Re‐analysis of “Peptidomic analysis of cartilage and subchondral bone in OA patients”

In the May 2019 issue of European Journal of Clinical Investigation, Gatenholm et al. reported on "a method for directly analyzing osteochondral samples straight out of the operating room without cell culturing, thereby enabling identification of potential peptide biomarkers to better understand the mechanisms involved in the development of osteoarthritis (OA) and pain"1. Six Samples from patients were investigated, 3 from wounded (WO) and 3 from macroscopically unwounded zones (UOA) of the femur condyle, manifesting OA based on total knee arthroplasty (TKA). Using peptidomics and Tandem Mass Tag (TMT) labeling, the authors in their study reported the identification of 6296 endogenous peptides derived from 915 proteins (889 protein groups) across samples

Dual mTOR/PI3K inhibition limits PI3K-dependent pathways activated upon mTOR inhibition in autosomal dominant polycystic kidney disease

Autosomal dominant polycystic kidney disease (ADPKD) is characterized by the development of kidney cysts leading to kidney failure in adulthood. Inhibition of mammalian target of rapamycin (mTOR) slows polycystic kidney disease (PKD) progression in animal models, but randomized controlled trials failed to prove efficacy of mTOR inhibitor treatment. Here, we demonstrate that treatment with mTOR inhibitors result in the removal of negative feedback loops and up-regulates pro-proliferative phosphatidylinositol 3-kinase (PI3K)-Akt and PI3K-extracellular signal-regulated kinase (ERK) signaling in rat and mouse PKD models. Dual mTOR/PI3K inhibition with NVP-BEZ235 abrogated these pro-proliferative signals and normalized kidney morphology and function by blocking proliferation and fibrosis. Our findings suggest that multi-target PI3K/mTOR inhibition may represent a potential treatment for ADPKD

The use of urinary proteomics in the assessment of suitability of mouse models for ageing

Ageing is a complex process characterised by a systemic and progressive deterioration of biological functions. As ageing is associated with an increased prevalence of age-related chronic disorders, understanding its underlying molecular mechanisms can pave the way for therapeutic interventions and managing complications. Animal models such as mice are commonly used in ageing research as they have a shorter lifespan in comparison to humans and are also genetically close to humans. To assess the translatability of mouse ageing to human ageing, the urinary proteome in 89 wild-type (C57BL/6) mice aged between 8–96 weeks was investigated using capillary electrophoresis coupled to mass spectrometry (CE-MS). Using age as a continuous variable, 295 peptides significantly correlated with age in mice were identified. To investigate the relevance of using mouse models in human ageing studies, a comparison was performed with a previous correlation analysis using 1227 healthy subjects. In mice and humans, a decrease in urinary excretion of fibrillar collagens and an increase of uromodulin fragments was observed with advanced age. Of the 295 peptides correlating with age, 49 had a strong homology to the respective human age-related peptides. These ortholog peptides including several collagen (N = 44) and uromodulin (N = 5) fragments were used to generate an ageing classifier that was able to discriminate the age among both wild-type mice and healthy subjects. Additionally, the ageing classifier depicted that telomerase knock-out mice were older than their chronological age. Hence, with a focus on ortholog urinary peptides mouse ageing can be translated to human ageing

Pathophysiological implications of urinary peptides in hepatocellular carcinoma

SIMPLE SUMMARY: In this study, the application of capillary electrophoresis mass spectrometry enabled identification of 31 urinary peptides significantly associated with hepatocellular carcinoma diagnosis and prognosis. Further assessment of these peptides lead to prediction of cellular proteases involved in their development namely Meprin A subunit α and Kallikrein-6. Subsequent identification of the proteases was verified by immunohistochemistry in normal liver, cirrhosis and hepatocellular carcinoma. Histopathological assessment of the proteases revealed numerical gradient staining signifying their involvement in liver fibrosis and hepatocellular carcinoma formation. The discovered urinary peptides offered a potential noninvasive tool for diagnosis and prognosis of hepatocellular carcinoma. ABSTRACT: 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

