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Controlling Temozolomide Efficacy by Light-Dependent Inhibition of O <sup>6</sup> -Methylguanine DNA Methyltransferase

2025· article· en· W4417133262 on OpenAlexafffund
Ivonne R. Lopez-Miranda, J. Sim, Gabrielle Juneau, Christopher J. Wilds, Andrew A. Beharry

Bibliographic record

VenueACS Medicinal Chemistry Letters · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA Repair Mechanisms
Canadian institutionsConcordia UniversityUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaCancer Research Society
KeywordsTemozolomideMethyltransferaseDNA methyltransferaseDNA repairDNA damageO-6-methylguanine-DNA methyltransferaseDNAEnzyme

Abstract

fetched live from OpenAlex

-Methylguanine DNA Methyltransferase (MGMT) is a major contributor in conferring resistance to alkylating agents such as temozolomide (TMZ) in cancers. The use of MGMT inhibitors can suppress resistance and enhance the efficacy of TMZ. However, current inhibitors are nonselective for cancer cells, and as a result, MGMT is also inhibited in healthy cells leading to severe side effects. Here, we report the development of a photoactivatable MGMT inhibitor, whereby irradiation is required for MGMT inhibition and subsequent enhancement of the TMZ sensitivity in T98G cells. This strategy is promising for tissue-specific therapy, whereby TMZ efficacy can only be enhanced in the cancerous region and not healthy tissue, controlled spatially by light.

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 score0.010
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.005
GPT teacher head0.229
Teacher spread0.224 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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