Evidence map›Paper›PMID 24499937›Full record

ArticlePLoS computational biology2014

A model for the epigenetic switch linking inflammation to cell transformation: deterministic and stochastic approaches.

Claude Gérard, Didier Gonze, Frédéric Lemaigre, Béla Novák

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.9field-weighted citation impact, top 28% 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

7 citing papers in PubMed, 20 citations in OpenAlex.

  1. Review
  2. Crucial Roles of miR-625 in Human Cancer.Frontiers in medicine · 2022
    Review
  3. Article
  4. Article
  5. Review
  6. lnflammation-induced epigenetic switches in cancer.Cellular and molecular life sciences : CMLS · 2016
    Review
  7. Article
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 4 institutions in 2 countries.

Claude GérardOxford Centre for Integrative Systems Biology, Department of Biochemistry, University of Oxford, Oxford, United Kingdom ; de Duve Institute, Université Catholique de Louvain (UCL), Brussels, Belgium.
Didier GonzeFaculté des Sciences, Université Libre de Bruxelles (ULB), Campus Plaine, Brussels, Belgium.
Frédéric Lemaigrede Duve Institute, Université Catholique de Louvain (UCL), Brussels, Belgium.
Béla NovákOxford Centre for Integrative Systems Biology, Department of Biochemistry, University of Oxford, Oxford, United Kingdom.
de Duve Institute · BEUCLouvain · BEUniversité Libre de Bruxelles · BEUniversity of Oxford · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recently, a molecular pathway linking inflammation to cell transformation has been discovered. This molecular pathway rests on a positive inflammatory feedback loop between NF-κB, Lin28, Let-7 microRNA and IL6, which leads to an epigenetic switch allowing cell transformation. A transient activation of an inflammatory signal, mediated by the oncoprotein Src, activates NF-κB, which elicits the expression of Lin28. Lin28 decreases the expression of Let-7 microRNA, which results in higher level of IL6 than achieved directly by NF-κB. In turn, IL6 can promote NF-κB activation. Finally, IL6 also elicits the synthesis of STAT3, which is a crucial activator for cell transformation. Here, we propose a computational model to account for the dynamical behavior of this positive inflammatory feedback loop. By means of a deterministic model, we show that an irreversible bistable switch between a transformed and a non-transformed state of the cell is at the core of the dynamical behavior of the positive feedback loop linking inflammation to cell transformation. The model indicates that inhibitors (tumor suppressors) or activators (oncogenes) of this positive feedback loop regulate the occurrence of the epigenetic switch by modulating the threshold of inflammatory signal (Src) needed to promote cell transformation. Both stochastic simulations and deterministic simulations of a heterogeneous cell population suggest that random fluctuations (due to molecular noise or cell-to-cell variability) are able to trigger cell transformation. Moreover, the model predicts that oncogenes/tumor suppressors respectively decrease/increase the robustness of the non-transformed state of the cell towards random fluctuations. Finally, the model accounts for the potential effect of competing endogenous RNAs, ceRNAs, on the dynamics of the epigenetic switch. Depending on their microRNA targets, the model predicts that ceRNAs could act as oncogenes or tumor suppressors by regulating the occurrence of cell transformation.

Indexed as

Cell Transformation, NeoplasticEpigenesis, GeneticInflammationComputer SimulationGenes, Tumor SuppressorHumansKineticsMicroRNAsModels, BiologicalNF-kappa BOncogenesPTEN PhosphohydrolaseRNA-Binding ProteinsSTAT3 Transcription FactorStochastic ProcessesLin28A protein, humanMicroRNAsMIRN21 microRNA, humanmirnlet7 microRNA, humanNF-kappa BPTEN PhosphohydrolasePTEN protein, humanRNA-Binding ProteinsSTAT3 protein, humanSTAT3 Transcription Factor

Identifiers

PMID24499937
PMCPMC3907303
OpenAlexW2009987946

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.