Urinary collagen peptides: Source of markers for bone metabolic processes in kidney transplant recipients.

INTRODUCTION: Kidney transplant recipients (KTRs) are at an increased risk of fractures. Total urinary hydroxyproline excretion served as marker for bone resorption (BR) but was replaced by ß-CrossLaps (CTX), a C-terminal collagen α-1(I) chain (COL1A1) telopeptide. We investigated the low-molecular-weight urinary proteome for peptides associated with changes in bone metabolism after kidney transplantation. METHODS: Clinical and laboratory data including serum levels of CTX in 96 KTR from two nephrology centers were correlated with signal intensities of urinary peptides identified by capillary electrophoresis mass spectrometry. RESULTS: Eighty-two urinary peptides were significantly correlated with serum CTX levels. COL1A1 was the predominant peptide source. Oral bisphosphonates were administered for decreased bone density in an independent group of 11 KTR and their effect was evaluated on the aforementioned peptides. Study of the peptides cleavage sites revealed a signature of Cathepsin K and MMP9. Seventeen of these peptides were significantly associated with bisphosphonate treatment, all showing a marked reduction in their excretion levels compared to baseline. DISCUSSION: This study provides strong evidence for the presence of collagen peptides in the urine of KTR that are associated with BR and that are sensitive to bisphosphonate treatment. Their assessment might become a valuable tool to monitor bone status in KTR.

A universal predictive and mechanistic urinary peptide signature in acute kidney injury.

BACKGROUND: The delayed diagnosis of acute kidney injury (AKI) episodes and the lack of specificity of current single AKI biomarkers hamper its management. Urinary peptidome analysis may help to identify early molecular changes in AKI and grasp its complexity to identify potential targetable molecular pathways. METHODS: In derivation and validation cohorts totalizing 1170 major cardiac bypass surgery patients and in an external cohort of 1569 intensive care unit (ICU) patients, a peptide-based score predictive of AKI (7-day KDIGO classification) was developed, validated, and compared to the reference biomarker urinary NGAL and NephroCheck and clinical scores. RESULTS: A set of 204 urinary peptides derived from 48 proteins related to hemolysis, inflammation, immune cells trafficking, innate immunity, and cell growth and survival was identified and validated for the early discrimination (< 4 h) of patients according to their risk to develop AKI (OR 6.13 [3.96-9.59], p < 0.001) outperforming reference biomarkers (urinary NGAL and [IGFBP7].[TIMP2] product) and clinical scores. In an external cohort of 1569 ICU patients, performances of the signature were similar (OR 5.92 [4.73-7.45], p < 0.001), and it was also associated with the in-hospital mortality (OR 2.62 [2.05-3.38], p < 0.001). CONCLUSIONS: An overarching AKI physiopathology-driven urinary peptide signature shows significant promise for identifying, at an early stage, patients who will progress to AKI and thus to develop tailored treatments for this frequent and life-threatening condition. Performance of the urine peptide signature is as high as or higher than that of single biomarkers but adds mechanistic information that may help to discriminate sub-phenotypes of AKI offering new therapeutic avenues.

Predictive performance and clinical application of COV50, a urinary proteomic biomarker in early COVID-19 infection: a prospective multicentre cohort study.

