Super-enhancer associated core regulatory circuits mediate susceptibility to retinoic acid in neuroblastoma cells
Bibliographic record
Abstract
Neuroblastoma is a pediatric tumour that accounts for more than 15% of cancer-related deaths in children. High-risk tumours are often difficult to treat, and patients’ survival chances are less than 50%. Retinoic acid treatment is part of the maintenance therapy given to neuroblastoma patients; however, not all tumours differentiate in response to retinoic acid. Within neuroblastoma tumors, two phenotypically distinct cell types have been identified based on their super-enhancer landscape and transcriptional core regulatory circuitries: adrenergic (ADRN) and mesenchymal (MES). We hypothesized that the distinct super-enhancers in these different tumour cells mediate differential response to retinoic acid. To this end, three different neuroblastoma cell lines, ADRN ( MYCN amplified and non-amplified) and MES cells, were treated with retinoic acid, and changes in the super-enhancer landscape upon treatment and after subsequent removal of retinoic acid was studied. Using ChIP-seq for the active histone mark H3K27ac, paired with RNA-seq, we compared the super-enhancer landscape in cells that undergo neuronal differentiation in response to retinoic acid versus those that fail to differentiate and identified unique super-enhancers associated with neuronal differentiation. Among the ADRN cells that respond to treatment, MYCN -amplified cells remain differentiated upon removal of retinoic acid, whereas MYCN non-amplified cells revert to an undifferentiated state, allowing for the identification of super-enhancers responsible for maintaining differentiation. This study identifies key super-enhancers that are crucial for retinoic acid-mediated differentiation.
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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 | 0.001 |
| 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) | 0.000 | 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".