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Record W1603547407 · doi:10.1002/stem.1472

Expression of FUS-CHOP fusion protein in immortalized/transformed human mesenchymal stem cells drives mixoid liposarcoma formation

2013· article· en· W1603547407 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueStem Cells · 2013
Typearticle
Languageen
FieldMedicine
TopicSarcoma Diagnosis and Treatment
Canadian institutionsHealth Canada
FundersInstituto de Salud Carlos IIIHealth CanadaInstitució Catalana de Recerca i Estudis AvançatsCancer Research UK
KeywordsBiologyMesenchymal stem cellFusion geneCancer researchFusion proteinCell fusionLiposarcomaStem cellCell biologySarcomaStromal cellCell cultureGeneGeneticsPathology

Abstract

fetched live from OpenAlex

Increasing evidence supports that mesenchymal stromal/stem cells (MSCs) may represent the target cell for sarcoma development. Although different sarcomas have been modeled in mice upon expression of fusion oncogenes in MSCs, sarcomagenesis has not been successfully modeled in human MSCs (hMSCs). We report that FUS-CHOP, a hallmark fusion gene in mixoid liposarcoma (MLS), has an instructive role in lineage commitment, and its expression in hMSC sequentially immortalized/transformed with up to five oncogenic hits (p53 and Rb deficiency, hTERT over-expression, c-myc stabilization, and H-RAS(v12) mutation) drives the formation of serially transplantable MLS. This is the first model of sarcoma based on the expression of a sarcoma-associated fusion protein in hMSC, and allowed us to unravel the differentiation processes and signaling pathways altered in the MLS-initiating cells. This study will contribute to test novel therapeutic approaches and constitutes a proof-of-concept to use hMSCs as target cell for modeling other fusion gene-associated human sarcomas.

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 score0.011
Threshold uncertainty score0.925

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
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 head0.018
GPT teacher head0.254
Teacher spread0.237 · 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