G-Cimp Status Prediction Of Glioblastoma Samples Using mRNA Expression Data
Authors:
Open Access
- 6 November 2012
- journal article
- research article
- Published by Public Library of Science (PLoS) in PLOS ONE
- Vol. 7 (11) , e47839
Abstract
Glioblastoma Multiforme (GBM) is a tumor with high mortality and no known cure. The dramatic molecular and clinical heterogeneity seen in this tumor has led to attempts to define genetically similar subgroups of GBM with the hope of developing tumor specific therapies targeted to the unique biology within each of these subgroups. Recently, a subset of relatively favorable prognosis GBMs has been identified. These glioma CpG island methylator phenotype, or G-CIMP tumors, have distinct genomic copy number aberrations, DNA methylation patterns, and (mRNA) expression profiles compared to other GBMs. While the standard method for identifying G-CIMP tumors is based on genome-wide DNA methylation data, such data is often not available compared to the more widely available gene expression data. In this study, we have developed and evaluated a method to predict the G-CIMP status of GBM samples based solely on gene expression data.Keywords
This publication has 19 references indexed in Scilit:
- DNA Methylation Profiling Identifies Global Methylation Differences and Markers of Adrenocortical TumorsThe Journal of Clinical Endocrinology & Metabolism, 2012
- IDH1 mutation is sufficient to establish the glioma hypermethylator phenotypeNature, 2012
- Reproducible Research in Computational ScienceScience, 2011
- High density DNA methylation array with single CpG site resolutionGenomics, 2011
- Why Is There a Lack of Consensus on Molecular Subgroups of Glioblastoma? Understanding the Nature of Biological and Statistical Variability in Glioblastoma Expression DataPLOS ONE, 2011
- A comparison of batch effect removal methods for enhancement of prediction performance using MAQC-II microarray gene expression dataThe Pharmacogenomics Journal, 2010
- Identification of a CpG Island Methylator Phenotype that Defines a Distinct Subgroup of GliomaCancer Cell, 2010
- Integrated Genomic Analysis Identifies Clinically Relevant Subtypes of Glioblastoma Characterized by Abnormalities in PDGFRA, IDH1, EGFR, and NF1Cancer Cell, 2010
- Unsupervised Analysis of Transcriptomic Profiles Reveals Six Glioma SubtypesCancer Research, 2009
- Rembrandt: Helping Personalized Medicine Become a Reality through Integrative Translational ResearchMolecular Cancer Research, 2009