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Advancing Protein Identification for Imaging Mass Spectrometry for Pathology

Award Information
Agency: Department of Health and Human Services
Branch: National Institutes of Health
Contract: 1R43GM103352-01
Agency Tracking Number: R43GM103352
Amount: $525,674.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: NIGMS
Solicitation Number: PA11-215
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
3333 COYOTE HILL RD
PALO ALTO, CA -
United States
DUNS: 967100921
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 MARSHALL BERN
 (650) 812-4443
 bern@proteinmetrics.com
Business Contact
 CHRISTOPHER BECKER
Phone: (650) 450-1029
Email: becker@proteinmetrics.com
Research Institution
 Stub
Abstract

DESCRIPTION (provided by applicant): Molecular signatures collected from intact tissue sections by MALDI imaging mass spectrometry (MALDI IMS) have shown high potential for use as a prognostic or diagnostic pathology tool in the clinical setting. A majorobstacle to the widespread deployment of MALDI IMS, however, is the difficulty of identifying the proteins contributing to the signatures. Researchers have tried a number of approaches, including in situ digestion, MALDI TOF/TOF tandem mass spectrometry, and top-down proteomics on specific image regions. In preliminary work, we have obtained promising experimental results using top-down proteomics on intact proteins in the 2 - 20 kDa range. However, the lack of successful algorithms and software to identifythe proteins in IMS mass signatures poses a major bottleneck. In particular, available top-down proteomics software relies heavily on high-accuracy mass spectrometry. The requirement for high accuracy precludes the use of some of the most sensitive mass analyzers such as linear ion traps, especially useful for these very small and complex samples. Protein Metrics Inc. is a new software company building on six years of algorithms and software research at Palo Alto Research Center. We plan to extend Byonic,our next- generation proteomics search engine, to intact proteins up to about 20 kDa. For proteins larger than 20 kDa, we will also build software for middle-down proteomics, specifically for assembling large peptides (2 - 20 kDa) produced by limited digestion to recover the identity of the intact proteins observed in IMS. The proposed Phase I feasibility study will allow us to perform controlled studies to determine the best experimental and bioinformatics approaches. Phase II will then build commercial-grade software. The proposed project will advance the state of the art in imaging mass spectrometry. Translation of imaging mass spectrometry to routine clinical pathology use will advance the state-of-the-art in disease diagnosis and treatment, and advance medical imaging and public health. PUBLIC HEALTH RELEVANCE: The project will develop commercial software that will improve our ability to identify the proteins and modifications represented in imaging mass spectrometry molecular signatures. Project success will make imaging mass spectrometry much more useful as a clinical pathology tool.

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

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