The DOI matches its Crossref record; 67 of the 67 references it cites were found in a registry or an index.
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.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The cited source says what the claim attributes to it.
In the citing paper
“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]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
STAR: ultrafast universal RNA-seq aligner
Dobin, A., Davis, C. A., Schlesinger, F., Drenkow, J., Zaleski, C., Jha, S., Batut, P., Chaisson, M., & Gingeras, T. R. (2013) · Bioinformatics · doi:10.1093/bioinformatics/bts635 · Cited by 51,709
limma powers differential expression analyses for RNA-sequencing and microarray studies
Ritchie, M. E., Phipson, B., Wu, D., Hu, Y., Law, C. W., Shi, W., & Smyth, G. K. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv007 · Cited by 40,458
(2008) · Journal of Machine Learning Research · Cited by 33,051
Regularization Paths for Generalized Linear Models via Coordinate Descent
Friedman, J., Hastie, T., & Tibshirani, R. (2010) · Journal of Statistical Software · doi:10.18637/jss.v033.i01 · Cited by 19,927
Cerami, E., Gao, J., Dogrusoz, U., Gross, B. E., Sumer, S. O., Aksoy, B. A., Jacobsen, A., Byrne, C. J., Heuer, M. L., Larsson, E., et al. (2012) · Cancer Discovery · doi:10.1158/2159-8290.cd-12-0095 · Cited by 17,455
Integrative Analysis of Complex Cancer Genomics and Clinical Profiles Using the cBioPortal
Gao, J., Aksoy, B. A., Dogrusoz, U., Dresdner, G., Gross, B., Sumer, S. O., Sun, Y., Jacobsen, A., Sinha, R., Larsson, E., et al. (2013) · Science Signaling · doi:10.1126/scisignal.2004088 · Cited by 15,160
Smyth, G. K. (2004) · Statistical Applications in Genetics and Molecular Biology · doi:10.2202/1544-6115.1027 · Cited by 11,829
STRING v10: protein–protein interaction networks, integrated over the tree of life
Szklarczyk, D., Franceschini, A., Wyder, S., Forslund, K., Heller, D., Huerta-Cepas, J., Simonovic, M., Roth, A., Santos, A., Tsafou, K. P., et al. (2015) · Nucleic Acids Research · doi:10.1093/nar/gku1003 · Cited by 10,436
MicroRNA expression profiles classify human cancers
Lü, J., Getz, G. A., Miska, E. A., Alvarez-Saavedra, E., Lamb, J., Peck, D., Sweet-Cordero, A., Ebert, B. L., Mak, R. H., Ferrando, A. A., et al. (2005) · Nature · doi:10.1038/nature03702 · Cited by 9,637
Self-citationAnalysis of protein-coding genetic variation in 60,706 humans
Exome Aggregation Consortium, Lek, M., Karczewski, K. J., Minikel, E. V., Samocha, K. E., Banks, E., Fennell, T., O’Donnell-Luria, A. H., Ware, J. S., Hill, A. J., et al. (2016) · Nature · doi:10.1038/nature19057 · Cited by 9,587
Self-citation
Cited by
Sorted by citations
Items 601–700 of 1,008
NCAPG promotes the progression of lung adenocarcinoma via the TGF-β signaling pathway
Wu, Y., Lin, Y., Pan, J., Tu, X., Xu, Y., Li, H., & Chen, Y. (2021) · Cancer Cell International · doi:10.1186/s12935-021-02138-w · Cited by 34
Self-citationYang, C., Zhang, Z., Tang, X., Zhang, X., Chen, Y., Hu, T., Zhang, H., Guan, M., Zhang, X., & Wu, Z. (2021) · Human Cell · doi:10.1007/s13577-021-00630-z · Cited by 35
McGrail, D. J., Pilie, P. G., Dai, H., Lam, T., Liang, Y., Voorwerk, L., Kok, M., Zhang, X. H.-F., Rosen, J. M., Heimberger, A. B., et al. (2021) · Science Translational Medicine · doi:10.1126/scitranslmed.abe6201 · Cited by 36
BCAT1: A risk factor in multiple cancers based on a pan‐cancer analysis
Li, G., Huang, H., Liang, Y., Pang, Q., Sun, H., Huang, Z., Dang, Y., Yang, L., & Chen, G. (2022) · Cancer Medicine · doi:10.1002/cam4.4525 · Cited by 35
Systematic review of the receptor tyrosine kinase superfamily in neuroblastoma pathophysiology
Rozen, E. J., & Shohet, J. M. (2021) · Cancer and Metastasis Reviews · doi:10.1007/s10555-021-10001-7 · Cited by 34
Multiplexed and reproducible high content screening of live and fixed cells using Dye Drop
Mills, C. E., Subramanian, K., Hafner, M. A., Niepel, M., Gerosa, L., Chung, M., Victor, C., Gaudio, B. L., Yapp, C., Nirmal, A. J., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-34536-7 · Cited by 30
Ying, B., Xu, W., Nie, Y. G., & Li, Y. (2022) · Disease Markers · doi:10.1155/2022/8446857 · Cited by 34
“CCLE covers the gene expression of thousands of swollen cell lines from dozens of tissues, so it is a sharp tool for tumor research [13].”
