Dual-potential electrochemiluminescence of single luminophore for detection of biomarker based on black phosphorus quantum dots as co-reactant.

Simultaneous cathodic and anodic electrochemiluminescence (ECL) emissions of needle-like nanostructures of Ru(bpy)32+ (RuNDs) as the only luminophore are reported based on different co-reactants. Cathodic ECL was attained from RuNDs/K2S2O8 system, while anodic ECL was achieved from RuNDs/black phosphorus quantum dots (BPQDs) system. Ferrocene attached to the hairpin DNA could quench the cathodic and anodic ECL simultaneously. Subsequently, the ECL signals recovered in the presence of tumor marker mucin 1 (MUC1), which made it possible to quantitatively detect MUC1. The variation of ECL signal was related linearly to the concentrations of MUC1 in the range 20 pg mL-1 to 10 ng mL-1, and the detection limits were calculated to 2.5 pg mL-1 (anodic system, 3σ) and 6.2 pg mL-1 (cathodic system, 3σ), respectively. The recoveries were 97.0%, 105%, and 95.2% obtained from three human serum samples, and the relative standard deviation (RSD) is 5.3%. As a proof of concept, this work realized simultaneous ECL emission of  a single luminophore, which initiates a new thought in biomarker ECL detection beyond the traditional ones. Simultaneous cathodic and anodic ECL emissions of RuNDs were reported based on different co-reactants. Ferrocene could quench the ECL emission in the cathode and the anode simultaneously. Thus, an aptasensor was constructed based on the variation of ECL intensity. As a proof of concept, this work realized simultaneous ECL emission of a single luminophore, which initiates a new thought in biomarker ECL detection beyond the traditional ones by avoiding the false positive signals.

Differential Urinary Proteome Analysis for Predicting Prognosis in Type 2 Diabetes Patients with and without Renal Dysfunction.

Renal dysfunction, a major complication of type 2 diabetes, can be predicted from estimated glomerular filtration rate (eGFR) and protein markers such as albumin concentration. Urinary protein biomarkers may be used to monitor or predict patient status. Urine samples were selected from patients enrolled in the retrospective diabetic kidney disease (DKD) study, including 35 with good and 19 with poor prognosis. After removal of albumin and immunoglobulin, the remaining proteins were reduced, alkylated, digested, and analyzed qualitatively and quantitatively with a nano LC-MS platform. Each protein was identified, and its concentration normalized to that of creatinine. A prognostic model of DKD was formulated based on the adjusted quantities of each protein in the two groups. Of 1296 proteins identified in the 54 urine samples, 66 were differentially abundant in the two groups (area under the curve (AUC): p-value < 0.05), but none showed significantly better performance than albumin. To improve the predictive power by multivariate analysis, five proteins (ACP2, CTSA, GM2A, MUC1, and SPARCL1) were selected as significant by an AUC-based random forest method. The application of two classifiers-support vector machine and random forest-showed that the multivariate model performed better than univariate analysis of mucin-1 (AUC: 0.935 vs. 0.791) and albumin (AUC: 1.0 vs. 0.722). The urinary proteome can reflect kidney function directly and can predict the prognosis of patients with chronic kidney dysfunction. Classification based on five urinary proteins may better predict the prognosis of DKD patients than urinary albumin concentration or eGFR.

Urinary peptidomic biomarkers of renal function in heart transplant recipients.

