Purpose: Urine proteomics is emerging as a powerful tool for biomarker discovery. The purpose of this study is the development of a well-characterized ''real life'' sample that can be used as reference standard in urine clinical proteomics studies. Experimental design: We report on the generation of male and female urine samples that are extensively characterized by different platforms and methods (CE-MS, LC-MS, LC-MS/MS, 1-D gel analysis in combination with nano-LC MS/MS (using LTQ-FT ultra), and 2-DE-MS) for their proteome and peptidome. In several cases analysis involved a definition of the actual biochemical entities, i.e. proteins/peptides associated with molecular mass and detected PTMs and the relative abundance of these compounds. Results: The combination of different technologies allowed coverage of a wide mass range revealing the advantages and complementarities of the different technologies. Application of these samples in ''inter-laboratory'' and ''inter-platform'' data comparison is also demonstrated. Conclusions and clinical relevance: These well-characterized urine samples are freely available upon request to enable data comparison especially in the context of biomarker discovery and validation studies. It is also expected that they will provide the basis for the comprehensive characterization of the urinary proteome.

Of the most important clinical needs for bladder cancer (BC) management is the identification of biomarkers for disease aggressiveness. Urine is a "gold mine" for biomarker discovery, nevertheless, with multiple proteins being in low amounts, urine proteomics becomes challenging. In the present study we applied a fractionation strategy of urinary proteins based on the use of immobilized metal affinity chromatography for the discovery of biomarkers for aggressive BC. Urine samples from patients with non invasive (two pools) and invasive (two pools) BC were subjected to immobilized metal affinity chromatography fractionation and eluted Bladder cancer (BC) 1 is the second in incidence and mortality cancer of the genitourinary system (1) and estimated to be the ninth most common malignancy (2). It is associated with a high recurrence rate underscoring the need for continuous surveillance following initial treatment. Cystoscopy still remains the gold standard for diagnosis and follow-up monitoring of bladder cancer. However, it is an invasive and unpleasant procedure, rendering particularly the regular surveillance program (e.g. cystoscopy every three months for the first year following initial diagnosis) not well accepted by the patients (3, 4). Urine Cytology is a noninvasive current detection tool for BC, suffering however from suboptimal sensitivity, especially for low grade tumors and being subjected to interobserver variability (5). The invasive nature of cystoscopy and the low effectiveness of cytology have prompted the search for novel and better ways to diagnose the disease with special emphasis on the early detection of disease recurrences and/or progression.Urine is regularly used in clinical practice and yields a wealth of information about the state of an individual's health. Because it can be collected in a noninvasive way it is more accessible than plasma or serum. In addition, there is no need for trained personnel for urine collection. Urine contains cells and cellular debris, inorganic ions (K ϩ , Na ϩ , Cl Ϫ , and Ca ϩ2 ), organic molecules (urea, uric acid, and creatinine) and proteins. If renal function is normal, urinary protein content is less

Purpose: Urothelial bladder cancer presents high recurrence rates, mandating continuous monitoring via invasive cystoscopy. The development of noninvasive tests for disease diagnosis and surveillance remains an unmet clinical need. In this study, validation of two urine-based biomarker panels for detecting primary and recurrent urothelial bladder cancer was conducted.Experimental Design: Two studies (total n ¼ 1,357) were performed for detecting primary (n ¼ 721) and relapsed urothelial bladder cancer (n ¼ 636). Cystoscopy was applied for detecting urothelial bladder cancer, while patients negative for recurrence had follow-up for at least one year to exclude presence of an undetected tumor at the time of sampling. Capillary electrophoresis coupled to mass spectrometry (CE-MS) was employed for the identification of urinary peptide biomarkers. The candidate urine-based peptide biomarker panels were derived from nested cross-sectional studies in primary (n ¼ 451) and recurrent (n ¼ 425) urothelial bladder cancer.Results: Two biomarker panels were developed on the basis of 116 and 106 peptide biomarkers using support vector machine algorithms. Validation of the urine-based biomarker panels in independent validation sets, resulted in AUC values of 0.87 and 0.75 for detecting primary (n ¼ 270) and recurrent urothelial bladder cancer (n ¼ 211), respectively. At the optimal threshold, the classifier for detecting primary urothelial bladder cancer exhibited 91% sensitivity and 68% specificity, while the classifier for recurrence demonstrated 87% sensitivity and 51% specificity. Particularly for patients undergoing surveillance, improved performance was achieved when combining the urine-based panel with cytology (AUC ¼ 0.87).Conclusions: The developed urine-based peptide biomarker panel for detecting primary urothelial bladder cancer exhibits good performance. Combination of the urine-based panel and cytology resulted in improved performance for detecting disease recurrence.

