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Systematic identification of genomic markers of drug sensitivity in cancer cells
Open accessAbstract
Clinical responses to anticancer therapies are often restricted to a subset of patients. In some cases, mutated cancer genes are potent biomarkers for responses to targeted agents. Here, to uncover new biomarkers of sensitivity and resistance to cancer therapeutics, we screened a panel of several hundred cancer cell lines--which represent much of the tissue-type and genetic diversity of human cancers--with 130 drugs under clinical and preclinical investigation. In aggregate, we found that mutated cancer genes were associated with cellular response to most currently available cancer drugs. Classic oncogene addiction paradigms were modified by additional tissue-specific or expression biomarkers, and some frequently mutated genes were associated with sensitivity to a broad range of therapeutic agents. Unexpected relationships were revealed, including the marked sensitivity of Ewing's sarcoma cells harbouring the EWS (also known as EWSR1)-FLI1 gene translocation to poly(ADP-ribose) polymerase (PARP) inhibitors. By linking drug activity to the functional complexity of cancer genomes, systematic pharmacogenomic profiling in cancer cell lines provides a powerful biomarker discovery platform to guide rational cancer therapeutic strategies.
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“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 [150]
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“BRAF mutation was associated with nutlin 3a sensitivity in the same study130.”
From MDM2, MDMX and p53 in oncogenesis and cancer therapy (2013) · cites this paper as [130]
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“p53 mutation status was the strongest indicator of nutlin 3a resistance”
From MDM2, MDMX and p53 in oncogenesis and cancer therapy (2013) · cites this paper as [130]
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“Even with such a simple readout, genes and pathways that determine drug response can be identified,199,200”
From Advancing Targeted Protein Degradation via Multiomics Profiling and Artificial Intelligence (2023) · cites this paper as [199]
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“More than 1200 established cancer cell lines and newly derived organoid models comprise the foundational model set of the Passports, including all those utilized in the Sanger’s GDSC project (5, 18) as well as cell models generated as part of the Human Cancer Models Initiative.”
From Cell Model Passports-a hub for clinical, genetic and functional datasets of preclinical cancer models (2019) · cites this paper as [5]
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Cites
Cytoscape: A software Environment for integrated models of biomolecular interaction networks
Shannon, P., Markiel, A., Ozier, O., Baliga, N. S., Wang, J. T., Ramage, D., Amin, N., Schwikowski, B., & Ideker, T. (2003) · Genome Research · doi:10.1101/gr.1239303 · Cited by 51,888
Regularization and Variable Selection Via the Elastic Net
Zou, H., & Hastie, T. (2005) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.1467-9868.2005.00503.x · Cited by 20,957
Lynch, T. J., Bell, D. W., Sordella, R., Gurubhagavatula, S., Okimoto, R. A., Brannigan, B. W., Harris, P. L., Haserlat, S. M., Supko, J. G., Haluska, F. G., et al. (2004) · New England Journal of Medicine · doi:10.1056/nejmoa040938 · Cited by 11,486
Self-citationBolstad, B. M., Irizarry, R. A., Åstrand, M., & Speed, T. P. (2003) · Bioinformatics · doi:10.1093/bioinformatics/19.2.185 · Cited by 8,328
The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity
Barretina, J., Caponigro, G., Stransky, N., Venkatesan, K., Margolin, A. A., Kim, S., Wilson, C. J., Lehár, J., Kryukov, G. V., Sonkin, D., et al. (2012) · Nature · doi:10.1038/nature11003 · Cited by 7,950
Improved survival with vemurafenib in melanoma with BRAF V600E mutation
Chapman, P. B., Hauschild, A., Robert, C., Haanen, J. B., Ascierto, P., Larkin, J., Dummer, R., Garbe, C., Testori, A., Maio, M., et al. (2011) · New England Journal of Medicine · doi:10.1056/nejmoa1103782 · Cited by 7,720
Clustering by Passing Messages Between Data Points
