Protein microarrays as diagnostic and prognostic tools

The goal of personalized medicine is to examine a patient's disease and prescribe medicine based not only on symptoms but also on the underlying cause unique to the individual. The discovery of signatures for disease state based not on a single measurement but on the measurement of a broad array of hundreds of molecular markers may be necessary to appropriately treat an individual. Toward this goal, analysis tools capable of measuring an array of markers must be developed. Antibody and protein microarrays are very well suited for this task. In this thesis, I will address the application of protein microarray technology to the goal of personalized medicine. I first present efforts directed at finding a signature for the onset of preeclampsia at >20 weeks of gestation in the urine or serum of patients at <16 weeks of gestation. I will discuss the development of an antibody microarray-based assay directed at a panel of cytokines and the application of the microarrays to assess patient prognosis. I will then present experiments where these microarrays are modified to include cytokines and chemokines related to end-stage renal disease. The same technique used to examine the preeclampsia urine and serum samples is used to test the serum of patients initiating dialysis for a signature that is predictive of early mortality (death <15 weeks after initiating treatment). Finally, I present the development of antigen microarrays to profile the immunologic response of patients with leukemia undergoing various forms of therapy. The serum of leukemia patients with chronic myelogenous or chronic lymphocytic leukemias are examined for the production of antibodies. Increased antibody production for leukemia-associated antigens after a given treatment implies that the patient's immune system is beginning to fight off the disease. This tool is designed to monitor patients going through clinical trials or conventional therapy. In the future, there may be a vaccine to boost a patient's immune response to an antigen associated with their cancer. This tool can help determine which antigens are already recognized by the immune system and which are not, directing therapy towards increasing the recognition of the other unrecognized antigens.