Evidence map›Paper›PMID 32915890›Full record

ArticlePloS one2020

MicroRNA expression profiles in molecular subtypes of clear-cell renal cell carcinoma are associated with clinical outcome and repression of specific mRNA targets.

Annelies Verbiest, Vincent Van Hoef, Cristina Rodriguez-Antona, Jesús García-Donas, Osvaldo Graña-Castro, Maarten Albersen, Marcella Baldewijns, Annouschka Laenen, Eduard Roussel, Patrick Schöffski and 5 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.3field-weighted citation impact, top 42% 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

6 citing papers in PubMed, 7 citations in OpenAlex.

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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

15 authors at 6 institutions in 3 countries.

Annelies VerbiestDepartment of General Medical Oncology, Leuven Cancer Institute, University Hospitals Leuven, Leuven, Belgium.ORCID 0000-0001-9024-863X
Vincent Van HoefBioinformatics Expertise Center, VIB, Leuven, Belgium.
Cristina Rodriguez-AntonaHereditary Endocrine Cancer Group, Human Cancer Genetics Programme, Spanish National Cancer Research Centre, Madrid, Spain.
Jesús García-DonasOncology Unit, HM Hospitales-Centro Integral Oncologico HM Clara Campal, Madrid, Spain.
Osvaldo Graña-CastroBioinformatics Unit, Structural Biology and Biocomputing Programme, Spanish National Cancer Research Centre, Madrid, Spain.
Maarten AlbersenDepartment of Urology, University Hospitals Leuven, Leuven, Belgium.
Marcella BaldewijnsDepartment of Imaging and Pathology, KU Leuven, Leuven, Belgium.
Annouschka LaenenBiostatistics and Statistical Bioinformatics Center, KU Leuven, Leuven, Belgium.
Eduard RousselDepartment of Urology, University Hospitals Leuven, Leuven, Belgium.
Patrick SchöffskiDepartment of General Medical Oncology, Leuven Cancer Institute, University Hospitals Leuven, Leuven, Belgium.
Agnieszka WozniakDepartment of General Medical Oncology, Leuven Cancer Institute, University Hospitals Leuven, Leuven, Belgium.
Stefano CarusoInserm, UMR-1162, Génomique fonctionnelle des tumeurs solides, IUH, Paris, France.
Gabrielle CouchyInserm, UMR-1162, Génomique fonctionnelle des tumeurs solides, IUH, Paris, France.
Jessica Zucman-RossiInserm, UMR-1162, Génomique fonctionnelle des tumeurs solides, IUH, Paris, France.
Benoit BeuselinckDepartment of General Medical Oncology, Leuven Cancer Institute, University Hospitals Leuven, Leuven, Belgium.
KU Leuven · BEInserm · FRSpanish National Cancer Research Centre · ESHM Hospitales · ESStatistics Belgium · BEVIB-KU Leuven Center for Microbiology · BE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Clear-cell renal cell carcinomas (ccRCC) can be divided into four transcriptomic subtypes, two of which have a favorable and two an unfavorable prognosis. To assess mechanisms driving these subtypes, we investigated their miRNA expression patterns. miRNAs are master regulators of mRNAs, that are widely deregulated in cancer. Unsupervised clustering in our dataset (n = 128) and The Cancer Genome Atlas (TCGA) validation set identified two distinct miRNA clusters that overlapped with the transcriptomic subtypes, underscoring the validity of these subtypes on a multi-omics level and suggesting a driving role for miRNAs. Discriminatory miRNAs for the favorable subtypes repressed epithelial-to-mesenchymal transition, based on gene set enrichment analysis and target-mRNA expression levels. Strikingly, throughout the entire dataset, miRNAs associated with favorable subtypes were also associated with longer overall survival after diagnosis, and miRNAs associated with unfavorable subtypes with shorter overall survival (Pearson r = -0.54, p<0.0001). These findings indicate a general shift in miRNA expression between more and less aggressive tumors. This adds to current literature, which usually suggests only a small subset of miRNAs as markers of aggressive disease. In conclusion, this study reveals distinct mRNA expression patterns underlying transcriptomic ccRCC-subtypes, whereby miRNAs associated with favorable subtypes counteract epithelial-to-mesenchymal transition. There is a general shift in miRNA expression in ccRCC, between more and less aggressive tumors.

Indexed as

Gene Expression ProfilingCarcinoma, Renal CellFemaleHumansIndazolesKidney NeoplasmsMaleMicroRNAsMiddle AgedPyrimidinesRNA, MessengerSulfonamidesSunitinibSurvival AnalysisIndazolesMicroRNAspazopanibPyrimidinesRNA, MessengerSulfonamidesSunitinib

Identifiers

PMID32915890
PMCPMC7485767
OpenAlexW3086981772

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.