Abstract: Objective To investigate the application of cluster analysis and discriminant analysis in diagnosing different pathological types of lung cancer by six kinds of tumor markers. Methods We collected 342 patients who received the first hospitalization and were finally diagnosed as lung cancer in Tumor Hospital Affiliated to Xinjiang Medical University from May 2012 to May 2013. Serum concentrations of SCC, CYFRA 21-1, CEA, CA125, Pro-GRP and NSE were assayed for every patient before any treatment. We compared the differences of the six tumor markers among SCLC, lung adenocarcinoma and lung squamous carcinoma. We clustered the six tumor marker indexes by cluster analysis, and samples of 342 cases of samples were analyzed by discriminant analysis. Results NSE and Pro-GRP levels were significantly higher in SCLC tissues than those in squamous carcinoma and lung adenocarcinoma tissues. SCC and CYFRA21-1 were obviously higher in lung squamous carcinoma tissues than those in SCLC and lung adenocarcinoma tissues; CEA and CA125 levels were significantly higher in lung adenocarcinoma tissues than those in SCLC and lung squamous carcinoma tissues. Cluster analysis showed that NSE and Pro-GRP was helpful for diagnosing SCLC, and CEA, CA125, SCC, CYFRA21-1 were beneficial in the diagnosis of NSCLC. The diagnosis coincidence rate for SCLC was 93.3% and for NSCLC was 83.0% by the discrimination function established on six tumor markers. Conclusion Cluster analysis and discriminant analysis indicate that NSE, Pro-GRP, CEA, CA125, SCC and CYFRA21-1 have certain diagnostic value in diagnosing the different pathological types of lung cancer.