Frey, B. J., & Dueck, D. (2007) · Science · doi:10.1126/science.1136800 · Cited by 6,855
In Vivo Activation of the p53 Pathway by Small-Molecule Antagonists of MDM2
Vassilev, L. T., Vu, B. T., Graves, B., Carvajal, D., Podlaski, F., Filipovic, Z., Kong, N., Kammlott, U., Lukacs, C., Klein, C., et al. (2004) · Science · doi:10.1126/science.1092472 · Cited by 4,661
Anaplastic Lymphoma Kinase Inhibition in Non–Small-Cell Lung Cancer
Kwak, E. L., Bang, Y., Camidge, D. R., Shaw, A. T., Solomon, B., Maki, R. G., Ou, S. I., Dezube, B. J., Janne, P. A., Costa, D. B., et al. (2010) · New England Journal of Medicine · doi:10.1056/nejmoa1006448 · Cited by 4,477
Self-citationBoland, C. R., Thibodeau, S. N., Hamilton, S. R., Sidransky, D., Eshleman, J. R., Burt, R. W., Meltzer, S. J., Rodrı́guez-Bigas, M. A., Fodde, R., Ranzani, G. N., et al. (1998) · PubMed · Cited by 4,087
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The Cancer Genome Atlas Research Network, Weinstein, J. N., Collisson, E. A., Mills, G. B., Shaw, K. R. M., Ozenberger, B. A., Ellrott, K., Shmulevich, I., Sander, C., & Stuart, J. M. (2013) · Nature Genetics · doi:10.1038/ng.2764 · Cited by 9,092
The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity
Barretina, J., Caponigro, G., Stransky, N., Venkatesan, K., Margolin, A. A., Kim, S., Wilson, C. J., Lehár, J., Kryukov, G. V., Sonkin, D., et al. (2012) · Nature · doi:10.1038/nature11003 · Cited by 7,950
Yang, W., Soares, J., Greninger, P., Edelman, E. J., Lightfoot, H., Forbes, S., Bindal, N., Beare, D., Smith, J. A., Thompson, I. R., et al. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks1111 · Cited by 4,051
Self-citationCancer epigenetics: from mechanism to therapy
Dawson, M. A., & Kouzarides, T. (2012) · Cell · doi:10.1016/j.cell.2012.06.013 · Cited by 3,203
Geeleher, P., Cox, N. J., & Huang, R. S. (2014) · PLoS ONE · doi:10.1371/journal.pone.0107468 · Cited by 2,444
Prospective Derivation of a Living Organoid Biobank of Colorectal Cancer Patients
van de Wetering, M., Francies, H. E., Francis, J. M., Bounova, G., Iorio, F., Pronk, A., van Houdt, W., van Gorp, J., Taylor-Weiner, A., Kester, L., et al. (2015) · Cell · doi:10.1016/j.cell.2015.03.053 · Cited by 2,408
Self-citationA Landscape of Pharmacogenomic Interactions in Cancer
Iorio, F., Knijnenburg, T. A., Vis, D. J., Bignell, G. R., Menden, M. P., Schubert, M., Aben, N., Gonçalves, E., Barthorpe, S., Lightfoot, H., et al. (2016) · Cell · doi:10.1016/j.cell.2016.06.017 · Cited by 2,090
Self-citationFrampton, G. M., Fichtenholtz, A., Otto, G. A., Wang, K., Downing, S. R., He, J., Schnall-Levin, M., White, J., Sanford, E. M., An, P., et al. (2013) · Nature Biotechnology · doi:10.1038/nbt.2696 · Cited by 2,157
Schulze, K., Imbeaud, S., Letouzé, E., Alexandrov, L. B., Calderaro, J., Rebouissou, S., Couchy, G., Meiller, C., Shinde, J., Soysouvanh, F., et al. (2015) · Nature Genetics · doi:10.1038/ng.3252 · Cited by 1,803
Self-citationOrganoid Cultures Derived from Patients with Advanced Prostate Cancer
Gao, D., Vela, I., Sboner, A., Iaquinta, P. J., Karthaus, W. R., Gopalan, A., Dowling, C., Wanjala, J. N., Undvall, E. A., Arora, V. K., et al. (2014) · Cell · doi:10.1016/j.cell.2014.08.016 · Cited by 1,559
The cellular thermal shift assay for evaluating drug target interactions in cells
Jafari, R., Almqvist, H., Axelsson, H., Ignatushchenko, M., Lundbäck, T., Nordlund, P., & Molina, D. M. (2014) · Nature Protocols · doi:10.1038/nprot.2014.138 · Cited by 1,548
Rouillard, A. D., Gundersen, G. W., Fernandez, N. F., Wang, Z., Monteiro, C. D., McDermott, M. G., & Ma’ayan, A. (2016) · Database · doi:10.1093/database/baw100 · Cited by 1,515
A Cancer Cell Program Promotes T Cell Exclusion and Resistance to Checkpoint Blockade
Jerby-Arnon, L., Shah, P., Cuoco, M. S., Rodman, C., Su, M.-J., Melms, J. C., Leeson, R., Kanodia, A., Mei, S., Lin, J.-R., et al. (2018) · Cell · doi:10.1016/j.cell.2018.09.006 · Cited by 1,429
Lessons from the Cancer Genome
Garraway, L. A., & Lander, E. S. (2013) · Cell · doi:10.1016/j.cell.2013.03.002 · Cited by 1,377
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Wade, M., Li, Y.-C., & Wahl, G. M. (2013) · Nature Reviews Cancer · doi:10.1038/nrc3430 · Cited by 1,279
