RESUMEN
<p><b>OBJECTIVE</b>To identify potential serum biomarkers that could be used to discriminate lung cancers from normal.</p><p><b>METHODS</b>Proteomic spectra of twenty-eight serum samples from patients with non-small cell lung cancer and twelve from normal individuals were generated by SELDI (Surfaced Enhanced Laser Desorption/Ionization) Mass Spectrometry. Anion-exchange columns were used to fractionate the sera into 6 designated pH groups. Two different types of protein chip arrays, IMAC-Cu and WCX2, were employed. Samples were examined in PBSII Protein Chip Reader (Ciphergen Biosystem Inc) and the discriminatory profiling between cancer and normal samples was analyzed with Biomarker Pattern software.</p><p><b>RESULTS</b>Five distinct potential lung cancer biomarkers with higher sensitivity and specificity were found, with four common biomarkers in both IMAC-Cu and WCX2 chip; the remaining biomarker occurred only in WCX2 chip. Two biomarkers were up-regulated while three biomarkers were down-regulated in the serum samples from patients with non-small cell lung cancer. The sensitivities provided by the individual biomarkers were 75%-96.43% and specificities were 75%-100%.</p><p><b>CONCLUSIONS</b>The preliminary results suggest that serum is a capable resource for detecting specific non-small cell lung cancer biomarkers. SELDI mass spectrometry is a useful tool for the detection and identification of new potential biomarker of non-small cell lung cancer in serum.</p>