The genetic landscape of choroid plexus tumors in children and adults
Bibliographic record
Abstract
BACKGROUND: Choroid plexus tumors (CPTs) are intraventricular brain tumors predominantly arising in children but also affecting adults. In most cases, driver mutations have not been identified, although there are reports of frequent chromosome-wide copy-number alterations and TP53 mutations, especially in choroid plexus carcinomas (CPCs). METHODS: DNA methylation profiling and RNA-sequencing was performed in a series of 47 CPTs. Samples comprised 35 choroid plexus papillomas (CPPs), 6 atypical choroid plexus papillomas (aCPPs) and 6 CPCs plus three recurrences thereof. Targeted TP53 and TERT promotor sequencing was performed in all samples. Whole exome sequencing (WES) and linked-read whole genome sequencing (WGS) was performed in 25 and 4 samples, respectively. RESULTS: Tumors comprised the molecular subgroups "pediatric A" (N=11), "pediatric B" (N=12) and "adult" (N=27). Copy-number alterations mainly represented whole-chromosomal alterations with subgroup-specific enrichments (gains of Chr1, 2 and 21q in "pediatric B" and gains of Chr5 and 9 and loss of Chr21q in "adult"). RNA sequencing yielded a novel CCDC47-PRKCA fusion transcript in one adult choroid plexus papilloma patient with aggressive clinical course; an underlying Chr17 inversion was demonstrated by linked-read WGS. WES and targeted sequencing showed TP53 mutations in 7/47 CPTs (15%), five of which were children. On the contrary, TERT promoter mutations were encountered in 7/28 adult patients (25%) and associated with shorter progression-free survival (log-rank test, p=0.015). CONCLUSION: Pediatric CPTs lack recurrent driver alterations except for TP53, whereas CPTs in adults show TERT promoter mutations or a novel CCDC47-PRKCA gene fusion, being associated with a more unfavorable clinical course.
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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".