Characterization and transformation potential of “Synthetic” astrocytes differentiated from murine embryonic stem cells
Bibliographic record
Abstract
Our objective was to determine if murine embryonic stem (ES) cells, which are readily available from repositories, could be developed as a model of gliomagenesis, recognizing the difficulty in obtaining and transforming somatic astrocytes. Using a stringently controlled sequential differentiation procedure on wild type (wt) and p53+/- ES cells, we established GFAP+A2B5-synthetic astrocytes with high efficiency (>90%). The synthetic astrocytes stably express several differentiated astrocyte associated structural proteins and biochemical markers, but lacked expression of differentiated neurons and oligodendrocytes. However, in contrast to somatic differentiated astrocytes, the synthetic astrocytes expressed stem cell markers, with a transcriptome profile similar to astrocytes differentiated from neural stem cells (NSC) and somatic astrocyte cultures established from E13.5-Cortex and P4-hippocampus. In addition, the synthetic astrocytes demonstrated plasticity, with ability to dedifferentiate into neuronal and oligodendrocyte lineages. Intracranial injection of postnatal differentiated somatic astrocytes or synthetic astrocytes of either wt or p53+/- background did not grow tumors, unlike corresponding ES cells that develop teratomas. In contrast, retroviral transduction of either wt or p53+/- synthetic astrocytes and not the postnatal somatic astrocytes, with relevant oncogenes found in human malignant astrocytomas (MDM2, myr-AKT, V12H-RAS), led to intracranial high-grade undifferentiated gliomas. This study demonstrates utilization of readily available ES cells of varying genetic backgrounds to model and further our understanding of gliomagenesis. Large numbers of replenishable derivative synthetic glial lineage cells retain genetic and phenotypic characteristics of progenitor cells and thereby are more amenable to transformation by genetic aberrations involved in gliomagenesis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".