Evidence map›Paper›PMID 31508509›Full record

ArticleCommunications biology2019

Genome-scale CRISPR knockout screen identifies

Pingping Fang, Cristabelle De Souza, Kay Minn, Jeremy Chien

Open access · goldAbstract read
In one paragraph

Article in Communications biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
2.4field-weighted citation impact, top 10% 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

29 citing papers in PubMed, 45 citations in OpenAlex.

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  20. Metabolic landscapes in sarcomas.Journal of hematology & oncology · 2021
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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

4 authors at 3 institutions in 1 country.

Pingping Fang1Department of Pharmacology, Toxicology and Therapeutics, The University of Kansas Medical Center, Kansas City, KS 66160 USA.
Cristabelle De Souza2Department of Internal Medicine, University of New Mexico Cancer Center, University of New Mexico School of Medicine, Albuquerque, NM 87131 USA.
Kay Minn2Department of Internal Medicine, University of New Mexico Cancer Center, University of New Mexico School of Medicine, Albuquerque, NM 87131 USA.
Jeremy Chien3Department of Biochemistry and Molecular Medicine, University of California, Davis, Sacramento, CA 95816 USA.ORCID 0000-0003-4744-8374
University of New Mexico · USUniversity of California, Davis · USUniversity of Kansas Medical Center · US

Funding

Transgenic & Gene-Targeting Shared ResourceP30CA168524 · NCI · UNIVERSITY OF KANSAS MEDICAL CENTER · PI ROY A. JENSEN · 2012 to 2026
$40.1M
NCI NIH HHS P30 CA168524
6 · The paper itself

Abstract

Treatment of cancer with poly (ADP-ribose) polymerase (PARP) inhibitors is currently limited to cells defective in the homologous recombination (HR) pathway. Identification of genetic targets that induce or mimic HR deficiencies will extend the clinical utility of PARP inhibitors. Here we perform a CRISPR/Cas9-based genome-scale loss-of-function screen, using the sensitivity of PARP inhibitor olaparib as a surrogate. We identify

Indexed as

CRISPR-Cas SystemsAntineoplastic AgentsApoptosis Regulatory ProteinsBiomarkersCellular SenescenceDNA DamageDrug Resistance, NeoplasmGene Knockdown TechniquesGenome-Wide Association StudyHumansPhosphoric Monoester HydrolasesPhthalazinesPiperazinesPoly(ADP-ribose) Polymerase InhibitorsSignal TransductionAntineoplastic AgentsApoptosis Regulatory ProteinsBiomarkersolaparibPhosphoric Monoester HydrolasesPhthalazinesPiperazinesPoly(ADP-ribose) Polymerase InhibitorsTIGAR protein, humanCancer genomicsCancer metabolismOvarian cancerTargeted therapies

Identifiers

PMID31508509
PMCPMC6733792
OpenAlexW2973160589

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.