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The Cancer Genome Atlas - Kidney Renal Clear Cell Carcinoma (TCGA-KIRC) data collection is part of a larger effort to enhance the TCGA data set with characterized radiological images. The Cancer Imaging Program (CIP) with the cooperation of several of the TCGA tissue-contributing institutions has archived a large portion of the radiological images of the genetically-analyzed KIRC cases.to build a research community focused on connecting cancer phenotypes to genotypes by providing clinical images matched to subjects from The Cancer Genome Atlas (TCGA). Clinical, genetic, and pathological data resides in
the Genomic Data Commons (GDC) Data Portal while the radiological data is stored on The Cancer Imaging Archive (TCIA).
Matched TCGA patient identifiers in both repositories, allowing allow researchers to explore the TCGA/TCIA databases for correlations between tissue genotype and , radiological phenotype . This collection within TCIA is related to the KIRC disease type within TCGA.and patient outcomes. Tissues for TCGA were collected from many sites all over the world in order to reach their accrual targets, usually around 500 specimens per cancer type. For this reason the image data sets are also extremely heterogeneous in terms of scanner modalities, manufacturers and acquisition protocols. In most cases the images were acquired as part of routine care and not as part of a controlled research study or clinical trial.
CIP TCGA Radiology Initiative
The CIP is supporting multiple projects within the academic community to encourage cross disciplinary research which utilizes the data provided in these resources. More can be learned about this effort on the Imaging Source Site (ISS) Groups are being populated and governed by participants from institutions that have provided imaging data to the archive for a given cancer type. Modeled after TCGA analysis groups, ISS groups are given the opportunity to publish a marker paper for a given cancer type per the guidelines in the table above. This opportunity will generate increased participation in building these multi-institutional data sets as they become an open community resource. Learn more about the TCGA Renal Phenotype Research Group page.
We would like to acknowledge the individuals and institutions that have provided data for this collection:
- Memorial Sloan-Kettering Cancer Center, New York, NY - Special thanks to Oguz Akin, MD and Pierre Elnajjar.
- University of Pittsburgh/UPMC, Pittsburgh, PA - Special thanks to Matthew Heller, MD and Rose Jarosz.
- Mayo Clinic, Rochester, MN - Special thanks to Bradley J. Erickson, MD, PhD from the Department of Radiology, Mayo Medical School.
- University of North Carolina, Chapel Hill, NC - Special thanks to J. Keith Smith, M.D., Ph.D. and Shanah Kirk.
- National Cancer Institute, Bethesda, MD - Special thanks to Marston Linehan, M.D. and Rabindra Gautam from the Urologic Oncology Branch.
- M.D. Anderson Cancer Center, Houston TX - Special thanks to Raghu Vikram, M.D., Department of Diagnostic Radiology, and Kimberly M. Garcia, Diagnostic Imaging - Transl. & Clinical Research.
- Roswell Park Cancer Institute, Buffalo NY - Special thanks to Charles Roche, MD; Ermalinda Bonaccio, MD; and Joe Filippini.
Extracted latest release of clinical data (TXT) from theTCGA
GDC Data Portal.
Version 1: Updated 2014/10/09