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Record W4221004489 · doi:10.1126/sciadv.abi7640

Transcriptional census of epithelial-mesenchymal plasticity in cancer

2022· article· en· W4221004489 on OpenAlexaff
David P. Cook, Barbara C. Vanderhyden

Bibliographic record

VenueScience Advances · 2022
Typearticle
Languageen
FieldMedicine
TopicCancer Cells and Metastasis
Canadian institutionsOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsMesenchymal stem cellCancerBiologyPlasticityCensusComputational biologyEvolutionary biologyCell biologyMedicineGeneticsEnvironmental healthPopulationMaterials science

Abstract

fetched live from OpenAlex

Epithelial-mesenchymal plasticity (EMP) contributes to tumor progression, promoting therapy resistance and immune cell evasion. Definitive molecular features of this plasticity have largely remained elusive due to the limited scale of most studies. Leveraging single-cell RNA sequencing data from 266 tumors spanning eight different cancer types, we identify expression patterns associated with intratumoral EMP. Integrative analysis of these programs confirmed a high degree of diversity among tumors. These diverse programs are associated with combinations of various common regulatory mechanisms initiated from cues within the tumor microenvironment. We show that inferring regulatory features can inform effective therapeutics to restrict EMP.

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 score0.389
Threshold uncertainty score0.718

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.029
GPT teacher head0.327
Teacher spread0.298 · 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

Citations62
Published2022
Admission routes1
Has abstractyes

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