Genomic estimates of aneuploid content in glioblastoma multiforme and improved classification.

ABSTRACT:

Purpose

Accurate classification of glioblastoma multiforme (GBM) is crucial for understanding its biologic diversity and informing diagnosis and treatment. The Cancer Genome Atlas (TCGA) project identified four GBM classes using gene expression data and separately identified three classes using methylation data. We sought to integrate multiple data types in GBM classification, understand biologic features of the newly defined subtypes, and reconcile with prior studies.

Experimental design

We used allele-specific copy number data to estimate the aneuploid content of each tumor and incorporated this measure of intratumor heterogeneity in class discovery. We estimated the potential cell of origin of individual subtypes and the euploid and aneuploid fractions using reference dat

SUBMITTER: Li B 

PROVIDER: S-EPMC3477792 | biostudies-literature | 2012 Oct

REPOSITORIES: biostudies-literature