Human urine proteomics: building a list of human urine cancer biomarkers

Quantitative proteomics identifies and validates urinary biomarkers of rhabdomyosarcoma in children

BACKGROUND

Rhabdomyosarcoma (RMS) is the most common soft tissue sarcoma with poor prognosis in children. The 5-year survival rate for early RMS has improved, whereas it remains unsatisfactory for advanced patients. Urine can rapidly reflect changes in the body and identify low-abundance proteins. Early screening of tumor markers through urine in RMS allows for earlier treatment, which is associated with better outcomes.

METHODS

RMS patients under 18 years old, including those newly diagnosed and after surgery, were enrolled. Urine samples were collected at the time points of admission and after four cycles of chemotherapy during follow-up. Then, a two-stage workflow was established. (1) In the discovery stage, differential proteins (DPs) were initially identified in 43 RMS patients and 12 healthy controls (HCs) using a data-independent acquisition method. (2) In the verification stage, DPs were further verified as biomarkers in 54 RMS patients and 25 HCs using parallel reaction monitoring analysis. Furthermore, a receiver operating characteristic (ROC) curve was used to construct the protein panels for the diagnosis of RMS. Gene Ontology (GO) and Ingenuity Pathway Analysis (IPA) software were used to perform bioinformatics analysis.

RESULTS

A total of 251 proteins were significantly altered in the discovery stage, most of which were enriched in the head, neck and urogenital tract, consistent with the most common sites of RMS. The most overrepresented biological processes from GO analysis included immunity, inflammation, tumor invasion and neuronal damage. Pathways engaging the identified proteins revealed 33 common pathways, including WNT/β-catenin signaling and PI3K/AKT signaling. Finally, 39 proteins were confirmed as urinary biomarkers for RMS, and a diagnostic panel composed of 5 candidate proteins (EPS8L2, SPARC, HLA-DRB1, ACAN, and CILP) was constructed for the early screening of RMS (AUC: 0.79, 95%CI = 0.66 ~ 0.92).

CONCLUSIONS

These findings provide novel biomarkers in urine that are easy to translate into clinical diagnosis of RMS and illustrate the value of global and targeted urine proteomics to identify and qualify candidate biomarkers for noninvasive molecular diagnosis.

Noninvasive urinary protein signatures associated with colorectal cancer diagnosis and metastasis

Currently, imaging, fecal immunochemical tests (FITs) and serum carcinoembryonic antigen (CEA) tests are not adequate for the early detection and evaluation of metastasis and recurrence in colorectal cancer (CRC). To comprehensively identify and validate more accurate noninvasive biomarkers in urine, we implement a staged discovery-verification-validation pipeline in 657 urine and 993 tissue samples from healthy controls and CRC patients with a distinct metastatic risk. The generated diagnostic signature combined with the FIT test reveals a significantly increased sensitivity (+21.2% in the training set, +43.7% in the validation set) compared to FIT alone. Moreover, the generated metastatic signature for risk stratification correctly predicts over 50% of CEA-negative metastatic patients. The tissue validation shows that elevated urinary protein biomarkers reflect their alterations in tissue. Here, we show promising urinary protein signatures and provide potential interventional targets to reliably detect CRC, although further multi-center external validation is needed to generalize the findings.

More sensitive and specific non-invasive biomarkers are desired for early detection of cancer. Here, the authors show a protein signature in the urine that increases sensitivity for colorectal cancer detection when combined with fecal immunochemical tests and corrects diagnosis in some fecal immunochemical tests-negative patients.

