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Treatment options for autosomal dominant polycystic kidney disease (ADPKD) will likely become available in the near future, hence reliable diagnostic and prognostic biomarkers for the disease are strongly needed. Here, we aimed to define urinary proteomic patterns in ADPKD patients, which aid diagnosis and risk stratification. By capillary electrophoresis online coupled to mass spectrometry (CE-MS), we compared the urinary peptidome of 41 ADPKD patients to 189 healthy controls and identified 657 peptides with significantly altered excretion, of which 209 could be sequenced using tandem mass spectrometry. A support-vector-machine based diagnostic biomarker model based on the 142 most consistent peptide markers achieved a diagnostic sensitivity of 84.5% and specificity of 94.2% in an independent validation cohort, consisting of 251 ADPKD patients from five different centers and 86 healthy controls. The proteomic alterations in ADPKD included, but were not limited to markers previously associated with acute kidney injury (AKI). The diagnostic biomarker model was highly specific for ADPKD when tested in a cohort consisting of 481 patients with a variety of renal and extrarenal diseases, including AKI. Similar to ultrasound, sensitivity and specificity of the diagnostic score depended on patient age and genotype. We were furthermore able to identify biomarkers for disease severity and progression. A proteomic severity score was developed to predict height adjusted total kidney volume (htTKV) based on proteomic analysis of 134 ADPKD patients and showed a correlation of r = 0.415 (p<0.0001) with htTKV in an independent validation cohort consisting of 158 ADPKD patients. In conclusion, the performance of peptidomic biomarker scores is superior to any other biochemical markers of ADPKD and the proteomic biomarker patterns are a promising tool for prognostic evaluation of ADPKD. © 2013 Kistler et al.

While large numbers of proteomic biomarkers have been described, they are generally not implemented in medical practice. We have investigated the reasons for this shortcoming, focusing on hurdles downstream of biomarker verification, and describe major obstacles and possible solutions to ease valid biomarker implementation. Some of the problems lie in suboptimal biomarker discovery and validation, especially lack of validated platforms with well-described performance characteristics to support biomarker qualification. These issues have been acknowledged and are being addressed, raising the hope that valid biomarkers may start accumulating in the foreseeable future. However, successful biomarker discovery and qualification alone does not suffice for successful implementation. Additional challenges include, among others, limited access to appropriate specimens and insufficient funding, the need to validate new biomarker utility in interventional trials, and large communication gaps between the parties involved in implementation. To address this problem, we propose an implementation roadmap. The implementation effort needs to involve a wide variety of stakeholders (clinicians, statisticians, health economists, and representatives of patient groups, health insurance, pharmaceutical companies, biobanks, and regulatory agencies). Knowledgeable panels with adequate representation of all these stakeholders may facilitate biomarker evaluation and guide implementation for the specific context of use. This approach may avoid unwarranted delays or failure to implement potentially useful biomarkers, and may expedite meaningful contributions of the biomarker community to healthcare.

Diabetic nephropathy (DN) is a progressive kidney disease, a well-known complication of long-standing diabetes. DN is the most frequent reason for dialysis in many Western countries. Early detection may enable development of specific drugs and early initiation of therapy, thereby postponing/preventing the need for renal replacement therapy. We evaluated urinary proteome analysis as a tool for prediction of DN. Capillary electrophoresis-coupled mass spectrometry was used to profile the low-molecular weight proteome in urine. We examined urine samples from a longitudinal cohort of type 1 and 2 diabetic patients (n = 35) using a previously generated chronic kidney disease (CKD) biomarker classifier to assess peptides of collected urines for signs of DN. The application of this classifier to samples of normoalbuminuric subjects up to 5 years prior to development of macroalbuminuria enabled early detection of subsequent progression to macroalbuminuria (area under the curve [AUC] 0.93) compared with urinary albumin routinely used to determine the diagnosis (AUC 0.67). Statistical analysis of each urinary CKD biomarker depicted its regulation with respect to diagnosis of DN over time. Collagen fragments were prominent biomarkers 3-5 years before onset of macroalbuminuria. Before albumin excretion starts to increase, there is a decrease in collagen fragments. Urinary proteomics enables noninvasive assessment of DN risk at an early stage via determination of specific collagen fragments.

