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Integration and analysis of genome-scale data from gliomas.

TitleIntegration and analysis of genome-scale data from gliomas.
Publication TypeJournal Article
Year of Publication2011
AuthorsRiddick G, Fine HA
JournalNat Rev Neurol
Volume7
Issue8
Pagination439-50
Date Published2011 Jul 05
ISSN1759-4766
KeywordsBrain Neoplasms, Computational Biology, Data Interpretation, Statistical, Epigenomics, Gene Dosage, Gene Expression Profiling, Genomics, Glioma, Humans, MicroRNAs, Precision Medicine, Proteomics
Abstract

Primary brain tumors are a leading cause of cancer-related mortality among young adults and children. The most common primary malignant brain tumor, glioma, carries a median survival of only 14 months. Two major multi-institutional programs, the Glioma Molecular Diagnostic Initiative and The Cancer Genome Atlas, have pursued a comprehensive genomic characterization of a large number of clinical glioma samples using a variety of technologies to measure gene expression, chromosomal copy number alterations, somatic and germline mutations, DNA methylation, microRNA, and proteomic changes. Classification of gliomas on the basis of gene expression has revealed six major subtypes and provided insights into the underlying biology of each subtype. Integration of genome-wide data from different technologies has been used to identify many potential protein targets in this disease, while increasing the reliability and biological interpretability of results. Mapping genomic changes onto both known and inferred cellular networks represents the next level of analysis, and has yielded proteins with key roles in tumorigenesis. Ultimately, the information gained from these approaches will be used to create customized therapeutic regimens for each patient based on the unique genomic signature of the individual tumor. In this Review, we describe efforts to characterize gliomas using genomic data, and consider how insights gained from these analyses promise to increase understanding of the biological underpinnings of the disease and lead the way to new therapeutic strategies.

DOI10.1038/nrneurol.2011.100
Alternate JournalNat Rev Neurol
PubMed ID21727940