ABSTRACT
Objective To investigate the serum proteomic patterns in lung cancer by surface enhanced laser desorption/ionization-time of flight-mass spectrometry (SELDI-TOF-MS) techniques and build diagnostic models in order to evaluate their clinical significance by biomarkers screening in lung cancer.Methods SELDI-TOF-MS and CM-10 protein chip were used to detect the serum proteomic patterns of 38 lung squamous cell carcinoma and 30 lung adenocarcinomas,including the comparation in 34 geminate patient serums before and after surgery.Nagative control setted as a group of 50 normal tissues.BioMarker Wizard and BioMarker pattern system software were used in combination to analyze the data and to develop diagnostic models.Results Two protein peaks from a total of 167 were chosen as a biomarker pattern in the training set.Two protein peaks pattern (mass/charge ratio [m/z] 6 010,5 330) was observed in the model that could be used as to distinguish lung cancer from non-cancerous diseases.It yielded a sensitivity of 98 ％ and a specificity of 96 ％.There were 9 different protein peaks (P ＜ 0.05) between pre-surgery and post-surgery.There were 8 different peaks (P ＜ 0.05) between metastasis and non-metastasis.Conclusion SELDI techniques can be employed as diagnosis in lung cancer patients with relatively high sensitivity and specificity,and also could be used as an effective tool for the screening of lung cancer.