Evidence map›Paper›PMID 32126976›Full record

ArticleBMC bioinformatics2020

Modelling the effect of subcellular mutations on the migration of cells in the colorectal crypt.

Lotte B Romijn, Axel A Almet, Chin Wee Tan, James M Osborne

Open access · goldAbstract read
In one paragraph

Article in BMC bioinformatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.3field-weighted citation impact, top 40% 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

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. 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 at 2 institutions in 3 countries.

Lotte B RomijnSchool of Mathematics and Statistics, University of Melbourne, Parkville, VIC, Australia.
Axel A AlmetWolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Oxford, UK.
Chin Wee TanPersonalised Oncology Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia.
James M OsborneSchool of Mathematics and Statistics, University of Melbourne, Parkville, VIC, Australia. jmosborne@unimelb.edu.au.ORCID http://orcid.org/0000-0002-5622-0104
The University of Melbourne · AUUniversity of California, Irvine · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMany cancers arise from mutations in cells within epithelial tissues. Mutations manifesting at the subcellular level influence the structure and function of the tissue resulting in cancer. Previous work has proposed how cell level properties can lead to mutant cell invasion, but has not incorporated detailed subcellular modelling

resultsWe present a framework that allows the straightforward integration and simulation of SBML representations of subcellular dynamics within multiscale models of epithelial tissues. This allows us to investigate the effect of mutations in subcellular pathways on the migration of cells within the colorectal crypt. Using multiple models we find that mutations in APC, a key component in the Wnt signalling pathway, can bias neutral drift and can also cause downward invasion of mutant cells in the crypt.

conclusionsOur framework allows us to investigate how subcellular mutations, i.e. knockouts and knockdowns, affect cell-level properties and the resultant migration of cells within epithelial tissues. In the context of the colorectal crypt, we see that mutations in APC can lead directly to mutant cell invasion.

Indexed as

Models, BiologicalCell AdhesionCell MovementCell ProliferationColorectal NeoplasmsDatabases, FactualHumansMutationWnt Signaling PathwayChasteColorectal cancerCryptMulticellular modellingSBML

Identifiers

PMID32126976
PMCPMC7053074
OpenAlexW3012230971

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.