Program Overview


Interactive tool that illustrates the components of The Cancer Genome Atlas.
Interactive: How It Works

There are at least 200 forms of cancer, and many more subtypes. Each of these is caused by errors in DNA that cause cells to grow uncontrolled. Identifying the changes in each cancer’s complete set of DNA – its genome – and understanding how such changes interact to drive the disease will lay the foundation for improving cancer prevention, early detection and treatment.

The Cancer Genome Atlas (TCGA), a collaboration between the National Cancer Institute (NCI) and National Human Genome Research Institute (NHGRI), aims to generate comprehensive, multi-dimensional maps of the key genomic changes in major types and subtypes of cancer. A three-year pilot project initiated in 2006 confirmed that an atlas of changes could be created for specific cancer types. It also showed that a national network of research and technology teams working on distinct but related projects could pool the results of their efforts, create an economy of scale and develop an infrastructure for making the data publicly accessible. Importantly, it proved that making the data freely available would enable researchers around the world to make and validate important discoveries. The success of the pilot led the National Institutes of Health to commit major resources to TCGA to collect and characterize additional tumor types. TCGA finalized tissue collection with matched tumor and normal tissues from 11,000 patients, allowing for the comprehensive characterization of 33 cancer types and subtypes, including 10 rare cancers.

Learn more about cancers selected for study. 

Each cancer has undergone comprehensive genomic characterization and analysis. The comprehensive data that have been generated by TCGA’s network approach are freely available and widely used by the cancer community through the TCGA Data Portal and the Cancer Genomics Hub (CGHub).

Learn more about the components of the TCGA Research Network by selecting a link below:

Biospecimen Core Resource (BCR)  – Tissue samples are carefully cataloged, processed, checked for quality and stored, complete with important medical information about the patient.

Genome Characterization Centers (GCCs) – Several technologies are used to analyze genomic changes involved in cancer. The genomic changes that are identified aree further studied by the Genome Sequencing Centers.

Genome Sequencing Centers (GSCs) – High-throughput Genome Sequencing Centers identify the changes in DNA sequences that are associated with specific types of cancer.

Proteome Characterization Centers (PCCs) – The centers, a component of NCI’s Clinical Proteomic Tumor Analysis Consortium, ascertain and analyze the total proteomic content of a subset of TCGA samples.

Data Coordinating Center (DCC) – The information that is generated by TCGA is centrally managed at the DCC and entered into the TCGA Data Portal and Cancer Genomics Hub as it becomes available. Centralization of data facilitates data transfer between the network and the research community, and makes data analysis more efficient. The DCC manages the TCGA Data Portal. 

Cancer Genomics Hub (CGHub) – Lower level sequence data is deposited into a secure repository. This database stores cancer genome sequences and alignments.

Genome Data Analysis Centers (GDACs) – Immense amounts of data from array and second-generation sequencing technologies must be integrated across thousands of samples. These centers provide novel informatics tools to the entire research community to facilitate broader use of TCGA data.

Learn more about TCGA by selecting a link below:

Mission and Goal
How It Works
History and Timeline
Future Directions

 Learn more about the cancer genomics field and TCGA's place in it by selecting a link below:

Tomczak, K., Czerwinska, P., and Wiznerowicz, M. (2015) The Cancer Genome Atlas (TCGA): an immeasurable source of knowledgeContemporary Oncology. 19(1A): A68-A77.

The future of cancer genomics. Nature Medicine. (2015). 21(2): 99.

Chin, L., Hahn, W.C., Getz, G., Meyerson, M. (2011) Making sense of cancer genomic data. Genes and Development. 25(6): 534-555.

Chin, L., Andersen, J.N., Futreal, P.A. (2011) Cancer genomics: from discovery science to personalized medicine. Nature Medicine. 17(3): 297-303.