High-Throughput 3D Screening Reveals Differences in Drug Sensitivities between Culture Models of JIMT1 Breast Cancer Cells
Open accessAbstract
The traditional method for studying cancer in vitro is to grow immortalized cancer cells in two-dimensional monolayers on plastic. However, many cellular features are impaired in these artificial conditions, and large changes in gene expression compared to tumors have been reported. Three-dimensional cell culture models have become increasingly popular and are suggested to be better models than two-dimensional monolayers due to improved cell-to-cell contact and structures that resemble in vivo architecture. The aim of this study was to develop a simple high-throughput three-dimensional drug screening method and to compare drug responses in JIMT1 breast cancer cells when grown in two dimensions, in poly(2-hydroxyethyl methacrylate) induced anchorage-independent three-dimensional models, and in Matrigel three-dimensional cell culture models. We screened 102 compounds with multiple concentrations and biological replicates for their effects on cell proliferation. The cells were either treated immediately upon plating, or they were allowed to grow in three-dimensional cultures for 4 days before the drug treatment. Large variations in drug responses were observed between the models indicating that comparisons of culture model-influenced drug sensitivities cannot be made based on the effects of a single drug. However, we show with the 63 most prominent drugs that, in general, JIMT1 cells grown on Matrigel were significantly more sensitive to drugs than cells grown in two-dimensional cultures, while the responses of cells grown in poly(2-hydroxyethyl methacrylate) resembled those of the two-dimensional cultures. Furthermore, comparing the gene expression profiles of the cell culture models to xenograft tumors indicated that cells cultured in Matrigel and as xenografts most closely resembled each other. In this study, we also suggest that three-dimensional cultures can provide a platform for systematic experimentation of larger compound collections in a high-throughput mode and be used as alternatives to traditional two-dimensional screens for better comparability to the in vivo state.
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
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?
JIMT1 breast cancer cells grew 1.86-fold faster in Matrigel than in 2D culture.
“For example, JIMT1 breast cancer cells grew 1.86-fold faster in Matrigel than in 2D culture. 33”
From Three-dimensional cell culture systems and their applications in drug discovery and cell-based biosensors (2014) · cites this paper as [33]
The same JIMT1 cell line cultured on synthetic polyHEMA 3D scaffold exhibited a proliferation rate 7.2-fold slower than in 2D culture.
“But interestingly, the same cell line cultured on the synthetic poly(2-hydroxyethylmethacrylate) (polyHEMA) 3D scaffold, exhibited a proliferation rate that was 7.2-fold slower than in 2D culture, 33”
From Three-dimensional cell culture systems and their applications in drug discovery and cell-based biosensors (2014) · cites this paper as [33]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Gene Expression Omnibus: NCBI gene expression and hybridization array data repository
Edgar, R. (2002) · Nucleic Acids Research · doi:10.1093/nar/30.1.207 · Cited by 13,288 · see citing works
Bioconductor: open software development for computational biology and bioinformatics
Gentleman, R., Carey, V., Bates, D., Bolstad, B., Dettling, M., Dudoit, S., Ellis, B., Gautier, L., Ge, Y., Gentry, J., et al. (2004) · Genome Biology · doi:10.1186/gb-2004-5-10-r80 · Cited by 13,133 · see citing works
The third dimension bridges the gap between cell culture and live tissue
Pampaloni, F., Reynaud, E. G., & Stelzer, E. H. K. (2007) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm2236 · Cited by 2,817 · see citing works
Pvclust: an R package for assessing the uncertainty in hierarchical clustering
Suzuki, R., & Shimodaira, H. (2006) · Bioinformatics · doi:10.1093/bioinformatics/btl117 · Cited by 2,456 · see citing works
Role of cell shape in growth control
Folkman, J., & Moscona, A. (1978) · Nature · doi:10.1038/273345a0 · Cited by 2,422 · see citing works
