An efficient method for derivation and propagation of glioblastoma cell lines that conserves the molecular profile of their original tumours

  • Fael Al-Mayhani T
  • Ball S
  • Zhao J
 et al. 
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Abstract

A growing body of evidence suggests that glioma stem-like cells are more representative of their parent tumours when cultured under defined serum-free conditions with the mitogens epidermal growth factor (EGF) and fibroblast growth factor (FGF). However, culturing these cells as free-floating spheroids can result in difficulty in efficiently deriving and propagating cell lines. We have combined neurosphere and monolayer culture techniques to improve the efficiency with which cells can be derived from clinical tumour samples under defined serum-free conditions. We have applied our protocol to consecutive samples of glioblastoma to show that they can form experimental tumours that recapitulate many of the histological features of the parent tumour. We go on to show that the tumour initiating cells also retain the cytogenetic abnormalities of the parent tumour. Finally we examined the cell lines for expression of markers associated with neural stem cells. Our results confirm the expression of transcription factors associated with neural patterning and specification including Sox2, Olig2, Pax6 and Nkx2.2. We went on to establish that these factors were also expressed in the parent tumour indicating that their expression was not a function of our culture conditions. The Cambridge Protocol is an efficient method of deriving stem-like tumour initiating cells from glioblastoma. Improving the efficiency of derivation will facilitate the improvement of in vitro and in vivo model systems to study disease mechanisms, screen drugs and develop novel therapeutic approaches in the future. © 2008 Elsevier B.V. All rights reserved.

Author-supplied keywords

  • Brain
  • CGH
  • Cancer
  • Cell culture
  • Glia
  • Glioblastoma
  • Glioma
  • Human
  • Model
  • Progenitor
  • Stem cell

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Authors

  • Talal M. Fael Al-Mayhani

  • Siolian L.R. Ball

  • Jing Wei Zhao

  • James Fawcett

  • Koichi Ichimura

  • Peter V. Collins

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