Urinary proteomics as a novel tool for biomarker discovery in kidney diseases

Novel Biomarkers for the diagnosis of diabetic nephropathy

Diabetes mellitus and its complications are a known public health problem nowadays. Diabetic nephropathy is one of the main complications and the result of multiple mechanisms, including: activation of the renin-angiotensin-aldosterone system, formation of advanced glycation end products and chronic inflammation that led to glomerular and tubulo-interstitial damage producing mesangial expansion and glomerulosclerosis, which finally results in chronic kidney disease. Early detection of diabetic nephropathy is essential for adequate intervention to stop, or at least slow down its progression. Multiple markers have been described, not only the classic ones such as serum creatinine, urea, and albuminuria, but at this point also novel biomarkers such as neutrophil gelatinase-associated lipocalin, tumor necrosis factor 1 receptor and monocyte chemoattractant protein-1, among others. The aim of this article was to provide an update review of the role of biomarkers in the diagnosis of diabetic nephropathy.

Progress in understanding primary glomerular disease: insights from urinary proteomics and in-depth analyses of potential biomarkers based on bioinformatics

Chronic kidney disease (CKD) has become a global public health challenge. While primary glomerular disease (PGD) is one of the leading causes of CKD, the specific pathogenesis of PGD is still unclear. Accurate diagnosis relies largely on invasive renal biopsy, which carries risks of bleeding, pain, infection and kidney vein thrombosis. Problems with the biopsy procedure include lack of glomeruli in the tissue obtained, and the sampling site not being reflective of the overall lesion in the kidney. Repeated renal biopsies to monitor disease progression cannot be performed because of the significant risks of bleeding and kidney vein thrombosis. On the other hand, urine collection, a noninvasive method, can be performed repeatedly, and urinary proteins can reflect pathological changes in the urinary system. Advancements in proteomics technologies, especially mass spectrometry, have facilitated the identification of candidate biomarkers in different pathological types of PGD. Such biomarkers not only provide insights into the pathogenesis of PGD but also are important for diagnosis, monitoring treatment, and prognosis. In this review, we summarize the findings from studies that have used urinary proteomics, among other omics screens, to identify potential biomarkers for different types of PGD. Moreover, we performed an in-depth bioinformatic analysis to gain a deeper understanding of the biological processes and protein-protein interaction networks in which these candidate biomarkers may participate. This review, including a description of an integrated analysis method, is intended to provide insights into the pathogenesis, noninvasive diagnosis, and personalized treatment efforts of PGD and other associated diseases.

Characterization of the Urinary Metagenome and Virome in Healthy Children

Recent advances in next-generation sequencing and metagenomic studies have provided insights into the microbial profile of different body sites. However, research on the microbial composition of urine is limited, particularly in children. The goal of this study was to optimize and develop reproducible metagenome and virome protocols using a small volume of urine samples collected from healthy children. We collected midstream urine specimens from 40 healthy children. Using the metagenomics shotgun approach, we tested various protocols. Different microbial roots such as Archaea, Bacteria, Eukaryota, and Viruses were successfully identified using our optimized urine protocol. Our data reflected much variation in the microbial fingerprints of children. Girls had significantly higher levels of Firmicutes, whereas boys had significantly higher levels of Actinobacteria. The genus Anaerococcus dominated the urinary bacteriome of healthy girls, with a significant increase in Anaerococcus prevotii, Anaerococcus vaginalis, and Veillonella parvula (p-value < 0.001) when compared with that of boys. An increased relative abundance of Xylanimonas and Arthrobacter, with a significantly high abundance of Arthrobacter sp. FB24 (p-value 0.0028) and Arthrobacter aurescences (p-value 0.015), was observed in boys. The urinary mycobiome showed a significant rise in the genus Malassezia and Malassezia globose fungus (p-value 0.009) in girls, whereas genus Saccharomyces (p-value 0.009) was significantly high in boys. The beta diversity of the urinary mycobiome was found to differ between different age groups. Boys had significantly more Mastadenovirus and Human mastadenovirus-A in their urinary virome than girls. With increasing age, we noticed an increase in the relative abundance of the order Caudovirales. Our optimized protocols allowed us to identify the unique microbes for each sex by using an adequate volume of urine (3−10 mL) to screen for the bacteriome, mycobiome, and virome profiles in the urine of healthy children. To the best of our knowledge, this is the first study to characterize the metagenomics profiles of urine in a healthy pediatric population.

Proteomics: Concepts and applications in human medicine

Proteomics is the complete evaluation of the function and structure of proteins to understand an organism’s nature. Mass spectrometry is an essential tool that is used for profiling proteins in the cell. However, biomarker discovery remains the major challenge of proteomics because of their complexity and dynamicity. Therefore, combining the proteomics approach with genomics and bioinformatics will provide an understanding of the information of biological systems and their disease alteration. However, most studies have investigated a small part of the proteins in the blood. This review highlights the types of proteomics, the available proteomic techniques, and their applications in different research fields.

Collagen Type III and VI Remodeling Biomarkers Are Associated with Kidney Fibrosis in Lupus Nephritis

Background

Lupus nephritis (LN) occurs in <40% of patients with SLE. Reliable biomarkers of kidney damage are needed to identify patients with SLE at risk of developing LN to improve screening, treat the disease earlier, and halt progression to kidney failure. Novel biomarkers of extracellular matrix remodeling were evaluated as markers of kidney fibrosis and disease activity in patients with LN.

Methods

Biomarkers of the interstitial collagen type III (PRO-C3) and type VI (PRO-C6) formation and of collagen type III (C3M) degradation were evaluated in the serum and urine of 40 patients with LN, 20 patients with SLE but without LN, 20 healthy controls, and ten biopsy controls (histologic kidney inflammation/damage without SLE). Their association with histologic markers of interstitial fibrosis and tubular atrophy, with inflammatory cell infiltration and with disease activity and chronicity in the patients with LN was assessed.

Results

Despite PRO-C3 (serum) and PRO-C6 (serum and urine) being significantly elevated in patients with LN compared with healthy controls, the markers did not differentiate patients with LN from those with SLE. C3M (urine) levels were not different in LN compared with the other groups. C3M (urine) strongly correlated and PRO-C6 (serum and urine) inversely correlated with kidney function (eGFR). The biomarkers of interstitial collagen turnover PRO-C6 (serum) and C3M (urine) correlated with histologic markers of interstitial fibrosis, tubular atrophy, and monocyte infiltration.

Conclusions

Noninvasive collagen turnover biomarkers are promising tools to identify patients with SLE with kidney histologic modifications.

