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Representational analysis of DNA copy number/methylation

Award Information
Agency: Department of Health and Human Services
Branch: National Institutes of Health
Contract: 1R43CA103406-01
Agency Tracking Number: CA103406
Amount: $99,676.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: N/A
Solicitation Number: N/A
Solicitation Year: N/A
Award Year: 2003
Award Start Date (Proposal Award Date): N/A
Award End Date (Contract End Date): N/A
Small Business Information
United States
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 (858) 202-4591
Business Contact
Phone: (858) 202-4502
Research Institution

DESCRIPTION (provided by applicant): Changes in methylation state and DNA copy number within the genome play a key role in cancer development and progression. Localization and quantification of these changes is important to the discovery of new tumor suppressor genes and oncogenes, and offers great potential in classifying cancer for clinical disease management. As such, the overall objective of this project is to develop a high-throughput array-based commercial technology to globally scan the genome for changes in DNA copy number (goal to detect two-fold differences) and methylation state. This will be accomplished via a reduced complexity representation approach using comparative genomic hybridization (CGH) and restriction landmark genome scanning (RLGS) technology on a BeadArrayTM platform. There are several immediate benefits offered by this representation approach. First of all, amplification of the representations will enhance signal to noise on the array. Secondly, improvements in generating representations will provide a more reproducible and robust process, allowing accurate detection of DNA copy number and methylation changes especially from archival samples exhibiting DNA degradation. Finally by converting RLGS from a 2-D gel-based approach (approximately 1000-2000 loci) to a BeadArrayTM-based analysis (approximately 1000-50,000 loci), a much higher locus resolution and sample throughput will be realized. This should enable the large-scale analysis of hundreds to thousands of tumor samples and lead to improved understanding of tumorogenesis. Phase II will apply this technology to the analysis of tumor samples and cell lines.

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

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