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Record W4223436726 · doi:10.3390/cancers14081908

Cannabinol Inhibits Cellular Proliferation, Invasion, and Angiogenesis of Neuroblastoma via Novel miR-34a/tRiMetF31/PFKFB3 Axis

2022· article· en· W4223436726 on OpenAlexafffund
Bo Wang, Dongping Li, Viktoriia Cherkasova, Marta Gerasymchuk, Aru Narendran, Igor Kovalchuk, Olga Kovalchuk

Bibliographic record

VenueCancers · 2022
Typearticle
Languageen
FieldMedicine
TopicNeuroblastoma Research and Treatments
Canadian institutionsUniversity of CalgaryUniversity of Lethbridge
FundersCanadian Institutes of Health ResearchNatural Sciences and Engineering Research Council of CanadaMitacs
KeywordsNeuroblastomaAngiogenesisCancer researchGene knockdownPediatric cancerCell growthDownregulation and upregulationProtein kinase BEctopic expressionCell cultureBiologyMedicineCancerCell biologySignal transductionInternal medicineGenetics

Abstract

fetched live from OpenAlex

High-risk neuroblastoma is an aggressive pediatric tumor. Despite great advances in neuroblastoma therapy and supportive care protocols, no curative treatment is available for most patients with this disease. Here, we uncover that CBN attenuated the cell proliferation, invasion, and angiogenesis of neuroblastoma cell lines in a dose-dependent manner via the inhibition of the AKT pathway and the upregulation of miR-34a that targets E2F1. Both miR-34a and a 31-nt tRNAiMet fragment (tRiMetF31) derived from miR-34a-guided cleavage were downregulated in 4 examined neuroblastoma cell lines inversely correlated with the levels of its direct target, the PFKFB3 protein. Moreover, ectopic tRiMetF31 suppressed proliferation, migration, and angiogenesis in the studied neuroblastoma cell lines. Conversely, tRiMetF31 knockdown promoted PFKFB3 expression, resulting in enhanced angiogenesis. Our findings reveal a suppressive role of CBN in neuroblastoma tumorigenesis, highlighting a novel and crucial miR-34a tumor suppressor network in CBN’s antineuroblastoma actions.

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 categoriesnone
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 score0.015
Threshold uncertainty score0.717

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.019
GPT teacher head0.254
Teacher spread0.234 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations17
Published2022
Admission routes2
Has abstractyes

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