A comprehensive view of the structure and expression of the ependymoma genome at presentation and relapse
Bibliographic record
Abstract
2073 Background: Although pediatric and adult ependymomas are associated with significant mortality and morbidity, little is known about the biology of these tumors. To identify underlying genetic alterations and cellular pathways that drive this disease, we conducted a genomic study of 200 adult and pediatric ependymomas. Methods: Using 500k single nucleotide polymorphism arrays, U133 Affymetrix gene and microRNA (miRNA) expression microarrays, and appropriate bioinformatics, we characterized 56 supratentorial (ST), 104 posterior fossa (PF), and 40 spinal (SP) ependymomas. Real-Time polymerase chain reaction and fluorescence in situ hybridization validated observed genetic events. Results: Gene expression profiles segregated tumors by site and identified disease subgroups within each anatomical region (4 ST, 4 PF, 1 SP). miRNA expression profiles identified these same subgroups, indicating that they are biologically distinct. Subgroup-specific gene expression profiles were dictated partly by developmental regulatory genes and partly by large chromosomal gains (eg. 1q, 5p, 16p) and losses (eg. 9p, 22q). Integrated genetic and expression mapping revealed key candidate tumor suppressor (TSG) and onco- genes, likely drivers of these large alterations. While large chromosomal changes occurred more frequently in SP tumors (p < 0.0001), ST tumors averaged more focal changes (n = 13.2) than PF (n = 6.2) or SP tumors (n = 3.0) (p < 0.0001). A total of 29 and 33 non-random focal amplifications and deletions, respectively, encompassing 402 known genes and miRNA clusters, were validated, of which 80 displayed copy number driven expression. These genetic alterations targeted specific cellular functions (e.g., cell adhesion, cell-cycle, neuronal development) and pathways (e.g., NOTCH, EPHRIN, TP53). Our cohort also included five sample sets consisting of primary tumor and at least two corresponding relapses. Genomic analysis of these tumors identified large chromosomal alterations as well as focal gains and losses associated with disease relapse. Conclusions: We present a highly comprehensive view of the ependymoma genome, including 80 previously unrecognized candidate TSG and oncogenes that may afford diagnostic and therapeutic targets. No significant financial relationships to disclose.
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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 | 0.000 |
| 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) | 0.002 | 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 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".