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Record W2027768047 · doi:10.1002/jcb.23149

The role of TWIST as a regulator in giant cell tumor of bone

2011· article· en· W2027768047 on OpenAlexaff
Shalini Singh, Isabella W.Y. Mak, Robert W. Cowan, Robert Turcotte, Gurmit Singh, Michelle Ghert

Bibliographic record

VenueJournal of Cellular Biochemistry · 2011
Typearticle
Languageen
FieldMedicine
TopicBone Tumor Diagnosis and Treatments
Canadian institutionsMcGill University Health CentreMontreal General HospitalMcMaster University
Fundersnot available
KeywordsRUNX2Stromal cellOsteoblastGiant-cell tumor of boneGene knockdownDownregulation and upregulationCancer researchOsteoclastGiant cellBiologyCell biologyRegulatorPathologyCell cultureMedicineGenetics

Abstract

fetched live from OpenAlex

Giant cell tumor of bone (GCT) is an aggressive tumor consisting of multinucleated osteoclast-like giant cells and proliferating osteoblast-like stromal cells. Our group has reported that the stromal cells express high levels of the bone resorbing matrix metalloproteinase (MMP)-13, and that this expression is regulated by the osteoblast transcription factor Runx2. The purpose of this study was to determine the upstream regulation of Runx2 in GCT cells. Using GCT stromal cells obtained from patient specimens, we demonstrated that TWIST, a master osteogenic regulator, was highly expressed in all GCT specimens. TWIST overexpression downregulated Runx2 expression whereas TWIST siRNA knockdown resulted in Runx2 and MMP-13 upregulation. Interestingly, cells obtained from a GCT lung metastasis showed a reverse regulatory pattern between TWIST and Runx2. In mutational analysis, we revealed a point mutation (R154S) at the Helix2 domain of TWIST. This TWIST mutation may be an essential underlying factor in the development and pathophysiology of these tumors in that they lead to inappropriate TWIST downregulation of Runx2, arrested osteoblastic differentiation, and the maintenance of an immature and neoplastic phenotype.

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 score0.297

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 head0.006
GPT teacher head0.206
Teacher spread0.200 · 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

Citations26
Published2011
Admission routes1
Has abstractyes

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