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Bedard, P. L., Hansen, A. R., Ratain, M. J., & Siu, L. L. (2013) · Nature · doi:10.1038/nature12627 · Cited by 1,231
PI3K/AKT signaling pathway and cancer: an updated review
Martini, M., Santis, M. C. D., Braccini, L., Gulluni, F., & Hirsch, E. (2014) · Annals of Medicine · doi:10.3109/07853890.2014.912836 · Cited by 1,195
Combinatorial drug therapy for cancer in the post-genomic era
Al-Lazikani, B., Banerji, U., & Workman, P. (2012) · Nature Biotechnology · doi:10.1038/nbt.2284 · Cited by 1,070
Perturbation-response genes reveal signaling footprints in cancer gene expression
(2017) · doi:10.1038/s41467-017-02391-6 · Cited by 1,108
Self-citationIdentification of genomic alterations in oesophageal squamous cell cancer
Song, Y., Li, L., Ou, Y., Gao, Z., Li, E., Li, X., Zhang, W., Wang, J., Xu, L., Zhou, Y., et al. (2014) · Nature · doi:10.1038/nature13176 · Cited by 1,088
Self-citationDNA repair dysregulation from cancer driver to therapeutic target
Curtin, N. J. (2012) · Nature Reviews Cancer · doi:10.1038/nrc3399 · Cited by 1,051
Co-occurring genomic alterations in non-small-cell lung cancer biology and therapy
Skoulidis, F., & Heymach, J. V. (2019) · Nature Reviews Cancer · doi:10.1038/s41568-019-0179-8 · Cited by 1,019
Next-Generation Machine Learning for Biological Networks
Camacho, D. M., Collins, K. M., Powers, R. K., Costello, J. C., & Collins, J. J. (2018) · Cell · doi:10.1016/j.cell.2018.05.015 · Cited by 1,012
5-fluorouracil and other fluoropyrimidines in colorectal cancer: Past, present and future
Vodenkova, S., Buchler, T., Cervena, K., Veskrnova, V., Vodicka, P., & Vymetalkova, V. (2020) · Pharmacology & Therapeutics · doi:10.1016/j.pharmthera.2019.107447 · Cited by 956
Skoulidis, F., Byers, L. A., Diao, L., Papadimitrakopoulou, V. A., Tong, P., Izzo, J., Behrens, C., Kadara, H., Parra, E. R., Canales, J. R., et al. (2015) · Cancer Discovery · doi:10.1158/2159-8290.cd-14-1236 · Cited by 936
Self-citationGenetic and transcriptional evolution alters cancer cell line drug response
Ben-David, U., Siranosian, B., Ha, G., Tang, H., Oren, Y., Hinohara, K., Strathdee, C. A., Dempster, J., Lyons, N. J., Burns, R., et al. (2018) · Nature · doi:10.1038/s41586-018-0409-3 · Cited by 931
Discovering the anticancer potential of non-oncology drugs by systematic viability profiling
Corsello, S. M., Nagari, R. T., Spangler, R. D., Rossen, J., Kocak, M., Bryan, J. G., Humeidi, R., Peck, D., Wu, X., Tang, A. A., et al. (2020) · Nature Cancer · doi:10.1038/s43018-019-0018-6 · Cited by 878
Ex vivo culture of circulating breast tumor cells for individualized testing of drug susceptibility
Yu, M., Bardia, A., Aceto, N., Bersani, F., Madden, M. W., Collier, M. D., Desai, R. N., Zhu, H., Comaills, V., Zheng, Z., et al. (2014) · Science · doi:10.1126/science.1253533 · Cited by 927
Self-citationCorrelating chemical sensitivity and basal gene expression reveals mechanism of action
Rees, M. G., Seashore-Ludlow, B. A., Cheah, J. H., Adams, D., Price, E. V., Gill, S., Javaid, S., Coletti, M. E., Jones, V., Bodycombe, N. E., et al. (2015) · Nature Chemical Biology · doi:10.1038/nchembio.1986 · Cited by 883
Self-citationGeeleher, P., Cox, N. J., & Huang, R. S. (2014) · Genome biology · doi:10.1186/gb-2014-15-3-r47 · Cited by 897
Reversible and adaptive resistance to BRAF(V600E) inhibition in melanoma
Sun, C., Wang, L., Huang, S., Heynen, G. J. J. E., Prahallad, A., Robert, C., Haanen, J., Blank, C., Wesseling, J., Willems, S. M., et al. (2014) · Nature · doi:10.1038/nature13121 · Cited by 888
Heterogeneity of genomic evolution and mutational profiles in multiple myeloma
Bolli, N., Avet-Loiseau, H., Wedge, D. C., Van Loo, P., Alexandrov, L. B., Martincorena, I., Dawson, K. J., Iorio, F., Nik-Zainal, S., Bignell, G. R., et al. (2014) · Nature Communications · doi:10.1038/ncomms3997 · Cited by 875
Self-citationTargeting transcription regulation in cancer with a covalent CDK7 inhibitor
Kwiatkowski, N. P., Zhang, T., Rahl, P. B., Abraham, B. J., Reddy, J., Ficarro, S. B., Dastur, A., Amzallag, A., Ramaswamy, S., Tesar, B. M., et al. (2014) · Nature · doi:10.1038/nature13393 · Cited by 865
Self-citationDrugging Topoisomerases: Lessons and Challenges
Pommier, Y. G. (2012) · ACS Chemical Biology · doi:10.1021/cb300648v · Cited by 867
