Microglia induces Gas1 expression in human brain tumor-initiating cells to reduce tumorigenecity
Bibliographic record
Abstract
We reported previously that microglia decreased the growth of human brain tumor-initiating cells (BTICs). Through microarray analyses of BTICs exposed in vitro to microglia, we found the induction of several genes ascribed to have roles in cell cycle arrest, reduced cell proliferation and differentiation. Herein, we tested the hypothesis that one of these genes, growth arrest specific 1 (Gas1), is a novel growth reduction factor that is induced in BTICs by microglia. We found that microglia increased the expression of Gas1 transcript and protein in glioblastoma patient-derived BTIC lines. Using neurosphere assay we show that RNAi-induced reduction of Gas1 expression in BTICs blunted the microglia-mediated BTIC growth reduction. The role of Gas1 in mediating BTIC growth arrest was further validated using orthotopic brain xenografts in mice. When microglia-induced Gas1-expressing BTIC cells (mGas1-BTICs) were implanted intra-cranially in mice, tumor growth was markedly decreased; this was mirrored in the remarkable increase in survival of mGas1-BT025 and mGas1-BT048 implanted mice, compared to mice implanted with non-microglia-exposed BTIC cells. In conclusion, this study has identified Gas1 as a novel factor and mechanism through which microglia arrest the growth of BTICs for anti-tumor property.
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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".