In Vitro Tumor Models: Advantages, Disadvantages, Variables, and Selecting the Right Platform
Open accessAbstract
In vitro tumor models have provided important tools for cancer research and serve as low-cost screening platforms for drug therapies; however, cancer recurrence remains largely unchecked due to metastasis, which is the cause of the majority of cancer-related deaths. The need for an improved understanding of the progression and treatment of cancer has pushed for increased accuracy and physiological relevance of in vitro tumor models. As a result, in vitro tumor models have concurrently increased in complexity and their output parameters further diversified, since these models have progressed beyond simple proliferation, invasion, and cytotoxicity screens and have begun recapitulating critical steps in the metastatic cascade, such as intravasation, extravasation, angiogenesis, matrix remodeling, and tumor cell dormancy. Advances in tumor cell biology, 3D cell culture, tissue engineering, biomaterials, microfabrication, and microfluidics have enabled rapid development of new in vitro tumor models that often incorporate multiple cell types, extracellular matrix materials, and spatial and temporal introduction of soluble factors. Other innovations include the incorporation of perfusable microvessels to simulate the tumor vasculature and model intravasation and extravasation. The drive toward precision medicine has increased interest in adapting in vitro tumor models for patient-specific therapies, clinical management, and assessment of metastatic potential. Here, we review the wide range of current in vitro tumor models and summarize their advantages, disadvantages, and suitability in modeling specific aspects of the metastatic cascade and drug treatment.
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Conventional in vitro 3D cancer models are static systems (not based on microfluidics).
“The conventional in vitro 3D cancer models are static systems (i.e., they are not based on microfluidics) [102], but they do provide a valuable alternative to animal models and have enabled important advances in cancer research in the last two decades [5,103].”
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 [102]
The Spheroid Formation section describes conventional, non-microfluidic ways to grow 3D spheroids, such as liquid overlay and hanging drops. But it also describes techniques that use microfluidic devices, and the Summary and Future Prospects section says these devices are increasingly used to form spheroids. The source therefore supports the distinction as a generalization, not as a categorical claim that 3D cancer models are non-microfluidic. (LLM, conf=0.84)
Experimental — accuracy not yet measuredObtaining concordance between animal models and clinical trials remains challenging, with an average rate of concordant results that barely reaches 8%.
“Seymour and Ghert et al. demonstrated that obtaining concordance between animal models and clinical trials remains challenging, with an average rate of concordant results that barely reaches 8%21,39,40.”
From Tumor-on-a-chip: from bioinspired design to biomedical application (2021) · cites this paper as [40]
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“…to recapitulate cell-cell and cell-ECM interactions, failure to accurately model the perfusion of oxygen, nutrients, metabolites and drugs into the tumor mass, high costs, and complexity that is hard to deconvolve (Mak et al., 2014; Katt et al., 2016; Fontana et al., 2021; Rodrigues et al., 2021).”
Background
- Authors
- Katt, M. E., Placone, A. L., Wong, A. D., Xu, Z. S., & Searson, P. C.
- Affiliations
- Johns Hopkins University (US)
- Corresponding author
- Searson, Peter C.
- Venue
- Frontiers in Bioengineering and Biotechnology
- Publisher
- Frontiers Media SA
- Published
- 2016-02-12
- Volume
- 4
- Pages
- 12-12
- ISSN
- 2296-4185 (ISSN-L)
- PMC
- PMC4751256
- OpenAlex
- W2275816640
- Cited by
- 754
- References
- 141
- Citations by year
- 2026: 40 · 2025: 62 · 2024: 78 · 2023: 75 · 2022: 89 · 2021: 99 · 2020: 111 · 2019: 78 · 2018: 72 · 2017: 40 · 2016: 10
- FWCI
- 4.76
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Frontiers in Bioengineering and Biotechnology (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- National Institutes of Health (R01CA170629)
- 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
- in vitro tumor model, metastasis, metastatic cascade, 3D cell culture, microfluidics, intravasation, extravasation, angiogenesis, extracellular matrix remodeling, tumor dormancy, precision medicine, drug screening
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.
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