Nestin protein expression is an independent prognostic marker in ependymoma and discriminates WHO II ependymoma with poor outcome
Bibliographic record
Abstract
We have previously shown that the ependymoma cancer stem cell model DKFZ-EP1NS recapitulate ependymoma tumorigenesis at the histological, molecular and clinical level in an orthotopic murine model. EP1NS cells are characterized by a high expression of the neuronal stem cell marker nestin and a stem cell expression signature. We have therefore examined nestin expression in a large cohort of 379 ependymoma primary tumors. High protein expression of nestin, as assessed by immunohistochemistry, is associated with poor prognosis. Most importantly, nestin separates grade II ependymomas into two groups with distinct survival, with nestin positive grade II ependymomas having the same poor prognosis as grade III anaplastic ependymomas. Additional information is gained when combining nestin IHC with classifications according to cytogenetic groups 1–3, and/or posterior fossa group A and B (PFA/PFB). Multivariable analysis demonstrates that nestin positivity is an independent marker for poor progression-free (PFS) and overall survival (OS). Finally, analysis of nestin co-regulated genes in two separate datasets (n=75 and n=102 ependymoma samples, respectively) reveals co-regulation of developmental and epigenetic processes. In summary, our data suggest nestin as a useful novel marker for ependymoma risk stratification, improving diagnostic precision in differentiating grade II and III, which is virtually arbitrary in daily practice. *These authors contributed equally to this work
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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".