Molecular Profiling Identifies Prognostic Subgroups of Pediatric Glioblastoma and Shows Increased YB-1 Expression in Tumors
Bibliographic record
Abstract
PURPOSE: Pediatric glioblastoma (pGBM) is a rare, but devastating brain tumor. In contrast to GBM in adults (aGBM), little is known about the mechanisms underlying its development. Our aim is to gain insight into the molecular pathways of pGBM. MATERIALS AND METHODS: Thirty-two pGBM and seven aGBM samples were investigated using biochemical and transcriptional profiling. Ras and Akt pathway activation was assessed through the phosphorylation of downstream effectors, and gene expression profiles were generated using the University Health Network Human 19K cDNA arrays. Results were validated using real-time polymerase chain reaction and immunohistochemistry and compared with existing data sets on aGBM. RESULTS: There are at least two subsets of pGBM. One subset, associated with Ras and Akt pathway activation, has very poor prognosis and exhibits increased expression of genes related to proliferation and to a neural stem-cell phenotype, similar to findings in aggressive aGBM. This subset was still molecularly distinguishable from aGBM after unsupervised and supervised analysis of expression profiles. A second subset, with better prognosis, is not associated with activation of Akt and Ras pathways, may originate from astroglial progenitors, and does not express gene signatures and markers shown to be associated with long-term survival in aGBM. Both subsets of pGBM show overexpression of Y-box-protein-1 that may help drive oncogenesis in this tumor. CONCLUSION: Our work, the first study of gene expression profiles in pGBM, provides valuable insight into active pathways and targets in a cancer with minimal survival, and suggests that these tumors cannot be understood exclusively through studies of aGBM.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".