Targeted urine proteomics in lupus nephritis - a meta-analysis

BACKGROUND

Proteomic approaches are central in biomarker discovery. While mass-spectrometry-based techniques are widely used, novel targeted proteomic platforms have enabled the high-throughput detection of low-abundance proteins in an affinity-based manner. Urine has gained growing attention as an ideal biofluid for monitoring renal disease including lupus nephritis (LN).

METHODS

Pubmed was screened for targeted proteomic studies of LN urine interrogating ≥1000 proteins. Data from the primary studies were combined and a meta-analysis was performed. Shared proteins elevated in active LN across studies were identified, and relevant pathways were elucidated using ingenuity pathway and gene ontology analysis. Urine proteomic data was cross-referenced against renal single-cell RNAseq data from LN kidneys.

RESULTS

Two high-throughput targeted proteomic platforms with capacity to interrogate ≥1000 proteins have been used to investigate LN urine. Twenty-three urine proteins were significantly elevated in both studies, including 10 chemokines, and proteins implicated in angiogenesis, and extracellular matrix turnover. Of these, Cathepsin S, CXCL10, FasL, ferritin, macrophage migration inhibitory factor (MIF), and resistin were also significantly elevated within LN kidneys.

CONCLUSION

Targeted urinary proteomics have uncovered multiple novel biomarkers for LN. Further validation in prospective cohorts and mechanistic studies are warranted to establish their clinical utility.

SWATH-MS Protocols in Human Diseases

Identification of molecular biomarkers for human diseases is one of the most important disciplines in translational science as it helps to elucidate their origin and early progression. Thus, it is a key factor in better diagnosis, prognosis, and treatment. Proteomics can help to solve the problem of sample complexity when the most common primary sample specimens were analyzed: organic fluids of easy access. The latest developments in high-throughput and label-free quantitative proteomics (SWATH-MS), together with more advanced liquid chromatography, have enabled the analysis of large sample sets with the sensitivity and depth needed to succeed in this task. In this chapter, we show different sample processing methods (major protein depletion, digestion, etc.) and a micro LC-SWATH-MS protocol to identify/quantify several proteins in different types of samples (serum/plasma, saliva, urine, tears).

Use of liquid chromatography-tandem mass spectrometry to perform urinary proteomic analysis of children with IgA nephropathy and Henoch-Schönlein purpura nephritis

The emerging technology of urinary proteomics has become an efficient biological approach for identifying biomarkers and characterizing pathogenesis in renal involvement. In this study, we attempted to elucidate the relationship between IgAN and HSPN in children, employing LC-MS/MS to perform urinary proteomic analyses using the DIA method. Early-morning spot urine was collected from patients with biopsy-proven IgAN (n = 19) and HSPN (n = 19) prior to treatment and renal biopsy in the Department of Pediatrics, Jinling Hospital, Nanjing, China, and did healthy volunteers (n = 14), from June 2018 to December 2019. Two hundred seventy-six urinary proteins and 125 urinary proteins were determined to be differentially expressed in children with IgAN (n = 4) and HSPN (n = 4), respectively, compared to the urinary proteins of healthy children (n = 4) (p < 0.05). GO analysis demonstrated that the differentially expressed proteins of the two groups, which were located in the extracellular matrix and cell membrane, were primarily involved in biological processes, including metabolic processes, immune system processes, cellular adhesion, cell proliferation, signaling, and biological regulation. KEGG analysis revealed that the differentially expressed proteins of the two groups were associated with cell adhesion molecules, ECM-receptor interactions, the PI3K-Akt signaling pathway, the complement and coagulation cascades, regulation of actin cytoskeleton, cholesterol metabolism, and platelet activation. The target proteins (alpha-1B-glycoprotein (A1BG) and afamin (AFM)), which participated in the complement and coagulation cascades and the regulation of complement activation, were further investigated in the independent validation cohort by ELISA. These proteins were significantly increased in children with IgAN (n = 15) and HSPN (n = 15) compared with the proteins observed in healthy controls (n = 10, P < 0.05). The validated results were consistent with the mass spectrometry results. SIGNIFICANCE: IgAN and HSPN both result from the glomerular deposition of abnormally glycosylated IgA1 with mesangial proliferative changes, and both diseases are common glomerulopathies in the pediatric population that are believed to be correlated. Interestingly, our data, by combining urinary proteomic analyses, showed that several uniform enrichment pathways played an important role in the progression of IgAN and HSPN, suggesting that we might reduce the renal involvement of the two diseases in children through these pathways. The same urinary proteins along these pathways were observed to be differentially expressed in children with IgAN and HSPN, implying that these proteins may be potential biomarkers to identify the two diseases. Future studies examining larger cohorts are warranted to confirm the validity of our findings.

The association between plasma proteomics and incident cardiovascular disease identifies MMP-12 as a promising cardiovascular risk marker in patients with chronic kidney disease

BACKGROUND AND AIMS

Previous proteomics efforts in patients with chronic kidney disease (CKD) have predominantly evaluated urinary protein levels. Therefore, our aim was to investigate the association between plasma levels of 80 cardiovascular disease-related proteins and the risk of major adverse cardiovascular events (MACE) in patients with CKD.

METHODS

Individuals with CKD stages 3-5 (eGFR below 60 ml min-1 [1.73 m]-2) from three community-based cohorts (PIVUS, ULSAM, SAVA), one diabetes cohort (CARDIPP) and one cohort with peripheral artery disease patients (PADVA) with information on 80 plasma protein biomarkers, assessed with a proximity extension assay, and follow-up data on incident MACE, were used as discovery sample. To validate findings and to asses generalizability to patients with CKD in clinical practice, an outpatient CKD-cohort (Malnutrition, Inflammation and Vascular Calcification (MIVC)) was used as replication sample.

RESULTS

In the discovery sample (total n = 1316), 249 individuals experienced MACE during 7.0 ± 2.9 years (range 0.005-12.9) of follow-up, and in the replication sample, 71 MACE events in 283 individuals over a mean ± SD change of 2.9 ± 1.2 years (range 0.1-4.0) were documented. Applying Bonferroni correction, 18 proteins were significantly associated with risk of MACE in the discovery cohort, adjusting for age and sex in order of significance, GDF-15, FGF-23, REN, FABP4, IL6, TNF-R1, AGRP, MMP-12, AM, KIM-1, TRAILR2, TNFR2, CTSL1, CSF1, PlGF, CA-125, CCL20 and PAR-1 (p < 0.000625 for all). Only matrix metalloproteinase 12 (MMP-12) was significantly associated with an increased risk of MACE in the replication sample (hazard ratio (HR) per SD increase, 1.36, 95% CI (1.07-1.75), p = 0.013).

CONCLUSIONS

Our proteomics analyses identified plasma MMP-12 as a promising cardiovascular risk marker in patients with CKD.

