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Submitted on December 8, 2006
Revised on July 25, 2007
Accepted on July 25, 2007

Proteomic analysis of conditioned media from three breast cancer cell lines: A mine for biomarkers and therapeutic targets

Vathany Kulasingam and Eleftherios P. Diamandis

Pathology and Laboratory Medicine, Mount Sinai Hospital, Toronto, Ontario M5G 1X5

Corresponding Author: ediamandis{at}mtsinai.on.ca

A “bottom-up” proteomic approach and a two-dimensional (strong cation-exchange followed by reversed-phase) liquid chromatography-tandem mass spectrometry (2D-LC-MS/MS) strategy on a linear ion trap (LTQ) was utilized to identify and compare expressions of extracellular and membrane-bound proteins in the conditioned media of 3 breast cell lines (MCF-10A, BT474 and MDA-MB-468). Proteomic analysis of the media identified in excess of 600, 500 and 700 proteins in MCF-10A, BT474 and MDA-MB-468, respectively. We successfully identified the internal control proteins, kallikreins 5, 6 and 10 (ranging in concentration from 2-50 µg/L) in MDA-MB-468 conditioned media (CM), as validated by ELISA and confidently identified Her2/neu in BT474 cells. Sub-cellular localization was determined based on Genome Ontology (GO) terms for all the 1,139 proteins, of which 34% were classified as extracellular and membrane-bound. Proteomic analysis of MDA-MB-468 cell lysate demonstrated that only 5% of all identified proteins were extracellular. This confirmed our hypothesis that examining the CM of cell lines, as opposed to the cell lysates, leads to a significant enrichment in secreted proteins. Tissue specificity, functional classifications and spectral counting were performed. Elafin, a protease inhibitor, identified in the conditioned media of BT474 and MDA-MB-468 and the three kallikreins (KLK5, KLK6 and KLK10) were validated using an immunoassay on various serum and biological samples. Some of the secreted proteins identified have established roles in breast cancer development (cell growth, differentiation, metastasis) and/or are linked to early onset breast cancer. Our approach to mining for low abundance molecules could identify proteins in various stages of breast cancer development. Many of the identified proteins are potentially useful to investigate as circulating serum breast cancer biomarkers.




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