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WP3: Cell Fate Decisions of Erythroid Progenitor Cells

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SEEK ID: https://fairdomhub.org/investigations/104

Projects: SBEpo - Systems Biology of Erythropoietin

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Created: 11th Oct 2016 at 11:26

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Lorenz Adlung

Projects: SBEpo - Systems Biology of Erythropoietin

Institutions: German Cancer Research Center (DKFZ)

https://orcid.org/0000-0002-0971-2309
Melania Barile

Projects: SBEpo - Systems Biology of Erythropoietin

Institutions: German Cancer Research Center (DKFZ)

Maja Rey project_administratorprogramme_administrator

Projects: SysMO-LAB, de.NBI-SysBio, Kinetics on the move - Workshop 2016, Example use cases, SBEpo - Systems Biology of Erythropoietin, FAIRDOM & LiSyM & de.NBI Data Structuring Training, FAIRDOM, EnzymeML, FAIRDOM Community Workers, GMDS Project Group "FAIRe Dateninfrastrukturen für die Biomedizinische Informatik", Working Group Nicole Radde, MIX-UP

Institutions: Heidelberg Institute for Theoretical Studies (HITS gGmbH)

Patricia Sauer

Projects: SBEpo - Systems Biology of Erythropoietin

Institutions: German Cancer Research Center (DKFZ)

Marcel Schilling

Projects: SBEpo - Systems Biology of Erythropoietin, MS_DILI

Institutions: German Cancer Research Center (DKFZ)

https://orcid.org/0000-0002-9517-5166
Christian Tönsing

Projects: SBEpo - Systems Biology of Erythropoietin

Institutions: University of Freiburg

https://orcid.org/0000-0003-2822-5191
Marie-Christine Wagner

Projects: SBEpo - Systems Biology of Erythropoietin

Institutions: German Cancer Research Center (DKFZ)

SBEpo - Systems Biology of Erythropoietin

Multi-level mathematical modeling of erythropoiesis for optimized expansion of erythroid progenitor cells and improved treatment regimes

Programme: e:Bio

Public web page: http://sbepo.de/

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Protein abundance of AKT and ERK pathway components governs cell type-specific regulation of proliferation
SBEpo - Systems Biology of Erythropoietin

Abstract (Expand)

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.

Authors: Lorenz Adlung, S. Kar, Marie-Christine Wagner, B. She, Sajib Chakraborty, J. Bao, S. Lattermann, M. Boerries, Hauke Busch, P. Wuchter, A. D. Ho, J. Timmer, Marcel Schilling, T. Hofer, U. Klingmuller

Date Published: 27th Jan 2017

Journal: Mol Syst Biol

Identification of Cell Type-Specific Differences in Erythropoietin Receptor Signaling in Primary Erythroid and Lung Cancer Cells
SBEpo - Systems Biology of Erythropoietin

Abstract (Expand)

Lung cancer, with its most prevalent form non-small-cell lung carcinoma (NSCLC), is one of the leading causes of cancer-related deaths worldwide, and is commonly treated with chemotherapeutic drugs … such as cisplatin. Lung cancer patients frequently suffer from chemotherapy-induced anemia, which can be treated with erythropoietin (EPO). However, studies have indicated that EPO not only promotes erythropoiesis in hematopoietic cells, but may also enhance survival of NSCLC cells. Here, we verified that the NSCLC cell line H838 expresses functional erythropoietin receptors (EPOR) and that treatment with EPO reduces cisplatin-induced apoptosis. To pinpoint differences in EPO-induced survival signaling in erythroid progenitor cells (CFU-E, colony forming unit-erythroid) and H838 cells, we combined mathematical modeling with a method for feature selection, the L1 regularization. Utilizing an example model and simulated data, we demonstrated that this approach enables the accurate identification and quantification of cell type-specific parameters. We applied our strategy to quantitative time-resolved data of EPO-induced JAK/STAT signaling generated by quantitative immunoblotting, mass spectrometry and quantitative real-time PCR (qRT-PCR) in CFU-E and H838 cells as well as H838 cells overexpressing human EPOR (H838-HA-hEPOR). The established parsimonious mathematical model was able to simultaneously describe the data sets of CFU-E, H838 and H838-HA-hEPOR cells. Seven cell type-specific parameters were identified that included for example parameters for nuclear translocation of STAT5 and target gene induction. Cell type-specific differences in target gene induction were experimentally validated by qRT-PCR experiments. The systematic identification of pathway differences and sensitivities of EPOR signaling in CFU-E and H838 cells revealed potential targets for intervention to selectively inhibit EPO-induced signaling in the tumor cells but leave the responses in erythroid progenitor cells unaffected. Thus, the proposed modeling strategy can be employed as a general procedure to identify cell type-specific parameters and to recommend treatment strategies for the selective targeting of specific cell types.

Authors: R. Merkle, Bernhard Steiert, F. Salopiata, S. Depner, A. Raue, N. Iwamoto, M. Schelker, H. Hass, M. Wasch, M. E. Bohm, O. Mucke, D. B. Lipka, C. Plass, W. D. Lehmann, C. Kreutz, J. Timmer, Marcel Schilling, U. Klingmuller

Date Published: 6th Aug 2016

Journal: PLoS Comput Biol

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