Premium
Spiking of serum specimens with exogenous reporter peptides for mass spectrometry based protease profiling as diagnostic tool
Author(s) -
Findeisen Peter,
Peccerella Teresa,
Post Stefan,
Wenz Frederik,
Neumaier Michael
Publication year - 2008
Publication title -
rapid communications in mass spectrometry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.528
H-Index - 136
eISSN - 1097-0231
pISSN - 0951-4198
DOI - 10.1002/rcm.3496
Subject(s) - proteases , chemistry , protease , mass spectrometry , chromatography , peptide , trypsin , computational biology , proteomics , biomarker discovery , biochemistry , enzyme , biology , gene
Serum is a difficult matrix for the identification of biomarkers by mass spectrometry (MS). This is due to high‐abundance proteins and their complex processing by a multitude of endogenous proteases making rigorous standardisation difficult. Here, we have investigated the use of defined exogenous reporter peptides as substrates for disease‐specific proteases with respect to improved standardisation and disease classification accuracy. A recombinant N‐terminal fragment of the Adenomatous Polyposis Coli (APC) protein was digested with trypsin to yield a peptide mixture for subsequent Reporter Peptide Spiking (RPS) of serum. Different preanalytical handling of serum samples was simulated by storage of serum samples for up to 6 h at ambient temperature, followed by RPS, further incubation under standardised conditions and testing for stability of protease‐generated MS profiles. To demonstrate the superior classification accuracy achieved by RPS, a pilot profiling experiment was performed using serum specimens from pancreatic cancer patients (n = 50) and healthy controls (n = 50). After RPS six different peak categories could be defined, two of which (categories C and D) are modulated by endogenous proteases. These latter are relevant for improved classification accuracy as shown by enhanced disease‐specific classification from 78% to 87% in unspiked and spiked samples, respectively. Peaks of these categories presented with unchanged signal intensities regardless of preanalytical conditions. The use of RPS generally improved the signal intensities of protease‐generated peptide peaks. RPS circumvents preanalytical variabilities and improves classification accuracies. Our approach will be helpful to introduce MS‐based proteomic profiling into routine laboratory testing. Copyright © 2008 John Wiley & Sons, Ltd.