BackgroundKrill-Burger, J. M., Dempster, J. M., Borah, A. A., Paolella, B. R., Root, D. E., Golub, T. R., Boehm, J. S., Hahn, W. C., McFarland, J. M., Vázquez, F., et al. (2023) · Genome biology · doi:10.1186/s13059-023-03020-w · Cited by 35
“…large matrix of all predictive features, including datasets released by Cancer Dependency Map (RNAseq, relative copy number, damaging mutation, missense mutation, hotspot mutation, fusion, cell line tissue/disease type) and published CCLE datasets 57,59 (RPPA, total proteomics, metabolomics, RRBS).”
BackgroundSelf-citationcSurvival: a web resource for biomarker interactions in cancer outcomes and in cell lines
Cheng, X., Liu, Y., Wang, J., Chen, Y., Robertson, A. G., Zhang, X., Jones, S. J. M., & Taubert, S. (2022) · Briefings in Bioinformatics · doi:10.1093/bib/bbac090 · Cited by 36
“Third, experimentally derived cancer cell line viability data [38– 40] and multiomics profiling [41] provide valuable in vitro information on genetic dependencies and interactions; however, no existing tool connects clinical data to such experimental studies.”
A Whole-Genome CRISPR Screen Identifies AHR Loss as a Mechanism of Resistance to a PARP7 Inhibitor
Chen, H., Diolaiti, M. E., O’Leary, P. C., Rojc, A., Krogan, N. J., Kim, M., & Ashworth, A. (2022) · Molecular Cancer Therapeutics · doi:10.1158/1535-7163.mct-21-0841 · Cited by 33
Sahoo, S. S., Ramanand, S. G., Gao, Y., Abbas, A., Kumar, A., Cuevas, I., Li, H., Aguilar, M., Xing, C., Mani, R. S., et al. (2022) · Journal of Clinical Investigation · doi:10.1172/jci157574 · Cited by 32
Self-citationYu, J., Feng, H., Sang, Q., Li, F., Chen, M., Yu, B., Xu, Z., Pan, T., Wu, X., Hou, J., et al. (2023) · EBioMedicine · doi:10.1016/j.ebiom.2023.104451 · Cited by 33
“Additionally, the conjoint analysis of the Genomics of Drug Sensitivity in Cancer (GDSC), 34 Cancer Cell Line Encyclopedia (CCLE), 35 and genome CRISPR – Cas9 screens also showed that VPS35 was a differentially expressed gene between the low-and high-erlotinib-sensitive groups and a prognostic gene…”
Genome-guided discovery of cancer therapeutic targets
Konda, P., Garinet, S., Allen, E. M. V., & Viswanathan, S. R. (2023) · Cell Reports · doi:10.1016/j.celrep.2023.112978 · Cited by 36
Ma, X., Wang, Q., Sun, C., Agarwal, I., Wu, H., Chen, J., Zhao, C., Qi, G., Teng, Q., Yuan, C., et al. (2023) · Cell Reports · doi:10.1016/j.celrep.2023.112944 · Cited by 34
Tanaka, A., Ogawa, M., Zhou, Y., Namba, K., Hendrickson, R. C., Miele, M. M., Li, Z., Klimstra, D. S., Buckley, P. G., Gulcher, J. R., et al. (2024) · Cell Reports · doi:10.1016/j.celrep.2024.113810 · Cited by 37
Multi-omics and pharmacological characterization of patient-derived glioma cell lines
Wu, M., Wang, T., Ji, N., Lu, T., Yuan, R., Wu, L., Zhang, J., Li, M., Cao, P., Zhao, J., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-51214-y · Cited by 34
Wang, H., Wang, X., Xu, L., Zhang, J., & Cao, H. (2019) · Aging · doi:10.18632/aging.102349 · Cited by 33
TPL2 enforces RAS-induced inflammatory signaling and is activated by point mutations
Dodhiawala, P. B., Khurana, N., Zhang, D., Cheng, Y., Li, L., Wei, Q., Seehra, K., Jiang, H., Grierson, P. M., Wang‐Gillam, A., et al. (2020) · Journal of Clinical Investigation · doi:10.1172/jci137660 · Cited by 34
Myeloid-derived suppressor cell depletion therapy targets IL-17A-expressing mammary carcinomas
Dawod, B., Liu, J., Gebremeskel, S., Yan, C. W., Sappong‐Kumankumah, A., Johnston, B., Hoskin, D. W., Marshall, J. S., & Wang, J. (2020) · Scientific Reports · doi:10.1038/s41598-020-70231-7 · Cited by 33
N-Terminal Acetyltransferases Are Cancer-Essential Genes Prevalently Upregulated in Tumours
Koufaris, C., & Kirmizis, A. (2020) · Cancers · doi:10.3390/cancers12092631 · Cited by 33
Yap1 Mediates Trametinib Resistance in Head and Neck Squamous Cell Carcinomas
