Proteins and polypeptides play an important role in our bodies as e.g. structural elements, enzymes, inhibitors, neurotransmitters, hormones or antibiotics. A deeper insight into the functional relevance of these polypeptides under different physiological and pathophysiological conditions is one of the main challenges in proteome research [1-4]. Proteome changes, i.e. alterations in the entire set of polypeptide concentrations or modifications at a given time point under defined conditions, reflect normal biological and pathological processes.
Traditionally, biomarker discovery was hypothesis driven, hence related to extensive biochemical research to characterize pathological processes for identification of potential biomarker candidates. In contrast, the fast-paced technical advancement over the last decades, especially in mass spectrometry and computer sciences, initiated a paradigm shift into the direction of hypothesis-free multi-parametric profiling approaches for biomarker discovery. These techniques provide a patient's protein profile of a specific intra- and inter-cellular compartment under different physiological and pathophysiological conditions. With the DiaPat® urine test the analysis of the human urinary proteome for diagnostic purposes has reached a technical level with the potential to revolutionize early disease diagnosis, drug discovery, and sensitive monitoring of a response to therapeutic intervention.
Due to non-invasive sampling and high pre-analytical stability urine provides several advantages among the clinically important and available body fluids: Urine is easily and non-invasively accessible in large quantities. In addition to urinary proteins, urine contains also genitourinary secretions as potential sources of biomarkers. Sample instability is less an issue compared to other body fluids, such as serum or plasma [5-8]. Standardized protocols for urine sampling to control various pre- analytical influences, such as sampling conditions, storage, freeze-thaw cycles, bacterial interferences and handling are available .
For urinary proteomic profiling, a crude unprocessed urine sample would be ideal. However, the presence of interfering compounds, such as salts or lipids, often limits this approach. Consequently, sample preparation protocols are necessary. Reproducibility of sample preparation protocols is of utmost importance [10-12] and it is advisable to remove biological matrix and other low-molecular weight compounds in a single step when ever possible.
The enormous complexity of the urinary proteome prevents its proteomic analysis in a single mass spectrometric step without additional separation to increase overall analytical resolution. For these purposes the DiaPat® approach was developed and has been successfully applied.
The analytical platform was approved by U.S. Food and Drug Administration (FDA).
1. Ma Y, Liu G, Du M, Stayton I: Recent developments in the determination of
urinary cancer biomarkers by capillary electrophoresis.
Electrophoresis 25(10-11), 1473-1484 (2004).
2. Vlahou A, Fountoulakis M: Proteomic approaches in the search for disease
biomarkers. J. Chromatogr. B Analyt.
Technol. Biomed. Life Sci. 814(1), 11-19 (2005).
3. Kolch W, Mischak H, Pitt AR: The molecular make-up of a tumour:
proteomics in cancer research.
Clin. Sci. (Lond) 108(5), 369-383 (2005).
4. Issaq HJ: The role of separation science in proteomics research.
Electrophoresis 22(17), 3629-3638 (2001).
5. Schaub S, Wilkins J, Weiler T, Sangster K, Rush D, Nickerson P: Urine protein
profiling with surface-enhanced laser-desorption/ionization time-of-flight mass
Kidney Int. 65(1), 323-332 (2004).
6. Theodorescu D, Wittke S, Ross MM, Walden M, Conaway M, Just I, Mischak H,
Frierson HF: Discovery and validation of new protein biomarkers for urothelial
cancer: a prospective analysis.
Lancet Oncol 7(3), 230-240 (2006).
7. Fiedler GM, Baumann S, Leichtle A, Oltmann A, Kase J, Thiery J, Ceglarek U:
Standardized peptidome profiling of human urine by magnetic bead separation
and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry.
Clin. Chem. 53(3), 421-428 (2007).
8. von Zur Muhlen C., Schiffer E, Zuerbig P, Kellmann M, Brasse M, Meert N, Vanholder
RC, Dominiczak AF, Chen YC, Mischak H, Bode C, Peter K: Evaluation of Urine
Proteome Pattern Analysis for Its Potential To Reflect Coronary Artery
Atherosclerosis in Symptomatic Patients. J.
Proteome. Res. 8(1), 335-345 (2009).
9. Mischak H, Apweiler R, Banks RE, Conaway M, Coon JJ, Dominizak A, Ehrich JH, Fliser
D, Girolami M, Hermjakob H, Hochstrasser DF, Jankowski V, Julian BA, Kolch W,
Massy Z, Neususs C, Novak J, Peter K, Rossing K, Schanstra JP, Semmes OJ,
Theodorescu D, Thongboonkerd V, Weissinger EM, Van Eyk JE, Yamamoto T:
Clinical Proteomics: a need to define the field and to begin to set adequate
J Proteomics Clin. Appl. 1), 148-156 (2007).
10. Petricoin EF, Ardekani AM, Hitt BA, Levine PJ, Fusaro VA, Steinberg SM, Mills GB,
Simone C, Fishman DA, Kohn EC, Liotta LA: Use of proteomic patterns in serum
to identify ovarian cancer.
Lancet 359(9306), 572-577 (2002).
11. Alaiya A, Al-Mohanna M, Linder S: Clinical cancer proteomics: promises and
Proteome Res. 4(4), 1213-1222 (2005).
12. Rifai N, Gillette MA, Carr SA: Protein biomarker discovery and validation:
the long and uncertain path to clinical utility.
Nat. Biotechnol. 24(8), 971-983 (2006).