Basu, A. B., Bodycombe, N. E., Cheah, J. H., Price, E. V., Liu, K., Schaefer, G. I., Ebright, R. Y., Stewart, M. L., Ito, D., Wang, S. Y., et al. (2013) · Cell · doi:10.1016/j.cell.2013.08.003 · Cited by 828
Ooft, S. N., Weeber, F., Dijkstra, K. K., McLean, C. M., Kaing, S., van Werkhoven, E., Schipper, L., Hoes, L., Vis, D. J., van de Haar, J., et al. (2019) · Science Translational Medicine · doi:10.1126/scitranslmed.aay2574 · Cited by 813
Harnessing Connectivity in a Large-Scale Small-Molecule Sensitivity Dataset
Seashore-Ludlow, B., Rees, M. G., Cheah, J. H., Cokol, M., Price, E. V., Coletti, M. E., Jones, V., Bodycombe, N. E., Soule, C. K., Gould, J., et al. (2015) · Cancer Discovery · doi:10.1158/2159-8290.cd-15-0235 · Cited by 813
Systems biology of cisplatin resistance: past, present and future
Galluzzi, L., Vitale, I., Michels, J., Brenner, C., Szabadkai, G., Harel-Bellan, A., Castedo, M., & Kroemer, G. (2014) · Cell Death & Disease · doi:10.1038/cddis.2013.428 · Cited by 782
Tan, T. Z., Miow, Q. H., Miki, Y., Noda, T., Mori, S., Huang, R. Y., & Thiery, J. P. (2014) · EMBO Molecular Medicine · doi:10.15252/emmm.201404208 · Cited by 792
Sustained proliferation in cancer: Mechanisms and novel therapeutic targets
Feitelson, M. A., Arzumanyan, A. L., Kulathinal, R. J., Blain, S. W., Holcombe, R. F., Mahajna, J. A., Marino, M., Martínez‐Chantar, M. L., Nawroth, R., Sánchez-García, I., et al. (2015) · Seminars in Cancer Biology · doi:10.1016/j.semcancer.2015.02.006 · Cited by 818
A community effort to assess and improve drug sensitivity prediction algorithms
Community, N. D., Costello, J. C., Heiser, L. M., Georgii, E., Gönen, M., Menden, M. P., Wang, N. J., Bansal, M., Ammad-ud-din, M., Hintsanen, P., et al. (2014) · Nature Biotechnology · doi:10.1038/nbt.2877 · Cited by 782
Growth rate inhibition metrics correct for confounders in measuring sensitivity to cancer drugs
Hafner, M., Niepel, M., Chung, M., & Sorger, P. K. (2016) · Nature Methods · doi:10.1038/nmeth.3853 · Cited by 681
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Murai, J., Huang, S.-Y. N., Renaud, A., Zhang, Y., Ji, J. J., Takeda, S., Morris, J., Teicher, B. A., Doroshow, J. H., & Pommier, Y. G. (2013) · Molecular Cancer Therapeutics · doi:10.1158/1535-7163.mct-13-0803 · Cited by 777
Patient-derived xenografts undergo mouse-specific tumor evolution
Ben-David, U., Ha, G., Tseng, Y.-Y., Greenwald, N. F., Oh, C., Shih, J., McFarland, J. M., Wong, B., Boehm, J. S., Beroukhim, R., et al. (2017) · Nature Genetics · doi:10.1038/ng.3967 · Cited by 716
Dulak, A. M., Stojanov, P., Peng, S., Lawrence, M. S., Fox, C., Stewart, C., Bandla, S., Imamura, Y., Schumacher, S. E., Shefler, E., et al. (2013) · Nature Genetics · doi:10.1038/ng.2591 · Cited by 736
Ewing Sarcoma: Current Management and Future Approaches Through Collaboration
Gaspar, N., Hawkins, D. S., Dirksen, U., Lewis, I. J., Ferrari, S., Deley, M. L., Kovar, H., Grimer, R. J., Whelan, J., Claude, L., et al. (2015) · Journal of Clinical Oncology · doi:10.1200/jco.2014.59.5256 · Cited by 757
Self-citationFrom tumour heterogeneity to advances in precision treatment of colorectal cancer
Punt, C. J. A., Koopman, M., & Vermeulen, L. (2017) · Nature Reviews Clinical Oncology · doi:10.1038/nrclinonc.2016.171 · Cited by 654
Andreu-Pérez, J., Poon, C. C. Y., Merrifield, R. D., Wong, S. T. C., & Yang, G. (2015) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2015.2450362 · Cited by 728
Cancer stem cell definitions and terminology: the devil is in the details
Valent, P., Bonnet, D. A., Maria, R. D., Lapidot, T., Copland, M., Melo, J. V., Chomienne, C., Ishikawa, F., Schuringa, J. J., Stassi, G., et al. (2012) · Nature reviews. Cancer · doi:10.1038/nrc3368 · Cited by 720
A Pan-Cancer Proteogenomic Atlas of PI3K/AKT/mTOR Pathway Alterations
Zhang, Y., Kwok-Shing Ng, P., Kucherlapati, M., Chen, F., Liu, Y., Tsang, Y. H., de Velasco, G., Jeong, K. J., Akbani, R., Hadjipanayis, A., et al. (2017) · Cancer Cell · doi:10.1016/j.ccell.2017.04.013 · Cited by 626
“(D) A gene expression signature of sensitivity to PI3K/AKT/mTOR inhibition in cancer cell lines, consisting of 146 genes (p < 0.01 by t test and p < 0.01 in regression model incorporating tumor type as a confounder), was derived using the dataset of Garnett et al. (2012).”
