Evidence map›Paper›PMID 34830897›Full record

ReviewCancers2021

Modeling the Tumor Microenvironment of Ovarian Cancer: The Application of Self-Assembling Biomaterials.

Ana Karen Mendoza-Martinez, Daniela Loessner, Alvaro Mata, Helena S Azevedo

Abstract readReview
In one paragraph

Review in Cancers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Polymeric Hydrogels for In Vitro 3D Ovarian Cancer Modeling.International journal of molecular sciences · 2022
    Review
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

4 authors.

Ana Karen Mendoza-MartinezSchool of Engineering and Materials Science, Queen Mary University of London, Mile End Road, London E1 4NS, UK.ORCID 0000-0003-1113-4971
Daniela LoessnerDepartment of Chemical Engineering, Faculty of Engineering, Monash University, Melbourne, VIC 3800, Australia.ORCID 0000-0001-5891-3441
Alvaro MataSchool of Pharmacy, University of Nottingham, Nottingham NG7 2RD, UK.
Helena S AzevedoSchool of Engineering and Materials Science, Queen Mary University of London, Mile End Road, London E1 4NS, UK.ORCID 0000-0002-5470-1844

Funding

Consejo Nacional de Ciencia y Tecnología 753881Medical Research Council MR/K026682/1Medical Research Council MR/R015651/1
6 · The paper itself

Abstract

Ovarian cancer (OvCa) is one of the leading causes of gynecologic malignancies. Despite treatment with surgery and chemotherapy, OvCa disseminates and recurs frequently, reducing the survival rate for patients. There is an urgent need to develop more effective treatment options for women diagnosed with OvCa. The tumor microenvironment (TME) is a key driver of disease progression, metastasis and resistance to treatment. For this reason, 3D models have been designed to represent this specific niche and allow more realistic cell behaviors compared to conventional 2D approaches. In particular, self-assembling peptides represent a promising biomaterial platform to study tumor biology. They form nanofiber networks that resemble the architecture of the extracellular matrix and can be designed to display mechanical properties and biochemical motifs representative of the TME. In this review, we highlight the properties and benefits of emerging 3D platforms used to model the ovarian TME. We also outline the challenges associated with using these 3D systems and provide suggestions for future studies and developments. We conclude that our understanding of OvCa and advances in materials science will progress the engineering of novel 3D approaches, which will enable the development of more effective therapies.

Indexed as

3D modelsbiomaterialextracellular matrixmechanical propertiesovarian cancerpeptidesself-assemblytumor microenvironment

Identifiers

PMID34830897
PMCPMC8616551

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.