Dataset Information

Empirical inference of circuitry and plasticity in a kinase signaling network.

ABSTRACT: Our understanding of physiology and disease is hampered by the difficulty of measuring the circuitry and plasticity of signaling networks that regulate cell biology, and how these relate to phenotypes. Here, using mass spectrometry-based phosphoproteomics, we systematically characterized the topology of a network comprising the PI3K/Akt/mTOR and MEK/ERK signaling axes and confirmed its biological relevance by assessing its dynamics upon EGF and IGF1 stimulation. Measuring the activity of this network in models of acquired drug resistance revealed that cells chronically treated with PI3K or mTORC1/2 inhibitors differed in the way their networks were remodeled. Unexpectedly, we also observed a degree of heterogeneity in the network state between cells resistant to the same inhibitor, indicating that even identical and carefully controlled experimental conditions can give rise to the evolution of distinct kinase network statuses. These data suggest that the initial conditions of the system do not necessarily determine the mechanism by which cancer cells become resistant to PI3K/mTOR targeted therapies. The patterns of signaling network activity observed in the resistant cells mirrored the patterns of response to several drug combination treatments, suggesting that the activity of the defined signaling network truly reflected the evolved phenotypic diversity.

SUBMITTER: Wilkes EH

PROVIDER: S-EPMC4485132 | biostudies-literature | 2015 Jun

REPOSITORIES: biostudies-literature

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Empirical inference of circuitry and plasticity in a kinase signaling network.

Wilkes Edmund H EH Terfve Camille C Gribben John G JG Saez-Rodriguez Julio J Cutillas Pedro Rodriguez PR

Proceedings of the National Academy of Sciences of the United States of America 20150609 25

Our understanding of physiology and disease is hampered by the difficulty of measuring the circuitry and plasticity of signaling networks that regulate cell biology, and how these relate to phenotypes. Here, using mass spectrometry-based phosphoproteomics, we systematically characterized the topology of a network comprising the PI3K/Akt/mTOR and MEK/ERK signaling axes and confirmed its biological relevance by assessing its dynamics upon EGF and IGF1 stimulation. Measuring the activity of this ne ...[more]

PMID: 26060313

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Dataset Information

Empirical inference of circuitry and plasticity in a kinase signaling network.

Publications

Empirical inference of circuitry and plasticity in a kinase signaling network.

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