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An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

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 co...

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Autores principales: Liu, Jianfang, Lichtenberg, Tara, Hoadley, Katherine A., Poisson, Laila M., Lazar, Alexander J., Cherniack, Andrew D., Kovatich, Albert J., Benz, Christopher C., Levine, Douglas A., Lee, Adrian V., Omberg, Larsson, Wolf, Denise M., Shriver, Craig D., Thorsson, Vesteinn, Hu, Hai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6066282/
https://www.ncbi.nlm.nih.gov/pubmed/29625055
http://dx.doi.org/10.1016/j.cell.2018.02.052
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author Liu, Jianfang
Lichtenberg, Tara
Hoadley, Katherine A.
Poisson, Laila M.
Lazar, Alexander J.
Cherniack, Andrew D.
Kovatich, Albert J.
Benz, Christopher C.
Levine, Douglas A.
Lee, Adrian V.
Omberg, Larsson
Wolf, Denise M.
Shriver, Craig D.
Thorsson, Vesteinn
Hu, Hai
author_facet Liu, Jianfang
Lichtenberg, Tara
Hoadley, Katherine A.
Poisson, Laila M.
Lazar, Alexander J.
Cherniack, Andrew D.
Kovatich, Albert J.
Benz, Christopher C.
Levine, Douglas A.
Lee, Adrian V.
Omberg, Larsson
Wolf, Denise M.
Shriver, Craig D.
Thorsson, Vesteinn
Hu, Hai
author_sort Liu, Jianfang
collection PubMed
description 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.
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spelling pubmed-60662822019-04-05 An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics Liu, Jianfang Lichtenberg, Tara Hoadley, Katherine A. Poisson, Laila M. Lazar, Alexander J. Cherniack, Andrew D. Kovatich, Albert J. Benz, Christopher C. Levine, Douglas A. Lee, Adrian V. Omberg, Larsson Wolf, Denise M. Shriver, Craig D. Thorsson, Vesteinn Hu, Hai Cell Article 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. 2018-04-05 /pmc/articles/PMC6066282/ /pubmed/29625055 http://dx.doi.org/10.1016/j.cell.2018.02.052 Text en This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/ (http://http://creativecommons.org/licenses/by-nc-nd/4.0/) ).
spellingShingle Article
Liu, Jianfang
Lichtenberg, Tara
Hoadley, Katherine A.
Poisson, Laila M.
Lazar, Alexander J.
Cherniack, Andrew D.
Kovatich, Albert J.
Benz, Christopher C.
Levine, Douglas A.
Lee, Adrian V.
Omberg, Larsson
Wolf, Denise M.
Shriver, Craig D.
Thorsson, Vesteinn
Hu, Hai
An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics
title An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics
title_full An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics
title_fullStr An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics
title_full_unstemmed An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics
title_short An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics
title_sort integrated tcga pan-cancer clinical data resource to drive high-quality survival outcome analytics
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6066282/
https://www.ncbi.nlm.nih.gov/pubmed/29625055
http://dx.doi.org/10.1016/j.cell.2018.02.052
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