OBJECTIVE: In recent years, support has increased for the notion that a subpopulation of brain tumour cells in possession of properties typically characteristic of stem cells is responsible for initiating and maintaining the tumour. Unravelling details of the brain tumour stem cell (BTSC) hierarchy, as well as interactions of these cells with various therapies, will be essential in the design of optimal treatment strategies. MATERIALS AND METHODS: Motivated by this, we have developed a mathematical model of the BTSC hypothesis that may aid in characterization of brain tumours, as well as in prediction of effective therapeutic strategies, which can be further validated in experimental and clinical studies. At the level of a small number of cells, the model developed herein is stochastic. For larger populations of cancer cells, the model is handled from a deterministic approach. RESULTS AND CONCLUSIONS: In the stochastic regime, importance of a relationship between the likelihoods of two distinct types of symmetric BTSC divisions in determining BTSC survival rates becomes apparent, consequently emphasizing the need for a set of biomarkers that are able to better characterize the BTSC hierarchy. At the large scale, we predict the importance of the aforementioned symmetric division rates in dictating brain tumour composition. Furthermore, we demonstrate possible therapeutic benefits of considering combination treatments of radiotherapy and putative BTSC inhibitors, such as bone morphogenetic proteins, while reinforcing the importance of developing novel treatment strategies that specifically target the BTSC subpopulation.
OBJECTIVE: In recent years, support has increased for the notion that a subpopulation of brain tumour cells in possession of properties typically characteristic of stem cells is responsible for initiating and maintaining the tumour. Unravelling details of the brain tumour stem cell (BTSC) hierarchy, as well as interactions of these cells with various therapies, will be essential in the design of optimal treatment strategies. MATERIALS AND METHODS: Motivated by this, we have developed a mathematical model of the BTSC hypothesis that may aid in characterization of brain tumours, as well as in prediction of effective therapeutic strategies, which can be further validated in experimental and clinical studies. At the level of a small number of cells, the model developed herein is stochastic. For larger populations of cancer cells, the model is handled from a deterministic approach. RESULTS AND CONCLUSIONS: In the stochastic regime, importance of a relationship between the likelihoods of two distinct types of symmetric BTSC divisions in determining BTSC survival rates becomes apparent, consequently emphasizing the need for a set of biomarkers that are able to better characterize the BTSC hierarchy. At the large scale, we predict the importance of the aforementioned symmetric division rates in dictating brain tumour composition. Furthermore, we demonstrate possible therapeutic benefits of considering combination treatments of radiotherapy and putative BTSC inhibitors, such as bone morphogenetic proteins, while reinforcing the importance of developing novel treatment strategies that specifically target the BTSC subpopulation.
Authors: Shideng Bao; Qiulian Wu; Roger E McLendon; Yueling Hao; Qing Shi; Anita B Hjelmeland; Mark W Dewhirst; Darell D Bigner; Jeremy N Rich Journal: Nature Date: 2006-10-18 Impact factor: 49.962
Authors: S G M Piccirillo; B A Reynolds; N Zanetti; G Lamorte; E Binda; G Broggi; H Brem; A Olivi; F Dimeco; A L Vescovi Journal: Nature Date: 2006-12-07 Impact factor: 49.962
Authors: Rossella Galli; Elena Binda; Ugo Orfanelli; Barbara Cipelletti; Angela Gritti; Simona De Vitis; Roberta Fiocco; Chiara Foroni; Francesco Dimeco; Angelo Vescovi Journal: Cancer Res Date: 2004-10-01 Impact factor: 12.701
Authors: Houman D Hemmati; Ichiro Nakano; Jorge A Lazareff; Michael Masterman-Smith; Daniel H Geschwind; Marianne Bronner-Fraser; Harley I Kornblum Journal: Proc Natl Acad Sci U S A Date: 2003-11-26 Impact factor: 11.205
Authors: Elizabeth Clayton; David P Doupé; Allon M Klein; Douglas J Winton; Benjamin D Simons; Philip H Jones Journal: Nature Date: 2007-02-28 Impact factor: 49.962
Authors: Gentao Liu; Xiangpeng Yuan; Zhaohui Zeng; Patrizia Tunici; Hiushan Ng; Iman R Abdulkadir; Lizhi Lu; Dwain Irvin; Keith L Black; John S Yu Journal: Mol Cancer Date: 2006-12-02 Impact factor: 27.401