TITLE

Identification of Protein Biomarkers in Dupuytren's Contracture using Surface Enhanced Laser Desorption Ionization Time-of-Flight Mass Spectrometry (SELDI-TOF-MS)

AUTHOR(S)
O'Gorman, David; Howard, Jeffrey C.; Varallo, Vincenzo M.; Cadieux, Peter; Bowley, Erin; McLean, Kris; Pak, Brian J.; Bing Siang Gan
PUB. DATE
June 2006
SOURCE
Clinical & Investigative Medicine;Jun2006, Vol. 29 Issue 3, p136
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
Background: To study the protein expression profiles associated with Dupuytren's contracture (DC) to identify potential disease protein biomarkers (PBM) using a proteomic technology - Surface Enhanced Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (SELDI-TOF-MS). Methods: Normal and disease palmar fascia from DC patients were analyzed using Ciphergen's SELDI-TOF-MS Protein Biological System II (PBSII) ProteinChip® reader. Analysis of the resulting SELDI-TOF spectra was carried out using the peak cluster analysis program (BioMarker Wizard, Ciphergen). Common peak clusters were then filtered using a bootstrap algorithm called SAM (Significant Analysis of Microarrays) for increased fidelity in our analysis. Results: Several differentially expressed low molecular weight (<20 kDa) tissue proteins were identified. Spectra generated using both ZipTipC18 aided Au array and WCX2 array based SELDI-TOF-MS were reproducible, with an average peak cluster mass standard deviation for both methods of <1.74 ×10-4. Initial peak cluster analysis of the SELDI spectra identified both up-(14) and down-(3)regulated proteins associated with DC. Further analysis of the peak cluster data using the bootstrap algorithm SAM identified three disease-associated protein features (4600.8 Da, 10254.5 Da, and 11405.1 Da) that were elevated (5.45, 11.7, and 4.28 fold, respectively, with a 0% median false discovery rate). Conclusion: SELDI-TOF-MS identified three potential low molecular weight tissue protein markers (p4.6DC, p10DC, p11.7DC) for DC. The ability of SELDI-TOF-MS to resolve low molecular weight proteins suggests that the method may provide a means of deciphering the biomarker-rich low molecular weight region of the human proteome. Application of such novel technology may help clinicians to focus on specific molecular abnormalities in diseases with no known molecular pathogenesis, and uncover therapeutic and/or diagnostic targets.
ACCESSION #
21118504

 

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