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Record W4404256900 · doi:10.1093/neuonc/noae165.0279

CSIG-30. EXPLORING THE ROLE OF CAPICUA (CIC) IN RESISTANCE MECHANISMS OF MEK INHIBITORS IN GLIOBLASTOMA

2024· article· en· W4404256900 on OpenAlexaff
Phooja Persaud

Bibliographic record

VenueNeuro-Oncology · 2024
Typearticle
Languageen
FieldMedicine
TopicFungal Biology and Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsGlioblastomaResistance (ecology)Cancer researchChemistryMedicineBiologyEcology

Abstract

fetched live from OpenAlex

Abstract Glioblastoma multiforme (GBM) is the most common and fatal primary brain tumor, resistant to conventional therapy. Despite its heterogeneous nature, a key feature of GBM is aberrant kinase signaling. Specifically, hyperactivation of receptor tyrosine kinases (RTK) and their downstream tumorigenic effectors Ras/MEK/Extracellular Signal Regulated Kinase (ERK) pathway are attributed to the aggressive nature of GBM. Capicua (CIC) is a High Mobility Group (HMG) box transcriptional repressor that directly binds to DNA and counteracts the transcription of genes typically expressed only in response to RTK activation such as oncogenic transcription factors ETV1/4/5. Hyperactive MEK/ERK signaling in GBM causes CIC degradation. The mechanism of CIC’s repressor function is not well understood, however, transcriptional repressors (like CIC) typically form co-repressor complexes to repress target genes. We discovered a novel interaction between CIC and the transcriptional regulator yin yang 1 (YY1), a context-dependent transcription factor that can repress or activate gene expression. We uncovered that 90-kDa ribosome S6 protein kinase (p90RSK), a downstream effector of ERK and a known CIC regulator, mediates the CIC/YY1 interaction. Interestingly, we found re-activation of p90RSK following MEK/ERK inhibition implicating p90RSK in the resistance mechanism of RTK/MEK/ERK inhibition in GBM. We hypothesize that p90RSK inhibition will stabilize the CIC/YY1 co-repressor complex and re-sensitize towards MEK/ERK inhibition. Patient-derived glioma stem-like cells (GSCs) were treated with increasing doses of BI-D1870 or LJI308 (p90RSK inhibitors) with and without selumetinib (MEK inhibitor) and various functional assays were performed to examine the effect of p90RSK inhibition on the CIC/YY1 complex and sensitization to MEK/ERK inhibition. Treatment with BI-D1870 and LJI308 markedly reduced viability and mRNA expression of ETV1/4/5 indicating that p90RSK inhibition may mediate CIC /YY1 DNA binding ability. Importantly, inhibiting p90RSK sensitized GSCs to MEK/ERK inhibition. These results highlight the importance of downstream p90RSK inhibition in stabilizing CIC/YY1 repressor complex function and sensitizing cells to RTK/MEK/ERK inhibition.

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 score0.066
Threshold uncertainty score0.275

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 head0.020
GPT teacher head0.278
Teacher spread0.258 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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