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Record W4404237702 · doi:10.1093/neuonc/noae165.0606

IMMU-13. TRANS-SPECIES STUDY OF IDH-MUTANT REPLICATION-REPAIR DEFICIENT HIGH-GRADE GLIOMAS (RRD-HGG) AND RESPONSE TO COMBINED TARGETED AND IMMUNOTHERAPY: AN IRRDC STUDY

2024· article· en· W4404237702 on OpenAlexaffabout
Anirban Das, Vienna Mazzoli, Nicholas Fernandez, Zoya Aamir, Nuno M. Nunes, Katharine O’Flaherty, Kevin Bielamowicz, Gadi Abebe‐Campino, Shani Caspi, Per Olof Nyman, Richard Graham, John Kim, Mari Wilhelmsson, Mette Jorgensen, Orli Michaeli, M Cespon Fernandez, A. O. Reddy, Nicholas Llosa, Amanda Li, Lucie Stengs, Logine Negm, Vanessa Bianchi, Melissa Edwards, Birgit Ertl‐Wagner, Julie Bennett, Peter B. Dirks, Éric Bouffet, Cynthia Hawkins, Uri Tabori

Bibliographic record

VenueNeuro-Oncology · 2024
Typearticle
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsMutantImmunotherapyReplication (statistics)Cancer researchBiologyMedicineImmune systemVirologyImmunologyGeneticsGene

Abstract

fetched live from OpenAlex

Abstract BACKGROUND AND AIMS IDH-mutant gliomas comprise <10% of HGG in children. RRD-HGG comprise 5-10% of childhood HGG, demonstrate high mutation burden (TMB) and respond to immune-checkpoint inhibition (ICI). The impact of RRD within childhood IDH-mutant gliomas, and effective therapeutic options for these patients are not well-established. METHODS Clinical and multi-omic analyses were performed on IDH mut -RRD-HGG registered to the IRRDC and the Toronto glioma taskforce. Tumor development and genomic data were studied from a novel IDH mut -RRD-HGG immunocompetent mouse model. Outcome following ICI and targeted therapy were evaluated. RESULTS RRD was detected in >60% of childhood IDH mut -HGG. IDH1-mutations were detected in 20% of RRD-HGG. All patients with IDH mut -RRD-HGG (n=49) harboured germline variants in MMR genes (CMMRD: 65%, Lynch: 35%). Contrary to sporadic IDH mut -gliomas, >91% were WHO-grades 3/4. Diffuse/multifocal disease involving the frontal lobe was frequent. TMB (median: 28 mutations/Mb) was lower than IDH-wildtype RRD-HGG (p<0.05). POLE/POLD1 mutations were absent. TP53 and ATRX were frequent somatic hits. Copy number changes, particularly CDKN2A/2B loss, were common. IDH-mutation contributed to an immune-suppressed microenvironment, with lower CD8-T-cell infiltration (immunohistochemistry) and tumor-inflammation scores (transcriptome; p<0.05). A novel mouse model (Olig2-Cre+/Msh2LoxP/LoxP/LSL-Idh1R132H/+) demonstrated similar TMB, diffuse cerebral involvement, slower growth, and lesser immune infiltrates as compared with IDH-wildtype RRD-HGG models, and provided opportunity for therapeutic testing. RRD contributed to poor survival in IDHmut-gliomas (p<0.001). Despite hypermutation, ICI monotherapy resulted in inferior survival in IDH mut -RRD-HGG vs IDH-wildtype RRD-HGG (p<0.05). Five patients developed metachronous IDH mut -RRD-HGG while on anti-PD1 treatment for IDH-wildtype RRD-HGG, suggesting intrinsic ICI-resistance. Ivosidenib (IDH-inhibitor) demonstrated objective response in 4/8 IDH mut -RRD-HGG. Furthermore, for IDH mut -RRD-HGG on ICI treatment, the addition of ivosidenib prolonged survival at 12-months in comparison to those without IDH-inhibition (p=0.01) CONCLUSIONS Hypermutant RRD-HGG with IDH1;p.R132H harbour unique immuno-biology and do not respond to anti-PD1 monotherapy. The addition of IDH-inhibition demonstrated favourable responses, supporting need for evaluation of the combination in clinical trials.

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)0.001
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
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
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 head0.026
GPT teacher head0.319
Teacher spread0.293 · 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 routes2
Has abstractyes

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