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Record W2542459035 · doi:10.1002/path.4780

A focused compound screen highlights the significance of epidermal growth factor receptor signalling in chordoma pathogenesis

2016· letter· en· W2542459035 on OpenAlexafffund
Mira Ghaly, Corin Seelemann, Arezu Jahani‐Asl

Bibliographic record

VenueThe Journal of Pathology · 2016
Typeletter
Languageen
FieldMedicine
TopicBone Tumor Diagnosis and Treatments
Canadian institutionsMcGill UniversityJewish General Hospital
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsChordomaEpidermal growth factor receptorMedicineEGFR inhibitorsCancer researchClinical significancePathologicalOncologyInternal medicineCancerPathology

Abstract

fetched live from OpenAlex

Chordoma is a rare primary bone cancer with limited treatment options. Surgical resection followed by radiotherapy has proven effective; however, when, in 30-40% of patients, tumours recur and metastasize, a high level of resistance to chemotherapies leaves these patients with a dearth of treatment options. Recent work published in the Journal of Pathology by Scheipl et al describing a focused compound drug screen highlights the significance of epidermal growth factor receptor (EGFR) signalling in chordoma, and shows potential for EGFR inhibitors as a way forward for developing an effective treatment for chordoma. Importantly, combining EGFR inhibitors with a MET inhibitor induces a synergistic effect on growth inhibition of resistant chordoma cells, highlighting the significance of combined EGFR and MET inhibitors as a potential avenue to defeat chemoresistance in chordoma patients. Copyright © 2016 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.445
Threshold uncertainty score0.694

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.032
GPT teacher head0.265
Teacher spread0.233 · 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 designNot applicable
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

Citations4
Published2016
Admission routes2
Has abstractyes

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