Evidence map›Paper›PMID 30727966›Full record

ArticleBMC genomics2019

A mathematical model as a tool to identify microRNAs with highest impact on transcriptome changes.

Marzena Mura, Roman Jaksik, Anna Lalik, Krzysztof Biernacki, Marek Kimmel, Joanna Rzeszowska-Wolny, Krzysztof Fujarewicz

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.2field-weighted citation impact, top 51% 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

0 citing papers in PubMed, 5 citations in OpenAlex.

No citing paper in PubMed yet.

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

7 authors at 1 institution in 2 countries.

Marzena MuraDepartment of Systems Engineering, Institute of Automatic Control, Silesian University of Technology, ul. Akademicka 16, 44-100, Gliwice, Poland. marzena.mura@polsl.pl.ORCID http://orcid.org/0000-0002-8482-3439
Roman JaksikDepartment of Systems Engineering, Institute of Automatic Control, Silesian University of Technology, ul. Akademicka 16, 44-100, Gliwice, Poland.
Anna LalikDepartment of Systems Engineering, Institute of Automatic Control, Silesian University of Technology, ul. Akademicka 16, 44-100, Gliwice, Poland.
Krzysztof BiernackiDepartment of Medical and Molecular Biology, School of Medicine with the Division of Dentistry in Zabrze, Medical University of Silesia in Katowice, Katowice, USA.
Marek KimmelDepartment of Systems Engineering, Institute of Automatic Control, Silesian University of Technology, ul. Akademicka 16, 44-100, Gliwice, Poland.
Joanna Rzeszowska-WolnyDepartment of Systems Engineering, Institute of Automatic Control, Silesian University of Technology, ul. Akademicka 16, 44-100, Gliwice, Poland. joanna.rzeszowska@polsl.pl.
Krzysztof FujarewiczDepartment of Systems Engineering, Institute of Automatic Control, Silesian University of Technology, ul. Akademicka 16, 44-100, Gliwice, Poland.
Silesian University of Technology · PL

Funding

Narodowe Centrum Nauki UMO-2015/19/B/ST7/02984
6 · The paper itself

Abstract

backgroundRapid changes in the expression of many messenger RNA (mRNA) species follow exposure of cells to ionizing radiation. One of the hypothetical mechanisms of this response may include microRNA (miRNA) regulation, since the amounts of miRNAs in cells also vary upon irradiation. To address this possibility, we designed experiments using cancer-derived cell lines transfected with luciferase reporter gene containing sequences targeted by different miRNA species in its 3'- untranslated region. We focus on the early time-course response (1 h past irradiation) to eliminate secondary mRNA expression waves.

resultsExperiments revealed that the irradiation-induced changes in the mRNA expression depend on the miRNAs which interact with mRNA. To identify the strongest interactions, we propose a mathematical model which predicts the mRNA fold expression changes, caused by perturbation of microRNA-mRNA interactions. Model was applied to experimental data including various cell lines, irradiation doses and observation times, both ours and literature-based. Comparison of modelled and experimental mRNA expression levels given miRNA level changes allows estimating how many and which miRNAs play a significant role in transcriptome response to stress conditions in different cell types. As an example, in the human melanoma cell line the comparison suggests that, globally, a major part of the irradiation-induced changes of mRNA expression can be explained by perturbed miRNA-mRNA interactions. A subset of about 30 out of a few hundred miRNAs expressed in these cells appears to account for the changes. These miRNAs play crucial roles in regulatory mechanisms observed after irradiation. In addition, these miRNAs have a higher average content of GC and a higher number of targeted transcripts, and many have been reported to play a role in the development of cancer.

conclusionsOur proposed mathematical modeling approach may be used to identify miRNAs which participate in responses of cells to ionizing radiation, and other stress factors such as extremes of temperature, exposure to toxins, and drugs.

Indexed as

Gene Expression Regulation, NeoplasticModels, BiologicalRadiation, IonizingStress, PhysiologicalCell Line, TumorGene Expression ProfilingHumansMicroRNAsNeoplasmsRNA, MessengerMicroRNAsRNA, Messengerionizing radiationmiRNAmiRNA-mRNA interactionsstressing factor

Identifiers

PMID30727966
PMCPMC6366035
OpenAlexW2917757266

What OpenQuestion holds

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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.