Evidence map›Paper›PMID 23724959›Full record

ArticleBMC genomics2013

Microarray and deep sequencing cross-platform analysis of the mirRNome and isomiR variation in response to epidermal growth factor.

Franc Llorens, Manuela Hummel, Lorena Pantano, Xavier Pastor, Ana Vivancos, Ester Castillo, Heidi Mattlin, Anna Ferrer, Matthew Ingham, Marc Noguera and 8 more

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
2.7field-weighted citation impact, top 11% 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

23 citing papers in PubMed, 35 citations in OpenAlex.

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  4. Bioengineered Noncoding RNAs Selectively Change Cellular miRNome Profiles for Cancer Therapy.The Journal of pharmacology and experimental therapeutics · 2018
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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

18 authors at 4 institutions in 4 countries.

Franc LlorensCentre for Genomic Regulation (CRG), Barcelona, Spain.
Manuela Hummel
Lorena Pantano
Xavier Pastor
Ana Vivancos
Ester Castillo
Heidi Mattlin
Anna Ferrer
Matthew Ingham
Marc Noguera
Robert Kofler
Juliane C Dohm
Raquel Pluvinet
Mònica Bayés
Heinz Himmelbauer
José Antonio del Rio
Eulàlia Martí
Lauro Sumoy
Centre for Genomic Regulation · ESPompeu Fabra University · ESInstitute of Predictive and Personalized Medicine of Cancer · ESUniversitat de Barcelona · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEpidermal Growth Factor (EGF) plays an important function in the regulation of cell growth, proliferation, and differentiation by binding to its receptor (EGFR) and providing cancer cells with increased survival responsiveness. Signal transduction carried out by EGF has been extensively studied at both transcriptional and post-transcriptional levels. Little is known about the involvement of microRNAs (miRNAs) in the EGF signaling pathway. miRNAs have emerged as major players in the complex networks of gene regulation, and cancer miRNA expression studies have evidenced a direct involvement of miRNAs in cancer progression.

resultsIn this study, we have used an integrative high content analysis approach to identify the specific miRNAs implicated in EGF signaling in HeLa cells as potential mediators of cancer mediated functions. We have used microarray and deep-sequencing technologies in order to obtain a global view of the EGF miRNA transcriptome with a robust experimental cross-validation. By applying a procedure based on Rankprod tests, we have delimited a solid set of EGF-regulated miRNAs. After validating regulated miRNAs by reverse transcription quantitative PCR, we have derived protein networks and biological functions from the predicted targets of the regulated miRNAs to gain insight into the potential role of miRNAs in EGF-treated cells. In addition, we have analyzed sequence heterogeneity due to editing relative to the reference sequence (isomiRs) among regulated miRNAs.

conclusionsWe propose that the use of global genomic miRNA cross-validation derived from high throughput technologies can be used to generate more reliable datasets inferring more robust networks of co-regulated predicted miRNA target genes.

Indexed as

Epidermal Growth FactorGene SilencingGene TargetingGenomicsHeLa CellsHigh-Throughput Nucleotide SequencingHumansMicroRNAsOligonucleotide Array Sequence AnalysisSequence Analysis, RNASignal TransductionTranscription, GeneticEpidermal Growth FactorMicroRNAs

Identifiers

PMID23724959
PMCPMC3680220
OpenAlexW1967675159

What OpenQuestion holds

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LicenceCC BY
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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.