Evidence map›Paper›PMID 32398776›Full record

ArticleNature communications2020

Integration of multiple biological contexts reveals principles of synthetic lethality that affect reproducibility.

Angel A Ku, Hsien-Ming Hu, Xin Zhao, Khyati N Shah, Sameera Kongara, Di Wu, Frank McCormick, Allan Balmain, Sourav Bandyopadhyay

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nature communications, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
2.1field-weighted citation impact, top 12% 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

21 citing papers in PubMed, 39 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

9 authors at 1 institution in 1 country.

Angel A KuDepartment of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, 94158, USA.
Hsien-Ming HuDepartment of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, 94158, USA.
Xin ZhaoDepartment of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, 94158, USA.
Khyati N ShahDepartment of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, 94158, USA.ORCID http://orcid.org/0000-0002-2510-803X
Sameera KongaraDepartment of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, 94158, USA.
Di WuHelen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, 94158, USA.
Frank McCormickHelen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, 94158, USA.
Allan BalmainHelen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, 94158, USA.ORCID http://orcid.org/0000-0001-6549-7861
Sourav BandyopadhyayDepartment of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, 94158, USA. Sourav.bandyopadhyay@ucsf.edu.ORCID http://orcid.org/0000-0003-3120-923X
University of California, San Francisco · US

Funding

Systems genetics analysis of tumor evolution in the mouseR35CA210018 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI ALLAN BALMAIN · 2017 to 2026
$8.0M
Bay Area Cancer Target Discovery and Development NetworkU01CA168370 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI MCCORMICK, FRANK PATRICK, MCMANUS, MICHAEL T · 2012 to 2016
$3.9M
NCI NIH HHS R35 CA210018NCI NIH HHS U01 CA168370
6 · The paper itself

Abstract

Synthetic lethal screens have the potential to identify new vulnerabilities incurred by specific cancer mutations but have been hindered by lack of agreement between studies. In the case of KRAS, we identify that published synthetic lethal screen hits significantly overlap at the pathway rather than gene level. Analysis of pathways encoded as protein networks could identify synthetic lethal candidates that are more reproducible than those previously reported. Lack of overlap likely stems from biological rather than technical limitations as most synthetic lethal phenotypes are strongly modulated by changes in cellular conditions or genetic context, the latter determined using a pairwise genetic interaction map that identifies numerous interactions that suppress synthetic lethal effects. Accounting for pathway, cellular and genetic context nominates a DNA repair dependency in KRAS-mutant cells, mediated by a network containing BRCA1. We provide evidence for why most reported synthetic lethals are not reproducible which is addressable using a multi-faceted testing framework.

Indexed as

Data AnalysisGene Regulatory NetworksSynthetic Lethal MutationsAnimalsBRCA1 ProteinCell Line, TumorComputational BiologyDisease Models, AnimalHumansMiceNeoplasmsProtein Interaction MapsProto-Oncogene Proteins p21(ras)Reproducibility of ResultsBRCA1 ProteinBRCA1 protein, humanKRAS protein, humanProto-Oncogene Proteins p21(ras)

Identifiers

PMID32398776
PMCPMC7217969
OpenAlexW3024669012

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.