Cancer Cell Lines for Drug Discovery and Development
Abstract
Despite the millions of dollars spent on target validation and drug optimization in preclinical models, most therapies still fail in phase III clinical trials. Our current model systems, or the way we interpret data from them, clearly do not have sufficient clinical predictive power. Current opinion suggests that this is because the cell lines and xenografts that are commonly used are inadequate models that do not effectively mimic and predict human responses. This has become such a widespread belief that it approaches dogma in the field of drug discovery and optimization and has spurred a surge in studies devoted to the development of more sophisticated animal models such as orthotopic patient-derived xenografts in an attempt to obtain more accurate estimates of whether particular cancers will respond to given treatments. Here, we explore the evidence that has led to the move away from the use of in vitro cell lines and toward various forms of xenograft models for drug screening and development. We review some of the pros and cons of each model and give an overview of ways in which the use of cell lines could be modified to improve the predictive capacity of this well-defined model. Cancer Res; 74(9); 2377–84. ©2014 AACR.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
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?
Since cell lines accumulate culture-related changes over many passages, methods were created to grow osteosarcoma tumours as primary cultures and as patient-derived xenograft libraries.
“Established cell cultures have been the predominant research models of osteosarcoma for decades, but the culture-related alterations that cell lines acquire over tens and sometimes hundreds of passages 220,221 led to the development of systems for propagating osteosarcoma tumours 220,221 by creating libraries of primary tumour cell cultures and patient-derived xenografts (PDXs).”
From Osteosarcoma (2022) · cites this paper as [221]
Cites
Multiplex Genome Engineering Using CRISPR/Cas Systems
Cong, L., Ran, F. A., Cox, D., Lin, S., Barretto, R., Habib, N., Hsu, P. D., Wu, X., Jiang, W., Marraffini, L. A., et al. (2013) · Science · doi:10.1126/science.1231143 · Cited by 15,339 · see citing works
RNA-Guided Human Genome Engineering via Cas9
Mali, P., Yang, L., Esvelt, K. M., Aach, J., Guell, M., DiCarlo, J. E., Norville, J. E., & Church, G. M. (2013) · Science · doi:10.1126/science.1232033 · Cited by 9,210 · see citing works
Comprehensive molecular characterization of human colon and rectal cancer
The Cancer Genome Atlas Network (2012) · Nature · doi:10.1038/nature11252 · Cited by 8,499 · see citing works
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 · see citing works
ZFN, TALEN, and CRISPR/Cas-based methods for genome engineering
Gaj, T., Gersbach, C. A., & Barbas, C. F. (2013) · Trends in Biotechnology · doi:10.1016/j.tibtech.2013.04.004 · Cited by 3,820 · see citing works
Sato, T., Stange, D. E., Ferrante, M., Vries, R. G. J., van Es, J. H., van den Brink, S., van Houdt, W. J., Pronk, A., van Gorp, J., Siersema, P. D., et al. (2011) · Gastroenterology · doi:10.1053/j.gastro.2011.07.050 · Cited by 3,753 · see citing works
