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The Cancer Genome Atlas (TCGA) Consortium Integrated DNA Methylation Analysis

GSE11233 Homo sapiens Expression profiling by array 8 samples Submitted 2009/01/01 Platform GPL4133
Summary
Aberrant hypermethylation of CpG dinucleotides located in CpG islands within the promoters of key cancer genes is an epigenetic abnormality associated with heritable transcriptional gene silencing and inactivation in cancer. The genes involved include important tumor suppressors affecting key pathways for tumor initiation and progression. These methylated sequences can serve as potentially valuable markers for cancer risk assessment, diagnosis, prognosis, and prediction of therapeutic responses. In addition, many key cancer genes may be targeted by both epigenetic and genetic alterations and, thus epigenetic analysis can help focus the search for mutations, and vice versa. Studies of major cancer types suggest that any individual patient’s tumor may harbor at least 300 or more DNA hypermethylated genes. In TCGA, a pilot project is underway to begin defining these genes for GBM via genomic approaches. The approach in the epigenetic pilot is a two-tiered one which, first, involves pharmacological treatment of both well established human GBM cell lines, and a cell line grown as a neurosphere to enrich for tumor propagating cells, with a DNA methylation inhibitor (5-aza-2’-deoxycytidine, DAC) or a histone deacetylation inhibitor (trichostatin A) followed by an expression transcriptome analysis as previously described (Schuebel et. al.). This has resulted in identification of more than 3,700 total candidate genes. In the second tier, the top candidates are then analyzed on a custom Illumina GoldenGate array with the capacity to monitor methylation at a single CpG dinucleotide in the CpG islands of 1,498 gene promoters for the high throughput analysis of TCGA GBM samples. Keywords: Microarray, Hypermethylome, DNA-hypermethylation, DAC, TSA, Epigenetic, TCGA, The Cancer Genome Atlas, GBM, Glioblastoma, Glioblastoma multiforme, Brain
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Also filed as BioProject PRJNA106731. Searching any of these in the dataset finder brings you back here.

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