MethodInfluentialA comprehensive transcriptional portrait of human cancer cell lines
Klijn, C. N., Durinck, S., Stawiski, E. W., Haverty, P. M., Jiang, Z., Liu, H., Degenhardt, J. D., Mayba, O., Gnad, F., Liu, J., et al. (2014) · Nature Biotechnology · doi:10.1038/nbt.3080 · Cited by 669
Self-citationClassification of endometrial carcinoma: more than two types
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Niederst, M. J., Sequist, L. V., Poirier, J. T., Mermel, C. H., Lockerman, E. L., Garcia, A. R., Katayama, R., Costa, C., Ross, K. N., Moran, T., et al. (2015) · Nature Communications · doi:10.1038/ncomms7377 · Cited by 647
Self-citationTargeting MYCN in Neuroblastoma by BET Bromodomain Inhibition
Puissant, A., Frumm, S. M., Alexe, G., Bassil, C. F., Qi, J., Chanthery, Y. H., Nekritz, E. A., Zeid, R., Gustafson, W. C., Greninger, P., et al. (2013) · Cancer Discovery · doi:10.1158/2159-8290.cd-12-0418 · Cited by 648
Self-citationWang, T., Yu, H., Hughes, N. W., Liu, B., Kendirli, A., Klein, K., Chen, W. W., Lander, E. S., & Sabatini, D. M. (2017) · Cell · doi:10.1016/j.cell.2017.01.013 · Cited by 632
Genomic and molecular characterization of esophageal squamous cell carcinoma
Lin, D., Hao, J., Nagata, Y., Xu, L., Li, S., Meng, X., Sato, Y., Okuno, Y., Varela, A. M., Ding, L., et al. (2014) · Nature Genetics · doi:10.1038/ng.2935 · Cited by 627
The Clinical Relevance of Cancer Cell Lines
Gillet, J.-P., Varma, S., & Gottesman, M. M. (2013) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/djt007 · Cited by 630
Liquid demixing of intrinsically disordered proteins is seeded by poly(ADP-ribose)
Altmeyer, M., Neelsen, K. J., Teloni, F., Pozdnyakova, I., Pellegrino, S., Grøfte, M., Rask, M., Streicher, W. W., Jungmichel, S., Nielsen, M. L., et al. (2015) · Nature Communications · doi:10.1038/ncomms9088 · Cited by 581
Advances in molecular classification and precision oncology in hepatocellular carcinoma
Rebouissou, S., & Nault, J. (2020) · Journal of Hepatology · doi:10.1016/j.jhep.2019.08.017 · Cited by 603
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von Karstedt, S., Montinaro, A., & Walczak, H. (2017) · Nature Reviews Cancer · doi:10.1038/nrc.2017.28 · Cited by 556
Byers, L. A., Wang, J., Nilsson, M. B., Fujimoto, J., Saintigny, P., Yordy, J. S., Giri, U. P., Peyton, M., Fan, Y. H., Diao, L., et al. (2012) · Cancer Discovery · doi:10.1158/2159-8290.cd-12-0112 · Cited by 553
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Giacomelli, A. O., Yang, X., Lintner, R. E., McFarland, J. M., Duby, M., Kim, J., Howard, T. P., Takeda, D. Y., Ly, S. H., Kim, E., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0204-y · Cited by 556
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Li, J., Zheng, S., Chen, B., Butte, A. J., Swamidass, S. J., & Lu, Z. (2015) · Briefings in Bioinformatics · doi:10.1093/bib/bbv020 · Cited by 569
Menden, M. P., Iorio, F., Garnett, M. J., McDermott, U., Benes, C. H., Ballester, P. J., & Sáez-Rodríguez, J. (2013) · PLoS ONE · doi:10.1371/journal.pone.0061318 · Cited by 543
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Kuenzi, B. M., Park, J., Fong, S. H., Sanchez, K. S., Lee, J., Kreisberg, J. F., Ma, J., & Ideker, T. (2020) · Cancer Cell · doi:10.1016/j.ccell.2020.09.014 · Cited by 544
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Eleveld, T. F., Oldridge, D. A., Bernard, V., Köster, J., Daage, L. C., Diskin, S. J., Schild, L. G., Bessoltane, N., Bellini, A., Chicard, M., et al. (2015) · Nature Genetics · doi:10.1038/ng.3333 · Cited by 536
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Horvath, P., Aulner, N., Bickle, M., Davies, A. M., Nery, E. D., Ebner, D., Montoya, M. C., Östling, P., Pietiäinen, V., Price, L. S., et al. (2016) · Nature Reviews Drug Discovery · doi:10.1038/nrd.2016.175 · Cited by 525
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Arafeh, R., Shibue, T., Dempster, J. M., Hahn, W. C., & Vazquez, F. (2025) · Nature Reviews Cancer · doi:10.1038/s41568-024-00763-x · Cited by 454
Studying clonal dynamics in response to cancer therapy using high-complexity barcoding
