EPID-25. THE CLINICAL AND MOLECULAR LANDSCAPE OF GLIOMAS IN ADOLESCENTS AND YOUNG ADULTS
Bibliographic record
Abstract
Abstract OBJECTIVE Gliomas in adolescents and young adults (AYA) are commonly treated with a standard chemo-radiation approach. Molecular alterations have not been comprehensively described to date. METHODS We compiled a multi-institutional cohort of patients diagnosed with glioma between 15-39.9 years over 20 years. Molecular analysis, therapeutic data and outcome was collected. For specific alterations, analysis included patients aged 0-39.9 years. RESULTS A total of 1900 patients with 876 AYA gliomas were included. Ongoing analysis reveals genetic alterations in 95% of available tumours. IDH p.R132H was found in 49% of tumours, while non-canonical IDH mutations were found in 7%. Paediatric-type mutations were found in 33% of AYA tumours with IDH-WT GBM accounting for the remaining 11%. The most common paediatric alterations in AYAs included BRAF p.V600E (11%) and FGFR alterations (7%) while BRAF fusions, H3 p.K27M and H3.3 p.G34R were rarely observed (4%, 4% and 1% respectively). BRAF fused tumours with non-canonical binding partners were enriched in AYAs. Analysis of BRAF-V600E gliomas between ages 0-40 revealed increased tendency for malignant tumours in patients > 20 years suggesting malignant transformation possibly due to higher rate of secondary hits. This resulted in worse overall-survival for AYA patients with BRAF-V600E glioma when compared to children under 20 years (p=0.0032). Ten-year OS of 100%, 90% and 95% was seen for BRAF fused, BRAF-V600E and FGFR-altered AYA low grade glioma respectively, compared to 14% and 25% for BRAF-V600E and FGFR-altered high grade glioma. In contrast, continuous decline was observed in the IDH-mutant gliomas with 10-year OS of 50% which declined to 29% at 15 years. CONCLUSIONS Gliomas in AYA often have non-canonical alterations that may evade standard molecular analysis. They are enriched for paediatric-type alterations with distinct molecularly-based outcomes. These tumours may respond to targeted inhibitors and would benefit from comprehensive diagnostic and therapeutic approaches.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".