly upregulated during experimental AKI as assessed by array transcriptomics. Kidney proteomics also identified MAGED2 as upregulated during AKI. The increased kidney expression of MAGED2 mRNA and protein was confirmed by qRT-PCR and western blot, respectively, in murine folic acid- and cisplatin-induced AKI. Immunohistochemistry located MAGED2 to tubular cells in experimental and human kidney injury. Tubular cell stressors [serum deprivation and the inflammatory cytokine tumour necrosis factor-like weak inducer of apoptosis (TWEAK)] upregulated MAGED2 in cultured tubular cells. CONCLUSIONS: MAGED2 is upregulated in tubular cells in experimental and human kidney injury and is increased by stressors in cultured tubular cells. This points to a role of MAGED2 in tubular cell injury during kidney disease that should be dissected by carefully designed functional approaches.

C/VDdb: A multi-omics expression profiling database for a knowledge-driven approach in cardiovascular disease (CVD).

The cardiovascular disease (C/VD) database is an integrated and clustered information resource that covers multi-omic studies (microRNA, genomics, proteomics and metabolomics) of cardiovascular-related traits with special emphasis on coronary artery disease (CAD). This resource was built by mining existing literature and public databases and thereafter manual biocuration was performed. To enable integration of omic data from distinct platforms and species, a specific ontology was applied to tie together and harmonise multi-level omic studies based on gene and protein clusters (CluSO) and mapping of orthologous genes (OMAP) across species. CAD continues to be a leading cause of death in the population worldwide, and it is generally thought to be an age-related disease. However, CAD incidence rates are now known to be highly influenced by environmental factors and interactions, in addition to genetic determinants. With the complexity of CAD aetiology, there is a difficulty in research studies to elucidate general elements compared to other cardiovascular diseases. Data from 92 studies, covering 13945 molecular entries (4353 unique molecules) is described, including data descriptors for experimental setup, study design, discovery-validation sample size and associated fold-changes of the differentially expressed molecular features (p-value<0.05). A dedicated interactive web interface, equipped with a multi-parametric search engine, data export and indexing menus are provided for a user-accessible browsing experience. The main aim of this work was the development of a data repository linking clinical information and molecular differential expression in several CVD-related traits from multi-omics studies (genomics, transcriptomics, proteomics and metabolomics). As an example case of how to query and identify data sets within the database framework and concomitantly demonstrate the database utility, we queried CAD-associated studies and performed a systems-level integrative analysis. URL: www.padb.org/cvd.

Urinary diagnostic proteomic markers for dynapenia in cancer patients.

Dynapenia is defined as the age-related loss of muscle strength, and plays a significant role in the loss of physical function and increased risk of disability among older individuals. The need for an early diagnosis supports the search for a biomarker that reflects muscle 'weakening'. This has previously proven difficult due to patient heterogeneity at presentation and lack of understanding of the underlying molecular mechanisms. The aim of the present study was to identify potential urinary biomarkers of dynapenia in patients undergoing potentially curative surgery for upper gastrointestinal cancer. Maximum isometric knee extensor strength (strain gauge) and maximum leg extensor power (Nottingham power rig) measurements were taken. Cut-off values for dynapenia were based on the Allied Dunbar national fitness survey. Values below the 5th percentile for the population matched for age and sex on the Allied Dunbar national fitness survey were used to stratify the cohort into dynapenic or normal. Urine samples taken at induction of anaesthesia were analysed by SELDI-TOF mass spectrometry using CM10 and IMAC30 chip-types to establish statistically significant m/z peak fingerprint patterns, followed by in-gel LC-MS/MS to identify molecular constituents. Statistical analysis of decision-tree calculations using Biomarker Pattern software resulted in models with sensitivities of 86 and 96%, specificities of 81 and 89%, and overall correctness of 84 and 93%, when applied to the entire cohort for power and strength measurement-based stratifications using the IMAC30 chip-type and the CM10 chip-type, respectively. The molecular identities of 10 peaks of interest were further investigated. After subtraction of potentially unrelated proteins, they were identified as fragments of Annexin A1, collagen α-1 (XV), perlecan and myotrophin. These results demonstrate that urinary screening can be used to define cancer-associated muscle weakness, and the identification of potential biomarkers could be invaluable in establishing a rapid test to measure and assess dynapenia in the clinical setting.

Proteomic identification of potential markers of myosteatosis in human urine.

