GENE-34. THERAPEUTICALLY TARGETING EPIGENOMIC AND TRANSCRIPTIONAL DYSFUNCTION IN ATRX-DEFICIENT GLIOMA
Bibliographic record
Abstract
Abstract Diffusely infiltrating gliomas feature loss-of-function mutations in the chromatin remodeler gene ATRX as defining molecular alterations delineating major adult and pediatric disease subtypes. We recently reported that Atrx deficiency drives glioma-relevant phenotypes, such as increased motility and astrocytic differentiation profiles, by directly modulating epigenomic landscapes and the corresponding transcriptional profiles in glioma cells of origin. In particular, Atrx deficiency was associated with disruptions in H3.3 histone content at key genetic loci. To further understand the downstream epigenomic dysfunction induced by ATRX deficiency, we compared genome-wide chromatin-state maps of Atrx+ and Atrx- primary murine neuroepithelial progenitors (mNPCs). This ChIP–seq analysis revealed major differences in the localization of heterochromatin repressive marks H3K9me3 and H3K27me3. Specifically, we identified peculiar locations in the genome displaying H3K9me3 depletion and gain of H3K27me3 upon Atrx inactivation. Interestingly, these regions were flanked by Atrx binding sites and perfectly co-localized with Lamina-Associated Domains, known to play important roles in tissue lineage specification. To better target this dysfunction, we utilized the Broad Institute Connectivity Map (CLUE analysis) to identify compounds likely to revert the unique transcriptional perturbations induced by Atrx deficiency. We found that HDAC inhibitors, as a compound class, yielded expression profiles strongly anticorrelated to those driven by Atrx deficiency in these datasets. Further integrating existing gene expression data from our mNPCs and the TCGA LGG project with our CLUE findings highlighted SIRT2, a class III HDAC, as a top potential target. SIRT2 expression was significantly upregulated in both Atrx- mNPCs and in ATRX-mutant gliomas and its specific chemical inhibition normalized cellular motility in both Atrx- mNPCs and ATRX-mutant, patient derived glioma stem cells. These findings indicate that SIRT2 inhibition represents a viable strategy to revert the epigenetic effects of ATRX deficiency on facultative heterochromatin and their transcriptional and phenotypic consequences.
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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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".