Proteomics-Based Machine Learning Approach as an Alternative to Conventional Biomarkers for Differential Diagnosis of Chronic Kidney Diseases

Diabetic nephropathy, hypertension, and glomerulonephritis are the most common causes of chronic kidney diseases (CKD). Since CKD of various origins may not become apparent until kidney function is significantly impaired, a differential diagnosis and an appropriate treatment are needed at the very early stages. Conventional biomarkers may not have sufficient separation capabilities, while a full-proteomic approach may be used for these purposes. In the current study, several machine learning algorithms were examined for the differential diagnosis of CKD of three origins. The tested dataset was based on whole proteomic data obtained after the mass spectrometric analysis of plasma and urine samples of 34 CKD patients and the use of label-free quantification approach. The k-nearest-neighbors algorithm showed the possibility of separation of a healthy group from renal patients in general by proteomics data of plasma with high confidence (97.8%). This algorithm has also be proven to be the best of the three tested for distinguishing the groups of patients with diabetic nephropathy and glomerulonephritis according to proteomics data of plasma (96.3% of correct decisions). The group of hypertensive nephropathy could not be reliably separated according to plasma data, whereas analysis of entire proteomics data of urine did not allow differentiating the three diseases. Nevertheless, the group of hypertensive nephropathy was reliably separated from all other renal patients using the k-nearest-neighbors classifier “one against all” with 100% of accuracy by urine proteome data. The tested algorithms show good abilities to differentiate the various groups across proteomic data sets, which may help to avoid invasive intervention for the verification of the glomerulonephritis subtypes, as well as to differentiate hypertensive and diabetic nephropathy in the early stages based not on individual biomarkers, but on the whole proteomic composition of urine and blood.

Urinary proteomics of Henoch-Schönlein purpura nephritis in children using liquid chromatography-tandem mass spectrometry

BACKGROUND

Henoch-Schönlein purpura nephritis (HSPN) is the principal cause of morbidity and mortality in children with Henoch-Schönlein purpura (HSP). However, the criteria for risk assessment currently used is not satisfactory. The urine proteome may provide important clues to indicate the development of HSPN.

METHODS

Here, we detected and compared the urine proteome of patients with HSPN and healthy controls by liquid chromatography-tandem mass spectrometry (LC-MS/MS) in the data-independent acquisition (DIA) mode. The differentially expressed proteins were analysed by gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. For validation, enzyme-linked immunosorbent assay (ELISA) was used to analyse the selected proteins.

RESULTS

A total of 125 proteins (29 upregulated and 96 downregulated) were found to be differentially expressed in children with HSPN compared with the controls. Forty-one proteins were predicted to have direct interactions. The enriched pathways mainly included focal adhesion, cell adhesion molecules, the PI3K-Akt signalling pathway, ECM-receptor interactions and so on. Cell adhesion related to the pathogenesis of HSPN was the main biological process identified in this study. The decrease in two proteins (integrin beta-1 and tenascin) was validated by ELISA.

CONCLUSIONS

Our study provides new insights into the assessment of HSPN progression in children, as well as new potential biomarkers. The data confirm the value of the urinary proteome in capturing the emergence of HSPN.

Proteomic Biomarkers for the Detection of Endometrial Cancer

Endometrial cancer is the leading gynaecological malignancy in the western world and its incidence is rising in tandem with the global epidemic of obesity. Early diagnosis is key to improving survival, which at 5 years is less than 20% in advanced disease and over 90% in early-stage disease. As yet, there are no validated biological markers for its early detection. Advances in high-throughput technologies and machine learning techniques now offer unique and promising perspectives for biomarker discovery, especially through the integration of genomic, transcriptomic, proteomic, metabolomic and imaging data. Because the proteome closely mirrors the dynamic state of cells, tissues and organisms, proteomics has great potential to deliver clinically relevant biomarkers for cancer diagnosis. In this review, we present the current progress in endometrial cancer diagnostic biomarker discovery using proteomics. We describe the various mass spectrometry-based approaches and highlight the challenges inherent in biomarker discovery studies. We suggest novel strategies for endometrial cancer detection exploiting biologically important protein biomarkers and set the scene for future directions in endometrial cancer biomarker research.

Magnetic mesoporous silica of loading copper metal ions for enrichment and LC-MS/MS analysis of salivary endogenous peptides

Peptidomics research is of great significance for discovering potential biomarkers and monitoring human diseases. As a kind of common clinical biofluid, saliva known for its noninvasive collection and easy accessibility has been widely used in peptidomics research. In this article, we combined immobilized metal ions affinity chromotography (IMAC) with mesoporous material and proposed the copper ion doped magnetic mesoporous silica material (denoted as Fe₃O₄@mSiO₂-Cu²⁺) which had a large surface area of 221 m² g^-1 and pore volume of 0.20 cm³ g^-1. By immobilizing copper ions onto the mesopore walls, the standard peptide Angiotensin II could be identified in an extremely low concentration of 0.1 fmol μl^-1 and in a mass ratio of 1:500 (Angiotensin II:BSA, m/m), which indicated significant sensitivity and a great size-exclusive ability. In addition, the introduction of polydopamine (PDA) made Fe₃O₄@mSiO₂-Cu²⁺ more hydrophilic and biocompatible which could improve the profiling of endogenous peptides in bio-sample. Finally, 131 endogenous peptides were identified in human saliva after enrichment with Fe₃O₄@mSiO₂-Cu²⁺. Therefore, Fe₃O₄@mSiO₂-Cu²⁺ nanoparticles provided a promising candidate protocol for biomarker discovery.

A cost-effective method for purification and characterization of human urinary albumin

We describe a simplified approach for the purification and characterization of urinary albumin, a key biomarker currently used for understanding the onset and prognosis of microalbuminuria. Urinary albumin was purified from human urine collected from diabetic kidney disease patients by using 2-stage tangential flow filtration process and set of column chromatography steps. The relative molecular mass of urinary albumin is 66,871 Da (SYNAPT G2 High Definition Mass Spectrometry System). Isolated urinary albumin was analyzed by SDS-PAGE, Western blotting, immunoelectrophoresis, Ouchterlony double-immunodiffusion, single radial immunodiffusion, size-exclusion HPLC and peptide mass fingerprint analysis. The size-exclusion HPLC elution profile of the purified urinary albumin was similar to that of a reference form of native albumin. Peptide mass fingerprint analysis of the purified urinary albumin yielded peptides that partially matched with known sequence of ALBU_HUMAN (P02768). This is the first report of purification and validation of immunochemically reactive form of urinary albumin from a large volume of urine of diabetic kidney disease patients. In this purification approach, the cost of the purified albumin is significantly lower.

