From oncogenic mutation to dynamic code

Oncogenic BRAF mutations can distort downstream signaling outcomes Signal transduction pathways (STPs) convert biochemical reactions into precise and reproducible biological outcomes. These functions are performed reliably and reproducibly against a background of noise (variation) arising from the s...

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Veröffentlicht in:Science (American Association for the Advancement of Science) 2018-08, Vol.361 (6405), p.844-845
Hauptverfasser: Kolch, Walter, Kiel, Christina
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Kiel, Christina
description Oncogenic BRAF mutations can distort downstream signaling outcomes Signal transduction pathways (STPs) convert biochemical reactions into precise and reproducible biological outcomes. These functions are performed reliably and reproducibly against a background of noise (variation) arising from the stochastic nature of biochemical reactions ( 1 ). Indeed, information theory analysis of STPs indicates that they have a limited capacity to discriminate information, including different ligands or different activation states of components ( 2 ). However, this discrimination is dramatically enhanced by adding dynamic information, such as signal rise time, signal duration, amplitude, and decay rate ( 3 ). The observation that differential activation dynamics of the extracellular signal-regulated kinase (ERK) pathway can determine whether rat pheochromocytoma cells proliferate or differentiate was reported more than 20 years ago ( 4 ), and evidence has since accumulated that STP dynamics control cell fate decisions. However, we are still struggling to understand how signaling dynamics is encoded and decoded and how pathological changes, such as the expression of mutant proteins, affect the dynamic STP code. On page 892 of this issue, Bugaj et al. ( 5 ) make use of new tools with which to decipher this code and reveal how certain cancer-associated BRAF mutations can corrupt the dynamic STP code and trick cells into unlicensed proliferation.
doi_str_mv 10.1126/science.aau8059
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subjects Activation
Background noise
Cancer
Cell fate
Cell proliferation
Coding
Decay rate
Extracellular signal-regulated kinase
Genetic Code
Information theory
Metabolic pathways
Mutation
Pheochromocytoma cells
Proteins
Signal transduction
Stochasticity
title From oncogenic mutation to dynamic code
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