We are developing a powerful new and proprietary approach for identification of disease-specific biomarkers in human proteomes. The basis of this approach is the balancing of proteome protein profiles using Solid-phase Peptide Combinatorial Library (SPCL) technology. The SPCL efficiently overcomes the major problem facing proteomics by decreasing the range of protein concentration without reducing the complexity. Specifically, it decreases the concentration of abundant proteins and increases the concentration of trace proteins within a sample while maintaining the difference in concentration of biomarkers between samples. Our technology comprises: A. balancing of protein concentrations in a sample using a solid-phase combinatorial peptide library (SPCL1) and eluting under non-denaturing conditions; B. differential labeling of disease state and normal balanced proteins with fluorophores; C. combining the labeled proteomes and incubating with SPCL2 for affinity separation; D. identifing and separating of beads enriched with disease state specific proteins by FACS; E. identifying bead associated proteins by MS; F. identifying peptide ligands responsible for high affinity binding of protein We will perform proof-of-principle studies to detect cardiac troponin spiked at 1 - 100 ng/ml into plasma. Assuming a sensitivity of troponin detection of < 10 ng/ml, we will analyze plasma from AMI-positive patients taken at 6 hours-post AMI for troponin and other potential AMI-related biomarkers. We expect that our technology will reveal novel biomarkers that may have significant medical importance and commercial value.
The specific aims are: 1) the optimization of the individual steps of the technology; 2) the demonstration of its feasibility by detecting cardiac troponin from both spiked normal and AMI patient samples; 3) the identification of high affinity peptide ligands for troponin. These ligands would be available for evaluation of their ability to improve sensitivity of early detection of troponin in clinical assays. This technology is applicable to a wide range of other diseases, as well as for profiling patients for response to therapies. We will generate revenues by service, partnerships with companies in clinical trials, and through licensing our biomarker candidates at an advanced stage of development. ? ? ?