MALDI-TOF-MS Analysis in the Identification of Urine Proteomic Patterns of Gestational Trophoblastic Disease

Gestational trophoblastic disease (GTD) is a group of highly aggressive, rare tumors. Human chorionic gonadotropin is a common biomarker used in the diagnosis and monitoring of GTD. To improve our knowledge of the pathology of GTD, we performed protein-peptide profiling on the urine of patients affected with gestational trophoblastic neoplasm (GTN). We analyzed urine samples from patients diagnosed with GTN (n = 26) and from healthy pregnant and non-pregnant controls (n = 17) using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS). Ions were examined in a linear mode over a m/z range of 1000–10,000. All GTN urine samples were analyzed before and after treatment and compared with those of the controls. The statistical analyses included multivariate classification algorithms as well as ROC curves. Urine sample analyses revealed there were significant differences in the composition of the ions between the evaluated groups. Comparing the pre-treatment and group with the pregnant controls, we identified two discriminatory proteins: hemoglobin subunit α (m/z = 1951.81) and complement C4A (m/z = 1895.43). Then, comparing urine samples from the post-treatment cases with those from the non-pregnant controls, we identified the peptides uromodulin fragments (m/z = 1682.34 and 1913.54) and complement C4A (m/z = 1895.43).

Identification of diagnostic upper gastrointestinal cancer tissue type-specific urinary biomarkers

Several potential urinary biomarkers exhibiting an association with upper gastrointestinal tumour growth have been previously identified, of which S100A6, S100A9, rabenosyn-5 and programmed cell death 6-interacting protein (PDCD6IP) were further validated and found to be upregulated in malignant tumours. The cancer cohort from our previous study was subclassified to assess whether distinct molecular markers can be identified for each individual cancer type using a similar approach. Urine samples from patients with cancers of the stomach, oesophagus, oesophagogastric junction or pancreas were analysed by surface-enhanced laser desorption/ionization-time-of-flight mass spectrometry using both CM10 and IMAC30 (Cu²⁺-complexed) chip types and LC-MS/MS-based mass spectrometry after chromatographic enrichment. This was followed by protein identification, pattern matching and validation by western blotting. We found 8 m/z peaks with statistical significance for the four cancer types investigated, of which m/z 2447 and 2577 were identified by pattern matching as fragments of cathepsin-B (CTSB) and cystatin-B (CSTB); both molecules are indicative of pancreatic cancer. Additionally, we observed a potential association of upregulated α-1-antichymotrypsin with pancreatic and gastric cancers, of PDCD6IP, vitelline membrane outer layer protein 1 homolog (VMO1) and triosephosphate isomerase (TPI1) with oesophagogastric junctional cancers, and of complement C4-A, prostatic acid phosphatase, azurocidin and histone-H1 with oesophageal cancer. Furthermore, the potential pancreatic cancer biomarkers CSTB and CTSB were validated independently by western blotting. Therefore, the present study identified two new potential urinary biomarkers that appear to be associated with pancreatic cancer. This may provide a simple, non-invasive screening test for use in the clinical setting.

A non-invasive biomarker of type III collagen degradation reflects ischaemia reperfusion injury in rats

Background

Maintenance of kidney function in kidney allografts remains a challenge, as the allograft often progressively develops fibrosis after kidney transplantation. Fibrosis is caused by the accumulation of extracellular matrix proteins like type I and III collagen (COL I and III) that replace the functional tissue. We assessed the concentrations of a neo-epitope fragment of COL III generated by matrix metalloproteinase-9 cleavage (C3M) in two rat models resembling the ischaemic injury taking place following kidney transplantation.

Methods

We measured C3M in urine (U-C3M) and plasma (P-C3M) samples of rats subjected to unilateral nephrectomy followed by sham operation (NTx) or ischaemia reperfusion injury (NTxIRI) as well as in rats subjected to bilateral ischaemia reperfusion injury (BiIRI). Levels of U-C3M were normalized to urinary creatinine and were correlated to plasma creatinine, blood urea nitrogen, messenger ribonucleic acid (mRNA) of markers of kidney injury, and mRNA and protein levels of markers of tissue repair and fibrosis.

Results

Levels of U-C3M were significantly elevated 7 days after ischaemia reperfusion in the NTxIRI. BiIRI animals showed higher levels of U-C3M after 7 and 14 days of reperfusion but not at 21 days. P-C3M did not change in any of the models. There was a significant correlation between U-C3M and mRNA levels of fibronectin, COL I alpha 1 chain (COL Ia1) and neutrophil gelatinase-associated lipocalin (NGAL), and protein levels of alpha smooth muscle actin (αSMA), fibronectin and COL III in NTxIRI but not in NTx animals. Levels of U-C3M increased significantly in the BiIRI animals subsequent to reperfusion, and mirrored the histological alterations. Furthermore, U-C3M was associated with the extent of fibrosis, and remained elevated even after plasma creatinine levels decreased.

Conclusions

These results demonstrate that degradation of COL III increases after ischaemia reperfusion injury, and that U-C3M may be a non-invasive marker of tissue repair and fibrosis in the ischaemic kidney.

Evaluation of a New Survivin ELISA and UBC® Rapid for the Detection of Bladder Cancer in Urine

Urine-based biomarkers for non-invasive diagnosis of bladder cancer are urgently needed. No single marker with sufficient sensitivity and specificity has been described so far. Thus, a combination of markers appears to be a promising approach. The aim of this case-control study was to evaluate the performance of an in-house developed enzyme-linked immunosorbent assay (ELISA) for survivin, the UBC^®Rapid test, and the combination of both assays. A total of 290 patients were recruited. Due to prior bladder cancer, 46 patients were excluded. Urine samples were available from 111 patients with bladder cancer and 133 clinical controls without urologic diseases. Antibodies generated from recombinant survivin were utilized to develop a sandwich ELISA. The ELISA and the UBC^®Rapid test were applied to all urine samples. Receiver operating characteristic (ROC) analysis was used to evaluate marker performance. The survivin ELISA exhibited a sensitivity of 35% with a specificity of 98%. The UBC^®Rapid test showed a sensitivity of 56% and a specificity of 96%. Combination of both assays increased the sensitivity to 66% with a specificity of 95%. For high-grade tumors, the combination showed a sensitivity of 82% and a specificity of 95%. The new survivin ELISA and the UBC^®Rapid test are both able to detect bladder cancer, especially high-grade tumors. However, the performance of each individual marker is moderate and efforts to improve the survivin assay should be pursued. A combination of both assays confirmed the benefit of using marker panels. The results need further testing in a prospective study and with a high-risk population.