Comparison of urine and plasma peptidome indicates selectivity in renal peptide handling

Purpose: Urine is considered to be produced predominantly as a result of plasma filtration in the kidney. However, the origin of the native peptides present in urine has never been investigated in detail. Therefore, we aimed to obtain a first insight into the origin of urinary peptides based on a side‐by‐side comprehensive analysis of the plasma and urine peptidome. Methods: Twenty‐two matched urine and plasma samples were analyzed for their peptidome using capillary electrophoresis coupled to mass spectrometry (CE‐MS; for relative quantification) and CE‐ or LC coupled to tandem mass spectrometry (CE‐ or LC‐ MS/MS; for peptide identification). The overlap and association of abundance of the different peptides present in these two body fluids were evaluated. Results: We were able to identify 561 plasma and 1461 urinary endogenous peptides. Only 90 peptides were detectable in both urine and plasma. No significant correlation was found when comparing the abundance of these common peptides, with the exception of collagen fragments. This observation was also supported when comparing published peptidome data from both plasma and urine. Conclusions and clinical relevance: Most of the plasma peptides are not detectable in urine, possibly due to tubular reabsorption. The majority of urinary peptides may in fact originate in the kidney. The notable exception is collagen fragments, which indicates potential selective exclusion of these peptides from tubular reabsorption. Experimental verification of this hypothesis is warranted

A urinary fragment of mucin-1 subunit α is a novel biomarker associated with renal dysfunction in the general population

Introduction: Sequencing peptides included in the urinary proteome identifies the parent proteins and may reveal mechanisms underlying the pathophysiology of chronic kidney disease. Methods: In 805 randomly recruited Flemish individuals (50.8% women; mean age, 51.1 years), we determined the estimated glomerular filtration rate (eGFR) from serum creatinine using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation. We categorized eGFR according to the National Kidney Foundation Kidney Disease Outcomes Quality Initiative guideline. We analyzed 74 sequenced urinary peptides with a detectable signal in more than 95% of participants. Follow-up measurements of eGFR were available in 597 participants. Results: In multivariable analyses, baseline eGFR decreased (P ≤ 0.022) with urinary fragments of mucin-1 (standardized association size expressed in ml/min/1.73 m2, −4.48), collagen III (−2.84), and fibrinogen (−1.70) and was bi-directionally associated (P ≤ 0.0006) with 2 urinary collagen I fragments (+2.28 and −3.20). The eGFR changes over 5 years (follow-up minus baseline) resulted in consistent estimates (P ≤ 0.025) for mucin-1 (−1.85), collagen (−1.37 to 1.43) and fibrinogen (−1.45) fragments. Relative risk of having or progressing to eGFR &lt;60 ml/min/1.73 m2 was associated with mucin-1. Partial least-squares analysis confirmed mucin-1 as the strongest urinary marker associated with decreased eGFR, with a score of 2.47 compared with 1.80 for a collagen I fragment as the next contender. Mucin-1 predicted eGFR decline to &lt;60 ml/min/1.73 m2 over and above microalbuminuria (P = 0.011) and retained borderline significance (P = 0.05) when baseline eGFR was accounted for. Discussion: In the general population, mucin-1 subunit α, an extracellular protein that is shed from renal tubular epithelium, is a novel biomarker associated with renal dysfunction

Association of kidney fibrosis with urinary peptides: a path towards non-invasive liquid biopsies?