Bhang, H.-E. C., Ruddy, D. A., Krishnamurthy Radhakrishna, V., Caushi, J. X., Zhao, R., Hims, M. M., Singh, A. P., Kao, I., Rakiec, D., Shaw, P., et al. (2015) · Nature Medicine · doi:10.1038/nm.3841 · Cited by 507
Inconsistency in large pharmacogenomic studies
Haibe-Kains, B., El-Hachem, N., Birkbak, N. J., Jin, A. C., Beck, A. H., Aerts, H. J. W. L., & Quackenbush, J. (2013) · Nature · doi:10.1038/nature12831 · Cited by 499
Synthetic Lethality and Cancer Therapy: Lessons Learned from the Development of PARP Inhibitors
Lord, C. J., Tutt, A. N. J., & Ashworth, A. (2014) · Annual Review of Medicine · doi:10.1146/annurev-med-050913-022545 · Cited by 493
The role of tumour-stromal interactions in modifying drug response: challenges and opportunities
McMillin, D. W., Negri, J. M., & Mitsiades, C. S. (2013) · Nature Reviews Drug Discovery · doi:10.1038/nrd3870 · Cited by 474
Pattern discovery and cancer gene identification in integrated cancer genomic data
Mo, Q., Wang, S., Seshan, V. E., Olshen, A. B., Schultz, N., Sander, C., Powers, R. S., Ladanyi, M., & Shen, R. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1208949110 · Cited by 474
Role of Merlin/NF2 inactivation in tumor biology
Petrilli, A. M., & Fernández‐Valle, C. (2015) · Oncogene · doi:10.1038/onc.2015.125 · Cited by 469
Next-Generation Sequencing in Oncology: Genetic Diagnosis, Risk Prediction and Cancer Classification
Kamps, R., Brandão, R. D., van den Bosch, B. J. C., Paulussen, A. D. C., Xanthoulea, S., Blok, M. J., & Romano, A. (2017) · International Journal of Molecular Sciences · doi:10.3390/ijms18020308 · Cited by 472
Bruna, A., Rueda, O. M., Greenwood, W., Batra, A. S., Callari, M., Batra, R. N., McNamara, K. L., Sandoval, J. L., Cassidy, J. W., Vidaković, A. T., et al. (2016) · Cell · doi:10.1016/j.cell.2016.08.041 · Cited by 442
Self-citationA metastasis map of human cancer cell lines
Jin, X., Demere, Z., Nair, K., Ali, A., Ferraro, G. B., Natoli, T. E., Deik, A., Petronio, L., Tang, A. A., Zhu, C., et al. (2020) · Nature · doi:10.1038/s41586-020-2969-2 · Cited by 436
MED12 Controls the Response to Multiple Cancer Drugs through Regulation of TGF-β Receptor Signaling
Huang, S., Hölzel, M., Knijnenburg, T., Schlicker, A., Roepman, P., McDermott, U., Garnett, M., Grernrum, W., Sun, C., Prahallad, A., et al. (2012) · Cell · doi:10.1016/j.cell.2012.10.035 · Cited by 430
Self-citationThe Genomic Landscape of the Ewing Sarcoma Family of Tumors Reveals Recurrent STAG2 Mutation
Brohl, A. S., Solomon, D. A., Chang, W., Wang, J., Song, Y., Sindiri, S., Patidar, R., Hurd, L., Chen, L., Shern, J. F., et al. (2014) · PLoS Genetics · doi:10.1371/journal.pgen.1004475 · Cited by 440
Self-citationRB1 : a prototype tumor suppressor and an enigmaPreprint
Dyson, N. J. (2016) · Genes & Development · doi:10.1101/gad.282145.116 · Cited by 453
Cancer Cell Lines for Drug Discovery and Development
Wilding, J. L., & Bodmer, W. F. (2014) · Cancer Research · doi:10.1158/0008-5472.can-13-2971 · Cited by 432
Caenepeel, S., Brown, S. P., Belmontes, B., Moody, G., Keegan, K. S., Chui, D., Whittington, D. A., Huang, X., Poppe, L., Cheng, A. C., et al. (2018) · Cancer Discovery · doi:10.1158/2159-8290.cd-18-0387 · Cited by 432
Self-citationDaemen, A., Peterson, D., Sahu, N., McCord, R., Du, X., Liu, B., Kowanetz, K., Hong, R., Moffat, J., Gao, M., et al. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1501605112 · Cited by 398
Self-citationMachine learning approaches to drug response prediction: challenges and recent progress
Adam, G. A., Rampášek, L., Safikhani, Z., Smirnov, P., Haibe‐Kains, B., & Goldenberg, A. (2020) · npj Precision Oncology · doi:10.1038/s41698-020-0122-1 · Cited by 459
Toso, A., Revandkar, A., Di Mitri, D., Guccini, I., Proietti, M., Sarti, M., Pinton, S., Zhang, J., Kalathur, M., Civenni, G., et al. (2014) · Cell Reports · doi:10.1016/j.celrep.2014.08.044 · Cited by 418
“Human cancer cell lines expression data set and sensitivity values to docetaxel treatment (IC50 values) were downloaded from http://www.cancerrxgene.org/downloads (Garnett et al., 2012).”
