Evidence map›Paper›PMID 21499821›Full record

ArticleJournal of cell communication and signaling2011

3D tumour models: novel in vitro approaches to cancer studies.

Agata Nyga, Umber Cheema, Marilena Loizidou

Open access · bronzeAbstract read
In one paragraph

Article in Journal of cell communication and signaling, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 166 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
166citing papers in PubMed, 3 pooled it
13.3field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

166 citing papers in PubMed, 3 syntheses or guidelines pooled it, 402 citations in OpenAlex.

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  4. TheMaterials today. Bio · 2026
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  18. iMaterials today. Bio · 2024
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106 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 1 country.

Agata NygaCentre for Nanotechnology, Biomaterials and Tissue Engineering, University College London, London, UK.
Umber Cheema
Marilena Loizidou
University College London · GBStanmore College · GB

Funding

Biotechnology and Biological Sciences Research Council BB/F023774/1
6 · The paper itself

Abstract

3D in vitro models have been used in cancer research as a compromise between 2-dimensional cultures of isolated cancer cells and the manufactured complexity of xenografts of human cancers in immunocompromised animal hosts. 3D models can be tailored to be biomimetic and accurately recapitulate the native in vivo scenario in which they are found. These 3D in vitro models provide an important alternative to both complex in vivo whole organism approaches, and 2D culture with its spatial limitations. Approaches to create more biomimetic 3D models of cancer include, but are not limited to, (i) providing the appropriate matrix components in a 3D configuration found in vivo, (ii) co-culturing cancer cells, endothelial cells and other associated cells in a spatially relevant manner, (iii) monitoring and controlling hypoxia- to mimic levels found in native tumours and (iv) monitoring the release of angiogenic factors by cancer cells in response to hypoxia. This article aims to overview current 3D in vitro models of cancer and review strategies employed by researchers to tackle these aspects with special reference to recent promising developments, as well as the current limitations of 2D cultures and in vivo models. 3D in vitro models provide an important alternative to both complex in vivo whole organism approaches, and 2D culture with its spatial limitations. Here we review current strategies in the field of modelling cancer, with special reference to advances in complex 3D in vitro models.

Identifiers

PMID21499821
PMCPMC3145874
OpenAlexW1979700784

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.