STEM-16. MACROH2A2 REPRESSES AN EPIGENETIC SELF-RENEWAL NETWORK IN GLIOBLASTOMA STEM CELLS
Bibliographic record
Abstract
Abstract Glioblastoma is a highly malignant tumour driven by a subset of self-renewing cells termed glioblastoma stem cells. This self-renewal phenotype is largely epigenetically driven, however, the exact epigenetic mechanisms underpinning it are poorly understood. We found that the histone variant macroH2A2 is repressed in a subset of glioblastoma tumours, and that this repression is associated with poorer survival. We interrogate the function of macroH2A2 using in vitro and in vivo patient-derived models. We show that macroH2A2 antagonizes self-renewal and expression of NPC and OPC-like markers, and rewires accessible chromatin by maintaining accessibility at a subset of enhancer elements. We identify small molecules that can upregulate macroH2A2 expression, and find that treatment with a small molecule reduces self-renewal, induces interferon sensitive genes, and a viral mimicry response, effects which are abolished by macroH2A2 knockdown. In summary, we identify macroH2A2 as a repressor of self-renewal in glioblastoma and suggest it may be a novel biomarker and potential marker of therapeutic susceptibility.
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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 | 0.000 |
| 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".