Evidence map›Paper›PMID 29774110›Full record

ArticleOncotarget2018

High-throughput 3-dimensional culture of epithelial ovarian cancer cells as preclinical model of disease.

Victoria Heredia-Soto, Andrés Redondo, Alberto Berjón, María Miguel-Martín, Esther Díaz, Roberto Crespo, Alicia Hernández, Laura Yébenes, Alejandro Gallego, Jaime Feliu and 2 more

Abstract read
In one paragraph

Article in Oncotarget, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
–field-weighted citation impact
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

22 citing papers in PubMed.

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  12. Polymeric Hydrogels for In Vitro 3D Ovarian Cancer Modeling.International journal of molecular sciences · 2022
    Review
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  19. The hallmarks of ovarian cancer: Focus on angiogenesis and micro-environment and new models for their characterisation.EJC supplements : EJC : official journal of EORTC, European Organization for Research and Treatment of Cancer ... [et al.] · 2020
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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

12 authors.

Victoria Heredia-SotoMolecular Pathology and Therapeutic Targets Research Lab, Instituto de Investigación del Hospital Universitario La Paz, IdiPAZ, Hospital Universitario La Paz, HULP, Madrid 28046, Spain.
Andrés RedondoDepartment of Medical Oncology, Hospital Universitario La Paz, HULP, Madrid 28046, Spain.
Alberto BerjónMolecular Pathology and Therapeutic Targets Research Lab, Instituto de Investigación del Hospital Universitario La Paz, IdiPAZ, Hospital Universitario La Paz, HULP, Madrid 28046, Spain.
María Miguel-MartínMolecular Pathology and Therapeutic Targets Research Lab, Instituto de Investigación del Hospital Universitario La Paz, IdiPAZ, Hospital Universitario La Paz, HULP, Madrid 28046, Spain.
Esther DíazTranslational Oncology Research Lab, IdiPAZ, Hospital Universitario La Paz, HULP, Madrid 28046, Spain.
Roberto CrespoTranslational Oncology Research Lab, IdiPAZ, Hospital Universitario La Paz, HULP, Madrid 28046, Spain.
Alicia HernándezDepartment of Gynecology and Obstetrics, Hospital Universitario La Paz, HULP, Madrid 28046, Spain.
Laura YébenesMolecular Pathology and Therapeutic Targets Research Lab, Instituto de Investigación del Hospital Universitario La Paz, IdiPAZ, Hospital Universitario La Paz, HULP, Madrid 28046, Spain.
Alejandro GallegoDepartment of Medical Oncology, Hospital Universitario La Paz, HULP, Madrid 28046, Spain.
Jaime FeliuCentro de Investigación Biomédica en Red de Cáncer, CIBERONC. Instituto de Salud Carlos III, Madrid 28029, Spain.
David HardissonMolecular Pathology and Therapeutic Targets Research Lab, Instituto de Investigación del Hospital Universitario La Paz, IdiPAZ, Hospital Universitario La Paz, HULP, Madrid 28046, Spain.
Marta MendiolaMolecular Pathology and Therapeutic Targets Research Lab, Instituto de Investigación del Hospital Universitario La Paz, IdiPAZ, Hospital Universitario La Paz, HULP, Madrid 28046, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRecent reports have identified distinct genomic patterns in ovarian carcinoma, including proliferative and mesenchymal-like groups, with worse outcome. The exact mechanisms driving the onset and progression of these tumors are still poorly understood. Additionally, researchers are concerned about the correct subtype stratification of the available cell line models, and the exploration of alternatives to monolayer culture. Identification of biomarkers to stratify cell lines, characterization of important processes as epithelial-mesenchymal transition (EMT), and the use of three-dimensional (3D) cultures as alternative models could be useful for cell line classification. METHODS AND

resultsIn this work, we present a descriptive analysis of 16 commonly used ovarian cancer cell lines. We have studied their morphology in 2- and 3D culture, and their response to cisplatin, observing in the majority of them an increased resistance in 3D. We have also performed an immunohistochemical analysis for proliferation marker Ki-67, and EMT related markers to establish phenotypes. Epithelial cells tend to show higher proliferative rates, and mesenchymal cells show an increase in EMT related markers, especially when cultured in 3D conditions.

conclusionsWe have stated the complex heterogeneity of ovarian cancer models, resembling primary tumors, agreeing with the argument that the cell line model for

Indexed as

3D cell culture modelepithelial mesenchymal transitionovarian cancer

Identifiers

PMID29774110
PMCPMC5955171

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.