The Mediator tail module cooperates with proneural factors to determine fate identity in Glioblastoma
Bibliographic record
Abstract
Abstract Glioblastoma stem cells (GSCs) exhibit latent neuronal lineage differentiation potential governed by the proneural transcription factor Achaete-scute homolog 1 (ASCL1) and harnessing and promoting terminal neuronal differentiation has been proposed as a novel therapeutic strategy. Here, using a genome-wide CRISPR suppressor screen we identified genes required for ASCL1-mediated neuronal differentiation. This approach revealed a specialized function of the Mediator complex tail module and of its subunits MED24 and MED25 for this process in GSCs, human fetal neural stem cells and pluripotent stem cells. We show that upon induction of neuronal differentiation MED25 is recruited to genomic loci co-occupied by ASCL1 to regulate neurogenic gene expression programs. MED24 and MED25 are sufficient to induce neuronal differentiation in GSC cultures and to mediate neuronal differentiation in multiple contexts. Collectively our data expand our understanding of the mechanisms underlying directed terminal neuronal differentiation in brain tumor stem cells and point to a unique function of the Mediator tail in neuronal reprogramming.
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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 | 0.001 |
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".