BACKGROUND: The SARS-CoV-2 pandemic is a worldwide challenge. The CRIT-CoV-U pilot study generated a urinary proteomic biomarker consisting of 50 peptides (COV50), which predicted death and disease progression from SARS-CoV-2. After the interim analysis presented for the German Government, here, we aimed to analyse the full dataset to consolidate the findings and propose potential clinical applications of this biomarker. METHODS: CRIT-CoV-U was a prospective multicentre cohort study. In eight European countries (Austria, France, Germany, Greece, North Macedonia, Poland, Spain, and Sweden), 1012 adults with PCR-confirmed COVID-19 were followed up for death and progression along the 8-point WHO scale. Capillary electrophoresis coupled with mass spectrometry was used for urinary proteomic profiling. Statistical methods included logistic regression and receiver operating characteristic curve analysis with a comparison of the area under curve (AUC) between nested models. Hospitalisation costs were derived from the care facility corresponding with the Markov chain probability of reaching WHO scores ranging from 3 to 8 and flat-rate hospitalisation costs adjusted for the gross per capita domestic product of each country. FINDINGS: From June 30 to Nov 19, 2020, 228 participants were recruited, and from April 30, 2020, to April 14, 2021, 784 participants were recruited, resulting in a total of 1012 participants. The entry WHO scores were 1-3 in 445 (44%) participants, 4-5 in 529 (52%) participants, and 6 in 38 (4%) participants; and of all participants, 119 died and 271 had disease progression. The odds ratio (OR) associated with COV50 in all 1012 participants for death was 2·44 (95% CI 2·05-2·92) unadjusted and 1·67 (1·34-2·07) when adjusted for sex, age, BMI, comorbidities, and baseline WHO score; and for disease progression, the OR was 1·79 (1·60-2·01) when unadjusted and 1·63 (1·41-1·91) when adjusted (p<0·0001 for all). The predictive accuracy of the optimised COV50 thresholds was 74·4% (71·6-77·1%) for mortality (threshold 0·47) and 67·4% (64·4-70·3%) for disease progression (threshold 0·04). When adjusted for covariables and the baseline WHO score, these thresholds improved AUCs from 0·835 to 0·853 (p=0·033) for death and from 0·697 to 0·730 (p=0·0008) for progression. Of 196 participants who received ambulatory care, 194 (99%) did not reach the 0·04 threshold. The cost reductions associated with 1 day less hospitalisation per 1000 participants were million Euro (M€) 0·887 (5-95% percentile interval 0·730-1·039) in participants at a low risk (COV50 <0·04) and M€2·098 (1·839-2·365) in participants at a high risk (COV50 ≥0·04). INTERPRETATION: The urinary proteomic COV50 marker might be predictive of adverse COVID-19 outcomes. Even in people with mild-to-moderate PCR-confirmed infections (WHO scores 1-4), the 0·04 COV50 threshold justifies earlier drug treatment, thereby potentially reducing the number of days in hospital and associated costs. FUNDING: German Federal Ministry of Health.

Noninvasive Diagnosis of Acute Rejection in Renal Transplant Patients Using Mass Spectrometric Analysis of Urine Samples: A Multicenter Diagnostic Phase III Trial.

Timely recognition and treatment of acute kidney graft rejection is important to prevent premature graft failure. A predefined urinary marker set for acute T cell-mediated rejection (TCMR) containing 14 peptides was tested for this purpose in a multicenter in-place validation study. Methods: Three hundred twenty-nine prospectively collected and 306 archived urine samples from 11 transplant centers in Germany, France, and Belgium were examined. Samples were taken immediately before a biopsy, performed for graft dysfunction within the first transplant year. Primary outcomes were sensitivity and specificity of the marker set for the diagnosis of biopsy-proven acute TCMR, with prespecified thresholds of 83% for sensitivity and 70% for specificity. Results: Eighty-two patients (13%) had acute TCMR grade I-III. In relation to the biopsy diagnosis of TCMR, the sensitivity of the urine test was 0.66 (95% confidence interval, 0.56-0.76) and the specificity 0.47 (95% confidence interval, 0.43-0.51), with an area under the curve (AUC) of 0.60. The different TCMR grades I-III were not reflected by the marker set, and borderline TCMR was not specifically detected. Secondary independent masked assessment of biopsies consented by 2 pathologists revealed an interobserver kappa value of 0.49 for diagnosing TCMR, compared with the local center's diagnosis. Using this consensus diagnosis, the AUC of the urine test was 0.63 (sensitivity 0.73, specificity 0.45). Post hoc optimization of the marker set improved the diagnostic performance in the study cohort (AUC 0.67) and in an independent patient cohort (AUC 0.69). Conclusions: This study illustrates the difficulty of proteomics-based diagnosis of TCMR and highlights the need for rigorous independent in-place validation and optimization of diagnostic biomarkers.

Association of the chronic kidney disease urinary proteomic predictor CKD273 with clinical risk factors of graft failure in kidney allograft recipients.

