Wiley Interdiscip Rev Syst Biol Med - Mechanistic modeling to investigate signaling by oncogenic Ras mutants.

Tópicos

{ model(2656) set(1616) predict(1553) }
{ cancer(2502) breast(956) screen(824) }
{ gene(2352) biolog(1181) express(1162) }
{ model(2220) cell(1177) simul(1124) }
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{ detect(2391) sensit(1101) algorithm(908) }

Resumo

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.

Resumo Limpo

mathemat model base biochem reaction mechan can power complement experiment investig cell signal network principl model potenti find behavior result wellunderstood compon interact measur properti concentr rate constant cancer result acquisit mutat alter express level andor biochemistri protein encod mutat gene mathemat model cell signal network also seem potenti predict chang alter cell signal produc cancer phenotyp ras common found cancer extens character level detail need develop model consid biochem mechanismbas model use studi mutant ras signal model demonstr clear possibl use observ properti individu reaction predict entir system behav produc high level signal drive cancer phenotyp model also demonstr differ model develop studi evalu suggest approach promis futur work

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