Targeting the IGF-Axis in Cultured Pediatric High-Grade Glioma Cells Inhibits Cell Cycle Progression and Survival
Bibliographic record
Abstract
Pediatric high-grade gliomas (pHGG) accounts for approximately 8-12% of primary brain tumors in children. Prognosis is poor, with a median survival of 9-15 months. Insulin-like growth factor 1-receptor (IGF-1R) gene amplifications have been identified in high-grade gliomas and may contribute to its highly aggressive phenotype, but the effect of IGF inhibitors on pHGG is yet to be determined. In the present study, we analyzed the response of patient-derived pediatric high-grade glioma cells to a novel IGF-1R inhibitor, the IGF-Trap. Using immunohistochemistry, we found that IGF-1R was localized to both the nucleus and cell membrane in different pHGG patient-derived xenograft (PDX) lines under basal conditions. In response to ligand binding, nuclear levels of the receptor increased, and this was associated with the transcriptional upregulation of both the receptor and cyclin D1, suggesting that IGF-1R could regulate its own expression and cell cycle progression in these cells. Insulin-like growth factor-1 (IGF-1) increased the proliferation of the pHGG cells DIPG13 and SGJ2, and this could be blocked by the addition of the IGF-Trap. The IGF-Trap reduced the colony formation of these cells in an optimal growth medium and impeded the ability of IGF-1 to rescue DIPG13 cells from starvation-induced apoptosis. Collectively, these results implicate the IGF-1 axis in the regulation of cell cycle progression, cellular proliferation, and cell survival in pHGG, and identify the IGF-axis as a target and the IGF-Trap as a potential inhibitor of this axis in pHGG.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".