Journal article
An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics
Cell, Vol.173(2), pp.400-416.e11
04/05/2018
DOI: 10.1016/j.cell.2018.02.052
PMCID: PMC6066282
PMID: 29625055
Abstract
For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale.
Details
- Title: Subtitle
- An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics
- Creators
- Jianfang LiuTara Lichtenberg - Nationwide Children's HospitalKatherine A Hoadley - University of North Carolina at Chapel HillLaila M Poisson - Henry Ford Health SystemAlexander J Lazar - The University of Texas MD Anderson Cancer CenterAndrew D Cherniack - Broad InstituteAlbert J Kovatich - Walter Reed National Military Medical CenterChristopher C Benz - Buck Institute for Research on AgingDouglas A Levine - York UniversityAdrian V Lee - University of PittsburghLarsson Omberg - Sage BionetworksDenise M Wolf - University of California, San FranciscoCraig D Shriver - Walter Reed National Military Medical CenterVesteinn Thorsson - Institute for Systems BiologyHai Hu
- Contributors
- Cancer Genome Atlas Research Network (Contributor)Deqin Ma (Contributor) - University of Iowa, PathologyMohammed M Milhem (Contributor) - University of Iowa, Internal MedicineAaron D Bossler (Contributor) - University of Iowa, Pathology
- Resource Type
- Journal article
- Publication Details
- Cell, Vol.173(2), pp.400-416.e11
- DOI
- 10.1016/j.cell.2018.02.052
- PMID
- 29625055
- PMCID
- PMC6066282
- ISSN
- 0092-8674
- eISSN
- 1097-4172
- Grant note
- U24 CA143843 / NCI NIH HHS U24 CA143867 / NCI NIH HHS U24 CA143858 / NCI NIH HHS U24 CA143882 / NCI NIH HHS P30 CA016086 / NCI NIH HHS U24 CA210957 / NCI NIH HHS U54 HG003067 / NHGRI NIH HHS U24 CA143845 / NCI NIH HHS U54 HG003079 / NHGRI NIH HHS P30 CA016672 / NCI NIH HHS U24 CA143835 / NCI NIH HHS U54 HG003273 / NHGRI NIH HHS U24 CA143840 / NCI NIH HHS P30 ES010126 / NIEHS NIH HHS U24 CA144025 / NCI NIH HHS U24 CA143866 / NCI NIH HHS U24 CA210950 / NCI NIH HHS U24 CA143883 / NCI NIH HHS U24 CA210990 / NCI NIH HHS U24 CA210949 / NCI NIH HHS U24 CA143799 / NCI NIH HHS U24 CA143848 / NCI NIH HHS R01 CA163722 / NCI NIH HHS U24 CA210988 / NCI NIH HHS
- Language
- English
- Date published
- 04/05/2018
- Academic Unit
- Hematology, Oncology, and Blood & Marrow Transplantation; Pathology; Internal Medicine
- Record Identifier
- 9984183985802771
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