Evidence map›Paper›PMID 22539522›Full record

ArticleRNA (New York, N.Y.)2012

Development of a siRNA and shRNA screening system based on a kinase fusion protein.

Sofie Pieraets, Luk Cox, Olga Gielen, Jan Cools

Open access · bronzeAbstract readValidation Study
In one paragraph

Article in RNA (New York, N.Y.), 2012. 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
0.4field-weighted citation impact, top 37% 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

4 authors at 1 institution in 1 country.

Sofie PieraetsCenter for the Biology of Disease, VIB, B-3000 Leuven, Belgium.
Luk Cox
Olga Gielen
Jan Cools
VIB-KU Leuven Center for Cancer Biology · BE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

RNA interference (RNAi) is one of the processes in the cell that regulates mRNA expression levels. RNAi can be exploited to experimentally knockdown the expression of one or more genes in cell lines or even in cells in vivo and also became an interesting tool to develop new therapeutic approaches. One of the major challenges of using RNAi is selecting effective shRNAs or siRNAs that sufficiently down-regulate the expression of the target gene. Here, we describe a system to select functional shRNAs or siRNAs that makes use of the leukemia cell line Ba/F3 that is dependent on the expression of a mutant form of the PDGFRα kinase for its proliferation and survival. The basis of this system is the generation of an expression construct, where part of the open reading frame of the gene of interest is linked to the mutant PDGFRα. Thus, shRNAs or siRNAs that effectively target the gene of interest also result in a reduction of the expression of the mutant PDGFRα protein, which can be detected by a reduction of the proliferation of the cells. We demonstrate that this validation system can be used for the selection of effective siRNAs as well as shRNAs. Unlike other systems, the system described here is not dependent on obtaining high-transduction efficiencies, and nonspecific effects of the siRNAs or shRNAs can be detected by comparing the effects in the presence or absence of the growth factor interleukin-3.

Indexed as

AnimalsCell Line, TumorCell ProliferationHumansInterleukin-3MiceOpen Reading FramesReceptors, Platelet-Derived Growth FactorRecombinant Fusion ProteinsRNA, Small InterferingInterleukin-3PDGF receptor tyrosine kinaseReceptors, Platelet-Derived Growth FactorRecombinant Fusion ProteinsRNA, Small Interfering

Identifiers

PMID22539522
PMCPMC3358651
OpenAlexW2149838858

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.