Evidence map›Paper›PMID 25877892›Full record

Observational studyScience translational medicine2015

Clonal status of actionable driver events and the timing of mutational processes in cancer evolution.

Nicholas McGranahan, Francesco Favero, Elza C de Bruin, Nicolai Juul Birkbak, Zoltan Szallasi, Charles Swanton

Open access · greenAbstract readObservational Study
In one paragraph

Observational study in Science translational medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 411 papers.

0numbers the graph read from it
0cells of the map it votes in
411citing papers in PubMed
26.7field-weighted citation impact, top 1% 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

411 citing papers in PubMed, 707 citations in OpenAlex.

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

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors at 4 institutions in 2 countries.

Nicholas McGranahanCancer Research UK London Research Institute, London WC2A 3LY, UK. Centre for Mathematics and Physics in the Life Sciences and Experimental Biology (CoMPLEX), University College London, London WC1E 6BT, UK.
Francesco FaveroCancer System Biology, Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, Lyngby 2800, Denmark.
Elza C de BruinUCL Cancer Institute, CRUK Lung Cancer Centre of Excellence, Paul O'Gorman Building, Huntley Street, London WC1E 6DD, UK.
Nicolai Juul BirkbakCancer Research UK London Research Institute, London WC2A 3LY, UK. Cancer System Biology, Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, Lyngby 2800, Denmark. UCL Cancer Institute, CRUK Lung Cancer Centre of Excellence, Paul O'Gorman Building, Huntley Street, London WC1E 6DD, UK.
Zoltan SzallasiCancer System Biology, Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, Lyngby 2800, Denmark. Children's Hospital Informatics Program, Harvard Medical School, Boston, MA 02115, USA.
Charles SwantonCancer Research UK London Research Institute, London WC2A 3LY, UK. UCL Cancer Institute, CRUK Lung Cancer Centre of Excellence, Paul O'Gorman Building, Huntley Street, London WC1E 6DD, UK. charles.swanton@crick.ac.uk.
CRUK Lung Cancer Centre of Excellence · GBCancer Research UK · GBHarvard University · USUniversity College London · GB

Funding

Cancer Research UK 17786Cancer Research UK 19310Cancer Research UK A11590Cancer Research UK A17786Cancer Research UK A19310
6 · The paper itself

Abstract

Deciphering whether actionable driver mutations are found in all or a subset of tumor cells will likely be required to improve drug development and precision medicine strategies. We analyzed nine cancer types to determine the subclonal frequencies of driver events, to time mutational processes during cancer evolution, and to identify drivers of subclonal expansions. Although mutations in known driver genes typically occurred early in cancer evolution, we also identified later subclonal "actionable" mutations, including BRAF (V600E), IDH1 (R132H), PIK3CA (E545K), EGFR (L858R), and KRAS (G12D), which may compromise the efficacy of targeted therapy approaches. More than 20% of IDH1 mutations in glioblastomas, and 15% of mutations in genes in the PI3K (phosphatidylinositol 3-kinase)-AKT-mTOR (mammalian target of rapamycin) signaling axis across all tumor types were subclonal. Mutations in the RAS-MEK (mitogen-activated protein kinase kinase) signaling axis were less likely to be subclonal than mutations in genes associated with PI3K-AKT-mTOR signaling. Analysis of late mutations revealed a link between APOBEC-mediated mutagenesis and the acquisition of subclonal driver mutations and uncovered putative cancer genes involved in subclonal expansions, including CTNNA2 and ATXN1. Our results provide a pan-cancer census of driver events within the context of intratumor heterogeneity and reveal patterns of tumor evolution across cancers. The frequent presence of subclonal driver mutations suggests the need to stratify targeted therapy response according to the proportion of tumor cells in which the driver is identified.

Indexed as

DNA Mutational AnalysisLoss of HeterozygosityCell Line, TumorGene DosageGene Expression Regulation, NeoplasticGenome, HumanGenomicsHumansMutationNeoplasmsOligonucleotide Array Sequence AnalysisPrecision MedicineSignal TransductionTime Factors

Identifiers

PMID25877892
PMCPMC4636056
OpenAlexW2154974159

What OpenQuestion holds

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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.