Abstract
Mammaglobin A (MGA) is an organ specific molecular biomarker for metastatic breast cancer diagnosis. However, there are still needs to develop optimal monoclonal antibodies (mAbs) to detect MGA expression in breast carcinoma by immunohistochemistry. In this study, we first generated mAbs against MGA. Then, we used epitope prediction and computer-assisted structural analysis to screen five dominant epitopes and identified mAbs against five epitopes. Further immunohistochemical analysis on 42 breast carcinoma specimens showed that MHG1152 and MGD785 had intensive staining mainly in membrane, while CHH11617, CHH995 and MJF656 had more intensive staining within the cytoplasm. MGA scoring results showed that MJF656 had the highest rate (92.8%) of positive staining among five mAbs, including higher staining intensity when compared with that of MHG1152 (p < 0.01) and CHH995 (p < 0.05) and the highest the mean percentage of cells stained among mAbs. Furthermore, we analyzed the relationship of positive staining rate by mAbs with patient clinical characteristics. The results suggest that MJF656 was able to detect MGA expression, especially in early clinical stage, low grade and lymph node metastasis-negative breast carcinoma. In conclusion, our study generated five mAbs against MGA and identified the best candidate for detection of MGA expression in breast cancer tissues.