ArticleProceedings of the National Academy of Sciences of the United States of America2015
Empirical inference of circuitry and plasticity in a kinase signaling network.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.
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Who cites it
42 citing papers in PubMed, 78 citations in OpenAlex.
- Modulation of Network Plasticity Opens Novel Therapeutic Possibilities in Cancer, Diabetes, and Neurodegeneration.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Inference of differential kinase interaction networks with KINference.Bioinformatics (Oxford, England) · 2025Article
- Phosphoproteomics identifies determinants of PAK inhibitor sensitivity in leukaemia cells.Cell communication and signaling : CCS · 2025Article
- Integrated molecular and functional characterization of the intrinsic apoptotic machinery identifies therapeutic vulnerabilities in glioma.Nature communications · 2024Article
- Network-based elucidation of colon cancer drug resistance mechanisms by phosphoproteomic time-series analysis.Nature communications · 2024Article
- Community detection in empirical kinase networks identifies new potential members of signalling pathways.PLoS computational biology · 2023Article
- Principles of phosphoproteomics and applications in cancer research.The Biochemical journal · 2023Article
- Phosphoproteomics data-driven signalling network inference: Does it work?Computational and structural biotechnology journal · 2023Article
- Pharmacological approaches to understanding protein kinase signaling networks.Frontiers in pharmacology · 2023Review
- KSTAR: An algorithm to predict patient-specific kinase activities from phosphoproteomic data.Nature communications · 2022Article
- eEF2K Activity Determines Synergy to Cotreatment of Cancer Cells With PI3K and MEK Inhibitors.Molecular & cellular proteomics : MCP · 2022Article
- Suppression of Endothelial Cell FAK Expression Reduces Pancreatic Ductal Adenocarcinoma Metastasis after Gemcitabine Treatment.Cancer research · 2022Article
- Accurate, high-coverage assignment of in vivo protein kinases to phosphosites from in vitro phosphoproteomic specificity data.PLoS computational biology · 2022Article
- Adipocytes disrupt the translational programme of acute lymphoblastic leukaemia to favour tumour survival and persistence.Nature communications · 2021Article
- Inositol treatment inhibits medulloblastoma through suppression of epigenetic-driven metabolic adaptation.Nature communications · 2021Article
- Drug ranking using machine learning systematically predicts the efficacy of anti-cancer drugs.Nature communications · 2021Article
- CD44/HA signaling mediates acquired resistance to a PI3Kα inhibitor.Cell death & disease · 2020Article
- Reconstructing kinase network topologies from phosphoproteomics data reveals cancer-associated rewiring.Nature biotechnology · 2020Article
- Cancer associated fibroblast FAK regulates malignant cell metabolism.Nature communications · 2020Article
- Using phosphoproteomics data to understand cellular signaling: a comprehensive guide to bioinformatics resources.Clinical proteomics · 2020Review
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.