The pathways downstream of ErbB-family proteins are very important in BC, especially when considering treatment with onco-protein inhibitors. We studied and implemented dynamic simulations of four downstream pathways and described the fragment of the signaling network we evaluated as a Molecular Interaction Map. Our simulations, enacted using Ordinary Differential Equations, involved 242 modified species and complexes, 279 reversible reactions and 110 catalytic reactions. Mutations within a single pathway tended to be mutually exclusive; only inhibitors acting at, or downstream (not upstream), of a given mutation were active. A double alteration along two distinct pathways required the inhibition of both pathways. We started an analysis of sensitivity/robustness of our network, and we systematically introduced several individual fluctuations of total concentrations of independent molecular species. Only very few cases showed significant sensitivity. We transduced the ErbB2 over-expressing BC line, BT474, with the HRAS (V12) mutant, then treated it with ErbB-family and phosphorylated MEK (MEKPP) inhibitors, Lapatinib and U0126, respectively. Experimental and simulation results were highly concordant, showing statistical significance for both pathways and for two respective endpoints, i.e. phosphorylated active forms of ERK and Akt, p one tailed = .0072 and = .0022, respectively. Working with a complex 39 basic species signaling network region, this technology facilitates both comprehension and effective, efficient and accurate modeling and data interpretation. Dynamic network simulations we performed proved to be both practical and valuable for a posteriori comprehension of biological networks and signaling, thereby greatly facilitating handling, and thus complete exploitation, of biological data.
Keywords: Akt, ErbB-family, ERK, dynamic simulations, oncogene mutations, onco-protein inhibitors, signaling-networks, systems biology, dynamic, oncogene, mutations, onco-protein, signaling, HRAS (V12) mutant, c-MET receptors, IGF-1R, SRC, integrins, MAPK, PI3K/Akt/mTOR, anti-VEGF/VEGFR, PARP inhibitors, Breast Cancer, MIM, ODEs, PI3KCA, NSCLC, COSMIC data-base, Cetuximab, Panitumumab, Matuzumab, Erlotinib, Gefitinib, BT474 cells, MEK inhibitor, EGF, EGFR, KRAS, BRAF, PI3K, fetal bovine serum, SDS-PAGE, ERKPP, KRAS-GTP, P-Y654 -catenin, E-Cadherin, sbsc, SKBR3 cells
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