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Next-generation characterization of the Cancer Cell Line Encyclopedia
Open accessAbstract
Large panels of comprehensively characterized human cancer models, including the Cancer Cell Line Encyclopedia (CCLE), have provided a rigorous framework with which to study genetic variants, candidate targets, and small-molecule and biological therapeutics and to identify new marker-driven cancer dependencies. To improve our understanding of the molecular features that contribute to cancer phenotypes, including drug responses, here we have expanded the characterizations of cancer cell lines to include genetic, RNA splicing, DNA methylation, histone H3 modification, microRNA expression and reverse-phase protein array data for 1,072 cell lines from individuals of various lineages and ethnicities. Integration of these data with functional characterizations such as drug-sensitivity, short hairpin RNA knockdown and CRISPR–Cas9 knockout data reveals potential targets for cancer drugs and associated biomarkers. Together, this dataset and an accompanying public data portal provide a resource for the acceleration of cancer research using model cancer cell lines. The original Cancer Cell Line Encyclopedia (CCLE) is expanded with deeper characterization of over 1,000 cell lines, including genomic, transcriptomic, and proteomic data, and integration with drug-sensitivity and gene-dependency data.
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“Through systematic mining of databases for correlations between the cytotoxicity of 4,518 clinical and pre-clinical small molecules and E3 ligase expression levels across hundreds of human cancer cell lines,3–5 we identified CR8, a cyclin-dependent kinase (CDK) inhibitor,6 as a compound that acts as a molecular glue degrader.”
From The CDK inhibitor CR8 acts as a molecular glue degrader that depletes cyclin K (2020) · cites this paper as [5]
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Metadata
- Authors
- 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., Hu, K., Andreev-Drakhlin, A. Y., Kim, J., Hess, J. M., Haas, B. J., Aguet, F., Weir, B. A., Rothberg, M. V., Paolella, B. R., Lawrence, M. S., Akbani, R., Lu, Y., Tiv, H. L., Gokhale, P. C., de Weck, A., Mansour, A. A., Oh, C., Shih, J., Hadi, K., Rosen, Y., Bistline, J., Venkatesan, K., Reddy, A., Sonkin, D., Liu, M., Lehar, J., Korn, J. M., Porter, D. A., Jones, M. D., Golji, J., Caponigro, G., Taylor, J. E., Dunning, C. M., Creech, A. L., Warren, A. C., McFarland, J. M., Zamanighomi, M., Kauffmann, A., Stransky, N., Imielinski, M., Maruvka, Y. E., Cherniack, A. D., Tsherniak, A., Vazquez, F., Jaffe, J. D., Lane, A. A., Weinstock, D. M., Johannessen, C. M., Morrissey, M. P., Stegmeier, F., Schlegel, R., Hahn, W. C., Getz, G., Mills, G. B., Boehm, J. S., Golub, T. R., Garraway, L. A., & Sellers, W. R.
- Affiliations
- Broad Institute (US)
- The University of Texas MD Anderson Cancer Center (US)
- Cornell University (US)
- National Cancer Institute (US)
- Novartis Institutes for BioMedical Research (CH)
- Dana-Farber Cancer Institute (US)
- Corresponding author
- Sellers, William R.
- ORCID
- Ghandi, Mahmoud
- Huang, Franklin W.
- Kryukov, Gregory V.
- McDonald, E. Robert
- Barretina, Jordi
- Li, Haoxin
- Hu, Kevin
- Andreev-Drakhlin, Alexander Y.
- Kim, Jaegil
- Hess, Julian M.
- Haas, Brian J.
- Aguet, François
- Rothberg, Michael V.
- Paolella, Brenton R.
- Lawrence, Michael S.
- Akbani, Rehan
- Lu, Yiling
- Tiv, Hong L.
- Gokhale, Prafulla C.
- Oh, Coyin
- Shih, Juliann
- Hadi, Kevin
- Rosen, Yanay
- Venkatesan, Kavitha
- Reddy, Anupama
- Sonkin, Dmitriy
- Liu, Manway
- Korn, Joshua M.
- Jones, Michael D.
- Taylor, Jordan E.
- Creech, Amanda L.
- McFarland, James M.
- Zamanighomi, Mahdi
- Kauffmann, Audrey
- Stransky, Nicolas
- Imielinski, Marcin
- Maruvka, Yosef E.
- Cherniack, Andrew D.
- Tsherniak, Aviad
- Jaffe, Jacob D.
- Lane, Andrew A.
- Weinstock, David M.
- Johannessen, Cory M.
- Stegmeier, Frank
- Hahn, William C.
- Getz, Gad
- Mills, Gordon B.
- Boehm, Jesse S.
- Golub, Todd R.
- Garraway, Levi A.
- Sellers, William R.
- Venue
- Nature
- Published
- 2019-05
- Volume
- 569
- Issue
- 7757
- Pages
- 503-508
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC6697103
- OpenAlex
- W2944727022
- Semantic Scholar
- b3631d8d2656c0c72ad92f3b0a77af2afde649a5
- Cited by
- 3,394
- References
- 67
- Citations by year
- 2026: 297 · 2025: 472 · 2024: 560 · 2023: 551 · 2022: 550 · 2021: 594 · 2020: 306 · 2019: 59
- FWCI
- 121.99
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- European Hematology Association (TRTH56)
- National Institutes of Health (5r21da025720-02)
- National Institute on Drug Abuse (R21-DA025720)
- National Cancer Institute (R50CA221675, P50CA217685, R01CA219943, P50CA098258, U24CA180922, U54CA224068, U24CA210949, U24CA210950, R50CA211461, R37CA225191, U01CA217842, U01CA176058, P30CA016672)
- Topics
- 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
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
- Keywords
- Cancer Cell Line Encyclopedia, cancer cell lines, drug sensitivity, gene dependency, RNA splicing, DNA methylation, histone H3 modifications, microRNA expression, reverse phase protein array, CRISPR/Cas9 knockout, shRNA knockdown, therapeutic target, biomarkers, multi-omics integration, public data portals
- MeSH terms
- Gene Editing, Antineoplastic Agents, Ethnicity, Histones, Humans, Neoplasms, RNA Splicing, Biomarkers, Tumor, Drug Resistance, Neoplasm, DNA Methylation, MicroRNAs, Protein Array Analysis, Cell Line, Tumor, Molecular Targeted Therapy
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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