Monks, A. P., Scudiero, D. A., Skehan, P., Shoemaker, R. H., Paull, K. D., Vistica, D. T., Hose, C. D., Langley, J. W., Cronise, P., Vaigro-Wolff, A., et al. (1991) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/83.11.757 · Cited by 3,305 · see citing works
Systematic identification of genomic markers of drug sensitivity in cancer cells
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., et al. (2012) · Nature · doi:10.1038/nature11005 · Cited by 2,456 · see citing works
Unresponsiveness of colon cancer to BRAF(V600E) inhibition through feedback activation of EGFR
Prahallad, A., Sun, C., Huang, S., Di Nicolantonio, F., Salazar, R., Zecchin, D., Beijersbergen, R. L., Bardelli, A., & Bernards, R. (2012) · Nature · doi:10.1038/nature10868 · Cited by 2,051 · see citing works
Evaluating cell lines as tumour models by comparison of genomic profiles
Domcke, S., Sinha, R., Levine, D. A., Sander, C., & Schultz, N. D. (2013) · Nature Communications · doi:10.1038/ncomms3126 · Cited by 1,426 · see citing works
Patient-derived tumour xenografts as models for oncology drug development
Tentler, J. J., Tan, A. C., Weekes, C. D., Jimeno, A., Leong, S., Pitts, T. M., Arcaroli, J. J., Messersmith, W. A., & Eckhardt, S. G. (2012) · Nature Reviews Clinical Oncology · doi:10.1038/nrclinonc.2012.61 · Cited by 1,277 · see citing works
Genome remodelling in a basal-like breast cancer metastasis and xenograft
Ding, L., Ellis, M. J., Li, S., Larson, D. E., Chen, K., Wallis, J. W., Harris, C. C., McLellan, M. D., Fulton, R. S., Fulton, L., et al. (2010) · Nature · doi:10.1038/nature08989 · Cited by 1,134 · see citing works
Isolation and in vitro expansion of human colonic stem cells
Jung, P., Sato, T., Merlos-Suárez, A., Barriga, F. M., Iglesias, M., Rossell, D., Auer, H., Gallardo, M., Blasco, M. A., Sancho, E., et al. (2011) · Nature Medicine · doi:10.1038/nm.2470 · Cited by 709 · see citing works
Patient-Derived Tumor Xenografts: Transforming Clinical Samples into Mouse Models
Siolas, D., & Hannon, G. J. (2013) · Cancer Research · doi:10.1158/0008-5472.can-13-1069 · Cited by 672 · see citing works
Roock, W. D., de Vriendt, V., Normanno, N., Ciardiello, F., & Tejpar, S. (2010) · The Lancet Oncology · doi:10.1016/s1470-2045(10)70209-6 · Cited by 605 · see citing works
(2003) · PubMed · Cited by 523 · see citing works
Cancer stem cells from colorectal cancer-derived cell lines
Yeung, T. M., Gandhi, S. C., Wilding, J. L., Muschel, R. J., & Bodmer, W. F. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0915135107 · Cited by 484 · see citing works
Self-citationDaniel, V. C., Marchionni, L., Hierman, J. S., Rhodes, J. T., Devereux, W. L., Rudin, C. M., Yung, R., Parmigiani, G., Dorsch, M., Peacock, C. D., et al. (2009) · Cancer Research · doi:10.1158/0008-5472.can-08-4210 · Cited by 469 · see citing works
Julien-Grille, S., Merino‐Trigo, A., Lacroix, L., Pocard, M. D., Goèré, D., Mariani, P., Landron, S., Bigot, L., Némati, F., Dartigues, P., et al. (2012) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-12-0372 · Cited by 358 · see citing works
Karyotypic complexity of the NCI-60 drug-screening panel.
