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An integrative model links multiple inputs and signaling pathways to the onset of DNA synthesis in hepatocytes
Author(s) -
Huard Jérémy,
Mueller Stephanie,
Gilles Ernst D.,
Klingmüller Ursula,
Klamt Steffen
Publication year - 2012
Publication title -
the febs journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.981
H-Index - 204
eISSN - 1742-4658
pISSN - 1742-464X
DOI - 10.1111/j.1742-4658.2012.08572.x
Subject(s) - cell cycle , dna synthesis , biology , microbiology and biotechnology , dna replication , hepatocyte growth factor , epidermal growth factor , growth factor , signal transduction , computational biology , dna , cell , genetics , cell culture , receptor
During liver regeneration, quiescent hepatocytes re‐enter the cell cycle to proliferate and compensate for lost tissue. Multiple signals including hepatocyte growth factor, epidermal growth factor, tumor necrosis factor α, interleukin‐6, insulin and transforming growth factor β orchestrate these responses and are integrated during the G 1 phase of the cell cycle. To investigate how these inputs influence DNA synthesis as a measure for proliferation, we established a large‐scale integrated logical model connecting multiple signaling pathways and the cell cycle. We constructed our model based upon established literature knowledge, and successively improved and validated its structure using hepatocyte‐specific literature as well as experimental DNA synthesis data. Model analyses showed that activation of the mitogen‐activated protein kinase and phosphatidylinositol 3‐kinase pathways was sufficient and necessary for triggering DNA synthesis. In addition, we identified key species in these pathways that mediate DNA replication. Our model predicted oncogenic mutations that were compared with the COSMIC database, and proposed intervention targets to block hepatocyte growth factor‐induced DNA synthesis, which we validated experimentally. Our integrative approach demonstrates that, despite the complexity and size of the underlying interlaced network, logical modeling enables an integrative understanding of signaling‐controlled proliferation at the cellular level, and thus can provide intervention strategies for distinct perturbation scenarios at various regulatory levels.

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