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|Title:||Molecular classification of liver cirrhosis in a rat model by proteomics and bioinformatics|
Recursive support vector machine
|Citation:||Xu, X.-Q., Leow, C.K., Lu, X., Zhang, X., Liu, J.S., Wong, W.-H., Asperger, A., Deininger, S., Leung, H.-C.E. (2004-10). Molecular classification of liver cirrhosis in a rat model by proteomics and bioinformatics. Proteomics 4 (10) : 3235-3245. ScholarBank@NUS Repository. https://doi.org/10.1002/pmic.200400839|
|Abstract:||Liver cirrhosis is a worldwide health problem. Reliable, noninvasive methods for early detection of liver cirrhosis are not availabe. Using a three-step approach, we classified sera from rats with liver cirrhosis following different treatment insults. The approach consisted of: (i) protein profiling using surface-enhanced laser desorption/ionization (SELDI) technology; (ii) selection of a statistically significant serum biomarker set using machine learning algorithms; and (iii) identification of selected serum biomarkers by peptide sequencing. We generated serum protein profiles from three groups of rats: (i) normal (n = 8), (ii) thioacetamide-induced liver cirrhosis (n = 22), and (iii) bile duct ligation-induced liver fibrosis (n = 5) using a weak cation exchanger surface. Profiling data were further analyzed by a recursive support vector machine algorithm to select a panel of statistically significant biomarkers for class prediction. Sensitivity and specificity of classification using the selected protein marker set were higher than 92%. A consistently down-regulated 3495 Da protein in cirrhosis samples was one of the selected significant biomarkers. This 3495 Da protein was purified on-chip and trypsin digested. Further structural characterization of this biomarkers candidate was done by using cross-platform matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) peptide mass fingerprinting (PMF) and matrix-assisted laser desorption/ionization time of flight/time of flight (MALDI-TOF/TOF) tandem mass spectrometry (MS/MS). Combined data from PMF and MS/MS spectra of two tryptic peptides suggested that this 3495 Da protein shared homology to a histidine-rich glycoprotein. These results demonstrated a novel approach to discovery of new biomarkers for early detection of liver cirrhosis and classification of liver diseases.|
|Appears in Collections:||Staff Publications|
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