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- Title
Assessing the clinical utility of cancer genomic and proteomic data across tumor types.
- Authors
Yuan, Yuan; Van Allen, Eliezer M; Omberg, Larsson; Wagle, Nikhil; Amin-Mansour, Ali; Sokolov, Artem; Byers, Lauren A; Xu, Yanxun; Hess, Kenneth R; Diao, Lixia; Han, Leng; Huang, Xuelin; Lawrence, Michael S; Weinstein, John N; Stuart, Josh M; Mills, Gordon B; Garraway, Levi A; Margolin, Adam A; Getz, Gad; Liang, Han
- Abstract
Molecular profiling of tumors promises to advance the clinical management of cancer, but the benefits of integrating molecular data with traditional clinical variables have not been systematically studied. Here we retrospectively predict patient survival using diverse molecular data (somatic copy-number alteration, DNA methylation and mRNA, microRNA and protein expression) from 953 samples of four cancer types from The Cancer Genome Atlas project. We find that incorporating molecular data with clinical variables yields statistically significantly improved predictions (FDR < 0.05) for three cancers but those quantitative gains were limited (2.2-23.9%). Additional analyses revealed little predictive power across tumor types except for one case. In clinically relevant genes, we identified 10,281 somatic alterations across 12 cancer types in 2,928 of 3,277 patients (89.4%), many of which would not be revealed in single-tumor analyses. Our study provides a starting point and resources, including an open-access model evaluation platform, for building reliable prognostic and therapeutic strategies that incorporate molecular data.
- Subjects
CANCER genetics; PROTEOMICS; PROTEIN expression; CANCER treatment; DNA methylation; DNA copy number variations; MICRORNA genetics
- Publication
Nature Biotechnology, 2014, Vol 32, Issue 7, p644
- ISSN
1087-0156
- Publication type
Article
- DOI
10.1038/nbt.2940