Mudianto, T., Campbell, K. M., Webb, J., Zolkind, P., Skidmore, Z. L., Riley, R., Barnell, E. K., Ozgenc, I., Giri, T., Dunn, G. P., et al. (2021) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-19-4179 · Cited by 33
Expression and prognosis analyses of BUB1, BUB1B and BUB3 in human sarcoma
Long, Z., Wu, T., Tian, Q., Carlson, L., Wang, W., & Wu, G. (2021) · Aging · doi:10.18632/aging.202944 · Cited by 33
Alkhathlan, A. H., AL-Abdulkarim, H. A., Khan, M., Khan, M., Alkholief, M. A., Alshamsan, A., Almomen, A. A., Albekairi, N. A., Alkhathlan, H. Z., & Siddiqui, M. R. H. (2021) · Materials · doi:10.3390/ma14123368 · Cited by 35
Jun, Y., Suh, Y.-S., Park, S., Lee, J., Kim, J.-I., Lee, S., Lee, W.-P., Anczuków, O., Yang, H.-K., & Lee, C. (2021) · Cancer Research · doi:10.1158/0008-5472.can-21-2117 · Cited by 33
“Finally, to explore whether our fi ndings from primary tumors are recapitulated in cell models, we pro fi led splicing patterns as described above using available RNA-seq data from 37 gastric cancer cell lines from CCLE (54).”
Self-citationYang, R., Chen, Z., Liang, L., Ao, S., Zhang, J., Chang, Z., Wang, Z., Zhou, Y., Duan, X., & Deng, T. (2022) · Immunology · doi:10.1111/imm.13557 · Cited by 34
“In addition, we obtained FCER1G mRNA expression data of 947 cell lines representing 32 different cancer types from Cancer Cell Line Encyclopedia [28] (CCLE) database (https://sites.”
MethodBüttner, F., Winter, S., Stühler, V., Rausch, S., Hennenlotter, J., Fuessel, S., Zastrow, S., Meinhardt, M., Toma, M. I., Jerónimo, C., et al. (2022) · Genome Medicine · doi:10.1186/s13073-022-01105-y · Cited by 33
Wang, Z., Yao, J., Dong, T., & Niu, X. (2022) · Journal of Immunology Research · doi:10.1155/2022/2756611 · Cited by 33
“Expression pro fi les and somatic mutation data of the human cancer cell lines (CCLs) were downloaded from the Cancer Cell Line Encyclopedia project [34].”
A functional analysis of 180 cancer cell lines reveals conserved intrinsic metabolic programs
Cherkaoui, S., Durot, S., Bradley, J., Critchlow, S. E., Dubuis, S., Masiero, M. M., Wegmann, R., Snijder, B., Othman, A., Bendtsen, C., et al. (2022) · Molecular Systems Biology · doi:10.15252/msb.202211033 · Cited by 32
“The association analysis was extended to metadata available for many cell lines in CCLE (Ghandi et al, 2019) on cancer type, histology, histology subtype, pathology, or ethnicity of the cancer donor.”
MethodGoh, J. J. H., Goh, C. J. H., Lim, Q. W., Zhang, S., Koh, C.-G., & Chiam, K. (2022) · Scientific Reports · doi:10.1038/s41598-022-24511-z · Cited by 33
McCabe, A., Zaheed, O., McDade, S. S., & Dean, K. A. (2023) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2023.1104514 · Cited by 33
Fu, Z., Rais, Y., Bismar, T. A., Hyndman, M. E., Le, X. C., & Drabovich, A. P. (2021) · Molecular & Cellular Proteomics · doi:10.1016/j.mcpro.2021.100075 · Cited by 32
Allosteric regulation of CAD modulates de novo pyrimidine synthesis during the cell cycle
Shin, J., Mir, H., Khurram, M. A., Fujihara, K. M., Dynlacht, B. D., Cardozo, T. J., & Possemato, R. (2023) · Nature Metabolism · doi:10.1038/s42255-023-00735-9 · Cited by 35
Personalized tumor combination therapy optimization using the single-cell transcriptome
Tang, C., Fu, S., Jin, X., Li, W., Xing, F., Duan, B., Cheng, X., Chen, X., Wang, S., Zhu, C., et al. (2023) · Genome Medicine · doi:10.1186/s13073-023-01256-6 · Cited by 35
“…trajectories related to the modulation of the antitumor immune response, including (1) active T cell exhaustion, (2) memory T cell exhaustion [46], (3) tumor-associated macrophage differentiation, and (4) cancer-associated fibroblast (CAF) differentiation, and defines the trajectory start…”
BackgroundMethodInfluentialRout, T., Mohapatra, A., & Kar, M. (2024) · Network Modeling Analysis in Health Informatics and Bioinformatics · doi:10.1007/s13721-024-00467-0 · Cited by 32
“It provides information on gene expression patterns, genetic mutations, and drug response profiles for different cancer cell lines (Ghandi et al. 2019).”
