TY - JOUR
T1 - An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics
AU - The Cancer Genome Atlas Research Network
AU - Liu, Jianfang
AU - Lichtenberg, Tara
AU - Hoadley, Katherine A.
AU - Poisson, Laila M.
AU - Lazar, Alexander J.
AU - Cherniack, Andrew D.
AU - Kovatich, Albert J.
AU - Benz, Christopher C.
AU - Levine, Douglas A.
AU - Lee, Adrian V.
AU - Liu, Yuexin
AU - Zhang, Wei
AU - Akbani, Rehan
AU - Broom, Bradley M.
AU - Ju, Zhenlin
AU - Kanchi, Rupa S.
AU - Korkut, Anil
AU - Li, Jun
AU - Liang, Han
AU - Ling, Shiyun
AU - Liu, Wenbin
AU - Lu, Yiling
AU - Mills, Gordon B.
AU - Rao, Arvind
AU - Weinstein, John N.
AU - Zhang, Jiexin
AU - Liu, Xiuping
AU - Wang, Linghua
AU - Fregnani, José H.
AU - Reis, Rui M.
AU - Ajani, Jaffer A.
AU - Behrens, Carmen
AU - Bondaruk, Jolanta
AU - Broaddus, Russell
AU - Czerniak, Bogdan
AU - Esmaeli, Bita
AU - Fujimoto, Junya
AU - Gershenwald, Jeffrey
AU - Guo, Charles
AU - Logothetis, Christopher
AU - Meric-Bernstam, Funda
AU - Moran, Cesar
AU - Ramondetta, Lois
AU - Rice, David
AU - Sood, Anil
AU - Tamboli, Pheroze
AU - Thompson, Timothy
AU - Troncoso, Patricia
AU - Tsao, Anne
AU - Wistuba, Ignacio
N1 - Publisher Copyright:
© 2018 Elsevier Inc.
PY - 2018/4/5
Y1 - 2018/4/5
N2 - 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. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types.
AB - 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. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types.
KW - Cox proportional hazards regression model
KW - TCGA
KW - The Cancer Genome Atlas
KW - clinical data resource
KW - disease-free interval
KW - disease-specific survival
KW - follow-up time
KW - overall survival
KW - progression-free interval
KW - translational research
UR - http://www.scopus.com/inward/record.url?scp=85044905247&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85044905247&partnerID=8YFLogxK
U2 - 10.1016/j.cell.2018.02.052
DO - 10.1016/j.cell.2018.02.052
M3 - Article
C2 - 29625055
AN - SCOPUS:85044905247
SN - 0092-8674
VL - 173
SP - 400-416.e11
JO - Cell
JF - Cell
IS - 2
ER -