Female patients affected by Fabry disease, an X-linked lysosomal storage disorder, exhibit a wide spectrum of symptoms, which renders diagnosis, and treatment decisions challenging. No diagnostic test, other than sequencing of the alpha-galactosidase A gene, is available and no biomarker has been proven useful to screen for the disease, predict disease course and monitor response to enzyme replacement therapy. Here, we used urine proteomic analysis based on capillary electrophoresis coupled to mass spectrometry and identified a biomarker profile in adult female Fabry patients. Urine samples were taken from 35 treatment-naïve female Fabry patients and were compared to 89 age-matched healthy controls. We found a diagnostic biomarker pattern that exhibited 88.2% sensitivity and 97.8% specificity when tested in an independent validation cohort consisting of 17 treatment-naïve Fabry patients and 45 controls. The model remained highly specific when applied to additional control patients with a variety of other renal, metabolic and cardiovascular diseases. Several of the 64 identified diagnostic biomarkers showed correlations with measures of disease severity. Notably, most biomarkers responded to enzyme replacement therapy, and 8 of 11 treated patients scored negative for Fabry disease in the diagnostic model. In conclusion, we defined a urinary biomarker model that seems to be of diagnostic use for Fabry disease in female patients and may be used to monitor response to enzyme replacement therapy.

ln the comparative proteomics studies, visualization has become an emerging technique in the analysis. It provides an intuitive overview of large-scale mass spectrometry data sets with possibilities to further explore data details at different levels. While different visualization tools have already been developed, they are often designed to handle one or a few mass spectrometry data sets. Apparently, this is not enough as many proteomics studies involve many samples. It is much desired to simultaneously visualize all data sets in order to better examine data sets. In this paper, we present a visualization tool named SyncPro for differential analysis of multiple pre-processed proteomics data sets. It offers features to (i) compare many dIlta sets simultaneously; (ii) facilitate data exploration through selection and extraction; (iii) quickly judge the quality of selected features. Our proposed method further enhances the functions of existing visualization tools. ©2010 IEEE.

BACKGROUND: The pathogenesis of diabetes mellitus (DM) is variable, comprising different inflammatory and immune responses. Proteome analysis holds the promise of delivering insight into the pathophysiological changes associated with diabetes. Recently, we identified and validated urinary proteomics biomarkers for diabetes. Based on these initial findings, we aimed to further validate urinary proteomics biomarkers specific for diabetes in general, and particularity associated with either type 1 (T1D) or type 2 diabetes (T2D). METHODOLOGY/PRINCIPAL FINDINGS: Therefore, the low-molecular-weight urinary proteome of 902 subjects from 10 different centers, 315 controls and 587 patients with T1D (n = 299) or T2D (n = 288), was analyzed using capillary-electrophoresis mass-spectrometry. The 261 urinary biomarkers (100 were sequenced) previously discovered in 205 subjects were validated in an additional 697 subjects to distinguish DM subjects (n = 382) from control subjects (n = 315) with 94% (95% CI: 92-95) accuracy in this study. To identify biomarkers that differentiate T1D from T2D, a subset of normoalbuminuric patients with T1D (n = 68) and T2D (n = 42) was employed, enabling identification of 131 biomarker candidates (40 were sequenced) differentially regulated between T1D and T2D. These biomarkers distinguished T1D from T2D in an independent validation set of normoalbuminuric patients (n = 108) with 88% (95% CI: 81-94%) accuracy, and in patients with impaired renal function (n = 369) with 85% (95% CI: 81-88%) accuracy. Specific collagen fragments were associated with diabetes and type of diabetes indicating changes in collagen turnover and extracellular matrix as one hallmark of the molecular pathophysiology of diabetes. Additional biomarkers including inflammatory processes and pro-thrombotic alterations were observed. CONCLUSIONS/SIGNIFICANCE: These findings, based on the largest proteomic study performed to date on subjects with DM, validate the previously describ

