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Record W4404230928 · doi:10.1093/neuonc/noae165.0511

DDDR-26. IDENTIFICATION OF MODULATORS OF IDH INHIBITOR SENSITIVITY IN<i>IDH</i>-MUTATED DIFFUSE GLIOMAS

2024· article· en· W4404230928 on OpenAlexaff
Sumaiyah Saleek, Eric Laugesen, Poorani Ganesh Subramani, Ruxiao Tian, Annette Wu, Samah El Ghamrasni, Adrian Levine, Zoya Aamir, Kevin Petrecca, Samuel K. McBrayer, Mario L. Suvà, Cynthia Hawkins, Uri Tabori, Tak W. Mak, Jérôme Fortin

Bibliographic record

VenueNeuro-Oncology · 2024
Typearticle
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsHospital for Sick ChildrenPrincess Margaret Cancer CentreMcGill University
Fundersnot available
KeywordsIdentification (biology)Sensitivity (control systems)BiologyBotanyEngineering

Abstract

fetched live from OpenAlex

Abstract Driver mutations in IDH1 and IDH2 characterize a substantial proportion of lower-grade diffuse gliomas in adults. Mutated IDH molecules cause the accumulation of D-2-hydroxyglutarate (D-2-HG), which perturbs many cellular functions, including metabolism, epigenetic regulation, and the ability to differentiate. This is notably associated with DNA and histone hyper-methylation. Recently, the newly developed IDH inhibitor, vorasidenib, was shown to delay tumor progression and the need for additional treatment in the groundbreaking INDIGO clinical trial. Nevertheless, the responses to vorasidenib were variable between patients, and so far have been established only for less aggressive disease. In addition, it is unclear to what extent vorasidenib can cause tumor regression. This highlights the need to identify molecules and pathways that control IDH inhibitor sensitivity. Towards this goal, we generated a new mouse model that combines Idh1R132H and Trp53 loss-of-function, targeted to oligodendrocyte progenitors. All the mutant mice develop diffuse gliomas that recapitulate the cardinal features of the corresponding human disease. We established multiple cell lines from these tumors, which retained expression of mutant IDH. The cells robustly produced D-2-HG, which was concentration-dependently suppressed by vorasidenib. Accordingly, vorasidenib could lower DNA methylation, and induce the expression of mature glial cell markers. To identify determinants of vorasidenib sensitivity, we performed genome-wide loss-of-function CRISPR/Cas9 functional genomics screens. In those experiments, targeting genes associated with astrocyte differentiation or Notch signaling enhanced cell fitness in the presence of vorasidenib, consistent with the anticipated effects of the drug on inducing cell differentiation. Conversely, vorasidenib-treated cells were more sensitive to the loss of regulators of cell growth and metabolism, and of some epigenetic regulators. These studies point to strategies that may enhance the efficacy of IDH inhibitors for the treatment of IDH mutated gliomas.

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 score0.002
Threshold uncertainty score0.006

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)0.0020.001

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 head0.016
GPT teacher head0.298
Teacher spread0.282 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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