Protein abundance of AKT and ERK pathway components governs cell type-specific regulation of proliferation

Lorenz Adlung, Sandip Kar, Marie Christine Wagner, Bin She, Sajib Chakraborty, Jie Bao, Susen Lattermann, Melanie Boerries, Hauke Busch, Patrick Wuchter, Anthony D. Ho, Jens Timmer, Marcel Schilling, Thomas Höfer*, Ursula Klingmüller

*Corresponding author for this work

Abstract

Signaling through the AKT and ERK pathways controls cell proliferation. However, the integrated regulation of this multistep process, involving signal processing, cell growth and cell cycle progression, is poorly understood. Here, we study different hematopoietic cell types, in which AKT and ERK signaling is triggered by erythropoietin (Epo). Although these cell types share the molecular network topology for pro-proliferative Epo signaling, they exhibit distinct proliferative responses. Iterating quantitative experiments and mathematical modeling, we identify two molecular sources for cell type-specific proliferation. First, cell type-specific protein abundance patterns cause differential signal flow along the AKT and ERK pathways. Second, downstream regulators of both pathways have differential effects on proliferation, suggesting that protein synthesis is rate-limiting for faster cycling cells while slower cell cycles are controlled at the G1-S progression. The integrated mathematical model of Epo-driven proliferation explains cell type-specific effects of targeted AKT and ERK inhibitors and faithfully predicts, based on the protein abundance, anti-proliferative effects of inhibitors in primary human erythroid progenitor cells. Our findings suggest that the effectiveness of targeted cancer therapy might become predictable from protein abundance.

Original languageEnglish
Article number904
JournalMolecular Systems Biology
Volume13
Issue number1
DOIs
Publication statusPublished - 01.01.2017

Funding

The authors thank Angela Lenze for autoMACS sorting of CD34+ cells, Verena Lang for help with the imaging flow cytometry, Marvin W?sch, Nora Schuhmacher, and Klara Zwadlow for excellent technical assistance, and Melania Barile, Helge Hass, and Bernhard Steiert for fruitful discussions about the mathematical model, as well as Aurelio Teleman and Kathrin Thedieck for their advice on the role of mTOR regulation. This work was supported by the SBCancer Network in the Helmholtz Alliance on Systems Biology as well as by the German Federal Ministry of Education and Research (BMBF)-funded CancerSys network LungSysII, the e:Bio network SBEpo, by the Helmholtz International Graduate School for Cancer Research at the German Cancer Research Center (DKFZ), the German Center for Lung Research (DZL) and the German Cancer Consortium (DKTK).

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being
  2. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure

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