Segmental Chromosomal Aberrations in Localized Neuroblastoma Can be Detected in Formalin‐Fixed Paraffin‐Embedded Tissue Samples and Are Associated With Recurrence
Bibliographic record
Abstract
BACKGROUND: Array comparative genomic hybridization (CGH) analyses of frozen tumors have shown strong associations between the pattern of chromosomal aberrations and outcome in patients with advanced-stage neuroblastoma. New platforms for analyzing chromosomal aberrations using formalin-fixed paraffin-embedded (FFPE) tissue have recently been developed. We sought to determine whether chromosomal microarray analysis (CMA) using FFPE tumors is feasible and if segmental chromosomal aberrations were prognostic of recurrence in localized neuroblastoma. METHODS: Patients with MYCN nonamplified International Neuroblastoma Staging System stage 1 and 2 disease who recurred were identified. CMA was performed with diagnostic FFPE samples using OncoScan™ FFPE Express 2.0. The prognostic significance of chromosomal pattern was validated in 105 patients with available CGH results. RESULTS: In 26 evaluable patients, 11 recurred locally, nine had metastatic relapse, and six remained progression free >3 years from diagnosis. No chromosomal aberrations were identified in four tumors. Numerical chromosomal aberrations (NCAs) without segmental chromosomal aberration (SCA) were identified in 11 patients: six progressed locally, two had metastatic progression and 3 remained progression-free. Eleven patients had SCAs: four progressed locally, six developed metastatic progression and one remained progression-free. Five or more SCAs were only detected in tumors from patients who developed metastases (P = 0.0004). In the validation cohort, SCAs were associated with inferior event-free survival (EFS) compared to NCA (5-year EFS 68% ± 8.3% vs. 91% ± 3.6%, respectively; P = 0.0083). CONCLUSIONS: It is feasible to evaluate chromosomal aberrations using FFPE neuroblastoma tissue. SCA is associated with inferior EFS in localized neuroblastoma patients, and multiple SCAs may be predictive of metastatic relapse.
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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 | 0.000 | 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) | 0.001 | 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".