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Record W4417303633 · doi:10.1093/narcan/zcaf050

What is in a name? Rethinking SMUG1 in genome maintenance

2025· review· en· W4417303633 on OpenAlexfundno aff
Natálie Rudolfová, Alexander Myr Sjetne, Nicola P. Montaldo, Torkild Visnes, Hilde Nilsen, Maurice Michel

Bibliographic record

VenueNAR Cancer · 2025
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA Repair Mechanisms
Canadian institutionsnot available
FundersNorges ForskningsrådKungliga Tekniska HögskolanEuropean CommissionEuropean Federation of Pharmaceutical Industries and AssociationsOntario Institute for Cancer ResearchDiamond Light SourceKreftforeningen
KeywordsDNA glycosylaseGenomeDNABase excision repairRNADNA repairNucleic acid

Abstract

fetched live from OpenAlex

Abstract Small base lesions in DNA are primarily repaired through the base excision repair pathway, which is initiated by DNA glycosylases. This review focuses on single-strand selective monofunctional uracil–DNA glycosylase (SMUG1), an enzyme whose name incompletely captures its broader biological roles. SMUG1 excises a wide range of substrates beyond uracil, shows a preference for double-stranded DNA, and has been reported to be a bifunctional DNA glycosylase with a weak lyase activity. Moreover, SMUG1 plays roles extending beyond DNA repair, including functions in RNA quality control and RNA biogenesis. Recently, genetic interactions have been described between SMUG1 and proteins that safeguard stressed replication forks, implicating a function for SMUG1 in cancer cell biology. Understanding SMUG1’s full repertoire is key to uncovering its role in genome maintenance and unlocking its potential as a therapeutic target. Here, we review the biochemical properties reported for SMUG1 and its distinct functions from other uracil–DNA glycosylases in vivo. We also highlight the emerging role of SMUG1 in cancer cells and its potential as a therapeutic target, emphasizing the need to define the genetic and molecular contexts in which its modulation may be beneficial.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.989
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 integrity0.0010.000
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 head0.023
GPT teacher head0.326
Teacher spread0.303 · 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 designOther design
Domainnot available
GenreReview

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

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