Evaluation of targeted therapeutics in cell lines and patient samples by quantifying signal transduction and protein levels

A7

In the rapidly emerging field of targeted therapy and translational medicine there is a strong need to find the right techniques to evaluate relevant endpoints at the bench and the bedside. Laboratory model systems, by design, are more homogenous, controlled and capable of generating large amounts of material for analysis. As treatment strategies and compounds move through the development pipeline toward the clinic, the systems in which they are being evaluated become more and more complex. Ideally, this fact can be addressed by focusing only on the specific targeted cells. For complex tissues, techniques such as cell sorting or laser capture micro-dissection (LCM) are being employed to parse out the different cell populations to address the concern of sample heterogeneity. While these techniques are well suited for nucleic acid analysis due to the ability to amplify the sample, these methods diminish overall material amounts and thus sampling ability of proteins. Since most pathologies are driven by dysfunctional expression or activity of proteins, and a majority of new therapies are targeted at these protein levels and/or activities, there is tremendous need for high fidelity, quantitative analysis techniques at the protein level. Here we describe applications using a nano-immunoassay platform (Firefly) that address these needs by sampling as few as 25 cells, separating non-phospho- from phospho-isoforms and quantitating absolute protein levels and activity. Data will be presented showing that the high content isoform distribution of proteins can potentially act as a predictive biomarker for targeted therapy response in chronic myelogeneous leukemia. Additionally, application of the platform to cell signaling pathway analysis in primary tumor stem cells and tumor populations dissected by LCM from heterogeneous biopsies will be shown.