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Characterization of antitumor auto-antibodies using combinatorial peptide librari

Award Information
Agency: Department of Health and Human Services
Branch: National Institutes of Health
Contract: 1R43CA168014-01A1
Agency Tracking Number: R43CA168014
Amount: $272,360.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: NCI
Solicitation Number: PA09-189
Timeline
Solicitation Year: 2012
Award Year: 2012
Award Start Date (Proposal Award Date): N/A
Award End Date (Contract End Date): N/A
Small Business Information
11 DEER PARK DR, STE 104
MONMOUTH JUNCTION, NJ -
United States
DUNS: 27661870
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 WLODEK MANDECKI
 (732) 355-0100
 mandecki@pharmaseq.com
Business Contact
 WLODEK MANDECKI
Phone: (732) 355-0100
Email: mandecki@pharmaseq.com
Research Institution
 Stub
Abstract

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 andbreast 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.

* Information listed above is at the time of submission. *

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