Characterization of antitumor auto-antibodies using combinatorial peptide librari

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DESCRIPTION (provided by applicant): The development of circulating auto-antibodies to tumor-associated antigens (TAAs) has been observed at early cancer stages. TAA auto-antibodies are attractive as diagnostic markers because they are stable and persistent in cancerous conditions yet minimally present in normal individuals and most noncancerous conditions. However, the identification of auto-antibodies specific for a particular type of cancer is complicated due to the relatively low-abundance of an individual antibody within the complexity of the human proteome. The purpose of the present project is to develop an approach to detect auto-antibodies to tumor-associated antigens using an encoded combinatorial peptide library synthesized on PharmaSeq's light-activated radio-frequency p-Chips. Preparing the combinatorial library on the p-Chip platform serves two purposes: 1) to enrich for low-abundance proteins based on established principles of solid-phase affinity adsorption and 2) to rapidly identify the affinity ligand on each chip based on the encoded ID. The main project goal is to synthesize an RFID-encoded peptide library consisting of several thousands of random tetramers using the "split-and-mix" method. We will use a high speed fluidics-based analytical instrument previously developed by PharmaSeq to identify p-Chips carrying specific peptides with affinity to human auto- antibodies. In addition we will quantitatively characterize differences in immunoglobulin profiles between early stage ovarian and breast cancer patient and normal control samples. The methods developed will enable, for the first time, a true encoded one- particle-one-compound high throughput library synthesis and screening method that is capable of direct translation as a clinical diagnostic platform. PUBLIC HEALTH RELEVANCE: Auto-antibodies generated against tumor-associated antigens show great potential for the accurate, early diagnosis of cancer but identifying antibodies specific to a particular type of cancer is challenging, requiring a sensitive, high-throughput system that can discriminate key biomarkers against a high protein load. The implementation of an RFID- encoded combinatorial peptide library with PharmaSeq's light-activated p-Chip system will enable the simultaneous enrichment and identification of clinically-relevant biomarkers on a unified, high-throughput platform.