We propose to develop an approach to allow rapid identification of proteins in complex mixtures suitable for protein expression mapping in total cell lysates. A robust approach to identify proteins as mixtures will advance cancer research in several areas. First, the approach has the potential to significantly improve the sensitivity of analysis of proteins. Benefits to cancer research will derive from the ability to identify proteins using smaller numbers of cells leading to direct examination of tumor biopsy samples. Rigorous molecular analysis at the protein level, encompassing separation, visualization, and identification, is currently difficult for small quantities of protein. The methodology proposed is general and therefore can be applied to the monitoring of gene produce expression, analysis and detection of cellular localization and post translational modification of proteins, and monitoring of major signal transduction networks involved in cancer. Second, the approach has great potential for automation allowing the technique to be transferred to laboratories involved in cancer research eliminating the need to collaborate with experts. Last, by developing the ability to quantitate and perform subtractive analyses changes in protein expression related to neoplastic transformation could be observed.
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