title: Serum peptidome patterns of hepatocellular carcinoma based on magnetic bead separation and mass spectrometry analysis.
abstract: BACKGROUND
  Hepatocellular carcinoma (HCC) is one of the most common cancers in the world,and the identification of biomarkers for the early detection is a relevant target. The purpose of the study is to discover specific low molecular weight (LMW) serum peptidome biomarkers and establish a diagnostic pattern for HCC.
  
  
  METHODS
  We undertook this pilot study using a combined application of magnetic beads with Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) technique and ClinPro Tools v2.2 to detect 32 patients with HCC, 16 patients with chronic hepatitis (CH), 16 patients with liver cirrhosis (LC) and 16 healthy volunteers.
  
  
  RESULTS
  The results showed 49, 33 and 37 differential peptide peaks respectively appeared in HCC, LC and CH groups. A Supervised Neural Network (SNN) algorithm was used to set up the classification model. Eleven of the identified peaks at m/z 5247.62, 7637.05, 1450.87, 4054.21, 1073.37, 3883.64, 5064.37, 4644.96, 5805.51, 1866.47 and 6579.6 were used to construct the peptides patterns. According to the model, we could clearly distinguish between HCC patients and healthy controls as well as between LC or CH patients and healthy controls.
  
  
  CONCLUSIONS
  The study demonstrated that a combined application of magnetic beads with MALDI-TOF MB technique was suitable for identification of potential serum biomarkers for HCC and it is a promising way to establish a diagnostic pattern.
  The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1503629821958720.
authors.affiliation: Department of Medical Oncology, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shannxi, PR China.
authors.forename: Xia
authors.initials: X
authors.lastname: Ying
authors.forename: Su-xia
authors.initials: SX
authors.lastname: Han
authors.forename: Jun-lan
authors.initials: JL
authors.lastname: Wang
authors.forename: Xia
authors.initials: X
authors.lastname: Zhou
authors.forename: Gui-hua
authors.initials: GH
authors.lastname: Jin
authors.forename: Long
authors.initials: L
authors.lastname: Jin
authors.forename: Hao
authors.initials: H
authors.lastname: Wang
authors.forename: Lei
authors.initials: L
authors.lastname: Wu
authors.forename: Jianying
authors.initials: J
authors.lastname: Zhang
authors.forename: Qing
authors.initials: Q
authors.lastname: Zhu
mesh_terms: D000465:Algorithms; D014408:Biomarkers, Tumor / Q000097:blood*; D006528:Carcinoma, Hepatocellular / Q000097:blood*; D016022:Case-Control Studies; D003937:Diagnosis, Differential; D006521:Hepatitis, Chronic / Q000097:blood; D006801:Humans; D018189:Immunomagnetic Separation; D008103:Liver Cirrhosis / Q000097:blood; D008113:Liver Neoplasms / Q000097:blood*; D008970:Molecular Weight; D010865:Pilot Projects; D011237:Predictive Value of Tests; D040901:Proteomics / Q000379:methods*; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization
chemical_list: D014408:Biomarkers, Tumor
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