Identification of Injury-Response State Determinants in Glioblastoma Stem Cells
Bibliographic record
Abstract
Abstract Glioblastoma (GBM) is a common and highly lethal type of primary brain tumor in adults. Therapeutic failure is partly attributed to a fraction of Glioblastoma Stem Cells (GSCs) that show high levels of heterogeneity and plasticity. GSCs exist in a transcriptional gradient between two states: Developmental (Dev) and Injury Response (IR) in which IR-GSCs exhibit more invasive behaviors. While previous studies have identified fitness genes in GSCs, the genes required to establish and maintain the Dev and IR states remain poorly defined. To identify the regulators of the IR GSC state, we performed a phenotypic genome-wide CRISPR-Cas9 knockout (KO) screen in patient-derived GSCs based on cell surface expression of the IR marker CD44. Notably, we found that perturbations of the histone acetyltransferase EP300 in IR GSCs led to decreased CD44 cell surface expression, significant downregulation of gene expression signatures associated with the IR state, and to decreased self-renewal and invasion. Furthermore, genetic targeting of Ep300 in a mouse GBM model delayed tumor initiation and/or progression. Collectively, our results establish EP300 as a regulator of the IR state in GSCs and provide a mechanistic basis for its therapeutic targeting in GBM. Significance A genome-wide phenotypic CRISPR-Cas9 screen in a patient-derived Glioblastoma Stem Cell line identified the genes required to maintain the Injury-Response cellular state, with a focus on the histone acetyl transferase gene EP300 . This study suggests how therapeutic targeting of cellular state could reduce the aggressiveness of GBM tumors.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | high |
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 | 0.001 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".