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Mechanistic modeling to investigate signaling by oncogenic Ras mutants

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Abstract Mathematical models based on biochemical reaction mechanisms can be a powerful complement to experimental investigations of cell signaling networks. In principle, such models have the potential to find the behaviors that result from well‐understood component interactions and their measurable properties, such as concentrations and rate constants. As cancer results from the acquisition of mutations that alter the expression level and/or the biochemistry of proteins encoded by mutated genes, mathematical models of cell signaling networks would also seem to have the potential to predict how these changes alter cell signaling to produce a cancer phenotype. Ras is commonly found in cancer and has been extensively characterized at the level of detail needed to develop such models. Here, we consider how biochemical mechanism‐based models have been used to study mutant Ras signaling. These models demonstrate that it is clearly possible to use observable properties of individual reactions to predict how the entire system behaves to produce the high levels of signal that drive the cancer phenotype. These models also demonstrate differences in how models are developed and studied. Their evaluation suggests which approaches are most promising for future work. WIREs Syst Biol Med 2012, 4:117–127. doi: 10.1002/wsbm.156 This article is categorized under: Biological Mechanisms > Cell Signaling

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Simplified portrayal of Ras signaling in receptor tyrosine kinase (RTK) models. Most models of RTK signaling that span from RTK through the extracellular signal regulated kinase (ERK)/mitogen‐activated protein kinase (MAPK) cascade include a simplified portrayal of Ras signaling. Such models typically include only inducible guanine nucleotide exchange factor (Sos1) and GTPase accelerating protein (p120GAP) activity on Ras and the interaction between Ras and its effector Raf‐1 that initiates the ERK/MAPK cascade.

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The reactions that regulate Ras signals. Ras proteins are typically found in the cell in a noncovalent complex with a guanine nucleotide, GDP or GTP. Several different processes collectively determine to which nucleotide Ras is bound. These include: Guanine nucleotide exchange factor activity on Ras, GTPase accelerating protein activity on Ras, Ras intrinsic nucleotide exchange, Ras intrinsic GTPase activity, and Ras interactions with effector proteins.

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Variations in how mutant signals are modeled and studied. Many models focus on transient signaling kinetics, i.e., how the level of wild‐type (WT) RasGTP changes with time after stimulus. Mutant Ras proteins result in a constitutively high level of Ras signal, and models of mutant Ras proteins can focus on constitutively high steady‐state signals. The modeled WT and mutant Ras proteins are characterized by different rate constants for the reactions that regulate Ras signals and the different concentrations of WT and mutant protein. Modeled Ras can be all WT, all mutant, or some proportion of all Ras mutant and WT, as is typically true for human cancers where only one Ras locus is mutated. By updating the rate constants of Ras regulatory reactions to the values for Ras mutant proteins, the model may yield a higher proportion of RasGTP and lead to greater downstream signaling. Alternatively, a modeled, fixed amount of Ras as RasGTP may allow one to study how this higher level of RasGTP impacts downstream signaling.

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Comparison of detailed models of Ras signaling applied to oncogenic mutants. The five models considered in the review are compared for which reaction processes they consider (Figure 1) as well what biology was considered and modeled (Figure 4). Shading indicates the indicated feature was included in the model‐based study.

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