Prognostic Significance of P16, EZH2, FOXJ1, and Tenascin Expression in Pediatric Ependymoma
Bibliographic record
Abstract
Background: The prognosis of pediatric ependymomas remains poor, with treatment being predominantly based on surgery with or without radiotherapy. The lack of robust therapeutic molecular markers for clinical use has hampered attempts to improve survival from ependymomas. This study aimed to assess the prognostic significance of p16, enhancer of zeste homolog 2 (EZH2), forkhead box protein J 1 (FOXJ1), and tenascin in pediatric ependymomas by evaluating their immunohistochemical expression and comparing them with clinical outcomes. Methods: A total of 22 children (< 14 years) with ependymoma were retrospectively analyzed for the expression of p16, EZH2, FOXJ1, and tenascin by immunohistochemical staining. Kaplan-Meier analysis was used to evaluate the association between immunohistochemical marker expression and patient survival. Results: Higher expression of p16, EZH2, FOXJ1, and tenascin was observed in 59.0%, 36.3%, 40.9%, and 68.1% of the ependymoma samples, respectively. Patients with p16-positive and p16-negative tumors had an overall median survival time of 5.38 and 3.38 years and an overall cumulative survival rate of 44.5% and 36.5%, respectively. P16 negativity was significantly associated with poorer outcome (P = 0.009). No relationship was observed between EZH2, FOXJ1, and tenascin expression and overall survival (P = 0.904, 0.844, and 0.646, respectively). Conclusions: Loss of p16 expression was associated with poor prognosis and may be used for risk stratification. Limitations of the present study include its small sample size and variable sensitivity of different antibody clones and detection methods. Int J Clin Pediatr. 2020;9(3):67-71 doi: https://doi.org/10.14740/ijcp385
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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".