Chronic kidney disease (CKD) is a prevalent cause of morbidity and mortality worldwide. A hallmark of CKD progression is renal fibrosis characterized by excessive accumulation of extracellular matrix (ECM) proteins. In this study, we aimed to investigate the correlation of the urinary proteome classifier CKD273 and individual urinary peptides with the degree of fibrosis. In total, 42 kidney biopsies and urine samples were examined. The percentage of fibrosis per total tissue area was assessed in Masson trichrome stained kidney tissues. The urinary proteome was analysed by capillary electrophoresis coupled to mass spectrometry. CKD273 displayed a significant and positive correlation with the degree of fibrosis (Rho = 0.430, P = 0.0044), while the routinely used parameters (glomerular filtration rate, urine albumin-to-creatinine ratio and urine protein-to-creatinine ratio) did not (Rho = -0.222; -0.137; -0.070 and P = 0.16; 0.39; 0.66, respectively). We identified seven fibrosis-associated peptides displaying a significant and negative correlation with the degree of fibrosis. All peptides were collagen fragments, suggesting that these may be causally related to the observed accumulation of ECM in the kidneys. CKD273 and specific peptides are significantly associated with kidney fibrosis; such an association could not be detected by other biomarkers for CKD. These non-invasive fibrosis-related biomarkers can potentially be implemented in future trials

A model to detect significant prostate cancer integrating urinary peptide and extracellular vesicle RNA data

There is a clinical need to improve assessment of biopsy-naïve patients for the presence of clinically significant prostate cancer (PCa). In this study, we investigated whether the robust integration of expression data from urinary extracellular vesicle RNA (EV-RNA) with urine proteomic metabolites can accurately predict PCa biopsy outcome. Urine samples collected within the Movember GAP1 Urine Biomarker study (n = 192) were analysed by both mass spectrometry-based urine-proteomics and NanoString gene-expression analysis (167 gene-probes). Cross-validated LASSO penalised regression and Random Forests identified a combination of clinical and urinary biomarkers for predictive modelling of significant disease (Gleason Score (Gs) ≥ 3 + 4). Four predictive models were developed: ‘MassSpec’ (CE-MS proteomics), ‘EV-RNA’, and ‘SoC’ (standard of care) clinical data models, alongside a fully integrated omics-model, deemed ‘ExoSpec’. ExoSpec (incorporating four gene transcripts, six peptides, and two clinical variables) is the best model for predicting Gs ≥ 3 + 4 at initial biopsy (AUC = 0.83, 95% CI: 0.77–0.88) and is superior to a standard of care (SoC) model utilising clinical data alone (AUC = 0.71, p < 0.001, 1000 resamples). As the ExoSpec Risk Score increases, the likelihood of higher-grade PCa on biopsy is significantly greater (OR = 2.8, 95% CI: 2.1–3.7). The decision curve analyses reveals that ExoSpec provides a net benefit over SoC and could reduce unnecessary biopsies by 30%

Recent Advances of Proteomics in Management of Acute Kidney Injury

Acute Kidney Injury (AKI) is currently recognized as a life-threatening disease, leading to an exponential increase in morbidity and mortality worldwide. At present, AKI is characterized by a significant increase in serum creatinine (SCr) levels, typically followed by a sudden drop in glomerulus filtration rate (GFR). Changes in urine output are usually associated with the renal inability to excrete urea and other nitrogenous waste products, causing extracellular volume and electrolyte imbalances. Several molecular mechanisms were proposed to be affiliated with AKI development and progression, ultimately involving renal epithelium tubular cell-cycle arrest, inflammation, mitochondrial dysfunction, the inability to recover and regenerate proximal tubules, and impaired endothelial function. Diagnosis and prognosis using state-of-the-art clinical markers are often late and provide poor outcomes at disease onset. Inappropriate clinical assessment is a strong disease contributor, actively driving progression towards end stage renal disease (ESRD). Proteins, as the main functional and structural unit of the cell, provide the opportunity to monitor the disease on a molecular level. Changes in the proteomic profiles are pivotal for the expression of molecular pathways and disease pathogenesis. Introduction of highly-sensitive and innovative technology enabled the discovery of novel biomarkers for improved risk stratification, better and more cost-effective medical care for the ill patients and advanced personalized medicine. In line with those strategies, this review provides and discusses the latest findings of proteomic-based biomarkers and their prospective clinical application for AKI management