The aim of this study was to discover and identify potential protein biomarkers specific for non-small cell lung cancer (NSCLC). Two hundred and thirty five (235) Serum samples with 112 NSCLC and 123 controls were randomly divided into a training set and a blind testing set. Serum proteomic profiles were analyzed using surface-enhanced laser desorption/ionization time-of-flight mass spectroscopy (SELDI-TOF-MS). Candidate protein biomarkers were purified by high Performance Liquid Chromatography (HPLC) and identified by liquid chromatography tandem mass spectrometry (LC-MS/MS) and validated using ProteinChip immunoassays. A total of 3 peaks (m/z with 6628, 9191 and 11412 Da) were screened out by SVM to construct the classification model with the high discriminatory power in the training set. The sensitivity and specificity of the model were 96.56% and 94.79% respectively in the blind testing set. The candidate biomarker with m/z of 6628 Da was found down-regulated in NSCLC patients, and identified as apolipoprotein C-I. Another two candidate biomarkers (9191 and 11412 Da) were found up-regulated in serum of NSCLC patients and identified as haptoglobin alpha-1 chain and S100A4, respectively. We have identified a set of biomarkers that could discriminate NSCLC from non-cancer controls. An efficient strategy, including SELDI-TOF-MS analysis, HPLC purification, MALDI-TOF-MS trace and LC-MS/MS identification, has been proved successfully.
Technology in cancer research & treatment 12/2009; 8(6):455-66. DOI:10.1177/153303460900800607 · 1.94 Impact Factor