BACKGROUND: Chronic kidney disease (CKD) is common in patients after heart transplantation (HTx). We assessed whether in HTx recipients the proteomic urinary classifier CKD273 or sequenced urinary peptides revealing the parental proteins correlated with the estimated glomerular filtration rate (eGFR). METHODS: In 368 HTx patients, we measured the urinary peptidome and analysed CKD273 and 48 urinary peptides with a detectable signal in >95% of participants. After 9.1 months (median), eGFR and the urinary biomarkers were reassessed. RESULTS: In multivariable Bonferroni-corrected analyses of the baseline data, a 1-SD increase in CKD273 was associated with a 11.4 [95% confidence interval (CI) 7.25-15.5] mL/min/1.73 m2 lower eGFR and an odds ratio of 2.63 (1.56-4.46) for having eGFR <60 mL/min/1.73 m2. While relating eGFR category at follow-up to baseline urinary biomarkers, CKD273 had higher (P = 0.007) area under the curve (0.75; 95% CI 0.70-0.80) than 24-h proteinuria (0.64; 95% CI 0.58-0.69), but additional adjustment for baseline eGFR removed significance of both biomarkers. In partial least squares analysis, the strongest correlates of the multivariable-adjusted baseline eGFR were fragments of collagen I (positive) and the mucin-1 subunit α (inverse). Associations between the changes in eGFR and the urinary markers were inverse for CKD273 and mucin-1 and positive for urinary collagen I. CONCLUSIONS: With the exception of baseline eGFR, CKD273 was more closer associated with imminent renal dysfunction than 24-h proteinuria. Fragments of collagen I and mucin-1-respectively, positively and inversely associated with eGFR and change in eGFR-are single-peptide markers associated with renal dysfunction.

Mucin-1 Increases Renal TRPV5 Activity In Vitro, and Urinary Level Associates with Calcium Nephrolithiasis in Patients.

Hypercalciuria is a major risk factor for nephrolithiasis. We previously reported that Uromodulin (UMOD) protects against nephrolithiasis by upregulating the renal calcium channel TRPV5. This channel is crucial for calcium reabsorption in the distal convoluted tubule (DCT). Recently, mutations in the gene encoding Mucin-1 (MUC1) were found to cause autosomal dominant tubulointerstitial kidney disease, the same disease caused by UMOD mutations. Because of the similarities between UMOD and MUC1 regarding associated disease phenotype, protein structure, and function as a cellular barrier, we examined whether urinary MUC1 also enhances TRPV5 channel activity and protects against nephrolithiasis. We established a semiquantitative assay for detecting MUC1 in human urine and found that, compared with controls (n=12), patients (n=12) with hypercalciuric nephrolithiasis had significantly decreased levels of urinary MUC1. Immunofluorescence showed MUC1 in the thick ascending limb, DCT, and collecting duct. Applying whole-cell patch-clamp recording of HEK cells, we found that wild-type but not disease mutant MUC1 increased TRPV5 activity by impairing dynamin-2- and caveolin-1-mediated endocytosis of TRPV5. Coimmunoprecipitation confirmed a physical interaction between TRPV5 and MUC1. However, MUC1 did not increase the activity of N-glycan-deficient TRPV5. MUC1 is characterized by variable number tandem repeats (VNTRs) that bind the lectin galectin-3; galectin-3 siRNA but not galectin-1 siRNA prevented MUC1-induced upregulation of TRPV5 activity. Additionally, MUC1 lacking VNTRs did not increase TRPV5 activity. Our results suggest that MUC1 forms a lattice with the N-glycan of TRPV5 via galectin-3, which impairs TRPV5 endocytosis and increases urinary calcium reabsorption.

[Value of quantitative examination of urine MUC1 in bladder transitional cell carcinoma].

OBJECTIVE: To evaluate the value of quantitative examination of MUC 1 in the urine of patients with bladder transitional cell carcinoma (BTCC). METHODS: Urine samples were obtained from 31 patients with BTCC for quantification of MUC 1 content by immunoradiometric analysis. The urine samples were also examined in 10 patients with cystitis glandularis, 10 with benign urine disease and 10 healthy volunteers. The differences in urine MUC1 content were statistically measured between the groups, between cancer patients of different clinical stages and classes, between primary and recurrent cancer patients, and between measurements taken before and after operation. RESULTS: Urine MUC 1 was detected in all the patients. No significant differences were found between the groups, nor between patients with BTCC in all stages (P>0.05), or between primary and recurrent cancer patients (P>0.05). But MUC 1 contents showed significant difference before and after the operation in the cancer patients (P<0.05). CONCLUSIONS: Urine MUC 1 can not serve as the marker to screen and diagnose BTCC, but it can be useful in therapeutic effect and prognostic evaluation. Specific oncogene markers are more significant than oncogene phenotype markers in clinical diagnosis and screen of BTCC.

Combined use of epithelial membrane antigen and nuclear matrix protein 52 as sensitive biomarkers for detection of bladder cancer.