An enzyme immunoassay for determining albumin in human urine samples using an ultra-microanalytical system

Microalbuminuria is a term to describe a moderate increase in the level of albumin in urine. It is an important prognostic marker for kidney damage in diseases such as diabetes mellitus and hypertension. A simple sandwich-type ultramicroELISA assay (UMELISA) has been developed for the measurement of albumin in human urine samples. Strips coated with a high affinity monoclonal antibody directed against albumin are used as solid phase, to ensure the specificity of the assay. The albumin assay was completed in 1 hr and 30 min, with a measuring range of 1.44-200 ng/mL. The intra- and inter-assay coefficients of variation were 3.98-4.35% and 7.59-8.92%, respectively, depending on the albumin concentrations evaluated. Percentage recovery ranged from 94.26 to 98.50%. Regression analysis showed a good correlation with the commercial quantitative turbidimetric test Microalbumin-turbilatex (n = 240, r = 0.994, p < .01). The analytical performance characteristics of our UMELISA MICROALBUMINA endorse its use for the quantification of albumin in human urine samples. This test will make a cost-effective diagnostic kit accessible to low-income countries such as Latin American countries and is now available in the Cuban Public Health System.

Disparities in prostate cancer incidence and mortality rates: Solvable or not?

Prostate cancer (PCa) is recognized as a disease possessing not only great variation in its geographic and racial distribution but also tremendous variation in its potential to cause morbidity and death and it, therefore, ought not to be considered a homogenous disease entity. Morbidity and death from PCa are disproportionately higher in men of African ancestry (MAA) who are generally observed to have more aggressive disease and worse outcomes following treatment compared to men of European ancestry (MEA). The higher rates of PCa among MAA relative to MEA appear to be multifactorial and related to inherent differences in biological aggressiveness; a continued lack of awareness of the disease and methods of prevention; a lower prevalence of screen-detected PCa; comparatively lower access to quality healthcare as well as systemic and institutionalized disparities in the administration of optimal care to MAA in developed countries such as the United States of America where high-quality care is available. Even when access to quality healthcare is assured in equal access settings, it appears that MAA still have worse outcomes after PCa treatment stage-for-stage and grade-for-grade compared to MEA, suggesting that, inherent racial, ethnic and biological differences are paramount in predicting poor outcomes. This review has explored the different contributing factors to the current disparities in PCa incidence and mortality rates with emphasis on the incongruence in how research has been conducted in understanding the disease towards developing therapies.

Significance of detection of urinary cathepsin D in patients with colorectal cancer liver metastasis

AIM: To find a more economical method for monitoring colorectal carcinoma liver metastasis by detecting whether cathepsin D can be used as a urinary biomarker of colorectal carcinoma liver metastasis.

METHODS: Random mid-stream urine samples were collected from patients with colorectal carcinoma with or without liver metastasis. The urine protein was enriched on NC membrane through pumping filtration, and Western blot was used to detect the concentration of cathepsin D after elution. Urine creatine was used to normalise the result.

RESULTS: The enriched protein showed a good quality and Western blot results indicated that the concentration of cathepsin D in urine of patients with colorectal carcinoma liver metastasis was significantly higher than those of healthy controls and CRC patients without metastasis.

CONCLUSION: The method of urine protein enrichment allows to obtain high quality urine protein quickly, and urinary cathepsin D may serve as a potential biomarker of colorectal carcinoma liver metastasis.

Advances in urinary protein biomarkers for urogenital and non-urogenital pathologies

The discovery of protein biomarkers that reflect the biological state of the body is of vital importance to disease management. Urine is an ideal source of biomarkers that provides a non-invasive approach to diagnosis, prognosis and prediction of diseases. Consequently, the study of the human urinary proteome has increased dramatically over the last 10 years, with many studies being published. This review focuses on urinary protein biomarkers that have shown potential, in initial studies, for diseases affecting the urogenital tract, specifically chronic kidney disease and prostate cancer, as well as other non-urogenital pathologies such as breast cancer, diabetes, atherosclerosis and osteoarthritis. PubMed was searched for peer-reviewed literature on the subject, published in the last 10 years. The keywords used were "urine, biomarker, protein, and/or prostate cancer/breast cancer/chronic kidney disease/diabetes/atherosclerosis/osteoarthritis". Original studies on the subject, as well as a small number of reviews, were analysed including the strengths and weaknesses, and we summarized the performance of biomarkers that demonstrated potential. One of the biggest challenges found is that biomarkers are often shared by several pathologies so are not specific to one disease. Therefore, the trend is shifting towards implementing a panel of biomarkers, which may increase specificity. Although there have been many advances in urinary proteomics, these have not resulted in similar advancements in clinical practice due to high costs and the lack of large data sets. In order to translate these potential biomarkers to clinical practice, vigorous validation is needed, with input from industry or large collaborative studies.

