Literature DB >> 24262153

Using a cell line breast cancer progression system to identify biomarker candidates.

Ten-Yang Yen1, Nicole Haste1, Leslie C Timpe1, Christina Litsakos-Cheung1, Roger Yen1, Bruce A Macher2.   

Abstract

Secreted and plasma membrane glycoproteins are considered excellent candidates for disease biomarkers. Herein we describe the identification of secreted and plasma membrane glycoproteins that are differentially expressed among a family of three breast cancer cell lines that models the progression of breast cancer. Using two-dimensional liquid chromatography-tandem mass spectrometry we identified more than 40 glycoproteins that were differentially expressed in either the premalignant (MCF10AT) or the fully malignant (MCF10CA1a) cell lines of this model system. Comparative analysis revealed that the differentially expressed breast cancer progression-associated glycoproteins were among the most highly expressed in the malignant (MCF10CA1a) breast cancer cell line; a subset of these was detected only in the malignant line; and others were detected in the malignant line at levels 25 to 50 times greater than in the benign (MCF10A) line. Using the results from this model cell system as a guide, we then carried out glycoproteomic analyses of normal and cancerous breast tissue lysates. Eleven of the glycoproteins differentially expressed in the breast cell lines were identified in the tissue lysates. Among these glycoproteins, collagen alpha-1 (XII) chain was expressed at dramatically higher (~10-fold) levels in breast cancer than in normal tissue. BIOLOGICAL SIGNIFICANCE: Identifying glycoproteins differentially expressed during cancer progression results in information on the biological processes and key pathways associated with cancer. In addition, new hypotheses and potential biomarkers result from these glycoproteomic studies. Our glycoproteomic analysis of this model of breast cancer provides a roadmap for future experimental interventions to further tease apart critical components of tumor progression.
Copyright © 2013 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Breast cancer; Differential expression; Glycoproteomics; Label-free quantitation; Non-malignant vs. malignant; Spectral counts

Mesh:

Substances:

Year:  2013        PMID: 24262153      PMCID: PMC3920745          DOI: 10.1016/j.jprot.2013.11.006

Source DB:  PubMed          Journal:  J Proteomics        ISSN: 1874-3919            Impact factor:   4.044


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