BACKGROUND: Kidney transplantation is the best treatment option for end-stage kidney disease but is still associated with long-term graft failure. In this study, we evaluated the application of urinary proteomics to identify grafts with high failure risk before initial decline of estimated glomerular filtration rate (eGFR) with irreversible graft changes. METHODS: Fifty-two living donor kidney transplant recipients (KTR) with 8-year follow-up were enrolled. All patients underwent clinical examination and had a routine laboratory screening at 3, 6, 12, 24, 36, 48 and 96 months post-transplantation, including creatinine, urea, albumin and 24-h proteinuria. Graft function was estimated according to Nankivell. Urine samples at Month 24 were analysed by capillary electrophoresis coupled mass spectrometry followed by classification with the chronic kidney disease classifier CKD273. RESULTS: CKD273 showed significant correlation with serum creatinine at every time point and moderate inverse correlation for the slope in glomerular filtration rates by Nankivell (r = -0.29, P = 0.05). Receiver operating characteristics analysis for graft loss and death within the next 6 years after proteomic analysis resulted in an area under curve value of 0.89 for CKD273 being superior to 0.67 for Nankivell eGFR. Stratification into CKD273-positive and -negative patient groups revealed a hazard ratio of 16.5 for prevalence of graft loss in case of CKD273 positivity. CONCLUSIONS: Using a representative KTR cohort with 8-year follow-up, we could demonstrate significant value of CKD273 for risk stratification of graft loss. This study provides the conceptual basis for further evaluation of CKD273 as a prognostic tool for long-term graft function risk stratification by large prospective clinical trials.

Pathophysiological Implications of Urinary Peptides in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is known to be associated with protein alterations and extracellular fibrous deposition. We investigated the urinary proteomic profiles of HCC patients in this prospective cross sectional multicentre study. 195 patients were recruited from the UK (Coventry) and Germany (Hannover) between 1 January 2013 and 30 June 2019. Out of these, 57 were HCC patients with a background of liver cirrhosis (LC) and 138 were non-HCC controls; 72 patients with LC, 57 with non-cirrhotic liver disease and 9 with normal liver function. Analysis of the urine samples was performed by capillary electrophoresis (CE) coupled to mass spectrometry (MS). Peptide sequences were obtained and 31 specific peptide markers for HCC were identified and further integrated into a multivariate classification model. The peptide model demonstrated 79.5% sensitivity and 85.1% specificity (95% CI: 0.81-0.93, p < 0.0001) for HCC and 4.1-fold increased risk of death (95% CI: 1.7-9.8, p = 0.0005). Proteases potentially involved in HCC progression were mapped to the N- and C-terminal sequence motifs of the CE-MS peptide markers. In silico protease prediction revealed that kallikrein-6 (KLK6) elicits increased activity, whilst Meprin A subunit α (MEP1A) has reduced activity in HCC compared to the controls. Tissue expression of KLK6 and MEP1A was subsequently verified by immunohistochemistry.

A urinary peptidomic profile predicts outcome in SARS-CoV-2-infected patients.

BACKGROUND: COVID-19 prediction models based on clinical characteristics, routine biochemistry and imaging, have been developed, but little is known on proteomic markers reflecting the molecular pathophysiology of disease progression. METHODS: The multicentre (six European study sites) Prospective Validation of a Proteomic Urine Test for Early and Accurate Prognosis of Critical Course Complications in Patients with SARS-CoV-2 Infection Study (Crit-COV-U) is recruiting consecutive patients (≥ 18 years) with PCR-confirmed SARS-CoV-2 infection. A urinary proteomic biomarker (COV50) developed by capillary-electrophoresis-mass spectrometry (CE-MS) technology, comprising 50 sequenced peptides and identifying the parental proteins, was evaluated in 228 patients (derivation cohort) with replication in 99 patients (validation cohort). Death and progression along the World Health Organization (WHO) Clinical Progression Scale were assessed up to 21 days after the initial PCR test. Statistical methods included logistic regression, receiver operating curve (ROC) analysis and comparison of the area under the curve (AUC). FINDINGS: In the derivation cohort, 23 patients died, and 48 developed worse WHO scores. The odds ratios (OR) for death per 1 standard deviation (SD) increment in COV50 were 3·52 (95% CI, 2·02-6·13, p <0·0001) unadjusted and 2·73 (1·25-5·95, p = 0·012) adjusted for sex, age, baseline WHO score, body mass index (BMI) and comorbidities. For WHO scale progression, the corresponding OR were 2·63 (1·80-3·85, p<0·0001) and 3·38 (1·85-6·17, p<0·0001), respectively. The area under the curve (AUC) for COV50 as a continuously distributed variable was 0·80 (0·72-0·88) for mortality and 0·74 (0·66-0·81) for worsening WHO score. The optimised COV50 thresholds for mortality and worsening WHO score were 0·47 and 0·04 with sensitivity/specificity of 87·0 (74·6%) and 77·1 (63·9%), respectively. On top of covariates, COV50 improved the AUC, albeit borderline for death, from 0·78 to 0·82 (p = 0·11) and 0·84 (p = 0·052) for mortality and from 0·68 to 0·78 (p = 0·0097) and 0·75 (p = 0·021) for worsening WHO score. The validation cohort findings were confirmatory. INTERPRETATION: This first CRIT-COV-U report proves the concept that urinary proteomic profiling generates biomarkers indicating adverse COVID-19 outcomes, even at an early disease stage, including WHO stages 1-3. These findings need to be consolidated in an upcoming final dataset. FUNDING: The German Federal Ministry of Health funded the study.

