Organotypic Modeling of the Tumor Landscape Article Swipe
YOU?
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· 2020
· Open Access
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· DOI: https://doi.org/10.3389/fcell.2020.606039
Cancer is a complex disease and it is now clear that not only epithelial tumor cells play a role in carcinogenesis. The tumor microenvironment is composed of non-stromal cells, including endothelial cells, adipocytes, immune and nerve cells, and a stromal compartment composed of extracellular matrix, cancer-associated fibroblasts and mesenchymal cells. Tumorigenesis is a dynamic process with constant interactions occurring between the tumor cells and their surroundings. Even though all connections have not yet been discovered, it is now known that crosstalk between actors of the microenvironment drives cancer progression. Taking into account this complexity, it is important to develop relevant models to study carcinogenesis. Conventional 2D culture models fail to represent the entire tumor microenvironment properly and the use of animal models should be decreased with respect to the 3Rs rule. To this aim, in vitro organotypic models have been significantly developed these past few years. These models have different levels of complexity and allow the study of tumor cells alone or in interaction with the microenvironment actors during the multiple stages of carcinogenesis. This review depicts recent insights into organotypic modeling of the tumor and its microenvironment all throughout cancer progression. It offers an overview of the crosstalk between epithelial cancer cells and their microenvironment during the different phases of carcinogenesis, from the early cell autonomous events to the late metastatic stages. The advantages of 3D over classical 2D or in vivo models are presented as well as the most promising organotypic models. A particular focus is made on organotypic models used for studying cancer progression, from the less complex spheroids to the more sophisticated body-on-a-chip. Last but not least, we address the potential benefits of these models in personalized medicine which is undoubtedly a domain paving the path to new hopes in terms of cancer care and cure.
Related Topics
- Type
- review
- Language
- en
- Landing Page
- https://doi.org/10.3389/fcell.2020.606039
- https://www.frontiersin.org/articles/10.3389/fcell.2020.606039/pdf
- OA Status
- gold
- Cited By
- 15
- References
- 225
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3109590185
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3109590185Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3389/fcell.2020.606039Digital Object Identifier
- Title
-
Organotypic Modeling of the Tumor LandscapeWork title
- Type
-
reviewOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2020Year of publication
- Publication date
-
2020-11-24Full publication date if available
- Authors
-
Maria M. Haykal, Clara Nahmias, Christine Varon, Océane MartinList of authors in order
- Landing page
-
https://doi.org/10.3389/fcell.2020.606039Publisher landing page
- PDF URL
-
https://www.frontiersin.org/articles/10.3389/fcell.2020.606039/pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://www.frontiersin.org/articles/10.3389/fcell.2020.606039/pdfDirect OA link when available
- Concepts
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Tumor microenvironment, Carcinogenesis, Stromal cell, Crosstalk, Biology, Cancer cell, Tumor progression, Extracellular matrix, Cancer research, Mesenchymal stem cell, Cancer, Cell biology, Tumor cells, Genetics, Optics, PhysicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
15Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 2, 2024: 3, 2023: 2, 2022: 2, 2021: 6Per-year citation counts (last 5 years)
- References (count)
-
225Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.promising | 241 |
| abstract_inverted_index.represent | 110 |
| abstract_inverted_index.spheroids | 261 |
| abstract_inverted_index.advantages | 224 |
| abstract_inverted_index.autonomous | 216 |
| abstract_inverted_index.complexity | 152 |
| abstract_inverted_index.epithelial | 13, 200 |
| abstract_inverted_index.metastatic | 221 |
| abstract_inverted_index.particular | 245 |
| abstract_inverted_index.throughout | 189 |
| abstract_inverted_index.adipocytes, | 32 |
| abstract_inverted_index.compartment | 40 |
| abstract_inverted_index.complexity, | 93 |
| abstract_inverted_index.connections | 69 |
| abstract_inverted_index.discovered, | 74 |
| abstract_inverted_index.endothelial | 30 |
| abstract_inverted_index.fibroblasts | 46 |
| abstract_inverted_index.interaction | 163 |
| abstract_inverted_index.mesenchymal | 48 |
| abstract_inverted_index.non-stromal | 27 |
| abstract_inverted_index.organotypic | 136, 180, 242, 250 |
| abstract_inverted_index.undoubtedly | 284 |
| abstract_inverted_index.Conventional | 104 |
| abstract_inverted_index.interactions | 57 |
| abstract_inverted_index.personalized | 280 |
| abstract_inverted_index.progression, | 256 |
| abstract_inverted_index.progression. | 88, 191 |
| abstract_inverted_index.Tumorigenesis | 50 |
| abstract_inverted_index.extracellular | 43 |
| abstract_inverted_index.significantly | 140 |
| abstract_inverted_index.sophisticated | 265 |
| abstract_inverted_index.surroundings. | 65 |
| abstract_inverted_index.body-on-a-chip. | 266 |
| abstract_inverted_index.carcinogenesis, | 211 |
| abstract_inverted_index.carcinogenesis. | 20, 103, 173 |
| abstract_inverted_index.microenvironment | 23, 85, 114, 166, 187, 205 |
| abstract_inverted_index.cancer-associated | 45 |
| cited_by_percentile_year.max | 98 |
| cited_by_percentile_year.min | 94 |
| corresponding_author_ids | https://openalex.org/A5023452339 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 4 |
| corresponding_institution_ids | https://openalex.org/I15057530, https://openalex.org/I154526488, https://openalex.org/I4210106115 |
| citation_normalized_percentile.value | 0.76883687 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |