title: Molecular classification of liver cirrhosis in a rat model by proteomics and bioinformatics.
abstract: Liver cirrhosis is a worldwide health problem. Reliable, noninvasive methods for early detection of liver cirrhosis are not available. 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.
authors.affiliation: Medical Proteomics and Bioanalysis Section, Genome Institute of Singapore, Singapore.
authors.forename: Xiu-Qin
authors.initials: XQ
authors.lastname: Xu
authors.forename: Chon K
authors.initials: CK
authors.lastname: Leow
authors.forename: Xin
authors.initials: X
authors.lastname: Lu
authors.forename: Xuegong
authors.initials: X
authors.lastname: Zhang
authors.forename: Jun S
authors.initials: JS
authors.lastname: Liu
authors.forename: Wing-Hung
authors.initials: WH
authors.lastname: Wong
authors.forename: Arndt
authors.initials: A
authors.lastname: Asperger
authors.forename: Sören
authors.initials: S
authors.lastname: Deininger
authors.forename: Hon-Chiu
authors.initials: HC
authors.lastname: Eastwood Leung
mesh_terms: D000465:Algorithms; D000818:Animals; D014408:Biomarkers, Tumor; D019295:Computational Biology / Q000379:methods*; D015536:Down-Regulation; D008099:Liver / Q000378:metabolism; D008103:Liver Cirrhosis / Q000378:metabolism*; D008297:Male; D010455:Peptides / Q000737:chemistry; D011506:Proteins / Q000737:chemistry; D040901:Proteomics / Q000379:methods*; D051381:Rats; D012680:Sensitivity and Specificity; D012984:Software; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization; D014357:Trypsin / Q000737:chemistry / Q000494:pharmacology; D000099053:Histidine-Rich Glycoprotein
chemical_list: D014408:Biomarkers, Tumor; D010455:Peptides; D011506:Proteins; D000099053:Histidine-Rich Glycoprotein; D014357:Trypsin