A multicenter prospective, randomized, placebo-controlled phase II/III trial for preemptive acute graft-versus-host disease therapy.

Acute graft-versus-host disease (aGvHD) contributes to about 50% of transplant-related mortality (non-relapse mortality) after allogeneic hematopoietic stem cell transplantation (HSCT). Here the predictive value of a urinary proteomic profile (aGvHD_MS17) was tested together with preemptive prednisolone therapy. Two-hundred and fifty-nine of 267 patients were eligible for analysis. Ninety-two patients were randomized upon aGvHD_MS17 classification factor above 0.1 to receive either prednisolone (2-2.5 mg/kg, N = 44) or placebo (N = 47; N = 1 randomization failure) for 5 days followed by tapering. The remaining 167 patients formed the observation group. The primary endpoint of the randomized trial was incidence of aGvHD grade II between randomization and day +100 post HSCT. Analysis of the short-term preemptive prednisolone therapy in the randomized patients showed no significant difference in incidence or severity of acute GvHD (HR: 1.69, 95% CI: 0.66-4.32, P = 0.27). Prednisolone as preemptive treatment did not lead to an increase in relapse (20.2% in the placebo and 14.0% in the prednisolone group (P = 0.46)). The frequency of adverse events was slightly higher in the placebo group (64.4% versus 50%, respectively). Taken together, the results of the Pre-GvHD trial demonstrated the feasibility and safety of preemptive prednisolone treatment in the randomized patients.

Discovery, validation and sequencing of urinary peptides for diagnosis of liver fibrosis-A multicentre study.

BACKGROUND: Liver fibrosis is a consequence of chronic inflammation and is associated with protein changes within the hepatocytes structure. In this study, we aimed to investigate if this is reflected by the urinary proteome and can be explored to diagnose liver fibrosis in patients with chronic liver disease. METHODS: In a multicentre combined cross-sectional and prospective diagnostic test validation study, 129 patients with varying degrees of liver fibrosis and 223 controls without liver fibrosis were recruited. Additionally, 41 patients with no liver, but kidney fibrosis were included to evaluate interference with expressions of kidney fibrosis. Urinary low molecular weight proteome was analysed by capillary electrophoresis coupled to mass spectrometry (CE-MS) and a support vector machine marker model was established by integration of peptide markers for liver fibrosis. FINDINGS: CE-MS enabled identification of 50 urinary peptides associated with liver fibrosis. When combined into a classifier, LivFib-50, it separated patients with liver fibrosis (N = 31) from non-liver disease controls (N = 123) in cross-sectional diagnostic phase II evaluation with an area under the curve (AUC) of 0.94 (95% confidence intervals (CI): 0.89-0.97, p<0.0001). When adjusted for age, LivFib-50 demonstrated an AUC of 0.94 (95% CI: 0.89-0.97, p<0.0001) in chronic liver disease patients with (N = 19) or without (N = 17) liver fibrosis progression. In this prospective diagnostic phase III validation set, age-adjusted LivFib-50 showed 84.2% sensitivity (95% CI: 60.4-96.6) and 82.4% specificity (95% CI: 56.6-96.2) for detection of liver fibrosis. The sequence-identified peptides are mainly fragments of collagen chains, uromodulin and Na/K-transporting ATPase subunit γ. We also identified ten putative proteolytic cleavage sites, eight were specific for matrix metallopeptidases and two for cathepsins. INTERPRETATION: In liver fibrosis, urinary peptides profiling offers potential diagnostic markers and leads to discovery of proteolytic sites that could be targets for developing anti-fibrotic therapy.

Urinary Proteomics Associates with COVID-19 Severity: Pilot Proof-of-Principle Data and Design of a Multicentric Diagnostic Study.

