Evidence map›Paper›PMID 24084849›Full record

ArticleScientific reports2013

Comprehensive identification of mutational cancer driver genes across 12 tumor types.

David Tamborero, Abel Gonzalez-Perez, Christian Perez-Llamas, Jordi Deu-Pons, Cyriac Kandoth, Jüri Reimand, Michael S Lawrence, Gad Getz, Gary D Bader, Li Ding and 1 more

Abstract read
In one paragraph

Article in Scientific reports, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 321 papers.

0numbers the graph read from it
0cells of the map it votes in
321citing 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

321 citing papers in PubMed.

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  14. IsJournal of oral microbiology · 2025
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261 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

11 authors.

David Tamborero1] Research Unit on Biomedical Informatics, Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Dr. Aiguader 88, Barcelona, Spain [2].
Abel Gonzalez-Perez
Christian Perez-Llamas
Jordi Deu-Pons
Cyriac Kandoth
Jüri Reimand
Michael S Lawrence
Gad Getz
Gary D Bader
Li Ding
Nuria Lopez-Bigas

Funding

Large Scale Genome SequencingU54HG003079 · NHGRI · WASHINGTON UNIVERSITY · PI DUTCHER, SUSAN K · 2004 to 2016
$445.7M
TR&D 3 - Network Guided Machine LearningP41GM103504 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI IDEKER, TREY · 2012 to 2024
$17.3M
A Turnkey System for High-throughput Variant Discovery and InterpretationU01HG006517 · NHGRI · WASHINGTON UNIVERSITY · PI DING, LI · 2012 to 2015
$3.0M
NHGRI NIH HHS U01 HG006517NHGRI NIH HHS U54 HG003079NIGMS NIH HHS P41 GM103504
6 · The paper itself

Abstract

With the ability to fully sequence tumor genomes/exomes, the quest for cancer driver genes can now be undertaken in an unbiased manner. However, obtaining a complete catalog of cancer genes is difficult due to the heterogeneous molecular nature of the disease and the limitations of available computational methods. Here we show that the combination of complementary methods allows identifying a comprehensive and reliable list of cancer driver genes. We provide a list of 291 high-confidence cancer driver genes acting on 3,205 tumors from 12 different cancer types. Among those genes, some have not been previously identified as cancer drivers and 16 have clear preference to sustain mutations in one specific tumor type. The novel driver candidates complement our current picture of the emergence of these diseases. In summary, the catalog of driver genes and the methodology presented here open new avenues to better understand the mechanisms of tumorigenesis.

Indexed as

CarcinogensMutationCell Transformation, NeoplasticDNA Mutational AnalysisGene Regulatory NetworksGenetic Association StudiesGenomicsHumansNeoplasmsReproducibility of ResultsSignal TransductionCarcinogens

Identifiers

PMID24084849
PMCPMC3788361

What OpenQuestion holds

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LicenceCC BY-NC-SA
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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.