Driven by input from its scientific community, the Cancer Imaging Program (CIP) finds itself at the junction of two powerful scientific requisites; the need for cross-disciplinary research and inter-institutional data-sharing to speed scientific discovery and reduce redundancy, and the need to provide imaging phenotype data to augment large scale genomic analysis.
Image data collections on this archive offer an opportunity to encourage a new and emerging research community focused on connecting cancer phenotypes to genotypes by making available clinical images matched to the NIH TCGA (The Cancer Genome Atlas). TCGA began in 2006 as a three-year pilot jointly sponsored by the National Cancer Institute and National Human Genome Research Institute. The TCGA pilot project (focused initially on glioblastoma, ovary, and lung cancers) confirmed that an atlas of genomic changes could be constructed for specific cancer types. It also showed that a national network of research and technology teams working on related projects could pool 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 distributed researchers to make and validate important discoveries. The success of that pilot led the National Institutes of Health to commit major new resources to TCGA to collect and characterize more than 20 additional tumor types.
As an opportunity to leverage that wealth of new biomedical knowledge, CIP committed substantial effort to gather and place in The Cancer Imaging Archive the clinical diagnostic images that match the genomically analyzed TCGA tissue cases. CIP has encouraged an ad hoc image research team to study glioblastoma. The Cancer Imaging Archive now contains a TCGA GBM collection with images from more than 150 cases whose molecular and clinical patient data can be accessed in the TCGA Data Portal. A multi-institutional team coordinated by Dr Adam Flanders of Thomas Jefferson University assembled researchers from University of Virginia, Emory, Stanford, Henry Ford Hospital and NCI CCR have demonstrated the advantages of such scientific collaboration by their rapid scientific progress and 4 abstracts presented this month at the American Society of NeuroRadiology meeting in Seattle, with still more publications and abstracts in the pipeline for future venues.
Presently, CIP is developing agreements with many of the TCGA Tissue Site Source institutions to recover and place in the Image Archive collections of diagnostic images that match the genomic data now being deposited in the publically accessible TCGA Data Portal on cancers of the breast (BRCA) renal (KIRC) and lung (LUAD) and in due time, many of the future 20-plus tumors that TCGA will characterize as the program moves forward.
Continuing these efforts CIP is working to accrue images from additional sites for both GBM and the other tissue types being collected as part of the original TCGA project. Please see the child pages below to view ongoing projects and data availability for each cancer type. Efforts have already begun in the following TCGA tissue types:
- GBM - Glioblastoma multiforme (GBM) data is actively being analyzed by the TCGA Glioma Phenotype Research Group
- BRCA - Breast invasive carcinoma (BRCA) data is currently in the training stages of analysis by the TCGA Breast Phenotype Research Group while waiting for the TCGA-BRCA collection to be loaded to TCIA.
- KIRC - Kidney renal clear cell carcinoma (KIRC) data is in the early stages of data collection and formation of the TCGA Renal Phenotype Research Group.
Included below are some posters and presentations which help summarize the CIP TCGA Radiology Initiative and its supporting components such as TCIA.
- A Scalable Methodology for Correlating Clinical Imaging Features with TCGA Data - presented at TCGA Network Symposium, November 17-18, Washington, DC
- The Cancer Imaging Archive: a Repository of Advanced Imaging Information Correlated with TCGA Samples - presented at TCGA Network Symposium, November 17-18, Washington, DC