The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Assessing the clinical utility of cancer genomic and proteomic data across tumor types
Open accessAbstract
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.
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Comprehensive genomic characterization defines human glioblastoma genes and core pathways
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Comprehensive genomic characterization of squamous cell lung cancers
The Cancer Genome Atlas Research Network (2012) · Nature · doi:10.1038/nature11404 · Cited by 3,994
Comprehensive molecular characterization of clear cell renal cell carcinoma
The Cancer Genome Atlas Research Network (2013) · Nature · doi:10.1038/nature12222 · Cited by 3,485
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Wagle, N., Van Allen, E. M., Treacy, D. J., Frederick, D. T., Cooper, Z. A., Taylor-Weiner, A., Rosenberg, M., Goetz, E. M., Sullivan, R. J., Farlow, D. N., et al. (2014) · Cancer Discovery · doi:10.1158/2159-8290.cd-13-0631 · Cited by 478
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Self-citationThe landscape of genomic alterations across childhood cancers
ICGC PedBrain-Seq Project, Gröbner, S. N., ICGC MMML-Seq Project, Worst, B. C., Weischenfeldt, J., Buchhalter, I., Kleinheinz, K., Rudneva, V. A., Johann, P. D., Balasubramanian, G. P., et al. (2018) · Nature · doi:10.1038/nature25480 · Cited by 1,572
Subclonal diversification of primary breast cancer revealed by multiregion sequencing
Yates, L. R., Gerstung, M., Knappskog, S., Desmedt, C., Gundem, G., Van Loo, P., Aas, T., Alexandrov, L. B., Larsimont, D., Davies, H., et al. (2015) · Nature Medicine · doi:10.1038/nm.3886 · Cited by 816
Pan-cancer analysis of the extent and consequences of intratumor heterogeneity
Andor, N., Graham, T. A., Jansen, M., Xia, L. C., Aktipis, C. A., Petritsch, C., Ji, H. P., & Maley, C. C. (2016) · Nature Medicine · doi:10.1038/nm.3984 · Cited by 768
A pan-cancer proteomic perspective on The Cancer Genome Atlas
Akbani, R., Ng, P. K. S., Werner, H. M. J., Shahmoradgoli, M., Zhang, F., Ju, Z., Liu, W., Yang, J.-Y., Yoshihara, K., Li, J., et al. (2014) · Nature Communications · doi:10.1038/ncomms4887 · Cited by 607
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Metadata
- Authors
- Yuan, Y., Van Allen, E. M., Omberg, L., Wagle, N., Amin-Mansour, A., Sokolov, A., Byers, L. A., Xu, Y., Hess, K. R., Diao, L., Han, L., Huang, X., Lawrence, M. S., Weinstein, J. N., Stuart, J. M., Mills, G. B., Garraway, L. A., Margolin, A. A., Getz, G., & Liang, H.
- Venue
- Nature Biotechnology
- Published
- 2014-06-22
- Volume
- 32
- Issue
- 7
- Pages
- 644-652
- ISSN
- 0733-222X (ISSN-L)
- 1087-0156
- 1546-1696
- OpenAlex
- W2130448611
- Cited by
- 280
- References
- 7
- FWCI
- 11.76
- Type
- journal article
- Language
- en
- Open access
- green
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- The paper
- Yuan, Y., Van Allen, E. M., Omberg, L., Wagle, N., Amin-Mansour, A., Sokolov, A., Byers, L. A., Xu, Y., Hess, K. R., Diao, L., Han, L., Huang, X., Lawrence, M. S., Weinstein, J. N., Stuart, J. M., Mills, G. B., Garraway, L. A., Margolin, A. A., Getz, G., & Liang, H. (2014). Assessing the clinical utility of cancer genomic and proteomic data across tumor types. Nature Biotechnology. https://doi.org/10.1038/nbt.2940
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