Facile synthesis of magnetic mesoporous hollow carbon microspheres for rapid capture of low-concentration peptides

Mesoporous and hollow carbon microspheres embedded with magnetic nanoparticles (denoted as MHM) were prepared via a facile self-sacrificial method for rapid capture of low-abundant peptides from complex biological samples. The morphology, structure, surface property, and magnetism were well-characterized. The hollow magnetic carbon microspheres have a saturation magnetization value of 130.2 emu g(-1) at room temperature and a Brunauer-Emmett-Teller specific surface area of 48.8 m(2) g(-1) with an average pore size of 9.2 nm for the mesoporous carbon shell. The effectiveness of these MHM affinity microspheres for capture of low-concentration peptides was evaluated by standard peptides, complex protein digests, and real biological samples. These multifunctional hollow carbon microspheres can realize rapid capture and convenient separation of low-concentration peptides. They were validated to have better performance than magnetic mesoporous silica and commercial peptide-enrichment products. In addition, they can be easily recycled and present excellent reusability. Therefore, it is expected that this work may provide a promising tool for high-throughput discovery of peptide biomarkers from biological samples for disease diagnosis and other biomedical applications.

Protein-Protein Interactions: Gene Acronym Redundancies and Current Limitations Precluding Automated Data Integration

Understanding protein interaction networks and their dynamic changes is a major challenge in modern biology. Currently, several experimental and in silico approaches allow the screening of protein interactors in a large-scale manner. Therefore, the bulk of information on protein interactions deposited in databases and peer-reviewed published literature is constantly growing. Multiple databases interfaced from user-friendly web tools recently emerged to facilitate the task of protein interaction data retrieval and data integration. Nevertheless, as we evidence in this report, despite the current efforts towards data integration, the quality of the information on protein interactions retrieved by in silico approaches is frequently incomplete and may even list false interactions. Here we point to some obstacles precluding confident data integration, with special emphasis on protein interactions, which include gene acronym redundancies and protein synonyms. Three human proteins (choline kinase, PPIase and uromodulin) and three different web-based data search engines focused on protein interaction data retrieval (PSICQUIC, DASMI and BIPS) were used to explain the potential occurrence of undesired errors that should be considered by researchers in the field. We demonstrate that, despite the recent initiatives towards data standardization, manual curation of protein interaction networks based on literature searches are still required to remove potential false positives. A three-step workflow consisting of: (i) data retrieval from multiple databases, (ii) peer-reviewed literature searches, and (iii) data curation and integration, is proposed as the best strategy to gather updated information on protein interactions. Finally, this strategy was applied to compile bona fide information on human DREAM protein interactome, which constitutes liable training datasets that can be used to improve computational predictions.

Poor histological lesions in IgA nephropathy may be reflected in blood and urine peptide profiling

Background

IgA nephropathy (IgAN) is the most common primary glomerulonephritis worldwide, leading to renal failure in 15% to 40% of cases. IgAN is diagnosed by renal biopsy, an invasive method that is not risk-free. We used blood and urine peptide profiles as a noninvasive method of linking IgAN-associated changes with histological lesions by Oxford classification.

Methods

We prospectively studied 19 patients with biopsy-proven IgAN and 14 healthy subjects from 2006 to 2009, excluding subjects with crescentic glomerulonephritis and collecting clinical and biochemical data at the time of diagnosis and during follow-up (24 months). Histological lesions were evaluated by Oxford classification. Proteomic analysis was performed by combining magnetic bead (MB) technology and mass spectrometry (MALDI-TOF MS) to obtain peptide profiles. Doubling of serum creatinine was considered a variable of poor renal prognosis.

Results

We identified 55 peptides—13 in serum, 26 in plasma, and 16 in urine—that differentiated IgAN patients from healthy subjects. A significant association was noted between serum/plasma and urine peptides and histological findings—ie, tubulointerstitial damage, segmental glomerulosclerosis, and endocapillary injury.

