Clustering of brain tumor cells: a first step for understanding tumor recurrence

ORAL

Abstract

Glioblastoma tumors are highly invasive; therefore the overall prognosis of patients remains poor, despite major improvements in treatment techniques. Cancer cells detach from the inner tumor core and actively migrate away [1]; eventually these invasive cells might form clusters, which can develop to recurrent tumors. In vitro experiments in collagen gel [1] followed the clustering dynamics of different glioma cell lines. Based on the experimental data, we formulated a stochastic model for cell dynamics, which identified two mechanisms of clustering. First, there is a critical value of the strength of adhesion; above the threshold, large clusters grow from a homogeneous suspension of cells; below it, the system remains homogeneous, similarly to the ordinary phase separation. Second, when cells form a cluster, there is evidence that their proliferation rate increases. We confirmed the theoretical predictions in a separate cell migration experiment on a substrate and found that both mechanisms are crucial for cluster formation and growth [2]. In addition to their medical importance, these phenomena present exciting examples of pattern formation and collective cell behavior in intrinsically non-equilibrium systems [3]. \\[4pt] [1] A. M. Stein et al, Biophys. J., 92, 356 (2007). \\[0pt] [2] E. Khain et al, EPL 88, 28006 (2009). \\[0pt] [3] E. Khain et al, Phys. Rev. E. 83, 031920 (2011).

Authors

  • Evgeniy Khain

    • Oakland University
    • Department of Phyiscs, Oakland University
  • M.O. Nowicki

    • Department of Neurological Surgery, The Ohio State University Medical Center
  • E.A. Chiocca

    • Department of Neurological Surgery, The Ohio State University Medical Center
  • S.E. Lawler

    • Department of Neurological Surgery, The Ohio State University Medical Center
  • C.M. Schneider-Mizell

    • Department of Physics, University of Michigan
  • L.M. Sander

    • Department of Physics, University of Michigan