SARS-CoV-2 infection results in a mild-to-moderate disease course in most patients, allowing outpatient self-care and quarantine. However, in approx. 10% of cases a two- or three-phasic critical disease course with starting from day 7 to 10 is observed. To facilitate and plan outpatient care, biomarkers prognosing such worsening at an early stage appear of outmost importance. In this accelerated article, we report on the identification of urinary peptides significantly associated with SARS-CoV-2 infection, and the development of a multi-marker urinary peptide based test, COVID20, that may enable prognosis of critical and fatal outcomes in COVID-19 patients. COVID20 is composed of 20 endogenous peptides mainly derived from various collagen chains that enable differentiating moderate or severe disease from critical state or death with 83% sensitivity at 100% specificity. Based on the performance in this pilot study, testing in a prospective study on 1000 patients has been initiated. This article is protected by copyright. All rights reserved.

Associations of urinary polymeric immunoglobulin receptor peptides in the context of cardio-renal syndrome.

The polymeric immunoglobulin receptor (pIgR) transports immunoglobulins from the basolateral to the apical surface of epithelial cells. PIgR was recently shown to be associated with kidney dysfunction. The immune defense is initiated at the apical surface of epithelial cells where the N-terminal domain of pIgR, termed secretory component (SC), is proteolytically cleaved and released either unbound (free SC) or bound to immunoglobulins. The aim of our study was to evaluate the association of pIgR peptides with the cardio-renal syndrome in a large cohort and to obtain information on how the SC is released. We investigated urinary peptides of 2964 individuals available in the Human Urine Proteome Database generated using capillary electrophoresis coupled to mass spectrometry. The mean amplitude of 23 different pIgR peptides correlated negatively with the estimated glomerular filtration rate (eGFR, rho = -0.309, p < 0.0001). Furthermore, pIgR peptides were significantly increased in cardiovascular disease (coronary artery disease and heart failure) after adjustment for eGFR. We further predicted potential proteases involved in urinary peptide generation using the Proteasix algorithm. Peptide cleavage site analysis suggested that several, and not one, proteases are involved in the generation of the SC. In this large cohort, we could demonstrate that pIgR is associated with the cardio-renal syndrome and provided a more detailed insight on how pIgR can be potentially cleaved to release the SC.

Proteomics for hematopoietic stem cell transplantation.

Introduction: After the genomic era, the analysis of the proteome has gained increasing importance. Peptides and/or proteins present in tissue or body fluids can depict health and are prone to change during disease, not only in configuration but also in abundance. Early on, high throughput proteome analysis was implemented in the diagnostic of therapy-linked or induced complications arising after allogeneic hematopoietic stem cell transplantation (HSCT). Several proteomic approaches are currently used in the prediction or diagnosis of acute and/or chronic graft-versus-host disease (GvHD).Areas covered: This review will report on two high throughput proteomics technologies used in the clinical setting to date, namely enzyme-linked-immunosorbent assays (ELISA) for key proteins involved in the pathogenesis of acute GvHD and on capillary electrophoresis coupled on-line to mass spectrometry (CE-MS). Here, we summarize the current data and discuss the strength as well as the limitations of each method and compare the usefulness and practicability in the post-HSCT setting for prediction and diagnosis of acute GvHD.Expert commentary: Both technologies are applied in the clinic and have been tested on several hundred patients after HSCT. The data from both technologies may complement each other in diagnosis of GvHD.

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.

Author Correction: Urinary CE-MS peptide marker pattern for detection of solid tumors.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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.

Proteomics biomarkers for solid tumors: Current status and future prospects.

Cancer is a heterogeneous multifactorial disease, which continues to be one of the main causes of death worldwide. Despite the extensive efforts for establishing accurate diagnostic assays and efficient therapeutic schemes, disease prevalence is on the rise, in part, however, also due to improved early detection. For years, studies were focused on genomics and transcriptomics, aiming at the discovery of new tests with diagnostic or prognostic potential. However, cancer phenotypic characteristics seem most likely to be a direct reflection of changes in protein metabolism and function, which are also the targets of most drugs. Investigations at the protein level are therefore advantageous particularly in the case of in-depth characterization of tumor progression and invasiveness. Innovative high-throughput proteomic technologies are available to accurately evaluate cancer formation and progression and to investigate the functional role of key proteins in cancer. Employing these new highly sensitive proteomic technologies, cancer biomarkers may be detectable that contribute to diagnosis and guide curative treatment when still possible. In this review, the recent advances in proteomic biomarker research in cancer are outlined, with special emphasis placed on the identification of diagnostic and prognostic biomarkers for solid tumors. In view of the increasing number of screening programs and clinical trials investigating new treatment options, we discuss the molecular connections of the biomarkers as well as their potential as clinically useful tools for diagnosis, risk stratification and therapy monitoring of solid tumors.

