The production of 3D tumor spheroids for cancer drug discovery
Open accessAbstract
New cancer drug approval rates are ≤ 5% despite significant investments in cancer research, drug discovery and development. One strategy to improve the rate of success of new cancer drugs transitioning into the clinic would be to more closely align the cellular models used in the early lead discovery with pre-clinical animal models and patient tumors. For solid tumors, this would mandate the development and implementation of three dimensional (3D) in vitro tumor models that more accurately recapitulate human solid tumor architecture and biology. Recent advances in tissue engineering and regenerative medicine have provided new techniques for 3D spheroid generation and a variety of in vitro 3D cancer models are being explored for cancer drug discovery. Although homogeneous assay methods and high content imaging approaches to assess tumor spheroid morphology, growth and viability have been developed, the implementation of 3D models in HTS remains challenging due to reasons that we discuss in this review. Perhaps the biggest obstacle to achieve acceptable HTS assay performance metrics occurs in 3D tumor models that produce spheroids with highly variable morphologies and/or sizes. We highlight two methods that produce uniform size-controlled 3D multicellular tumor spheroids that are compatible with cancer drug research and HTS; tumor spheroids formed in ultra-low attachment microplates, or in polyethylene glycol dimethacrylate hydrogel microwell arrays.
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?
When a tumor exceeds a critical diameter of 200 μm, hypoxia develops at its central core.
“When a tumor exceeds a critical diameter of 200 μm, hypoxia develops at its central core, and a complex biochemical cascade commands vascularization to start [126,184].”
From The Tumor-on-Chip: Recent Advances in the Development of Microfluidic Systems to Recapitulate the Physiology of Solid Tumors (2019) · cites this paper as [126]
The PEGDMA hydrogel microwell arrays section reports a hypoxic central core in large (600 μm) breast-cancer microtumors. It does not establish 200 μm as a critical diameter for tumors generally. The section also reports increased pro-angiogenic VEGF, but not that vascularization begins. (LLM, conf=0.88)
Experimental — accuracy not yet measuredA complex biochemical cascade commands vascularization to start when a tumor exceeds a critical diameter of 200 μm.
“When a tumor exceeds a critical diameter of 200 μm, hypoxia develops at its central core, and a complex biochemical cascade commands vascularization to start [126,184].”
From The Tumor-on-Chip: Recent Advances in the Development of Microfluidic Systems to Recapitulate the Physiology of Solid Tumors (2019) · cites this paper as [126]
The PEGDMA hydrogel microwell arrays section reports a hypoxic central core and increased pro-angiogenic VEGF in 600 μm breast-cancer microtumors. It does not establish a critical diameter of 200 μm or show that a biochemical cascade initiates vascularization at that threshold; the reported finding concerns an angiogenic signal, not observed vessel formation. No page number is available in our copy. (LLM, conf=0.88)
Experimental — accuracy not yet measuredSuspension culture generally has high throughput but lacks the ability to control the size and uniformity of the spheroids formed.
“Suspension culture generally has high throughput but lack the ability to control the size and uniformity of the spheroids formed [64,65].”
From Microfluidic modelling of the tumor microenvironment for anti-cancer drug development (2019) · cites this paper as [65]
The ‘Anchorage-independent tumor spheroids’ section says many methods produce aggregates with widely varying sizes and morphologies, supporting the uniformity concern. It does not support the claim that suspension culture generally has high throughput: it says some methods are labor-intensive and have been used only for small pilot screens. The ‘Ultra-low attachment microplates’ section also describes a method that is suitable for high-throughput screening and produces uniform-sized spheroids. (LLM, conf=0.88)
Experimental — accuracy not yet measuredTumor spheroids can be used to mimic in vivo tumor microenvironments because they have the ability to provide metabolism, proliferation, and species concentration gradients similar to those found in vivo.
“It can be used to mimic in vivo tumor microenvironments because it has the ability to provide metabolism, proliferation, and species concentration gradients similar to those found in vivo175,176.”
