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Novel predication of protein biomarkers in interferon-gamma-stimulated breast cancer cells

Proteomics is the large-scale study of localization, identification, structure, and function of the proteome. A proteome is the complete set of proteins expressed and modified by an organism under a specific set of environmental conditions. This study was undertaken to investigate the novel protein...

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Bibliographic Details
Published in:International journal of health sciences 2019-03, Vol.13 (2), p.35-43
Main Authors: Ssadh, Hussain Al, Abdulmonem, Waleed Al
Format: Article
Language:English
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Summary:Proteomics is the large-scale study of localization, identification, structure, and function of the proteome. A proteome is the complete set of proteins expressed and modified by an organism under a specific set of environmental conditions. This study was undertaken to investigate the novel protein biomarkers that play a role in breast cancer under inflammatory condition. The two-dimensional gel electrophoresis (2-DE) was applied in the context of the breast cancer model system to investigate the effect of interferon-gamma (IFN-γ) on the differential protein expression in breast cancer-derived cell lines CAMA-1 and 3,4-methylenedioxyamphetamine (MDA)-MB-231. Whole cell lysates were prepared from IFN-γ-stimulated and non-stimulated CAMA-1 and MDA-MB-231 cells for 2-DE to obtain information for potential differential protein expression. Protein spots in the gels were visualized by silver staining and analyzed by Progenesis SameSpot. Gels were then scanned using the Epson image scanner with LabScan 6.0 software. The ExPASy tool was used to identify and quantify breast cancer cell membrane proteins expressed in response to IFN-γ. In the present proteomics study, a series of differentially expressed proteins were analyzed in IFN-γ-stimulated CAMA-1 and MDA-MB-231 cells. While results obtained from this analysis can be used as preliminary data to identify differences between untreated and IFN-γ-treated samples, they were not used for further mass spectrometry analysis. The data described and discussed here can be utilized for further data validation projects and could assist in the discovery of new breast cancer-related proteins and molecular pathways.
ISSN:1658-3639