Journal
MOLECULAR & CELLULAR PROTEOMICS
Volume 12, Issue 4, Pages 1005-1016Publisher
AMER SOC BIOCHEMISTRY MOLECULAR BIOLOGY INC
DOI: 10.1074/mcp.O112.026617
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Funding
- American Recovery and Reinvestment Act funds through National Institutes of Health Grant [R01 HG005805]
- EDRN program of the NCI
- NIGMS Grant from Center for Systems Biology [2P50 GM076547]
- American Recovery and Reinvestment Act (ARRA) funds [R01 HG005805]
- National Human Genome Research Institute
- National Center of Competence in Research Neural Plasticity and Repair
- Swiss National Science Foundation Grant [31003A_135805, 3100A0-107679]
- SystemsX.ch/InfectX
- SystemsX.ch/BIP
- PRIME-XS Project
- European Union 7th Framework Programme Grant [262067]
- European Research Council Grant [ERC-2008-AdG 233226]
- Luxembourg Centre for Systems Biomedicine
- University of Luxembourg
- National Science Foundation MRI Grant [0923536]
- German Academic Exchange Service
- Div Of Biological Infrastructure
- Direct For Biological Sciences [923536] Funding Source: National Science Foundation
- Swiss National Science Foundation (SNF) [31003A_135805] Funding Source: Swiss National Science Foundation (SNF)
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Protein biomarkers have the potential to transform medicine as they are clinically used to diagnose diseases, stratify patients, and follow disease states. Even though a large number of potential biomarkers have been proposed over the past few years, almost none of them have been implemented so far in the clinic. One of the reasons for this limited success is the lack of technologies to validate proposed biomarker candidates in larger patient cohorts. This limitation could be alleviated by the use of antibody-independent validation methods such as selected reaction monitoring (SRM). Similar to measurements based on affinity reagents, SRM-based targeted mass spectrometry also requires the generation of definitive assays for each targeted analyte. Here, we present a library of SRM assays for 5568 N-glycosites enabling the multiplexed evaluation of clinically relevant N-glycoproteins as biomarker candidates. We demonstrate that this resource can be utilized to select SRM assay sets for cancer-associated N-glycoproteins for their subsequent multiplexed and consistent quantification in 120 human plasma samples. We show that N-glycoproteins spanning 5 orders of magnitude in abundance can be quantified and that previously reported abundance differences in various cancer types can be recapitulated. Together, the established N-glycoprotein SRMAtlas resource facilitates parallel, efficient, consistent, and sensitive evaluation of proposed biomarker candidates in large clinical sample cohorts. Molecular & Cellular Proteomics 12: 10.1074/mcp.O112.026617, 1005-1016, 2013.
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