A Tumorigenic MLL-Homeobox Network in Human Glioblastoma Stem Cells
Bibliographic record
Abstract
Glioblastoma growth is driven by cancer cells that have stem cell properties, but molecular determinants of their tumorigenic behavior are poorly defined. In cancer, altered activity of the epigenetic modifiers Polycomb and Trithorax complexes may contribute to the neoplastic phenotype. Here, we provide the first mechanistic insights into the role of the Trithorax protein mixed lineage leukemia (MLL) in maintaining cancer stem cell characteristics in human glioblastoma. We found that MLL directly activates the Homeobox gene HOXA10. In turn, HOXA10 activates a downstream Homeobox network and other genes previously characterized for their role in tumorigenesis. The MLL-Homeobox axis we identified significantly contributes to the tumorigenic potential of glioblastoma stem cells. Our studies suggest a role for MLL in contributing to the epigenetic heterogeneity between tumor-initiating and non-tumor-initiating cells in glioblastoma.
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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".