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Early diagnosis of lung cancer is important for successful treatment and improving the outcome of patients. We explored novel tools for screening serum biomarkers to distinguish adenocarcinoma of the lung from healthy controls by serum protein profiles.
Serum samples were taken from 31 patients with adenocarcinoma of the lung and 31 healthy controls, matched for age, sex and smoking status. Serum samples were applied to strong anion 2(SAX-2) protein chips to generate mass spectra by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS). Protein peak identification and clustering were performed using Biomarker Wizard, compared by MATLAB 7.5 and a classification tree was constructed using R weka software. The validity of the classification tree was then challenged with a blind test.