Mouse glioma gene expression profiling identifies novel human glioma‐associated genes
Bibliographic record
Abstract
Based on previous studies demonstrating increased RAS activity in human astrocytomas, we developed a transgenic mouse model (B8) that targets an activated RAS molecule to astrocytes. Within 3 to 4 months after birth, these mice develop high-grade astrocytomas that are histologically identical to human astrocytomas. To characterize genetic events associated with B8 mouse astrocytoma formation, we employed comparative gene expression profiling of wild-type cultured mouse astrocytes, non-neoplastic B8 astrocytes, B8 astrocytoma cultures, and two other astrocytoma cultures from independently derived RAS transgenic mouse lines. We identified several classes of gene expression changes, including those associated with the non-neoplastic state in the B8 transgenic mouse, those associated with astrocytoma formation, and those specifically associated with only one of the three independently derived transgenic mouse astrocytomas. Differential expression of several unique genes was confirmed at the protein level in both the RAS transgenic mouse astrocytomas and two human glioblastoma multiforme cell lines. Furthermore, reexpression of one of these downregulated astrocytoma-associated proteins, GAP43, resulted in C6 glioma cell growth suppression. The use of this transgenic mouse model to identify novel genetic changes that might underlie the pathogenesis of human high-grade astrocytomas provides a unique opportunity to discover future targets for brain tumor therapy.
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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 | 0.001 | 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, 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".