HGG-11. Integrated molecular profiling of H3 wild-type diffuse paediatric-type high-grade glioma
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Background Within the WHO2021 CNS Tumour Classification, oncohistone H3-mutations define around half of paediatric-type diffuse high grade glioma, however the remaining tumours (H3-WT-PDHGG) are less well described. Methods Published and unpublished DNA sequencing from n = 1601 H3-WT-PDHGG cases were integrated with n = 1847 cases with methylation array profiling, along with bulk (n = 251) and single-cell (n = 65) RNAseq data. Results Within H3-WT high-grade glioma, a total of 11 MNP12.8-defined subgroups were found to have a peak incidence <18years, excluding infant hemispheric glioma. Clustering of methylation data by tSNE/UMAP highlighted two highly distinct superclusters, with multiple subgroups within each. Supercluster_I was defined by radiation-induced secondary and/or hypermutant tumours, incorporating HGG-E (n = 44), cerebellar-enriched tumours (n = 38), and the paediatric RTK1 group (n = 295), further split into A, B and C subgroups. There were profound molecular differences between RTK1A and B/C subgroups, with 1A harbouring few CNAs and many more SNVs (SETD2, NF1), even in the absence of a hypermutator phenotype (also enriched compared to RTK1B/C), as well as a significantly longer overall survival. Distinct from these subgroups was Supercluster_II, which included pedHGG-RTK2A/B (n = 117), but also pedHGGA/B (n = 84) and pedHGG-MYCN (n = 122) subgroups, in addition to the predominantly H3-WT DMG-EGFR (n = 86). Although seemingly disparate, a common feature of these tumours was a highly infiltrative phenotype, either involving multiple cerebral lobes (gliomatosis cerebri) or thalami (bithalamic glioma). Analogous to pedHGG-RTK1, RTK2A harboured few CNAs and more CNVs (BCOR, PIK3CA), and a longer survival compared with 2B. Integrating subgroup-specific differential methylation and gene expression identified subgroup-specific epigenetic regulation of numerous developmentally-restricted transcription factors associated with their distinct neurodevelopmental origins; combining deconvolution approaches to bulk analyses with integrated scRNAseq allowed for identification of subgroup-specific immune cell annotation. Conclusion H3-WT-PDHGG segregate into two major classes with common clinical features, but each with multiple subgroups harbouring key molecular and phenotypic differences.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it