Evidence map›Paper›PMID 23797109›Full record

ArticleG3 (Bethesda, Md.)2013

Miniature short hairpin RNA screens to characterize antiproliferative drugs.

Saranya Kittanakom, Anthony Arnoldo, Kevin R Brown, Iain Wallace, Tada Kunavisarut, Dax Torti, Lawrence E Heisler, Anuradha Surendra, Jason Moffat, Guri Giaever and 1 more

Open access · goldAbstract read
In one paragraph

Article in G3 (Bethesda, Md.), 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.4field-weighted citation impact, top 33% 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

2 citing papers in PubMed, 7 citations in OpenAlex.

  1. Chemical genetics in drug discovery.Current opinion in systems biology · 2017
    Review
  2. Article
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

11 authors at 2 institutions in 2 countries.

Saranya KittanakomDepartment of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 3E1, Canada.
Anthony Arnoldo
Kevin R Brown
Iain Wallace
Tada Kunavisarut
Dax Torti
Lawrence E Heisler
Anuradha Surendra
Jason Moffat
Guri Giaever
Corey Nislow
University of Toronto · CASiriraj Hospital · TH

Funding

Technology to Identify and Assay Chemical Genomic ProbesR01HG003317 · NHGRI · STANFORD UNIVERSITY · PI DAVIS, RONALD WAYNE · 2004 to 2012
$9.1M
NHGRI NIH HHS 5 R01 HG003317 08NHGRI NIH HHS R01 HG003317
6 · The paper itself

Abstract

The application of new proteomics and genomics technologies support a view in which few drugs act solely by inhibiting a single cellular target. Indeed, drug activity is modulated by complex, often incompletely understood cellular mechanisms. Therefore, efforts to decipher mode of action through genetic perturbation such as RNAi typically yields "hits" that fall into several categories. Of particular interest to the present study, we aimed to characterize secondary activities of drugs on cells. Inhibiting a known target can result in clinically relevant synthetic phenotypes. In one scenario, drug perturbation could, for example, improperly activate a protein that normally inhibits a particular kinase. In other cases, additional, lower affinity targets can be inhibited as in the example of inhibition of c-Kit observed in Bcr-Abl-positive cells treated with Gleevec. Drug transport and metabolism also play an important role in the way any chemicals act within the cells. Finally, RNAi per se can also affect cell fitness by more general off-target effects, e.g., via the modulation of apoptosis or DNA damage repair. Regardless of the root cause of these unwanted effects, understanding the scope of a drug's activity and polypharmacology is essential for better understanding its mechanism(s) of action, and such information can guide development of improved therapies. We describe a rapid, cost-effective approach to characterize primary and secondary effects of small-molecules by using small-scale libraries of virally integrated short hairpin RNAs. We demonstrate this principle using a "minipool" composed of shRNAs that target the genes encoding the reported protein targets of approved drugs. Among the 28 known reported drug-target pairs, we successfully identify 40% of the targets described in the literature and uncover several unanticipated drug-target interactions based on drug-induced synthetic lethality. We provide a detailed protocol for performing such screens and for analyzing the data. This cost-effective approach to mammalian knockdown screens, combined with the increasing maturation of RNAi technology will expand the accessibility of similar approaches in academic settings.

Indexed as

Antineoplastic AgentsBenzamidesCell Line, TumorCell ProliferationFusion Proteins, bcr-ablGenetic VectorsHigh-Throughput Nucleotide SequencingHumansImatinib MesylateLentivirusMiniaturizationPiperazinesProteinsProto-Oncogene Proteins c-kitPyrimidinesRNA InterferenceAntineoplastic AgentsBenzamidesFusion Proteins, bcr-ablImatinib MesylatePiperazinesProteinsProto-Oncogene Proteins c-kitPyrimidinesRNA, Small Interferingnext-generation sequencingshRNA screeningsynthetic lethality

Identifiers

PMID23797109
PMCPMC3737177
OpenAlexW2137075120

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.