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Proteomics and Protein Markers |
1 Translational Research Laboratory, Institute of Womens Health, University College London, London, United Kingdom.
2 Cancer Proteomics Group, Ludwig Institute for Cancer Research, London Branch, London, United Kingdom.
3 Department of Computer Science, Royal Holloway College, University of London, London, United Kingdom.
4 Ciphergen Biosystems, Inc., Fremont, CA.
aAddress correspondence to this author at: Translational Research Laboratory, Institute of Womens Health, University College London, Huntley Street, London, WC1E 6DH, UK. Fax 44-207-6796334; e-mail jtimms{at}ludwig.ucl.ac.uk.
Background: High-throughput proteomic methods for disease biomarker discovery in human serum are promising, but concerns exist regarding reproducibility of results and variability introduced by sample handling. This study investigated the influence of different preanalytic handling methods on surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) protein profiles of prefractionated serum. We investigated whether older collections with longer sample transit times yield useful protein profiles, and sought to establish the most feasible collection methods for future clinical proteomic studies.
Methods: To examine the effect of tube type, clotting time, transport/incubation time, temperature, and storage method on protein profiles, we used 6 different handling methods to collect sera from 25 healthy volunteers. We used a high-throughput, prefractionation strategy to generate anion-exchange fractions and examined their protein profiles on CM10, IMAC30-Cu, and H50 arrays by using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry.
Results: Prolonged transport and incubation at room temperature generated low mass peaks, resulting in distinctions among the protocols. The most and least stringent methods gave the lowest overall peak variances, indicating that proteolysis in the latter may have been nearly complete. For samples transported on ice there was little effect of clotting time, storage method, or transit time. Certain proteins (TTR, ApoCI, and transferrin) were unaffected by handling, but others (ITIH4 and hemoglobin ß) displayed significant variability.
Conclusions: Changes in preanalytical handling variables affect profiles of serum proteins, including proposed disease biomarkers. Proteomic analysis of samples from serum banks collected using less stringent protocols is applicable if all samples are handled identically.
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