Mortenson, K. L., Dawes, C., Wilson, E. R., Patchen, N. E., Johnson, H. E., Gertz, J., Bailey, S. D., Yang, J., Varley, K. E., & Zhang, X. (2024) · Nature Communications · doi:10.1038/s41467-024-50387-w · Cited by 35
“Prostate cancer cell lines LNCaP, MDAPCA2B, 22Rv1, and VCaP, ER a -positive breast cancer cell lines ZR751, T47D, and MCF7, lymphoma cell lines REC1 and DOHH2, and lung squamous cell line NCIH2170 were obtained from the Cancer Cell Line Encyclopedia (CCLE) 65,66 .”
InfluentialReprogramming neuroblastoma by diet-enhanced polyamine depletion
Cherkaoui, S., Turn, C. S., Yuan, Y., Lu, W., Yang, L., McBride, M. J., Eigenmann, C., Allen, G. E., Panasenko, O. O., Zhang, L., et al. (2025) · Nature · doi:10.1038/s41586-025-09564-0 · Cited by 36
Leylek, T. R., Jeusset, L. M., Lichtensztejn, Z., & McManus, K. J. (2020) · Scientific Reports · doi:10.1038/s41598-020-57530-9 · Cited by 32
Stern, J. L., Hibshman, G. N., Hu, K., Ferrara, S. E., Costello, J. C., Kim, W., Tamayo, P., Cech, T. R., & Huang, F. W. (2020) · Molecular Cancer Research · doi:10.1158/1541-7786.mcr-19-1244 · Cited by 30
Self-citationO-GlcNAc Transferase – An Auxiliary Factor or a Full-blown Oncogene?
Itkonen, H. M., Loda, M. F., & Mills, I. G. (2021) · Molecular Cancer Research · doi:10.1158/1541-7786.mcr-20-0926 · Cited by 32
Foroutan, M., Molania, R., Pfefferle, A., Behrenbruch, C., Scheer, S., Kallies, A., Speed, T. P., Cursons, J., & Huntington, N. D. (2021) · Cancer Immunology Research · doi:10.1158/2326-6066.cir-21-0137 · Cited by 35
Drugging the undruggable proteins in cancer: A systems biology approach
Pathmanathan, S., Grozavu, I., Lyakisheva, A., & Štagljar, I. (2021) · Current Opinion in Chemical Biology · doi:10.1016/j.cbpa.2021.07.004 · Cited by 33
Kumar, M., Molkentine, D. P., Molkentine, J. M., Bridges, K. A., Xie, T., Yang, L., Hefner, A. J., Gao, M., Bahri, R., Dhawan, A., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-26570-8 · Cited by 34
Lenoir, W. F., Morgado, M. C., DeWeirdt, P. C., McLaughlin, M. E., Griffith, A. L., Sangree, A. K., Feeley, M. N., Anvar, N. E., Kim, E., Bertolet, L. L., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-26867-8 · Cited by 31
Lv, Y., Tang, W., Zhang, Z., Lin, Q., Luo, Y., Zheng, P., Li, K., Jia, X., YuZhi, P., Ji, M., et al. (2022) · Oncogene · doi:10.1038/s41388-022-02284-z · Cited by 32
“To validate the stratified expression trend, CUL9 mRNA levels were compared between TP53 and TP53 cells in the cancer cell line Encyclopedia (CCLE) database [31].”
MethodBioinformatics roadmap for therapy selection in cancer genomics
Jiménez‐Santos, M. J., García‐Martín, S., Torre, C. F., Domenico, T. D., Goméz-López, G., & Al‐Shahrour, F. (2022) · Molecular Oncology · doi:10.1002/1878-0261.13286 · Cited by 35
Zhao, C., Zhang, Z., & Tao, J. (2022) · Frontiers in Oncology · doi:10.3389/fonc.2022.1000993 · Cited by 32
Yang, W., Zhang, M., Zhang, T.-X., Liu, J.-H., Hao, M.-W., Yan, X., Gao, H., Lei, Q.-Y., Cui, J., & Zhou, X. (2024) · JCI Insight · doi:10.1172/jci.insight.178535 · Cited by 31
“To address the resistance of KRAS G12C inhibitors, transcriptomic analyses were carried out using the previously published data from 20 KRAS G12C–mutant cell lines (5–7 , 34 ).”
