The DOI matches its Crossref record, with a small difference in title or year; 10 of the 10 references it cites were found in a registry or an index.
Pharmacogenomic agreement between two cancer cell line data sets
Open accessAbstract
Large cancer cell line collections broadly capture the genomic diversity of human cancers and provide valuable insight into anti-cancer drug response. Here we show substantial agreement and biological consilience between drug sensitivity measurements and their associated genomic predictors from two publicly available large-scale pharmacogenomics resources: The Cancer Cell Line Encyclopedia and the Genomics of Drug Sensitivity in Cancer databases.
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“However, large-scale drug sensitivity studies using the MEK and ERK inhibitors did not reveal the same degree of selectivity in KRAS mutant cells (69, 70) (Figure 4).”
From KRAS mutation in pancreatic cancer (2021) · cites this paper as [70]
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“Notably, the majority of KRAS-mutant CRC cell lines exhibit elevated ABCB1 expression (39)”
From The drug efflux pump MDR1 promotes intrinsic and acquired resistance to PROTACs in cancer cells (2022) · cites this paper as [39]
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The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity
Barretina, J., Caponigro, G., Stransky, N., Venkatesan, K., Margolin, A. A., Kim, S., Wilson, C. J., Lehár, J., Kryukov, G. V., Sonkin, D., et al. (2012) · Nature · doi:10.1038/nature11003 · Cited by 7,950
A collection of breast cancer cell lines for the study of functionally distinct cancer subtypes
Neve, R. M., Chin, K., Fridlyand, J., Yeh, J., Baehner, F. L., Fevr, T., Clark, L., Bayani, N., Coppé, J., Tong, F. K., et al. (2006) · Cancer Cell · doi:10.1016/j.ccr.2006.10.008 · Cited by 3,224
Systematic identification of genomic markers of drug sensitivity in cancer cells
Garnett, M. J., Edelman, E. J., Heidorn, S. J., Greenman, C. D., Dastur, A., Lau, K. W., Greninger, P., Thompson, I. R., Luo, X., Soares, J., et al. (2012) · Nature · doi:10.1038/nature11005 · Cited by 2,456
Garraway, L. A., Widlund, H. R., Rubin, M. A., Getz, G., Berger, A. J., Ramaswamy, S., Beroukhim, R., Milner, D. A., Granter, S. R., Du, J., et al. (2005) · Nature · doi:10.1038/nature03664 · Cited by 1,548
Self-citationBRAF mutation predicts sensitivity to MEK inhibition
Solit, D. B., Garraway, L. A., Pratilas, C. A., Sawai, A., Getz, G. A., Basso, A., Ye, Q., Lobo, J. M., She, Y., Osman, I., et al. (2005) · Nature · doi:10.1038/nature04304 · Cited by 1,326
Cell line-based platforms to evaluate the therapeutic efficacy of candidate anticancer agents
Sharma, S. V., Haber, D. A., & Settleman, J. (2010) · Nature reviews. Cancer · doi:10.1038/nrc2820 · Cited by 600
Inconsistency in large pharmacogenomic studies
Haibe-Kains, B., El-Hachem, N., Birkbak, N. J., Jin, A. C., Beck, A. H., Aerts, H. J. W. L., & Quackenbush, J. (2013) · Nature · doi:10.1038/nature12831 · Cited by 499
Predicting drug susceptibility of non–small cell lung cancers based on genetic lesions
Sos, M. L., Michel, K., Zander, T., Weiss, J. M., Frommolt, P., Peifer, M., Li, D., Ullrich, R. T., Koker, M., Fischer, F., et al. (2009) · Journal of Clinical Investigation · doi:10.1172/jci37127 · Cited by 258
Advances in the preclinical testing of cancer therapeutic hypotheses
Caponigro, G., & Sellers, W. R. (2011) · Nature Reviews Drug Discovery · doi:10.1038/nrd3385 · Cited by 165
Comparison and validation of genomic predictors for anticancer drug sensitivity
Papillon‐Cavanagh, S., Jay, N. D., El-Hachem, N., Olsen, C., Bontempi, G., Aerts, H. J. W. L., Quackenbush, J. F., & Haibe‐Kains, B. (2013) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2012-001442 · Cited by 65
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The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity
Barretina, J., Caponigro, G., Stransky, N., Venkatesan, K., Margolin, A. A., Kim, S., Wilson, C. J., Lehár, J., Kryukov, G. V., Sonkin, D., et al. (2012) · Nature · doi:10.1038/nature11003 · Cited by 7,950
Next-generation characterization of the Cancer Cell Line Encyclopedia
Ghandi, M., Huang, F. W., Jané-Valbuena, J., Kryukov, G. V., Lo, C. C., McDonald, E. R., Barretina, J., Gelfand, E. T., Bielski, C. M., Li, H., et al. (2019) · Nature · doi:10.1038/s41586-019-1186-3 · Cited by 3,394
A Landscape of Pharmacogenomic Interactions in Cancer
Iorio, F., Knijnenburg, T. A., Vis, D. J., Bignell, G. R., Menden, M. P., Schubert, M., Aben, N., Gonçalves, E., Barthorpe, S., Lightfoot, H., et al. (2016) · Cell · doi:10.1016/j.cell.2016.06.017 · Cited by 2,090
Genetic and transcriptional evolution alters cancer cell line drug response
Ben-David, U., Siranosian, B., Ha, G., Tang, H., Oren, Y., Hinohara, K., Strathdee, C. A., Dempster, J., Lyons, N. J., Burns, R., et al. (2018) · Nature · doi:10.1038/s41586-018-0409-3 · Cited by 931
Self-citationGrowth rate inhibition metrics correct for confounders in measuring sensitivity to cancer drugs
Hafner, M., Niepel, M., Chung, M., & Sorger, P. K. (2016) · Nature Methods · doi:10.1038/nmeth.3853 · Cited by 681
Metadata
- Authors
- The Cancer Cell Line Encyclopedia Consortium, & The Genomics of Drug Sensitivity in Cancer Consortium
- Venue
- Nature
- Published
- 2015-11-16
- Volume
- 528
- Issue
- 7580
- Pages
- 84-87
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC6343827
- OpenAlex
- W2318806991
- Cited by
- 418
- References
- 10
- Citations by year
- 2026: 17 · 2025: 26 · 2024: 33 · 2023: 37 · 2022: 49 · 2021: 47 · 2020: 38 · 2019: 78 · 2018: 36 · 2017: 37 · 2016: 19
- FWCI
- 31.30
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- RWTH Publications (RWTH Aachen) (submittedVersion)
- Funders
- Wellcome Trust (086357, 102696STRATTON, 102696)
- Cancer Research UK (A16629)
- National Institutes of Health (5u54hg006097-03)
- National Human Genome Research Institute (1U54HG006097-01, U54-HG006097)
- Topics
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Drug Discovery › Computational Drug Discovery Methods
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Chromatin Remodeling and Cancer
- Keywords
- cancer cell lines, drug sensitivity, pharmacogenomics, GDSC, data concordance, anticancer drug response, drug library
- MeSH terms
- Humans, Neoplasms, Pharmacogenetics, Reproducibility of Results, Databases, Factual, Inhibitory Concentration 50, Cell Line, Tumor, Datasets as Topic
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