Functional Analysis of metastasis-Associated Proteins

  • Goodison, Steven (PI)

Project: Research project

Project Details


DESCRIPTION (provided by applicant): The overall goal of this project is to obtain novel information on the molecular mechanisms of tumor metastasis, in order to contribute to understanding of the pathogenesis of this process and to obtain data that would be clinically useful. The proposed approach is designed to progress from identifying and verifying metastasis-associated proteins and transcripts, to genetic manipulation of specific genes in matched metastatic and non-metastatic clonal cell lines, and to lead into clinical correlation studies using archived human tumor tissues. In order to facilitate research investigations into the molecular mechanisms of breast tumor metastasis, we have derived a series of monoclonal breast tumor cell lines in which candidate metastasis-associated genes can be screened and functionally tested. Monoclonal tumor cell lines of opposite metastatic propensity were derived from the polyclonal breast carcinoma cell lines MDA-MB-435 and MDA-MB-231. Within this proposal, we will conduct a detailed analysis of the protein profile of the series of breast tumor cells using a newly developed 2D liquid separation/mass-mapping proteomic approach. This method uses isoelectric focusing and non-porous silica reversed-phase high-performance liquid chromatography to create an image of pI vs Mr analogous to 2D gel electrophoresis. Proteins will be identified based upon MALDI-TOF-MS peptide mapping and intact Mr, and quantitative comparisons will be performed between cell line lysate samples. Proteins identified and validated as being differentially expressed with regard to metastatic phenotype will be selected for genetic manipulation and resulting cell lines will be tested for behavior using in vitro and in vivo assays. Finally, the expression of candidate proteins/genes will be studied in archived normal and diseased human breast tissue samples. Correlation with clinicopathologic information will identify those candidate breast antigens with the most promising diagnostic and prognostic marker utility.
StatusNot started


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