A.He. performed experiments and analyzed data. L.B. generated and provided critical reagents. T.S. and A.Ts assisted with mRNAseq and ATAC-seq data analysis, interpretation and T.S. generated figures. J.Z. and A.Te. performed and analyzed the targeted proteomics experiments. V.K., P.G. and M.B. contributed in data analysis and interpretation. T.C. and D.B. interpreted data. P.V. designed and supervised the study, performed data analysis, and wrote the manuscript.

Phenylalanine hydroxylase (PAH) is a pterin-dependent non-heme metalloenzyme that catalyzes the oxidation of phenylalanine to tyrosine, which is the rate-limiting step in the catabolism of Phe. Chromobacterium violaceum phenylalanine hydroxylase (cPAH) has been prepared and its steady-state mechanism has been investigated. The enzyme requires iron for maximal activity. Initial rate measurements, done in the presence of the 6,7-dimethyl-5,6,7,8-tetrahydropterin (DMPH(4)) cofactor, yielded an average apparent k(cat) of 36+/-1 s(-1). The apparent K(M) values measured for the substrates DMPH(4), L-Phe, and O(2) are 44+/-7, 59+/-10, and 76+/-7 microM, respectively. Steady-state kinetic analyses using double-reciprocal plots revealed line patterns consistent with a sequential ter-bi mechanism in which L-Phe is the middle substrate in the order of binding. The occurrence of a line intersection on the double-reciprocal plot abscissa when either pterin or O(2) is saturated suggests that, prior to O(2) binding, DMPH(4) and L-Phe are in associative pre-equilibrium with cPAH. Together with an inhibition study using the oxidized cofactor, 7,8-dimethyl-6,7-dihydropterin, it is conclusive that the mechanism is fully ordered, with DMPH(4) binding the active site first, L-Phe second, and O(2) last. This represents the first conclusive steady-state mechanism for a PAH enzyme.

High resolution proteomics approaches have been successfully utilized for the comprehensive characterization of the cell proteome. However, in the case of quantitative proteomics an open question still remains, which quantification strategy is best suited for identification of biologically relevant changes, especially in clinical specimens. In this study, a thorough comparison of a label-free approach (intensity-based) and 8-plex iTRAQ was conducted as applied to the analysis of tumor tissue samples from non-muscle invasive and muscle-invasive bladder cancer. For the latter, two acquisition strategies were tested including analysis of unfractionated and fractioned iTRAQ-labeled peptides. To reduce variability, aliquots of the same protein extract were used as starting material, whereas to obtain representative results per method further sample processing and MS analysis were conducted according to routinely applied protocols. Considering only multiple-peptide identifications, LC-MS/MS analysis resulted in the identification of 910, 1092 and 332 proteins by label-free, fractionated and unfractionated iTRAQ, respectively. The label-free strategy provided higher protein sequence coverage compared to both iTRAQ experiments. Even though pre-fraction of the iTRAQ labeled peptides allowed for a higher number of identifications, this was not accompanied by a respective increase in the number of differentially expressed changes detected. Validity of the proteomics output related to protein identification and differential expression was determined by comparison to existing data in the field (Protein Atlas and published data on the disease). All methods predicted changes which to a large extent agreed with published data, with label-free providing a higher number of significant changes than iTRAQ. Conclusively, both label-free and iTRAQ (when combined to peptide fractionation) provide high proteome coverage and apparently valid predictions in terms of differential expression, nevertheless label-free provides higher sequence coverage and ultimately detects a higher number of differentially expressed proteins. The risk for receiving false associations still exists, particularly when analyzing highly heterogeneous biological samples, raising the need for the analysis of higher sample numbers and/or application of adjustment for multiple testing.

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