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Record W2033091977 · doi:10.1021/ml4003138

Potent Targeting of the STAT3 Protein in Brain Cancer Stem Cells: A Promising Route for Treating Glioblastoma

2013· article· en· W2033091977 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueACS Medicinal Chemistry Letters · 2013
Typearticle
Languageen
FieldMedicine
TopicCytokine Signaling Pathways and Interactions
Canadian institutionsHospital for Sick ChildrenThe Scarborough HospitalUniversity of CalgaryOntario Institute for Cancer ResearchUniversity of Toronto
Fundersnot available
KeywordsSTAT3GliomaCancer researchIn vivoBrain tumorStem cellCancer stem cellGlioblastomaMedicineCancerPhosphorylationBiologyPathologyInternal medicineCell biology

Abstract

fetched live from OpenAlex

The STAT3 gene is abnormally active in glioblastoma (GBM) and is a critically important mediator of tumor growth and therapeutic resistance in GBM. Thus, for poorly treated brain cancers such as gliomas, astrocytomas, and glioblastomas, which harbor constitutively activated STAT3, a STAT3-targeting therapeutic will be of significant importance. Herein, we report a most potent, small molecule, nonphosphorylated STAT3 inhibitor, 31 (SH-4-54) that strongly binds to STAT3 protein (K D = 300 nM). Inhibitor 31 potently kills glioblastoma brain cancer stem cells (BTSCs) and effectively suppresses STAT3 phosphorylation and its downstream transcriptional targets at low nM concentrations. Moreover, in vivo, 31 exhibited blood-brain barrier permeability, potently controlled glioma tumor growth, and inhibited pSTAT3 in vivo. This work, for the first time, demonstrates the power of STAT3 inhibitors for the treatment of BTSCs and validates the therapeutic efficacy of a STAT3 inhibitor for GBM clinical application.

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.

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 score0.017
Threshold uncertainty score0.485

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 head0.012
GPT teacher head0.253
Teacher spread0.241 · 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