Myosteatosis, the infiltration of fat in skeletal muscle, is associated with lower skeletal muscle density (SMD) as detected by computed tomography (CT). It increases with aging and obesity and is thought to play a role in the aetiology of insulin resistance and type II diabetes. The clinical significance of myosteatosis in cancer cachexia, however, remains to be determined. Along with demonstrable subcutaneous and visceral lipolysis, myosteatosis may also be a key component of the syndrome. We aimed to investigate the use of human urine as a non-invasive way to screen for molecular biomarkers of myosteatosis/reduced SMD using SELDI-TOF mass spectrometry. Pre-operative CT scans of patients undergoing surgery for upper gastrointestinal or hepatopancreaticobiliary cancer were analysed at the level of the third lumbar vertebrae. Myosteatosis was inferred as the presence of reduced SMD, which was defined as Hounsfield units for skeletal muscle <39.5 (two standard deviations below a normal healthy cohort). Urine was analysed by mass spectrometry using CM10 and IMAC30 SELDI-chips. Peaks observed in the CM10 and IMAC30 chip types, showed marked expressional differences between control and myosteatosis, were further investigated by mascot SELDI matrix matching. A total of 55 patients was recruited; 31 patients were found to be myosteatotic on CT scan. Application of the IMAC30-derived model to the entire cohort showed a sensitivity of 97%, specificity of 71% and an overall correctness of 85%. Application of the CM10 chipset-based model to the entire cohort, showed a 77% sensitivity, 67% specificity and 73% overall correctness. Analysis of the peaks of interest resulted in the identification of significant fragments of cathepsin C, argin, arylsulfatase A and glial fibrillary acidic protein. We identified several potential urinary molecular biomarkers associated with reduced SMD in cancer. Such markers are potentially useful in deriving a clinical screening test for myosteatosis.

Integrative analysis of Multiple Sclerosis using a systems biology approach.

Multiple sclerosis (MS) is a chronic autoimmune disorder characterized by inflammatory-demyelinating events in the central nervous system. Despite more than 40 years of MS research its aetiology remains unknown. This study aims to identify the most frequently reported and consistently regulated molecules in MS in order to generate molecular interaction networks and thereby leading to the identification of deregulated processes and pathways which could give an insight of the underlying molecular mechanisms of MS. Driven by an integrative systems biology approach, gene-expression profiling datasets were combined and stratified into "Non-treated" and "Treated" groups and additionally compared to other disease patterns. Molecular identifiers from dataset comparisons were matched to our Multiple Sclerosis database (MuScle; www.padb.org/muscle ). From 5079 statistically significant molecules, correlation analysis within groups identified a panel of 16 high-confidence genes unique to the naïve MS phenotype, whereas the "Treated" group reflected a common pattern associated with autoimmune disease. Pathway and gene-ontology clustering identified the Interferon gamma signalling pathway as the most relevant amongst all significant molecules, and viral infections as the most likely cause of all down-stream events observed. This hypothesis-free approach revealed the most significant molecular events amongst different MS phenotypes which can be used for further detailed studies.

Proteomics and Metabolomics for AKI Diagnosis.

Acute kidney injury (AKI) is a severe and frequent condition in hospitalized patients. Currently, no efficient therapy of AKI is available. Therefore, efforts focus on early prevention and potentially early initiation of renal replacement therapy to improve the outcome in AKI. The detection of AKI in hospitalized patients implies the need for early, accurate, robust, and easily accessible biomarkers of AKI evolution and outcome prediction because only a narrow window exists to implement the earlier-described measures. Even more challenging is the multifactorial origin of AKI and the fact that the changes of molecular expression induced by AKI are difficult to distinguish from those of the diseases associated or causing AKI as shock or sepsis. During the past decade, a considerable number of protein biomarkers for AKI have been described and we expect from recent advances in the field of omics technologies that this number will increase further in the future and be extended to other sorts of biomolecules, such as RNAs, lipids, and metabolites. However, most of these biomarkers are poorly defined by their AKI-associated molecular context. In this review, we describe the state-of-the-art tissue and biofluid proteomic and metabolomic technologies and new bioinformatics approaches for proteomic and metabolomic pathway and molecular interaction analysis. In the second part of the review, we focus on AKI-associated proteomic and metabolomic biomarkers and briefly outline their pathophysiological context in AKI.