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Record W2913881486 · doi:10.1016/j.neo.2019.05.004

The FUS-DDIT3 Interactome in Myxoid Liposarcoma

2019· article· en· W2913881486 on OpenAlexafffund
Jamie Yu, Shane Colborne, Christopher S. Hughes, Gregg B. Morin, Torsten O. Nielsen

Bibliographic record

VenueNeoplasia · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Chromatin Dynamics
Canadian institutionsBC Cancer AgencyUniversity of British Columbia
FundersCanadian Cancer Society Research InstituteTerry Fox Research Institute
KeywordsInteractomeMyxoid liposarcomaBiologyChromatin immunoprecipitationChromatinCancer researchComputational biologyLiposarcomaGene expressionPathologyMedicineGeneGeneticsSarcoma

Abstract

fetched live from OpenAlex

Myxoid liposarcoma is a malignant lipogenic tumor that develops in deep soft tissues. While local control rates are good, current chemotherapy options remain ineffective against metastatic disease. Myxoid liposarcoma is characterized by the FUS-DDIT3 fusion oncoprotein that is proposed to function as an aberrant transcription factor, but its exact mechanism of action has remained unclear. To identify the key functional interacting partners of FUS-DDIT3, this study utilized immunoprecipitation-mass spectrometry (IP-MS) to identify the FUS-DDIT3 interactome in whole cell lysates of myxoid liposarcoma cells, and results showed an enrichment of RNA processing proteins. Further quantitative MS analyses of FUS-DDIT3 complexes isolated from nuclear lysates showed that members of several chromatin regulatory complexes were present in the FUS-DDIT3 interactome, including NuRD, SWI/SNF, PRC1, PRC2, and MLL1 COMPASS-like complexes. Co-immunoprecipitation validated the associations of FUS-DDIT3 with BRG1/SMARCA4, BAF155/SMARCC1, BAF57/SMARCE1, and KDM1A. Data from this study provides candidates for functional validation as potential therapeutic targets, particularly for emerging epigenetic drugs.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.806
Threshold uncertainty score0.319

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 head0.002
GPT teacher head0.201
Teacher spread0.199 · 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

Citations45
Published2019
Admission routes2
Has abstractyes

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