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Record W4383187429 · doi:10.1158/0008-5472.can-23-1066

Repurposing Two Old Friends to Fight Cancer: Caffeine and Statins

2023· letter· en· W4383187429 on OpenAlexafffund
Derek W. Stouth, Paul Lebeau, Richard C. Austin

Bibliographic record

VenueCancer Research · 2023
Typeletter
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Lipids, and Metabolism
Canadian institutionsHamilton Health SciencesSt. Joseph’s Healthcare Hamilton
FundersCanadian Institutes of Health Research
KeywordsMevalonate pathwayStatinRepurposingCaffeineCancerPrenylationMedicinePharmacologyHMG-CoA reductaseCholesterolLimitingLovastatinDrug repositioningReductaseCancer researchEnzymeDrugChemistryBiologyInternal medicineBiochemistry

Abstract

fetched live from OpenAlex

Statins are a class of cholesterol-lowering drugs that inhibit 3-hydroxy-3-methylglutaryl-CoA reductase, the rate-limiting enzyme of the mevalonate pathway. Evidence suggests that certain cancers depend on the mevalonate pathway for growth and survival, and thus blocking the mevalonate pathway with statins may offer a viable therapeutic approach for treating cancer, or at least enhance the efficacy of existing cancer drugs. In this issue of Cancer Research, Tran and colleagues showed that caffeine works jointly with FOXM1 inhibition to enhance the antitumor activity of statins in neuroblastoma cells. They found that caffeine synergizes with statins by suppressing statin-induced feedback activation of the mevalonate pathway. Here, we reflect on the potential of combining caffeine and statin drugs as a strategy for potentiating anticancer activity. See related article by Tran et al., p. 2248.

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)0.001
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.389
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.058
GPT teacher head0.411
Teacher spread0.353 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations8
Published2023
Admission routes2
Has abstractyes

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