Evidence map›Paper›PMID 30657980›Full record

ArticleNucleic acids research2019

Identification of microRNA clusters cooperatively acting on epithelial to mesenchymal transition in triple negative breast cancer.

Laura Cantini, Gloria Bertoli, Claudia Cava, Thierry Dubois, Andrei Zinovyev, Michele Caselle, Isabella Castiglioni, Emmanuel Barillot, Loredana Martignetti

Abstract read
In one paragraph

Article in Nucleic acids research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers.

0numbers the graph read from it
0cells of the map it votes in
48citing 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

48 citing papers in PubMed.

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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

9 authors.

Laura CantiniInstitut Curie, 26 rue d'Ulm, F-75005 Paris, France.
Gloria BertoliInstitute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), Italy.
Claudia CavaInstitute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), Italy.
Thierry DuboisInstitut Curie, 26 rue d'Ulm, F-75005 Paris, France.
Andrei ZinovyevInstitut Curie, 26 rue d'Ulm, F-75005 Paris, France.
Michele CaselleDepartment of Physics and INFN, Università degli Studi di Torino, Turin, Italy.
Isabella CastiglioniInstitute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), Italy.
Emmanuel BarillotInstitut Curie, 26 rue d'Ulm, F-75005 Paris, France.
Loredana MartignettiInstitut Curie, 26 rue d'Ulm, F-75005 Paris, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

MicroRNAs play important roles in many biological processes. Their aberrant expression can have oncogenic or tumor suppressor function directly participating to carcinogenesis, malignant transformation, invasiveness and metastasis. Indeed, miRNA profiles can distinguish not only between normal and cancerous tissue but they can also successfully classify different subtypes of a particular cancer. Here, we focus on a particular class of transcripts encoding polycistronic miRNA genes that yields multiple miRNA components. We describe 'clustered MiRNA Master Regulator Analysis (ClustMMRA)', a fully redesigned release of the MMRA computational pipeline (MiRNA Master Regulator Analysis), developed to search for clustered miRNAs potentially driving cancer molecular subtyping. Genomically clustered miRNAs are frequently co-expressed to target different components of pro-tumorigenic signaling pathways. By applying ClustMMRA to breast cancer patient data, we identified key miRNA clusters driving the phenotype of different tumor subgroups. The pipeline was applied to two independent breast cancer datasets, providing statistically concordant results between the two analyses. We validated in cell lines the miR-199/miR-214 as a novel cluster of miRNAs promoting the triple negative breast cancer (TNBC) phenotype through its control of proliferation and EMT.

Indexed as

Cell Line, TumorCell ProliferationDatasets as TopicEpithelial-Mesenchymal TransitionGene SilencingHumansMicroRNAsMultigene FamilyNeoplasm InvasivenessReproducibility of ResultsTriple Negative Breast NeoplasmsMicroRNAs

Identifiers

PMID30657980
PMCPMC6412120

What OpenQuestion holds

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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.