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SP4 - Signaling Networks D. Arlt & Ö. Sahin, Stefan Uhlmann, Aoife Ward, Aleksandra Balwierz, Steve Wagner, Azeem Hussain, Sara Burmester, Moritz Küblbeck, Sandra Blaszkiewicz (DKFZ) We uncover the cross talk that happens between different growth factor and hormone signaling pathways relevant for cell cycle progression in breast cancer. This work shall lead to knowledge of key modulators of drug resistance and to novel biomarkers. Applying qualitative and quantitative experimental methods we determine the relations as well as interconnections between connected signaling pathways. We started of with a major focus on ERBB signaling in ERBB2 amplified subgroup of breast cancer (Sahin et al., 2009). Uncovering the regulation and feedback regulation of the ERBB-signaling network (at the protein level). Individual genes of the network are knocked down, and the effects (protein abundance, phosphorylation states) of all other components of the network quantitatively analyzed (with SP7). In addition to studying the protein components within the gene interaction networks of signaling, we also regard micro RNAs and ther specific contribution in the modulation and feedback regulation of cellular signaling. Several miRNAs have been shown to directly target and regulate components of the EGFR receptor network. Along these lines, we recently identified miR-200bc/429 to target PLC gamma1 and to differentially regulate ERBB-signaling as well as E-cadherin associated cell invasion (Uhlmann et al., 2010), we now study miRNAs which are involved in the regulation of the EGFR receptor signaling in a network approach to find potential “hub-central” miRNA/gene pairs to increase the efficiency of drug treatments used against EGFR. We further investigate the potential of miRNAs to serve as molecular markers in cancer (Haller et al., 2010). Recently, we expanded to also address the ER+ and triple negative tumor subtypes and the role of genetic (e.g., CNV, mutation) and epigenetic (e.g., promoter methylation) changes involved in acquired and de novo drug resistance. There, we examine respective changes in patient samples and cell line as well as in tumor mouse models. |
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