Oncogenic PKA signaling increases c-MYC protein expression through multiple targetable mechanisms
Chan, G. K. L., Maisel, S., Hwang, Y. C., Pascual, B. C., Wolber, R. R., Vu, P., Patra, K. C., Bouhaddou, M., Kenerson, H. L., Lim, H. C., et al. (2023) · eLife · doi:10.7554/elife.69521 · Cited by 32
“, 2015), Colo741 has an activating BRAF mutation (Ghandi et al., 2019) which may maintain its proliferation even when cMYC expression is blocked.”
BackgroundSWEET: a single-sample network inference method for deciphering individual features in disease
Chen, H., Hsueh, C., Lee, C., Hao, T.-Y., Tu, T.-Y., Chang, L.-Y., Lee, J., & Lin, C. (2023) · Briefings in Bioinformatics · doi:10.1093/bib/bbad032 · Cited by 30
“Analyses of the RNA-seq data of 7177 patient samples from TCGA and of 1101 cell lines from the Cancer Cell Line Encyclopedia (CCLE) project [16] further validated the effectiveness of the SWEET method in characterizing individual features, such as somatic mutation genes (SMGs), mut-driver genes (MDGs) and essential ge…”
MethodDesign and Development of IKZF2 and CK1α Dual Degraders
Miyamoto, D. K., Curnutt, N. M., Park, S., Stavropoulos, A., Kharas, M. G., & Woo, C. M. (2023) · Journal of Medicinal Chemistry · doi:10.1021/acs.jmedchem.3c01736 · Cited by 31
Rossetti, S., Broege, A., Sen, A., Khan, S. A., MacNeil, I. A., Molden, J. S., Kopher, R. A., Schulz, S., & Laing, L. G. (2024) · npj Breast Cancer · doi:10.1038/s41523-024-00648-0 · Cited by 31
“Cell lines ’ driver alterations in PAM pathway genes were identi fi ed by cBioPortal (https://www.cbioportal.org/) analysis of the Cancer Cell Line Encyclopedia (CCLE, Broad 2019 dataset) 64 .”
MethodA genetic basis for sex differences in Xp11 translocation renal cell carcinoma
Achom, M., Sadagopan, A., Bao, C., McBride, F., Li, J., Konda, P., Tourdot, R. W., Xu, Q., Nakhoul, M., Gallant, D. S., et al. (2024) · Cell · doi:10.1016/j.cell.2024.07.038 · Cited by 35
New Frontiers for Molecular Pathology
Domagala-Kulawik, J. J. (2019) · Frontiers in Medicine · doi:10.3389/fmed.2019.00284 · Cited by 31
Nutlin-Induced Apoptosis Is Specified by a Translation Program Regulated by PCBP2 and DHX30
Rizzotto, D., Zaccara, S., Rossi, A., Galbraith, M. D., Andrysík, Z., Pandey, A., Sullivan, K. D., Quattrone, A., Espinosa, J. M., Dassi, E., et al. (2020) · Cell Reports · doi:10.1016/j.celrep.2020.03.011 · Cited by 28
Metabolic pathway alterations in microvascular endothelial cells in response to hypoxia
Cohen, E. B., Geck, R. C., & Toker, A. (2020) · PLoS ONE · doi:10.1371/journal.pone.0232072 · Cited by 30
The foggy world(s) of p63 isoform regulation in normal cells and cancer
Pokorná, Z., Vysloužil, J., Hrabal, V., Vojtĕsek, B., & Coates, P. J. (2021) · The Journal of Pathology · doi:10.1002/path.5656 · Cited by 34
Biological significance of KRAS mutant allele expression in ovarian endometriosis
Yachida, N., Yoshihara, K., Suda, K., Nakaoka, H., Ueda, H., Sugino, K., Yamaguchi, M., Mori, Y., Yamawaki, K., Tamura, R., et al. (2021) · Cancer Science · doi:10.1111/cas.14871 · Cited by 32
Berglund, A., Putney, R. M., Hamaidi, I., & Kim, S. (2021) · Experimental & Molecular Medicine · doi:10.1038/s12276-021-00612-z · Cited by 33
Thomas, L. W., Esposito, C., Morgan, R., Price, S., Young, J., Williams, S. P., Maddalena, L. A., McDermott, U., & Ashcroft, M. A. (2021) · Communications Biology · doi:10.1038/s42003-021-02098-x · Cited by 31
EGFR and PI3K Pathway Activities Might Guide Drug Repurposing in HPV-Negative Head and Neck Cancers
Möck, A., Plath, M. M., Moratin, J., Tapken, M. J., Jäger, D., Krauß, J., Fröhling, S., Heß, J., & Zaoui, K. (2021) · Frontiers in Oncology · doi:10.3389/fonc.2021.678966 · Cited by 31
NSD1: A Lysine Methyltransferase between Developmental Disorders and Cancer
Tauchmann, S., & Schwaller, J. (2021) · Life · doi:10.3390/life11090877 · Cited by 35
Scully, T., KASE, N. G., Gallagher, E. J., & LeRoith, D. (2021) · Scientific Reports · doi:10.1038/s41598-021-97327-y · Cited by 29
Q-omics: Smart Software for Assisting Oncology and Cancer Research
Lee, J., Kim, Y., Jin, S., Yoo, H., Jeong, S., Jeong, E., & Yoon, S. (2021) · Molecules and Cells · doi:10.14348/molcells.2021.0169 · Cited by 31
“Large collateral datasets, including those on mutations, gene expression, drug/RNAi screening and patient survival, are publicly available from diverse resources (Barretina et al., 2012; Cancer Genome Atlas Research Network et al., 2013; Ghandi et al., 2019; Guan et al., 2019; Iorio et al., 2016; Monks et al., 2018; S…”
BackgroundWang, Q., Karvelsson, S. T., Kotronoulas, A., Guðjónsson, Þ., Halldórsson, S., & Rolfsson, Ó. (2021) · Molecular & Cellular Proteomics · doi:10.1016/j.mcpro.2021.100185 · Cited by 30
“A, based on data from an open-source database – CCLE (left) (39), GFPT2 was higher in basal and claudin-low cell lines while lowly expressed in HER2-positive and luminal cell lines.”
