Evidence map›Paper›PMID 35735676›Full record

ArticleGels (Basel, Switzerland)2022

Self-Assembled Peptide Habitats to Model Tumor Metastasis.

Noora Al Balushi, Mitchell Boyd-Moss, Rasika M Samarasinghe, Aaqil Rifai, Stephanie J Franks, Kate Firipis, Benjamin M Long, Ian A Darby, David R Nisbet, Dodie Pouniotis and 1 more

Abstract read
In one paragraph

Article in Gels (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. 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

11 authors.

Noora Al BalushiSchool of Health and Biomedical Sciences, RMIT University, Melbourne, VIC 3000, Australia.ORCID 0000-0002-9509-6417
Mitchell Boyd-MossSchool of Engineering, RMIT University, Melbourne, VIC 3000, Australia.ORCID 0000-0002-8670-8477
Rasika M SamarasingheSchool of Medicine, Deakin University, Waurn Ponds, VIC 3216, Australia.ORCID 0000-0002-3669-0985
Aaqil RifaiSchool of Engineering, RMIT University, Melbourne, VIC 3000, Australia.
Stephanie J FranksLaboratory of Advanced Biomaterials, Research School of Chemistry and the John Curtin School of Medical Research, Australian National University, Canberra, ACT 2601, Australia.ORCID 0000-0002-7095-3451
Kate FiripisSchool of Engineering, RMIT University, Melbourne, VIC 3000, Australia.ORCID 0000-0002-0534-4924
Benjamin M LongFuture Regions Research Centre, Federation University Australia, Mount Helen, VIC 3353, Australia.
Ian A DarbySchool of Health and Biomedical Sciences, RMIT University, Melbourne, VIC 3000, Australia.
David R NisbetLaboratory of Advanced Biomaterials, Research School of Chemistry and the John Curtin School of Medical Research, Australian National University, Canberra, ACT 2601, Australia.ORCID 0000-0002-1343-0769
Dodie PouniotisSchool of Health and Biomedical Sciences, RMIT University, Melbourne, VIC 3000, Australia.
Richard J WilliamsSchool of Engineering, RMIT University, Melbourne, VIC 3000, Australia.ORCID 0000-0003-3831-8738

Funding

Australian Research Council DP130103131National Health and Medical Research Council GNT1144996
6 · The paper itself

Abstract

Metastatic tumours are complex ecosystems; a community of multiple cell types, including cancerous cells, fibroblasts, and immune cells that exist within a supportive and specific microenvironment. The interplay of these cells, together with tissue specific chemical, structural and temporal signals within a three-dimensional (3D) habitat, direct tumour cell behavior, a subtlety that can be easily lost in 2D tissue culture. Here, we investigate a significantly improved tool, consisting of a novel matrix of functionally programmed peptide sequences, self-assembled into a scaffold to enable the growth and the migration of multicellular lung tumour spheroids, as proof-of-concept. This 3D functional model aims to mimic the biological, chemical, and contextual cues of an in vivo tumor more closely than a typically used, unstructured hydrogel, allowing spatial and temporal activity modelling. This approach shows promise as a cancer model, enhancing current understandings of how tumours progress and spread over time within their microenvironment.

Indexed as

cancerfunctionalisationhydrogelmatrixpeptideself-assembly

Identifiers

PMID35735676
PMCPMC9223161

What OpenQuestion 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 OpenQuestion graph.