Quantitative RNA Analysis from Urine Using Real Time PCR

Urine is emerging as a biological fluid suitable to perform liquid biopsy in a minimally invasive manner, a fundamental attribute for prevention and early detection of cancer. Urine biomarkers can be analyzed in voided urine, in urine sediment, and urine supernatant. In the case of urothelial carcinoma, in which tumor cells are in direct contact with urine, the assessment of the levels of biomarkers in the urinary cell fraction appears to be the most promising approach to identify diagnostic and prognostic biomarkers in a noninvasive way. Here, we describe a protocol to collect and process urine samples to obtain urinary exfoliated cells. Furthermore, we describe the methodology to isolate RNA from urinary cells and to quantify gene expression levels from these urinary cells.

Proteomics Applications in Health: Biomarker and Drug Discovery and Food Industry

Advancing in genome sequencing has greatly propelled the understanding of the living world; however, it is insufficient for full description of a biological system. Focusing on proteomics has emerged as another large-scale platform for improving the understanding of biology. Proteomic experiments can be used for different aspects of clinical and health sciences such as food technology, biomarker discovery and drug target identification. Since proteins are main constituents of foods, proteomic technology can monitor and characterize protein content of foods and their change during production process. The proteomic biomarker discovery is advanced in various diseases such as cancer, cardiovascular diseases, AIDS, and renal diseases which provide non-invasive methods by the use of body fluids such as urine and serum. Proteomics is also used in drug target identification using different approaches such as chemical proteomics and protein interaction networks. The development and application of proteomics has increased tremendously over the last decade. Advances in proteomics methods offer many promising new directions of studying in clinical fields. In this regard, we want to discuss proteomics technology application in food investigations, drug, and biomarker discovery.

Integrated Kidney Exosome Analysis for the Detection of Kidney Transplant Rejection

Kidney transplant patients require life-long surveillance to detect allograft rejection. Repeated biopsy, albeit the clinical gold standard, is an invasive procedure with the risk of complications and comparatively high cost. Conversely, serum creatinine or urinary proteins are noninvasive alternatives but are late markers with low specificity. We report a urine-based platform to detect kidney transplant rejection. Termed iKEA (integrated kidney exosome analysis), the approach detects extracellular vesicles (EVs) released by immune cells into urine; we reasoned that T cells, attacking kidney allografts, would shed EVs, which in turn can be used as a surrogate marker for inflammation. We optimized iKEA to detect T-cell-derived EVs and implemented a portable sensing system. When applied to clinical urine samples, iKEA revealed high level of CD3-positive EVs in kidney rejection patients and achieved high detection accuracy (91.1%). Fast, noninvasive, and cost-effective, iKEA could offer new opportunities in managing transplant recipients, perhaps even in a home setting.

Microplate magnetic chemiluminescence immunoassay for detecting urinary survivin in bladder cancer

Survivin is a tumor marker for bladder cancer; however the role of urinary survivin levels has not been fully elucidated due to the limitations of current detection methods. Based on two survivin-specific monoclonal antibodies (McAbs) already confirmed through enzyme linked immunosorbent assays, the present study aimed to establish a microplate magnetic chemiluminescence immunoassay (CLIA) for the detection of urinary survivin levels and evaluate its application for the diagnosis of patients with bladder cancer. Horseradish peroxidase and biotin conjugates were used to label two different anti-survivin McAbs, respectively. The labeled antibodies combined with survivin to form a sandwiched immune complex. The streptavidin magnetic particles (MPs) served as the solid phase and the separator. The relevant parameters involved in the immunoassay, including the immunoassay reagents used and the physicochemical parameters were optimized. Then, urine samples from 130 patients with bladder cancer and 113 healthy controls were detected, and analyzed using the established method. The method was linear to 1,000 ng/ml survivin with a detection limit of 0.83 ng/ml. The intra- and inter-assay coefficients of variation were <8, and <11%, respectively. The concentration of diluted survivin and the dilution ratios gave a linear correlation of 0.9989. The results demonstrated that the urinary survivin levels in patients with bladder cancer were significantly higher (P<0.001) compared with that in healthy controls. At a survivin concentration of 2.0884 ng/ml, the sensitivity and specificity were 86.9 and 61.9%, respectively. Furthermore, the urinary survivin levels were positively correlated with metastatic stage, histological stage and recurrence (P<0.01). In conclusion, the present study preliminarily proposed a microplate magnetic CLIA for survivin detection and further evaluated the value of urinary survivin as a diagnostic marker for bladder cancer.

Urinary glycated uromodulin in diabetic kidney disease

Advanced glycation end-products (AGEs) form during oxidative stress, which is increased in diabetes mellitus (DM). Uromodulin is a protein with a renal protective effect, and may be subject to glycation. The implications of uromodulin glycation and AGEs in the urine are not understood. Here, immunoprecipitation and liquid chromatography–mass spectrometry identified glycated uromodulin (glcUMOD) in the urine of 62.5% of patients with diabetic kidney disease (DKD), 20.0% of patients with non-diabetic chronic kidney disease (CKD), and no DM patients with normal renal function or healthy control participants; a finding replicated in a larger cohort of 84 patients with CKD in a case–control study (35 with DM, 49 without). Uromodulin forms high molecular weight polymers that associate with microvesicles and exosomes. Differential centrifugation identified uromodulin in the supernatant, microvesicles, and exosomes of the urine of healthy participants, but only in the supernatant of samples from patients with DKD, suggesting that glycation influences uromodulin function. Finally, the diagnostic and prognostic utility of measuring urinary glcUMOD concentration was examined. Urinary glcUMOD concentration was substantially higher in DKD patients than non-diabetic CKD patients. Urinary glcUMOD concentration predicted DKD status, particularly in patients with CKD stages 1–3a aged <65 years and with urine glcUMOD concentration ≥9,000 arbitrary units (AU). Urinary uromodulin is apparently glycated in DKD and forms AGEs, and glcUMOD may serve as a biomarker for DKD.

A novel approach for the chromatographic purification and peptide mass fingerprinting of urinary free light chains

We describe a chromatographic approach for the purification of urinary free light chains (FLCs) viz., lambda free light chains (λ-FLCs) and kappa free light chains (κ-FLCs). Isolated urinary FLCs were analyzed by SDS-PAGE, immunoblotting and mass spectrometry (MS). The relative molecular masses of λ-FLC and κ-FLC are 22,933.397 and 23,544.336Da respectively. Moreover, dimer forms of each FLC were also detected in mass spectrum which corresponds to 45,737.747 and 47,348.028Da respectively for λ-FLCs and κ-FLCs. Peptide mass fingerprint analysis of the purified λ-FLCs and κ-FLCs has yielded peptides that partially match with known light chain sequences viz., gi|218783338 and gi|48475432 respectively. The tryptic digestion profile of isolated FLCs infers the exclusive nature of them and they may be additive molecules in the dictionary of urinary proteins. This is the first report of characterization and validation of FLCs from large volume samples by peptide sequencing. This simple and cost-effective approach to purification of FLCs, together with the easy availability of urine samples make the large-scale production of FLCs possible, allowing exploration of various bioclinical as well as biodiagnostic applications.

