G-cimp Status Prediction of Glioblastoma Samples Using MRNA Expression Data

Overview

Journal PLoS One

Specialties General Medicine
Science

Date 2012 Nov 10

PMID 23139755

Citations 23

Authors

Mehmet Baysan

Serdar Bozdag

Margaret C Cam

Svetlana Kotliarova

Susie Ahn

Jennifer Walling

Jonathan K Killian

Holly Stevenson

Paul Meltzer

Howard A Fine

Affiliations

Soon will be listed here.

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.

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