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Expression signature of IFN/STAT1 signaling genes predicts poor survival outcome in glioblastoma multiforme in a subtype-specific manner.
- Source :
-
PloS one [PLoS One] 2012; Vol. 7 (1), pp. e29653. Date of Electronic Publication: 2012 Jan 05. - Publication Year :
- 2012
-
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.
- Subjects :
- Bayes Theorem
Databases, Genetic
Gene Regulatory Networks genetics
Genes, Neoplasm genetics
Humans
Interferons metabolism
Models, Genetic
Proportional Hazards Models
Reproducibility of Results
STAT1 Transcription Factor metabolism
Survival Analysis
Time Factors
Treatment Outcome
Gene Expression Profiling
Gene Expression Regulation, Neoplastic
Glioblastoma classification
Glioblastoma genetics
Interferons genetics
STAT1 Transcription Factor genetics
Signal Transduction genetics
Subjects
Details
- Language :
- English
- ISSN :
- 1932-6203
- Volume :
- 7
- Issue :
- 1
- Database :
- MEDLINE
- Journal :
- PloS one
- Publication Type :
- Academic Journal
- Accession number :
- 22242177
- Full Text :
- https://doi.org/10.1371/journal.pone.0029653