<i>GATA6</i> is an astrocytoma tumor suppressor gene identified by gene trapping of mouse glioma model
Bibliographic record
Abstract
Malignant astrocytomas are the most common and lethal adult primary brain tumor. Retroviral gene trapping of nontransformed neonatal astrocytes from a glial fibrillary acidic protein (GFAP):(V12)Ha-Ras murine astrocytoma model led to isolation of the transcription factor Gata6. Loss of Gata6 resulted in enhanced proliferation and transformation of astrocytes. Human malignant astrocytoma cell lines, explant xenografts, and operative specimens demonstrated loss of GATA6 expression. Loss-of-function GATA6 mutations with loss of heterozygosity of the GATA6 locus were found in human malignant astrocytoma specimens but not in lower-grade astrocytomas or normal adult astrocytes. Knockdown of Gata6 expression in (V12)Ha-Ras or p53-/- astrocytes, but not in parental murine or human astrocytes, led to acceleration of tumorgenesis. Knockin GATA6 expression in human malignant astrocytoma cells reduced their tumorgenic growth with decreased VEGF expression. Collectively, these data demonstrate that GATA6, isolated from a murine astrocytoma model, is a novel tumor suppressor gene that is a direct target of mutations during malignant progression of murine and human astrocytomas. This work also demonstrates the utility of random mutagenesis strategies, such as gene trapping, on murine cancer models toward discovery of novel genetic alterations in corresponding human cancers.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".