lumi : a pipeline for processing Illumina microarray
Du, P., Kibbe, W. A., & Lin, S. M. (2008) · Bioinformatics · doi:10.1093/bioinformatics/btn224 · Cited by 2,028 · see citing works
Weaver, V. M., Petersen, O. W., Wang, F., Larabell, C. A., Briand, P., Damsky, C., & Bissell, M. J. (1997) · The Journal of Cell Biology · doi:10.1083/jcb.137.1.231 · Cited by 1,483 · see citing works
Use of within-array replicate spots for assessing differential expression in microarray experiments
Smyth, G. K., Michaud, J., & Scott, H. S. (2005) · Computer applications in the biosciences · doi:10.1093/bioinformatics/bti270 · Cited by 1,406 · see citing works
Three-dimensional culture models of normal and malignant breast epithelial cells
Lee, G. Y., Kenny, P. A., Lee, E. H., & Bissell, M. J. (2007) · Nature Methods · doi:10.1038/nmeth1015 · Cited by 1,336 · see citing works
Kenny, P. A., Lee, G. Y., Myers, C. A., Neve, R. M., Semeiks, J. R., Spellman, P. T., Lorenz, K., Lee, E. H., Barcellos‐Hoff, M. H., PETERSEN, O. W., et al. (2008) · eScholarship (California Digital Library) · Cited by 1,039 · see citing works
RankProd: a bioconductor package for detecting differentially expressed genes in meta-analysis
Hong, F., Breitling, R., McEntee, C., Wittner, B. S., Nemhauser, J. L., & Chory, J. (2006) · Bioinformatics · doi:10.1093/bioinformatics/btl476 · Cited by 741 · see citing works
Wang, F., Weaver, V. M., Petersen, O. W., Larabell, C. A., Dedhar, S., Briand, P., Lupu, R., & Bissell, M. J. (1998) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.95.25.14821 · Cited by 653 · see citing works
Ml, L., Aggeler, J., Farson, D. A., Hatier, C., Hassell, J. R., & Bissell, M. J. (1987) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.84.1.136 · Cited by 620 · see citing works
Loessner, D., Stok, K. S., Lutolf, M. P., Hutmacher, D. W., Clements, J. A., & Rizzi, S. C. (2010) · Biomaterials · doi:10.1016/j.biomaterials.2010.07.064 · Cited by 602 · see citing works
Modeling tissue-specific signaling and organ function in three dimensions
Schmeichel, K. L., & Bissell, M. J. (2003) · Journal of Cell Science · doi:10.1242/jcs.00503 · Cited by 583 · see citing works
Model-based variance-stabilizing transformation for Illumina microarray data
Lin, S. M., Du, P., Huber, W. K., & Kibbe, W. A. (2008) · Nucleic Acids Research · doi:10.1093/nar/gkm1075 · Cited by 515 · see citing works
Subtype and pathway specific responses to anticancer compounds in breast cancer
Heiser, L. M., Sadanandam, A., Kuo, W., Benz, S. C., Goldstein, T. C., Ng, S., Gibb, W. J., Wang, N. J., Ziyad, S., Tong, F. K., et al. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1018854108 · Cited by 464 · see citing works
Pickl, M., & Ries, C. H. (2008) · Oncogene · doi:10.1038/onc.2008.394 · Cited by 403 · see citing works
Multicellular resistance: a paradigm for clinical resistance?
Desoize, B. (2000) · Critical Reviews in Oncology/Hematology · doi:10.1016/s1040-8428(00)00086-x · Cited by 400 · see citing works
Kokkinos, M. I., Wafai, R., Wong, M. K., Newgreen, D. F., Thompson, E. W., & Waltham, M. (2007) · Cells Tissues Organs · doi:10.1159/000101320 · Cited by 394 · see citing works
Weigelt, B., Lo, A. T., Park, C. C., Gray, J. W., & Bissell, M. J. (2009) · Breast Cancer Research and Treatment · doi:10.1007/s10549-009-0502-2 · Cited by 336 · see citing works
Park, C. C., Zhang, H., Pallavicini, M., Gray, J. W., Baehner, F., Park, C. J., & Bissell, M. J. (2006) · Cancer Research · doi:10.1158/0008-5472.can-05-3071 · Cited by 326 · see citing works
Ghosh, S., Spagnoli, G. C., Martin, I., Ploegert, S., Demougin, P., Heberer, M., & Reschner, A. (2005) · Journal of Cellular Physiology · doi:10.1002/jcp.20320 · Cited by 326 · see citing works
Bissell, M. J., Kenny, P. A., & Radisky, D. C. (2005) · Cold Spring Harbor Symposia on Quantitative Biology · doi:10.1101/sqb.2005.70.013 · Cited by 297 · see citing works
3-D Tumor Model forIn VitroEvaluation of Anticancer Drugs
Horning, J. L., Sahoo, S. K., Vijayaraghavalu, S., Dimitrijevic, S., Vasir, J. K., Jain, T. K., Panda, A. K., & Labhasetwar, V. D. (2008) · Molecular Pharmaceutics · doi:10.1021/mp800047v · Cited by 292 · see citing works
Acquired multicellular-mediated resistance to alkylating agents in cancer.
