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Twenty Years on: What Do We Really Know about Ewing Sarcoma and What Is the Path Forward?

2015· review· en· W1657723498 on OpenAlexaff
Elizabeth R. Lawlor, Poul H. Sorensen

Bibliographic record

VenueCritical Reviews™ in Oncogenesis · 2015
Typereview
Languageen
FieldMedicine
TopicSarcoma Diagnosis and Treatment
Canadian institutionsUniversity of British ColumbiaBC Cancer Agency
FundersNational Cancer Institute
KeywordsPathognomonicDiseaseMedicineMetastasisSarcomaEpigeneticsClinical trialBioinformaticsOncologyBiologyInternal medicinePathologyCancerGene

Abstract

fetched live from OpenAlex

Ewing sarcoma (ES) is a highly aggressive bone and soft-tissue tumor with peak incidence among adolescents and young adults. Despite advances in local control and systemic chemotherapy, metastatic relapse after an initial clinical remission remains a significant clinical problem. In addition, metastasis at the time of presentation or at relapse continues to be the leading cause of death for patients diagnosed with ES. Since the discovery of the pathognomonic EWS-FLI1 fusion gene more than 20 years ago, much about the molecular and cellular biology of ES pathogenesis has been learned. In addition, more recent exploitation of advances in stem cell and developmental biology has provided key insights into the cellular origins of ES and the role of epigenetic deregulation in tumor initiation and maintenance. Nevertheless, the mechanisms that drive tumor relapse and metastasis remain largely unknown. These gaps in our knowledge continue to hamper the development of novel therapeutic strategies that may improve outcomes for patients with relapsed and metastatic disease. In this article we review the current status of ES biology research, highlighting areas of investigation that we consider to have the greatest potential to yield findings that will translate into clinically significant advances.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.981
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.083
GPT teacher head0.404
Teacher spread0.321 · 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.

Study designOther design
Domainnot available
GenreReview

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

Citations89
Published2015
Admission routes1
Has abstractyes

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