Abstract 4561: Quantitative phosphoproteomics of an AKT inhibitor in a PTEN-LOF breast model by label free phospho-dMS demonstrates modulation of protein transcription, protein translation, and motility

Proceedings: AACR 101st Annual Meeting 2010‐‐ Apr 17‐21, 2010; Washington, DC Among the many types of molecular mechanisms that are currently understood, none is more important for the control of cellular faith than the network of protein kinases and phosphatases. The importance of understanding these signaling networks is furthermore highlighted by the fact that virtually all major pharmaceutical companies have significant projects focused on targeted interference against oncogenic kinases as potential anti-tumor therapies. Yet, a system's wide analysis of signaling phosphorylations by these inhibitors in in vivo (i.e. tissue or xenograft models) is cost prohibitive and rarely performed. The use of mass spectrometry is a powerful approach to study complex mixtures, and some techniques have used either chemical or metabolical isotopic labeling strategies to quantify protein differences between cohorts. While these techniques have been shown to be useful and are routinely applied for cell culture systems, they do not extend readily to in vivo studies as these require either combining of samples or are dependent on the duty cycle of the mass spectrometer. Here we report a generally applicable proteomic approach to identify global protein phosphorylation changes in in-vivo systems. This label-free discovery platform, named phospho-differential mass spectrometry (phospho-dMS) does not require complex mixing or pooling strategies or isotope labeling, and instead identifies statistically significant changes in full scan mass spectrometry data. Hence, in-vivo samples can be analyzed individually, allowing the use of longitudinal designs and within-subject data analysis. We demonstrate phospho-dMS on 27 breast tumor tissues samples (3 concentrations, 3 time points, 3 mice each) excised from a PTEN-LOF mouse model. We quantified in excess of 2000 high confidence phosphorylation events. The most prominent protein modules inhibited by compound treatment (P<0.0001) relate to cytoskeletal machinery such as cell polarity and cytoskeletal reorganization, transcription factors, co-activators, and protein translation with known relevance to cancer. For the first time, using quantitative MS, the topology and significance of phosphorylation networks may be investigated in xenograft, GEM models, and tumor tissue samples marking a new era of cancer signaling research Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 4561.