Quantitative body fluid proteomics in medicine - A focus on minimal invasiveness

Identification of new biomarkers specific for various pathological conditions is an important field in medical sciences. Body fluids have emerging potential in biomarker studies especially those which are continuously available and can be collected by non-invasive means. Changes in the protein composition of body fluids such as tears, saliva, sweat, etc. may provide information on both local and systemic conditions of medical relevance. In this review, our aim is to discuss the quantitative proteomics techniques used in biomarker studies, and to present advances in quantitative body fluid proteomics of non-invasively collectable body fluids with relevance to biomarker identification. The advantages and limitations of the widely used quantitative proteomics techniques are also presented. Based on the reviewed literature, we suggest an ideal pipeline for body fluid analyses aiming at biomarkers discoveries: starting from identification of biomarker candidates by shotgun quantitative proteomics or protein arrays, through verification of potential biomarkers by targeted mass spectrometry, to the antibody-based validation of biomarkers. The importance of body fluids as a rich source of biomarkers is discussed.

SIGNIFICANCE

Quantitative proteomics is a challenging part of proteomics applications. The body fluids collected by non-invasive means have high relevance in medicine; they are good sources for biomarkers used in establishing the diagnosis, follow up of disease progression and predicting high risk groups. The review presents the most widely used quantitative proteomics techniques in body fluid analysis and lists the potential biomarkers identified in tears, saliva, sweat, nasal mucus and urine for local and systemic diseases.

Site-specific characterization of N-linked glycosylation in human urinary glycoproteins and endogenous glycopeptides

Glycosylation is a very important post-translational modification involved in various cellular processes, such as cell adhesion, signal transduction and immune response. Urine is a rich source of glycoproteins and attractive biological fluid for biomarker discovery, owing to its availability, ease of collection, and correlation with pathophysiology of diseases. Although the urinary proteomics have been explored previously, the urinary glycoproteome characterization remains challenging requiring the development and optimization of analytical and bioinformatics methods for protein glycoprofiling. This study describes the high confident identification of 472 unique N-glycosylation sites covering 256 urinary glycoproteins. Besides, 202 unique N-glycosylation sites were identified in low molecular weight endogenous glycopeptides, which belong to 90 glycoproteins. Global site-specific characterization of the N-linked glycan heterogeneity was achieved by intact glycopeptide analysis, revealing 303 unique glycopeptides most of them displaying complex/hybrid glycans composed by sialic acid and fucose. These datasets consist in a valuable resource of glycoproteins and N-glycosylation sites found in healthy human urine that can be further explored in different disorders, in which the N-linked glycosylation may be aberrant.

Analytical Performance of ELISA Assays in Urine: One More Bottleneck towards Biomarker Validation and Clinical Implementation

ELISA is the main approach for the sensitive quantification of protein biomarkers in body fluids and is currently employed in clinical laboratories for the measurement of clinical markers. As such, it also constitutes the main methodological approach for biomarker validation and further qualification. For the latter, specific assay performance requirements have to be met, as described in respective guidelines of regulatory agencies. Even though many clinical ELISA assays in serum are regularly used, ELISA clinical applications in urine are significantly less. The scope of our study was to evaluate ELISA assay analytical performance in urine for a series of potential biomarkers for bladder cancer, as a first step towards their large scale clinical validation. Seven biomarkers (Secreted protein acidic and rich in cysteine, Survivin, Slit homolog 2 protein, NRC-Interacting Factor 1, Histone 2B, Proteinase-3 and Profilin-1) previously described in the literature as having differential expression in bladder cancer were included in the study. A total of 11 commercially available ELISA tests for these markers were tested by standard curve analysis, assay reproducibility, linearity and spiking experiments. The results show disappointing performance with coefficients of variation>20% for the vast majority of the tests performed. Only 3 assays (for Secreted protein acidic and rich in cysteine, Survivin and Slit homolog 2 protein) passed the accuracy thresholds and were found suitable for further application in marker quantification. These results collectively reflect the difficulties in developing urine-based ELISA assays of sufficient analytical performance for clinical application, presumably attributed to the urine matrix itself and/or presence of markers in various isoforms.

Human Urine Proteomics: Analytical Techniques and Clinical Applications in Renal Diseases

Urine has been in the center of attention among scientists of clinical proteomics in the past decade, because it is valuable source of proteins and peptides with a relative stable composition and easy to collect in large and repeated quantities with a noninvasive procedure. In this review, we discuss technical aspects of urinary proteomics in detail, including sample preparation, proteomic technologies, and their advantage and disadvantages. Several recent experiments are presented which applied urinary proteome for biomarker discovery in renal diseases including diabetic nephropathy, immunoglobulin A (IgA) nephropathy, focal segmental glomerulosclerosis, lupus nephritis, membranous nephropathy, and acute kidney injury. In addition, several available databases in urinary proteomics are also briefly introduced.

A proteomic glimpse into human ureter proteome

Urine has evolved as one of the most important biofluids in clinical proteomics due to its noninvasive sampling and its stability. Yet, it is used in clinical diagnostics of several disorders by detecting changes in its components including urinary protein/polypeptide profile. Despite the fact that majority of proteins detected in urine are primarily originated from the urogenital (UG) tract, determining its precise source within the UG tract remains elusive. In this article, we performed a comprehensive analysis of ureter proteome to assemble the first unbiased ureter dataset. Next, we compared these data to urine, urinary exosome, and kidney mass spectrometric datasets. Our result concluded that among 2217 nonredundant ureter proteins, 751 protein candidates (33.8%) were detected in urine as urinary protein/polypeptide or exosomal protein. On the other hand, comparing ureter protein hits (48) that are not shown in corresponding databases to urinary bladder and prostate human protein atlas databases pinpointed 21 proteins that might be unique to ureter tissue. In conclusion, this finding offers future perspectives for possible identification of ureter disease-associated biomarkers such as ureter carcinoma. In addition, the ureter proteomic dataset published in this article will provide a valuable resource for researchers working in the field of urology and urine biomarker discovery. All MS data have been deposited in the ProteomeXchange with identifier PXD002620 (http://proteomecentral.proteomexchange.org/dataset/PXD002620).