Background. The renal Fanconi syndrome (FS) is characterized by renal glucosuria, loss of electrolytes, bicarbonate and lactate, generalized hyperaminoaciduria and low-molecular-weight proteinuria. We studied the urinary low-molecular-weight proteome to identify excreted peptides indicative of a pathogenetic mechanism leading to tubular dysfunction. Methods. We established a urinary proteome pattern using capillary electrophoresis mass spectrometry (CE-MS) of 7 paediatric patients with cystinosis and 6 patients with ifosfamide-induced FS as the study group, and 54 healthy volunteers and 45 patients suffering from other renal diseases such as lupus nephritis (n = 8), focal segmental glomerulosclerosis (n = 27), minimal change disease (n = 7) and membranous glomerulonephritis (n = 3) as controls. Consequently, we conducted a blinded study consisting of 11 FS patients and 9 patients with renal disease other than FS. Additionally, we applied this pattern to 294 previously measured samples of patients with different renal diseases. Amino acid sequences of some marker proteins were obtained. Results. Specificity for detecting FS was 89% and sensitivity was 82%. The marker peptides constituting the proteome pattern are fragments derived from osteopontin, uromodulin and collagen alpha-1. Conclusions. CE-MS can be used to diagnose FS in paediatric patients and might be a future tool for the non-invasive diagnosis of FS. The reduced amount of the marker proteins osteopontin and uromodulin indicates loss of function of tubular excretion in all patients suffering from FS regardless of the underlying cause. In addition, the six different fragments of the collagen alpha-1 (I) chain were either elevated or reduced in the urine. This indicates a change of proteases in collagen degradation as observed in interstitial fibrosis. These changes were prominent irrespectively of the stages of FS. This indicates fibrosis as an early starting pathogenetic reason for the development of renal

ABSTRACT It is widely thought that the biological outcomes of Raf-1 activation are solely attributable to the activation of the MEK/extracellular signal-regulated kinase (ERK) pathway. However, an increasing number of reports suggest that some Raf-1 functions are independent of this pathway. In this report we show that mutation of the amino-terminal 14-3-3 binding site of Raf-1 uncouples its ability to activate the MEK/ERK pathway from the induction of cell transformation and differentiation. In NIH 3T3 fibroblasts and COS-1 cells, mutation of serine 259 resulted in Raf-1 proteins which activated the MEK/ERK pathway as efficiently as v-Raf. However, in contrast to v-Raf, RafS259 mutants failed to transform. They induced morphological alterations and slightly accelerated proliferation in NIH 3T3 fibroblasts but were not tumorigenic in mice and behaved like wild-type Raf-1 in transformation assays measuring loss of contact inhibition or anchorage-independent growth. Curiously, the RafS259 mutants inhibited focus induction by an activated MEK allele, suggesting that they can hyperactivate negative-feedback pathways. In primary cultures of postmitotic chicken neuroretina cells, RafS259A was able to sustain proliferation to a level comparable to that sustained by the membrane-targeted transforming Raf-1 protein, RafCAAX. In contrast, RafS259A was only a poor inducer of neurite formation in PC12 cells in comparison to RafCAAX. Thus, RafS259 mutants genetically separate MEK/ERK activation from the ability of Raf-1 to induce transformation and differentiation. The results further suggest that RafS259 mutants inhibit signaling pathways required to promote these biological processes.

ABSTRACT The Raf-1 kinase activates the ERK (extracellular-signal-regulated kinase) pathway. The cyclic AMP (cAMP)-dependent protein kinase (PKA) can inhibit Raf-1 by direct phosphorylation. We have mapped all cAMP-induced phosphorylation sites in Raf-1, showing that serines 43, 259, and 621 are phosphorylated by PKA in vitro and induced by cAMP in vivo. Serine 43 phosphorylation decreased the binding to Ras in serum-starved but not in mitogen-stimulated cells. However, the kinase activity of a RafS43A mutant was fully inhibited by PKA. Mutation of serine 259 increased the basal Raf-1 activity and rendered it largely resistant to inhibition by PKA. cAMP increased Raf-1 serine 259 phosphorylation in a PKA-dependent manner with kinetics that correlated with ERK deactivation. PKA also decreased Raf-1 serine 338 phosphorylation of Raf-1, previously shown to be required for Raf-1 activation. Serine 338 phosphorylation of a RafS259A mutant was unaffected by PKA. Using RafS259 mutants we also demonstrate that Raf-1 is the sole target for PKA inhibition of ERK and ERK-induced gene expression, and that Raf-1 inhibition is mediated mainly through serine 259 phosphorylation.