News | 2013
Sci Transl Med. 2013 Aug 14;5(198):198ra106. doi: 10.1126/scitranslmed.3005807.
Fetal Urinary Peptides to Predict Postnatal Outcome of Renal Disease in Fetuses with Posterior Urethral Valves (PUV).
Klein J, Lacroix C, Caubet C, Siwy J, Zürbig P, Dakna M, Muller F, Breuil B, Stalmach A, Mullen W, Mischak H, Bandin F, Monsarrat B, Bascands JL, Decramer S, Schanstra JP.
Bilateral congenital abnormalities of the kidney and urinary tract (CAKUT), although are individually rare diseases, remain the main cause of chronic kidney disease in infants worldwide. Bilateral CAKUT display a wide spectrum of pre- and postnatal outcomes ranging from death in utero to normal postnatal renal function. Methods to predict these outcomes in utero are controversial and, in several cases, lead to unjustified termination of pregnancy. Using capillary electrophoresis coupled with mass spectrometry, we have analyzed the urinary proteome of fetuses with posterior urethral valves (PUV), the prototypic bilateral CAKUT, for the presence of biomarkers predicting postnatal renal function. Among more than 4000 fetal urinary peptide candidates, 26 peptides were identified that were specifically associated with PUV in 13 patients with early end-stage renal disease (ESRD) compared to 15 patients with absence of ESRD before the age of 2. A classifier based on these peptides correctly predicted postnatal renal function with 88% sensitivity and 95% specificity in an independent blinded validation cohort of 38 PUV patients, outperforming classical methods, including fetal urine biochemistry and fetal ultrasound. This study demonstrates that fetal urine is an important pool of peptides that can predict postnatal renal function and thus be used to make clinical decisions regarding pregnancy.
Leukemia. 2013 Jul 11. doi: 10.1038/leu.2013.210. [Epub ahead of print]
Proteomic peptide profiling for preemptive diagnosis of acute graft-versus-host-disease after allogeneic stem cell transplantation.
Weissinger EM, Metzger J, Dobbelstein C, Wolff D, Schleuning M, Kuzmina Z, Greinix H, Dickinson AM, Mullen W, Kreipe H, Hamwi I, Morgan M, Krons A, Tchebotarenko I, Ihlenburg-Schwarz D, Dammann E, Collin M, Ehrlich S, Diedrich H, Stadler M, Eder M, Holler E, Mischak H, Krauter J, Ganser A.
Allogeneic hematopoietic stem cell transplantation (allo-HSCT) is one curative treatment for hematologic malignancies, but is compromised by life threatening complications, such as severe acute graft-versus-host disease (aGvHD). Prediction of severe aGvHD as early as possible is crucial to allow timely initiation of treatment. Here we report on a multicentre validation of an aGvHD-specific urinary proteomic classifier (aGvHD_MS17) in 423 patients. Samples (n=1106) were collected prospectively between day +7 and day +130 and analyzed using capillary electrophoresis coupled on-line to mass spectrometry (CE-MS). Integration of aGvHD_MS17 analysis with demographic and clinical variables using a logistic regression model led to correct classification of patients developing severe aGvHD 14 days prior to any clinical signs with 82.4% sensitivity and 77.3% specificity. Multivariate regression analysis showed that aGvHD_MS17 positivity was the only strong predictor for aGvHD grade III or IV (P<0.0001). The classifier consists of 17 peptides derived from albumin, β2-microglobulin, CD99, fibronectin, and various collagen α chains, indicating inssflammation, activation of T-cells, and changes in the extracellular matrix as early signs of GvHD-induced organ damage. This study is currently the largest demonstration of accurate and investigator-independent prediction of patients at risk for severe aGvHD, thus allowing preemptive therapy based on proteomic profiling.Leukemiaaccepted article preview online, 11 July 2013; doi:10.1038/leu.2013.210.