Kobayashi, H., Man, S., Graham, C. H., Kapitain, S. J., Teicher, B. A., & Kerbel, R. S. (1993) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.90.8.3294 · Cited by 277 · see citing works
Tanner, M., Kapanen, A. I., Junttila, T. T., Raheem, O., Grénman, S., Elo, J. P., Elenius, K., & Isola, J. J. (2004) · Molecular Cancer Therapeutics · doi:10.1158/1535-7163.1585.3.12 · Cited by 272 · see citing works
Gurski, L. A., Jha, A. K., Zhang, C., Jia, X., & Farach-Carson, M. C. (2009) · Biomaterials · doi:10.1016/j.biomaterials.2009.07.054 · Cited by 269 · see citing works
β1 Integrin Inhibition Dramatically Enhances Radiotherapy Efficacy in Human Breast Cancer Xenografts
Park, C. C., Zhang, H. J., Yao, E. S., Park, C. J., & Bissell, M. J. (2008) · Cancer Research · doi:10.1158/0008-5472.can-07-6390 · Cited by 220 · see citing works
Serebriiskii, I. G., Castelló-Cros, R., Lamb, A., Golemis, E. A., & Cukierman, E. (2008) · Matrix Biology · doi:10.1016/j.matbio.2008.02.008 · Cited by 176 · see citing works
Cheng, W., Kandel, J. J., Yamashiro, D. J., Canoll, P., & Anastassiou, D. (2012) · PLoS ONE · doi:10.1371/journal.pone.0034705 · Cited by 132 · see citing works
Lan, S.-F., Safiejko‐Mroczka, B., & Starly, B. (2010) · Toxicology in Vitro · doi:10.1016/j.tiv.2010.02.015 · Cited by 123 · see citing works
Erlichman, C., & Vidgen, D. (1984) · PubMed · Cited by 94 · see citing works
Lin, Y., Buckhaults, P., Lee, J. R., Xiong, H., Farrell, C. L., Podolsky, R. H., Schade, R. R., & Dynan, W. S. (2009) · Neoplasia · doi:10.1593/neo.09542 · Cited by 93 · see citing works
Dimanche‐Boitrel, M., Pelletier, H., Genne, P., et al. (1992) · International Journal of Cancer · doi:10.1002/ijc.2910500502 · Cited by 91 · see citing works
David, L., Dulong, V., Cerf, D. L., et al. (2007) · Acta Biomaterialia · doi:10.1016/j.actbio.2007.08.012 · Cited by 91 · see citing works
Factors affecting growth and drug sensitivity of mouse mammary tumor lines in collagen gel cultures.
Miller, B. E., Miller, F. R., & Heppner, G. H. (1985) · PubMed · Cited by 88 · see citing works
Li, Q., Chow, A. B., & Mattingly, R. R. (2009) · Journal of Pharmacology and Experimental Therapeutics · doi:10.1124/jpet.109.160390 · Cited by 77 · see citing works
VENNTURE–A Novel Venn Diagram Investigational Tool for Multiple Pharmacological Dataset Analysis
Martin, B., Chadwick, W., Yi, T., Park, S. S., Lu, D., Ni, B., Gadkaree, S. K., Farhang, K., Becker, K. G., & Maudsley, S. R. (2012) · PLoS ONE · doi:10.1371/journal.pone.0036911 · Cited by 70 · see citing works
Kim, H., Phung, Y., & Ho, M. (2012) · PLoS ONE · doi:10.1371/journal.pone.0039556 · Cited by 68 · see citing works
Regulation of extracellular matrix degradation by cell—extracellular matrix interactions
Werb, Z., Tremble, P., Werb, Z., Damsky, C. H., Tremble, P., & Damsky, C. H. (1990) · Cell Differentiation and Development · doi:10.1016/0922-3371(90)90043-v · Cited by 62 · see citing works
Miller, F. R., McEachern, D., & Miller, B. E. (1989) · PubMed · Cited by 61 · see citing works
Aceto, N., Duss, S., MacDonald, G., Meyer, D. S., Roloff, T. C., Hynes, N. E., & Bentires‐Alj, M. (2012) · Breast Cancer Research · doi:10.1186/bcr3329 · Cited by 50 · see citing works
Pelletier, H., Millot, J. M., Chauffert, B., et al. (1990) · PubMed · Cited by 49 · see citing works
Shi, Y., Bao, Y. L., Wu, Y., et al. (2011) · SLAS DISCOVERY · doi:10.1177/1087057111398486 · Cited by 47 · see citing works
Effect of culture conditions on the chemosensitivity of ovarian cancer cell lines
Fernando, A., Glaysher, S., Conroy, M., et al. (2006) · Anti-Cancer Drugs · doi:10.1097/01.cad.0000224445.23953.d9 · Cited by 27 · see citing works
Garrido, C. R., Chauffert, B., Pinard, D., et al. (1995) · International Journal of Cancer · doi:10.1002/ijc.2910610621 · Cited by 26 · see citing works
Tumor cell heterogeneity: divided-colony assay for measuring drug response.
