Proteomic Analysis to Identify Novel Circulating Breast Cancer Markers

Abstract

Twenty serum samples from healthy women and breast cancer patients at different stages were fractionated using two separate antibody columns to remove highly abundant proteins. Samples were randomized prior to fractionation and mass spectrometry testing. Each fraction was digested with trypsin and subsequently analyzed by LC-MS. Peptides were targeted based on the disease to control peak intensity ratios measured in the averages of all mass spectra in each group and t-tests of the intensity of each individual peak. A series of preprocessing steps were employed to produce an expansive list of peptides for further investigation and sequencing. These steps included spectral alignment, baseline subtraction, normalization, identifying of local maxima, further identifying "large" maxima as peaks, and looking for signs of differential expression. The antibody columns removed 20 of the most abundant proteins in serum. Using LC-MS and bioinformatics analysis we found 12 differentially expressed peaks in the Cancer vs. Healthy groups. Efforts are ongoing to identify targeted peptide ion signals using tandem matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS/MS). Serum fractionation using specific antibody columns followed by LC-MS and bioinformatics analysis is a feasible approach to peptide profiling in health women and breast cancer patients.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2005
Accession Number
ADA449897

Entities

People

  • Francisco J. Esteva

Organizations

  • The University of Texas MD Anderson Cancer Center

Tags

DTIC Thesaurus Topics

  • Antibodies
  • Biological Markers
  • Blood Proteins
  • Breast Cancer
  • Chemistry
  • Computational Biology
  • Fractionation
  • Intensity
  • Liquid Chromatography
  • Mass Spectra
  • Mass Spectrometry
  • Neoplasms
  • Proteins
  • Proteomics
  • Spectra
  • Spectrometry
  • Statistical Analysis

Readers

  • Analytical Chemistry
  • Oncology and Biomarker-Based Cancer Detection.

Technology Areas

  • Biotechnology
  • Directed Energy