Pang, B., Qiao, X., Janssen, L., Velds, A., Groothuis, T. A., Kerkhoven, R. M., Nieuwland, M., Ovaa, H., Rottenberg, S., van Tellingen, O., et al. (2013) · Nature Communications · doi:10.1038/ncomms2921 · Cited by 431
Gallo, M. L., O’Hara, A. J., Rudd, M. L., Urick, M. E., Hansen, N. F., O’Neil, N. J., Price, J. C., Zhang, S., England, B. M., Godwin, A. K., et al. (2012) · Nature Genetics · doi:10.1038/ng.2455 · Cited by 426
Pharmacogenomic agreement between two cancer cell line data sets
The Cancer Cell Line Encyclopedia Consortium, & The Genomics of Drug Sensitivity in Cancer Consortium (2015) · Nature · doi:10.1038/nature15736 · Cited by 418
Molecular aspects of cancer cell resistance to chemotherapy
Rebucci, M., & Michiels, C. (2013) · Biochemical Pharmacology · doi:10.1016/j.bcp.2013.02.017 · Cited by 423
HER2 expression identifies dynamic functional states within circulating breast cancer cells
Jordan, N. V., Bardia, A., Wittner, B. S., Benes, C. H., Ligorio, M., Zheng, Y., Yu, M., Sundaresan, T. K., LiCausi, J. A., Desai, R. N., et al. (2016) · Nature · doi:10.1038/nature19328 · Cited by 408
Self-citationAn unbiased oncology compound screen to identify novel combination strategies
O'Neil, J., Benita, Y., Feldman, I., Chenard, M., Roberts, B., Liu, Y., Li, J., Kral, A., Lejnine, S., Loboda, A., et al. (2016) · Molecular Cancer Therapeutics · doi:10.1158/1535-7163.mct-15-0843 · Cited by 407
Self-citationOvarian Cancer Cell Line Panel (OCCP): Clinical Importance of In Vitro Morphological Subtypes
Beaufort, C. M., Helmijr, J. C. A., Piskorz, A. M., Hoogstraat, M., Ruigrok-Ritstier, K., Besselink, N., Murtaza, M., van IJcken, W. F. J., Heine, A. A. J., Smid, M., et al. (2014) · PLoS ONE · doi:10.1371/journal.pone.0103988 · Cited by 403
“Worldwide, there are about 100 ovarian cancer cell lines generated as described in literature [12–17] and about 70 of these are available at ATCC, ECACC, RIKEN, DSMZ, JCRB or Cancer Research Technology.”
BackgroundCharacterizing Mutational Signatures in Human Cancer Cell Lines Reveals Episodic APOBEC Mutagenesis
Petljak, M., Alexandrov, L. B., Brammeld, J. S., Price, S., Wedge, D. C., Großmann, S., Dawson, K. J., Ju, Y. S., Iorio, F., Tubío, J. M. C., et al. (2019) · Cell · doi:10.1016/j.cell.2019.02.012 · Cited by 407
Self-citationTargeting Epigenetic Readers in Cancer
Dawson, M. A., Kouzarides, T., & Huntly, B. J. P. (2012) · New England Journal of Medicine · doi:10.1056/nejmra1112635 · Cited by 405
Yu, C., Mannan, A. M., Yvone, G. M., Ross, K. N., Zhang, Y.-L., Marton, M. A., Taylor, B. R., Crenshaw, A., Gould, J. Z., Tamayo, P., et al. (2016) · Nature Biotechnology · doi:10.1038/nbt.3460 · Cited by 362
Corcoran, R. B., Cheng, K. A., Hata, A. N., Faber, A. C., Ebi, H., Coffee, E. M., Greninger, P., Brown, R. D., Godfrey, J. T., Cohoon, T. J., et al. (2013) · Cancer Cell · doi:10.1016/j.ccr.2012.11.007 · Cited by 377
Self-citationBono, J. S. D., Ramanathan, R. K., Mina, L. A., Chugh, R. K., Glaspy, J. A., Rafii, S., Kaye, S. B., Sachdev, J. C., Heymach, J. V., Smith, D. C., et al. (2017) · Cancer Discovery · doi:10.1158/2159-8290.cd-16-1250 · Cited by 390
Jarada, T. N., Rokne, J. G., & Alhajj, R. (2020) · Journal of Cheminformatics · doi:10.1186/s13321-020-00450-7 · Cited by 384
Hickman, J. A., Graeser, R., Hoogt, R. D., Vidic, S., Brito, C., Gutekunst, M., & van der Kuip, H. (2014) · Biotechnology Journal · doi:10.1002/biot.201300492 · Cited by 405
Metadata
- Authors
