Detecting glycan cancer biomarkers in serum samples using MALDI FT-ICR mass spectrometry data

Donald A. Barkauskas, Hyun Joo An, Scott R. Kronewitter, Maria Lorna De Leoz, Helen K Chew, Ralph W deVere White, Gary S Leiserowitz, Suzanne Miyamoto, Carlito B Lebrilla, David M Rocke

Research output: Contribution to journalArticle

32 Scopus citations

Abstract

Motivation: The development of better tests to detect cancer in its earliest stages is one of the most sought-after goals in medicine. Especially important are minimally invasive tests that require only blood or urine samples. By profiling oligosaccharides cleaved from glycosylated proteins shed by tumor cells into the blood stream, we hope to determine glycan profiles that will help identify cancer patients using a simple blood test. The data in this article were generated using matrix-assisted laser desorption/ionization Fourier transform ion cyclotron resonance mass spectrometry (MALDI FT-ICR MS). We have developed novel methods for analyzing this type of mass spectrometry data and applied it to eight datasets from three different types of cancer (breast, ovarian and prostate). Results: The techniques we have developed appear to be effective in the analysis of MALDI FT-ICR MS data. We found significant differences between control and cancer groups in all eight datasets, including two structurally related compounds that were found to be significantly different between control and cancer groups in all three types of cancer studied.

Original languageEnglish (US)
Pages (from-to)251-257
Number of pages7
JournalBioinformatics
Volume25
Issue number2
DOIs
StatePublished - Jan 2009

ASJC Scopus subject areas

  • Biochemistry
  • Molecular Biology
  • Computational Theory and Mathematics
  • Computer Science Applications
  • Computational Mathematics
  • Statistics and Probability

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