Roschke, A. V., Tonon, G., Gehlhaus, K., Mctyre, N., Bussey, K. J., Lababidi, S., Scudiero, D. A., Weinstein, J. N., & Kirsch, I. R. (2003) · PubMed · Cited by 289 · see citing works
PARP-1 Inhibition as a Targeted Strategy to Treat Ewing's Sarcoma
Brenner, J. C., Feng, F. Y.-C., Han, S., Patel, S., Goyal, S. V., Bou‐Maroun, L. M., Liu, M., Lonigro, R. J., Prensner, J. R., Tomlins, S. A., et al. (2012) · Cancer Research · doi:10.1158/0008-5472.can-11-3648 · Cited by 286 · see citing works
Analysis of P53 mutations and their expression in 56 colorectal cancer cell lines
Liu, Y., & Bodmer, W. F. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0510146103 · Cited by 257 · see citing works
Self-citationZhao, L., Lim, S. Y., Gordon-Weeks, A. N., Tapmeier, T. T., Im, J. H., Cao, Y., Beech, J. S., Allen, P. D., Smart, S., & Muschel, R. J. (2012) · Hepatology · doi:10.1002/hep.26094 · Cited by 226 · see citing works
Williams, S. A., Anderson, W. C., Santaguida, M. T., & Dylla, S. J. (2013) · Laboratory Investigation · doi:10.1038/labinvest.2013.92 · Cited by 185 · see citing works
Alli, E., Sharma, V. B., Sunderesakumar, P., & Ford, J. (2009) · Cancer Research · doi:10.1158/0008-5472.can-08-4016 · Cited by 152 · see citing works
Human induced pluripotent stem cells and their use in drug discovery for toxicity testing
Scott, C. W., Peters, M. F., & Dragan, Y. P. (2013) · Toxicology Letters · doi:10.1016/j.toxlet.2013.02.020 · Cited by 150 · see citing works
S Phase Assembly of Centromeric Heterochromatin and Cohesion
Bailis, J. M., & Forsburg, S. L. (2004) · Cell Cycle · doi:10.4161/cc.3.4.799 · Cited by 139 · see citing works
Cancer Stem Cells Persist in Many Cancer Cell Lines
Setoguchi, T., Taga, T., & Kondo, T. (2004) · Cell Cycle · doi:10.4161/cc.3.4.795 · Cited by 123 · see citing works
Aljitawi, O. S., Li, D., Xiao, Y., Zhang, D., Karthik, R., Stehno‐Bittel, L., Veldhuizen, P. J. V., Lin, T. L., Kambhampati, S., & Garimella, R. (2013) · Leukemia & lymphoma/Leukemia and lymphoma · doi:10.3109/10428194.2013.793323 · Cited by 113 · see citing works
Bergamaschi, A., Hjortland, G. O., Triulzi, T., Sørlie, T., Johnsen, H., Ree, A. H., Russnes, H. G., Trønnes, S., Mælandsmo, G. M., Fodstad, Ø., et al. (2009) · Molecular Oncology · doi:10.1016/j.molonc.2009.07.003 · Cited by 111 · see citing works
Bracht, K., Nicholls, A. M., Liu, Y., et al. (2010) · British Journal of Cancer · doi:10.1038/sj.bjc.6605780 · Cited by 110 · see citing works
Moro, M., Bertolini, G., Tortoreto, M., Pastorino, U., Sozzi, G., & Roz, L. (2012) · BioMed Research International · doi:10.1155/2012/568567 · Cited by 98 · see citing works
Origin of the vasculature supporting growth of primary patient tumor xenografts
Hylander, B. L., Punt, N., Tang, H., Hillman, J. C., Vaughan, M. M., Bshara, W., Pitoniak, R., & Repasky, E. A. (2013) · Journal of Translational Medicine · doi:10.1186/1479-5876-11-110 · Cited by 81 · see citing works
Tveit, K. M., & Pihl, A. (1981) · British Journal of Cancer · doi:10.1038/bjc.1981.276 · Cited by 51 · see citing works
Ashraf, S. Q., Nicholls, A. M., Wilding, J. L., Ntouroupi, T. G., Mortensen, N., & Bodmer, W. F. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1218750110 · Cited by 47 · see citing works
Self-citationStem Cell Differentiation and Lumen Formation in Colorectal Cancer Cell Lines and Primary Tumors
Ashley, N., Yeung, T. M., & Bodmer, W. F. (2013) · Cancer Research · doi:10.1158/0008-5472.can-13-0454 · Cited by 46 · see citing works
Self-citationMyofibroblast activation in colorectal cancer lymph node metastases
Yeung, T. M., Buskens, C. J., Wang, L. M., et al. (2013) · British Journal of Cancer · doi:10.1038/bjc.2013.209 · Cited by 42 · see citing works
