Detection of serum protein biomarkers by surface enhanced laser desorption/ionization in patients with adenocarcinoma of the lung

Aim 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. Methods 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. Results The software identified 102 peaks and m/z 14022.9 and m/z 3735.99 was used to construct a classification tree. The classification tree effectively separated adenocarcinoma of lung patients from healthy controls, achieving a validity of 100%. The blind test challenged the model with a sensitivity of 100% and a specificity of 100%. Conclusion The results suggested that the SELDI-TOF-MS technique can correctly distinguish adenocarcinoma of lung patients from healthy controls and showed great potential for development as a screening test for the detection of lung cancer.