Diagnosing Breast Cancer Using Protease Fingerprint

In the original fellowship proposal, I planed to profile protease activity using substrate phage display library in the biological samples from mice at different stages of breast cancer. I first used the substrate phage display library I constructed to characterize substrate recognition profiles of two tumor-related proteases, Metalloproteinase-2 (MMP-2) and 9 (MMP-9). Three groups of MMP-2 substrate sequences were novel and found highly selective for MMP-2 over MMP-9. This result supports the hypothesis that substrate phage display library can be used to differentiate diminutive structural difference of proteases. However, I found that phage display library had limited application for in vivo protease profiling because only small quantity of proteases present in the biological samples. Hence, I modified my approach of carrying out the functional study of disease-related proteases and developed a one-pot phage selection system that yield the substrate recognition profile of multiple purified proteases from a single round of selection. This method allows analysis of multiple proteases simultaneously, and prior knowledge of substrate preference is not required. As an illustration, a phage selection with a mixture of thrombin and factor Xa (serine proteases) along with MMP-9 and atrolysin C (metalloproteinases). Peptide substrates were identified that (1) have high kcat/Km ration, (2) are selective for individual proteases, and (3) match the sequences of known physiological substrates. Ultimately, highly selective peptide substrates for disease-related proteases can be obtained, and an array of selective peptide substrates can be assembled and profile protease activity in the biological samples from mice at different stages of breast cancer.