Evidence map›Paper›PMID 28223711›Full record

ArticleScientific reports2017

Identification of novel cancer therapeutic targets using a designed and pooled shRNA library screen.

David Oliver, Hao Ji, Piaomu Liu, Alexander Gasparian, Ellen Gardiner, Samuel Lee, Adrian Zenteno, Lillian O Perinskaya, Mengqian Chen, Phillip Buckhaults and 5 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
1.7field-weighted citation impact, top 16% 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

24 citing papers in PubMed, 45 citations in OpenAlex.

  1. Review
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  6. The role of CaMKK2 in Golgi-associated vesicle trafficking.Biochemical Society transactions · 2023
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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 2 institutions in 1 country.

David OliverUniversity of South Carolina, College of Pharmacy, Department of Drug Discovery and Biomedical Sciences, Columbia, SC 29208, USA.
Hao JiUniversity of South Carolina, College of Pharmacy, Department of Drug Discovery and Biomedical Sciences, Columbia, SC 29208, USA.
Piaomu LiuUniversity of South Carolina, College of Arts and Sciences, Department of Statistics, Columbia, SC 29208, USA.
Alexander GasparianUniversity of South Carolina, College of Pharmacy, Department of Drug Discovery and Biomedical Sciences, Columbia, SC 29208, USA.
Ellen GardinerUniversity of South Carolina, College of Pharmacy, Department of Drug Discovery and Biomedical Sciences, Columbia, SC 29208, USA.
Samuel LeeUniversity of South Carolina, College of Pharmacy, Department of Drug Discovery and Biomedical Sciences, Columbia, SC 29208, USA.
Adrian ZentenoUniversity of South Carolina, College of Pharmacy, Department of Drug Discovery and Biomedical Sciences, Columbia, SC 29208, USA.
Lillian O PerinskayaUniversity of South Carolina, College of Pharmacy, Department of Drug Discovery and Biomedical Sciences, Columbia, SC 29208, USA.
Mengqian ChenUniversity of South Carolina, College of Pharmacy, Department of Drug Discovery and Biomedical Sciences, Columbia, SC 29208, USA.
Phillip BuckhaultsUniversity of South Carolina, College of Pharmacy, Department of Drug Discovery and Biomedical Sciences, Columbia, SC 29208, USA.
Eugenia BroudeUniversity of South Carolina, College of Pharmacy, Department of Drug Discovery and Biomedical Sciences, Columbia, SC 29208, USA.
Michael D WyattUniversity of South Carolina, College of Pharmacy, Department of Drug Discovery and Biomedical Sciences, Columbia, SC 29208, USA.
Homayoun ValafarUniversity of South Carolina, College of Engineering and Computing, Department of Computer Sciences and Engineering, Columbia, SC 29208, USA.
Edsel PeñaUniversity of South Carolina, College of Arts and Sciences, Department of Statistics, Columbia, SC 29208, USA.
Michael ShtutmanUniversity of South Carolina, College of Pharmacy, Department of Drug Discovery and Biomedical Sciences, Columbia, SC 29208, USA.
University of South Carolina · USBentley University · US

Funding

Supplement for South Carolina BRIN - 1P20 RR16461P20RR016461 · NCRR · UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA · PI DEAVOR, JAMES · 2001 to 2011
$32.3M
Targeting NMDA Receptors and Brain Estradiol to Rescue Memory in Aging FemalesP20GM109091 · NIGMS · UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA · PI KIARIS, HIPPOKRATIS, RONINSON, IGOR B · 2014 to 2024
$25.2M
TISSUE BIOREPOSITORYP20RR017698 · NCRR · UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA · PI FAYAD, RAJA · 2002 to 2011
$22.5M
TISSUE BIOREPOSITORY COREP30GM103336 · NIGMS · UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA · PI BERGER, FRANKLIN G. · 2013 to 2017
$5.4M
A Genetic Model for Early-Onset Breast and Colon Cancer in African AmericansU01CA158428 · NCI · UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA · PI BUCKHAULTS, PHILLIP JOE, BUNZ, FRED · 2012 to 2016
$1.5M
NCI NIH HHS U01 CA158428NCRR NIH HHS P20 RR016461NCRR NIH HHS P20 RR017698NIGMS NIH HHS P20 GM109091NIGMS NIH HHS P30 GM103336
6 · The paper itself

Abstract

Targeted cancer therapeutics aim to exploit tumor-specific, genetic vulnerabilities specifically affecting neoplastic cells without similarly affecting normal cells. Here we performed sequencing-based screening of an shRNA library on a panel of cancer cells of different origins as well as normal cells. The shRNA library was designed to target a subset of genes previously identified using a whole genome screening approach. This focused shRNA library was infected into cells followed by analysis of enrichment and depletion of the shRNAs over the course of cell proliferation. We developed a bootstrap likelihood ratio test for the interpretation of the effects of multiple shRNAs over multiple cell line passages. Our analysis identified 44 genes whose depletion preferentially inhibited the growth of cancer cells. Among these genes ribosomal protein RPL35A, putative RNA helicase DDX24, and coatomer complex I (COPI) subunit ARCN1 most significantly inhibited growth of multiple cancer cell lines without affecting normal cell growth and survival. Further investigation revealed that the growth inhibition caused by DDX24 depletion is independent of p53 status underlining its value as a drug target. Overall, our study establishes a new approach for the analysis of proliferation-based shRNA selection strategies and identifies new targets for the development of cancer therapeutics.

Indexed as

Drug DesignCell Line, TumorCell ProliferationCoatomer ProteinDEAD-box RNA HelicasesGene LibraryHumansLikelihood FunctionsNeoplasmsRibosomal ProteinsRNA InterferenceRNA, Small InterferingTumor Suppressor Protein p53Coatomer ProteinDDX24 protein, humanDEAD-box RNA HelicasesRibosomal ProteinsRNA, Small InterferingRPL35A protein, humanTumor Suppressor Protein p53

Identifiers

PMID28223711
PMCPMC5320502
OpenAlexW2589482385

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.