PLoS ONE 8(6): e66682. doi:10.1371/journal.pone.0066682
Proteomics as a Quality Control Tool of Pharmaceutical Probiotic Bacterial Lysate Products
Klein G, Schanstra JP, Hoffmann J, Mischak H, Siwy J
Probiotic bacteria have a wide range of applications in veterinary and human therapeutics. Inactivated probiotics are complex samples and quality control (QC) should measure as many molecular features as possible. Capillary electrophoresis coupled to mass spectrometry (CE/MS) has been used as a multidimensional and high throughput method for the identification and validation of biomarkers of disease in complex biological samples such as biofluids. In this study we evaluate the suitability of CE/MS to measure the consistency of different lots of the probiotic formulation Pro-Symbioflor which is a bacterial lysate of heat-inactivated Escherichia coli and Enterococcus faecalis. Over 5000 peptides were detected by CE/MS in 5 different lots of the bacterial lysate and in a sample of culture medium. 71 to 75% of the total peptide content was identical in all lots. This percentage increased to 87–89% when allowing the absence of a peptide in one of the 5 samples. These results, based on over 2000 peptides, suggest high similarity of the 5 different lots. Sequence analysis identified peptides of both E. coli and E. faecalis and peptides originating from the culture medium, thus confirming the presence of the strains in the formulation. Ontology analysis suggested that the majority of the peptides identified for E. coli originated from the cell membrane or the fimbrium, while peptides identified for E. faecalis were enriched for peptides originating from the cytoplasm. The bacterial lysate peptides as a whole are recognised as highly conserved molecular patterns by the innate immune system as microbe associated molecular pattern (MAMP). Sequence analysis also identified the presence of soybean, yeast and casein protein fragments that are part of the formulation of the culture medium. In conclusion CE/MS seems an appropriate QC tool to analyze complex biological products such as inactivated probiotic formulations and allows determining the similarity between lots.
PLoS ONE 8(6): e67514. doi:10.1371/journal.pone.0067514
Seminal Plasma as a Source of Prostate Cancer Peptide Biomarker Candidates for Detection of Indolent and Advanced Disease
Neuhaus J, Schiffer E, Wilcke P, Bauer HW, Leung H, Siwy J, Ulrici W, Paasch U, Horn LC, Stolzenburg J
Extensive prostate specific antigen screening for prostate cancer generates a high number of unnecessary biopsies and over-treatment due to insufficient differentiation between indolent and aggressive tumours. We hypothesized that seminal plasma is a robust source of novel prostate cancer (PCa) biomarkers with the potential to improve primary diagnosis of and to distinguish advanced from indolent disease.
In an open-label case/control study 125 patients (70 PCa, 21 benign prostate hyperplasia, 25 chronic prostatitis, 9 healthy controls) were enrolled in 3 centres. Biomarker panels a) for PCa diagnosis (comparison of PCa patients versus benign controls) and b) for advanced disease (comparison of patients with post surgery Gleason score ,7 versus Gleason score .7) were sought. Independent cohorts were used for proteomic biomarker discovery and testing the performance of the identified biomarker profiles. Seminal plasma was profiled using capillary electrophoresis mass spectrometry. Pre-analytical stability and analytical precision of the proteome analysis were determined. Support vector machine learning was used for classification. Stepwise application of two biomarker signatures with 21 and 5 biomarkers provided 83% sensitivity and 67% specificity for PCa detection in a test set of samples. A panel of 11 biomarkers for advanced disease discriminated between patients with Gleason score 7 and organ-confined (,pT3a) or advanced ($pT3a) disease with 80% sensitivity and 82% specificity in a preliminary validation setting. Seminal profiles showed excellent preanalytical stability. Eight biomarkers were identified as fragments of N-acetyllactosaminide beta-1,3-N-acetylglucosaminyltransferase, prostatic acid phosphatase, stabilin-2, GTPase IMAP family member 6, semenogelin-1 and -2. Restricted sample size was the major limitation of the study.
