The DOI matches its Crossref record; 55 of the 55 references it cites were found in a registry or an index.
The Clinical Relevance of Cancer Cell Lines
Open accessAbstract
Although advances in genomics during the last decade have opened new avenues for translational research and allowed the direct evaluation of clinical samples, there is still a need for reliable preclinical models to test therapeutic strategies. Human cancer-derived cell lines are the most widely used models to study the biology of cancer and to test hypotheses to improve the efficacy of cancer treatment. Since the development of the first cancer cell line, the clinical relevance of these models has been continuously questioned. Based upon recent studies that have fueled the debate, we review the major events in the development of the in vitro models and the emergence of new technologies that have revealed important issues and limitations concerning human cancer cell lines as models. All cancer cell lines do not have equal value as tumor models. Some have been successful, whereas others have failed. However, the success stories should not obscure the growing body of data that motivates us to develop new in vitro preclinical models that would substantially increase the success rate of new in vitro-assessed cancer treatments.
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.
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
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
Intratumor Heterogeneity and Branched Evolution Revealed by Multiregion Sequencing
Gerlinger, M., Rowan, A. J., Horswell, S., Larkin, J., Endesfelder, D., Gronroos, E., Martinez, P., Matthews, N., Stewart, A., Tarpey, P., et al. (2012) · New England Journal of Medicine · doi:10.1056/nejmoa1113205 · Cited by 7,774
Lamb, J., Crawford, E. D., Peck, D., Modell, J. W., Blat, I. C., Wrobel, M. J., Lerner, J., Brunet, J.-P., Subramanian, A., Ross, K. N., et al. (2006) · Science · doi:10.1126/science.1132939 · Cited by 5,257
A collection of breast cancer cell lines for the study of functionally distinct cancer subtypes
Neve, R. M., Chin, K., Fridlyand, J., Yeh, J., Baehner, F. L., Fevr, T., Clark, L., Bayani, N., Coppe, J.-P., Tong, F., et al. (2006) · Cancer Cell · doi:10.1016/j.ccr.2006.10.008 · Cited by 3,188
The NCI60 human tumour cell line anticancer drug screen
Shoemaker, R. H. (2006) · Nature Reviews Cancer · doi:10.1038/nrc1951 · Cited by 2,620
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
Lee, J., Kotliarova, S., Kotliarov, Y., Li, A., Su, Q., Donin, N. M., Pastorino, S., Purow, B. W., Christopher, N., Zhang, W., et al. (2006) · Cancer Cell · doi:10.1016/j.ccr.2006.03.030 · Cited by 2,311
The Liver: Biology and Pathobiology.
(1983) · Annals of Internal Medicine · doi:10.7326/0003-4819-98-5-690_3 · Cited by 1,590
Progress in Clinical and Biological Research
Smyth, J. F. (1979) · Journal of Clinical Pathology · doi:10.1136/jcp.32.7.742-d · Cited by 1,543
The Connectivity Map: A new tool for biomedical research
Lamb, J. (2007) · Nature Reviews Cancer · doi:10.1038/nrc2044 · Cited by 945
Cited by
Artificial Intelligence in Cancer Research and Precision Medicine
Bhinder, B., Gilvary, C., Madhukar, N. S., & Elemento, O. (2021) · Cancer Discovery · doi:10.1158/2159-8290.cd-21-0090 · Cited by 781
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
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
Microenvironment drives cell state, plasticity, and drug response in pancreatic cancer
Raghavan, S., Winter, P. S., Navia, A. W., Williams, H. L., DenAdel, A., Lowder, K. E., Galvez-Reyes, J., Kalekar, R. L., Mulugeta, N., Kapner, K. S., et al. (2021) · Cell · doi:10.1016/j.cell.2021.11.017 · Cited by 592
Cell surface protein glycosylation in cancer
Christiansen, M. N., Chik, J., Lee, L., Anugraham, M., Abrahams, J. L., & Packer, N. H. (2014) · PROTEOMICS · doi:10.1002/pmic.201300387 · Cited by 518
Metadata
- Authors
- Gillet, J.-P., Varma, S., & Gottesman, M. M.
- Venue
- JNCI Journal of the National Cancer Institute
- Publisher
- Oxford University Press (OUP)
- Published
- 2013-02-21
- Volume
- 105
- Issue
- 7
- Pages
- 452-458
- ISSN
- 0027-8874 (ISSN-L)
- 1460-2105
- OpenAlex
- W2168102484
- Cited by
- 599
- References
- 55
- FWCI
- 13.75
- Type
- journal article
- Language
- en
- Open access
- green
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: The Clinical Relevance of Cancer Cell Lines. https://app.cochat.ai/papers/10.1093/jnci/djt007
- The paper
- Gillet, J.-P., Varma, S., & Gottesman, M. M. (2013). The Clinical Relevance of Cancer Cell Lines. JNCI Journal of the National Cancer Institute. https://doi.org/10.1093/jnci/djt007
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.