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Record W4205470750 · doi:10.3410/f.739682655.793583633

Faculty Opinions recommendation of Circular RNA-encoded oncogenic E-cadherin variant promotes glioblastoma tumorigenicity through activation of EGFR-STAT3 signalling.

2021· dataset· en· W4205470750 on OpenAlexaff
Housheng Hansen He

Bibliographic record

VenueFaculty Opinions – Post-Publication Peer Review of the Biomedical Literature · 2021
Typedataset
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCircular RNAs in diseases
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health Network
Fundersnot available
KeywordsCadherinCancer researchTranslation (biology)Circular RNAGliomaEpidermal growth factor receptorRNABiologySignallingGlioblastomaCellCell biologyReceptorGeneMessenger RNAGenetics

Abstract

fetched live from OpenAlex

Activated EGFR signalling drives tumorigenicity in 50% of glioblastoma (GBM). However, EGFR-targeting therapy has proven ineffective in treating patients with GBM, indicating that there is redundant EGFR activation. Circular RNAs are covalently closed RNA transcripts that are involved in various physiological and pathological processes. Herein, we report an additional activation mechanism of EGFR signalling in GBM by an undescribed secretory E-cadherin protein variant (C-E-Cad) encoded by a circular E-cadherin (circ-E-Cad) RNA through multiple-round open reading frame translation. C-E-Cad is overexpressed in GBM and promotes glioma stem cell tumorigenicity. C-E-Cad activates EGFR independent of EGF through association with the EGFR CR2 domain using a unique 14-amino-acid carboxy terminus, thereby maintaining glioma stem cell tumorigenicity. Notably, inhibition of C-E-Cad markedly enhances the antitumour activity of therapeutic anti-EGFR strategies in GBM. Our results uncover a critical role of C-E-Cad in stimulating EGFR signalling and provide a promising approach for treating EGFR-driven GBM. PMID: 33664496

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)0.008
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: Dataset · Consensus signal: Dataset
Teacher disagreement score0.024
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.001
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 head0.027
GPT teacher head0.333
Teacher spread0.306 · 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
GenreDataset

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
Published2021
Admission routes1
Has abstractyes

Explore more

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