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Investigating the Link between Molecular Subtypes of Glioblastoma, Epithelial-Mesenchymal Transition, and CD133 Cell Surface Protein

Overview of attention for article published in PLOS ONE, May 2013
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Title
Investigating the Link between Molecular Subtypes of Glioblastoma, Epithelial-Mesenchymal Transition, and CD133 Cell Surface Protein
Published in
PLOS ONE, May 2013
DOI 10.1371/journal.pone.0064169
Pubmed ID
Authors

Hadi Zarkoob, Joseph H. Taube, Sheila K. Singh, Sendurai A. Mani, Mohammad Kohandel

Abstract

In this manuscript, we use genetic data to provide a three-faceted analysis on the links between molecular subclasses of glioblastoma, epithelial-to-mesenchymal transition (EMT) and CD133 cell surface protein. The contribution of this paper is three-fold: First, we use a newly identified signature for epithelial-to-mesenchymal transition in human mammary epithelial cells, and demonstrate that genes in this signature have significant overlap with genes differentially expressed in all known GBM subtypes. However, the overlap between genes up regulated in the mesenchymal subtype of GBM and in the EMT signature was more significant than other GBM subtypes. Second, we provide evidence that there is a negative correlation between the genetic signature of EMT and that of CD133 cell surface protein, a putative marker for neural stem cells. Third, we study the correlation between GBM molecular subtypes and the genetic signature of CD133 cell surface protein. We demonstrate that the mesenchymal and neural subtypes of GBM have the strongest correlations with the CD133 genetic signature. While the mesenchymal subtype of GBM displays similarity with the signatures of both EMT and CD133, it also exhibits some differences with each of these signatures that are partly due to the fact that the signatures of EMT and CD133 are inversely related to each other. Taken together these data shed light on the role of the mesenchymal transition and neural stem cells, and their mutual interaction, in molecular subtypes of glioblastoma multiforme.

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Mendeley readers

The data shown below were compiled from readership statistics for 111 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
India 2 2%
Germany 1 <1%
Brazil 1 <1%
United Kingdom 1 <1%
Nigeria 1 <1%
United States 1 <1%
Unknown 104 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 25 23%
Researcher 25 23%
Student > Master 20 18%
Student > Bachelor 10 9%
Student > Doctoral Student 6 5%
Other 17 15%
Unknown 8 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 35 32%
Biochemistry, Genetics and Molecular Biology 28 25%
Medicine and Dentistry 20 18%
Neuroscience 9 8%
Computer Science 2 2%
Other 6 5%
Unknown 11 10%