MethodSzilágyi, S. S., Amsalem-Zafran, A. R., Shapira, K. E., Ehrlich, M., & Henis, Y. I. (2022) · BMC Biology · doi:10.1186/s12915-022-01252-z · Cited by 31
“The transcript expression level of BMPRII from the Cancer Cell Line Encyclopedia [65] is given in Additional file 2: Table S1.”
BackgroundMethodInfluentialLee, S. H., Yim, S. Y., Jeong, Y. S., Li, Q., Kang, S., Sohn, B. H., Kumar, S. V., Shin, J., Choi, Y. R., Shim, J., et al. (2022) · Hepatology · doi:10.1002/hep.32490 · Cited by 32
“Because antigen- specific T- cell receptor (TCR) repertoire is correlated with clinical response to immune checkpoint blockade immunotherapy (CBI),[41,42] we evaluated TCR repertoires from RNA- seq data.”
MethodSelf-citationSOX17 and PAX8 constitute an actionable lineage-survival transcriptional complex in ovarian cancer
Lin, L., Shi, K., Zhou, S., Cai, M., Zhang, C., Sun, Y., Zang, J., Cheng, L., Ye, K., Ma, P., et al. (2022) · Oncogene · doi:10.1038/s41388-022-02210-3 · Cited by 31
Computational estimation of quality and clinical relevance of cancer cell lines
Trastulla, L., Noorbakhsh, J., Vazquez, F., McFarland, J., & Iorio, F. (2022) · Molecular Systems Biology · doi:10.15252/msb.202211017 · Cited by 31
“…RNA splicing, DNA methylation, microRNA expression, global histone modifications, proteomic and metabolomic quantitative profiles in more than 1,000 CCLs from multiple lineages and ethnicities (Ghandi et al , 2019; Li et al , 2019; Nusinow et al , 2020; preprint: Goncalves et al , 2022).”
BackgroundSelf-citationPooled genetic screens with image‐based profiling
Walton, R. T., Singh, A. K., & Blainey, P. C. (2022) · Molecular Systems Biology · doi:10.15252/msb.202110768 · Cited by 29
“…also be used to examine cancer-relevant phenotypes such as signaling dynamics, kinase activity, DNA damage, glucose consumption, and epithelial-to-mesenchymal transition (Kim et al , 2011; Purvis et al , 2012; Regot et al , 2014; Lotz-Jenne et al , 2016; Ghezzi et al , 2019; Goglia et al , 2020).”
BackgroundDeePathNet: A Transformer-Based Deep Learning Model Integrating Multiomic Data with Cancer Pathways
Cai, Z., Poulos, R. C., Aref, A., Robinson, P. J., Reddel, R. R., & Zhong, Q. (2024) · Cancer Research Communications · doi:10.1158/2767-9764.crc-24-0285 · Cited by 36
PRMT blockade induces defective DNA replication stress response and synergizes with PARP inhibition
Li, Y., Dobrolecki, L. E., Sallas, C., Zhang, X., Kerr, T. D., Bisht, D., Wang, Y., Awasthi, S., Kaundal, B., Wu, S., et al. (2023) · Cell Reports Medicine · doi:10.1016/j.xcrm.2023.101326 · Cited by 32
Self-citationYin, G., Liu, L., Yu, T., Yu, L., Feng, M., Zhou, C., Wang, X., Teng, G., Ma, Z., Zhou, W., et al. (2024) · Genome Medicine · doi:10.1186/s13073-024-01286-8 · Cited by 30
“We examined the mutations of both CDKAL1 and CENPT in different BC cell lines using the Cancer Cell Line Encyclopedia (CCLE) online database [51].”
