Ensembles of protein termini and specific proteolytic signatures as candidate biomarkers of disease

Early accurate diagnosis and personalized treatment are essential in order to treat complex or fatal diseases such as cancer and autoimmune, cardiovascular and neurodegenerative diseases. To realize this vision, new diagnostic and prognostic biomarkers are urgently required. MS-based proteomics is the most promising approach for protein biomarker identification, but suffers in clinical translation of biomarker candidates that show only quantitative differences from normal tissue. Indeed, success in translating proteomic data to biomarkers in the clinic has been disappointing. Here, we propose that protein termini provide a new opportunity for biomarker discovery due to qualitative differences in intact and new protein termini between diseased and normal tissues. Altered proteolysis occurs in most pathologies. Disease- and process-specific protein modifications, including proteolytic processing and subsequent modification of the terminal amino acids, frequently lead to altered protein activity that plays key roles in the disease process. Thus, mapping of ensembles of characteristic protein termini provides a proteolytic signature of high information content that shows both quantitative and most importantly qualitative differences in different diseases and stage of disease. These unique protein biomarkers have the added benefit of being mechanistically informative by revealing the activity state of the bioactive protein. Moreover, proteome-wide isolation of protein termini leads to generalized sample simplification, thereby enabling up to three orders of magnitude lower LODs compared to traditional shotgun proteomic approaches. We introduce the potential of protein termini for biomarker discovery, briefly review methods enabling large-scale studies of protein termini, and discuss how these may be integrated into a termini-oriented biomarker discovery pipeline from discovery to clinical application.