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The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity
Open accessAbstract
The systematic translation of cancer genomic data into knowledge of tumour biology and therapeutic possibilities remains challenging. Such efforts should be greatly aided by robust preclinical model systems that reflect the genomic diversity of human cancers and for which detailed genetic and pharmacological annotation is available. Here we describe the Cancer Cell Line Encyclopedia (CCLE): a compilation of gene expression, chromosomal copy number and massively parallel sequencing data from 947 human cancer cell lines. When coupled with pharmacological profiles for 24 anticancer drugs across 479 of the cell lines, this collection allowed identification of genetic, lineage, and gene-expression-based predictors of drug sensitivity. In addition to known predictors, we found that plasma cell lineage correlated with sensitivity to IGF1 receptor inhibitors; AHR expression was associated with MEK inhibitor efficacy in NRAS-mutant lines; and SLFN11 expression predicted sensitivity to topoisomerase inhibitors. Together, our results indicate that large, annotated cell-line collections may help to enable preclinical stratification schemata for anticancer agents. The generation of genetic predictions of drug response in the preclinical setting and their incorporation into cancer clinical trial design could speed the emergence of 'personalized' therapeutic regimens.
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In the citing paper
“The CCLE dataset has previously been used to identify biomarkers for drug resistance and susceptibility (Barretina et al., 2012).”
From Efficient Parameter Estimation Enables the Prediction of Drug Response Using a Mechanistic Pan-Cancer Pathway Model (2018) · cites this paper as Barretina et al., 2012
In the citing paper
“JDQ443 antiproliferative activity was assessed by a high-throughput cell viability assay in a large panel of KRASG12C-mutated (N = 17) and non–G12C-mutated (N = 225) cell lines from the Cancer Cell Line Encyclopedia (29). JDQ443 demonstrated potent antiproliferative activity selectively toward the KRASG12C-mutated lines (Fig. 2A and B).”
In the citing paper
“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 [69]
In the citing paper
“Large-scale efforts aimed at linking tumor genomic alterations with sensitivity to cytotoxic and targeted therapies have uncovered a wealth of pharmacogenomic interactions in NSCLC and other cancer types149–152.”
From Co-occurring genomic alterations in non-small-cell lung cancer biology and therapy (2019) · cites this paper as [151]
In the citing paper
“interrogation of the expression data from the cancer cell line encyclopedia20 (CCLE) database revealed that classical SCLC cell lines have significantly reduced levels of EGFR mRNA compared with adenocarcinoma cell lines”
From RB loss in resistant EGFR mutant lung adenocarcinomas that transform to small-cell lung cancer (2015) · cites this paper as [20]
In the citing paper
“Other expression datasets integrated into the latest version are the Cancer Cell Line Encyclopedia (16) and cell perturbation expression data from the Library of Integrated Network-Based Cellular Signatures (17).”
From TCRD and pharos 2021: mining the human proteome for disease biology (2021) · cites this paper as [16]
In the citing paper
“The Passport model name is accompanied by synonyms and most importantly unique identifiers utilized by established resources such as Research Resource Identifiers (RRID) (19), the Catalogue of Somatic Mutations in Cancer (COSMIC) (20) and CCLE (6) to aid data integration and alignment.”
From Cell Model Passports-a hub for clinical, genetic and functional datasets of preclinical cancer models (2019) · cites this paper as [6]
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Cites
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Metadata
- Authors
- Barretina, J., Caponigro, G., Stransky, N., Venkatesan, K., Margolin, A. A., Kim, S., Wilson, C. J., Lehár, J., Kryukov, G. V., Sonkin, D., Reddy, A., Liu, M., Murray, L., Berger, M. F., Monahan, J. E., Morais, P., Meltzer, J., Korejwa, A., Jané-Valbuena, J., Mapa, F. A., Thibault, J., Bric-Furlong, E., Raman, P., Shipway, A., Engels, I. H., Cheng, J., Yu, G. K., Yu, J., Aspesi, P., de Silva, M., Jagtap, K., Jones, M. D., Wang, L., Hatton, C., Palescandolo, E., Gupta, S., Mahan, S., Sougnez, C., Onofrio, R. C., Liefeld, T., MacConaill, L., Winckler, W., Reich, M., Li, N., Mesirov, J. P., Gabriel, S. B., Getz, G., Ardlie, K., Chan, V., Myer, V. E., Weber, B. L., Porter, J., Warmuth, M., Finan, P., Harris, J. L., Meyerson, M., Golub, T. R., Morrissey, M. P., Sellers, W. R., Schlegel, R., & Garraway, L. A.
