Program Overview

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), has generated comprehensive, multi-dimensional maps of the key genomic changes in 33 types of cancer. The TCGA dataset, 2.5 petabytes of data describing tumor tissue and matched normal tissues from more than 11,000 patients, is publically available and has been used widely by the research community. The data have contributed to more than a thousand studies of cancer by independent researchers and to the TCGA research network publications.

TCGA created a genomic data analysis pipeline that can effectively collect, select, and analyze human tissues for genomic alterations on a very large scale. The success of this national network of research and technology teams serves as a model for future projects and exemplifies the tremendous power of teamwork in science.

Though TCGA is coming to a close in early 2017, new NCI genomics initiatives, run through the Center for Cancer Genomics (CCG), will continue to build upon the success of TCGA by using the same model of collaboration for large-scale genomic analysis and by making the genomics data publically available.

Visit the Center for Cancer Genomics website for more information on the NCI’s current and future initiatives in cancer genomics.

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.