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Abstract A022 Characterizing the cell of origin of Ewing sarcoma

2024· article· en· W4402267850 on OpenAlexaboutno aff
Elena Vasileva, Claire Arata, J. Gage Crump, James F. Amatruda

Bibliographic record

VenueCancer Research · 2024
Typearticle
Languageen
FieldMedicine
TopicSarcoma Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsSarcomaEwing's sarcomaMedicinePathology

Abstract

fetched live from OpenAlex

Abstract Ewing sarcoma (ES) is a malignant bone and soft tissue tumor that affects children, adolescents, and young adults. ES is characterized by the presence of a driver fusion oncogene, most frequently EWSR1-FLI1. The cell of origin of Ewing sarcoma and the mechanisms of EWSR1-FLI1-driven cell transformation are the subjects of long-standing debates, largely due to the absence of a representative mouse model. Previous reports have suggested that bone-marrow mesenchyme or/and neural crest cells may serve as potential cells of origin for Ewing sarcoma. These hypotheses have never been tested in vivo, as the EWSR1-FLI1 fusion causes severe developmental toxicity in most cell types. To address these questions, we developed a stable model enabling controlled expression of the human EWSR1-FLI1 oncofusion specifically in neural crest cells. Using this model, we demonstrated that expression of human EWSR1-FLI1 oncofusion in neural crest cells can lead to their transformation and the development of tumors in vivo. Here we applied innovative single-cell transcriptomic, genetic, and high-resolution imaging approaches to characterize cells giving rise to EWSR1-FLI1 driven tumors in zebrafish model of Ewing sarcoma. EWSR1-FLI1 hindered the normal differentiation of neural crest cells into glial and neuronal lineages. Instead, EWSR1-FLI1 strongly reprogrammed neural crest cells by upregulating the expression of mesodermal regulators, including the key mesodermal regulator tbxta (Brachyury or T) transcription factor. tbxta/TBXT expression was maintained in subset of zebrafish and human Ewing sarcomas. Our model provides a mechanism by which a neural crest cell population can be transformed to Ewing sarcoma, a malignancy with predominant mesenchymal features. Taken together, these findings shed light on the cellular and molecular mechanisms underlying Ewing sarcoma development and provide valuable insights into its pathogenesis. Citation Format: Elena Vasileva, Claire Arata, Gage Crump, James Amatruda. Characterizing the cell of origin of Ewing sarcoma [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pediatric Cancer Research; 2024 Sep 5-8; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl):Abstract nr A022.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.145
GPT teacher head0.440
Teacher spread0.295 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2024
Admission routes1
Has abstractyes

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