MethodTran, D., Nguyen, H., Pham, V.-D., Nguyen, T. N. P., Luu, H. N., Phan, L. M., DeStefano, C. B., Yeung, S. J., & Nguyen, T. (2025) · Briefings in Bioinformatics · doi:10.1093/bib/bbaf150 · Cited by 37
Endometrial cancer and its cell lines
Skok, K., Maver, U., Gradišnik, L., Kozar, N., Takač, I., & Arko, D. (2019) · Molecular Biology Reports · doi:10.1007/s11033-019-05226-3 · Cited by 30
Zhu, M. M. T., Burugu, S., Gao, D., Yu, J., Kos, Z., Leung, S. C. Y., Horst, B. A. J., & Nielsen, T. O. (2020) · Modern Pathology · doi:10.1038/s41379-020-0550-z · Cited by 30
Chen, H., Chong, W., Yang, X., Zhang, Y., Sang, S., Li, X., & Lü, M. (2020) · OncoImmunology · doi:10.1080/2162402x.2020.1788252 · Cited by 30
Cytosolic pH regulates proliferation and tumour growth by promoting expression of cyclin D1
Koch, L. M., Birkeland, E. S., Battaglioni, S., Helle, X., Meerang, M., Hiltbrunner, S., Ibáñez, A. J., Peter, M., Fontecedro, A. C., Opitz, I., et al. (2020) · Nature Metabolism · doi:10.1038/s42255-020-00297-0 · Cited by 30
SASH1 is a prognostic indicator and potential therapeutic target in non-small cell lung cancer
Burgess, J. T., Bolderson, E., Adams, M. N., Duijf, P. H. G., Zhang, S., Gray, S. G., Wright, G. M., Richard, D. J., & O'Byrne, K. J. (2020) · Scientific Reports · doi:10.1038/s41598-020-75625-1 · Cited by 30
Küster, M. M., Schneider, M. A., Richter, A. M., Richtmann, S., Winter, H., Kriegsmann, M., Pullamsetti, S. S., Stiewe, T., Savai, R., Muley, T., et al. (2020) · Cancers · doi:10.3390/cancers12123528 · Cited by 30
MT1 and MT2 melatonin receptors play opposite roles in brain cancer progression
Kinker, G. S., Ostrowski, L. H., Ribeiro, P. A. C., Chanoch-Myers, R., Muxel, S. M., Tirosh, I., Spadoni, G., Rivara, S., Martins, V. R., Santos, T. G., et al. (2021) · Journal of Molecular Medicine · doi:10.1007/s00109-020-02023-5 · Cited by 31
Davies, R. G., Liu, L., Sheng, T., Tuano, N., Chaturvedi, R., Huang, K. K., Itman, C., Mandoli, A., Qamra, A., Hu, C., et al. (2021) · Genome biology · doi:10.1186/s13059-021-02266-6 · Cited by 30
Chou, C., Hsieh, Y.-H., Ku, S., Shen, W., Anuraga, G., Ta, H. D. K., Lee, K., Lee, Y., Lin, C., Wang, C., et al. (2021) · Biomedicines · doi:10.3390/biomedicines9111601 · Cited by 30
Guo, Y., Wang, R., Li, J., Song, Y., Min, J., Zhao, T., Hua, L., Shi, J., Zhang, C., Ma, P., et al. (2021) · Frontiers in Immunology · doi:10.3389/fimmu.2021.769425 · Cited by 30
AmpliconSuite: an end-to-end workflow for analyzing focal amplifications in cancer genomesPreprint
Luebeck, J., Huang, E., Kim, F., Liefeld, T., Dameracharla, B., Ahuja, R., Schreyer, D., Prasad, G., Adamaszek, M., Kenkre, R., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.05.06.592768 · Cited by 30
Molecular mechanisms of ferroptosis and its antitumor applications in natural products
Yu, D., Wang, Q., Zhang, Q., Cai, M., Liu, S., & Zhang, W. (2023) · Acta Biochimica et Biophysica Sinica · doi:10.3724/abbs.2023120 · Cited by 30
“Previous studies suggested that ALOX plays a limited role in ferroptosis because the expression of ALOX is low in cell lines that are commonly studied for ferroptosis, and ALOX inhibitors usually have RTA activity [43,81].”
BackgroundKwon, J., Oh, J.-S., Seok, S. H., An, H., Lee, Y. J., Lee, N. Y., Ha, T., Kim, H. A., Yoon, G. M., Kim, S. E., et al. (2023) · Molecular Cancer · doi:10.1186/s12943-023-01857-0 · Cited by 31
“We found that MKN-74, a human GC cell line, harbors a RASA1 truncating mutation [43].”
