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Expression Signature of IFN/STAT1 Signaling Genes Predicts Poor Survival Outcome in Glioblastoma Multiforme in a Subtype-Specific Manner

Overview of attention for article published in PLOS ONE, January 2012
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Title
Expression Signature of IFN/STAT1 Signaling Genes Predicts Poor Survival Outcome in Glioblastoma Multiforme in a Subtype-Specific Manner
Published in
PLOS ONE, January 2012
DOI 10.1371/journal.pone.0029653
Pubmed ID
Authors

Christine W. Duarte, Christopher D. Willey, Degui Zhi, Xiangqin Cui, Jacqueline J. Harris, Laura Kelly Vaughan, Tapan Mehta, Raymond O. McCubrey, Nikolai N. Khodarev, Ralph R. Weichselbaum, G. Yancey Gillespie

Abstract

Previous reports have implicated an induction of genes in IFN/STAT1 (Interferon/STAT1) signaling in radiation resistant and prosurvival tumor phenotypes in a number of cancer cell lines, and we have hypothesized that upregulation of these genes may be predictive of poor survival outcome and/or treatment response in Glioblastoma Multiforme (GBM) patients. We have developed a list of 8 genes related to IFN/STAT1 that we hypothesize to be predictive of poor survival in GBM patients. Our working hypothesis that over-expression of this gene signature predicts poor survival outcome in GBM patients was confirmed, and in addition, it was demonstrated that the survival model was highly subtype-dependent, with strong dependence in the Proneural subtype and no detected dependence in the Classical and Mesenchymal subtypes. We developed a specific multi-gene survival model for the Proneural subtype in the TCGA (the Cancer Genome Atlas) discovery set which we have validated in the TCGA validation set. In addition, we have performed network analysis in the form of Bayesian Network discovery and Ingenuity Pathway Analysis to further dissect the underlying biology of this gene signature in the etiology of GBM. We theorize that the strong predictive value of the IFN/STAT1 gene signature in the Proneural subtype may be due to chemotherapy and/or radiation resistance induced through prolonged constitutive signaling of these genes during the course of the illness. The results of this study have implications both for better prediction models for survival outcome in GBM and for improved understanding of the underlying subtype-specific molecular mechanisms for GBM tumor progression and treatment response.

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Geographical breakdown

Country Count As %
United States 3 3%
Germany 1 <1%
Brazil 1 <1%
Unknown 96 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 22 22%
Researcher 17 17%
Student > Master 8 8%
Student > Doctoral Student 7 7%
Student > Postgraduate 7 7%
Other 24 24%
Unknown 16 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 30 30%
Biochemistry, Genetics and Molecular Biology 23 23%
Medicine and Dentistry 16 16%
Neuroscience 4 4%
Immunology and Microbiology 3 3%
Other 7 7%
Unknown 18 18%