HGG-11. TRANS-SPECIES STUDY OF IDH-MUTANT REPLICATION-REPAIR DEFICIENT HIGH-GRADE GLIOMAS (RRD-HGG) AND RESPONSE TO COMBINED TARGETED AND IMMUNOTHERAPY: AN IRRDC STUDY
Bibliographic record
Abstract
Abstract BACKGROUND 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 with childhood IDH-mutant gliomas, and effective therapeutic options for these patients are not well-established. METHODS Clinical and multi-omic analyses were performed on IDHmut-RRD-HGG registered to the IRRDC and the glioma taskforce. Tumor development and genomic data were studied from a novel IDHmut-RRD-HGG immunocompetent mouse model. Outcome following ICI and targeted therapy were evaluated. RESULTS IDH mut-RRD-HGG accounted for >60% of childhood IDH-mutant-HGG. Conversely, IDH1-mutations were detected in 20% of RRD-HGG. All patients (n=48) harboured germline mutations in MMR genes (CMMRD: 62%, Lynch syndrome: 38%). Contrary to sporadic IDH-mutant-gliomas, the majority (>90%) were high-grade. Diffuse/multifocal involvement, predominantly involving the frontal lobe, was frequent. TMB was lower than IDH-wildtype RRD-HGG (median: 28 mutations/Mb, p<0.05). Secondary POLE/POLD1 mutations were absent. TP53 and ATRX were frequent somatic hits. Copy number changes, particularly loss of CDKN2A/2B, were common. CD8-T-cell infiltration (immunohistochemistry) and tumor inflammation score (transcriptome) were lower than IDH-wildtype RRD-HGG (p<0.05). A novel mouse model (Olig2Cre+/Msh2LoxP/LSL-Idh1R132H) revealed similar lower TMB, diffuse cerebral involvement, slower growth, and low immune infiltrates as compared with IDH-wildtype RRD-HGG models. IDHmut-RRD-HGG demonstrated worse survival as compared to sporadic IDH-mutant-HGG (p<0.001). Within RRD-HGG, ICI monotherapy resulted in inferior survival in IDHmut-RRD-HGG vs IDH-wildtype RRD-HGG (p<0.05). Five patients developed metachronous IDHmut-RRD-HGG while on anti-PD1 treatment for IDH-wildtype RRD-HGG, suggesting intrinsic resistance. Interestingly, an IDH-inhibitor demonstrated objective response in 4/8 IDHmut-RRD-HGG. Furthermore, for IDHmut-RRD-HGG on ICI treatment, the addition of an IDH-inhibitor prolonged survival at 12-months in comparison to those without (p=0.01). CONCLUSION 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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".