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Comparative serum proteome analysis of human lymph node negative/positive invasive ductal carcinoma of the breast and benign breast disease controls via label-free semiquantitative shotgun technology.
- Source :
-
Omics : a journal of integrative biology [OMICS] 2009 Aug; Vol. 13 (4), pp. 291-300. - Publication Year :
- 2009
-
Abstract
- Serum proteomics provides a useful tool to identify potential biomarkers associated with cancer progression. In the present study, a two-dimensional liquid chromatography-tandem mass spectrometry (2D-LC-MS/MS) on a linear ion trap was utilized to identify and compare serum proteins from breast cancer patients. Three groups of 21 human sera, 7 from patients with lymph node-negative invasive ductal carcinoma (IDCB), 7 from patients with lymph node-positive IDCB, and 7 controls from patients with benign breast diseases, were analyzed. Through proteomic analysis, a total of 2,078 proteins were identified with at least two unique peptide hits. By quantification with label-free spectral counting, a fruitful list of serum proteins with significant differences in abundance accompanying the progression of breast cancer was found. Through hierarchical cluster analysis based on the differently expressed proteins in selection, we found that different groups of sera could be distinguished. Among the selected proteins, tenascin-XB (TNXB) was further validated by the ELISA method in 131 serum samples as a promising biomarker for early metastasis of breast cancer. These experiments revealed the valuable potential of label-free quantitative 2D-LC-MS/MS for identification of novel biomarkers for disease progression.
- Subjects :
- Adult
Breast Neoplasms pathology
Case-Control Studies
Chromatography, Liquid methods
Cluster Analysis
Computational Biology
Female
Humans
Lymphatic Metastasis
Middle Aged
Tandem Mass Spectrometry methods
Biomarkers, Tumor metabolism
Breast Diseases pathology
Breast Neoplasms metabolism
Proteome analysis
Proteomics methods
Subjects
Details
- Language :
- English
- ISSN :
- 1557-8100
- Volume :
- 13
- Issue :
- 4
- Database :
- MEDLINE
- Journal :
- Omics : a journal of integrative biology
- Publication Type :
- Academic Journal
- Accession number :
- 19624269
- Full Text :
- https://doi.org/10.1089/omi.2009.0016