Congenital Glioblastoma: A Clinicopathologic and Genetic Analysis
Bibliographic record
Abstract
Congenital central nervous system (CNS) tumors are uncommon, accounting for 1% of all childhood brain tumors. They present clinically either at birth or within the first 3 months. Glioblastoma (GBM) only rarely occurs congenitally and has not been fully characterized. We examined clinicopathologic features and genetic alterations of six congenital GBMs. Tumors were seen by neuroimaging as large, complex cerebral hemispheric masses. All showed classic GBM histopathology, including diffuse infiltration, dense cellularity, GFAP-positivity, high mitotic activity, endothelial proliferation and pseudopalisading necrosis. Neurosurgical procedures and adjuvant therapies varied. Survivals ranged from 4 days to 7.5 years; two of the three long-term survivors received chemotherapy, whereas the three short-term survivors did not. Paraffin-embedded tissue sections were used for FISH analysis of EGFR, chromosomes 9p21 (p16/CDKN2A) and 10q ( PTEN/DMBT1); sequencing of PTEN and TP53; and immunohistochemistry for EGFR and p53. We uncovered 10q deletions in two cases. No EGFR amplifications, 9p21 deletions, or mutations of TP53 or PTEN were noted; however, nuclear p53 immunoreactivity was strong in 5/6 cases. Tumors were either minimally immunoreactive (n = 3) or negative (n = 3) for EGFR. We conclude that congenital GBMs show highly variable survivals. They are genetically distinct from their adult counterparts and show a low frequency of known genetic alterations. Nonetheless, the strong nuclear expression of p53 in these and other pediatric GBMs could indicate that p53 dysregulation is important to tumorigenesis.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 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".