Advancing Urinary Protein Biomarker Discovery by Data-Independent Acquisition on a Quadrupole-Orbitrap Mass Spectrometer

The promises of data-independent acquisition (DIA) strategies are a comprehensive and reproducible digital qualitative and quantitative record of the proteins present in a sample. We developed a fast and robust DIA method for comprehensive mapping of the urinary proteome that enables large scale urine proteomics studies. Compared to a data-dependent acquisition (DDA) experiments, our DIA assay doubled the number of identified peptides and proteins per sample at half the coefficients of variation observed for DDA data (DIA = ∼8%; DDA = ∼16%). We also tested different spectral libraries and their effects on overall protein and peptide identifications and their reproducibilities, which provided clear evidence that sample type-specific spectral libraries are preferred for reliable data analysis. To show applicability for biomarker discovery experiments, we analyzed a sample set of 87 urine samples from children seen in the emergency department with abdominal pain. The whole set was analyzed with high proteome coverage (∼1300 proteins/sample) in less than 4 days. The data set revealed excellent biomarker candidates for ovarian cyst and urinary tract infection. The improved throughput and quantitative performance of our optimized DIA workflow allow for the efficient simultaneous discovery and verification of biomarker candidates without the requirement for an early bias toward selected proteins.

Proteomic analysis reveals differentially secreted proteins in the urine from patients with clear cell renal cell carcinoma

OBJECTIVE

The aim of this study was to evaluate the differentially secreted protein profile in the urine from patients with clear cell renal cell carcinoma (ccRCC) using mass spectrometry-based methods. Urine composition can reflect kidney physiology and can be used to detect markers for renal diseases. Moreover, characterization of the secretome is likely to assist in the investigation of new drugs for biological targets and diagnose the ccRCC at an early stage.

METHODS AND MATERIALS

Urine samples from patients were divided according to Fuhrman degree (FI-IV), which was associated with the cellular differentiation as good prognosis (GP) and poor prognosis (PP). Healthy individuals were used as the control group (CG). We used both qualitative and quantitative mass spectrometry-based analyses that involved the following approaches: 1-dimensional gel electrophoresis combined with liquid chromatography mass spectrometry in tandem (1DE LC-MS/MS), in-solution digestion combined with label-free 1-dimensional LC-MS(E) (1D LC-MS(E)), and bidimensional gel electrophoresis combined with matrix-assisted laser desorption/ionization time of flight in tandem (2DE MALDI-TOF/TOF) or combined with LC-MS/MS.

RESULTS

All the strategies allowed the identification of 354 proteins from the CG, GP, and PP groups. Qualitative experiments using 1DE LC-MS/MS analysis detected different protein profiles, and 224 proteins were identified in all groups. The label-free MS(E) quantitative analysis identified 113 proteins and generated novel information on secreted protein profiles, including 49 up-secreted proteins in the urine from patients with ccRCC and 40 down-secreted proteins related to the CG. Proteins such as kininogen-1, uromodulin, apolipoprotein D, polyubiquitin, and CD59 glycoprotein were down secreted according to the groups CG>GP>PP. In contrast, apolipoprotein A, fibrinogen, and haptoglobin were up secreted in patient groups. The same expression profile observed for kininogen-1, apolipoprotein D, fibrinogen, and haptoglobin was corroborated by 2DE LC-MS/MS or 2DE MALDI-TOF/TOF analyses. These 2 strategies also showed 13 differentially secreted proteins among the 3 groups.

CONCLUSIONS

The proteins kininogen-1, apolipoprotein D, fibrinogen, and haptoglobin presented similar quantitative protein profiles according to MS(E) and 2DE approaches. The latter proteins were up secreted and the former ones were down-regulated. The strategies used proved to be valuable in identifying proteins that were differentially secreted in urine from patients with RCC.

Advances in urinary proteome analysis and applications in systems biology

The urinary proteome is the focus of many studies due to the ease of urine collection and the relative proteome stability. Systems biology allows the combination of multiple omics studies, forming a link between proteomics, metabolomics, genomics and transcriptomics. In-depth data interpretation is achieved by bioinformatics analysis of -omics data sets. It is expected that the contribution of systems biology to the study of the urinary proteome will offer novel insights. The main focus of this review is on technical aspects of proteomics studies, available tools for systems biology analysis and the application of urinary proteomics in clinical studies and systems biology.

State-of-the-art nanoplatform-integrated MALDI-MS impacting resolutions in urinary proteomics

Urine proteomics has become a subject of interest, since it has led to a number of breakthroughs in disease diagnostics. Urine contains information not only from the kidney and the urinary tract but also from other organs, thus urinary proteome analysis allows for identification of biomarkers for both urogenital and systemic diseases. The following review gives a brief overview of the analytical techniques that have been in practice for urinary proteomics. MALDI-MS technique and its current application status in this area of clinical research have been discussed. The review comments on the challenges facing the conventional MALDI-MS technique and the upgradation of this technique with the introduction of nanotechnology. This review projects nano-based techniques such as nano-MALDI-MS, surface-assisted laser desorption/ionization, and nanostructure-initiator MS as the platforms that have the potential in trafficking MALDI-MS from the lab to the bedside.

Comparative proteomic analyses of urine from rat urothelial carcinoma chemically induced by exposure to N-butyl-N-(4-hydroxybutyl)-nitrosamine

Bladder cancer is estimated to be the ninth most common malignancy with a high rate of recurrence and progression despite therapy, early diagnosis being crucial for timely intervention.

Pursuing type 1 diabetes mellitus and related complications through urinary proteomics

Diabetes mellitus is a chronic metabolic disease with multiple complications, and its successful management requires early diagnosis, to allow timely interventions. Here, we have comprehensively analyzed the proteome changes in urine of type 1 diabetic subjects with and without complications such as retinopathy and nephropathy. gel electrophoresis combined to liquid chromatography-tandem mass spectrometry (GeLC-MS/MS) analysis of midstream urine highlighted the mechanisms involved in disease pathogenesis as, for instance wound healing and blood coagulation in all diabetics or altered ganglioside metabolism in retinopathy, and also some urinary proteins with potential diagnosis value. From these, gelsolin and antithrombin-III appear as promising diagnosis markers for type 1 diabetes mellitus (T1DM), whereas ephrin type-B receptor 4 and vitamin K-dependent protein Z seem to be promising markers for advanced T1DM disease state presenting retinopathy and nephropathy (T1DM-R + N). Data also suggest urinary ganglioside GM2 activator and beta-hexosaminidase subunit beta as potential urinary markers of retinopathy in diabetics. Taken together, the present exploratory urinary proteomic analysis might be seen as an important starting point for studies targeting specific urinary proteins aimed at the implementation of new biomarkers for the early detection of T1DM-related microvascular complications.

