Abstract:

Objective To explore the changes of proteomic spectra from plasma of patients with lung cancer or benign lung diseases and health controls in order to establish a primary diagnosis model of lung cancer. Methods The proteomic spectra from plasma of 108 patients with lung cancer, 40 patients with benign lung diseases and 22 healthy individuals were analysed by surface-enhanced laser desorption/ionization time of flight mass spectrometry (SELDI-TOF-Ms). The best decision tree model was established by cluster analysis and principal component analysis. Then the model was blindly validated by the protein of 21 patients with lung benign diseases and 47 patients with stage I lung cancer. Results Twenty-three significantly differentially expressed protein peaks were successfully detected (P<0.001). Blinded validation suggested that the accuracy for diagnosing lung cancer was 72.06%, the sensitivity and specificity were 72.34% and 71.43%, respectively, and the positive predictive value and negative predictive value were 85.0% and 78.95%, espectively. Conclusion SELDI-TOF-Ms protein chip technology provides a new tool for the early diagnosis of lung cancer.

Key words: surface-enhanced laser desorption/ionization time of flight mass spectrometry, plasma, lung cancer,
protein array, molecular markers