The Cancer Genome Atlas - Tissue Accrual

Tissue Accrual

Tissue requirements vary from tissue type to tissue type and from cancer type to cancer type. Disease experts from the project’s Disease Working Groups help to define the characteristics of the typical tissue samples accrued as “standard of care” in the United States and how TCGA can best utilize the tissue. For example, the Brain Disease Working Group determined that samples containing more than 50% necrosis would not be suitable for TCGA and that 80% tumor nuclei were required in the viable portion of the tumor. TCGA has some general guidelines that it follows as a starting point for collecting samples from any types of tumors. These include a minimum of 200 mg in size, no less than 80% tumor nuclei and a matched source of germline DNA (such as blood or purified DNA). In addition, institutions submitting tissues to TCGA must have a minimal clinical data set as defined by the Disease Working Group, signed consents which have been approved by their institution’s IRB as well as a material transfer agreement with TCGA.

Recently, the NCI removed approximately $130M of ARRA from the NCI’s “Prime Contract” with Science Applications International Corporation (SAIC) to fund tissue accrual and a variety of other activities through the NCI Office of Acquisition. $42M is available for tissue accrual through the NCI using “Requests for Quotations” (RFQs) and “Requests for Proposals” (RFPs) to generate purchase orders and contracts, respectively. RFQs are primarily used for the collection of retrospective samples from established banks while RFPs are used for the prospective collection of samples.

Institutions that contribute samples to TCGA are paid for their samples. In addition, the contributing institution has access to all of the molecular data generated on their samples, while maintaining a link between the TCGA unique identifier and their own unique identifier. This permits contributing institutions to link back to the clinical data for their samples and to enter into collaborations with other institutions that have similar data on TCGA samples, thus increasing the power of outcome analysis.