BI-21 * BRAF MUTATION AND CDKN2A DELETIONS DEFINE A CLINICALLY DISTINCT SUBGROUP OF CHILDHOOD SECONDARY HIGH GRADE GLIOMA
Bibliographic record
Abstract
PURPOSE: Pediatric secondary high grade glioma (sHGG), which result from malignant transformation of low grade glioma (PLGG), are a poorly understood group of tumors with devastating outcomes. PATIENTS AND METHODS: We performed a population-based study combined with long-term follow-up of PLGG that transformed to sHGG. Exonic-sequencing and copy number alterations were investigated on a discovery cohort, followed by detailed genetic analysis of all tumors. Clinical and outcome data analysis of a genetically distinct subgroup was performed. RESULTS: sHGG were observed in 28/888 (3.2%) patients treated in Southern Ontario for PLGG with a median latency of 2.74 years (range, 0.18-20.3 years). sHGG were characterized by a high somatic mutation load (23 per genome). Alterations in chromatin modifying genes and major telomere maintenance pathways were observed in 57% and 54% of sHGG respectively. However, specific mutations in IDH1, H3F3A G34 and ATRX were extremely rare. The most recurrent somatic alterations were the oncogenic BRAF V600E mutation and deletion of the tumor suppressor gene CDKN2A, observed in 39% and 57% of sHGG respectively. Importantly, all BRAF V600E and 80% of CDKN2A alterations could be traced to the patient-matched PLGG counterparts. These early alterations were rarely observed in non-transformed PLGG (p < 0.0001) and primary childhood high grade glioma (p = 0.0023). The BRAF mutant sHGG subgroup was characterized by longer latency periods to transformation than non-BRAF mutant sHGG (median 6.59 versus 1.62 years; p < 0.0001). Furthermore, 5-year overall survival of children with BRAF mutant and wild-type PLGG that transformed were 75% ± 15% and 29% ± 12% respectively (p = 0.024). CONCLUSION: BRAF V600E mutations and CDKN2A deletions constitute a clinically distinct subtype of sHGG. The prolonged course to transformation provides a window of opportunity for aggressive surgical interventions, targeted therapy against oncogenic BRAF, and extended surveillance to potentially mitigate the devastating transformation event.
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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 | 0.000 | 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) | 0.001 | 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".