Urinary proteomics to diagnose chronic active antibody-mediated rejection in pediatric kidney transplantation - a pilot study.

Chronic antibody-mediated rejection (cABMR) is the main cause of long-term renal graft loss. Late-stage diagnosis is made by detecting donor-specific antibodies (DSA) in blood combined with typical histomorphological lesions in renal allografts. There is a need for noninvasive biomarkers for cABMR that might permit screening and earlier diagnosis. In a case control study of 24 pediatric renal transplant recipients, urine samples were analyzed using capillary electrophoresis and mass spectrometry. Patients were matched with 36 pediatric renal transplant patients without cABMR. Statistical analysis used the nonparametric Wilcoxon test to identify 79 significant biomarkers, which were combined to a support vector machine-based classifier. After validation in an independent test cohort of eight pediatric patients with and 12 without cABMR, the area under the receiver operating characteristic (ROC) curve (AUC) for detection of cABMR was 0.92 (95% CI 0.71-0.99) with a sensitivity of 100% (95% CI 63-100%) and a specificity of 75% (95% CI 43-95%). Combining this classifier with the urinary proteomic marker CKD273 improved the detection of patients with cABMR with misclassification in only 2/20 of the patients. These data indicate that a biomarker pattern derived from urinary proteomics allows the detection of cABMR in pediatric renal transplant recipients with high sensitivity and moderate specificity.

Clinical Proteomics for Post-Hematopoeitic Stem Cell Transplantation Outcomes.

Allogeneic hematopoietic stem cell transplantation (HSCT) is the most effective form of tumor immunotherapy available to date. However, while HSCT can induce beneficial graft-versus-leukemia (GVL) effect, the adverse effect of graft-versus-host disease (GVHD), which is closely linked to GVL, is the major source of morbidity and mortality following HSCT. Until recently, available diagnostic and staging tools frequently fail to identify those at higher risk of disease progression or death. Furthermore, there are shortcomings in the prediction of the need for therapeutic interventions or the response rates to different forms of therapy. The past decade has been characterized by an explosive evolution of proteomics technologies, largely due to important advances in high-throughput MS instruments and bioinformatics. Building on these opportunities, blood biomarkers have been identified and validated both as promising diagnostic tools, prognostic tools that risk-stratify patients before future occurrence of GVHD and as predictive tools for responsiveness to GVHD therapy and non-relapse mortality. These biomarkers might facilitate timely and selective therapeutic intervention. This review summarizes current information on clinical proteomics for GVHD as well as other complications following HSCT. Finally, it proposes future directions for the translation of clinical proteomics to discovery of new potential therapeutic targets to the development of drugs.

Urinary CE-MS peptide marker pattern for detection of solid tumors.

Urinary profiling datasets, previously acquired by capillary electrophoresis coupled to mass-spectrometry were investigated to identify a general urinary marker pattern for detection of solid tumors by targeting common systemic events associated with tumor-related inflammation. A total of 2,055 urinary profiles were analyzed, derived from a) a cancer group of patients (n = 969) with bladder, prostate, and pancreatic cancers, renal cell carcinoma, and cholangiocarcinoma and b) a control group of patients with benign diseases (n = 556), inflammatory diseases (n = 199) and healthy individuals (n = 331). Statistical analysis was conducted in a discovery set of 676 cancer cases and 744 controls. 193 peptides differing at statistically significant levels between cases and controls were selected and combined to a multi-dimensional marker pattern using support vector machine algorithms. Independent validation in a set of 635 patients (293 cancer cases and 342 controls) showed an AUC of 0.82. Inclusion of age as independent variable, significantly increased the AUC value to 0.85. Among the identified peptides were mucins, fibrinogen and collagen fragments. Further studies are planned to assess the pattern value to monitor patients for tumor recurrence. In this proof-of-concept study, a general tumor marker pattern was developed to detect cancer based on shared biomarkers, likely indicative of cancer-related features.