Kuczek, T., & Axelrod, D. E. (1987) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.84.13.4490 · Cited by 23 · see citing works
Drug sensitivity of ten human tumor cell lines compared to mouse leukemia (L1210) cells
Badiner, G. J., Hamilton, R. D., Li, L. H., et al. (1987) · Investigational New Drugs · doi:10.1007/bf00175291 · Cited by 6 · see citing works
Kenny, P. A., Lee, G. Y., Myers, C. A., Neve, R. M., Semeiks, J. R., Spellman, P. T., Lorenz, K., Lee, E. H., Barcellos-Hoff, M. H., Petersen, O. W., et al. (2007) · Molecular Oncology · doi:10.1016/j.molonc.2007.02.004 · Cited by 2 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Edmondson, R., Broglie, J. J., Adcock, A. F., & Yang, L. (2014) · ASSAY and Drug Development Technologies · doi:10.1089/adt.2014.573 · Cited by 2,515 · see citing works
The production of 3D tumor spheroids for cancer drug discovery
Sant, S., & Johnston, P. A. (2017) · Drug Discovery Today: Technologies · doi:10.1016/j.ddtec.2017.03.002 · Cited by 404 · see citing works
3D scaffolds in breast cancer research
Rijal, G., & Li, W. (2016) · Biomaterials · doi:10.1016/j.biomaterials.2015.12.016 · Cited by 169 · see citing works
Polysaccharide matrices used in 3D in vitro cell culture systems
Diekjürgen, D., & Grainger, D. W. (2017) · Biomaterials · doi:10.1016/j.biomaterials.2017.06.020 · Cited by 125 · see citing works
Toward the broad adoption of 3D tumor models in the cancer drug pipeline
Cox, M. C., Reese, L. M., Bickford, L. R., & Verbridge, S. S. (2015) · ACS Biomaterials Science & Engineering · doi:10.1021/acsbiomaterials.5b00172 · Cited by 80 · see citing works
- Authors
- Hongisto, V., Jernström, S., Fey, V., Mpindi, J.-P., Kleivi Sahlberg, K., Kallioniemi, O., & Perälä, M.
- Affiliations
- VTT Technical Research Centre of Finland (FI)
- Oslo University Hospital (NO)
- University of Helsinki (FI)
- Corresponding author
- Hongisto, Vesa
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2013-10-23
- Volume
- 8
- Issue
- 10
- Pages
- e77232
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC3806867
- OpenAlex
- W2009798744
- Cited by
- 181
- References
- 50
- Citations by year
- 2026: 3 · 2025: 8 · 2024: 5 · 2023: 17 · 2022: 22 · 2021: 16 · 2020: 20 · 2019: 17 · 2018: 13 · 2017: 24 · 2016: 15 · 2015: 11 · 2014: 10
- FWCI
- 6.61
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- PLoS ONE (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, other-oa)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Figshare (submittedVersion, cc-by)
- Työväentutkimus Vuosikirja (submittedVersion)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › 3D Printing in Biomedical Research
- Health Sciences › Medicine › Oncology › Cancer Cells and Metastasis
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cell Biology › Cellular Mechanics and Interactions
- Keywords
- 3D cell culture, breast cancer, high-throughput drug screening, Matrigel, poly(2-hydroxyethyl methacrylate), anchorage-independent growth, drug sensitivity, cell proliferation
- MeSH terms
- Antineoplastic Agents, Breast Neoplasms, Collagen, Drug Combinations, Drug Screening Assays, Antitumor, Female, Humans, Laminin, Polyhydroxyethyl Methacrylate, Proteoglycans, Gene Expression Regulation, Neoplastic, Linear Models, Cell Culture Techniques, Gene Expression Profiling, Cell Line, Tumor, Cell Proliferation, High-Throughput Screening Assays
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
