Genetics of progression of pleomorphic xanthoastrocytoma (PXA) in the pediatric population
Bibliographic record
Abstract
Recent publications suggest that with time, PXAs, rare low grade astrocytomas of children and young adults, may acquire anaplastic features and progress to malignancy with a prognosis similar to high grade astrocytomas. As malignant progression of low grade astrocytomas is rare in children, we sought to uncover the genetic changes that underlie this transformation. A search of the databases at our institution (1985–2007) identified 7 patients with a primary diagnosis of PXA. Most had multiple recurrences, with two fatalities. Extracted DNA was hybridized onto 500K SNP mapping gene arrays (Affymetrix) and gene copy‐number changes identified (dCHIP). Analysis of copy‐number changes at first presentation showed few alterations, mainly corresponding to genes within the Wnt/Cadherin pathways. However, with recurrences, the number of genes with copy‐number changes increased and other pathways implicated in cell proliferation, motility and invasiveness became modified, with prominent involvement of the integrin, Ras, and EGFR pathways. These data show that recurring PXAs acquire cumulative and progressive genetic changes that contribute to their rapid growth and increasing invasiveness and thus their less favorable outcome. Further, our experience supports the idea that in the pediatric population, PXAs are prone to recurrences and do not behave as typical low grade astrocytomas. Funding: CIHR.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".