- Garnett, M. J., Edelman, E. J., Heidorn, S. J., Greenman, C. D., Dastur, A., Lau, K. W., Greninger, P., Thompson, I. R., Luo, X., Soares, J., Liu, Q., Iorio, F., Surdez, D., Chen, L., Milano, R. J., Bignell, G. R., Tam, A. T., Davies, H., Stevenson, J. A., Barthorpe, S., Lutz, S. R., Kogera, F., Lawrence, K., McLaren-Douglas, A., Mitropoulos, X., Mironenko, T., Thi, H., Richardson, L., Zhou, W., Jewitt, F., Zhang, T., O’Brien, P., Boisvert, J. L., Price, S., Hur, W., Yang, W., Deng, X., Butler, A., Choi, H. G., Chang, J. W., Baselga, J., Stamenkovic, I., Engelman, J. A., Sharma, S. V., Delattre, O., Saez-Rodriguez, J., Gray, N. S., Settleman, J., Futreal, P. A., Haber, D. A., Stratton, M. R., Ramaswamy, S., McDermott, U., & Benes, C. H.
- Affiliations
- Wellcome Sanger Institute (GB)
- Harvard University (US)
- European Bioinformatics Institute (GB)
- Institut Curie (FR)
- Centre Hospitalier Universitaire Vaudois (CH)
- Howard Hughes Medical Institute (US)
- Corresponding author
- McDermott, Ultan
- Benes, Cyril H.
- ORCID
- Garnett, Mathew J.
- Greenman, Chris D.
- Dastur, Anahita
- Lau, King Wai
- Greninger, Patricia
- Thompson, I. Richard
- Luo, Xi
- Liu, Qingsong
- Iorio, Francesco
- Surdez, Didier
- Chen, Li
- Davies, Helen
- Barthorpe, Syd
- Lawrence, Karl
- Mironenko, Tatiana
- Richardson, Laura
- Zhou, Wenjun
- Zhang, Tinghu
- O’Brien, Patrick
- Hur, Wooyoung
- Yang, Wanjuan
- Deng, Xianming
- Choi, Hwan Geun
- Chang, Jae Won
- Baselga, Jose
- Stamenkovic, Ivan
- Engelman, Jeffrey A.
- Delattre, Olivier
- Gray, Nathanael S.
- Settleman, Jeffrey
- Futreal, P. Andrew
- Haber, Daniel A.
- Stratton, Michael R.
- McDermott, Ultan
- Benes, Cyril H.
- Venue
- Nature
- Published
- 2012-03
- Volume
- 483
- Issue
- 7391
- Pages
- 570-575
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC3349233
- OpenAlex
- W2125789330
- Cited by
- 2,456
- References
- 39
- Citations by year
- 2026: 106 · 2025: 101 · 2024: 114 · 2023: 145 · 2022: 161 · 2021: 228 · 2020: 162 · 2019: 183 · 2018: 212 · 2017: 198 · 2016: 214 · 2015: 199 · 2014: 197 · 2013: 153 · 2012: 82
- FWCI
- 66.78
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- SERVAL (Université de Lausanne) (acceptedVersion, other-oa)
- IRIS (submittedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- UEA Digital Repository (University of East Anglia) (submittedVersion)
- Funders
- Howard Hughes Medical Institute
- Wellcome Trust (086357)
- Cancer Research UK
- National Institutes of Health (5u54hg006097-03)
- National Human Genome Research Institute (1U54HG006097-01, U54-HG006097)
- National Institute of General Medical Sciences (P41GM079575)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
- Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Lung Cancer Treatments and Mutations
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Chromatin Remodeling and Cancer
- Keywords
- drug sensitivity, drug resistance, pharmacogenomics, cancer cell lines, genomic biomarkers, oncogene addiction, Ewing sarcoma, PARP inhibitors, topoisomerase inhibitors, SLFN11, tissue-specific biomarkers
- MeSH terms
- Poly(ADP-ribose) Polymerase Inhibitors, Cell Survival, Drug Screening Assays, Antitumor, Genetic Markers, Humans, Indoles, Neoplasms, Pharmacogenetics, Phthalazines, Piperazines, Sarcoma, Ewing, Oncogene Proteins, Fusion, Genome, Human, Gene Expression Regulation, Neoplastic, Drug Resistance, Neoplasm, Genomics, RNA-Binding Protein EWS, Cell Line, Tumor, Proto-Oncogene Protein c-fli-1, Genes, Neoplasm
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