OBJECTIVE: To screen biomarkers for classification in lung adenocarcinoma and lung squamous carcinoma by using laser capture microdissection (LCM) and surface-enhanced laser desorption ionization time-of-flight mass spectrometry (SELDI-TOF-MS) and support vector machine (SVM). METHODS: Six specimens of lung adenocarcinoma tissues and seven specimens of lung squamous carcinoma tissues obtained during operation were made into frozen sections and stained by improved H-E solution. About 1.2 x 10(5) of homogeneous adenocarcinoma cells and 1.4 x 10(5) of homogeneous lung squamous carcinoma cells were collected using LCM. Then SELDI profiles based on PBS II(+)SELDI-TOF-MS (IMAC protein chip) and the data were analyzed by support vector machine (SVM). RESULTS: Eighty seven differential protein peaks were found and top ten of them were identified as candidate biomarkers. The expression levels of 6 proteins among them with the molecular weights of 3333, 3592, 3848, 5036, 5191, and 5211 respectively in the lung squamous cancer tissues were weaker than those in the adenocarcinoma tissues, and the expression levels of 4 proteins with the molecular weights of 2505, 4004, 4847, and 11 412 in the lung squamous carcinoma tissues were stronger than those in the adenocarcinoma tissues. The expression of the protein with the molecular weight of 4847 in the squamous cancer was significantly stronger than that in the adenocarcinoma (p + 0.032). A discriminatory pattern consisting of 3 proteins with the molecular weights of 4847, 11 412, and 3592 was established with a sensitivity of 100% and a specificity of 100% respectively in separating adenocarcinoma from squamous carcinoma. CONCLUSION: There is a difference in protein component between adenocarcinoma and squamous carcinoma. LCM combined with SELDI-TOF-MS help screen a biomarker pattern to distinguish lung adenocarcinoma from lung squamous carcinoma with high sensitivity and specificity.