The glycolyzer: Automated glycan annotation software for high performance mass spectrometry and its application to ovarian cancer glycan biomarker discovery

Scott R. Kronewitter, Maria Lorna A De Leoz, John S. Strum, Hyun Joo An, Lauren M. Dimapasoc, Andrés Guerrero, Suzanne Miyamoto, Carlito B Lebrilla, Gary S Leiserowitz

Research output: Contribution to journalArticle

38 Citations (Scopus)

Abstract

Human serum glycomics is a promising method for finding cancer biomarkers but often lacks the tools for streamlined data analysis. The Glycolyzer software incorporates a suite of analytic tools capable of identifying informative glycan peaks out of raw mass spectrometry data. As a demonstration of its utility, the program was used to identify putative biomarkers for epithelial ovarian cancer from a human serum sample set. A randomized, blocked, and blinded experimental design was used on a discovery set consisting of 46 cases and 48 controls. Retrosynthetic glycan libraries were used for data analysis and several significant candidate glycan biomarkers were discovered via hypothesis testing. The significant glycans were attributed to a glycan family based on glycan composition relationships and incorporated into a linear classifier motif test. The motif test was then applied to the discovery set to evaluate the disease state discrimination performance. The test provided strongly predictive results based on receiver operator characteristic curve analysis. The area under the receiver operator characteristic curve was 0.93. Using the Glycolyzer software, we were able to identify a set of glycan biomarkers that highly discriminate between cases and controls, and are ready to be formally validated in subsequent studies.

Original languageEnglish (US)
Pages (from-to)2523-2538
Number of pages16
JournalProteomics
Volume12
Issue number15-16
DOIs
StatePublished - Aug 2012

Fingerprint

Tumor Biomarkers
Ovarian Neoplasms
Mass spectrometry
Polysaccharides
Mass Spectrometry
Software
Biomarkers
Glycomics
Serum
Design of experiments
Classifiers
Research Design
Demonstrations
Testing
Chemical analysis

Keywords

  • Biomarkers
  • Clinical glycomics
  • Data processing
  • Glycoproteomics
  • Human serum
  • Ovarian cancer

ASJC Scopus subject areas

  • Molecular Biology
  • Biochemistry

Cite this

The glycolyzer : Automated glycan annotation software for high performance mass spectrometry and its application to ovarian cancer glycan biomarker discovery. / Kronewitter, Scott R.; De Leoz, Maria Lorna A; Strum, John S.; An, Hyun Joo; Dimapasoc, Lauren M.; Guerrero, Andrés; Miyamoto, Suzanne; Lebrilla, Carlito B; Leiserowitz, Gary S.

In: Proteomics, Vol. 12, No. 15-16, 08.2012, p. 2523-2538.

Research output: Contribution to journalArticle

Kronewitter, SR, De Leoz, MLA, Strum, JS, An, HJ, Dimapasoc, LM, Guerrero, A, Miyamoto, S, Lebrilla, CB & Leiserowitz, GS 2012, 'The glycolyzer: Automated glycan annotation software for high performance mass spectrometry and its application to ovarian cancer glycan biomarker discovery', Proteomics, vol. 12, no. 15-16, pp. 2523-2538. https://doi.org/10.1002/pmic.201100273
Kronewitter, Scott R. ; De Leoz, Maria Lorna A ; Strum, John S. ; An, Hyun Joo ; Dimapasoc, Lauren M. ; Guerrero, Andrés ; Miyamoto, Suzanne ; Lebrilla, Carlito B ; Leiserowitz, Gary S. / The glycolyzer : Automated glycan annotation software for high performance mass spectrometry and its application to ovarian cancer glycan biomarker discovery. In: Proteomics. 2012 ; Vol. 12, No. 15-16. pp. 2523-2538.
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