BACKGROUND: The advent of noninvasive urine-based markers as well as other novel modalities has yielded improved diagnostic accuracy. However, the new markers failed to reach higher sensitivity and specificity. We therefore evaluated the potential role of epithelial membrane antigen (EMA) and nuclear matrix protein 52 (NMP-52) singly and combined as noninvasive biomarkers for the detection of bladder cancer (BC). METHODS: A total of 160 individuals including 66 patients with BC, 54 patients with benign urologic disorders and 40 healthy volunteers were investigated. Urinary EMA at 130 kDa and NMP at 52 kDa were identified, purified and quantified by Western blot, electroelution and enzyme-linked immunosorbent assay (ELISA). The diagnostic performance of each biomarker and their combination were compared using area under receiver operating characteristic curves (AUC). RESULTS: Mean urinary EMA, 2.42 µg/mL, and NMP-52, 17.85 µg/mL, were significantly elevated in patients with BC compared to controls, 1.18 and 3.44 µg/mL, respectively (p<0.0001). The combined use of these markers yielded values which were increased 4.4- and 13.7-fold in the benign and malignant disease groups, respectively, with respect to the normal group. The values of EMA and NMP-52 were significantly higher in patients with higher-grade tumors than those with lower-grade tumors (p<0.0001). Moreover, this combination could predict all BC stages and grades with 0.91 AUC, 94% sensitivity and 80% specificity. CONCLUSIONS: EMA and NMP-52 in combination could be promising noninvasive biomarkers for BC detection.

Evaluation of Pepscan analyses for epitope mapping of anti-MUC1 monoclonal antibodies--a comparative study and review of five antibodies.

Many murine monoclonal antibodies against MUC1 mucin have been analysed for reactivity against short overlapping peptides with sequences based upon that of the 20 amino acid tandem repeat of the MUC1 protein core, in order to identify the minimum binding units or epitopes. This report summarises the findings using a set of overlapping heptamers to identify the epitopes of 5 established anti-MUC1 antibodies. The results are evaluated and reviewed in comparison to those obtained using other length peptides and other assay formats for epitope mapping using the Pepscan technique.

Urinary epitectin (MUC-1 glycoprotein) in the menstrual cycle and interstitial cystitis.

PURPOSE: We compared interstitial cystitis and control urine specimens for epitectin (MUC-1 glycoprotein), an epithelial mucin. MATERIALS AND METHODS: Urinary epitectin was measured in 28 patients with interstitial cystitis and 26 healthy controls. Ten controls provided multiple urine samples to determine whether urinary epitectin changes with the menstrual cycle. RESULTS: Epitectin levels were stable throughout the menstrual cycle. Interstitial cystitis cases had decreased urinary epitectin-to-creatinine ratios (mean 3.89 versus 6.38 micrograms./mg. creatinine for controls, p = 0.0035) and epitectin concentrations (mean 1.96 versus 4.30 micrograms./ml., respectively, p = 0.0005). CONCLUSIONS: Decreased mean urinary epitectin levels may reflect a cause (epithelial mucin deficiency) or a consequence of interstitial cystitis.

Lack of evidence for an immunosuppressive role for MUC1.

The in vitro anti-proliferative properties of various supernatants from MUC1-expressing cell lines and of purified preparations of MUC1 were evaluated. We have observed that supernatants from the MUC1-and MUC3-positive cell line T47D, but not from the MUC1- and MUC4-positive cell line MCF7, were able to inhibit proliferation of cells from various haematopoietic cell lines. Although the activity of T47D supernatants could be abrogated by immunodepletion of MUC1, immunopurified MUC1 from T47D was unable to inhibit cell proliferation. Significantly, supernatants from mouse 3T3 cells transfected with a secreted form of MUC1 or from BHK-21 cells infected with a recombinant vaccinia virus coding for the secreted form of MUC1, as well as preparations of purified MUC1 from bile or urine, were likewise unable to inhibit T cell proliferation. Surprisingly, a crude mixture of bile mucins had a suppressive effect on T cell growth. Our results suggest that other molecules, such as amino sugars or other mucins, which can associate with MUC1, are likely to be responsible for the observed anti-proliferative effects of T47D cells.