OT-05 * H3.3-K27M IS A NEGATIVE PROGNOSTIC MARKER IN THALAMIC PEDIATRIC GLIOMA
Bibliographic record
Abstract
Pediatric gliomas are the most commonly diagnosed brain cancer in children, accounting for approximately 50% of all cases. Recently, we conducted genome-analysis of diffuse intrinsic pontine glioma (DIPG), which specifically arises in the brainstem. Through this, we identified a histone H3.3 mutation (a lysine-methionine substitution at position 27 [K27M]) in approximately 70% of cases. We then showed that H3.3K27M is a negative prognostic marker for DIPG patients independent of histology. We hypothesized a similar prognostic role for H3.3K27M in thalamic gliomas. Utilizing a newly optimized, ultra-sensitive digital droplet PCR assay, we analyzed 38 radiologically confirmed thalamic gliomas (13 low grade and 25 high grade gliomas). Median survival for patients with high grade thalamic gliomas was 1.35 years vs 8.71 years for low grade thalamic glioma patients. Three (23%) low grade and 11 (44%) high grade gliomas tested positive for the H3.3K27M mutation. 31 patients, clinically annotated for treatment, extent of resection, age and outcome were used to determine the prognostic implications of H3.3-K27M. Kaplan-Meier survival analysis revealed significantly worse overall survival of thalamic glioma patients harbouring the H3.3-K27M mutation versus wild type samples (log rank p < 0.001) with a median survival of 1.04 vs 5.81 years for H3.3K27M vs WT thalamic gliomas, respectively. Multivariate cox analysis demonstrated H3.3K27M mutation status to be independent of WHO grade as a predictor of overall survival with a hazard ratio of 6.5 (95% confidence intervals 1.78-24.4, p = 0.005). These findings provide the first evidence that H3.3K27M status is a negative prognostic indicator for thalamic pediatric glioma. Furthermore, we have optimized a digital droplet PCR assay to assess mutation status in small samples, including formalin-fixed paraffin embedded, with high sensitivity and specificity in a clinical setting.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".