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Record W3159804362 · doi:10.1101/2021.04.29.21255920

Mutational signatures in esophageal squamous cell carcinoma from eight countries of varying incidence

2021· preprint· en· W3159804362 on OpenAlexaff
Sarah Moody, S. Senkin, S. M. Ashiqul Islam, Jingwei Wang, Dariush Nasrollahzadeh, Ricardo Cortez Cardoso Penha, Stephen Fitzgerald, Erik N. Bergstrom, Joshua Atkins, Yudou He, Azhar Khandekar, Karl Smith‐Byrne, Christine Carreira, Valérie Gaborieau, Calli Latimer, Emily Thomas, Irina Abnizova, Pauline E. Bucciarelli, David Jones, Jon W. Teague, Behnoush Abedi‐Ardekani, Stefano Serra, Jean‐Yves Scoazec, Hiva Saffar, Farid Azmoudeh-Ardelan, Masoud Sotoudeh, Arash Nikmanesh, Michael Edén, Paul Richman, Lia S. Campos, Rebecca C. Fitzgerald, Luis Felipe Ribeiro, Charles P. Dzamalala, Blandina T. Mmbaga, Tatsuhiro Shibata, Diana Menya, Alisa M. Goldstein, Nan Hu, Reza Malekzadeh, Abdolreza Fazel, Valerie McCormack, James McKay, Sandra Pérdomo, Ghislaine Scélo, Estelle Chanudet, Laura Humphreys, Ludmil B. Alexandrov, Paul Brennan, Michael R. Stratton

Bibliographic record

VenuemedRxiv · 2021
Typepreprint
Languageen
FieldMedicine
TopicEsophageal Cancer Research and Treatment
Canadian institutionsUniversity Health Network
FundersNIHR Cambridge Biomedical Research CentreMedical Research CouncilNational Institute for Health and Care ResearchWorld Cancer Research FundWereld Kanker Onderzoek FondsCancer Research UKCentre International de Recherche sur le CancerWorld Health Organization
KeywordsIncidence (geometry)Germline mutationAPOBECEsophageal squamous cell carcinomaGermlineBiologyGeneticsMutationEsophageal cancerCancerCancer researchOncologyInternal medicineGenomeMedicineGene

Abstract

fetched live from OpenAlex

Abstract Esophageal squamous cell carcinoma (ESCC) shows a remarkable variation in incidence which is not fully explained by known lifestyle and environmental risk factors. It has been speculated that an unknown exogenous exposure(s) could be responsible. Here we combine the fields of mutational signature analysis with cancer epidemiology to study 552 ESCC genomes from eight countries with varying incidence rates. The mutational profiles of ESCC were similar across all countries studied. Associations between specific mutational signatures and ESCC risk factors were identified for tobacco, alcohol, opium and germline variants, with modest impacts on mutation burden. We find no evidence of a mutational signature indicative of an exogenous exposure capable of explaining the differences in ESCC incidence. APOBEC associated mutational signatures SBS2 and SBS13 were present in 88% and 91% of cases respectively and accounted for a quarter of the mutation burden on average, indicating that activation of APOBEC is a crucial step in ESCC tumor development.

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), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.092
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.293
Teacher spread0.274 · 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 designObservational
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

Citations26
Published2021
Admission routes1
Has abstractyes

Explore more

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