Evidence map›Paper›PMID 31097696›Full record

ArticleNature communications2019

Functional linkage of gene fusions to cancer cell fitness assessed by pharmacological and CRISPR-Cas9 screening.

Gabriele Picco, Elisabeth D Chen, Luz Garcia Alonso, Fiona M Behan, Emanuel Gonçalves, Graham Bignell, Angela Matchan, Beiyuan Fu, Ruby Banerjee, Elizabeth Anderson and 10 more

Abstract read
In one paragraph

Article in Nature communications, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 85 papers.

0numbers the graph read from it
0cells of the map it votes in
85citing papers in PubMed
–field-weighted citation impact
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

85 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Article
  15. Review
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

25 more citing papers are in PubMed but not listed here.

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

20 authors.

Gabriele PiccoWellcome Sanger Institute, Wellcome Genome Campus, Cambridge, CB10 1SA, UK.
Elisabeth D ChenWellcome Sanger Institute, Wellcome Genome Campus, Cambridge, CB10 1SA, UK.ORCID http://orcid.org/0000-0003-2129-7985
Luz Garcia AlonsoEuropean Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Cambridge, CB10 1SD, UK.ORCID http://orcid.org/0000-0002-7863-9619
Fiona M BehanWellcome Sanger Institute, Wellcome Genome Campus, Cambridge, CB10 1SA, UK.ORCID http://orcid.org/0000-0002-9070-7688
Emanuel GonçalvesWellcome Sanger Institute, Wellcome Genome Campus, Cambridge, CB10 1SA, UK.
Graham BignellWellcome Sanger Institute, Wellcome Genome Campus, Cambridge, CB10 1SA, UK.
Angela MatchanWellcome Sanger Institute, Wellcome Genome Campus, Cambridge, CB10 1SA, UK.
Beiyuan FuWellcome Sanger Institute, Wellcome Genome Campus, Cambridge, CB10 1SA, UK.
Ruby BanerjeeWellcome Sanger Institute, Wellcome Genome Campus, Cambridge, CB10 1SA, UK.
Elizabeth AndersonWellcome Sanger Institute, Wellcome Genome Campus, Cambridge, CB10 1SA, UK.
Adam ButlerWellcome Sanger Institute, Wellcome Genome Campus, Cambridge, CB10 1SA, UK.
Cyril H BenesMassachusetts General Hospital, 55 Fruit Street, Boston, MA, 02114, USA.
Ultan McDermottWellcome Sanger Institute, Wellcome Genome Campus, Cambridge, CB10 1SA, UK.
David DowOpen Targets, Wellcome Genome Campus, Cambridge, CB10 1SA, UK.
Francesco IorioWellcome Sanger Institute, Wellcome Genome Campus, Cambridge, CB10 1SA, UK.ORCID http://orcid.org/0000-0001-7063-8913
Euan StronachOpen Targets, Wellcome Genome Campus, Cambridge, CB10 1SA, UK.
Fengtang YangWellcome Sanger Institute, Wellcome Genome Campus, Cambridge, CB10 1SA, UK.ORCID http://orcid.org/0000-0002-3573-2354
Kosuke YusaWellcome Sanger Institute, Wellcome Genome Campus, Cambridge, CB10 1SA, UK.
Julio Saez-RodriguezEuropean Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Cambridge, CB10 1SD, UK.ORCID http://orcid.org/0000-0002-8552-8976
Mathew J GarnettWellcome Sanger Institute, Wellcome Genome Campus, Cambridge, CB10 1SA, UK. mathew.garnett@sanger.ac.uk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Many gene fusions are reported in tumours and for most their role remains unknown. As fusions are used for diagnostic and prognostic purposes, and are targets for treatment, it is crucial to assess their function in cancer. To systematically investigate the role of fusions in tumour cell fitness, we utilized RNA-sequencing data from 1011 human cancer cell lines to functionally link 8354 fusion events with genomic data, sensitivity to >350 anti-cancer drugs and CRISPR-Cas9 loss-of-fitness effects. Established clinically-relevant fusions were identified. Overall, detection of functional fusions was rare, including those involving cancer driver genes, suggesting that many fusions are dispensable for tumour fitness. Therapeutically actionable fusions involving RAF1, BRD4 and ROS1 were verified in new histologies. In addition, recurrent YAP1-MAML2 fusions were identified as activators of Hippo-pathway signaling in multiple cancer types. Our approach discriminates functional fusions, identifying new drivers of carcinogenesis and fusions that could have clinical implications.

Indexed as

Antineoplastic AgentsBiomarkers, TumorCarcinogenesisCell Line, TumorCRISPR-Cas SystemsDatasets as TopicDrug Resistance, NeoplasmEarly Detection of CancerGene Expression ProfilingGene Expression Regulation, NeoplasticGene FusionGenomicsHigh-Throughput Nucleotide SequencingHumansNeoplasmsSequence Analysis, RNAAntineoplastic AgentsBiomarkers, Tumor

Identifiers

PMID31097696
PMCPMC6522557

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.