Evidence map›Paper›PMID 37221612›Full record

ArticleGenome biology2023

Genomic hallmarks and therapeutic implications of G0 cell cycle arrest in cancer.

Anna J Wiecek, Stephen J Cutty, Daniel Kornai, Mario Parreno-Centeno, Lucie E Gourmet, Guidantonio Malagoli Tagliazucchi, Daniel H Jacobson, Ping Zhang, Lingyun Xiong, Gareth L Bond and 2 more

Abstract read
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In one paragraph

Article in Genome biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers.

0numbers the graph read from it
0cells of the map it votes in
49citing 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

49 citing papers in PubMed.

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  19. Cancer Cell Dormancy in the Bone Microenvironment.Current osteoporosis reports · 2025
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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

12 authors.

Anna J WiecekUCL Genetics Institute, Department of Genetics, Evolution and Environment, University College London, London, UK.
Stephen J CuttyInstitute of Clinical Sciences, Faculty of Medicine, Imperial College London, London, UK.
Daniel KornaiUCL Genetics Institute, Department of Genetics, Evolution and Environment, University College London, London, UK.
Mario Parreno-CentenoUCL Genetics Institute, Department of Genetics, Evolution and Environment, University College London, London, UK.
Lucie E GourmetUCL Genetics Institute, Department of Genetics, Evolution and Environment, University College London, London, UK.
Guidantonio Malagoli TagliazucchiUCL Genetics Institute, Department of Genetics, Evolution and Environment, University College London, London, UK.
Daniel H JacobsonUCL Genetics Institute, Department of Genetics, Evolution and Environment, University College London, London, UK.
Ping ZhangWellcome Centre for Human Genetics, University of Oxford, Oxford, UK.
Lingyun XiongWellcome Centre for Human Genetics, University of Oxford, Oxford, UK.
Gareth L BondInstitute of Cancer and Genomic Sciences, University of Birmingham, Edgbaston, Birmingham, UK.
Alexis R BarrInstitute of Clinical Sciences, Faculty of Medicine, Imperial College London, London, UK.
Maria SecrierUCL Genetics Institute, Department of Genetics, Evolution and Environment, University College London, London, UK. m.secrier@ucl.ac.uk.ORCID 0000-0003-2758-1741

Funding

Biotechnology and Biological Sciences Research Council BB/R01356X/1Cancer Research UK 25729Cancer Research UK C63833/A25729Medical Research Council MC_UP_1605/8Medical Research Council MR/N013867/1Medical Research Council MR/T042184/1Wellcome TrustWellcome Trust 204841/Z/16/ZWellcome Trust 215296/Z/19/Z
6 · The paper itself

Abstract

backgroundTherapy resistance in cancer is often driven by a subpopulation of cells that are temporarily arrested in a non-proliferative G0 state, which is difficult to capture and whose mutational drivers remain largely unknown.

resultsWe develop methodology to robustly identify this state from transcriptomic signals and characterise its prevalence and genomic constraints in solid primary tumours. We show that G0 arrest preferentially emerges in the context of more stable, less mutated genomes which maintain TP53 integrity and lack the hallmarks of DNA damage repair deficiency, while presenting increased APOBEC mutagenesis. We employ machine learning to uncover novel genomic dependencies of this process and validate the role of the centrosomal gene CEP89 as a modulator of proliferation and G0 arrest capacity. Lastly, we demonstrate that G0 arrest underlies unfavourable responses to various therapies exploiting cell cycle, kinase signalling and epigenetic mechanisms in single-cell data.

conclusionsWe propose a G0 arrest transcriptional signature that is linked with therapeutic resistance and can be used to further study and clinically track this state.

Indexed as

GenomicsNeoplasmsCell CycleCell Cycle CheckpointsHumansMutagenesisBulk/single-cell sequencingCancerCell cycle arrestData integrationG0Genomic dependenciesMachine learningPersister cells

Identifiers

PMID37221612
PMCPMC10204193

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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.