Evidence map›Paper›PMID 31619517›Full record

ArticleThe Journal of biological chemistry2019

The RNA-binding protein SART3 promotes miR-34a biogenesis and G

Emily J Sherman, Dylan C Mitchell, Amanda L Garner

Open access · hybridAbstract read
In one paragraph

Article in The Journal of biological chemistry, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
1.2field-weighted citation impact, top 21% 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

26 citing papers in PubMed, 32 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

3 authors at 1 institution in 1 country.

Emily J ShermanProgram in Chemical Biology, University of Michigan, Ann Arbor, Michigan 48109.ORCID 0000-0002-3632-271X
Dylan C MitchellProgram in Chemical Biology, University of Michigan, Ann Arbor, Michigan 48109.
Amanda L GarnerProgram in Chemical Biology, University of Michigan, Ann Arbor, Michigan 48109 algarner@umich.edu.ORCID 0000-0002-0870-3347
University of Michigan · US

Funding

Proteogenomics of Cancer Training ProgramT32CA140044 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI RAO, ARVIND, SARTOR, MAUREEN AGNES · 2010 to 2024
$3.9M
NCI NIH HHS T32 CA140044
6 · The paper itself

Abstract

MicroRNAs (miRNAs or miRs) are small, noncoding RNAs that are implicated in the regulation of most biological processes. Global miRNA biogenesis is altered in many cancers, and RNA-binding proteins play a role in miRNA biogenesis, presenting a promising avenue for targeting miRNA dysregulation in diseases. miR-34a exhibits tumor-suppressive activities by targeting cell cycle regulators CDK4/6 and anti-apoptotic factor BCL-2, among other regulatory pathways such as Wnt, TGF-β, and Notch signaling. Many cancers exhibit down-regulation or loss of miR-34a, and synthetic miR-34a supplementation has been shown to inhibit tumor growth

Indexed as

Antigens, NeoplasmApoptosisCell Cycle CheckpointsCell Line, TumorCell ProliferationGene Expression Regulation, NeoplasticHumansLung NeoplasmsMicroRNAsNeoplasm ProteinsProtein BindingProteomicsRNA-Binding ProteinsSpliceosomesAntigens, NeoplasmMicroRNAsMIRN34 microRNA, humanmirnlet7 microRNA, humanNeoplasm ProteinsRNA-Binding ProteinsSART3 protein, humancancercell cyclecyclin-dependent kinase 4/6 (CDK4/6)lung cancermicroRNA biogenesismicroRNA biologymicroRNA (miRNA)miR-34anon-small cell lung cancer (NSCLC)posttranscriptional regulationprecursor microRNA (pre-miRNA)proteomicsRNA-binding proteinRNA-induced silencingRNA-protein interactionsmall noncoding RNAsquamous cell carcinoma antigen recognized by T-cells 3 (SART3)

Identifiers

PMID31619517
PMCPMC6873168
OpenAlexW2981119268

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.