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

Publication date

2018-04-05

Authors

Liu, Jianfang
Lichtenberg, Tara M.
Hoadley, Katherine A.
Poisson, Laila M.
Lazar, Alexander J.
Cherniack, Andrew D.
Kovatich, Albert J.
Benz, Christopher
Levine, Douglas A.
Lee, Adrian V.

Editors

Advisors

Supervisors

Document Type

Article

Collections

Open Access logo

License

cc_by_nc_nd

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. 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.

Keywords

clinical data resource, Cox proportional hazards regression model, disease-free interval, disease-specific survival, follow-up time, overall survival, progression-free interval, TCGA, The Cancer Genome Atlas, translational research, General Biochemistry,Genetics and Molecular Biology

Citation

Liu, J, Lichtenberg, T M, Hoadley, K A, Poisson, L M, Lazar, A J, Cherniack, A D, Kovatich, A J, Benz, C, Levine, D A, Lee, A V, Omberg, L, Wolf, D M, Shriver, C D, Thorsson, V, Caesar-Johnson, S J, Demchok, J A, Felau, I, Kasapi, M, Ferguson, M L, Hutter, C M, Sofia, H J, Tarnuzzer, R, Wang, Z, Yang, L, Zenklusen, J C, Zhang, J, Chudamani, S, Liu, J, Lolla, L, Naresh, R, Pihl, T, Sun, Q, Wan, Y, Wu, Y, Cho, J, DeFreitas, T, Frazer, S, Gehlenborg, N, Getz, G, Heiman, D I, Kim, J, Lawrence, M S, Lin, P, Meier, S, Noble, M S, Saksena, G, Voet, D, Zhang, H, Bernard, B, de Krijger, R & The Cancer Genome Atlas Research Network 2018, 'An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics', Cell, vol. 173, no. 2, pp. 400-416.e11. https://doi.org/10.1016/j.cell.2018.02.052