A preliminary analysis of non-small cell lung cancer biomarkers in serum.

Objective: To identify potential serum biomarkers that could be used to discriminate lung cancers from normal.

Methods: 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.

Results: 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%.

Conclusions: 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.