We also identified 3 peptides—corresponding to bradykinin, uromodulin, and alpha-1-antitrypsin—that were associated with severity of lesions, such as tubulointerstitial damage and segmental glomerulosclerosis.

Moreover, blood peptides with m/z 2953, 5337, 9287, and 9289 and urine peptides with m/z 1769, 1898, 1913, 1945, 2491, 2756, 2977, 3004, 3389, and 4752 correlated significantly with poor renal function.

Conclusions

In patients with IgAN, the use of noninvasive approaches, such as blood and urine proteomics, can provide valuable information beyond that of standard diagnostic techniques, allowing us to identify blood and urine peptide profiles that are associated with poor histological lesions in IgAN patients.

Two-dimensional SDS-PAGE fractionation of biological samples for biomarker discovery

Two-dimensional electrophoresis is still a very valuable tool in proteomics, due to its reproducibility and its ability to analyze complete proteins. However, due to its sensitivity to dynamic range issues, its most suitable use in the frame of biomarker discovery is not on very complex fluids such as plasma, but rather on more proximal, simpler fluids such as CSF, urine, or secretome samples. Here, we describe the complete workflow for the analysis of such dilute samples by two-dimensional electrophoresis, starting from sample concentration, then the two-dimensional electrophoresis step per se, ending with the protein detection by fluorescence.

Uromodulin and α(1)-antitrypsin urinary peptide analysis to differentiate glomerular kidney diseases

BACKGROUND/AIMS

Glomerular kidney disease (GKD) is suspected in patients based on proteinuria, but its diagnosis relies primarily on renal biopsy. We used urine peptide profiling as a noninvasive means to link GKD-associated changes to each glomerular entity.

METHODS

Urinary peptide profiles of 60 biopsy-proven glomerular patients and 14 controls were analyzed by combining magnetic bead peptide enrichment, MALDI-TOF MS analysis, and ClinProTools v2.0 to select differential peptides. Tentative identification of the differential peptides was carried out by HPLC-MS/MS.

RESULTS

The HPLC-MS/MS results suggest that uromodulin (UMOD; m/z: 1682, 1898 and 1913) and α(1)-antitrypsin (A1AT; m/z: 1945, 2392 and 2505) are differentially expressed urinary peptides that distinguish between GKD patients and healthy subjects. Low UMOD and high A1AT peptide abundance was observed in 80-92% of patients with GKD. Proliferative forms of GKD were distinguished from nonproliferative forms, based on a combination of UMOD and A1AT peptides. Nonproliferative forms correlated with higher A1AT peptide levels - focal segmental glomerulosclerosis was linked more closely to high levels of the m/z 1945 peptide than minimal change disease.

CONCLUSION

We describe a workflow - urinary peptide profiling coupled with histological findings - that can be used to distinguish GKD accurately and noninvasively, particularly its nonproliferative forms.

Approaches for the study of cancer: towards the integration of genomics, proteomics and metabolomics

Recent technological advances, combined with the development of bioinformatic tools, allow us to better address biological questions combining -omic approaches (i.e., genomics, metabolomics and proteomics). This novel comprehensive perspective addresses the identification, characterisation and quantitation of the whole repertoire of genes, proteins and metabolites occurring in living organisms. Here we provide an overview of recent significant advances and technologies used in genomics, metabolomics and proteomics. We also underline the importance and limits of mass accuracy in mass spectrometry-based -omics and briefly describe emerging types of fragmentation used in mass spectrometry. The range of instruments and techniques used to address the study of each -omic approach, which provide vast amounts of information (usually termed "high-throughput" technologies in the literature) is briefly discussed, including names, links and descriptions of the main databases, data repositories and resources used. Integration of multiple -omic results and procedures seems necessary. Therefore, an emerging challenge is the integration of the huge amount of data generated and the standardisation of the procedures and methods used. Functional data integration will lead to answers to unsolved questions, hopefully, applicable to clinical practice and management of patients.