MétaCan
Menu
Back to cohort
Record W3012000879 · doi:10.1101/2020.03.20.984476

The pathognomonic FOXL2 C134W mutation alters DNA binding specificity

2020· preprint· en· W3012000879 on OpenAlexafffund
Annaïck Carles, Genny Trigo‐Gonzalez, Rachelle Cao, Siwei Cheng, Michelle Moksa, Misha Bilenky, David G. Huntsman, Gregg B. Morin, Martin Hirst

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2020
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsCanada's Michael Smith Genome Sciences CentreUniversity of British Columbia
FundersTerry Fox Research Institute
KeywordsBiologyMissense mutationGeneticsSomatic cellMutationTranscription factorTranscriptomePoint mutationComputational biologyCell biologyMolecular biologyGeneGene expression

Abstract

fetched live from OpenAlex

Abstract The somatic missense point mutation c.402C>G (p.C134W) in the FOXL2 transcription factor is pathognomonic for adult-type granulosa cell tumours (AGCT) and a diagnostic marker for this tumour type. However, the molecular consequences of this mutation and its contribution to the mechanisms of AGCT pathogenesis remain unclear. To explore the mechanisms driving FOXL2 C134W pathogenicity we engineered V5-FOXL2 WT and V5-FOXL2 C134W inducible isogenic cell lines and performed ChIP-seq and transcriptome profiling. We found that FOXL2 C134W associates with the majority of the FOXL2 WT DNA elements as well as a large collection of unique elements genome-wide. We confirmed an altered DNA binding specificity for FOXL2 C134W in vitro and identified unique targets of FOXL2 C134W including SLC35F2 whose expression increased sensitivity to YM155 in our model. Statement of Significance Mechanistic understanding of FOXL2 C134W induced regulatory state alterations drives discovery of a rationally designed therapeutic strategy.

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 score0.010

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 head0.011
GPT teacher head0.245
Teacher spread0.234 · 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

Citations10
Published2020
Admission routes2
Has abstractyes

Explore more

Same venuebioRxiv (Cold Spring Harbor Laboratory)Same topicCRISPR and Genetic EngineeringFrench-language works237,207