BackgroundMethMarkerDB: a comprehensive cancer DNA methylation biomarker database
Zhu, Z., Zhou, Q., Sun, Y., Lai, F., Wang, Z., Hao, Z., & Li, G. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkad923 · Cited by 29
“…functions of DMRs, we curated a diverse set of annotations, including meQTLs ( 34 ,35 ), SNPs ( 36–41 ), enhancers ( 42–47 ), super-enhancers ( 48–50 ), silencers ( 51 ), chromatin accessibility information ( 29 , 52 , 53 ), motif binding sites ( 52–56 ) and gene expression data ( 57–59 ).”
BackgroundMicrobiota-shaped neutrophil senescence regulates sexual dimorphism in bladder cancer
Zhu, Q., Zhang, G., Cao, M., Huang, H., He, D., Zang, Z., Xing, J., Zhan, M., Pei, S., Deng, X., et al. (2025) · Nature Immunology · doi:10.1038/s41590-025-02126-6 · Cited by 30
Chen, P., Zhang, L., Zhang, W., Sun, C., Wu, C., He, Y., & Zhou, C. (2020) · Journal for ImmunoTherapy of Cancer · doi:10.1136/jitc-2020-001391 · Cited by 29
Claeys, A., Luijts, T., Marchal, K., & den Eynden, J. V. (2021) · PLoS Genetics · doi:10.1371/journal.pgen.1009368 · Cited by 27
Processing and Analysis of RNA-seq Data from Public Resources
Zoabi, Y., & Shomron, N. (2021) · Methods in molecular biology · doi:10.1007/978-1-0716-1103-6_4 · Cited by 31
Wang, C., Sample, K. M., Gajendran, B., Kapranov, P., Liu, W., Hu, A., Zacksenhaus, E., Li, Y., Hao, X., & Ben‐David, Y. (2021) · Frontiers in Immunology · doi:10.3389/fimmu.2021.607836 · Cited by 29
Yang, Z., Wu, X., Wei, Y., Polyanskaya, S. A., Iyer, S. V., Jung, M., Lach, F. P., Adelman, E. R., Klingbeil, O., Milazzo, J. P., et al. (2021) · Cancer Discovery · doi:10.1158/2159-8290.cd-20-1542 · Cited by 31
Mapping the Landscape of Synthetic Lethal Interactions in Liver Cancer
Chen, Y., Guo, Y., Qian, R., Huang, Y., Zhang, L., Wang, J., Huang, X., Liu, Z., Qin, W., Wang, C., et al. (2021) · Theranostics · doi:10.7150/thno.63416 · Cited by 29
Orchestrating and sharing large multimodal data for transparent and reproducible research
Mammoliti, A., Smirnov, P., Nakano, M., Safikhani, Z., Eeles, C. B., Seo, H., Nair, S. K., Mer, A. S., Smith, I., Ho, C., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-25974-w · Cited by 31
Carvalho, R. F., do Canto, L. M., Cury, S. S., Hansen, T. F., Jensen, L. H., & Rogatto, S. R. (2021) · Cancers · doi:10.3390/cancers13215492 · Cited by 29
Histone N-terminal acetyltransferase NAA40 links one-carbon metabolism to chemoresistance
Demetriadou, C., Raoukka, A., Charidemou, E., Mylonas, C., Michael, C., Parekh, S., Koufaris, C., Skourides, P. A., Papageorgis, P., Tessarz, P., et al. (2021) · Oncogene · doi:10.1038/s41388-021-02113-9 · Cited by 29
Wang, L., Shi, J., Liu, S., Huang, Y., Ding, H., Zhao, B., Liu, Y., Wang, W., Yang, J., & Chen, Z. (2022) · Frontiers in Oncology · doi:10.3389/fonc.2022.915240 · Cited by 31
“(F) Cancer Specific Survival curve of tumor and normal groups in GSE32849 (G) mRNA expression of RAC3 in CCLE database (H) Western blotting analysis of RAC3 basal protein expression in 8 BCa cell lines and 1 ureteral epithelium cell (SV-HUC-1); Tubulin was used as a loading control (I) Western blotting analysis of RAC…”
BackgroundInfluentialEnhanced Deep Learning Model for Personalized Cancer Treatment
Ahmed, H., Hamad, S. H., Shedeed, H. A., & Hussein, A. S. (2022) · IEEE Access · doi:10.1109/access.2022.3209285 · Cited by 29
Wang, H., Li, J., Kan, W., Xu, G., Luo, G.-H., Song, N., Wu, W., Feng, B., Fu, J.-F., Tu, Y., et al. (2023) · Acta Pharmacologica Sinica · doi:10.1038/s41401-023-01112-8 · Cited by 29
“We also analyzed AML cell lines data from Depmap database [25], GDSC database [26] and past research [27] which had proteomic data, Crispr activation screening data and in vitro sensitivity data (Fig.”
BackgroundMethodSelf-citation
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.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