From Tumor-on-a-chip: from bioinspired design to biomedical application (2021) · cites this paper as [175]
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
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
Hydrogels as extracellular matrix mimics for 3D cell culture
Tibbitt, M. W., & Anseth, K. S. (2009) · Biotechnology and Bioengineering · doi:10.1002/bit.22361 · Cited by 2,727 · see citing works
Deconstructing the third dimension – how 3D culture microenvironments alter cellular cues
Baker, B. M., & Chen, C. S. (2012) · Journal of Cell Science · doi:10.1242/jcs.079509 · Cited by 1,760 · see citing works
Patient-Derived Xenograft Models: An Emerging Platform for Translational Cancer Research
Hidalgo, M. M., Amant, F. C., Biankin, A. V., Budínská, E., Byrne, A. T., Caldas, C., Clarke, R. B., de Jong, S., Jonkers, J., Mælandsmo, G. M., et al. (2014) · Cancer Discovery · doi:10.1158/2159-8290.cd-14-0001 · Cited by 1,748 · see citing works
Spheroid-based drug screen: Considerations and practical approach
Friedrich, J., Seidel, C., Ebner, R., & Kunz-Schughart, L. A. (2009) · Nature Protocols · doi:10.1038/nprot.2008.226 · Cited by 1,742 · see citing works
Gao, H., Korn, J. M., Ferretti, S., Monahan, J. E., Wang, Y., Singh, M., Zhang, C., Schnell, C., Yang, G., Zhang, Y., et al. (2015) · Nature Medicine · doi:10.1038/nm.3954 · Cited by 1,393 · see citing works
Abbott, A. (2003) · Nature · doi:10.1038/424870a · Cited by 1,237 · see citing works
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 · see citing works
Vinci, M., Gowan, S., Boxall, F., Patterson, L., Zimmermann, M., Court, W., Lomas, C., Mendiola, M., Hardisson, D., & Eccles, S. A. (2012) · BMC Biology · doi:10.1186/1741-7007-10-29 · Cited by 1,024 · see citing works
Engineering tumors with 3D scaffolds
Fischbach, C., Chen, R., Matsumoto, T., Schmelzle, T., Brugge, J. S., Polverini, P. J., & Mooney, D. J. (2007) · Nature Methods · doi:10.1038/nmeth1085 · Cited by 823 · see citing works
High drug attrition rates—where are we going wrong?
Hutchinson, L., & Kirk, R. (2011) · Nature Reviews Clinical Oncology · doi:10.1038/nrclinonc.2011.34 · Cited by 517 · see citing works
Härmä, V., Virtanen, J., Mäkelä, R., Happonen, A., Mpindi, J.-P., Knuuttila, M., Kohonen, P., Lötjönen, J., Kallioniemi, O., & Nees, M. (2010) · PLoS ONE · doi:10.1371/journal.pone.0010431 · Cited by 344 · see citing works
Three-dimensional cell culturing by magnetic levitation
Haisler, W. L., Timm, D. M., Gage, J. A., Tseng, H., Killian, T. C., & Souza, G. R. (2013) · Nature Protocols · doi:10.1038/nprot.2013.125 · Cited by 299 · see citing works
Clonogenic assay with established human tumour xenografts
Fiebig, H., Maier, A., & Burger, A. M. (2004) · European Journal of Cancer · doi:10.1016/j.ejca.2004.01.009 · Cited by 290 · see citing works
Advanced Cell Culture Techniques for Cancer Drug Discovery
Lovitt, C. J., Shelper, T., & Avery, V. M. (2014) · Biology · doi:10.3390/biology3020345 · Cited by 280 · see citing works
Head and neck squamous cell carcinoma cell lines: Established models and rationale for selection
Lin, C. J., Grandis, J. R., Carey, T. E., Gollin, S. M., Whiteside, T. L., Koch, W. M., Ferris, R. L., & Lai, S. Y. (2006) · Head & Neck · doi:10.1002/hed.20478 · Cited by 266 · see citing works
A Simple Hanging Drop Cell Culture Protocol for Generation of 3D Spheroids
Foty, R. (2011) · Journal of Visualized Experiments · doi:10.3791/2720 · Cited by 263 · see citing works
