The Cancer Genome Atlas (TCGA) is a project, begun in 2005, to catalogue genetic mutations responsible for cancer, using genome sequencing and bioinformatics. TCGA represents an effort in the War on Cancer that is applying high-throughput genome analysis techniques to improve our ability to diagnose, treat, and prevent cancer through a better understanding of the genetic basis of this disease.
TCGA is supervised by the National Cancer Institute and the National Human Genome Research Institute. A three-year pilot project, begun in 2006, focused on characterization of three types of human cancers: glioblastoma multiforme, lung, and ovarian cancer. In 2009, it expanded into phase II, which plans to complete the genomic characterization and sequence analysis of 20-25 different tumor types by 2014. Funding is split between genome characterization centers (GCCs), which perform the sequencing, and genome data analysis centers (GDACs), which perform the bioinformatic analyses.
The project is unique in terms of the size of the patient cohort interrogated (scheduled are 500 patient samples, far more than most genomics studies), and the number of different techniques used to analyze the patient samples. Techniques that are being used include gene expression profiling, copy number variation profiling, SNP genotyping, genome wide DNA methylation profiling, microRNA profiling, and exon sequencing of at least 1,200 genes. The TCGA is sequencing the entire genomes of some tumors, including at least 6,000 candidate genes and microRNA sequences. This targeted sequencing is being performed by all three sequencing centers using hybrid-capture technology. In phase II, TCGA is performing whole exon sequencing on 80% of the cases and whole genome sequencing on 80% of the cases used in the project.
Read more about The Cancer Genome Atlas: Project Goals, TCGA Project Management, Tissue Accrual, TCGA Funding, Organization of The Project, List of Tumors and Entrance of A Tumor Type Into TCGA, Publication Reports and Findings By TCGA, See Also
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