Seminal plasma represents a robust source of potential peptide makers for primary PCa diagnosis. Our findings warrant further prospective validation to confirm the diagnostic potential of identified seminal biomarker candidates.
Diabetologia. 2013 Feb;56(2):259-67.
A urinary peptide biomarker set predicts worsening of albuminuria in type 2 diabetes mellitus.
Roscioni SS, de Zeeuw D, Hellemons ME, Mischak H, Zürbig P, Bakker SJ, Gansevoort RT, Reinhard H, Persson F, Lajer M, Rossing P, Heerspink HJ.
Microalbuminuria is considered the first clinical sign of kidney dysfunction and is associated with a poor renal and cardiovascular prognosis in type 2 diabetes. Detection of patients who are prone to develop micro- or macroalbuminuria may represent an effective strategy to start or optimise therapeutic intervention. Here we assessed the value of a urinary proteomic-based risk score (classifier) in predicting the development and progression of microalbuminuria.
We conducted a prospective case-control study. Cases (n=44) and controls (n=44) were selected from the PREVEND (Prevention of Renal and Vascular End-stage Disease) study and from the Steno Diabetes Center (Gentofte, Denmark). Cases were defined by transition from normo- to microalbuminuria or from micro- to macroalbuminuria over a follow-up of 3 years. Controls with no transitions in albuminuria were pair-matched for age, sex and albuminuria status. A model for the progression of albuminuria was built using a proteomic classifier based on 273 urinary peptides.
The proteomic classifier was independently associated with transition to micro- or macroalbuminuria (OR 1.35 [95% CI 1.02, 1.79], p = 0.035). The classifier predicted the development and progression of albuminuria on top of albuminuria and estimated GFR (eGFR, area under the receiver operating characteristic [ROC] curve increase of 0.03, p = 0.002; integrated discrimination index [IDI]: 0.105, p = 0.002). Fragments of collagen and α-2-HS-glycoprotein showed significantly different expression between cases and controls.
Although limited by the relatively small sample size, these results suggest that analysis of a urinary biomarker set enables early renal risk assessment in patients with diabetes. Further work is required to confirm the role of urinary proteomics in the prevention of renal failure in diabetes.
Gut. 2013 Jan;62(1):122-30.
Urine proteomic analysis differentiates cholangiocarcinoma from primary sclerosing cholangitis and other benign biliary disorders
Metzger J, Negm AA, Plentz RR, Weismüller TJ, Wedemeyer J, Karlsen TH, Dakna M, Mullen W, Mischak H, Manns MP, Lankisch TO
Diagnosis and curative treatment of cholangiocarcinoma (CC) often comes too late due to the lack of reliable tumour markers especially in patients with primary sclerosing cholangitis (PSC). The authors recently introduced bile proteomic analysis for CC diagnosis. Nevertheless, bile collection depends on invasive endoscopic retrograde cholangiography. The authors therefore evaluated urine proteomic analysis for non-invasive CC diagnosis.
Using capillary electrophoresis mass spectrometry the authors established a CC-specific peptide marker model based on the distribution of 42 peptides in 14 CC, 13 PSC and 14 benign biliary disorder (BBD) patients. Results In cross-sectional validation of 123 patients, the urine peptide marker model correctly classified 35 of 42 CC patients and 64 of 81 PSC and BBD patients with an area under the curve value of 0.87 (95% CI 0.80 to 0.92, p¼0.0001, 83% sensitivity, 79% specificity). Evaluation of 101 normal controls resulted in 86% specificity. All 10 patients with CC on top of PSC were correctly classified. The majority of sequence-identified peptides are fragments of interstitial collagens with some of them also detected in blood indicating their extra-renal origin. Immunostaining of liver sections for matrix metallopeptidase 1 indicated increased activity of the interstitial collagenase in liver epithelial cells of CC patients.
The urine test differentiates CC from PSC and other BBD and may provide a new diagnostic noninvasive tool for PSC surveillance and CC detection.