Wenzel, C., Riefke, B., Gründemann, S., Krebs, A., Christian, S., Prinz, F., Osterland, M., Golfier, S., Raese, S., Ansari, N., et al. (2014) · Experimental Cell Research · doi:10.1016/j.yexcr.2014.01.017 · Cited by 257 · see citing works
Bioprinting the Cancer Microenvironment
Zhang, Y. S., Duchamp, M., Öklü, R., Ellisen, L. W., Langer, R., & Khademhosseini, A. (2016) · ACS Biomaterials Science & Engineering · doi:10.1021/acsbiomaterials.6b00246 · Cited by 251 · see citing works
Yip, D., & Cho, C. H. (2013) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2013.03.008 · Cited by 236 · see citing works
Anticancer drug development: the grand challenges
Hait, W. N. (2010) · Nature Reviews Drug Discovery · doi:10.1038/nrd3144 · Cited by 231 · see citing works
Hongisto, V., Jernström, S., Fey, V., Mpindi, J.-P., Kleivi Sahlberg, K., Kallioniemi, O., & Perälä, M. (2013) · PLoS ONE · doi:10.1371/journal.pone.0077232 · Cited by 181 · see citing works
Three-dimensional in vitro cancer models: a short review
Wang, C., Tang, Z., Zhao, Y., Yao, R., Li, L., & Sun, W. (2014) · Biofabrication · doi:10.1088/1758-5082/6/2/022001 · Cited by 173 · see citing works
Ekert, J. E., Johnson, K., Strake, B., Pardinas, J. R., Jarantow, S. W., Perkinson, R. A., & Colter, D. C. (2014) · PLoS ONE · doi:10.1371/journal.pone.0092248 · Cited by 165 · see citing works
Preclinical development of molecular-targeted agents for cancer
Ocaña, A., Pandiella, A., Siu, L. L., & Tannock, I. F. (2010) · Nature Reviews Clinical Oncology · doi:10.1038/nrclinonc.2010.194 · Cited by 158 · see citing works
Establishment and characterization of SV40 T-antigen immortalized human esophageal epithelial cells.
Stoner, G. D., Kaighn, M. E., Reddel, R. R., et al. (1991) · PubMed · Cited by 156 · see citing works
Shin, C. S., Kwak, B., Han, B., & Park, K. (2013) · Molecular Pharmaceutics · doi:10.1021/mp300595a · Cited by 135 · see citing works
Rotem, A., Janzer, A., Izar, B., Ji, Z., Doench, J. G., Garraway, L. A., & Struhl, K. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1505979112 · Cited by 126 · see citing works
Howes, A. L., Richardson, R. D., Finlay, D., & Vuori, K. (2014) · PLoS ONE · doi:10.1371/journal.pone.0108283 · Cited by 121 · see citing works
Drug Discovery Approaches Utilizing Three-Dimensional Cell Culture
Ryan, S.-L., Baird, A., Vaz, G. M. F., Urquhart, A. J., Senge, M. O., Richard, D. J., O'Byrne, K. J., & Davies, A. M. (2016) · Assay and Drug Development Technologies · doi:10.1089/adt.2015.670 · Cited by 120 · see citing works
Bae, H., Chu, H., Edalat, F., Cha, J. M., Sant, S., Kashyap, A., Ahari, A. F., Kwon, C. H., Nichol, J. W., Manoucheri, S., et al. (2012) · Journal of Tissue Engineering and Regenerative Medicine · doi:10.1002/term.1494 · Cited by 109 · see citing works
Self-citationLi, X., Zhang, X., Zhao, S., Wang, J., Liu, G., & Du, Y. (2013) · Lab on a Chip · doi:10.1039/c3lc51103k · Cited by 94 · see citing works
Selective inhibition of esophageal cancer cells by combination of HDAC inhibitors and Azacytidine
Ahrens, T. D., Timme, S., Hoeppner, J., et al. (2015) · Epigenetics · doi:10.1080/15592294.2015.1039216 · Cited by 74 · see citing works
Singh, M., Close, D. A., Mukundan, S., Johnston, P. A., & Sant, S. (2015) · Assay and Drug Development Technologies · doi:10.1089/adt.2015.662 · Cited by 69 · see citing works
Self-citationNew anticancer agents: in vitro and in vivo evaluation.
