Next-generation characterization of the Cancer Cell Line Encyclopedia
By Mahmoud Ghandi, F. Huang, Judit Jané-Valbuena, G. Kryukov, Christopher C. Lo, E. McDonald, J. Barretina, Ellen T. Gelfand, C. Bielski, Haoxin Li and 58 more. Nature, 2019
2,830 citations recorded by the source corpus.
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.
Subfields: Cancer Research, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/b3631d8d2656c0c72ad92f3b0a77af2afde649a5
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Citations in the corpus
- Quantitative Proteomics of the Cancer Cell Line Encyclopedia (2020, neutral): “The SKI complex, LTN1, RPL22, and RPL22L1 are resident on the ribosome.”
- Empowering Biomedical Discovery with AI Agents (2024, neutral): “…omics, super-resolution microscopy, and gene editing have generated datasets on normal and perturbed cells, covering areas such as multi-omics [98– 100], cell viability [101], morphology [102], cryo-electron microscopy and tomography [103, 104], and multiplexed spatial proteomics [105, 106].”
- The high mobility group protein HMG20A cooperates with the histone reader PHF14 to modulate TGFβ and Hippo pathways (2022, background): “Publicly available databases used in our analysis included the DepMap portal (21Q3 data release; https://depmap. org/), the CCLE portal (https://portals.broadinstitute. org/ccle), the TCGA Research Network (https://www. cancer.gov/tcga), the MSigDB database (https://www.gseamsigdb.org/gsea/msigdb/),”