Background: Non Small Cell Lung Cancer (NSCLC) is the major cause of cancer related-death. Many patients receive diagnosis at advanced stage leading to a poor prognosis. At present, no satisfactory screening tests are available in clinical practice and the discovery and validation of new biomarkers is mandatory. Surface Enhanced Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (SELDI-ToF-MS) is a recent high-throughput technique used to detect new tumour markers. In this study we performed SELDI-ToF-MS analysis on serum samples treated with the ProteoMiner™ kit, a combinatorial library of hexapeptide ligands coupled to beads, to reduce the wide dynamic range of protein concentration in the sample. Serum from 44 NSCLC patients and 19 healthy controls were analyzed with IMAC30-Cu and H50 ProteinChip Arrays.
Results: Comparing SELDI-ToF-MS protein profiles of NSCLC patients and healthy controls, 28 protein peaks were found significantly different (p < 0.05), and were used as predictors to build decision classification trees. This statistical analysis selected 10 protein peaks in the low-mass range (2-24 kDa) and 6 in the high-mass range (40-80 kDa). The classification models for the low-mass range had a sensitivity and specificity of 70.45% (31/44) and 68.42% (13/19) for IMAC30-Cu, and 72.73% (32/44) and 73.68% (14/19) for H50 ProteinChip Arrays.
Conclusions: These preliminary results suggest that SELDI-ToF-MS protein profiling of serum samples pretreated with ProteoMiner™ can improve the discovery of protein peaks differentially expressed between NSCLC patients and healthy subjects, useful to build classification algorithms with high sensitivity and specificity. However, identification of the significantly different protein peaks needs further study in order to provide a better understanding of the biological nature of these potential biomarkers and their role in the underlying disease process.