Ising model for cooperative processing of extracellular information by protein-tyrosine kinases and cell adhesion molecules

Michael Kraus, Bernhard Wolf

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

Activation of receptor tyrosine kinases by multiple growth factors (GFs) is a major process through which mitogenic information is transmitted into cells. Cell cycle progression additionally requires the coordinated interaction of cellular adhesion receptors with extracellular matrix (ECM) molecules. Recent data from several groups, which demonstrated that integrin-ECM contacts promote multiple phosphorylations of intracellular components although the integrin cytoplasmic domains do not have intrinsic protein kinase activity, support the theory that some adhesion receptor families transduce extracellular signals cooperatively with protein-tyrosine kinases (PTKs). Based on the well-established hypothesis that adhesion receptors induce an aggregation of PTKs through a rearrangement of the cytoskeleton, a mathematical minimal model for the regulation of PTKs is presented which accounts for the synergism between different environmental signals mediated by growth factors and cell adhesion molecules (CAM) or cell adhesion associated substances like carcinoembryonic antigen (CEA). The model, which is closely related to a two-dimensional Ising model describing order-disorder transitions in ferromagnetic crystals, provides evidence that a cell-type-specific pattern of cell adhesion molecules may function as a molecular amplifier which promotes the metastatic activity of malignant tumor cells through the indirect induction of intracellular PTK activity.

Original languageEnglish
Pages (from-to)89-98
Number of pages10
JournalBioSystems
Volume33
Issue number2
DOIs
StatePublished - 1994
Externally publishedYes

Keywords

  • Extracellular matrix
  • Ising model
  • Monte Carlo simulation
  • Receptor tyrosine kinases
  • Signal transduction
  • Tumor associated antigens (CEA)
  • growth factors

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