Proteomics for breast cancer urine biomarkers

Although the survival of breast cancer (BC) patients has increased over the last two decades due to improved screening programs and postoperative adjuvant systemic therapies, many patients die from metastatic relapse. Current biomarkers used in the clinic are not useful for the early detection of BC, or monitoring its progression, and have limited value in predicting response to treatment. The development of proteomic techniques has sparked new searches for novel protein markers for many diseases including BC. Proteomic techniques allow for a high-throughput analysis of samples with the visualization and quantification of thousands of potential protein and peptide markers. Human urine is one of the most interesting and useful biofluids for routine testing and provides an excellent resource for the discovery of novel biomarkers, with the advantage over tissue biopsy samples due to the ease and less invasive nature of collection. In this review, we summarize the results from studies where urine was used as a source for BC biomarker research and discuss urine sample preparation, its advantage, challenges, and limitation. We focus on the gel-based proteomic approaches as well as the recent development of quantitative techniques in BC urine biomarker detection. Finally, the future use of modern proteomic techniques in BC biomarker identification will be discussed.

Proteome-base biomarkers in diabetes mellitus: progress on biofluids' protein profiling using mass spectrometry

The worldwide number of individuals suffering from diabetes mellitus (DM) has been projected to rise from 171 million in 2000 to 366 million in 2030. Identification of specific biomarkers for prediction and monitoring of DM is needed not only for the adequate screening diagnosis but also to assist the design of interventions to prevent or delay progression of this pathology and its attendant complications. Proteomic methods based on MS hold special promise for the identification of novel biomarkers that might form the foundation for new clinical tests, but to date, their contribution has been somehow unfruitful. Indeed, from more than 300 proteins found differently modulated in body fluids from diabetic patients, approximately 50 were validated with other approaches like ELISA or Western blotting and the clinical trials are being initiated to employ biofluids' proteomics (specifically urinary proteomics) in clinical decision. This review provides an overview of MS-based applications in the identification of potential biomarkers for DM, emphasizing the methodological challenges involved.

Screening for urinary biomarkers of steroid-resistant nephrotic syndrome in children

The present study aimed to screen for urinary biomarkers of steroid-resistant nephrotic syndrome (SRNS) in children. These biomarkers were divided into three groups, the control, the steroid-sensitive nephrotic syndrome (SSNS) and the SRNS groups, which were composed of 45, 32 and 9 children, respectively. Urine samples were obtained and analyzed using Au-chips. Compared with the control group, the peak intensities of four proteins, measured using mass-to-charge ratios, were significantly increased in the primary nephrotic syndrome (PNS; SSNS and SRNS combined) group (P<0.01). The intensity of three and one peaks increased significantly in the SSNS and SRNS groups, respectively, compared with the control (P<0.01). Compared with the SRNS group, the intensity of one protein peak increased in the SSNS group (P<0.01). The diagnostic model was established based on these four protein peaks. The sensitivity and specificity of the model were 88.89 and 93.75%, respectively. Four differentially expressed proteins may consequently serve as urinary biomarkers for SRNS in children.

Proteomic candidate biomarkers of drug-induced nephrotoxicity in the rat

Improved biomarkers of acute nephrotoxicity are coveted by the drug development industry, regulatory agencies, and clinicians. In an effort to identify such biomarkers, urinary peptide profiles of rats treated with two different nephrotoxins were investigated. 493 marker candidates were defined that showed a significant response to cis-platin comparing a cis-platin treated cohort to controls. Next, urine samples from rats that received three consecutive daily doses of 150 or 300 mg/kg gentamicin were examined. 557 potential biomarkers were initially identified; 108 of these gentamicin-response markers showed a clear temporal response to treatment. 39 of the cisplatin-response markers also displayed a clear response to gentamicin. Of the combined 147 peptides, 101 were similarly regulated by gentamicin or cis-platin and 54 could be identified by tandem mass spectrometry. Most were collagen type I and type III fragments up-regulated in response to gentamicin treatment. Based on these peptides, classification models were generated and validated in a longitudinal study. In agreement with histopathology, the observed changes in classification scores were transient, initiated after the first dose, and generally persistent over a period of 10–20 days before returning to control levels. The data support the hypothesis that gentamicin-induced renal toxicity up-regulates protease activity, resulting in an increase in several specific urinary collagen fragments. Urinary proteomic biomarkers identified here, especially those common to both nephrotoxins, may serve as a valuable tool to investigate potential new drug candidates for the risk of nephrotoxicity.

Analysis of urinary proteomic patterns for type 2 diabetic nephropathy by ProteinChip

OBJECTIVE

To detect urinary proteomic profiling of patients with type 2 diabetes by using ProteinChip array technology, for searching new potential biomarkers in early diagnosis of type 2 diabetic nephropathy (T2DN).

METHODS

A total of 95 urine samples from type 2 diabetic patients with normoalbuminuria (DM, n=30), microalbuminuria (DNl, n=25) and macroalbuminuria (DN2, n=20), and healthy controls (n=20) were analyzed by SELDI-TOF-MS (the surface-enhanced laser desorption/ionization time-of-flight mass spectrometry) technology combined with bioinformatics tools.

RESULTS

Over 300 proteins or peptides from 1 to 80 kDa were obtained using ProteinChip. About 40 of them with the m/z values from 2008.78 to 79176.55 Da were significantly differentiated between type 2 diabetic patients and control subjects. Four proteins of mass 2797.03, 4545.77, 4984.03 and 9083.71 Da were selected as the potential biomarkers for T2DN with sensitivity of 88% and specificity of 96.7%.

CONCLUSION

ProteinChip technology can help to discover new biomarkers and provide a novel non-invasive tool to early diagnosis of T2DN.

Proteomic analysis of acute kidney injury: biomarkers to mechanisms

Acute kidney injury (AKI) is a devastating clinical condition, both in terms of mortality and costs, and is occurring with increasing incidence. Despite better clinical care, the outcomes of AKI have changed little in the last 50 years. This lack of progress is due in part to a lack of early diagnostic biomarkers and a poor understanding of the disease mechanisms. This review will focus on the rapid progress being made in both the understanding of AKI and the promising panel of early biomarkers for AKI that have come out of both direct proteomic analysis of body fluids of AKI patients and more targeted proteomic approaches using clues from other methods such as transcriptomics. This review concludes with a discussion of the future of proteomics and personalized medicine in AKI and the challenges presented in translating these exciting proteomic results to the clinic.

[Biomarkers in lupus nephritis]

Systemic lupus erythematosus is a polysystemic autoimmune disease. One of the most common and serious complication is lupus nephritis. Notification of these complications before organic disorder, prediction of flares, starting aggressive therapy as early as possible, and the follow-up of successful treatment would be desirable. There is an intensive need for identifying the best biomarker for monitoring flare activity. The goal of this review is to present not only the most frequently ordered serologic tests, but the latest, partly experimental biomarkers reflecting flares, which are not used in clinical practice. Biomarkers used specifically in lupus nephritis are also described.