DIPG-38. ID1 EXPRESSION CORRELATES WITH H3F3A K27M MUTATION AND EXTRA-PONTINE INVASION IN DIPG
Bibliographic record
Abstract
ID1 regulates transcription by interacting with bHLH transcription factors and previous work has shown that over-expression of the recurrent DIPG H3F3A K27M and ACVR1 mutations in cultured astrocytes lead to an increase in ID1 expression; this has not been validated in human DIPG. DNA (exome)/RNA sequencing of 34 DIPGs and 17 normal samples (SickKids) revealed that ID1 expression was significantly increased in tumor as compared to normal (p=0.001). ID1 expression was significantly higher in H3F3A K27M-mutated tumors as compared to normal (p=0.003), but not in ACVR1-mutated tumors. This was confirmed in an analysis of pediatric high-grade gliomas (PedcBioPortal) where ID1 expression was increased in H3F3A K27M-mutated tumors as compared to H3 wildtype (p=0.0055, n=189), but not in ACVR1-mutated tumors as compared to ACVR1 wildtype (p=0.1178, n=114). In an additional patient with DIPG at autopsy, multi-focal sequencing revealed clonal mutations in HIST1H3B K27M and ACVR1 and ID1 expression correlated with tumor size and cerebellar invasion. We identified several genes whose expression in pediatric HGG correlated with that of ID1 and which have been implicated in invasion and/or metastasis in various solid tumors. ChipSeq revealed reduced K27 me3 and elevated K27 acetylation at the ID1 locus in multiple K27M-mutant DIPG cell lines, pointing to an epigenetic control of this phenotype in H3F3A K27M-mutated DIPGs. Based on these data, we propose that epigenetically controlled upregulation of ID1 promotes DIPG invasion in H3F3A K27M-mutated DIPG and represents an optimal therapeutic target.
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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 | 0.000 |
| 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".