In vitro modeling of glioblastoma initiation using PDGF-AA and p53-null neural progenitors
Bibliographic record
Abstract
BACKGROUND: Imagining ways to prevent or treat glioblastoma (GBM) has been hindered by a lack of understanding of its pathogenesis. Although overexpression of platelet derived growth factor with two A-chains (PDGF-AA) may be an early event, critical details of the core biology of GBM are lacking. For example, existing PDGF-driven models replicate its microscopic appearance, but not its genomic architecture. Here we report a model that overcomes this barrier to authenticity. METHODS: Using a method developed to establish neural stem cell cultures, we investigated the effects of PDGF-AA on subventricular zone (SVZ) cells, one of the putative cells of origin of GBM. We microdissected SVZ tissue from p53-null and wild-type adult mice, cultured cells in media supplemented with PDGF-AA, and assessed cell viability, proliferation, genome stability, and tumorigenicity. RESULTS: Counterintuitive to its canonical role as a growth factor, we observed abrupt and massive cell death in PDGF-AA: wild-type cells did not survive, whereas a small fraction of null cells evaded apoptosis. Surviving null cells displayed attenuated proliferation accompanied by whole chromosome gains and losses. After approximately 100 days in PDGF-AA, cells suddenly proliferated rapidly, acquired growth factor independence, and became tumorigenic in immune-competent mice. Transformed cells had an oligodendrocyte precursor-like lineage marker profile, were resistant to platelet derived growth factor receptor alpha inhibition, and harbored highly abnormal karyotypes similar to human GBM. CONCLUSION: This model associates genome instability in neural progenitor cells with chronic exposure to PDGF-AA and is the first to approximate the genomic landscape of human GBM and the first in which the earliest phases of the disease can be studied directly.
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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".