Evidence map›Paper›PMID 29895694›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2018

Cancer-mutation network and the number and specificity of driver mutations.

Jaime Iranzo, Iñigo Martincorena, Eugene V Koonin

Open access · bronzeAbstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 73 papers.

0numbers the graph read from it
0cells of the map it votes in
73citing papers in PubMed
4.0field-weighted citation impact, top 5% 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

73 citing papers in PubMed, 138 citations in OpenAlex.

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  19. Nanomedicine (London, England) · 2024
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13 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

3 authors at 2 institutions in 2 countries.

Jaime IranzoNational Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894; jaime.iranzosanz@nih.gov koonin@ncbi.nlm.nih.gov.
Iñigo MartincorenaWellcome Trust Sanger Institute, CB10 1SA Hinxton, Cambridgeshire, United Kingdom.
Eugene V KooninNational Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894; jaime.iranzosanz@nih.gov koonin@ncbi.nlm.nih.gov.ORCID 0000-0003-3943-8299
National Institutes of Health · USWellcome Sanger Institute · GB

Funding

Cancer Research UK 21777
6 · The paper itself

Abstract

Cancer genomics has produced extensive information on cancer-associated genes, but the number and specificity of cancer-driver mutations remains a matter of debate. We constructed a bipartite network in which 7,665 tumors from 30 cancer types are connected via shared mutations in 198 previously identified cancer genes. We show that about 27% of the tumors can be assigned to statistically supported modules, most of which encompass one or two cancer types. The rest of the tumors belong to a diffuse network component suggesting lower gene specificity of driver mutations. Linear regression of the mutational loads in cancer genes was used to estimate the number of drivers required for the onset of different cancers. The mean number of drivers in known cancer genes is approximately two, with a range of one to five. Cancers that are associated with modules had more drivers than those from the diffuse network component, suggesting that unidentified and/or interchangeable drivers exist in the latter.

Indexed as

Gene Regulatory NetworksGenes, NeoplasmModels, GeneticMutationHumansNeoplasmsbipartite networkscancer typescommunity detectiondriver mutationspassenger mutations

Identifiers

PMID29895694
PMCPMC6042135
OpenAlexW2784427696

What OpenQuestion holds

Textmetadata
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.