Zips, D., Thames, H. D., & Baumann, M. A. (2005) · PubMed · Cited by 69 · see citing works
Three-Dimensional Breast Cancer Models Mimic Hallmarks of Size-Induced Tumor Progression
Singh, M., Mukundan, S., Jaramillo, M., Oesterreich, S., & Sant, S. (2016) · Cancer Research · doi:10.1158/0008-5472.can-15-2304 · Cited by 68 · see citing works
Self-citationPersonalized therapies in the cancer "omics" era
Ocaña, A., & Pandiella, A. (2010) · Molecular Cancer · doi:10.1186/1476-4598-9-202 · Cited by 67 · see citing works
Krausz, E., Hoogt, R. D., Gustin, E. M., Cornelissen, F. W., Grand‐Perret, T., Janssen, L., Vloemans, N., Wuyts, D., Frans, S., Axel, A. E., et al. (2012) · SLAS DISCOVERY · doi:10.1177/1087057112456874 · Cited by 65 · see citing works
Miniaturized Three-Dimensional Cancer Model for Drug Evaluation
Lovitt, C. J., Shelper, T., & Avery, V. M. (2013) · Assay and Drug Development Technologies · doi:10.1089/adt.2012.483 · Cited by 59 · see citing works
Patient‐derived xenografts as tools in pharmaceutical development
Izumchenko, E., Meir, J., Bedi, A., Wysocki, P., Hoque, M. O., & Sidransky, D. (2016) · Clinical Pharmacology & Therapeutics · doi:10.1002/cpt.354 · Cited by 57 · see citing works
Trask, O. J., Moore, A., & LeCluyse, E. L. (2014) · Assay and Drug Development Technologies · doi:10.1089/adt.2013.525 · Cited by 53 · see citing works
Tveit, K. M., Endresen, L., Rugstad, H. E., et al. (1981) · British Journal of Cancer · doi:10.1038/bjc.1981.223 · Cited by 48 · see citing works
A High-Throughput Soft Agar Assay for Identification of Anticancer Compound
Anderson, S. N., Towne, D. L., Burns, D. J., & Warrior, U. (2007) · SLAS DISCOVERY · doi:10.1177/1087057107306130 · Cited by 44 · see citing works
Alley, M. C., Pacula-Cox, C. M., Hursey, M. L., et al. (1991) · PubMed · Cited by 42 · see citing works
An HTS-Compatible 3D Colony Formation Assay to Identify Tumor-Specific Chemotherapeutics
Horman, S. R., To, J., & Orth, A. P. (2013) · SLAS DISCOVERY · doi:10.1177/1087057113499405 · Cited by 38 · see citing works
Fichter, C. D., Gudernatsch, V., Przypadlo, C. M., Follo, M., Schmidt, G., Werner, M., & Laßmann, S. (2014) · Journal of Molecular Medicine · doi:10.1007/s00109-014-1187-5 · Cited by 36 · see citing works
Johnston, P. A., Sen, M., Hua, Y., et al. (2013) · Assay and Drug Development Technologies · doi:10.1089/adt.2013.524 · Cited by 31 · see citing works
Self-citationAutomation of 3D Cell Culture Using Chemically Defined Hydrogels
Rimann, M., Angres, B., Tenzer, I. P., Braum, S., & Graf‐Hausner, U. (2013) · SLAS TECHNOLOGY · doi:10.1177/2211068213508651 · Cited by 28 · see citing works
Johnston, P. A., Sen, M., Hua, Y., Camarco, D. P., Shun, T. Y., Lazo, J. S., Wilson, G. M., Resnick, L., LaPorte, M. G., Wipf, P., et al. (2015) · Assay and Drug Development Technologies · doi:10.1089/adt.2015.663 · Cited by 27 · see citing works
Self-citationAutomated soft agar assay for the high-throughput screening of anticancer compounds
Thierbach, R., & Steinberg, P. (2009) · Analytical Biochemistry · doi:10.1016/j.ab.2009.01.029 · Cited by 24 · see citing works
Ahrens, T. D., Timme, S., Ostendorp, J., et al. (2015) · Laboratory Investigation · doi:10.1038/labinvest.2015.148 · Cited by 15 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Three-Dimensional Spheroids as In Vitro Preclinical Models for Cancer Research
Pinto, B., Henriques, A. C., Silva, P. M. A., & Bousbaa, H. (2020) · Pharmaceutics · doi:10.3390/pharmaceutics12121186 · Cited by 440 · see citing works
Tumor-on-a-chip: from bioinspired design to biomedical application
Liu, X., Fang, J., Huang, S., Wu, X., Xie, X., Wang, J., Liu, F., Zhang, M., Peng, Z., & Hu, N. (2021) · Microsystems & Nanoengineering · doi:10.1038/s41378-021-00277-8 · Cited by 246 · see citing works
