Affinity-Based Serum Proteomics for Ovarian Cancer Early Diagnosis; Annual rept. 15 Nov 2006-14 Nov 2007

摘要

Our research project is intended to exploit unique characteristics of phage and yeast recombinant antibodies as the basis for a serum biomarker discovery platform for ovarian cancer. In brief, we select from large recombinant libraries those binding sequences which bind to cancer related material but not to control serum, then we evaluate these sub libraries in high throughput using novel recombinant antibody arrays probed with serum from our serum repository. At present, we are on track based on our initial proposal. We have (1) selected a well-balanced group of cases (serum and proximal fluid) and controls for our initial discovery, (2) identified thousands of unique binding sequences that bind to the cases and not controls, (3) printed over 1,700 recombinant antibodies on high density arrays and (4) probed those arrays with individual sera from 50 cases (including early and late stage, and high and average risk women) and 50 asymptomatic controls. In addition to these tasks, we have also undertaken several research tasks to further optimize our experimental protocols. These include a series of shotgun proteomics experiments used to characterize the protein constituents of the clinical materials used in our selection, an evaluation of multiple array normalization and processing protocols to tailor data analysis to our array platform, and improved methods for high throughput shuffling (yeast library only) and purification of antibodies. At present, materials from our project include libraries of binding agents and data, including microarrays profiling dozens of specimens and mass spectrometry data characterizing the constituents of ovary tumor proximal fluid. To date, the major findings of our proposal include the proof of principle that (based on our data analysis) the panning and array procedures are capable of evaluating thousands of unique antibodies, and that (based on the proteomics measurements) the selection material is rich in putative biomarkers.