- Affiliations
- Broad Institute (US)
- Genomics Institute of the Novartis Research Foundation (US)
- Harvard University (US)
- Corresponding author
- Schlegel, Robert
- Garraway, Levi A.
- ORCID
- Barretina, Jordi
- Stransky, Nicolas
- Venkatesan, Kavitha
- Wilson, Christopher J.
- Lehár, Joseph
- Kryukov, Gregory V.
- Sonkin, Dmitriy
- Reddy, Anupama
- Liu, Manway
- Murray, Lauren
- Berger, Michael F.
- Monahan, John E.
- Mapa, Felipa A.
- Raman, Pichai
- Yu, Guoying K.
- Yu, Jianjun
- Aspesi, Peter
- Jones, Michael D.
- Wang, Li
- Gupta, Supriya
- Liefeld, Ted
- MacConaill, Laura
- Winckler, Wendy
- Reich, Michael
- Li, Nanxin
- Mesirov, Jill P.
- Gabriel, Stacey B.
- Getz, Gad
- Ardlie, Kristin
- Chan, Vivien
- Myer, Vic E.
- Weber, Barbara L.
- Meyerson, Matthew
- Golub, Todd R.
- Sellers, William R.
- Garraway, Levi A.
- Venue
- Nature
- Published
- 2012-03-28
- Volume
- 483
- Issue
- 7391
- Pages
- 603-607
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC3320027
- OpenAlex
- W2043398720
- Cited by
- 7,950
- References
- 28
- Citations by year
- 2026: 361 · 2025: 501 · 2024: 617 · 2023: 719 · 2022: 723 · 2021: 839 · 2020: 682 · 2019: 687 · 2018: 628 · 2017: 500 · 2016: 516 · 2015: 436 · 2014: 348 · 2013: 283 · 2012: 103
- FWCI
- 124.24
- Type
- journal article
- Language
- en
- Update notices
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- National Institutes of Health (DP2OD002750)
- National Human Genome Research Institute (U54HG003067)
- National Cancer Institute (R33CA155554, R33CA126674)
- National Institute of General Medical Sciences (R01GM074024)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Drug Discovery › Computational Drug Discovery Methods
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Chromatin Remodeling and Cancer
- Keywords
- Cancer Cell Line Encyclopedia, anticancer drug sensitivity, drug resistance, cancer cell lines, Ewing sarcoma, PARP inhibitors, SLFN11, topoisomerase inhibitors, MEK inhibitors, NRAS mutation, aryl hydrocarbon receptor, gene expression profiles, chromosomal copy number, predictive modeling, precision oncology
- MeSH terms
- Antineoplastic Agents, Chromosomes, Human, Clinical Trials as Topic, Drug Screening Assays, Antitumor, Encyclopedias as Topic, Humans, Models, Biological, Neoplasms, Pharmacogenetics, Plasma Cells, Genes, ras, Genome, Human, Gene Expression Regulation, Neoplastic, Databases, Factual, Sequence Analysis, DNA, Receptor, IGF Type 1, Receptors, Aryl Hydrocarbon, Cell Lineage, Gene Expression Profiling, Mitogen-Activated Protein Kinase Kinases, Genomics, Cell Line, Tumor, Precision Medicine, Topoisomerase Inhibitors
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