Functional screen for secreted proteins by monoclonal antibody library and identification of Mac-2 binding protein (Mac-2BP) as a potential therapeutic target and biomarker for lung cancer

摘要

Identification of secreted proteins of lung cancer could provide new candidates of serum biomarkers for cancer diagnosis or targets for therapeutic intervention. In this study, we developed a novel strategy that combined functional monoclonal antibody library screening technique and mass spectrometry to identify functional secreted proteins. BALB/c mice were immunized with cancer cells isolated from fresh human lung cancer tissues. The monoclonal antibody library containing 1160 mAbs was established with the mouse spleen cells, whose serum had most anti-proliferative effect on lung cancer cells. Monoclonal antibodies were subjected to an immunoreactive and functional screen and monoclonal antibodies that reacted strongly with secreted proteins in condition medium and lung cancer tissues with high inhibotion of cell proliferation were selected. Antigens that recognized by antibodies were obtained by immunoprecipitation and then identified by mass spectrometry. Mac-2-binding protein (Mac-2BP), the antigen of 13H3 antibody, was identified using this approach. Functional studies demonstrated that the 13H3 antibody suppressed lung cancer cell lines ANIP-973 and A549 proliferation in vitro and inhibit ANIP973 xenograft tumors growth in vivo by inducing cell-cycle arrest at G1 phase, with up-regulation of p27 and down-regulation of cyclin D1. Moreover, the serum level of Mac-2BP was significantly higher in lung cancer patients than healthy controls. At a cutoff value of 6 μg/ml, Mac-2BP might be a diagnostic biomarker of lung cancer, especially for SCLC. Mac-2BP concentrations of 6 μg/ml or higher was associated with poor overall survival in univariate analysis, and was an independent predictor in the multivariate COX analysis. Together, these results firstly demonstrated that Mac-2BP can be used as a therapeutic target and potential biomarker for lung cancer. Our strategy is feasible, which may facilitate the identification of novel secreted biomarkers of lung cancer.