EPCO-21. CORE REGULATORY CIRCUIT TRANSCRIPTION FACTORS DRIVE EXPRESSION FROM HIGH LEVEL AMPLICONS IN PEDIATRIC HIGH-GRADE GLIOMAS
Bibliographic record
Abstract
Abstract BACKGROUND Pediatric High-Grade Gliomas (pHGGs) show recurrent high-level amplifications around the oncogenes MET, MYCN and EGFR. However what drives expression of the oncogenes from these amplicons remains unclear. We aim to discover enhancers on these amplicons that are responsible for oncogene expressions and the core regulatory transcription factors (TFs) they bind. METHOD Using RNA-seq from 12 pHGG cell lines, we identified groups of high and low-expressing pHGG lines for MET, MYCN and EGFR. We then compared the H3K27Ac ChIP-seq between the two groups using diffbind. This allowed us to identify statistically significant peaks that are differentially activated in the oncogene-high v.s. oncogene-low expressing groups. Additionally, we overlapped the positions of these candidate oncogene enhancers with the regions that are recurrently incorporated into high-level amplicons based on published whole genome sequencing data. Using a previously defined set of core regulatory TFs we determined which TF binds the amplified oncogene enhancers and could be driving oncogenic expressions of MET, MYCN and EGFR in pHGGs. RESULTS We identify 3 cell lines for both the high- and low-expressing groups for each oncogene. Cell lines with high expression of the oncogene showed distinct enhancers with significant enrichment in H3K27Ac compared to the cell lines with low expression for each oncogene. Of all enhancers with enrichment high oncogene expression groups those with binding sites for known pHGG core regulatory circuit TF were preferentially incorporated into the high-level amplicons of the oncogene. We also identified core TFs that bind enhancers for MYCN, EGFR and MET as well as core TFs that are unique to a single oncogene. CONCLUSION We identified candidate core transcription factor that drives expression of multiple oncogenes in pHGG. These could serve as a potential novel therapeutic target for pHGGs with addiction to MYCN or RTK signaling.
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How this classification was reachedexpand
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 | 0.000 |
| 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 | 0.001 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".