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Reconstruction and signal propagation analysis of the Syk signaling network in breast cancer cells

Author

Listed:
  • Aurélien Naldi
  • Romain M Larive
  • Urszula Czerwinska
  • Serge Urbach
  • Philippe Montcourrier
  • Christian Roy
  • Jérôme Solassol
  • Gilles Freiss
  • Peter J Coopman
  • Ovidiu Radulescu

Abstract

The ability to build in-depth cell signaling networks from vast experimental data is a key objective of computational biology. The spleen tyrosine kinase (Syk) protein, a well-characterized key player in immune cell signaling, was surprisingly first shown by our group to exhibit an onco-suppressive function in mammary epithelial cells and corroborated by many other studies, but the molecular mechanisms of this function remain largely unsolved. Based on existing proteomic data, we report here the generation of an interaction-based network of signaling pathways controlled by Syk in breast cancer cells. Pathway enrichment of the Syk targets previously identified by quantitative phospho-proteomics indicated that Syk is engaged in cell adhesion, motility, growth and death. Using the components and interactions of these pathways, we bootstrapped the reconstruction of a comprehensive network covering Syk signaling in breast cancer cells. To generate in silico hypotheses on Syk signaling propagation, we developed a method allowing to rank paths between Syk and its targets. We first annotated the network according to experimental datasets. We then combined shortest path computation with random walk processes to estimate the importance of individual interactions and selected biologically relevant pathways in the network. Molecular and cell biology experiments allowed to distinguish candidate mechanisms that underlie the impact of Syk on the regulation of cortactin and ezrin, both involved in actin-mediated cell adhesion and motility. The Syk network was further completed with the results of our biological validation experiments. The resulting Syk signaling sub-networks can be explored via an online visualization platform.Author summary: The complex nature of cancer hampers traditional biological approaches to unravel its molecular mechanisms and develop targeted drug therapies. Cancer affects a number of “hallmark” cellular processes controlled by multiple signaling pathways. Our goal is to identify the pathways that negatively affect tumor development and progression. We established that the Syk protein tyrosine kinase exhibits a tumor-suppressive function in breast cancer. Large scale global biochemical analyses allowed to identify Syk targets in cancer cells, but their mechanisms and interrelationships remain unknown. Our main goal was to pinpoint a limited number of biologically realistic molecular “paths” from Syk to its effectors. We therefore developed a new methodology combining graph theoretical methods allowing to reveal the shortest “paths” between “nodes” in a graph including an approach that investigates also longer “paths”. Applied to the Syk network, this method allowed us to propose and validate new signaling axes relating Syk to major effectors of the cell adhesion and mobility that are crucial cancer hallmarks.

Suggested Citation

  • Aurélien Naldi & Romain M Larive & Urszula Czerwinska & Serge Urbach & Philippe Montcourrier & Christian Roy & Jérôme Solassol & Gilles Freiss & Peter J Coopman & Ovidiu Radulescu, 2017. "Reconstruction and signal propagation analysis of the Syk signaling network in breast cancer cells," PLOS Computational Biology, Public Library of Science, vol. 13(3), pages 1-27, March.
  • Handle: RePEc:plo:pcbi00:1005432
    DOI: 10.1371/journal.pcbi.1005432
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    References listed on IDEAS

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    1. Jens S. Andersen & Christopher J. Wilkinson & Thibault Mayor & Peter Mortensen & Erich A. Nigg & Matthias Mann, 2003. "Proteomic characterization of the human centrosome by protein correlation profiling," Nature, Nature, vol. 426(6966), pages 570-574, December.
    2. Peter J. P. Coopman & Michael T. H. Do & Mara Barth & Emma T. Bowden & Andrew J. Hayes & Eugenia Basyuk & Jan K. Blancato & Phyllis R. Vezza & Sandra W. McLeskey & Paul H. Mangeat & Susette C. Mueller, 2000. "The Syk tyrosine kinase suppresses malignant growth of human breast cancer cells," Nature, Nature, vol. 406(6797), pages 742-747, August.
    3. Kakajan Komurov & Michael A White & Prahlad T Ram, 2010. "Use of Data-Biased Random Walks on Graphs for the Retrieval of Context-Specific Networks from Genomic Data," PLOS Computational Biology, Public Library of Science, vol. 6(8), pages 1-10, August.
    4. Emre Guney & Baldo Oliva, 2012. "Exploiting Protein-Protein Interaction Networks for Genome-Wide Disease-Gene Prioritization," PLOS ONE, Public Library of Science, vol. 7(9), pages 1-12, September.
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