EPCO-46. CHARACTERIZING ATYPICAL TERATOID RHABDOID TUMOR SUBTYPE ENHANCER INTERACTION LANDSCAPE
Bibliographic record
Abstract
Abstract Atypical Teratoid Rhabdoid Tumor (ATRT) is one of the most aggressive pediatric tumors of the central nervous system (CNS). The majority of ATRTs are characterized by the recurrent bi-allelic loss of the SWI/SNF nucleosome remodeling complex core component gene, SMARCB1, or SMARCA4 in rare cases. Despite its bland genome, three ATRT subgroups “SHH”, “TYR”, and “MYC” were discovered with unique molecular profiles. Also, distinct activating histone mark H3K27ac profiles between molecular subgroups were identified, suggesting subgroup-specific regulatory networks through enhancers. However, comprehensive cis-regulatory network descriptions in ATRT are lacking. Here, we aim to elucidate ATRT subgroup pathogenesis through its dysregulated enhancer-promoter interactions. We have created a regulatory mutational profile of the three ATRT subgroups using whole-genome sequencing method of 60 ATRT tumors and matching genome-wide H3K27ac profiles on 16 tumors. To investigate mutation burden on cis-regulations, we have employed high-throughput Hi-C chromatin immunoprecipitation (HiChIP) technique to directly map enhancer sequences involved in DNA-looping with high specificity and sensitivity. Recent findings from our lab suggest that activating interaction PDGFRB confer to therapeutics venerability in the MYC subgroup. Here, our preliminary analysis shows a hub of interactions near PDGFRB reveals an extensive interaction hub with long-range enhancer interactions extending as far as 1500Kb, suggesting a much more complicated regulatory picture than previously expected. Interestingly, we have identified long-range DNA interactions between PDGFRB and H3K27ac marks upstream of its gene body and overstretching into other gene elements. This result suggests a potential alternative activation mechanism for MYC cell lines. Our next steps are to perform performing additional HiChIP assays on other ATRT cell lines from other subgroups to capture the full range of ATRT’s heterogeneity. Comprehensive mapping of the non-coding genome and enhancer regulatory network would help identify critical pathogenic elements underlying ATRT biology and provide insights into therapeutic targets.
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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 | 0.000 | 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".