Lang, S., Smith, J., Hyde, C., et al. (2006) · In Vitro Cellular & Developmental Biology - Animal · doi:10.1290/0511080.1 · Cited by 29 · see citing works
Wilding, J. L., McGowan, S. J., Liu, Y., et al. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1015604107 · Cited by 22 · see citing works
Self-citationRothenberg‐Thurley, M., Vick, B., Schneider, S., et al. (2013) · Blood · doi:10.1182/blood.v122.21.49.49 · Cited by 2 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Beird, H. C., Bielack, S. S., Flanagan, A. M., Gill, J., Heymann, D., Janeway, K. A., Livingston, J. A., Roberts, R. D., Strauss, S. J., & Gorlick, R. (2022) · Nature Reviews Disease Primers · doi:10.1038/s41572-022-00409-y · Cited by 660 · see citing works
The molecular landscape of colorectal cancer cell lines unveils clinically actionable kinase targets
Medico, E., Russo, M., Picco, G., Cancelliere, C., Valtorta, E., Corti, G., Buscarino, M., Isella, C., Lamba, S., Martinoglio, B., et al. (2015) · Nature Communications · doi:10.1038/ncomms8002 · Cited by 302 · see citing works
Emerging organoid models: leaping forward in cancer research
Fan, H., Demirci, U., & Chen, P. (2019) · Journal of Hematology & Oncology · doi:10.1186/s13045-019-0832-4 · Cited by 199 · see citing works
Predicting and characterizing a cancer dependency map of tumors with deep learning
Chiu, Y.-C., Zheng, S., Wang, L.-J., Iskra, B. S., Rao, M. K., Houghton, P. J., Huang, Y., & Chen, Y. (2021) · Science Advances · doi:10.1126/sciadv.abh1275 · Cited by 84 · see citing works
“Furthermore, a model trained using merely CCL data may not fully capture tumor-specific contexts such as tumor heterogeneity and its microenvironment (19, 20).”
Method2D- and 3D-Based Intestinal Stem Cell Cultures for Personalized Medicine
Liu, Y., & Chen, Y.-G. (2018) · Cells · doi:10.3390/cells7120225 · Cited by 37 · see citing works
Rao, G., Kim, I.-K., Conforti, F., Liu, J., Zhang, Y.-W., & Giaccone, G. (2018) · European Journal of Cancer · doi:10.1016/j.ejca.2018.05.013 · Cited by 34 · see citing works
Engineering cell heterogeneity into organs-on-a-chip
Mertz, D. R., Ahmed, T., & Takayama, S. (2018) · Lab on a Chip · doi:10.1039/c8lc00413g · Cited by 33 · see citing works
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 · see citing works
Boussommier-Calleja, A. (2020) · Bioengineering Innovative Solutions for Cancer · doi:10.1016/b978-0-12-813886-1.00013-9 · Cited by 10 · see citing works
- Authors
- Wilding, J. L., & Bodmer, W. F.
- Affiliations
- John Radcliffe Hospital (GB)
- ORCID
- Bodmer, Walter F.
- Venue
- Cancer Research
- Published
- 2014-04-30
- Volume
- 74
- Issue
- 9
- Pages
- 2377-2384
- ISSN
- 0008-5472 (ISSN-L)
- 1538-7445
- OpenAlex
- W2130072062
- Cited by
- 432
- References
- 40
- Citations by year
- 2026: 24 · 2025: 27 · 2024: 47 · 2023: 37 · 2022: 36 · 2021: 54 · 2020: 45 · 2019: 43 · 2018: 29 · 2017: 32 · 2016: 30 · 2015: 20 · 2014: 8
- FWCI
- 3.41
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Cancer Research (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Oncology › Cancer Cells and Metastasis
- Health Sciences › Veterinary › Small Animals › Animal testing and alternatives
- Health Sciences › Medicine › Reproductive Medicine › Science, Research, and Medicine
- Keywords
- cancer cell lines, xenograft models, drug screening, prediction model, drug development, preclinical models, translational oncology
- MeSH terms
- Animals, Antineoplastic Agents, Drug Screening Assays, Antitumor, Humans, Neoplasms, Cell Line, Tumor
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
