Identification of quantitative and/or qualitative protein expression differences as well as the characterization of specific cancer cell proteomes would further cancer research and diagnosis. Today, the most commonly used tool for proteome analysis is two-dimensional (2D) electrophoresis. Although this technology is informative, it is extremely cumbersome, time consuming and lacks automation and proper reproducibility. In this proposal, we suggest developing an automated, high performance proteome analyzer for the diagnosis of breast and prostate cancers. This system will generate complete, high resolution 2D proteome maps from cell lysates in approximately 30 minutes, with real time detection, using imaging based laser induced fluorescence technology. The proposed approach is based on electric field mediated separation in capillary dimensions, along with proprietary fluorescent staining methodology. An advanced image formation and registration algorithm will be implemented for the analysis of the 2D proteome maps and for quantitative and comparative purposes between samples, e.g. cancer cells vs. normal cell, anticancer drug treated cells vs. non treated cells, etc. The advantage of the proposed technology over existing techniques is its simplicity, high speed, good reproducibility, and excellent detection sensitivity. Similarly to CT-scan images, 2D proteome maps can be stored in an electronic format for future reference and retrospective analysis.

Proposed Commercial Applications

We anticipate that the High Performance Proteome Analyze will be prototyped by the end of Phase II, and will be sold initially to the molecular diagnostic research market, which is engaged in developing and verifying clinical diagnostic tests. We plan to address these markets by establishing collaborative agreements with major corporate partners for the development and marketing of diagnostic tests for screening of cancer and infectious diseases.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Small Business Innovation Research Grants (SBIR) - Phase I (R43)
Project #
1R43CA080569-01
Application #
2792615
Study Section
Special Emphasis Panel (ZRG3-SSS-2 (01))
Program Officer
Song, Min-Kyung H
Project Start
1999-02-12
Project End
2000-01-31
Budget Start
1999-02-12
Budget End
2000-01-31
Support Year
1
Fiscal Year
1999
Total Cost
Indirect Cost
Name
Genetic Biosystems, Inc.
Department
Type
DUNS #
City
San Diego
State
CA
Country
United States
Zip Code
92121