Ultra high-risk PFA ependymoma is characterized by loss of chromosome 6q
Bibliographic record
Abstract
BACKGROUND: Within PF-EPN-A, 1q gain is a marker of poor prognosis, however, it is unclear if within PF-EPN-A additional cytogenetic events exist which can refine risk stratification. METHODS: Five independent non-overlapping cohorts of PF-EPN-A were analyzed applying genome-wide methylation arrays for chromosomal and clinical variables predictive of survival. RESULTS: Across all cohorts, 663 PF-EPN-A were identified. The most common broad copy number event was 1q gain (18.9%), followed by 6q loss (8.6%), 9p gain (6.5%), and 22q loss (6.8%). Within 1q gain tumors, there was significant enrichment for 6q loss (17.7%), 10q loss (16.9%), and 16q loss (15.3%). The 5-year progression-free survival (PFS) was strikingly worse in those patients with 6q loss, with a 5-year PFS of 50% (95% CI 45%-55%) for balanced tumors, compared with 32% (95% CI 24%-44%) for 1q gain only, 7.3% (95% CI 2.0%-27%) for 6q loss only and 0 for both 1q gain and 6q loss (P = 1.65 × 10-13). After accounting for treatment, 6q loss remained the most significant independent predictor of survival in PF-EPN-A but is not in PF-EPN-B. Distant relapses were more common in 1q gain irrespective of 6q loss. RNA sequencing comparing 6q loss to 6q balanced PF-EPN-A suggests that 6q loss forms a biologically distinct group. CONCLUSIONS: We have identified an ultra high-risk PF-EPN-A ependymoma subgroup, which can be reliably ascertained using cytogenetic markers in routine clinical use. A change in treatment paradigm is urgently needed for this particular subset of PF-EPN-A where novel therapies should be prioritized for upfront therapy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| 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) | 0.002 | 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".