Microfluidic modelling of the tumor microenvironment for anti-cancer drug development
Shang, M., Soon, R. H., Lim, C. T., Khoo, B. L., & Han, J. (2019) · Lab on a Chip · doi:10.1039/c8lc00970h · Cited by 227 · see citing works
Trujillo-de Santiago, G., Flores-Garza, B. G., Tavares-Negrete, J. A., Lara-Mayorga, I. M., González-Gamboa, I., Zhang, Y. S., Rojas-Martínez, A., Ortiz-López, R., & Álvarez, M. M. (2019) · Materials · doi:10.3390/ma12182945 · Cited by 184 · see citing works
“Modified from Sant and Johnston 2017 [126]; (b) Fabrication of spheroids by the following scaffold-free methods: (i) hanging drop [122,127–129], (ii) liquid-overlay method [130–136], and (iii) force-driven method [129,132,137–141]; (c) Fabrication of spheroids by the following scaffold-based…”
BackgroundMethodInfluentialTumor cells and their crosstalk with endothelial cells in 3D spheroids
Shoval, H., Karsch-Bluman, A., Brill-Karniely, Y., Stern, T., Zamir, G., Hubert, A., & Benny, O. (2017) · Scientific Reports · doi:10.1038/s41598-017-10699-y · Cited by 138 · see citing works
Fan, T. M., Roberts, R. D., & Lizardo, M. M. (2020) · Frontiers in Oncology · doi:10.3389/fonc.2020.00013 · Cited by 90 · see citing works
Kim, T. Y., Kofron, C. M., King, M. E., Markes, A. R., Okundaye, A. O., Qu, Z., Mende, U., & Choi, B.-R. (2018) · PLOS ONE · doi:10.1371/journal.pone.0196714 · Cited by 57 · see citing works
Bridging the gap between tumor-on-chip and clinics: a systematic review of 15 years of studies
Bouquerel, C., Dubrova, A., Hofer, I., Phan, D. T. T., Bernheim, M., Ladaigue, S., Cavaniol, C., Maddalo, D., Cabel, L., Mechta-Grigoriou, F., et al. (2023) · Lab on a Chip · doi:10.1039/d3lc00531c · Cited by 58 · see citing works
Wang, G., An, Y., Zhang, X., Ding, P., Bi, H., & Zhao, Z. (2021) · Gels · doi:10.3390/gels7040247 · Cited by 45 · see citing works
Boghaert, E. R., Cox, M. C., & Vaidya, K. S. (2022) · Cancer Research · doi:10.1158/0008-5472.can-21-3236 · Cited by 17 · see citing works
Generation of a Three-Dimensional In Vitro Ovarian Cancer Co-culture Model for Drug Screening Assays
Tofani, L. B., Sousa, L. O., Luiz, M. T., Abriata, J. P., Marchetti, J. M., Leopoldino, A. M., & Swiech, K. (2021) · Journal of Pharmaceutical Sciences · doi:10.1016/j.xphs.2021.04.003 · Cited by 14 · see citing works
Tomak, A., Saglam-Metiner, P., Coban, R., Oksel-Karakus, C., & Yesil-Celiktas, O. (2025) · Tissue and Cell · doi:10.1016/j.tice.2025.103080 · Cited by 6 · see citing works
- Authors
- Sant, S., & Johnston, P. A.
- Affiliations
- University of Pittsburgh (US)
- Corresponding author
- Johnston, Paul A.
- Venue
- Drug Discovery Today: Technologies
- Publisher
- Elsevier BV
- Published
- 2017-03
- Volume
- 23
- Pages
- 27-36
- ISSN
- 1740-6749 (ISSN-L)
- PMC
- PMC5497458
- OpenAlex
- W2606980922
- Semantic Scholar
- f1bf08642241d305968e216b5e72d70dc2f99d71
- Cited by
- 404
- References
- 51
- Citations by year
- 2026: 29 · 2025: 38 · 2024: 45 · 2023: 53 · 2022: 52 · 2021: 55 · 2020: 64 · 2019: 37 · 2018: 25 · 2017: 6
- FWCI
- 2.90
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Drug Discovery Today Technologies (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- NIH (EB018575)
- Department of Pharmaceutical Sciences at University of Pittsburgh
- 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 › Molecular Medicine › Hydrogels: synthesis, properties, applications
- Keywords
- tumor spheroids, anticancer drug discovery, high-throughput screening, 3D tumor models, spheroid morphology, tissue engineering
- MeSH terms
- Animals, Antineoplastic Agents, Humans, Methacrylates, Polyethylene Glycols, Tumor Cells, Cultured, Spheroids, Cellular, Hydrogels, Drug Discovery, High-Throughput Screening Assays, Tumor Microenvironment
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
