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Comprehensive Glycoproteomic Tool Development for Cancer Biomarkers

Award Information
Agency: Department of Health and Human Services
Branch: National Institutes of Health
Contract: 1R41GM112750-01A1
Agency Tracking Number: R41GM112750
Amount: $685,860.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: 300
Solicitation Number: PA11-214
Solicitation Year: 2015
Award Year: 2014
Award Start Date (Proposal Award Date): 2014-09-22
Award End Date (Contract End Date): 2016-08-31
Small Business Information
San Carlos, CA 94070-2060
United States
DUNS: 967100921
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 (650) 230-1845
Business Contact
Phone: (650) 450-1029
Research Institution
GRAND RAPIDS, MI 49503-2518
United States

 Domestic Nonprofit Research Organization

DESCRIPTION provided by applicant This project addresses the need for better methods for deciphering the glycosylation of proteins in clinical samples Glycosylation is an important modifier of protein structure and function and contributes to disease processes But we currently know little about the glycosylation of most proteins The current methods for probing glycans on proteins are not suitable for meeting this need as they require much material and many processing steps Here we propose and practical approach to probing protein glycosylation that will provide the ability to obtain structural and compositional information with limited sample
usage the ability to precisely compare glycan levels between samples and ready translation into a clinical assay We will achieve this goal through novel informatics techniques that facilitate the combined use of mass spectrometry MS and lectin binding for studying glycans Phase II will focus on glycoprotein biomarkers of pancreatic cancer MS provides the monosaccharide compositions of glycans and some sequence information but it leaves ambiguities about sequence or linkage variants Likewise lectins can give precise measurements of specific structures using small amounts of sample but they do not provide a complete picture of each glycan We predict that quantitatively integrating the two types of information will give more accurate information than either method alone We will quantitatively link lectin experiments to MS experiments using the common language of motifs substructures of glycans In Aim we will develop an algorithm for identifying what glycan motifs are most likely present in a sample based on lectin binding In Aim we will develop tools for integrating
lectin and MS data and will use the method to characterize and compare the glycans of three different purified glycoproteins We will determine whether the linking of MS and lectin data provides more complete information than either method alone with limited sample consumption and the ability to make precise comparisons between samples PUBLIC HEALTH RELEVANCE The carbohydrate modifications on proteins have important roles in protein structure and function but currently we are lacking much fundamental information about protein glycosylation in healthy and disease conditions The lack of information results from limitations in the current experimental methods Here we propose a practical and powerful method for studying protein glycosylation in clinical samples which can open new opportunities in disease and biomarker research

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

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