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Abstract: Serum proteome investigations have raised an incredible interest in the research of novel molecular biomarker, nevertheless few of the proposed evidences have been translated to the clinical practice. One of the limiting factors has been the lack of generally accepted guidelines for clinical proteomics studies and the lack of a robust analytical and pre-analytical ground for the proposed classification models. Pre-analytical issues may results in a deep impact for biomarker discovery campaign. In this study we present a systematic evaluation of sample storage and sampling conditions for clinical proteomics investigations. We have developed and validated a linear MALDI-TOF-MS protein profiling method to explore the low protein molecular weight region (5–20kDa) of serum samples. Data normalization and processing was performed using optimise peak detection routine (LIMPIC) able to describe each group under investigation. Data were acquired either from healthy volunteers and from multiple sclerosis patients in order to highlight ex vivo protein profile alteration related to different physio-pathological conditions. Our data showed critical conditions for serum protein profiles depending on storage times and temperatures: 23°C, 4°C, −20°C and −80°C. We demonstrated that upon a −20°C short term storage, characteristic degradation profiles are associated with different clinical groups. Protein signals were further identified after preparative HPLC separation by peptide sequencing on a nanoLC-Q-TOF TANDEM mass spectrometer. Apolipoprotein A-IV and complement C3 protein fragments, transthyretin and the oxidized isoforms in different apolipoprotein species represent the major molecular features of such a degradation pattern. [Copyright &y& Elsevier]

In order to effectively develop personalized medicine for kidney diseases we urgently need to develop highly accurate biomarkers for use in the clinic, since current biomarkers of kidney damage (changes in serum creatinine and/or urine albumin excretion) apply to a later stage of disease, lack accuracy, and are not connected with molecular pathophysiology. Analysis of urine peptide content (urinary peptidomics) has emerged as one of the most attractive areas in disease biomarker discovery. Urinary peptidome analysis allows the detection of short and long-term physiological or pathological changes occurring within the kidney. Urinary peptidomics has been applied extensively for several years now in renal patients, and may greatly improve kidney disease management by supporting earlier and more accurate detection, prognostic assessment, and prediction of response to treatment. It also promises better understanding of kidney disease pathophysiology, and has been proposed as a "liquid biopsy" to discriminate various types of renal disorders. Furthermore, proteins being the major drug targets, peptidome analysis may allow one to evaluate the effects of therapies at the protein signaling pathway level. We here review the most recent findings on urinary peptidomics in the setting of the most common kidney diseases. [ABSTRACT FROM AUTHOR]