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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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The Evolving Genomic Landscape of Esophageal Squamous Cell Carcinoma Under Chemoradiotherapy
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Bekele, R. T., Samant, A. S., Nassar, A. H., So, J., Garcia, E. P., Curran, C. R., Hwang, J. H., Mayhew, D. L., Nag, A., Thorner, A. R., et al. (2021) · Journal of Clinical Investigation · doi:10.1172/jci147849 · Cited by 39
CDT1 Is a Novel Prognostic and Predictive Biomarkers for Hepatocellular Carcinoma
Cai, C., Zhang, Y., Hu, X., Hu, W., Yang, S., Qiu, H., & Chu, T. (2021) · Frontiers in Oncology · doi:10.3389/fonc.2021.721644 · Cited by 37
Cancer catecholamine conundrum
Wackerhage, H., Christensen, J. F., Ilmer, M., von Luettichau, I., Renz, B. W., & Schönfelder, M. (2021) · Trends in cancer · doi:10.1016/j.trecan.2021.10.005 · Cited by 36
Comparative optimization of combinatorial CRISPR screens
Li, R., Klingbeil, O., Monducci, D., Young, M. J., Rodriguez, D. J., Bayyat, Z., Dempster, J. M., Kesar, D., Yang, X., Zamanighomi, M., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-30196-9 · Cited by 37
Self-citationReversal of viral and epigenetic HLA class I repression in Merkel cell carcinoma
Lee, P. C., Klaeger, S., Le, P. M., Korthauer, K. D., Cheng, J., Ananthapadmanabhan, V., Frost, T. C., Stevens, J. D., Wong, A. Y. L., Iorgulescu, J. B., et al. (2022) · Journal of Clinical Investigation · doi:10.1172/jci151666 · Cited by 38
“(H) Unsupervised clustering by Euclidian distance of RNA-Seq expression values of class I pathway genes and MYC family genes across all cancer cell lines in the Cancer Cell Line Encyclopedia (44).”
InfluentialAchreja, A., Yu, T., Mittal, A., Choppara, S., Animasahun, O. H., Nenwani, M., Wuchu, F., Meurs, N., Mohan, A., Jeon, J. H., et al. (2022) · Nature Metabolism · doi:10.1038/s42255-022-00636-3 · Cited by 33
Buikhuisen, J. Y., Gomez Barila, P. M., Torang, A., Dekker, D., de Jong, J. H., Cameron, K., Vitale, S., Stassi, G., van Hooff, S. R., Castro, M. A. A., et al. (2021) · Cancers · doi:10.3390/cancers13040801 · Cited by 33
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“The CCLE is a collection of ~1000 cancer cell lines, on which multiple omics measurements were made in order to elucidate the mechanisms of different cancers [28].”
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Gene Expression Profiles in Cancers and Their Therapeutic Implications
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“In addition, we found that the abundance of 1-MNA (the end product of the NNMT-catalyzed reaction) was generally low in luminal compared to basal-like breast cancer cell lines (Fig EV1E; Sarri (cid:2) o et al , 2008; Ghandi et al , 2019).”
Molecular Characterization and Landscape of Breast cancer Models from a multi-omics Perspective
Ortiz, M. M. O., & Andrechek, E. R. (2023) · Journal of Mammary Gland Biology and Neoplasia · doi:10.1007/s10911-023-09540-2 · Cited by 35
Ramberger, E., Sapozhnikova, V., Ng, Y. L. D., Dolnik, A., Ziehm, M., Popp, O., Sträng, E., Kull, M., Grünschläger, F., Krüger, J., et al. (2024) · Nature Cancer · doi:10.1038/s43018-024-00784-3 · Cited by 47
“2f) 28,29 .”
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Hao, Q., Zong, X., Sun, Q., Lin, Y.-C., Song, Y. J., Hashemikhabir, S., Hsu, R. Y. C., Kamran, M. Z., Chaudhary, R., Tripathi, V., et al. (2020) · eLife · doi:10.7554/elife.55102 · Cited by 35
Vulnerability to low-dose combination of irinotecan and niraparib in ATM-mutated colorectal cancer
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Inhibition of relaxin autocrine signaling confers therapeutic vulnerability in ovarian cancer
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MCM2-7 complex is a novel druggable target for neuroendocrine prostate cancer
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Identifying novel therapeutic targets in gastric cancer using genome-wide CRISPR-Cas9 screening
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Precision Combination Therapies Based on Recurrent Oncogenic Coalterations
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Self-citationWEE1 inhibition induces glutamine addiction in T-cell acute lymphoblastic leukemia
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Identifying the genes impacted by cell proliferation in proteomics and transcriptomics studies
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“) [13], normalized gene expression levels in TPM (transcripts per million) units were obtained from the DepMap portal (depmap.”
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“Using CCLE-derived expression data for these lines (43), it was found that the PC1-positive genes were more highly expressed at baseline in insensitive cell lines ( Fig.”
MethodA consensus platform for antibody characterization
Ayoubi, R., Ryan, J., Bolívar, S. G., Alende, C., Moleón, V. R., Fotouhi, M., Alqazzaz, M., Southern, K., Alshafie, W., Baker, M. R., et al. (2024) · Nature Protocols · doi:10.1038/s41596-024-01095-8 · Cited by 35
“Assessment of target expression in each cell line is conducted using RNA sequencing data accessible via the Cancer Dependency Map Portal (DepMap (https://depmap.org); RRID: SCR_017655), which offers transcriptomic profiles for over a thousand cancer cell lines 35 .”
Computational frameworks transform antagonism to synergy in optimizing combination therapies
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“Drawing from DrugComb 39 , Chemical Database, and Enzymes of the BioMolecular General Repository Laboratory 40 , HuRI 41 , and Cancer Cell Line Encyclopedia 42 , DGSSynADR leverages comprehensive drug interaction data and multi-omics information to power its predictions 38 .”
Holding on to Junk Bonds: Intron Retention in Cancer and Therapy
Monteuuis, G., Schmitz, U., Petrova, V., Kearney, P. S., & Rasko, J. E. J. (2020) · Cancer Research · doi:10.1158/0008-5472.can-20-1943 · Cited by 34
Vlachavas, E., Bohn, J. R., Ückert, F., & Nürnberg, S. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22062822 · Cited by 37
Pyko, J., Rosemann, J., Müller, L., Kappler, M., Eckert, A. W., Glaß, M., Misiak, D., Hüttelmaier, S., Ballhausen, W. G., Hatzfeld, M., et al. (2021) · Molecular Cancer · doi:10.1186/s12943-021-01384-w · Cited by 34
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
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