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Record W4415151539 · doi:10.1101/2025.10.12.681852

Extensive and differential platinum chemotherapy mutagenesis in children

2025· preprint· en· W4415151539 on OpenAlexaff
Anna Wenger, Henry Lee-Six, Manàs Dave, Mehdi Layeghifard, Andrew Lawson, Federico Abascal, Pantelis Nicola, Taryn D. Treger, Toochi Ogbonnah, Conor Parks, Thomas R. W. Oliver, Jonathan Kennedy, Angus Hodder, Nathaniel D. Anderson, Felipe Luz Torres Silva, Mi K. Trinh, Thomas Dowe, Marwo Habarwaa, Sergio Assia‐Zamora, Miriam Cortés Cerisuelo, Wayel Jassem, Anil Dhawan, Vandana Jain, Karin Straathof, Maesha Deheragoda, Iñigo Martincorena, Liina Palm, J. Ciaran Hutchinson, Tim Coorens, Claire Trayers, Nigel Heaton, Adam Shlien, Yoh Zen, Foad J. Rouhani, Sam Behjati

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2025
Typepreprint
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicChemical Reactions and Isotopes
Canadian institutionsHospital for Sick Children
FundersNIHR Great Ormond Street Hospital Biomedical Research CentreMedical Research CouncilLittle Princess TrustKing's Health PartnersNational Institute for Health and Care ResearchKing's College LondonFundação de Amparo à Pesquisa do Estado de São PauloWenner-Gren StiftelsernaKing's College Hospital NHS Foundation TrustNIHR Cambridge Biomedical Research CentreWellcome Trust
KeywordsMutagenesisMutationGeneChemotherapyCancerWhole genome sequencingCisplatinDNA

Abstract

fetched live from OpenAlex

SUMMARY Childhood cancer survivors often develop long-term adverse effects, which may be caused by direct mutagenesis of cytotoxic agents. Some of these agents generate distinctive DNA imprints (mutational signatures), as exemplified by platinum chemotherapeutics. Here, we examined chemotherapy mutagenesis in paediatric tissues by deploying a duplex sequencing method (NanoSeq), which enables mutation calling from single DNA molecules. We surveyed whole genomes of paediatric liver, blood and other tissues, obtained from surgical resections and at post-mortem. Platinum signatures pervaded all tissues extensively, elevating mutation burdens of paediatric tissues to levels seen in adults. Remarkably, we found a tissue-specific mutational signature in the liver. We examined the functional potential of mutations by gene focused NanoSeq, which revealed that platinum agents cause a vast repertoire of cancer causing variants across normal tissues, such as leukaemogenic mutations in blood. This finding may conceivably link cancer treatment in childhood to mutation-driven long term sequelae.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.392
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.029
GPT teacher head0.323
Teacher spread0.294 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

Explore more

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